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Sarnico shipyard

The timeless workshop.

The Sarnico shipyard, created in 1842 on Lake Iseo in the heart of Franciacorta, is where it all started, from the construction of the legendary wooden hulls to the current yachts, from 8 to 21 metres.

Sarnico is also home to Riva Classiche, the new Riva division that brings together the inimitable heritage and know-how of Riva RAM, created in 1957, and the unrivalled assortment offered by Marina Riva, the exclusive retailer of original accessories and spare parts for vintage Riva powerboats.

The heart of the shipyard is the office of Engineer Carlo Riva, called “la Plancia”: he planned it considering not only the design, but above all its functionality. For this reason, the studio is located in the centre of the depot’s large vault, with an arch 40 metres wide supported by two other lateral pillars, which also support two overhead cranes, each of which is capable of lifting yachts weighing over 20 tonnes.

The daring and futuristic architecture of this office, protected along with the entire shipyard by the Environmental Heritage Department, is still permeated today by the genius of its creator.

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Sarnico Yachts

Sarnico is an internationally recognized brand of boats and motor yachts that hail from the shipyards of Cantieri di Sarnico in Italy. In less than two decades in the industry, Sarnico has established itself as a maker of luxurious motor yachts that are carefully crafted by its skilled workers. Furthermore, it has been known as a company that has set high standards for its production which is mainly the reason why it is considered to be among the most popular brands of motor yachts for sale today. The Sarnico models, although distinct in design from one another, are similar and have elements that make each unmistakably Sarnico. According to the company, all Sarnico boats for sale are carefully designed not only to provide quality, comfort and performance but also to portray the image of Cantieri di Sarnico as a motor yacht company. The venture of Cantieri di Sarnico into the business of making boats for sale began in 1992 when the company started working on its first model, the Sarnico Maxim 55. However, it was not until 1994 that Sarnico introduced the Sarnico 55 to the public. Although the completion of the model took the company two years of redesigning and restructuring, the company says that it was well worth the wait as Sarnico quickly became recognized by enthusiasts of motor yachts around the world. One year after the launch of the Sarnico 55 to the market, Cantieri di Sarnico introduced the Sarnico 45. Although the 45 is among the company’s first models, it continues to be one of the most ordered among all the current Sarnico boats for sale today. A few years later, Cantieri di Sarnico released the Sarnico 40 model which then led to the 43. Cantieri di Sarnico reached the peak of its success soon after brothers Antonio and Luigi Foresti took over the operations of the Sarnico shipyard. The two were known to be among the most passionate Italian sea goers. Luigi Foresti was also recognized as a champion of sports competitions at sea. The two brothers’ love for motor yachts translated into their success in the industry. As soon as they took over the shipyard, the Foresti brothers expanded its operations and began tapping international markets and soon, Sarnico boats for sale were available across the globe. During the early 2000s, the Sarnico 65 and the 58 were introduced to the market and were quickly established as Sarnico’s biggest boats for sale. Two years after the launch of the two models, the company’s production was expanded through the acquisition of a 10,000-square meter roofed shipyard located in Brescia. Soon after this production expansion, Cantieri di Sarnico reached the sale of its 220th boat. Today, through the continuous innovation of Cantieri di Sarnico, the company prides itself in combining the latest technologies with the traditional process of boat-making. Among its technological developments are the usage of a computer system that molds the boats precisely. Furthermore, the company has constant efforts to reduce the noise of each boat both from the inside and from the outside. This effort led to the production of the Sarnico 43, the first Cantieri di Sarnico model to be granted permission to cruise through the Zurich Lake areas. The company considers this as a milestone as few boats have been allowed to reach the sound regulated areas. With sixteen years of experience in the industry of ship building, Cantieri di Sarnico continues to receive orders from many different parts of the world for their different models. There are many Sarnico motor yachts for sale around the world today. Among the most popular are the Sarnicos 45, 50, 58, and 65.

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When in Italy , just imagine the exquisite taste, detail and quality. And when it is taken in love with the sea brothers, it turns out another masterpiece. This is a very young shipyard, founded in 1992, very quickly won the hearts of its luxurious interiors, with expensive finishes and quality of workmanship. And before it was acquired by the Lombards Luigi (Luigi) and Antonio Foresti (Antonio Foresti), managed to release 55-foot model and Sarnico 45, which is still one of the most popular. the Brothers Foresti very quickly, in just 6 years brought the brand to an international level. Collaborating with famous designers, such as >Carlo Nuvolari (Nuvolari Carlo) and Dan Leonard (Dan Lenard), Brunello Acampora (Brunello Acampora) and Dante O. Benini (Dante O. Benini), Sarnico has become the subject of luxury and refined taste. the Beginning of the century Sarnico said launching open Sarnico 58, and the descent of its flagship Sarnico 65, the first coupe with an unusual profile, slightly elongated teardrop shape of the cabin. 58-foot-tall model appeared at the shipyard in Kapriolo , Sarnico, where he moved in 2003. br> Sports Sarnico Spider in 2006 and was selected "European boat of the year 2007". Luigi of Foresti prefer to show their boats in action and to fight for the victory in the competition, such as in the toughest race Viareggio — Monte Carlo Viareggio where even a 5-point storm did not prevent him to mine gold. In 2007, acquired the historical Sarnico shipyard Jiacomo Colombo, founded in 1956 and known >speed boats >cabin cruisers. the Result of collaboration between steel 7 innovative models 26 and 36 Bellagio, the 37 Alldays, 24 Super Indios Electric, 25 Super Indios, Spider Special and a new flagship “Grande” of 80 feet. In 2011 the exhibition in Genoa the company unveiled two new boat: Sarnico Spider 46 GTS and Colombo 39 Alldays.

Manufacturing

the Shipyard is located in the Italian Lombardy city Kapriolo . Unique and elegant furniture in the cabins is created by master carpenters of lake Iseo , using traditional methods. For finishing selected exotic woods: wenge and Zebrano, different stunning colors and exceptional durability. Innovative construction technologies and precise Assembly ensure strength and quality, high performance and low fuel consumption. New models of boats do not appear often, every two years, but each is an unbeatable combination of beauty, precision Assembly, and innovation.

the Shipyard specializiruetsya in the production of motor boats from 24 to 80 feet — >open >semi - >private — in which combines luxury, technology and unmatched Italian quality.

Modern and comfortable, luxurious and properly gathered, where innovative technology neatly hidden under exclusive finish and elegant style.

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Home » Applied Research – Types, Methods and Examples

Applied Research – Types, Methods and Examples

Table of Contents

Applied Research

Definition:

Applied research is a type of scientific inquiry that focuses on developing practical solutions to real-world problems. It involves the use of existing knowledge, theories, and techniques to address specific problems or challenges in a particular field or industry.

Applied research is often conducted in collaboration with industry or government partners, who provide funding and expertise to support the research. The results of applied research are typically intended to be directly applicable to the real world, and may involve the development of new products, technologies, or processes.

Types of Applied Research

Types of Applied Research are as follows:

Action Research

This type of research is designed to solve specific problems within an organization or community. The research involves collaboration between researchers and stakeholders to develop solutions to issues that affect the organization or community.

Evaluation Research

This type of research is used to assess the effectiveness of a particular program, policy, or intervention. Evaluation research is often used in government, healthcare, and social service settings to determine whether programs are meeting their intended goals.

Developmental Research

This type of research is used to develop new products, technologies, or processes. The research may involve the testing of prototypes or the development of new methods for production or delivery.

Diagnostic Research

This type of research is used to identify the causes of problems or issues. Diagnostic research is often used in healthcare, where researchers may investigate the causes of a particular disease or condition.

Policy Research

This type of research is used to inform policy decisions. Policy research may involve analyzing the impact of existing policies or evaluating the potential outcomes of proposed policies.

Predictive Research

This type of research is used to forecast future trends or events. Predictive research is often used in marketing, where researchers may use data analysis to predict consumer behavior or market trends.

Data Collection Methods

In applied research, data collection methods can be broadly classified into two categories: Quantitative and Qualitative methods:

Quantitative Data Collection

Quantitative research methods involve collecting numerical data that can be analyzed statistically. The most commonly used quantitative data collection methods in applied research include:

• Surveys : Surveys are questionnaires designed to collect data from a large sample of people. Surveys can be conducted face-to-face, over the phone, or online.
• Experiments : Experiments involve manipulating variables to test cause-and-effect relationships. Experiments can be conducted in the lab or in the field.
• Observations : Observations involve watching and recording behaviors or events in a systematic way. Observations can be conducted in the lab or in natural settings.
• Secondary data analysis: Secondary data analysis involves analyzing data that has already been collected by someone else. This can include data from government agencies, research institutes, or other sources.

Qualitative Data Collection

Qualitative research methods involve collecting non-numerical data that can be analyzed for themes and patterns. The most commonly used qualitative data collection methods in applied research include:

• Interviews : Interviews involve asking open-ended questions to individuals or groups. Interviews can be conducted in-person, over the phone, or online.
• Focus groups : Focus groups involve a group of people discussing a topic with a moderator. Focus groups can be conducted in-person or online.
• Case studies : Case studies involve in-depth analysis of a single individual, group, or organization.
• Document analysis : Document analysis involves analyzing written or recorded documents to extract data. This can include analyzing written records, audio recordings, or video recordings.

Data Analysis Methods

In applied research, data analysis methods can be broadly classified into two categories: Quantitative and Qualitative methods:

Quantitative Data Analysis

Quantitative data analysis methods involve analyzing numerical data to identify patterns and trends. The most commonly used quantitative data analysis methods in applied research include:

• Descriptive statistics: Descriptive statistics involve summarizing and presenting data using measures such as mean, median, mode, and standard deviation.
• Inferential statistics : Inferential statistics involve testing hypotheses and making predictions about a population based on a sample of data. This includes methods such as t-tests, ANOVA, regression analysis, and correlation analysis.
• Data mining: Data mining involves analyzing large datasets to identify patterns and relationships using machine learning algorithms.

Qualitative Data Analysis

Qualitative data analysis methods involve analyzing non-numerical data to identify themes and patterns. The most commonly used qualitative data analysis methods in applied research include:

• Content analysis: Content analysis involves analyzing written or recorded data to identify themes and patterns. This includes methods such as thematic analysis, discourse analysis, and narrative analysis.
• Grounded theory: Grounded theory involves developing theories and hypotheses based on the analysis of data.
• Interpretative phenomenological analysis: Interpretative phenomenological analysis involves analyzing data to identify the subjective experiences of individuals.
• Case study analysis: Case study analysis involves analyzing a single individual, group, or organization in-depth to identify patterns and themes.

Applied Research Methodology

Applied research methodology refers to the set of procedures, tools, and techniques used to design, conduct, and analyze research studies aimed at solving practical problems in real-world settings. The general steps involved in applied research methodology include:

• Identifying the research problem: The first step in applied research is to identify the problem to be studied. This involves conducting a literature review to identify existing knowledge and gaps in the literature, and to determine the research question.
• Developing a research design : Once the research question has been identified, the next step is to develop a research design. This involves determining the appropriate research method (quantitative, qualitative, or mixed methods), selecting the data collection methods, and designing the sampling strategy.
• Collecting data: The third step in applied research is to collect data using the selected data collection methods. This can include surveys, interviews, experiments, observations, or a combination of methods.
• Analyzing data : Once the data has been collected, it needs to be analyzed using appropriate data analysis methods. This can include descriptive statistics, inferential statistics, content analysis, or other methods, depending on the type of data collected.
• Interpreting and reporting findings : The final step in applied research is to interpret the findings and report the results. This involves drawing conclusions from the data analysis and presenting the findings in a clear and concise manner.

Applications of Applied Research

Some applications of applied research are as follows:

• Product development: Applied research can help companies develop new products or improve existing ones. For example, a company might conduct research to develop a new type of battery that lasts longer or a new type of software that is more efficient.
• Medical research : Applied research can be used to develop new treatments or drugs for diseases. For example, a pharmaceutical company might conduct research to develop a new cancer treatment.
• Environmental research : Applied research can be used to study and address environmental problems such as pollution and climate change. For example, research might be conducted to develop new technologies for reducing greenhouse gas emissions.
• Agriculture : Applied research can be used to improve crop yields, develop new varieties of plants, and study the impact of pests and diseases on crops.
• Education : Applied research can be used to study the effectiveness of teaching methods or to develop new teaching strategies.
• Transportation : Applied research can be used to develop new technologies for transportation, such as electric cars or high-speed trains.
• Communication : Applied research can be used to improve communication technologies, such as developing new methods for wireless communication or improving the quality of video calls.

Examples of Applied Research

Here are some real-time examples of applied research:

• COVID-19 Vaccine Development: The development of COVID-19 vaccines is a prime example of applied research. Researchers applied their knowledge of virology and immunology to develop vaccines that could prevent or reduce the severity of COVID-19.
• Autonomous Vehicles : The development of autonomous vehicles involves applied research in areas such as artificial intelligence, computer vision, and robotics. Companies like Tesla, Waymo, and Uber are conducting extensive research to improve their autonomous vehicle technology.
• Renewable Energy : Research is being conducted on renewable energy sources like solar, wind, and hydro power to improve efficiency and reduce costs. This is an example of applied research that aims to solve environmental problems.
• Precision Agriculture : Applied research is being conducted in the field of precision agriculture, which involves using technology to optimize crop yields and reduce waste. This includes research on crop sensors, drones, and data analysis.
• Telemedicine : Telemedicine involves using technology to deliver healthcare remotely. Applied research is being conducted to improve the quality of telemedicine services, such as developing new technologies for remote diagnosis and treatment.
• Cybersecurity : Applied research is being conducted to improve cybersecurity measures and protect against cyber threats. This includes research on encryption, network security, and data protection.

Purpose of Applied Research

The purpose of applied research is to solve practical problems or improve existing products, technologies, or processes. Applied research is focused on specific goals and objectives and is designed to have direct practical applications in the real world. It seeks to address problems and challenges faced by individuals, organizations, or communities and aims to provide solutions that can be implemented in a practical manner.

The primary purpose of applied research is to generate new knowledge that can be used to solve real-world problems or improve the efficiency and effectiveness of existing products, technologies, or processes. Applied research is often conducted in collaboration with industry, government, or non-profit organizations to address practical problems and create innovative solutions.

Applied research is also used to inform policy decisions by providing evidence-based insights into the effectiveness of specific interventions or programs. By conducting research on the impact of policies and programs, decision-makers can make informed decisions about how to allocate resources and prioritize interventions.

Overall, the purpose of applied research is to improve people’s lives by developing practical solutions to real-world problems. It aims to bridge the gap between theory and practice, and to ensure that research findings are put into action to achieve tangible benefits.

When to use Applied Research

Here are some specific situations when applied research may be appropriate:

• When there is a need to develop a new product : Applied research can be used to develop new products that meet the needs of consumers. For example, a company may conduct research to develop a new type of smartphone with improved features.
• When there is a need to improve an existing product : Applied research can also be used to improve existing products. For example, a company may conduct research to improve the battery life of an existing product.
• When there is a need to solve a practical problem: Applied research can be used to solve practical problems faced by individuals, organizations, or communities. For example, research may be conducted to find solutions to problems related to healthcare, transportation, or environmental issues.
• When there is a need to inform policy decisions: Applied research can be used to inform policy decisions by providing evidence-based insights into the effectiveness of specific interventions or programs.
• When there is a need to improve efficiency and effectiveness: Applied research can be used to improve the efficiency and effectiveness of processes or systems. For example, research may be conducted to identify ways to streamline manufacturing processes or to improve the delivery of healthcare services.

Characteristics of Applied Research

The following are some of the characteristics of applied research:

• Focus on solving real-world problems : Applied research focuses on addressing specific problems or needs in a practical setting, with the aim of developing solutions that can be implemented in the real world.
• Goal-oriented: A pplied research is goal-oriented, with a specific aim of solving a particular problem or meeting a specific need. The research is usually designed to achieve a specific outcome, such as developing a new product, improving an existing process, or solving a particular issue.
• Practical and relevant: Applied research is practical and relevant to the needs of the industry or field in which it is conducted. It aims to provide practical solutions that can be implemented to improve processes or solve problems.
• Collaborative : Applied research often involves collaboration between researchers and practitioners, such as engineers, scientists, and business professionals. Collaboration allows for the exchange of knowledge and expertise, which can lead to more effective solutions.
• Data-driven: Applied research is data-driven, relying on empirical evidence to support its findings and recommendations. Data collection and analysis are important components of applied research, as they help to identify patterns and trends that can inform decision-making.
• Results-oriented: Applied research is results-oriented, with an emphasis on achieving measurable outcomes. Research findings are often used to inform decisions about product development, process improvement, or policy changes.
• Time-bound : Applied research is often conducted within a specific timeframe, with deadlines for achieving specific outcomes. This helps to ensure that the research stays focused on its goals and that the results are timely and relevant to the needs of the industry or field.

Advantages of Applied Research

Some of the advantages of applied research are as follows:

• Practical solutions: Applied research is focused on developing practical solutions to real-world problems, making it highly relevant to the needs of the industry or field in which it is conducted. The solutions developed through applied research are often highly effective and can be implemented quickly to address specific issues.
• Improved processes: Applied research can help organizations to improve their processes, leading to increased efficiency and productivity. The research can identify areas for improvement, such as bottlenecks or inefficiencies, and provide recommendations for optimizing processes.
• Innovation: Applied research can lead to the development of new products, services, and technologies that can transform industries and create new opportunities for growth and innovation. The research can help organizations to identify unmet needs and develop new solutions to meet them.
• Collaboration : Applied research often involves collaboration between researchers and practitioners, leading to the exchange of knowledge and expertise. Collaboration can result in more effective solutions and can help to build partnerships between academia and industry.
• Increased competitiveness : Applied research can help organizations to stay competitive by enabling them to adapt to changing market conditions and customer needs. The research can provide insights into emerging trends and technologies, helping organizations to stay ahead of the curve.
• Economic growth: Applied research can contribute to economic growth by creating new industries and jobs. The research can lead to the development of new technologies and products that can drive economic growth and create new opportunities for entrepreneurship and innovation.

Limitations of Applied Research

Some of the limitations of applied research are as follows:

• Limited generalizability: Applied research often focuses on specific contexts and may not be generalizable to other settings. This means that the findings of applied research may not be applicable to other industries, regions, or populations.
• Time and resource constraints: Applied research is often conducted within a specific timeframe and with limited resources. This can limit the scope and depth of the research and may prevent researchers from exploring all possible avenues.
• Potential for bias: Applied research may be influenced by the interests and perspectives of the organization or industry funding the research. This can lead to a bias in the research and potentially compromise the objectivity and validity of the findings.
• Ethical considerations: Applied research may raise ethical concerns, particularly if it involves human subjects or sensitive issues. Researchers must adhere to ethical standards and ensure that the research is conducted in a responsible and respectful manner.
• Limited theoretical development: Applied research tends to focus on practical solutions and may not contribute significantly to theoretical development in a particular field. This can limit the broader impact of the research and may hinder the development of new theories and frameworks.
• Limited focus on long-term impact: Applied research often focuses on short-term outcomes, such as developing a new product or improving a process. This may limit the focus on long-term impacts, such as the sustainability of the solution or its broader implications for the industry or society.

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• Published: 17 November 2021

Blurring divides between basic and applied

Nature Food volume  2 ,  page 831 ( 2021 ) Cite this article

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Basic and applied research too often remain divided in agriculture. With stagnating and, in some cases, declining research funding, the innovation we need in agriculture for food systems transformation calls for greater connection and communication between the two.

Basic research is conducted to gain a more complete understanding of a subject without specific applications in mind. The goals are to obtain new observations and knowledge of the foundations of phenomena. By contrast, applied research aims to gain knowledge in order to meet a specific, recognized need. For example, according to the National Science Foundation , basic research may include activities with broad or general applications, such as the study of how plant genomes change, but should exclude research directed towards a specific application or requirement, such as the optimization of the genome of a specific crop species. In the agricultural research and development (R&D) system, Huffman and Evenson 1 developed a structural representation to define the R&D fields, which include the general sciences, the pre-technology sciences and technology invention. General sciences include chemistry, mathematics and biology. Pre-technology sciences include plant and animal genetics, soil physics and chemistry, and plant and animal pathology. Technology invention includes plant and animal breeding, agronomy and veterinary medicine.

Agriculture is now facing growing challenges, such as increasing crop production while improving efficiency under various soil, water and climate condition constraints. Innovation to address these challenges cannot be achieved by basic or applied science alone, as the growing integration of and iteration between the two has made clear. For example, comprehensive basic knowledge of genes and their regulatory pathways has facilitated improved breeding efficiency, and the science applied within the crop field easily integrates knowledge from plant molecular biology and tools such as phenomics, genomics and informatics. Similarly, the efficiency of field-based soil management approaches has been improved by developing a fundamental understanding of rhizosphere biogeochemical processes and knowledge of molecular-scale biogeochemical processes. In practice, we have innovated and progressed by working with the blurred line between basic and applied research.

In agriculture, although funding agencies and universities still commonly use the terms ‘basic’ and ‘applied’ to categorize research disciplines, the combined term ‘basic and applied agricultural research’ is increasingly used when referring to agricultural R&D activities. It has become common understanding over time that although agricultural research is application-oriented, the creation of scientific knowledge at the bench and its application should go hand in hand. Traditional basic research is becoming more application-oriented, and the progress of traditional applied research is increasingly driven by breakthroughs in basic research. The advent of CRISPR–Cas9 gene editing is a successful example of a discovery from basic biology being applied to biotechnology and medicine 2 ; the development of the Cas9 endonuclease for genome editing resulted from more than a decade of basic research on the biological function of CRISPR. Now that research activities have outgrown their original definitions, simply categorizing research into basic and applied is no longer meaningful. In response, translational research is a growing trend. In the crop context, this refers to a systematic effort to convert basic research knowledge into practical applications 3 . However, this type of translational research is still lacking — although considerable progress has been made in basic plant science in recent decades, relatively few new ideas have been tested in an applied context 3 .

Basic research is, in the main, publicly funded. In the United States, public investment in agricultural research has declined, while applied research has seen a sharp increase 4 . Meanwhile, private-sector funding has also increased over time, favouring applied research. Overall, this change may leave less room for basic agricultural research. However, important agricultural innovations can come from a better understanding of the basic biology of plants and animals 5 , and advances in basic science are needed to provide new ways to address future challenges in the agricultural sector. The disproportionate focus on short-term economical returns could jeopardize agricultural innovation in the long run. Under declining and stagnant funding conditions, the best approach to advance agricultural research is to promote efficient connection and communication between basic and applied science.

Agriculture is a broad, multidisciplinary field, and dividing research into basic and applied can over-simplify the research objectives and impede cross-disciplinary collaboration. Funding agencies, research institutions and the scientific community need to increase interactions between basic and applied research to ensure sustainable development and the implementation of agricultural innovations.

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How to Conduct Research on Your Farm or Ranch

Common research designs for farmers.

or call (301) 779-1007 to order.

Completely Randomized Design

The completely randomized design works best in tightly controlled situations and very uniform conditions. A farmer wants to study the effects of four different fertilizers (A, B, C, D) on corn productivity. Three replicates of each treatment are assigned randomly to 12 plots.

The simplest experimental layout is a completely randomized design (Figure 3). This layout works best in tightly controlled situations and very uniform conditions. For this reason, the completely randomized design is not commonly used in field experiments. You can use it if you are working with a very uniform field, in a greenhouse or growth chamber, or if you have no idea about the variability in your field. The statistical analysis of completely randomized designs is not covered in this publication.

Paired Comparison

As the name implies, the paired comparison is used to compare the effect of two different treatments assigned randomly within blocks. Each block contains two plots—one plot of each treatment—and blocks are replicated four to six times across the field. Typically, plots run the length of the field and are one or two tractor widths in order to facilitate management. Figure 4 shows the layout for a typical paired comparison experiment.

In collecting yield data or other samples from the field, measurements are generally taken from the center rows of a plot in order to avoid any “edge effects.” You can use this design to evaluate any pair of treatments: comparing two varieties, growing the crop with and without starter fertilizer, comparing two rates of fertilizer application, comparing the timing of nutrient application, or using two different cover crop treatments, for example. The paired comparison is a type of randomized block design, but it is usually classified on its own since we use a simplified statistical analysis, the t-test, to analyze the data when compared to the standard randomized complete block design (described next). The t-test will help you determine whether the difference you observe in two treatments is due to natural variation or is a real difference. It is described in the section, Using the t-Test to Compare Two Treatments .

The paired comparison is used to study two treatments. Each treatment should still be replicated several times, generally in blocks that should be set up to account for any known field variability. Randomize treatments within each block. Harvest only the middle rows of each plot (e.g., eight middle rows). Adapted from Anderson (1993).

Randomized Complete Block

A randomized complete block experiment. Adapted from Nielsen (2010).

The randomized complete block design is used to evaluate three or more treatments. As with the paired comparison, blocking and the orientation of plots helps to address the problem of field variability as described earlier (Figure 3). Each block contains a complete set of treatments, and the treatments are randomized within each block. Four to six replications of a “complete block” are sufficient for most on-farm research projects. Figure 5 shows a schematic of a randomized complete block design with three treatments. The statistical test known as analysis of variance (ANOVA) is used to analyze the data from a randomized complete block experiment.

The split-plot design is for experiments that look at how different sets of treatments interact with each other. It is also used when one of the treatment factors needs more replication or when it is difficult to change the level of one of the factors. For example, in a cover crop study, it may be most convenient due to machinery limitations to plant cover crops in larger areas (the main plots) and then impose other treatments such as fertilizer rates in the sub-plots. In this design, main treatments are overlaid with another set of sub-treatments. Though fairly easy to set up in the field, a split-plot experiment will usually take up a larger area and be more complex to implement, manage and analyze. Given the greater number of treatments and the interaction component, using ANOVA for the split-plot design is also more complex than with the paired comparison or the randomized complete block. It is best to work with someone who has expertise in this type of research design when setting up a split-plot experiment. An example of a split-plot design is shown in Figure 6.

In split-plot design, one treatment (the main plot—fallow or pea) is split further into another treatment (sub-plots) of interest. Here, compost and fish fertilizer are compared to a no-treatment control. Main plots are sometimes decided by field machinery limitations, such as the pea planter used to plant a larger area, with compost and fish emulsion applied to smaller areas. Adapted from Sooby (2001).

Sustainable Agriculture Research and Education in the Field: A Proceedings (1991)

Chapter: introduction, introduction.

Charles M. Benbrook

These proceedings are based on a workshop that brought together scientists, farmer-innovators, policymakers, and interested members of the public for a progress report on sustainable agriculture research and education efforts across the United States. The workshop, which was held on April 3 and 4, 1990, in Washington, D.C., was sponsored by the Office of Science and Education of the U.S. Department of Agriculture and the Board on Agriculture of the National Research Council. The encouraging new science discussed there should convince nearly everyone of two facts.

First, the natural resource, economic, and food safety problems facing U.S. agriculture are diverse, dynamic, and often complex. Second, a common set of biological and ecological principles—when systematically embodied in cropping and livestock management systems—can bring improved economic and environmental performance within the reach of innovative farmers. Some people contend that this result is not a realistic expectation for U.S. agriculture. The evidence presented here does not support such a pessimistic assessment.

The report of the Board on Agriculture entitled Alternative Agriculture (National Research Council, 1989a) challenged everyone to rethink key components of conventional wisdom and contemporary scientific dogma. That report has provided encouragement and direction to those individuals and organizations striving toward more sustainable production systems, and it has provoked skeptics to articulate why they feel U.S. agriculture cannot—some even say should not—seriously contemplate the need for such change. The debate has been spirited and generally constructive.

Scholars, activists, professional critics, and analysts have participated in

this debate by writing papers and books, conducting research, and offering opinions about alternative and sustainable agriculture for over 10 years. Over the past decade, many terms and concepts have come and gone. Most people—and unfortunately, many farmers—have not gone very far beyond the confusion, frustration, and occasional demagoguery that swirls around the different definitions of alternative, low-input, organic, and sustainable agriculture.

Fortunately, though, beginning in late 1989, a broad cross-section of people has grown comfortable with the term sustainable agriculture. The May 21, 1990, issue of Time magazine, in an article on sustainable agriculture entitled “It's Ugly, But It Works” includes the following passage:

[A] growing corps of experts [are] urging farmers to adopt a new approach called sustainable agriculture. Once the term was synonymous with the dreaded O word—a farm-belt euphemism for trendy organic farming that uses no synthetic chemicals. But sustainable agriculture has blossomed into an effort to curb erosion by modifying plowing techniques and to protect water supplies by minimizing, if not eliminating, artificial fertilizers and pest controls.

Concern and ridicule in farm publications and during agribusiness meetings over the philosophical roots of low-input, sustainable, or organic farming have given way to more thoughtful appraisals of the ecological and biological foundations of practical, profitable, and sustainable farming systems. While consensus clearly does not yet exist on how to “fix” agriculture's contemporary problems, a constructive dialogue is now under way among a broad cross-section of individuals, both practitioners and technicians involved in a wide variety of specialties.

This new dialogue is powerful because of the people and ideas it is connecting. Change will come slowly, however. Critical comments in some farm magazines will persist, and research and on-farm experimentation will not always lead to the hoped for insights or breakthroughs. Some systems that now appear to be sustainable will encounter unexpected production problems. Nonetheless, progress will be made.

The Board on Agriculture believes that over the next several decades significant progress can and will be made toward more profitable, resource-conserving, and environmentally prudent farming systems. Rural areas of the United States could become safer, more diverse, and aesthetically pleasing places to live. Farming could, as a result, become a more rewarding profession, both economically and through stewardship of the nation's soil and water resources. Change will be made possible; and it will be driven by new scientific knowledge, novel on-farm management tools and approaches, and economic necessity. The policy reforms adopted in the 1990 farm bill, and ongoing efforts to incorporate environmental objectives

into farm policy, may also in time make a significant difference in reshaping the economic environment in which on-farm management decisions are made.

This volume presents an array of new knowledge and insight about the functioning of agricultural systems that will provide the managerial and technological foundations for improved farming practices and systems. Examples of the research projects under way around the country are described. Through exploration of the practical experiences, recent findings, and insights of these researchers, the papers and discussions presented in this volume should demonstrate the value of field- and farm-level systems-based research that is designed and conducted with ongoing input from farmer-innovators.

Some discussion of the basic concepts that guide sustainable agriculture research and education activities may be useful. Definitions of key terms, such as sustainable agriculture, alternative agriculture, and low-input sustainable agriculture, are drawn from Alternative Agriculture and a recent paper (Benbrook and Cook, 1990).

BASIC CONCEPTS AND OPERATIONAL DEFINITIONS

Basic concepts.

Sustainable agriculture, which is a goal rather than a distinct set of practices, is a system of food and fiber production that

improves the underlying productivity of natural resources and cropping systems so that farmers can meet increasing levels of demand in concert with population and economic growth;

produces food that is safe, wholesome, and nutritious and that promotes human well-being;

ensures an adequate net farm income to support an acceptable standard of living for farmers while also underwriting the annual investments needed to improve progressively the productivity of soil, water, and other resources; and

complies with community norms and meets social expectations.

Other similar definitions could be cited, but there is now a general consensus regarding the essential elements of sustainable agriculture. Various definitions place differing degrees of emphasis on certain aspects, but a common set of core features is now found in nearly all definitions.

While sustainable agriculture is an inherently dynamic concept, alternative agriculture is the process of on-farm innovation that strives toward the goal of sustainable agriculture. Alternative agriculture encompasses efforts by farmers to develop more efficient production systems, as well as

efforts by researchers to explore the biological and ecological foundations of agricultural productivity.

The challenges inherent in striving toward sustainability are clearly dynamic. The production of adequate food on a sustainable basis will become more difficult if demographers are correct in their estimates that the global population will not stabilize before it reaches 11 billion or 12 billion in the middle of the twenty-first century. The sustainability challenge and what must be done to meet it range in nature from a single farm field, to the scale of an individual farm as an enterprise, to the food and fiber needs of a region or country, and finally to the world as a whole.

A comprehensive definition of sustainability must include physical, biological, and socioeconomic components. The continued viability of a farming system can be threatened by problems that arise within any one of these components. Farmers are often confronted with choices and sacrifices because of seemingly unavoidable trade-offs—an investment in a conservation system may improve soil and water quality but may sacrifice near-term economic performance. Diversification may increase the efficiency of resource use and bring within reach certain biological benefits, yet it may require additional machinery and a more stable and versatile labor supply. Indeed, agricultural researchers and those who design and administer farm policy must seek ways to alleviate seemingly unwelcome trade-offs by developing new knowledge and technology and, when warranted, new policies.

Operational Definitions

Sustainable agriculture is the production of food and fiber using a system that increases the inherent productive capacity of natural and biological resources in step with demand. At the same time, it must allow farmers to earn adequate profits, provide consumers with wholesome, safe food, and minimize adverse impacts on the environment.

As defined in our report, alternative agriculture is any system of food or fiber production that systematically pursues the following goals (National Research Council, 1989a):

more thorough incorporation of natural processes such as nutrient cycling, nitrogen fixation, and beneficial pest-predator relationships into the agricultural production process;

reduction in the use of off-farm inputs with the greatest potential to harm the environment or the health of farmers and consumers;

productive use of the biological and genetic potential of plant and animal species;

improvement in the match between cropping patterns and the productive potential and physical limitations of agricultural lands; and

profitable and efficient production with emphasis on improved farm management, prevention of animal disease, optimal integration of livestock and cropping enterprises, and conservation of soil, water, energy, and biological resources.

Conventional agriculture is the predominant farming practices, methods, and systems used in a region. Conventional agriculture varies over time and according to soil, climatic, and other environmental factors. Moreover, many conventional practices and methods are fully sustainable when pursued or applied properly and will continue to play integral roles in future farming systems.

Low-input sustainable agriculture (LISA) systems strive to achieve sustainability by incorporating biologically based practices that indirectly result in lessened reliance on purchased agrichemical inputs. The goal of LISA systems is improved profitability and environmental performance through systems that reduce pest pressure, efficiently manage nutrients, and comprehensively conserve resources.

Successful LISA systems are founded on practices that enhance the efficiency of resource use and limit pest pressures in a sustainable way. The operational goal of LISA should not, as a matter of first principles, be viewed as a reduction in the use of pesticides and fertilizers. Higher yields, lower per unit production costs, and lessened reliance on agrichemicals in intensive agricultural systems are, however, often among the positive outcomes of the successful adoption of LISA systems. But in much of the Third World an increased level of certain agrichemical and fertilizer inputs will be very helpful if not essential to achieve sustainability. For example, the phosphorous-starved pastures in the humid tropics will continue to suffer severe erosion and degradation in soil physical properties until soil fertility levels are restored and more vigorous plant growth provides protection from rain and sun.

Farmers are continuously modifying farming systems whenever opportunities arise for increasing productivity or profits. Management decisions are not made just in the context of one goal or concern but in the context of the overall performance of the farm and take into account many variables: prices, policy, available resources, climatic conditions, and implications for risk and uncertainty.

A necessary step in carrying out comparative assessments of conventional and alternative farming systems is to understand the differences between farming practices, farming methods, and farming systems. It is somewhat easier, then, to determine what a conventional practice, method, or system is and how an alternative or sustainable practice, method, or system might or should differ from a conventional one. The following definitions are drawn from the Glossary of Alternative Agriculture (National Research Council, 1989a).

A farming practice is a way of carrying out a discrete farming task such as a tillage operation, particular pesticide application technology, or single conservation practice. Most important farming operations—preparing a seedbed, controlling weeds and erosion, or maintaining soil fertility, for example—require a combination of practices, or a method. Most farming operations can be carried out by different methods, each of which can be accomplished by several unique combinations of different practices. The manner in which a practice is carried out—the speed and depth of a tillage operation, for example—can markedly alter its consequences.

A farming method is a systematic way to accomplish a specific farming objective by integrating a number of practices. A discrete method is needed for each essential farming task, such as preparing a seedbed and planting a crop, sustaining soil fertility, managing irrigation, collecting and disposing of manure, controlling pests, and preventing animal diseases.

A farming system is the overall approach used in crop or livestock production, often derived from a farmer's goals, values, knowledge, available technologies, and economic opportunities. A farming system influences, and is in turn defined by, the choice of methods and practices used to produce a crop or care for animals.

In practice, farmers are constantly adjusting cropping systems in an effort to improve a farm's performance. Changes in management practices generally lead to a complex set of results—some positive, others negative—all of which occur over different time scales.

The transition to more sustainable agriculture systems may, for many farmers, require some short-term sacrifices in economic performance in order to prepare the physical resource and biological ecosystem base needed for long-term improvement in both economic and environmental performance. As a result, some say that practices essential to progress toward sustainable agriculture are not economically viable and are unlikely to take hold on the farm (Marten, 1989). Their contention may prove correct, given current farm policies and the contemporary inclination to accept contemporary, short-term economic challenges as inviolate. Nonetheless, one question lingers: What is the alternative to sustainable agriculture?

PUBLIC POLICY AND RESEARCH IN SUSTAINABLE AGRICULTURE

Farmers, conservationists, consumers, and political leaders share an intense interest in the sustainability of agricultural production systems. This interest is heightened by growing recognition of the successes achieved by innovative farmers across the country who are discovering alternative agriculture practices and methods that improve a farm's economic and environmental performance. Ongoing experimental efforts on the farm, by no

means universally successful, are being subjected to rigorous scientific investigation. New insights should help farmers become even more effective stewards of natural resources and produce food that is consistently free of man-made or natural contaminants that may pose health risks.

The major challenge for U.S. agriculture in the 1990s will be to strike a balance between near-term economic performance and long-term ecological and food safety imperatives. As recommended in Alternative Agriculture (National Research Council, 1989a), public policies in the 1990s should, at a minimum, no longer penalize farmers who are committed to resource protection or those who are trying to make progress toward sustainability. Sustainability will always remain a goal to strive toward, and alternative agriculture systems will continuously evolve as a means to this end. Policy can and must play an integral role in this process.

If sustainability emerges as a principal farm and environmental policy goal, the design and assessment of agricultural policies will become more complex. Trade-offs, and hence choices, will become more explicit between near-term economic performance and enhancement of the long-term biological and physical factors that can contribute to soil and water resource productivity.

Drawing on expertise in several disciplines, policy analysts will be compelled to assess more insightfully the complex interactions that link a farm's economic, ecological, and environmental performance. It is hoped that political leaders will, as a result, recognize the importance of unraveling conflicts among policy goals and more aggressively seizing opportunities to advance the productivity and sustainability of U.S. agriculture.

A few examples may help clarify how adopting the concept of sustainability as a policy goal complicates the identification of cause-and-effect relationships and, hence, the design of remedial policies.

When a farmer is pushed toward bankruptcy by falling crop prices, a farm operation can become financially unsustainable. When crop losses mount because of pest pressure or a lack of soil nutrients, however, the farming system still becomes unsustainable financially, but for a different reason. In the former example, economic forces beyond any individual farmer's control are the clear cause; in the latter case the underlying cause is rooted in the biological management and performance of the farming system.

The biological and economic performance of a farming system can, in turn, unravel for several different reasons. Consider an example involving a particular farm that is enrolled each year in the U.S. Department of Agriculture's commodity price support programs. To maintain eligibility for government subsidies on a continuing basis, the farmer understands the importance of growing a certain minimum (base) acreage of the same crop each year. Hence, the cropping pattern on this farm is likely to lead to a

buildup in soilborne pathogens that attack plant roots and reduce yields. As a result, the farmer might resort to the use of a fumigant to control the pathogens, but the pesticide might become ineffective because of steadily worsening microbial degradation of the fumigant, or a pesticide-resistant pathogen may emerge.

A solution to these new problems might be to speed up the registration of another pesticide that could be used, or relax regulatory standards so more new products can get registered, or both. Consider another possibility. A regulatory agency may cancel use of a fumigant a farmer has been relying upon because of food safety, water quality, or concerns about it effect on wildlife. The farmer might then seek a change in grading standards or an increase in commodity prices or program benefits if alternative pesticides are more costly.

Each of these problems is distinctive when viewed in isolation and could be attacked through a number of changes in policy. The most cost-effective solution, however, will prove elusive unless the biology of the whole system is perceptively evaluated. For this reason, in the policy arena, just as on the farm, it is critical to know what the problem is that warrants intervention and what the root causes of the problem really are.

Research Challenges

In thinking through agricultural research priorities, it should be acknowledged that the crossroads where the sciences of agriculture and ecology meet remain largely undefined, yet clearly promising. There is too little information to specify in detail the features of a truly sustainable agriculture system, yet there is enough information to recognize the merit in striving toward sustainability in a more systematic way.

The capacity of current research programs and institutions to carry out such work is suspect (see Investing in Research [National Research Council, 1989b]). It also remains uncertain whether current policies and programs that were designed in the 1930s or earlier to serve a different set of farmer needs can effectively bring about the types of changes needed to improve ecological management on the modern farm.

In the 1980s, the research community reached consensus on the diagnosis of many of agriculture's contemporary ills; it may take most of the 1990s to agree on cures, and it will take at least another decade to get them into place. Those who are eager for a quick fix or who are just impatient are bound to be chronically frustrated by the slow rate of change.

Another important caution deserves emphasis. The “silver bullet” approach to solving agricultural production problems offers little promise for providing an understanding of the ecological and biological bases of sustainable agriculture. The one-on-one syndrome seeks to discover a new

pesticide for each pest, a new plant variety when a new strain of rust evolves, or a new nitrogen management method when nitrate contamination of drinking water becomes a pressing social concern. This reductionist approach reflects the inclination in the past to focus scientific and technological attention on products and outcomes rather than processes and on overcoming symptoms rather than eliminating causes. This must be changed if research aimed at making agriculture more sustainable is to move ahead at the rate possible given the new tools available to agricultural scientists.

One area of research in particular—biotechnology—will benefit from a shift in focus toward understanding the biology and ecology underlying agricultural systems. Biotechnology research tools make possible powerful new approaches in unraveling biological interactions and other natural processes at the molecular and cellular levels, thus shedding vital new light on ecological interactions with a degree of precision previously unimagined in the biological sciences. However, rather than using these new tools to advance knowledge about the functioning of systems as a first order of priority, emphasis is increasingly placed on discovering products to solve specific production problems or elucidating the mode of action of specific products.

This is regrettable for several reasons. A chance to decipher the physiological basis of sustainable agriculture systems is being put off. The payoff from focusing on products is also likely to be disappointing. The current widespread pattern of failure and consolidation within the agricultural biotechnology industry suggests that biotechnology is not yet mature enough as a science to reliably discover, refine, and commercialize product-based technologies. Products from biotechnology are inevitable, but a necessary first step must be to generate more in-depth understanding of biological processes, cycles, and interactions.

Perhaps the greatest potential of biotechnology lies in the design and on-farm application of more efficient, stable, and profitable cropping and livestock management systems. For farmers to use such systems successfully, they will need access to a range of new information and diagnostic and analytical techniques that can be used on a real-time basis to make agronomic and animal husbandry judgments about how to optimize the efficiencies of the processes and interactions that underlie plant and animal growth.

Knowledge, in combination with both conventional and novel inputs, will be deployed much more systematically to avoid soil nutrient or animal nutrition-related limits on growth; to ensure that diseases and pests do not become serious enough to warrant the excessive use of costly or hazardous pesticides; to increase the realistically attainable annual level of energy flows independent of purchased inputs within agroecosystems; and to maximize a range of functional symbiotic relationships between soil micro-

and macrofauna, plants, and animals. Discrete goals will include pathogen-suppressive soils, enhanced rotation effects, pest suppression by populations of plant-associated microorganisms, nutrient cycling and renewal, the optimization of general resistance mechanisms in plants by cultural practices, and much more effective soil and water conservation systems that benefit from changes in the stability of soil aggregates and the capacity of soils to absorb and hold moisture.

Because of the profound changes needed to create and instill this new knowledge and skills on the farm, the recommendations in Alternative Agriculture (National Research Council, 1989a) emphasize the need to expand systems-based applied research, on-farm experimentation utilizing farmers as research collaborators, and novel extension education strategies—the very goals of the U.S. Department of Agriculture's LISA program.

Future research efforts—and not just those funded through LISA—should place a premium on the application of ecological principles in the multidisciplinary study of farming system performance. A diversity of approaches in researching and designing innovative farming systems will ensure broad-based progress, particularly if farmers are actively engaged in the research enterprise.

Benbrook, C., and J. Cook. 1990. Striving toward sustainability: A framework to guide on-farm innovation, research, and policy analysis. Speech presented at the 1990 Pacific Northwest Symposium on Sustainable Agriculture, March 2.

Marten, J. 1989. Commentary: Will low-input rotations sustain your income? Farm Journal, Dec. 6.

National Research Council. 1989a. Alternative Agriculture. Washington, D.C.: National Academy Press.

National Research Council. 1989b. Investing in Research: A Proposal to Strengthen the Agricultural, Food, and Environmental System. Washington, D.C.: National Academy Press.

Interest is growing in sustainable agriculture, which involves the use of productive and profitable farming practices that take advantage of natural biological processes to conserve resources, reduce inputs, protect the environment, and enhance public health. Continuing research is helping to demonstrate the ways that many factors—economics, biology, policy, and tradition—interact in sustainable agriculture systems.

This book contains the proceedings of a workshop on the findings of a broad range of research projects funded by the U.S. Department of Agriculture. The areas of study, such as integrated pest management, alternative cropping and tillage systems, and comparisons with more conventional approaches, are essential to developing and adopting profitable and sustainable farming systems.

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5 5 Experimental design: agricultural field experiments and clinical trials

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This chapter discusses the statistical approach to experimental design, with an emphasis on the core concepts of randomization and blocking. It focuses initially on agricultural field experiments, but also describes the basic elements of a type of medical research investigation known as a clinical trial.

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A typology to guide design and assessment of participatory farming research projects

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• Published: 07 April 2023
• Volume 5 , pages 159–174, ( 2023 )

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Participatory modes of agricultural research have gained significant attention over the last 40 years. While many scholars and practitioners agree that engaging farmers and other stakeholders is a valuable complement to traditional scientific research, there is significant diversity in the goals and approaches used by participatory projects. Building on previous conceptual frameworks on divergent approaches to participatory farming research (PFR), we propose an updated synthetic typology that can be used to design, evaluate, and distinguish PFR projects. Key elements of our typology include a recognition of the multidimensionality of projects that reflect different combinations of: (a) the goals or motivations behind engaging farmers in research, (b) the specific methods or approaches used to implement a PFR project, and (c) the social, institutional, and biophysical contexts that shape the dynamics and outcomes from PFR. We use this typology to highlight how particular manifestations of participatory agricultural research projects—ranging from farmer advisory boards, on-farm demonstrations, and researcher- versus farmer-led on-farm research projects—combine goals, methods, and contexts in distinctive ways. Proponents of PFR projects would benefit from clarifying how their work fits into or extends this multidimensional typology.

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1 Introduction

Conventional scientific research has been credited with impressive gains in productivity and efficiency in the USA and global agriculture. However, the traditional transfer-of-technology (ToT) model in which scientific innovations are created by experts then disseminated to farmers has come under increasing criticism for generating undesirable environmental and socioeconomic externalities, and for ignoring the important role of farmer knowledge and peer-to-peer social networks in the evolution of complex farming systems (Neef et al. 2013 ). Researchers in the ToT model have often treated agricultural challenges as tame problems that are technical in nature and have mechanical, straightforward solutions (DeFries and Nagendra 2017 ). This approach fails to appreciate the critical role of cultural, social, and physical contexts play in shaping outcomes (Ashby 2003 ).

Partly as a response to critiques of the ToT model, participatory approaches to agricultural research have attracted increasing attention since the early 1980s (e.g., Chambers 1983 , 1994 ; Ashby 1986 ; Taylor 1991 ; Pretty 1995 ; Pound et al. 2003 ; Scoones and Thompson 2009 ). Advocates have argued that engaging farmers earlier in the research process can ensure new technologies are appropriate for target populations and that participatory methods are essential to develop and support more agroecologically based farming systems that rely heavily on locally managed biophysical and socioeconomic processes (Berthet et al 2016 ; MacMillan and Benton 2014 ; Sumane et al. 2018 ).

While many scholars and practitioners now agree that facilitating participation of farmers and other stakeholders can be a valuable complement to traditional scientific research, there is significant diversity in the specific motivations and approaches used, and in their epistemological assumptions about the value of knowledge generated from participatory research. In other words, all participatory farming research (PFR) is not equal. Examples of PFR in the literature include demonstration farms, use of farmer research advisory boards, implementation of collaborative on-farm research trials, and work by farmer-led research networks, among others. This diversity of approaches can create confusion and limits the potential to select the most appropriate approaches to engaging farmers in agricultural research.

Over the last 40 years, a number of PFR scholars and practitioners have proposed typologies and conceptual frameworks to help organize this diverse collection of activities. Lilja and Ashby ( 1999 ) differentiated projects based on the degree of decision-making control held by scientists vs. farmers and whether or not there was an organized effort to structure communication between researchers and farmers. Johnson et al. ( 2003 ; 2004 ) built on this work to propose a framework with three components: (a) a ladder of participation in which farmers are given more significant control over research decisions as you climb the ladder, (b) a recognition that farmer participation and control could occur at different stages of the research process, and (c) a recognition that participation could be used to achieve different goals or purposes (e.g., improving the efficiency and effectiveness of the innovation process vs. empowerment of rural people). Probst and Hageman ( 2003 ) proposed a similar framework that included these three attributes, but argued that attention should also be given to epistemological assumptions, the formality of research design and methods, the characteristics of participating farmers or stakeholders, and the role of external actors and broader policy or institutional context.

Most of these earlier approaches explicitly or implicitly suggested a broadly unidimensional framework in which combinations of goals/methods were arranged from low to high levels of farmer participation. In contrast, Neef and Neubert ( 2011 ) proposed a more fine-grained framework that integrated key concepts from previous work as well as additional classification dimensions based on their own experiences in participatory research and development projects (see also Neef and Neubert 2005 ). Their framework proposed six dimensions that could be used to account for the diversity of participatory agricultural research projects and their outcomes: project type (a combination of research objectives and institutional context), project approach (combining research methods, epistemology, plans and processes), researcher characteristics (previous experience, attitudes, and commitment), stakeholder characteristics (experiences, perceptions, and capacity), interactions between researchers and stakeholders (levels and intensity of participation and contributions by scientists vs. stakeholders, timing), and stakeholders’ benefits (desired or intended outcomes, ranging from innovation, new knowledge, skill building, improved livelihoods, and empowerment).

While comprehensive, the Neef and Neubert framework blurs a critical distinction between internal factors involved in the design and implementation of a project, and features of the external social, institutional, and organizational conditions that shaped the ability of PFR projects to achieve their goals. Moreover, the framework they propose fails to capture some of the important concepts and distinctions that have been raised in earlier work. In this paper, we use a narrative review of the published literature on participatory methods (in both agricultural and non-agricultural contexts) to propose a relatively simple typology that captures the diversity of PFR methods that can be combined in different ways on different projects. We use this typology to classify a number of prominent PFR approaches in the literature to highlight some key differences across projects based on their goals and methodologies. We also suggest ways in which this typology can be used to guide the design, implementation, and critical evaluation of future on-farm participatory research projects.

2 Differences among approaches to participatory farmer research

Growing uncertainties due to climate change, increasing application of digital platforms by farmers, and appreciation for the complexity of farming systems has led to a resurgence of interest in on-farm research projects as a vehicle for transformational change in agriculture (Lacoste et al. 2021 ). In response, we conducted a comprehensive search of published articles indexed in the Web of Science through 2021 which include the following key terms: ‘on-farm research,’ ‘on-farm experiment*,’ ‘farmer-led research,’ ‘participatory agricultural research,’ and ‘participatory on-farm research.’ We focused our search on examples of PFR work, particularly papers that categorized or distinguished differences in goals, methods, and approaches across the literature. This review helped us identify some of the diverse motivations/goals, methodological approaches, and epistemological assumptions about the status of knowledge created by non-scientists across these projects. Additionally, this search uncovered a number of synthesis papers that offered theoretical concepts and proposed methodological frameworks to characterize and critique different manifestations of PFR. Below, we draw from this previous work, as well as from the larger literature on participatory approaches to research (from non-agricultural settings), to outline a multidimensional classification scheme or typology that can be used to recognize and understand the implications of different choices for how to organize, implement, and evaluate PFR.

2.1 Objectives/goals for PFR

One of the critical distinctions between alternative approaches to participatory research is reflected in the diverse goals or underlying motivations for involving farmers and other stakeholders in agricultural research. A number of authors have presented schema to categorize the different goals or objectives that they expect to come from using PFR. Most highlight a difference between functional and normative outcomes (Hellin et al. 2008 ; Neef and Neubert 2011 ).

Functionally, participatory approaches can be used to ensure that agricultural research done in a manner that increases the validity, usefulness, or efficiency of the research process and the adoption or utilization of new knowledge and technologies (Lilja and Bellon 2008 ). In the broader participatory research literature, Blackstock et al. ( 2007 ) differentiate between two subcategories of ‘functional’ goals: (a) instrumental motivations, that focus more on using collaborative approaches to defuse conflict and increase acceptance of scientific work, and (b) substantive motivations in which the inclusion of multiple perspectives can both improve our basic understanding of and help identify the most appropriate solutions for the context.

Normatively, participation may be used to achieve specific ethical or moral objectives. This often includes the goal of addressing social and economic inequality by bringing underrepresented voices into the research process and/or using participatory methods to give more power to disadvantaged groups and communities to advance their own interests (Hacker 2013 ; Wilson 2019 ).

2.1.1 Functional–instrumental goals

PFR methods are often motivated by functional–instrumental goals to increase trust and acceptance of scientific knowledge and ultimately to accelerate adoption of new agricultural innovations. In contrast to functional–substantive goals (discussed below), functional–instrumental goals generally do not expect farmers’ knowledge or feedback to seriously alter the trajectory of scientific research and discovery. Instead, participation is focused on helping farmers understand how to apply, adopt, and eventually disseminate knowledge and innovations that were produced using traditional scientific methods.

Lawrence et al. ( 2007 ) noted that some farming systems researchers working on international development view farmer participation mainly as a mechanism to validate new technologies, tweak or establish ‘proper’ input levels, and identify the most attractive packages of practices that can be used in extension programs. In each case, the emphasis is focused on helping researchers demonstrate the relevance of their research so they can accelerate farmer implementation of scientifically recommended practices (Lacoste et al. 2021 ). Johnson et al. ( 2004 ) also point to projects where ‘turnkey solutions’ are presented, and farmer participation is designed to identify barriers that need to be overcome in order to increase uptake and use of scientific research and new innovations.

Functional–instrumental goals in PFR parallel work from sustainability science and sustainability transitions literature that focuses on the mechanisms of collective or social learning (Van Mierlo and Beers 2020 ) and the use of processes that engage societal actors more directly in the scientific process (Schneider et al. 2019 ; Turnheim et al. 2015 ). This work often seeks to engage societal actors (or non-scientists) less because they can contribute special and complementary forms of knowledge to a research process, and more because these are the actors whose understanding and decisions are critical to any societal transformation.

2.1.2 Functional–substantive goals

By contrast, researchers working on complex farming systems or in resource constrained settings have long recognized that farmer feedback can also be useful in directing the design and implementation of formal scientific experimental methods which can substantively shape the actual knowledge that is generated. They have argued that engaging farmers as partners allows research scientists to test their knowledge and findings under working farm conditions and to collect farmer input on the interpretation of scientific findings and evaluation of recommendations (Lambrou 2001 ; Hellin et al. 2008 ; Hurst et al. 2022 ). Engagement can also be used to create or adapt new technologies or management practices to ensure they are able to address the needs of diverse producers (Hermans et al. 2021 ). For example, scientists using participatory plant breeding methods can ask farmers to identify traits important to them so they can be prioritized in crop or livestock breeding programs (Sperling et al. 2001 ; Witcombe et al. 2005 ). In this way, farmer feedback can substantively impact the conduct and trajectory of scientific research.

In addition to shaping scientific agendas and adapting scientific recommendations to better fit local situations, substantive motivations for participatory research can also include a desire to incorporate farmer observations and experiences as intrinsically important and complementary sources of knowledge. To many practitioners, PFR should quintessentially be seen as a process of co-production of knowledge (Brugnach and Ingram 2012 ) that combines alternative ways of knowing (representational, relational, and reflective). Scientists may elect to collaborate with farmers to co-produce new knowledge by combining scientific experiments with insights and findings based on farmer observations and accumulated experiential knowledge (Lawrence et al. 2007 ).

The use of participatory approaches to capitalize on the lived experiences and accumulated knowledge of practitioners is a core element of what is often called ‘post-normal’ science. Unlike ‘normal science,’ in which problems are divided into smaller and smaller questions to be answered by expert scientists using reductionist methods, post-normal science (PNS) is explicitly designed to be used to address complex scientific questions in which ‘facts are uncertain, values in dispute, stakes high, and decisions urgent’ (Funtowicz and Ravetz 1991 , p.138). To advance under these conditions, it is argued that knowledge about risks and hazards can benefit from incorporating information from people with lived experience, so-called extended facts coming from an extended peer community (Turnpenny et al. 2011 , p.292). Criteria for evaluating the validity of knowledge claims under PNS approaches also emerge from a process in which societal actors engage in dialogue with experts to jointly assess their merits (Funtowitcz and Ravetz 1993 , p.744).

Aksoy and Oz ( 2020 ) have argued that participatory methods can help farmers and researcher find a common language that places two distinct forms of agricultural knowledge (traditional and scientific) on an equal ground. On-farm research and collaboration can be an important technique to discover or validate existing farmer knowledge and understandings of the impacts of agricultural management practices and technologies (Witcombe et al. 2005 ; Ceccarelli et al. 2003 ; Ceccarelli and Grando 2007 ). One approach is to support farmer research networks that facilitate peer-to-peer exchange of observations and experience to accelerate the accumulation of collective knowledge among farmers, as well as to make that information more available to scientists working on the same farming systems (Probst and Hagemann 2003 ).

The idea that understanding the dynamics of complex systems (and developing solutions that can actually effect changes in the world) requires scientists to engage with non-scientific actors is a core tenet of most transdisciplinary (TD) research methods. TD approaches are generally characterized as research that (a) integrates methods and perspectives from multiple scientific disciplines to create a more robust interdisciplinary scientific understanding and (b) incorporates actors from the ‘life-world’ into the research process (Hadorn et al. 2008 ). Differences between traditional disciplinary (and interdisciplinary) scientific work and TD research generally lie in the levels of involvement and relative roles of scientists and societal actors in the process of problem identification, problem structuring, learning and analysis, and implementation of recommendations (Elzinga 2008 ).

In the context of PFR, Lawrence et al. ( 2007 ) have noted that there is often a tension between the perceived relevance and rigor of research depending on how much participants rely on formal research designs and the extent to which information from unreplicated and relatively simple observational trials can be integrated with findings from controlled on experiments. Pragmatically, this tension can be seen in whether or not results from on-farm observations and trials are taken seriously by scientists or project leaders, or given equivalent epistemological status as results from formal on-station experiments. Similarly, it is worth asking whether data and findings from PFR projects are expected to be publishable in peer-reviewed journals or generalizable to other regions beyond the specific farms or communities where research takes place.

The TD literature provides some guidance on these points. Epistemologically, many TD scholars distinguish between 3 types of knowledge: systems knowledge, target knowledge, and transformational knowledge (Pohl and Hadorn 2008 ; Smetschka & Gaube 2020 ). Systems knowledge reflects an understanding of empirical processes and interactions in the life-world that generates better understanding of how current complex systems work. Target knowledge helps identify needs for changes in current systems and the features of desirable alternatives. Transformational knowledge is about how best to transition from the current system to the target system (e.g., knowledge about technical, social, legal, and other means of action). TD (or PFR) methods can be used to produce all three types of knowledge.

2.1.3 Normative-empowerment goals

In addition to functional goals, participatory approaches may be used because it is normatively the right thing to do (Pretty 1995 ). These motivations for PFR often parallel the goals and methods used in the community-based participatory research literature discussed above—democratizing the knowledge production process, addressing structural inequalities, and generating social change (Bell and Reed 2021 ; Reason and Bradbury 2001 ). A primary normative goal is to increase the human and social capital of participants and empower them to solve their own problems through experimentation, adaptation, and innovation (Hellin et al. 2008 ; Lilja and Dixon 2008 ). Frequently these goals include a focus on traditionally marginalized or underrepresented farmers, including women, members of racial or ethnic minorities, or small or limited resource farms who are often not served by conventional agricultural research and extension systems (Johnson et al. 2004 ; Neef and Neubert 2011 ).

Hellin et al. ( 2008 ) make a distinction between using PFR to empower individual farmers and using it to strengthen intermediate organizations that support equitable and sustainable agricultural development. In the former case, the emphasis is often on building farmers’ capacity to create networks or to use scientific principles to improve the pace and efficiency of knowledge generation (Ashby et al. 2000 ; Braun et al. 2000 ). Increasing local people’s capacity for self-directed innovation can create conditions for emancipation or transformation of social inequality in agricultural settings (Probst and Hagmann 2003 ).

In the latter case, building better relationships between farmers and upstream development organizations or agencies can boost collective social capital and make institutions more responsive to grass roots needs and priorities (Johnson et al. 2004 ). Lawrence et al. ( 2007 ) point to a third phase of farming systems research that studies the complex system of interest as a whole, rather than attempting to control all the parts individually. In this approach, the emphasis is on developing a social learning process where researchers and other actors in farming systems learn how to contextualize and apply their knowledge and new technologies. Echoing the goals of sustainability transitions scholars, this focus uses PFR to create new social structures and institutions that are adapted to the needs of concrete needs and challenges faced by diverse farmer communities.

2.1.4 Non-research or manipulative goals

While PFR is generally pursued to advance either functional and/or normative goals, some scholars have noted that participatory engagement can also be deployed as a strategy simply to demonstrate or extend knowledge that had been generated through conventional (non-participatory) research, or what Pretty ( 1995 ) refers to as ‘passive participation.’ In these cases, the goal is not actually to do research and generate new knowledge, or to adapt scientific knowledge to local contexts, but rather to convince farmers to embrace the findings or recommendations of normal (mode 1) agricultural research. In this way, nominally participative processes can be deployed simply to gain the agreement of farmers and other target audiences for projects that experts or government officials have already decided were needed (Cornwall 2008 ). By emphasizing acceptance and adoption of scientific knowledge and innovations, these projects place most weight on what farmers can learn from researchers, such as learning new varieties’ names and characteristics, or how to use their farms to demonstrate the benefits of recommended agronomic practices to other farmers. In extreme cases, insincere or ‘manipulative’ participatory approaches can even be used to generate acquiescence for programs or policies that may not be in local actors’ best interests (Jones et al. 2014 ).

2.2 Methods for Implementing PFR

Aside from recognizing the distinctive goals that participatory agricultural research may be designed to accomplish, PFR projects can also be classified based on their choice of methods or approaches along a number of dimensions. These can include issues of decision-making (degree of farmer authority), timing (stage of the research process where participation occurs), structured communication (style and formality of interactions), representation (who participates), and location (where research takes place). In much of the literature on participatory research, the distinctions between the goals (discussed above) and methods of participatory research (discussed below) can be blurred. In our proposed typology, we seek to draw attention to the different combinations of goals and methods that may be observed across PFR projects.

2.2.1 Decision-making authority

Nearly all participatory approaches involve the use of methods, tools, and strategies that are designed to enhance the control of practitioners and beneficiaries on decision-making processes that affect their resources, works, and livelihoods (Bell and Reed 2021 ). In the community development or collaborative natural resource management literature, this can involve the devolution of decision-making power to individuals or groups in society who are directly impacted by public policy decisions (Reed et al. 2018 ).

When participatory approaches are used to conduct agricultural research, most of the key questions about decision-making authority reflect the balance of input and impact on final decisions allocated to farmers (and perhaps other stakeholders) versus scientists and researchers (Farrington and Martin 1988 ; Lambrou 2001 ; Neef and Neubert 2011 ). For example, Sperling et al ( 2001 ) distinguished participatory plant breeding projects based on whether they were initiated and led by farmers (farmer-led) or by external actors, like government or university programs (formal-led). Depending on the organization of a PFR project, farmers can play different roles that range from providing scientists with (a) land, labor, or seeds, (b) information about their problems or needs, and/or (c) technical or social leadership to help govern, manage, or implement a project.

Building on the concept of a ‘ladder of participation’ originally developed by Arnstein ( 1969 ), and applied to agricultural research by Biggs ( 1989 ) and Lilja and Ashby ( 1999 ), Johnson et al. ( 2003 ) have proposed a useful synthesis typology of PFR that includes 5 core rungs or degrees of participation:

Conventional projects where farmers are asked to help implement research by providing land or labor to research projects that are fully conceived and designed by scientists, but where farmers have little input into the research questions or choice of treatments or methods. This has also been called ‘contractual’ participation (Biggs 1989 ; Probst and Hageman 2003), ‘nominal’ participation (Neef and Neubert 2011 ), or ‘passive’ participation (Pimbert 2011 ; Pretty 1995 ).

Consultative projects where scientists actively consult with farmers to learn their opinions and preferences, but retain the final decision-making authority themselves. This has also been referred to as ‘functional’ participation (Pretty 1995 ).

Collaborative projects where decision-making authority about research is shared equally between scientists and farmers, also referred to as ‘cooperation’ or ‘co-learning’ (Cook et al. 2017 ), or ‘co-production’ (Reed et al. 2018 ).

Collegial projects where farmers consult with scientists to get their input, but farmers retain the final decision-making authority. Some have referred to these types of arrangements as ‘interactive’ participation (Pretty 1995 )

Independent projects where farmers work with only nominal input from researchers to design and implement their own agricultural research projects, either individually or in groups. Others have referred to these as ‘self-mobilization’ (Pretty 1995 ) or ‘collective action’ research (Cook et al. 2017 ).

2.2.2 Timing of participation

Related to the different levels of decision-making authority given to farmers, some scholars have identified differences across projects based on the timing of when farmer input on research decisions is encouraged or allowed. Farrington and Martin ( 1988 ) distinguished three key stages of a research project where farmer participation could potentially be important: problem identification, conduct of the research, and dissemination of the research. Similarly, Johnson et al. ( 2003 ) write about the three stages of an innovation process:

The Design Stage when problems or opportunities for research are identified and prioritized, there is an initial diagnosis of the problem and framing of research questions, and decisions are made about which new ideas to test, what outcomes to monitor, and which farmers or fields will be involved.

The Testing Stage when potential solutions are tested and evaluated, including implementing fieldwork, monitoring progress and outcomes, interpreting the data or findings, and making decisions about what solutions to recommend.

The Diffusion Stage where steps taken to build awareness of recommended solutions among potential users through the use of demonstrations, educational events, and development of extension or outreach materials.

Different PFR projects may target any or all of these stages.

2.2.3 Organization and modes of communication

A number of scholars have pointed to the importance of different ways to organize or structure communication and flows of information between scientists and stakeholders in participatory projects. In their work on forms of public engagement more broadly, Rowe and Frewer ( 2005 ) distinguish between three possible modes of information exchange: communication, consultation, and participation. Communication modes are characterized by one-way flows of information from experts to stakeholders or society. Consultation modes are used to solicit input from specific social actors on topics that have both been selected by scientists. Participation modes require full two-way communication between experts/scientists and the public where information flows in both directions with joint formulation of goals and outcomes. Reed et al. ( 2018 ) note that all three can be seen in self-described ‘participatory’ projects, but the first two are usually top-down approaches, while two-way exchanges can either be controlled by scientists, stakeholders, or some combination of the two.

Almost 20 years ago, Ashby and Lilja ( 2004 ) adapted these ideas in their typology of participatory agricultural research by emphasizing both the direction of information flows and the degree of organized communication that occurs within a project. This last criterion adds an important element since it helps distinguish participatory projects in which communication is systematic, consistent, intentional, and organized from projects that approach communication and information exchange in a more ad hoc manner. Neef and Neubert ( 2011 ) express a similar idea by highlighting the type, frequency, and intensity of interactions as a key dimension of classifying approaches to stakeholder participation in agricultural research.

2.2.4 Who participates?

The question of who participates—as well as who is excluded and who exclude themselves—is a crucial one when categorizing PFR projects (Leventon et al. 2016 ). Two aspects of who participates in a research process can help classify different approaches (Ashby 1996 ). One is whether the participants are representative of local farming communities or a population of target end-users. The second is whether the participants are knowledgeable or bring the right mix of relevant expertise to the process.

In the first instance, the methods scientists use to recruit or invite farmers can impact the degree to which PFR produces knowledge or insights that will be relevant to the full range of producers found in an area (Probst and Hagmann 2003 ). Most agroecological settings are characterized by social and economic differences where a minority of farmers have disproportionate access to land, labor and capital resources, while female, ethnic and racial minority, and limited resource producers face greater obstacles to their ability to take advantage of new innovations (Som Castellano and Mook 2022 ).

Depending on the goals and objectives of a participatory project, whether or not participants are representative of these different subgroups can make an important difference (Taylor 1991 , p.45,48). Used effectively, participatory research grounded in diversity analysis can draw out and build on the range of perceptions, interests, and status found in farming communities to support more equitable and sustainable outcomes. To be effective, researchers should identify the key dimensions of diversity or difference that merit inclusion and design the process to ensure that key stakeholders are represented and able to participate. At a minimum, PFR projects that are conscious and intentional about the recruitment of farmers are more likely to ensure representation of the types of farms that are the target beneficiaries of their efforts.

In the second instance, projects that embrace and seek to incorporate the experiential knowledge held by local farmers may find that not all producers are equally skilled at observing outcomes associated with alternative management practices or accumulating knowledge about the dynamics of local agroecosystems (Farrington and Martin 1988 ). Som Castellano and Mook ( 2022 ) indicate that the research topic and question development process and methods can significantly shape the types of relevant stakeholders to include.

In both cases, whether or not the mix of farmer participants is ‘ideal’ will hinge on the overall goals or objectives of the participatory process. There can also be tensions between these two ideas since a farmer’s familiarity and comfort with scientists and formal research institutions, ability to find time to participate, and capacity to experiment with alternative management practices are not equally present in fully representative groups of farmers (Neef and Neubert 2011 ). Similarly, without conscious efforts to understand and manage power dynamics across diverse farmer subgroups, participatory processes can struggle to get authentic and complete participation from the full spectrum of actors (Reed et al. 2018 ).

2.2.5 Location of research

Several authors have noted that the physical location where knowledge production and sharing takes place can shape who participates and whether and how new information is created and exchanged (Barreteau et al. 2010 ; Bell and Reed 2021 ). The strength of on-station research lies in the ability of research scientists to implement complex experimental designs and closely observe the results of treatments or manipulations under controlled conditions. A centerpiece of the traditional ToT model, on-station research is often conducted first to develop basic knowledge that can then be offered or conveyed to farmers (Leeuwis 2004 ). For example, fundamental knowledge about the biophysical dynamics of managed farming systems is often viewed by researchers as a precursor to helping farmers figure out how best to manage their operations (Toffolini et al. 2017 ).

By contrast, on-farm research can be done for several reasons. First, on-farm research provides an opportunity to test findings from on-station research under more realistic or representative production conditions. It can help scientists better understand the complex dynamics and interactions among elements of working socioeconomic and agroecological systems, and how actual outcomes from new management approaches can be shaped by the biophysical, cultural, and socioeconomic attributes of specific farming landscapes and communities (Wojcik et al. 2019 ). If it is an explicit goal of the PFR project, on-farm research can also be used to gather and aggregate farmers’ tacit knowledge and experiential observations about the performance of different management strategies. It can also provide a more intimate venue for deeper interactions and collaboration between farmers and scientists, where participants can deliberate and reflect on the connections and dissonances between experiential and expert scientific knowledge (Baars 2011 ).

2.3 Participatory farming research typology

These various dimensions which can distinguish between different approaches to PFR are summarized in Fig.  1 . While we see strong potential linkages between the specific goals set out for a particular PFR project and the methods that would be most likely to achieve those goals, we also recognize that these may be combined in various and distinctive ways. In the next section, we review some of the most common examples of PFR in the published literature and classify them against this typology. Importantly, as with the framework proposed by Neef and Neubert ( 2011 ), our typology is multidimensional and not a simple ‘ladder of participation’ in which all dimensions move up and down a participatory spectrum in the same way.

Dimensions along which PFR projects can be classified

2.4 Recognizing differences across PFR approaches

There are a wide range of specific examples of PFR in the peer-reviewed publications that include some degree of farmer participation in agricultural research in the work identified in our search of the literature. While not an exhaustive list, below we highlight some of the more common exemplars below, using examples from published papers, and discuss how they can be categorized and distinguished by our PFR typology.

2.4.1 Farmer research advisory boards

Many traditional agricultural science programs at public land grant universities in the USA include the use of farmer and stakeholder advisory boards to review and provide input into ongoing research projects. This is particularly common for larger applied interdisciplinary projects, which comprise a growing share of the federally funded agricultural research portfolio. While there is virtually no published research literature on the various forms and impacts of these types of boards, in our experience they are usually expected to achieve both functional–instrumental and non-research goals. In the first instance, farmer input may be solicited about the broad topics that the research should address, and farmers may offer specific feedback related to particular methodological approaches or interpretations of the findings. In the latter case, advisory boards frequently serve a demonstration/outreach goal wherein results from research are shared with advisors to test how well they will resonate with the broader farming target audience.

Members of farmer advisory boards are rarely given much power to make decisions about core research design issues but more typically play a consultative role in which their suggestions and reactions may influence decisions by the scientists that implement the actual research. Advisory boards can weigh in at all three stages of the research process (design, testing, and diffusion). The structure and format of advisory board meetings comprise one exemplar for organized communication between farmers and scientists, and information flows reflect a consultation model in which presentations from scientists to researchers take up most time on meeting agendas, but there are designated moments where questions, comments, and suggestions are solicited from farmers.

In our experience, farmers selected to serve on advisory boards represent individuals who are identified as leaders in their industry, have the time and resources that allow them to attend advisory board meetings, and typically have denser social and professional ties to university researchers, government conservation agencies, and established farm or commodity organizations. There is evidence that women are underrepresented on advisory boards (Mackenzie 1994 ). They are much more likely to be selected for their expertise or social positions than to represent the full range or diversity of producer types.

2.4.2 On-farm demonstrations

On-farm demonstrations have long been a tool used by outreach and extension programs to bring greater visibility to new agricultural research or innovations (Ingram et al. 2018 ). Typically placed on working farms, on-farm demonstrations are designed to highlight the performance and outcomes associated with new seed varieties, technological innovations, or recommended management practices. While there are exceptions, in most cases the demonstrations are not designed to generate new knowledge or data, but rather are set up to bring attention to findings from more controlled experimental research that has already been done elsewhere. The main goal is thus not to do participatory research per se, but to partner with host farmers to use their farms to demonstrate to the broader farm community that new innovations or practices actually work under realistic farming conditions. Examples of situations where on-farm work is more oriented to answering fundamental or applied research questions are described in a separate section below.

Compared to other approaches to PFR, farmers that host on-farm demonstrations are usually given relatively little decision-making authority about the design of research (since it is usually already done), though they do get to decide if they want to participate, and which practices they want to highlight on their farms. In this way, they are participating at the last (diffusion) stage of the research and innovation process. On-farm demonstrations do represent a formal, organized form of communication between scientists and farmers, but the direction of information flows is typically one-way (educating farmers about scientific knowledge), with few organized mechanisms to incorporate host (or attendee) farmer feedback into future iterations of the research program.

In the literature, on-farm demonstrations are often pursued by researchers and extension specialists who recognize the importance of social networks and opinion leaders as key drivers of the adoption and diffusion of agricultural innovations (Rogers 2004 ). As such, selection of host farms frequently prioritizes individuals who are seen as influential and trusted sources of advice among their peers (Pappa et al. 2018 ).

2.4.3 On-farm research

In addition to advisory boards and demonstrations, the literature on participatory farming research includes many examples of actual research projects that take place under working farm conditions. These can be organized in many different ways, with varying goals, farmer roles, degree of organized communication, and methods for selecting participants.

Scientist-led on-farm trials: One subgenre of on-farm research involves trials that are designed by scientists, but implemented on a number of collaborating farms. There is a growing literature using aggregated on-farm data to answer scientific questions about the performance of different management practices under realistic management conditions (de Souza et al. 2012 ; Kharel et al. 2019 ; Kyveryga 2019 ; Laurent et al. 2019 ).

A primary goal of replicated on-farm trials is to test the performance or outcomes associated with different management practices under working farm conditions. Because of the logistical difficulties associated with incorporating complex research designs in the on-farm context, research designs tend to be simplified. For example, many on-farm trials involve split-field comparisons of two or three practices instead of replicated and randomized small plot designs. As a result of these limitations, on-farm research is used by scientists to advance a mix of functional–substantive and functional–instrumental goals. Substantively, there may be new knowledge generated that confronts or expands current scientific understanding of farming systems or the impacts of different management practices. More likely, however, the focus of the on-farm work will be on how best to adapt new innovations or practices to ensure they fit into the complex labor, management, and equipment constraints faced by actual farmers. In some cases, the on-farm research also serves an extension or outreach goal (similar to the discussion of on-farm demonstrations above).

Since they are normally designed and implemented by scientists, the host farmers may or may not be given much decision-making authority to refine research questions, contribute to research designs, or interpret the data coming from their farms. More commonly, their input is solicited at the testing (as opposed to design) stage of the research and innovation process. There is wide variation in the degree to which on-farm trials have organized mechanisms for structured communication between farmers and scientists. At one end of the spectrum, farmers may simply serve as hosts, but have few formal opportunities for engaging researchers in reviewing the findings. At the other end, farmers may be formally invited to help design the projects up front, provide input on or assist with field management and data collection decisions, and collaboratively engage with scientists in the review and discussion of the results.

Mother-baby trials: One variant of coordinated on-farm research is the Mother–Baby Trials (MBT) approach that has been used extensively in international development contexts (Snapp 2002 ). This approach typically pairs a replicated experimental ‘mother’ trial conducted under controlled conditions on a research experiment station with a set of simpler ‘baby’ trials that are implemented across a network of collaborating farms (Snapp et al. 2018 ). MBT projects typically blend research and empowerment goals. A major objective is to test alternatives under on-farm conditions and to incorporate farmer knowledge and preferences into research design and evaluation (functional–substantive). Some MBT projects also seek to empower farmers to innovate or adapt agricultural innovations to better fit their needs and ensure that development efforts benefit women and smallholder communities (functional–instrumental and empowerment goals).

Advocates for MBT approaches typically embrace an engaged and iterative learning model where farmers are given significant authority and control over the research design and implementation, and interactions between farmers and scientists take place through multiple iterative cycles of research where the trajectory of the research is refined and adjusted. Decision-making authority is typically shared (collaborative). Significant effort is devoted to organizing communication (e.g., through farmer trainings and meetings) that focus on two-way exchange of information (participatory modes).

Discovery Farms : In the early 2000s, extension personnel at the University of Wisconsin launched a collaborative on-farm research project to set up edge-of-field monitoring stations to quantify the impact of alternative management practices on water quality outcomes on a handful of Wisconsin farms (Frame 2000 ; Radatz et al. 2018 ; Stuntebeck et al. 2011 ). Research at these ‘Discovery Farms’ has been organized and coordinated by a farmer governing board, which leads the research design, interpretation, and recommendations associated with the work. At least one farmer-only meeting is held each year to review progress.

A major goal of the Wisconsin Discovery Farms (WDF) project is to improve understanding of how best management practices (BMPs) perform under realistic working farm conditions (functional–substantive goal), and to give farmers the ability to adapt or adjust recommended BMPs to better fit their farm operations (functional–instrumental). The WDF program also includes an extension/outreach component and there is also a strong assumption that giving farmers ownership and control over the research will lead to more rapid acceptance of the results and increase the rate of BMP adoption across the state (non-research goals). Farmers are typically engaged early in the design phase of the research and have the authority to overrule scientists when making research design decisions (a collegial mode). There is a well-established structure for organizing interactions between farmers and scientists, and information is exchanged using two-way communication modes.

In the ensuing years, a number of other states established their own Discovery Farm or edge-of-field monitoring networks, though the degree of farmer decision-making control and relative balance of research versus outreach goals seem to vary widely (Awole et al. 2018 ). For example, the Arkansas Discovery Farms (Sharpley et al. 2015 ) gather applied on-farm research data on a number of farms to compare conventional and recommended management practices using a similar paired field design. However, the project is less directly controlled by farmers and farmer participants (e.g., is more consultative than collegial). Similarly, the USDA Agricultural Research Service has installed surface and groundwater monitoring stations in 40 fields on 20 farms as part of an Ohio Edge-of-Field network (Williams et al. 2016 ). Farmers on that project negotiate with the scientists to determine which practices are tested on their farms, but most of the data collection, analysis, and interpretation activities are done by scientists then shared with the farmers. In both cases, the locus of decision-making is more consultative than collegial, and the level and direction of organized communication between farmers and scientists is less formal and more consultative than communicative.

Discovery farm programs generally target ‘representative’ types of farms. The WDF program sought willing and committed partners through a statewide call for cooperators, and selected farms if they represented ‘typical operations and issues’ faced by Wisconsin farmers (Frame, n.d.). The Arkansas DF program sough operations that are ‘reflective of typical farming systems’ (Sharpley et al. 2015 , p.187).

Farmer research networks: One of the longest-running on-farm research networks in the US is coordinated by Practical Farmers of Iowa (PFI), a farmer-led organization established in 1987 (Thompson and Thompson 1990 ). PFI’s goal is to ‘empower farmers to generate and share knowledge through timely and relevant farmer-led research’ (Practical Farmers of Iowa 2021 , p.4). In 2020, 66 cooperator farmers participated in 81 research trials. Research topics and questions are generated by farmers, and research designs are crafted by farmers in consultation with PFI staff scientists. Projects typically involve at least 3 replications across each study field, and two or more treatment comparisons; frequently producers collaborate to reproduce similar trials across their farms. Farmers are responsible for implementing projects and taking measurements throughout the trials, and collectively share and review results and observations at an annual PFI cooperators meeting.

Another example is the Ohio State University eFields program (Ohio State University 2021 ). Led by a group of county extension educators and research scientists, the project matches individual producers with an OSU partner to design and implement relatively simple on-farm trials to compare multiple treatments using principles of randomization and replication. In many cases, research faculty identify a core topic and encourage local extension educators to recruit farmers to replicate the experiment on their farms. In other cases, topics and research questions emerge from discussions between farmers and county educators. Most eFields studies are run for one or two field seasons. Data are analyzed and reports produced by eFields staff. Results are shared in an annual summary report that is distributed in print and digital formats. A similar program has been run in Nebraska for over 20 years (Thompson et al. 2019 ).

A third model can be seen in the use of Farmer Field Schools (FFS) to engage groups of farmers in facilitated and coordinated research and learning programs, particularly around integrated pest management strategies. There is a large literature on the design and impact of FFS projects (Davis 2006 ; Feder et al. 2003 ; Van den Berg and Jiggins 2007 ). FFS projects provide training for farmers to conduct their own research, including research design, analytical skills, and problem solving (Davis et al. 2011 ). Groups of farmers are encouraged to observe and experiment on their farms to develop improved understanding of the functional relationships between pests and crops. Most FFS projects seek to address the needs of smaller and limited resource farmers in developing country contexts and embrace social values such as local agency, equity, and empowerment (Nelson et al. 2019 ).

These examples illustrate the broad range of goals and approaches used in on-farm research networks. Most value the intrinsic epistemological value of the information gleaned from on-farm research (functional–substantive), and nearly all embrace the value of on-farm research as a means to promote the practical use and adoption of new agricultural innovations (non-research). To different degrees, many farmer research networks also seek to empower farmers to take control over the research process and give them skills to answer questions without reliance on scientists. Farmer decision-making authority ranges from consultative to collaborative to collegial. Farmers usually participate in all three stages of the research process (design, testing and diffusion), but the depth of their role varies widely. There are different degrees of formal or organized communication and interactions between farmers and scientists.

2.5 Classifying different PFR approaches

Table 1 presents some of the key differences in goals and approaches that are associated with different types of PFR work. In some cases, it is possible to clearly and consistently identify the core or dominant goals or approaches associated with each type of PFR. In other cases, it would appear that there can be a wide variation in the ways in which the same PFR ‘type’ is implemented by project leaders.

3 Discussion and conclusions

Calls to engage farmers in participatory agricultural research have been common since the 1970s, but the specific approaches used to implement this strategy have varied widely. This diversity of approaches presents a challenge to the systematic study of outcomes associated with engaging farmers in agricultural research. It also reflects some lingering conceptual confusion about which dimensions or choices are most important to consider when designing and implementing PFR projects.

Previous typologies of PFR (and participatory research more generally) have often relied unidimensional linear schema that array projects on a ladder or spectrum that range from low to high levels of participation. While the overall level of power and control given to farmers is indeed a defining feature, it can be helpful to recognize that PFR projects can vary along multiple and independent dimensions, and different combinations of traits are best captured in a multidimensional typology (e.g., Neef and Neubert 2011 , p.182). In this paper, we have attempted to synthesize some of the existing frameworks into a comprehensive but still elegant typology. We encourage the application of our typology as a reflexive tool to guide the design or assessment of participatory agricultural research projects. By making choices about the goals, decision-making authority, timing, communication methods, and selection of participants on PFR projects more explicit, we will be able to learn more from past projects and improve the chances that future efforts can achieve their objectives (Barreteau et al. 2010 , p.15).

In most instances, the combinations of methods used in PFR are linked either explicitly or implicitly to the particular goals or objectives of the organizers. For example, in the international development context, the limitations of conventional research and extension systems to address the needs of small and limited resource farmers were a primary motivation for exploring participatory approaches (Chambers 1997 , p.5). This has led to a strong emphasis on methods that leverage farmers’ tacit and experiential knowledge about local socio-ecological systems (systems knowledge) to improve the science (functional–substantive goals). They also reflect the use of PFR to build the capacity of local farmers to diagnose and address their own problems (empowerment goals). In turn, organizers are more likely to experiment with more radical approaches that give farmers more authority and control at earlier stages in the research process and devote significant resources to facilitating farmer-scientist and peer-to-peer exchange of information.

In the USA, PFR projects often have less transformative goals, with greater emphasis on engaging farmers in later stages of the research process to tweak or adjust the design of technologies (functional–instrumental goals) or that see on-farm research more as a mechanism to promote adoption of recommended management practices (non-research goals) and less as a site for serious knowledge production (Hurst et al. 2022 ). In such cases, we are likely to see more consultative modes occurring later in the research process with less of a focus on organized or facilitated two-way communication.

That said, the choice of any particular PFR approach depends on more than just the motivations of the organizers. As demonstrated by the Agricultural Innovation Systems literature (Hall et al. 2006 ; Hermans et al. 2021 ; Klerkx et al. 2012 ), the broader socioeconomic, cultural, and institutional context can affect the likelihood that particular outcomes will emerge. Some settings will be more conducive to successful participatory processes than others (Cornwall 2008 ; Reed et al. 2018 ). Institutional reward systems for scientists, farmer capacity to devote time to engaging in a participatory research project, and political acceptance of (or resistance to) the empowerment of farmers can all shape the conduct and outcomes of PFR (Barbercheck et al. 2012 , p.96). In addition, awareness of the importance of context should not only shape the design or success of a project, but can also generate efforts to change reward systems, confront inequality, and redistribute power to ensure more effective and successful engagement of farmers in the co-production of knowledge (Ashby and Sperling 1995 ; Bell and Reed 2021 , p.6; Whitton and Carmichael 2022 ).

The configuration of approaches may also be fluid over the life of a single project, and the motivations for participation may evolve for farmers and scientists over time (Reed et al. 2018 ). As such, expecting and designing flexibility into a PFR project could help ensure that the program can adapt to changes in goals, shared understanding, and socioeconomic and political contexts (Douthwaite and Hoffecker 2017 , p.87).

To the extent that PFR is designed to generate useful knowledge of farming systems and to identify innovative management practices that can advance farmer and societal goals (Wiek et al. 2014 ), the epistemological status of farmer knowledge and alternative research designs is likely to be a source of tension. Scientists often question whether or not meaningful participatory on-farm research can be done without randomization and replication of treatments, and the use of experimental controls (Lilja and Bellon 2008 , p.481). Some have worked to adapt formal scientific research designs to be more practical in an on-farm research context (Taylor 1991 ; PFI 2021). Others celebrate the more holistic and situated knowledge held by farmers, and question whether imposition of reductionistic research scientific methods is necessary (or even desirable) on participatory research projects for knowledge co-production, especially in research networks (Bidwell 2009 , p.745; Hurst et al. 2022 ). In any case, the enduring tension between rigor and relevance is likely to impact the evolution of PFR methodologies for years to come (Lawrence et al. 2007 , p.163). Lessons from the large and expanding literatures on transdisciplinarity, post-normal science, and community-based participatory action research (CBPAR) provide a wealth of guidance on how best to negotiate these bumpy roads (Barreteau et al. 2010 ; Bell and Reed 2021 ; Funtowitcz and Ravetz 1993 ; (Maida 2009 ; Nowotny et al. 2001 ; Pohl and Hadron 2008 ; Smetschka & Gaube 2020 ; Stringer 2007 ; Turnpenny et al. 2011 ; Wallerstein and Duran 2010 ).

In this paper, we have drawn from a large and diverse literature on participatory farmer research to outline a practical typology to guide the design, implementation, and evaluation of PFR projects. Based on our work in both US and European contexts, we believe that there remains considerable variation in the ways that practitioners use the terms ‘on-farm research’ and ‘participatory farmer research.’ It is our expectation that this typology can help clarify differences across projects and ensure that the design of PFR methods is appropriate to achieve the specific goals of the project. Moreover, we hope that the typology will provoke some deeper reflection about the possible motivations and applications of PFR among scientists (and non-scientists) who have a general interest in the idea, but have not had the opportunity to read widely in this literature. This includes asking hard questions about what level of farmer involvement they are prepared to support, the level of control and power that farmers are given, the types of communication they use, and the ways in which they recruit different types of farmers to participate in PFR projects. We hope that these reflections will provide greater opportunities for deeper levels of engagement with farmers in on-farm research projects and create pathways to new forms of innovation and discovery that can help a broader range of farmers adapt to future climate, market, and political changes in ways that increase their social, economic, and environmental sustainability (Douthwaite and Hoffecker 2017 ).

Data availability

Not applicable.

Code availability

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Acknowledgements

An earlier version of this paper was developed through an interdisciplinary workshop supported by the Agriculture and Food Research Initiative (AFRI) Advancing Scholarship and Practice of Stakeholder Engagement in Working Landscapes (Grant No. 2020-01551 Project Accession No. 1023309) from the USDA National Institute of Food and Agriculture. Contributions and input from workshop participants are reflected in this final product. Partial funding for the project was also supported by the U.S. National Science Foundation Innovations at the Nexus of Food, Energy, and Water Systems (INFEWS) Grant No. SES-1739909.

Partial funding for this paper was provided by a USDA AFRI grant and a National Science Foundation Grant (see acknowledgements above).

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Jackson-Smith, D., Veisi, H. A typology to guide design and assessment of participatory farming research projects. Socio Ecol Pract Res 5 , 159–174 (2023). https://doi.org/10.1007/s42532-023-00149-7

Received : 16 December 2021

Revised : 28 February 2023

Accepted : 02 March 2023

Published : 07 April 2023

Issue Date : June 2023

DOI : https://doi.org/10.1007/s42532-023-00149-7

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Agricultural research: definition, examples.

Agricultural research is a specialized kind of research system that can be carried out using laboratory and field facilities as well as by interacting with farmers as critical informants for their betterment and raising their day-to-day level of livelihood. Agricultural research is based on crops, livestock, fisheries, forests, and the environment.

Until the 1970s, the primary focus was on crop­based research to meet the growing demand for food grains to feed the millions of people in the global context.

As such, it was known as cropping system research.

Since the 1980s, it has significantly shifted from cropping system to farming system research as a holistic approach encompassing all sectors of food production, such as crops, livestock, fisheries, and forests, including the environment.

What is the primary focus of agricultural research?

Agricultural research is a specialized system that uses both laboratory and field facilities, as well as interactions with farmers, to improve their livelihood and address day-to-day challenges. It encompasses various sectors like crops, livestock, fisheries, forests, and the environment.

How do the researchers anticipate the study’s findings on sustainable farming methods to be beneficial?

The research findings are expected to help identify the best farming methods for environmentally friendly, sustainable agricultural production systems. These insights will be valuable for policymakers at the national level, guiding them in making informed decisions about sustainable agricultural land uses.

How does agricultural research contribute to the betterment of farmers’ livelihoods?

Agricultural research provides critical insights and solutions to farmers, addressing their day-to-day challenges, enhancing productivity, and promoting sustainable practices, ultimately improving their overall livelihood.

Agricultural Research Examples

Here are two examples that demonstrate what agricultural research is:

It is a long-felt demand in the agricultural sector to know the extent of participation of rural households in livestock production activities.

A student of Bangladesh Agricultural University designed a study to identify the type of livestock activities usually undertaken by rural farmers.

The study aimed to assess the labor contribution of males, females, children and paid workers to each identified activity.

Farmers in Bangladesh usually follow traditional farming practices and depend mainly on chemical fertilizers and chemical pesticides for higher yield without or with less application of organic fertilizers/compost/IPM. They usually apply excess dosage of chemical fertilizers and pesticides without understanding soil/plant requirements.

Thus it indicates the consequence of decreasing soil fertility status day by day, which already resulted in <2% organic matter content, whereas it should be maintained at least 5%.

Therefore, to overcome this situation and restore our soil’s plant nutrients, integrated nutrient and pest management through increased use of compost/organic fertilizers/IPM is a crucial need.

Considering this, a study on sustainable agriculture through organic farming and IPM practices in Dinajpur was conducted.

Keeping these issues in view, Uttam Kumar Mojumder and some of his colleagues (2013) designed a study to identify the state of food security and farming practices of small and marginal farmers’ communities to identify the sustainable farming system and suitable farming methods and to demonstrate and promote sustainable farming methods.

As the researchers speculate, the research findings will help to identify the best farming methods and their uses to achieve environmentally friendly, sustainable agricultural production systems.

The policymakers at the national level will get information about the assessment of organic farming, which will help them make suitable decisions concerning sustainable agricultural land uses.

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50 Examples of Applied Research

Applied research is the cornerstone of progress across a multitude of fields, driving innovation and practical solutions to real-world problems. In this article,I explained 50 examples of applied research, each contributing to the betterment of society. These examples showcase the diverse ways in which research is harnessed to create meaningful impact.

Definition of Applied Research

Applied research is the systematic study and exploration of existing knowledge to solve specific, practical problems. It goes beyond theoretical understanding, aiming to provide tangible solutions and improvements in various domains.

Importance of Applied Research

Applied research is instrumental in fostering innovation, improving efficiency, and addressing societal challenges. It bridges the gap between knowledge and application, transforming theories into practical solutions that benefit humanity.

The Scope of Applied Research

This article explores 50 diverse examples of applied research, categorized into various fields, highlighting their significance and impact.

Examples of Applied Research in Medicine

Examples of Applied Research in Medicine are given below:

Drug Development

Applied research in medicine has revolutionized drug development. Through meticulous studies and clinical trials, scientists have developed life-saving medications, from antibiotics to cutting-edge cancer treatments.

Medical Devices

Innovative medical devices, like MRI machines and pacemakers, are outcomes of applied research. Engineers and medical experts collaborate to improve patient care and outcomes through advanced technology.

Clinical Trials

Clinical trials are a vital aspect of applied medical research. They validate the effectiveness and safety of medical interventions, ensuring that new treatments are safe and efficacious before they reach the market.

Examples of Applied Research in Technology

Examples of Applied Research in Technology are given below:

Renewable Energy

Applied research in renewable energy has led to significant breakthroughs in harnessing sustainable power sources. Solar panels, wind turbines, and geothermal systems are now more efficient, reducing the reliance on fossil fuels.

Artificial intelligence is transforming industries with applications in data analysis, automation, and machine learning. Research in AI drives innovation in areas such as autonomous vehicles, healthcare diagnostics, and personalized recommendations.

Cybersecurity

The field of cybersecurity relies on applied research to safeguard digital assets. Researchers continuously develop new encryption techniques, threat detection systems, and security protocols to protect against cyberattacks.

Examples of Applied Research in Environmental Science

Examples of Applied Research in Environmental Science are given below:

Climate Change Mitigation

Applied research addresses climate change through innovative solutions like carbon capture technology, sustainable energy sources, and strategies for reducing greenhouse gas emissions.

Sustainable Agriculture

Research in sustainable agriculture promotes eco-friendly farming practices, optimizing crop yields while minimizing environmental impact. Methods like precision agriculture and organic farming are outcomes of applied research.

Conservation Biology

Applied research in conservation biology aims to protect endangered species and ecosystems. This includes habitat restoration, captive breeding programs, and measures to combat poaching and deforestation.

Examples of Applied Research in Education

Examples of Applied Research in Education are given below:

Curriculum Development

Applied research in education focuses on improving curriculum design, and making learning more effective and engaging. Researchers evaluate teaching methods and materials to enhance student outcomes.

Learning Techniques

Applied research investigates innovative learning techniques and cognitive processes. Adaptive learning platforms and neuroeducation studies are enhancing educational effectiveness.

Educational Technology

EdTech research leads to the development of digital tools and resources, such as online learning platforms and interactive educational apps, which revolutionize how students access information and engage with educational content.

Examples of Applied Research in Business

Examples of Applied Research in Business are given below:

Market Research

Applied research in business informs marketing strategies, product development, and customer satisfaction. Consumer behavior studies and market trend analysis are crucial in decision-making processes.

Product Development

Businesses rely on applied research to create new products or improve existing ones. This may involve consumer feedback, quality assurance, and production efficiency enhancements.

Supply Chain Optimization

Research in supply chain management ensures efficient logistics, reducing costs and minimizing waste. Inventory management systems, route optimization, and demand forecasting are areas of applied research.

Examples of Applied Research in Social Sciences

Examples of Applied Research in Social Sciences are given below:

Public Policy Analysis

Applied research in the social sciences informs public policy decisions. Studies on socioeconomic trends, healthcare access, and education outcomes guide policymakers in creating effective solutions.

Research in criminology focuses on crime prevention and criminal behavior analysis. Applied research is critical in developing effective law enforcement strategies and criminal justice policies.

Psychology Interventions

Applied psychology research leads to interventions that improve mental health and well-being. Therapeutic approaches, behavioral therapy, and counseling techniques are outcomes of this research.

Examples of Applied Research in Engineering

Examples of Applied Research in Engineering are given below:

Infrastructure Development

Engineering research drives infrastructure development. Innovations in civil engineerings, such as bridge design, road construction, and urban planning, improve the quality of life for communities.

Materials Science

Materials science research results in the development of advanced materials for various applications. From aerospace materials to biomedical implants, applied research enhances the performance and durability of products.

Transportation Systems

Transportation research focuses on improving mobility and sustainability. Applied research in transportation engineering leads to innovations in public transit, traffic management, and vehicle design.

Examples of Applied Research in Agriculture

Examples of Applied Research in Agriculture are given below:

Crop Improvement

Applied research in agriculture is essential for developing crop varieties with higher yields, resistance to pests, and better adaptability to changing environmental conditions.

Pest Control

Research in pest control provides sustainable methods to protect crops and reduce the environmental impact of pesticides. Integrated pest management systems are a prime example of applied research.

Soil science research enhances soil health and fertility, critical for agricultural productivity. Applied research leads to soil management techniques that optimize crop growth and minimize soil degradation.

Examples of Applied Research in Space Exploration

Examples of Applied Research in Space Exploration are given below:

Rocket Propulsion

Applied research in space exploration drives rocket propulsion technology, enabling safer and more efficient space travel. Advances in propulsion systems are crucial for missions beyond Earth.

Astronomical Observations

Astronomical research leads to advanced observation techniques and technology. Telescopes, space probes, and data analysis methods help us unravel the mysteries of the cosmos.

Space Medicine

Applied research in space medicine addresses the unique challenges of human health in space. This includes studies on microgravity effects, life support systems, and healthcare protocols for astronauts.

Applied research permeates our lives, from healthcare and technology to the environment and education. The 50 examples presented here are just a glimpse of the remarkable contributions that applied research makes to society. As innovation continues to drive progress, we can anticipate ongoing advancements and a promising future for applied research in addressing the world’s most pressing challenges.

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Agriculture Research

Industrial areas are associated with concentrated pools of personal and economic opportunities. However, urban imagery is misconstrued as the sole concretization of progress. We are abandoning agricultural lands in search of greener pastures in the cement and steel wonderland. We are converting fertile fields into urban projects, gambling our food source, for one. To mitigate future more devastating losses, academic institutes have poured hard work into writing researches in agriculture.

Agriculture research can be either or both qualitative and quantitative research . Agricultural science is not a new idea. It started roughly around the time when man learned he could grow his food. The concept was simple: “Plant A is edible, Plant B is not. Let’s plant more of A.” As humans practiced growing plants and animals for general consumption, we learned better ways to generate a better yield. Soon, we developed tools for the trade: chemicals, machines, and their derivatives that make farming more systematic and efficient.

Why We Research

More than 20,000 years since man’s first attempt at cultivation , yet a lot about agriculture is still an open question. Farming is not just about sowing seeds and reaping fruits. Complex processes occur between the planting and harvesting periods. In the past, farmers rely on trial-and-error methods to find out what works for them. Not having a strong and reliable foundation for our next move could mean our families would be hungry indefinitely. Just producing food wasn’t enough.

Food security

The marriage of agriculture and education allowed better crop management. We increased the yield and nutritional value of plants while making them grow healthier. We saw development in farming methods and innovations based on research and scientific investigations. An in-depth understanding of plant biology allowed for improved food production and reduced damages from pestilence and acts of God.

It is in the genes

Rice is one of the primary agricultural commodities in the world. Rice flowers bloom at a specific period in the morning, at times for two hours, for a few days. In that short time, the plant must be able to pollinate successfully. However, favorable weather will not discount the impact of pests and infections on the plant’s normal life cycle. One of the things that agricultural research scientists in the lab have worked on is tinkering with the genes of different rice varieties to extend or shorten the flowering time and making the plant resistant to fatal infestations and conditions.

Bigger is better

Another feat in the history of agriculture is farmers transforming corn into what it is today. In the past, a starkly different-looking plant would bear small fruits, not unlike the size of our fingers. The early civilization in Mexico did not have the present knowledge and resource about corn’s biology and genetics. It took several thousands of years of selectively cultivating the desirable traits of the plant teosinte into the hearty sized corn cob that we know and love today.

But not always

Not all agriculture research has turned out desirable, however. For years, people have worked on producing a big, juicy variant of red tomatoes. Researchers have tinkered with the genes that influence the size of the fruit. By doing so, they have unintentionally affected the genes that make the tomatoes taste good. Therefore, some big tomatoes today aren’t palatable as the genetic pathway responsible for its distinct sweetness was accidentally altered.

Nevertheless, agricultural science is hard at work on its effort to keep the world fed and healthy. It is unswayed in finding better ways to produce food that meet the demands of the modern world.

Price For Progress

However, it seems that the modern world is the giant goliath of farmers and scientists. Our idea of progress and advancement left out the contribution of agriculture in the past. Not to mention, people now prefer working in offices and establishments. The rise in population, decreasing land area to grow food, and the declining number of people who see farming as a good job to get all threaten our food security.

In urban areas, indoor gardening is gaining momentum. The rising prices of commodities makes growing your food a sensible choice. However, we should note that that small space in your apartment balcony or that small strip of land beside your house can’t feed you and your family forever.

10+ Agriculture Research Examples

If we can’t regain the farm lands or provide support to the dwindling population of farmers, we will face food crisis. We need to intensify agricultural research to prevent global hunger.

1. National Agriculture Research Example

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2. Global Agriculture Research System Example

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3. Agriculture Research in Development Example

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4. Agriculture Investment Research Example

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5. Computer Application in Agriculture Research Example

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6. Standard Agriculture Research Example

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7. Printable Agricultural Research Example

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8. Long Term Agriculture Research Example

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9. Agriculture Assessment Ethics Research Example

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10. Sample Agriculture Research in Development Example

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11. Public Agriculture Research Example

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Getting Started

The following are reminders on how to make writing your agricultural research papers less arduous.

1. Define The Problem

Your first step to any research is identifying the area that you wish to work on. A literature review is a good way to start your case. Reading on updated and recent materials regarding your chosen topic will help you explore the problem and determine its place in the context of society. Is the problem urgent? Is your contribution original? By spotting the gaps in related literature, you can give new information or significantly improve current practices.

2. Write A Proposal

Drafting a research proposal requires the researcher’s familiarity with the chosen topic and thesis design. Reviewers will look into your capacity to perform the study before it is approved. The convincing pledge of skill is found in your literature review. When you are vying for a study grant, you should consider the interests of the institution that you are approaching. Their priorities should be aligned with the goals of your research.

3. The Common Good

Since you are proposing a study in agriculture, you should be aware of the goal of this community. Your expected findings should be beneficial to the farmers and the agricultural sector. The problem should be specific, clear, relevant, and timely. Even if the result will be negative, the study should still have something useful to provide the community. Don’t forget, your research must follow all the ethical guidelines for research.

4. Be Two Steps Ahead

Create a visual roadmap for your research project. Flow charts and research plans are organization tools that will help you a great deal during your entire endeavor. They keep you grounded on the things you have to perform. You can also track your progress the whole time using Gantt charts , and see to it that your goals are achieved. Cover your bases and plan a successful study ahead.

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For example, Theory of Agricultural Ethics and Human Liability (Zamani 2016) is one of the theories that have resulted from basic research in the field of agriculture. Applied agricultural research is a kind of research which its results are used to meet the needs and solve agricultural problems (Shiri et al. 2011; Valizadeh et al. 2018a).

This is an example of applied research that aims to solve environmental problems. Precision Agriculture: Applied research is being conducted in the field of precision agriculture, which involves using technology to optimize crop yields and reduce waste. This includes research on crop sensors, drones, and data analysis.

Fig. 4.3 A classi cation of methods to study agricultural systems. The review results were. synthetized in the method map ( a) that shows the 3 hierarchical levels retained ("method groups ...

Examples include crop yield, weed density, milk production or animal weight gain. Plot: Plots are the basic units of a field research project—the specific-sized areas in which each treatment is applied. Replication: Replication means repeating individual treatment plots within the field research area.

Basic research is, in the main, publicly funded. In the United States, public investment in agricultural research has declined, while applied research has seen a sharp increase 4.Meanwhile ...

US Department of Agriculture. This site is maintained by SARE Outreach for the SARE program and is based upon work supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, under award No. 2021-38640-34723.SARE Outreach operates under cooperative agreements with the University of Maryland to develop and disseminate information about sustainable agriculture.

3.2. Applied research 33. 4. ... and increase crop yields is a good example of output of research. ... In agricultural research, the motives include tackling food .

Examples of the research projects under way around the country are described. Through exploration of the practical experiences, recent findings, and insights of these researchers, the papers and discussions presented in this volume should demonstrate the value of field- and farm-level systems-based research that is designed and conducted with ...

The main characteristics of AISs are expounded, and three recent or on-going practical examples are described. As the use of IS in agriculture is relatively new, and because the approach is being applied to research, dissemination, and the exploitation of commercial market opportunities, the operational issues for IS and IPs are still evolving.

Download Citation | On May 20, 2019, Chris O. Andrew and others published Applied Agricultural Research: Foundations and Methodology | Find, read and cite all the research you need on ResearchGate

Description. This study focuses on applied research as a service to a client with a problem that research can help solve. Because applied research has a definite purpose, there is usually a time constraint, a deadline by which the work must be completed, as well as a limit on the resources the client has available or is willing to use ...

Abstract. Biotechnology is a wide-ranging science that uses modern technologies to construct biological processes, organisms, cells or cellular components. The clinical new instruments, industry, and products developed by biotechnologists are useful in research, agriculture and other major fields. The biotechnology is as ancient as civilization.

Future research directions have been identified to promote the research into sustainable development of nano-enabled agriculture. ... For example, 50-70% of the nitrogen applied by conventional fertilizers is ... noses (e-noses) regarded as artificial intelligent systems and next generation of sensors. They have been frequently applied in ...

Participatory modes of agricultural research have gained significant attention over the last 40 years. While many scholars and practitioners agree that engaging farmers and other stakeholders is a valuable complement to traditional scientific research, there is significant diversity in the goals and approaches used by participatory projects. Building on previous conceptual frameworks on ...

Fundamental and Applied Research in Agriculture: A dichotomy in biology harms both theory and practice. Richard Levins Authors Info & Affiliations. Science. 10 Aug 1973. Vol 181, Issue 4099. pp. 523-524. DOI: 10.1126/science.181.4099.523. PREVIOUS ARTICLE. Welfare Reform 1973: The Social Services Dimension.

About 4 percent of Federal support for research at universities and colleges was for agri-culture ($408 million of $10 billion). Agriculture's future share of Federal resources for science and research may depend on how society judges the benefits of agri-cultural research compared with other public investments.

Applied research is designed to solve practical problems of the modern world rather than to acquire knowledge for knowledge's sake. One might legitimately say that applied research aims to improve human conditions. For example, applied researchers may investigate ways and means to: Improve agricultural crop production;

The Applied Research and Development Program (ARDP) is one of the three program areas under the Crop Protection and Pests Management Program (CPPM) that supports IPM research and extension projects. ARDP supported projects develop new IPM tactics, technologies, practices, and strategies through research (single function), research-led (at least 20% of the funds must be spent on extension ...

Here are two examples that demonstrate what agricultural research is: Example #1. It is a long-felt demand in the agricultural sector to know the extent of participation of rural households in livestock production activities. A student of Bangladesh Agricultural University designed a study to identify the type of livestock activities usually ...

W. N.PATON, Farm Economics Section, Department of Agriculture, Wellington. METHODOLOGY may be defined as systematic knowledge of the best way of setting to work.In the development and progress of the I" sciences methodology has played avery important role.So also in the realm of agricultural research,. methodology is a vital neces-

Examples of Applied Research in Agriculture are given below: Crop Improvement. Applied research in agriculture is essential for developing crop varieties with higher yields, resistance to pests, and better adaptability to changing environmental conditions. Pest Control.

10+ Agriculture Research Examples. If we can't regain the farm lands or provide support to the dwindling population of farmers, we will face food crisis. We need to intensify agricultural research to prevent global hunger. 1. National Agriculture Research Example. ncap.res.in.

Maize residue cover (MRC) is an important parameter to quantify the degree of crop residue cover in the field and its spatial distribution characteristics. It is also a key indicator of conservation tillage. Rapid and accurate estimation of maize residue cover (MRC) and spatial mapping are of great significance to increasing soil organic carbon, reducing wind and water erosion, and maintaining ...

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