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Article Contents

1. introduction, 2. analytical framework, 3. literature search, 5. discussion, 6. conclusion, acknowledgement.

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Research impact assessment in agriculture—A review of approaches and impact areas

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Peter Weißhuhn, Katharina Helming, Johanna Ferretti, Research impact assessment in agriculture—A review of approaches and impact areas, Research Evaluation , Volume 27, Issue 1, January 2018, Pages 36–42, https://doi.org/10.1093/reseval/rvx034

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Research has a role to play in society’s endeavour for sustainable development. This is particularly true for agricultural research, since agriculture is at the nexus between numerous sustainable development goals. Yet, generally accepted methods for linking research outcomes to sustainability impacts are missing. We conducted a review of scientific literature to analyse how impacts of agricultural research were assessed and what types of impacts were covered. A total of 171 papers published between 2008 and 2016 were reviewed. Our analytical framework covered three categories: (1) the assessment level of research (policy, programme, organization, project, technology, or other); (2) the type of assessment method (conceptual, qualitative, or quantitative); and (3) the impact areas (economic, social, environmental, or sustainability). The analysis revealed that most papers (56%) addressed economic impacts, such as cost-effectiveness of research funding or macroeconomic effects. In total, 42% analysed social impacts, like food security or aspects of equity. Very few papers (2%) examined environmental impacts, such as climate effects or ecosystem change. Only one paper considered all three sustainability dimensions. We found a majority of papers assessing research impacts at the level of technologies, particularly for economic impacts. There was a tendency of preferring quantitative methods for economic impacts, and qualitative methods for social impacts. The most striking finding was the ‘blind eye’ towards environmental and sustainability implications in research impact assessments. Efforts have to be made to close this gap and to develop integrated research assessment approaches, such as those available for policy impact assessments.

Research has multiple impacts on society. In the light of the international discourse on grand societal challenges and sustainable development, the debate is reinforced about the role of research on economic growth, societal well-being, and environmental integrity ( 1 ). Research impact assessment (RIA) is a key instrument to exploring this role ( 2 ).

A number of countries have begun using RIA to base decisions for allocation of funding on it, and to justify the value of investments in research to taxpayers ( 3 ). The so-called scientometric assessments with a focus on bibliometric and exploitable results such as patents are the main basis for current RIA practices ( 4–6 ). However, neither academic values of science, based on the assumption of ‘knowledge as progress’, nor market values frameworks (‘profit as progress’) seem adequate for achieving and assessing broader public values ( 7 ). Those approaches do not explicitly acknowledge the contribution of research to solving societal challenges, although they are sufficient to measure scientific excellence ( 8 ) or academic impact.

RIA may however represent a vital element for designing socially responsible research processes with orientation towards responsibility for a sustainable development ( 9 , 10 ). In the past, RIAs occurred to focus on output indicators and on links between science and productivity while hardly exploring the wider societal impacts of science ( 11 ). RIA should entail the consideration of intended and non-intended, positive and negative, and long- and short-term impacts of research ( 12 ). Indeed, there has been a broadening of impact assessments to include, for example, cultural and social returns to society ( 13 ). RIA is conceptually and methodologically not yet sufficiently equipped to capture wider societal implications, though ( 14 ). This is due to the specific challenges associated with RIA, including inter alia unknown time lags between research processes and their impacts ( 15–17 ). Independent from their orientation, RIAs are likely to influence research policies for years to come ( 18 ).

Research on RIA and its potential to cover wider societal impacts has examined assessment methods and approaches in specific fields of research, and in specific research organizations. The European Science Foundation ( 19 ) and Guthrie et al. ( 20 ) provided overviews of a range of methods usable in assessment exercises. They discuss generic methods (e.g. economic analyses, surveys, and case studies) with view to their selection for RIAs. Methods need to fit the objectives of the assessment and the characteristics of the disciplines examined. Econometric methods consider the rate of return over investment ( 21 ), indicators for ‘productive interactions’ between the stakeholders try to capture the social impact of research ( 22 ), and case study-based approaches map the ‘public values’ of research programmes ( 8 , 23 ). No approach is generally favourable over another, while challenges exist in understanding which impact areas are relevant in what contexts. Penfield et al. ( 6 ) looked at the different methods and frameworks employed in assessment approaches worldwide, with a focus on the UK Research Excellence Framework. They argue that there is a need for RIA approaches based on types of impact rather than research discipline. They point to the need for tools and systems to assist in RIAs and highlight different types of information needed along the output-outcome-impact-chain to provide for a comprehensive assessment. In the field of public health research, a minority of RIAs exhibit a wider scope on impacts, and these studies highlight the relevance of case studies ( 24 ). However, case studies often rely on principal investigator interviews and/or peer review, not taking into account the views of end users. Evaluation practices in environment-related research organizations tend to focus on research uptake and management processes, but partially show a broader scope and longer-term outcomes. Establishing attribution of environmental research to different types of impacts was identified to be a key challenge ( 25 ). Other authors tested impact frameworks or impact patterns in disciplinary public research organizations. For example, Gaunand et al. ( 26 ) analysed an internal database of the French Agricultural research organization INRA with 1,048 entries to identify seven impact areas, with five going beyond traditional types of impacts (e.g. conservation of natural resources or scientific advice). Besides, for the case of agricultural research, no systematic review of RIA methods exists in the academic literature that would allow for an overview of available approaches covering different impact areas of research.

Against this background, the objective of this study was to review in how far RIAs of agricultural research capture wider societal implications. We understand agricultural research as being a prime example for the consideration of wider research impacts. This is because agriculture is a sector which has direct and severe implications for a range of the UN Sustainable Development Goals. It has a strong practice orientation and is just beginning to develop a common understanding of innovation processes ( 27 ).

The analysis of the identified literature on agricultural RIA (for details, see next section ‘Literature search’) built on a framework from a preliminary study presented at the ImpAR Conference 2015 ( 28 ). It was based on three categories to explore the impact areas that were addressed and the design of RIA. In particular, the analytical framework consisted of: ( 1 ) the assessment level of research; ( 2 ) the type of assessment method; and ( 3 ) the impact areas covered. On the side, we additionally explored the time dimension of RIA, i.e. whether the assessment was done ex ante or ex post (see Fig. 1 ).

Analytical framework for the review of non-scientometric impact assessment literature of agricultural research.

Agricultural research and the ramifications following from that refer to different levels of assessment (or levels of evaluation, ( 29 )). We defined six assessment levels that can be the subject of a RIA: policy, programme, organization, project, technology, and other. The assessment level of the RIA is a relevant category, since it shapes the approach to the RIA (e.g. the impact chain of a research project differs to that at policy level). The assessment level was clearly stated in all of the analysed papers and in no case more than one assessment level was addressed. Articles were assigned to the policy level, if a certain public technology policy ( 30 ) or science policy, implemented by governments to directly or indirectly affect the conduct of science, was considered. Exemplary topics are research funding, transfer of research results to application, or contribution to economic development. Research programmes were understood as instruments that are adopted by government departments, or other organizational entities to implement research policies and fund research activities in a specific research field (e.g. programmes to promote research on a certain crop or cultivation technique). Articles dealing with the organizational level assess the impact of research activities of a specific research organization. The term research organization comprises public or private research institutes, associations, networks, or partnerships (e.g. the Consultative Group on International Agricultural Research (CGIAR) and its research centres). A research project is the level at which research is actually carried out, e.g. as part of a research programme. The assessment of a research project would consider the impacts of the whole project, from planning through implementation to evaluation instead of focusing on a specific project output, like a certain agricultural innovation. The technology level was considered to be complementary to the other assessment levels of research and comprises studies with a strong focus on specific agricultural machinery or other agricultural innovation such as new crops or crop rotations, fertilizer applications, pest control, or tillage practices, irrespective of the agricultural system (e.g. smallholder or high-technology farming, or organic, integrated, or conventional farming). The category ‘other’ included one article addressing RIA at the level of individual researchers (see ( 31 )).

We categorized the impact areas along the three dimensions of sustainable development by drawing upon the European Commission’s impact assessment guidelines (cf. ( 32 )). The guidelines entail a list of 7 environmental impacts, such as natural resource use, climate change, or aspects of nature conservation; 12 social impacts, such as employment and working conditions, security, education, or aspects of equity; and 10 economic impacts, including business competitiveness, increased trade, and several macroeconomic aspects. The European Commission’s impact assessment guidelines were used as a classification framework because it is one of the most advanced impact assessment frameworks established until to date ( 33 ). In addition, we opened a separate category for those articles exploring joint impacts on the three sustainability dimensions. Few articles addressed impacts in two sustainability dimensions which we assigned to the dominating impact area.

To categorize the type of RIA method, we distinguished between conceptual, qualitative, and quantitative. Conceptual analyses include the development of frameworks or concepts for measuring impacts of agricultural research (e.g. tracking of innovation pathways or the identification of barriers and supporting factors for impact generation). Qualitative and quantitative methods were identified by the use of qualitative data or quantitative data, respectively (cf. ( 34–36 )). Qualitative data can be scaled nominally or ordinally. It is generated by interviews, questionnaires, surveys or choice experiments to gauge stakeholder attitudes to new technologies, their willingness to pay, and their preference for adoption measures. The generation of quantitative data involves a numeric measurement in a standardized way. Such data are on a metric scale and are often used for modelling. The used categorization is rather simple. We assigned approaches which employed mixed-method approaches according to their dominant method. We preferred this over more sophisticated typologies to achieve a high level of abstraction and because the focus of our analysis was on impact areas rather than methods. However, to show consistencies with existing typologies of impact assessment methods ( 19 , 37 ), we provide an overview of the categorization chosen and give examples of the most relevant types of methods.

To additionally explore the approach of the assessment ( 38 ), the dimensions ex ante and ex post were identified. The two approaches are complementary: whereas ex ante impact assessments are usually conducted for strategic and planning purposes to set priorities, ex post impact assessments serve as accountability validation and control against a baseline. The studies in our sample that employed an ex ante approach to RIA usually made this explicit, while in the majority of ex post impact assessments, this was indicated rather implicitly.

This study was performed as a literature review based on Thomson Reuters Web of Science TM Core Collection, indexed in the Science Citation Index Expanded (SCI-Exp) and the Social Sciences Citation Index (SSCI). The motivation for restricting the analysis to articles from ISI-listed journals was to stay within the boundaries of internationally accepted scientific quality management and worldwide access. The advantages of a search based on Elsevier’s Scopus ® (more journals and alternative publications, and more articles from social and health science covered) would not apply for this literature review, with regard to the drawbacks of an index system based on abstracts instead of citation indexes, which is not as transparent as the Core Collection regarding the database definable by the user. We selected the years of 2008 to mid-2016 for the analysis (numbers last updated on 2 June 2016) . First, because most performance-based funding systems have been introduced since 2000, allowing sufficient time for the RIA approaches to evolve and literature to be published. Secondly, in 2008 two key publications on RIA of agricultural research triggered the topic: Kelley, et al. ( 38 ) published the lessons learned from the Standing Panel on Impact Assessment of CGIAR; Watts, et al. ( 39 ) summarized several central pitfalls of impact assessment concerning agricultural research. We took these publications as a starting point for the literature search. We searched in TOPIC and therefore, the terms had to appear in the title, abstract, author keywords, or keywords plus ® . The search query 1 filtered for agricultural research in relation to research impact. To cover similar expressions, we used science, ‘R&D’, and innovation interchangeably with research, and we searched for assessment, evaluation, criteria, benefit, adoption, or adaptation of research.

We combined the TOPIC search with a less strict search query 2 in TITLE using the same groups of terms, as these searches contained approximately two-thirds non-overlapping papers. Together they consisted of 315 papers. Of these, we reviewed 282 after excluding all document types other than articles and reviews (19 papers were not peer-reviewed journal articles) and all papers not written in English language (14 papers). After going through them, 171 proved to be topic-relevant and were included in the analysis.

Analysis matrix showing the number of reviewed articles, each categorized to an assessment level and an impact area (social, economic, environmental, or all three (sustainability)). Additionally, the type of analytical method (conceptual, quantitative, and qualitative) is itemized

In the agricultural RIA, the core assessment level of the reviewed articles was technology (39%), while the other levels were almost equally represented (with the exception of ‘other’). Generally, most papers (56%) addressed economic research impacts, closely followed by social research impacts (42%); however, only three papers (2%) addressed environmental research impacts and only 1 of 171 papers addressed all three dimensions of sustainable development. Assessments at the level of research policy slightly emphasized social impacts over economic impacts (18 papers, or 58%), whereas assessments at the level of technology clearly focused primarily on economic impacts (46 papers, or 68%).

The methods used for agricultural RIA showed no preference for one method type (see Table 1 ). Approximately 31% of the papers assessed research impacts quantitatively, whereas 37% used qualitative methods. Conceptual considerations on research impact were applied by 32% of the studies. A noticeable high number of qualitative studies were conducted to assess social impacts. At the evaluation level of research policy and research programmes, we found a focus on quantitative methods, if economic impacts were assessed.

Overview on type of methods used for agricultural RIA

a Mix of conceptual and qualitative methods.

b Mix of conceptual, qualitative, and quantitative methods.

Additionally, 37 ex ante studies, compared to 134 ex post studies, revealed that the latter clearly dominated, but no robust relation to any other investigated characteristic was found. Of the three environmental impact studies, none assessed ex ante , while the one study exploring sustainability impacts did. The share of ex ante assessments regarding social impacts was very similar to those regarding economic impacts. Within the assessment levels of research (excluding ‘others’ with only one paper), no notable difference between the shares of ex ante assessments occurred as they ranged between 13 and 28%.

The most relevant outcome of the review analysis was that only 3 of the 171 papers focus on the environmental impacts of agricultural research. This seems surprising because agriculture is dependent on an intact environment. However, this finding is supported by two recent reviews: one from Bennett, et al. ( 40 ) and one from Maredia and Raitzer ( 41 ). Both note that not only international agricultural research in general but also research on natural resource management shows a lack regarding large-scale assessments of environmental impacts. The CGIAR also recognized the necessity to deepen the understanding of the environmental impacts of its work because RIAs had largely ignored environmental benefits ( 42 ).

A few papers explicitly include environmental impacts of research in addition to their main focus. Raitzer and Maredia ( 43 ) address water depletion, greenhouse gas emissions, and landscape effects; however, their overall focus is on poverty reduction. Ajayi et al. ( 44 ) report the improvement of soil physical properties and soil biodiversity from introducing fertilizer trees but predominantly measure economic and social effects. Cavallo, et al. ( 45 ) investigate users’ attitudes towards the environmental impact of agricultural tractors (considered as technological innovation) but do not measure the environmental impact. Briones, et al. ( 46 ) configure an environmental ‘modification’ of economic surplus analysis, but they do not prioritize environmental impacts.

Of course, the environmental impacts of agricultural practices were the topic of many studies in recent decades, such as Kyllmar, et al. ( 47 ), Skinner, et al. ( 48 ), Van der Werf and Petit ( 49 ), among many others. However, we found very little evidence for the impact of agricultural research on the environment. A study on environmental management systems that examined technology adoption rates though not the environmental impacts is exemplarily for this ( 50 ). One possible explanation is based on the observation made by Morris, et al. ( 51 ) and Watts, et al. ( 39 ). They see impact assessments tending to accentuate the success stories because studies are often commissioned strategically as to demonstrate a certain outcome. This would mean to avoid carving out negative environmental impacts that conflict with, when indicated, the positive economic or societal impacts of the assessed research activity. In analogy to policy impact assessments, this points to the need of incentives to equally explore intended and unintended, expected and non-expected impacts from scratch ( 52 ). From those tasked with an RIA, this again requires an open attitude in ‘doing RIA’ and towards the findings of their RIA.

Another possible explanation was given by Bennett, et al. ( 40 ): a lack of skills in ecology or environmental economics to cope with the technically complex and data-intensive integration of environmental impacts. Although such a lack of skills or data could also apply to social and economic impacts, continuous monitoring of environmental data related to agricultural practices is particularly scarce. A third possible explanation is a conceptual oversight, as environmental impacts may be thought to be covered by the plenty of environmental impact assessments of agricultural activities itself.

The impression of a ‘blind eye’ on the environment in agricultural RIA may change when publications beyond Web of Science TM Core Collection are considered ( 53 ) or sources other than peer-reviewed journal articles are analysed (e.g. reports; conference proceedings). See, for example, Kelley, et al. ( 38 ), Maredia and Pingali ( 54 ), or FAO ( 55 ). Additionally, scientific publications of the highest quality standard (indicated by reviews and articles being listed in the Web of Science TM Core Collection) seem to not yet reflect experiences and advancements from assessment applications on research and innovation policy that usually include the environmental impact ( 56 ).

Since their beginnings, RIAs have begun to move away from narrow exercises concerned with economic impacts ( 11 ) and expanded their scope to social impacts. However, we only found one sustainability approach in our review that would cover all three impact areas of agricultural research (see ( 57 )). In contrast, progressive approaches to policy impact assessment largely attempt to cover the full range of environmental, social, and economic impacts of policy ( 33 , 58 ). RIAs may learn from them.

Additionally, the focus of agricultural research on technological innovation seems evident. Although the word innovation is sometimes still used for new technology (as in ‘diffusion of innovations’), it is increasingly used for the process of technical and institutional change at the farm level and higher levels of impact. Technology production increasingly is embedded in innovation systems ( 59 ).

The review revealed a diversity of methods (see Table 2 ) applied in impact assessments of agricultural research. In the early phases of RIA, the methods drawn from agricultural economics were considered as good standard for an impact assessment of international agricultural research ( 39 ). However, quantitative methods most often address economic impacts. In addition, the reliability of assessments based on econometric models is often disputed because of strong relationships between modelling assumptions and respective results.

Regarding environmental (or sustainability) impacts of agricultural research, the portfolio of assessment methods could be extended by learning from RIAs in other impact areas. In our literature sample, only review, framework development (e.g. key barrier typologies, environmental costing, or payments for ecosystem services), life-cycle assessment, and semi-structured interviews were used for environmental impacts of agricultural research.

In total, 42 of the 171 analysed papers assessed the impact of participatory research. A co-management of public research acknowledges the influence of the surrounding ecological, social, and political system and allows different types of stakeholder knowledge to shape innovation ( 60 ). Schut, et al. ( 36 ) conceptualize an agricultural innovation support system, which considers multi-stakeholder dynamics next to multilevel interactions within the agricultural system and multiple dimensions of the agricultural problem. Another type of participation in RIAs is the involvement of stakeholders to the evaluation process. A comparatively low number of six papers considered participatory evaluation of research impact, of them three in combination with impact assessment of participatory research.

Approximately 22% of the articles in our sample on agricultural research reported that they conducted their assessments ex ante , but most studies were ex post assessments. Watts, et al. ( 39 ) considered ex ante impact assessment to be more instructive than ex post assessment because it can directly guide the design of research towards maximizing beneficial impacts. This is particularly true when an ex ante assessment is conducted as a comparative assessment comprising a set of alternative options ( 61 ).

Many authors of the studies analysed were not explicit about the time frames considered in their ex post studies. The potential latency of impacts from research points to the need for ex post (and ex ante) studies to account for and analyse longer time periods, either considering ‘decades’ ( 62 , 63 ) or a lag distribution covering up to 50 years, with a peak approximately in the middle of the impact period ( 64 ). This finding is in line with the perspective of impact assessments as an ongoing process throughout a project’s life cycle and not as a one-off process at the end ( 51 ). Nevertheless, ex post assessments are an important component of a comprehensive evaluation package, which includes ex ante impact assessment, impact pathway analysis, programme peer reviews, performance monitoring and evaluation, and process evaluations, among others ( 38 ).

RIA is conceptually and methodologically not yet sufficiently equipped to capture wider societal implications, though ( 14 ). This is due to the specific challenges associated with RIA, including inter alia unknown time lags between research processes and their impacts ( 15–17 ). Independent from their orientation, RIAs are likely to influence research policies for years to come ( 18 ).

However, in the cases in which a RIA is carried out, an increase in the positive impacts (or avoidance of negative impacts) of agricultural research does not follow automatically. Lilja and Dixon ( 65 ) state the following methodological reasons for the missing impact of impact studies: no accountability with internal learning, no developed scaling out, the overlap of monitoring and evaluation and impact assessment, the intrinsic nature of functional and empowering farmer participation, the persistent lack of widespread attention to gender, and the operational and political complexity of multi-stakeholder impact assessment. In contrast, a desired impact of research could be reached or boosted by specific measures without making an impact assessment at all. Kristjanson, et al. ( 66 ), for example, proposed seven framework conditions for agricultural research to bridge the gap between scientific knowledge and action towards sustainable development. RIA should develop into process-oriented evaluations, in contrast to outcome-oriented evaluation ( 67 ), for addressing the intended kind of impacts, the scope of assessment, and for choosing the appropriate assessment method ( 19 ).

This review aimed at providing an overview of impact assessment activities reported in academic agricultural literature with regard to their coverage of impact areas and type of assessment method used. We found a remarkable body of non-scientometric RIA at all evaluation levels of agricultural research but a major interest in economic impacts of new agricultural technologies. These are closely followed by an interest in social impacts at multiple assessments levels that usually focus on food security and poverty reduction and rely slightly more on qualitative assessment methods. In contrast, the assessment of the environmental impacts of agricultural research or comprehensive sustainability assessments was exceptionally limited. They may have been systematically overlooked in the past, for the reason of expected negative results, thought to be covered by other impact studies or methodological challenges. RIA could learn from user-oriented policy impact assessments that usually include environmental impacts. Frameworks for RIA should avoid narrowing the assessment focus and instead considering intended and unintended impacts in several impact areas equally. It seems fruitful to invest in assessment teams’ environmental analytic skills and to expand several of the already developed methods for economic or social impact to the environmental impacts. Only then, the complex and comprehensive contribution of agricultural research to sustainable development can be revealed.

The authors would like to thank Jana Rumler and Claus Dalchow for their support in the Web of Science analysis and Melanie Gutschker for her support in the quantitative literature analysis.

This work was supported by the project LIAISE (Linking Impact Assessment to Sustainability Expertise, www.liaisenoe.eu ), which was funded by Framework Programme 7 of the European Commission and co-funded by the Leibniz-Centre for Agricultural Landscape Research. The research was further inspired and supported by funding from the ‘Guidelines for Sustainability Management’ project for non-university research institutes in Germany (‘Leitfaden Nachhaltigkeitsmanagement’, BMBF grant 311 number 13NKE003A).

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Research and Science

From fostering continued economic growth to adapting to the effects of climate change and addressing food security, the United States can continue to be a leader in global agriculture. Each day, the work of USDA scientists and researchers touches the lives of all Americans - from the farm field to the kitchen table and from the air we breathe to the energy that powers our country.

The challenges facing agriculture, natural resources, and conservation are immense and can be addressed through robust research enterprise and educational programs. USDA intramural and extramural science helps to protect, secure, and improve our food, agricultural and natural resources systems.

USDA Science and Research Strategy, 2023-2026: Cultivating Scientific Innovation

The “ USDA Science and Research Strategy, 2023-2026: Cultivating Scientific Innovation (PDF, 21.4 MB)” presents a near-term vision for transforming U.S. agriculture through science and innovation, and outlines USDA’s highest scientific priorities. The S&RS is a call to action for USDA partners, stakeholders, and customers to join the conversation and help identify innovative research strategies that lead to real-world, practical solutions that help farmers, producers, and communities thrive.

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USDA Science and Research Strategy

AGARDA: A Vision for Disruptive Science to Confront Audacious Challenges

Agriculture Advanced Research and Development Authority (AGARDA) Implementation Strategy (PDF, 1.8 MB) is a framework outlining a new approach for delivering disruptive breakthrough discoveries for agriculture.

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• Global Food Supply and Security
• Climate and Energy Needs
• Sustainable Use of Natural Resources
• Nutrition and Childhood Obesity
• Food Safety
• Education and Science Literacy
• Rural-urban Interdependence/Rural Prosperity

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An additional focus is to establish more sustainable systems that enhance crop and animal health. Our scientists and university partners have revealed the genetic blueprints of a host of plants and animals including the genomes of apples, pigs, and turkeys, and in 2012, they furthered understanding of the tomato, bean, wheat and barley genomes -- key drivers in developing the resilience of those crops to feed growing populations.

NASS has developed animated U.S. crop progress and topsoil moisture maps , along with other resources, to help experts assess farmland data. USDA researchers also created the Maize Genome Database, an important tool to help farmers improve traits in a crop vital to the world. Meeting growing global demand for food, fiber, and biofuel requires robust investment in agricultural research and development (R&D) from both public and private sectors. USDA is a leader in remote sensing and mapping to visualize data in support of agricultural policy and business decision making as well as program operation. We ranked first worldwide among research institutions publishing on priority diseases in animal health including salmonellosis, avian influenza , mycobacterial disease, coccidiosis, campylobacterosis, mastitis and others.

USDA conducts and supports science that informs decisions and policies contributing to a safe food supply and the reduction of foodborne hazards. Our scientists found the primary site where the virus that causes foot-and-mouth disease begins infection in cattle and developed an improved vaccine against the disease. They are also working on new strategies to control mites and other major honey bee problems such as colony collapse disorder .

Improving Nutrition and Confronting Obesity

USDA builds the evidence base for food-based and physical activity strategies and develops effective education activities to promote health and reduce malnutrition and obesity in children and high-risk populations. For example, ARS evaluated school characteristics associated with healthier or less healthy food preparation practices and offerings and found that the school nutrition environment could be improved by requiring food service managers to hold nutrition-related college degrees, pass a food service training program, and by participating in a school-based nutrition program such as USDA Team Nutrition .

USDA-supported science is investigating the causes of childhood obesity so that our country can address the epidemic. In these efforts, USDA supports nutrition education programs and encourages Americans to consume more nutritious foods like fruits and vegetables. Our scientists are part of an international team that has found a way to boost the nutritional value of broccoli, tomatoes and corn, and have worked to find ways to bolster the nutritional content of other staple crops like oats and rice. USDA research has supported these efforts, showing how healthy foods can often cost less than foods that are high in saturated fat, added sugar and/or sodium.

In 2013, USDA updated the national assessment of urban and rural food deserts - low-income areas with limited access to affordable and nutritious food - and provided information on the socioeconomic and demographic characteristics that distinguish food deserts from other areas, for decision-makers and stakeholders concerned about access to healthy foods.

Conserving Natural Resources and Combating Climate Change

USDA develops and delivers science-based knowledge that empowers farmers, foresters, ranchers, landowners, resource managers, policymakers, and Federal agencies to manage the risks, challenges, and opportunities of climate variability, and that informs decision-making and improves practices in environmental conservation.

Our scientists are developing rice and corn crops that are drought- and flood-resistant and helping to improve the productivity of soil, as well as production systems that require increasing smaller amounts of pesticides or none at all.

Vegetation indices contained in VegScape have proven useful for assessing crop condition and identifying the aerial extent of floods, drought, major weather anomalies, and vulnerabilities of early/late season crops. This tool allows users to monitor and track weather anomalies' effects on crops in near real time and compare this information to historical data on localized levels or across States.

Additionally, our researchers have examined the potential impacts of a suite of climate scenarios on U.S. crop production. Studies like these will help policymakers, farmers, industry leaders and others better understand and adapt to a changing climate on America's crop production.

Our researchers created i-Tree , urban forest management software to help cities understand the value of urban trees through carbon sequestration, erosion protection, energy conservation and water filtration, and since 2009 have continued building on the success of the tool and expanding its use. Our scientists are conducting research on uses of wood, helping companies meet green building design standards and creating jobs using forest products. We have also worked with Major League Baseball to reduce the occurrence of broken baseball bats.

USDA supports families managing through tough economic times by helping residents save energy at home and conserve water, with a program run by Cooperative Extension and our land-grant university partners. Cooperative Extension-affiliated volunteer monitoring programs have engaged citizens in water monitoring to better understand the effects of climate change and/or aquatic invasive species on local waters. Collectively, these programs interacted with hundreds of local, State, and Federal partners. The programs help citizens detect the presence of invasive species and harmful algal blooms.

Science Education and Extension

USDA recognizes the importance of recruiting, cultivating, and developing the next generation of scientists, leaders, and a highly skilled workforce for food, agriculture, natural resources, forestry, environmental systems, and life sciences.

The NIFA interagency agreement with the U.S. Fish and Wildlife Service leverages technology and innovation and involves youth in STEM outreach and exposure. Youth participants developed science process skills related to using GIS and research design, analyzing and interpreting data, and reporting findings to the community which has enabled them to become better consumers of science and citizens capable of making wise STEM policy choices.

USDA strives to provide effective research, education, and extension activities that inform public and private decision-making in support of rural and community development . NASS holds outreach events throughout the Census cycle with underserved and minority and disadvantaged farming groups to promote participation in the Census of Agriculture . With funding and support from NIFA, many Tribal Colleges are offering Reservation citizens training ranging from basic financial literacy to business start-up and marketing information so that families not only survive, but thrive.

In addition, the ERS Atlas of Rural and Small Town America brings together over 80 demographic, economic, and agricultural statistics for every county in all 50 states and assembles statistics in four broad categories -- people, jobs, agriculture, and geography.

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Farmers’ transition to climate-smart agriculture: a systematic review of the decision-making factors affecting adoption.

1. Introduction

2. materials and methods, 2.1. study selection, 2.2. screening process, 2.3. data extraction and analysis, 3.1. study characteristics, 3.2. determinants of farmer adoption of csa practices, 3.2.1. socio-demographic factors, 3.2.2. psychological factors, 3.2.3. farm characteristics, 3.2.4. biotic/abiotic factors, 3.2.5. characteristics of the practice/technology, 3.2.6. systemic factors, 3.2.7. policy factors, 4. discussion, 5. conclusions, supplementary materials, author contributions, conflicts of interest.

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Gemtou, M.; Kakkavou, K.; Anastasiou, E.; Fountas, S.; Pedersen, S.M.; Isakhanyan, G.; Erekalo, K.T.; Pazos-Vidal, S. Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption. Sustainability 2024 , 16 , 2828. https://doi.org/10.3390/su16072828

Gemtou M, Kakkavou K, Anastasiou E, Fountas S, Pedersen SM, Isakhanyan G, Erekalo KT, Pazos-Vidal S. Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption. Sustainability . 2024; 16(7):2828. https://doi.org/10.3390/su16072828

Gemtou, Marilena, Konstantina Kakkavou, Evangelos Anastasiou, Spyros Fountas, Soren Marcus Pedersen, Gohar Isakhanyan, Kassa Tarekegn Erekalo, and Serafin Pazos-Vidal. 2024. "Farmers’ Transition to Climate-Smart Agriculture: A Systematic Review of the Decision-Making Factors Affecting Adoption" Sustainability 16, no. 7: 2828. https://doi.org/10.3390/su16072828

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Toward Sustainable Agricultural Systems in the 21st Century

In the last 20 years, there has been a remarkable emergence of innovations and technological advances that are generating promising changes and opportunities for sustainable agriculture, yet at the same time the agricultural sector worldwide faces numerous daunting challenges. Not only is the agricultural sector expected to produce adequate food, fiber, and feed, and contribute to biofuels to meet the needs of a rising global population, it is expected to do so under increasingly scarce natural resources and climate change. Growing awareness of the unintended impacts associated with some agricultural production practices has led to heightened societal expectations for improved environmental, community, labor, and animal welfare standards in agriculture.

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• Published: 02 January 2024

Scale up urban agriculture to leverage transformative food systems change, advance social–ecological resilience and improve sustainability

• Jiangxiao Qiu   ORCID: orcid.org/0000-0002-3741-5213 1 , 2 ,
• Hui Zhao   ORCID: orcid.org/0000-0003-1414-3443 1 , 2 ,
• Ni-Bin Chang 3 ,
• Chloe B. Wardropper   ORCID: orcid.org/0000-0002-0652-2315 4 ,
• Catherine Campbell   ORCID: orcid.org/0000-0003-1574-3221 5 ,
• Jacopo A. Baggio   ORCID: orcid.org/0000-0002-9616-4143 6 ,
• Zhengfei Guan 7 ,
• Patrice Kohl 8 ,
• Joshua Newell   ORCID: orcid.org/0000-0002-1440-8715 9 &
• Jianguo Wu 10  

Nature Food volume  5 ,  pages 83–92 ( 2024 ) Cite this article

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Scaling up urban agriculture could leverage transformative change, to build and maintain resilient and sustainable urban systems. Current understanding of drivers, processes and pathways for scaling up urban agriculture, however, remains fragmentary and largely siloed in disparate disciplines and sectors. Here we draw on multiple disciplinary domains to present an integrated conceptual framework of urban agriculture and synthesize literature to reveal its social–ecological effects across scales. We demonstrate plausible multi-phase developmental pathways, including dynamics, accelerators and feedback associated with scaling up urban agriculture. Finally, we discuss key considerations for scaling up urban agriculture, including diversity, heterogeneity, connectivity, spatial synergies and trade-offs, nonlinearity, scale and polycentricity. Our framework provides a transdisciplinary roadmap for policy, planning and collaborative engagement to scale up urban agriculture and catalyse transformative change towards more robust urban resilience and sustainability.

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Acknowledgements

This study is funded by the National Science Foundation (ICER-1830036). J.Q. also acknowledges the US Department of Agriculture, National Institute of Food and Agriculture, Research Capacity Fund (FLA-FTL-006277) and McIntire–Stennis (FLA-FTL-006371), and University of Florida School of Natural Resources and Environment for partial financial support of this work.

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School of Forest, Fisheries, and Geomatics Sciences, Fort Lauderdale Research and Education Center, University of Florida, Gainesville, FL, USA

Jiangxiao Qiu & Hui Zhao

School of Natural Resources and Environment, University of Florida, Gainesville, FL, USA

Department of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USA

Ni-Bin Chang

Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA

Chloe B. Wardropper

Department of Family, Youth and Community Sciences, University of Florida, Gainesville, FL, USA

Catherine Campbell

School of Politics, Security, and International Affairs and National Center for Integrated Coastal Research, University of Central Florida, Orlando, FL, USA

Jacopo A. Baggio

Food and Resource Economics Department, Gulf Coast Research and Education Center, University of Florida, Gainesville, FL, USA

Zhengfei Guan

Department of Environmental Studies, College of Environmental Science and Forestry, State University of New York, Syracuse, NY, USA

Patrice Kohl

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Joshua Newell

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J.Q. led the initial conceptualization of this work, and all authors contributed to the development of ideas. J.Q. designed the analyses, developed the visualizations and led the writing of the original draft. H.Z. conducted the literature search and screening of relevant empirical urban agriculture studies. All co-authors contributed to editing and revision of the manuscript.

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Extended data

Extended data fig. 1 schematic diagram to illustrate the concept and spatial scale of the ‘urban regions’, at which urban agriculture is defined..

Urban regions are essentially a large regional landscape encompassing a major central population center, a network of urban centers, and a mosaic of surrounding natural, rural, and production lands with internal heterogeneity and contrasting patterns. Different forms of urban agriculture practices can occur in locales (for example, as shown in arrows) along the spatial gradient of the urban regions.

Extended Data Fig. 2 Nascent real-world examples of scaling up urban agriculture across the globe.

Paris, France (A) has opened one of the world’s largest operating urban rooftop farms to feed its residents and foster climate resilience; New York City, United States (B) boasts the most extensive network of community gardens (>550) to improve food access and life quality of residents and local communities; and Shanghai, China (C) has implemented the masterplans (construction began in 2017) to develop Sunqiao Urban Agriculture District ( ∼ 100 hectare) with numerous large-scale vertical farming systems for feeding burgeoning urban populations and reducing external food dependency.

Extended Data Fig. 3 Dominant urban agriculture types along the infrastructure and technology, and size gradients, with typical commercial (purple colored) and non-commercial (green colored) types.

Size of the boxes is in relative terms, and approximates the common and representative range of each urban agriculture type along these two axes. The location of urban agriculture types along these gradients is determined based on qualitative notions of the authors after the comprehensive review of the contemporary literature, which may evolve over time.

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Qiu, J., Zhao, H., Chang, NB. et al. Scale up urban agriculture to leverage transformative food systems change, advance social–ecological resilience and improve sustainability. Nat Food 5 , 83–92 (2024). https://doi.org/10.1038/s43016-023-00902-x

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Agricultural research methodology

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The objective of this document is to provide a tool to understand aspects and future orientations of agricultural research. It begins with an overview of the concept and/or definition of agricultural research. It then focuses on the role of agricultural research in achieving the goals of 2030 Agenda, different types of agricultural researched, systemic research methodology in agriculture, and finally different kinds of use for agricultural research.

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Research in agriculture and food security: retrospects and prospects

• Fabio G. Santeramo 1  

Agriculture & Food Security volume  13 , Article number:  42 ( 2024 ) Cite this article

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Research in agricultural science has deeply evolved during the past decades, shifting attention from local to global issues, from production functions to market dynamics and equilibrium models, from orthodox economic theories to multidisciplinary frameworks. While evolving, agricultural science has constantly targeted solutions to feed the world [ 1 ]. These tendencies have been parallel to the development of new paradigms for agriculture, moving toward complex agri-food systems inspired to principles of security, resilience, sustainability and inclusiveness [ 2 ], that require technological innovations, financial support, policy interventions, regional and international cooperation and a long run vision [ 3 ].

The complex, multifaceted and multidisciplinary nature of the agri-food systems is also reflected in the dynamic conceptualization of food security. In the late nineties, it has been recognized that thinking about food security has shifted from global and national to household and individual, from a food first perspective to a livelihood perspective, and from objective indicators to subjective perception [ 4 ]. Far from being defined as the condition of a country to have “ access to enough food to meet dietary energy requirements ” [ 5 , p. 5], food security evokes a multidimensional, multilevel, multiactor framework, conceptualized as resting on three [ 6 ], four [ 7 ] or even six pillars [ 8 ].

The “ challenge of feeding 9 billion people ” [ 9 ] is further complicated by novel threats and contests, spanning from climate changes [ 10 ], pandemics [ 11 ], and geopolitical tensions [ 12 ], as well as by the need to face food insecurity in developed economies [ 13 ], where income inequality [ 14 ], food waste [ 15 ], poor nutrient intakes [ 16 , 17 ], and complex value chains [ 18 , 19 ] drive food insecurity in apparently wealthy conditions [ 20 ].

These issues call for a tremendous effort in research to produce evidence-based recommendations and orient entrepreneurs, consumers, and policymakers’ decisions. As one of the leading journals in food security, the pioneering advances in research reported in Agriculture & Food Security have far reaching implications both for the developing world and for developed economies. The Journal has a solid tradition in promoting high-level research within the field of food security research, to foster actions, projects, and interventions for more sustainable, resilient and inclusive agri-food systems. Its mission is to welcome research spanning a large range of relevant academic disciplines, including agricultural, ecological, environmental, nutritional, public health and policy. In its large scope, the Journal welcomes diverse topics, including agricultural and environmental sciences, agricultural and food economics and policy, food technology and innovation, information sciences and decision theory, health economics and policy for food and nutritional security. A renowned and widely representative Editorial Board ensures excellence and guarantees unbiased gender, geographic and topic representation of scholars based in least developing countries, emerging economies and developed countries.

Agriculture & Food Security currently has two ongoing collections pointing at timely research that should be promoted in agricultural science. The Climate and Food Security collection will shape the debate on the climate–agriculture–food security nexus. The rationale behind the collection it straightforward. Being responsible for greenhouse gas emissions, food systems need to be reformed to be inclusive, sustainable and resilient. This transition can be achieved through policy reforms, social innovations, new business models and technological advancements [ 21 , 22 , 23 ]. The collection Building Resilience through Sustainable Food Environments and Diets promotes discussion on sustainable food environments and diets that are healthy, nutritious and secure. It addresses the complex interplay between agricultural practices, environmental sustainability, and food security. The challenge will involve changes in consumers preferences, marketing strategies, and policy legacies, reflected in food claims, sustainability labels, voluntary standards, and so on [ 24 , 25 , 26 ]. With such a terrific agenda, Agriculture & Food Security is committed to continue serving as a platform to host excellent and impactful research that will feed debates and inform decisions: we are committed to serve academics, policymakers and the whole society.

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Injecting manure into growing cover crops can cut pollution, support corn crops

Compared to traditional surface application, injecting dairy farm manure into a live cover crop in early spring reduces ammonia escape, nitrous oxide emissions, soil nitrogen loss.

A research plot after dairy manure slurry was injected into a growing cover crop in early spring when temperatures were cooler, A new study demonstrated that the practice achieved multiple conservation goals while maintaining corn yield.   Credit: Sailesh Sigdel/Penn State . All Rights Reserved .

September 25, 2024

By Jeff Mulhollem

UNIVERSITY PARK, Pa. — Nitrogen in the soil, where plants can readily utilize it, benefits crop growth and health. However, nitrogen leaving the soil — whether through leaching into the groundwater table, flowing with surface runoff into streams or escaping into the air as ammonia or in nitrous oxide emissions — is detrimental to the environment.

Nitrogen management is a concern for dairy farmers, especially those in Pennsylvania and elsewhere in the U.S. Northeast who use manure as a fertilizer and employ no-till agriculture for improved soil health, lower fuel and labor costs, less dust and erosion, and better water conservation.

To better guide these farmers, a team of Penn State agricultural scientists conducted a new study on dairy manure management strategies for ecosystem services in no-till crop systems. In findings recently published in Agronomy Journal , they report a new strategy that achieves multiple conservation goals while maintaining corn yield: injecting manure into a growing cover crop in early spring .

“Applying manure early in the spring synchronized with a growing cover crop, when temperatures are cooler, can reduce ammonia and nitrous oxide emissions compared to later in the spring when temperatures are warmer, and the cover crop has been terminated,” said first author Sailesh Sigdel, a doctoral degree candidate in agricultural and environmental plant science. “This practice offers a potential strategy to simultaneously achieve multiple conservation and agronomic goals.”

Many no-till dairy farmers grow winter crops, such as cereal rye or annual ryegrass and red clover, between corn and forage crops grown for cattle feed, noted research team leader Heather Karsten , associate professor of crop production/ecology in the College of Agricultural Sciences .

“Cover crops are grown to increase soil organic matter and improve soil fertility by capturing excess nutrients after a summer annual crop is harvested,” she said. “They also help prevent soil erosion, limit nutrient runoff, improve soil structure and can even help suppress weeds.”

The surest way to prevent nitrogen loss as ammonia gas and nitrogen-laden runoff is to inject liquid manure below the surface of the ground, Karsten said, explaining this approach is considered a best management practice to lessen agricultural pollution in the troubled Chesapeake Bay watershed , to which Pennsylvania belongs. But it’s not a perfect strategy.

“While manure injection typically conserves ammonia, we also know that conserved nitrogen can contribute to increased emissions of nitrous oxide — a potent greenhouse gas that is contributing to climate change — through a process in the soil known as nitrification and denitrification,” she said. “In 2022, about 75% of U.S. nitrous oxide emissions were from agriculture. So, our research focused on how to reduce those emissions.”

In experiments conducted at Penn State’s Russell E. Larson Agricultural Research Center, the researchers compared four dairy farming scenarios. They evaluated early spring surface broadcasting and liquid dairy manure injection for a growing cover crop, as well as with late-spring applications for a cover crop that was terminated by an herbicide.

“Our study found that when manure was injected into live cover crops in early spring, it reduced nitrous oxide loss by 55% while maintaining yields compared to the current recommended injection practice of applying manure after terminating cover crops before corn planting,” Sigdel said. “This approach offers a potential win-win manure and cover crop management strategy, achieving both agronomic and environmental goals.”

Curtis Dell, with the U.S. Department of Agriculture’s Pasture Systems and Watershed Management Research station at University Park, contributed to the research.

The U.S. Department of Agriculture’s National Institute of Food and Agriculture supported this research. 

Jeff Mulhollem

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A scoping review on technology applications in agricultural extension

1 Department of Agricultural Leadership, Education and Communications, Texas A&M University, College Station, Texas, United States of America

Anjorin Ezekiel Adeyemi

Emily catalan, ashlynn kogut.

2 Department of Teaching, Learning, and Culture, Texas A&M University College, Station, Texas, United States of America

Cristina Guzman

Associated data.

All relevant data for this study is publicly available from the Texas Data Repository ( https://doi.org/10.18738/T8/VNLOTC ).

Agricultural extension plays a crucial role in disseminating knowledge, empowering farmers, and advancing agricultural development. The effectiveness of these roles can be greatly improved by integrating technology. These technologies, often grouped into two categories–agricultural technology and educational technology–work together to yield the best outcomes. While several studies have been conducted using technologies in agricultural extension programs, no previous reviews have solely examined the impact of these technologies in agricultural extension, and this leaves a significant knowledge gap especially for professionals in this field. For this scoping review, we searched the five most relevant, reliable, and comprehensive databases (CAB Abstracts (Ovid), AGRICOLA (EBSCO), ERIC (EBSCO), Education Source (EBSCO), and Web of Science Core Collection) for articles focused on the use of technology for training farmers in agricultural extension settings. Fifty-four studies published between 2000 and 2022 on the use of technology in agricultural extension programs were included in this review. Our findings show that: (1) most studies were conducted in the last seven years (2016–2022) in the field of agronomy, with India being the most frequent country and Africa being the most notable region for the studies; (2) the quantitative research method was the most employed, while most of the included studies used more than one data collection approach; (3) multimedia was the most widely used educational technology, while most of the studies combined more than one agricultural technology such as pest and disease control, crop cultivation and harvesting practices; (4) the impacts of technology in agricultural extension were mostly mixed, while only the educational technology type had a statistically significant effect or impact of the intervention outcome. From an analysis of the results, we identified potential limitations in included studies’ methodology and reporting that should be considered in the future like the need to further analyze the specific interactions between the two technology types and their impacts of some aspects of agricultural extension. We also looked at the characteristics of interventions, the impact of technology on agricultural extension programs, and current and future trends. We emphasized the gaps in the literature that need to be addressed.

1. Introduction

Agricultural extension programs play a crucial role in disseminating knowledge, empowering farmers, and driving agricultural development. From the earliest times, agricultural extension has been noted to traditionally, through the research scientists, develop products and methods which are transferred to the farmers through the extension agents for adoption. The transfer process which was mostly in-person or through radio communications [ 1 ] became largely inadequate to catch up with the expanding population as well as the rapid pace of development. This was further compounded by reduced government funding, uncertainties of the effectiveness of the methods, the extent of the relevance of the knowledge disseminated, and the appropriateness of the models [ 2 ] giving rise to introspection for paradigm shifts in the extension methods and practices. Hence, to enhance the effectiveness of these extension programs, the use of technology such as information and communication technologies (ICTs), digital technologies, farm simulation, and others became very much necessary. Rajkhowa & Qaim [ 3 ] noted that technology application has the potentials for improving the delivery of agricultural extension programs and disseminating agricultural research to farmers and producers since they can lower communication costs, improving smallholder market access and household welfare. By leveraging technology, agricultural extension can overcome geographical barriers, reach a wider audience, and provide access to valuable information and resources, leading to improved farming practices, increased productivity, and enhanced agricultural outcomes [ 4 ].

By exploring the application of technology in agricultural extension programs, this scoping review aims to shed light on the current state of research, identify gaps, and map the overall landscape of this rapidly evolving field. By examining journal articles, conference proceedings, and dissertations, this review specifically describes the outcomes of technology application in agricultural extension under three objectives which are the substantive features, methodological features, and characteristics of technology application in the context of agricultural extension. The findings of this scoping review will provide valuable insights for policymakers who are faced with the decision of expending their resources on the most effective yet economical technology. It can also provide researchers with empirical evidence supporting their decisions when designing adoption and diffusions models for agricultural innovations, as well as practitioners in the field of agricultural extension who will come face-to-face with the users of these innovations. The review will facilitate evidence-based decision-making and inform the development of effective policies and practices by offering an overview of the impact of technology application in agricultural extension. Moreover, it will foster collaboration among stakeholders, encouraging partnerships and knowledge-sharing to drive agricultural development.

Furthermore, the findings of this research will make significant contributions to establish a foundation for future studies. Through this study, we envisage a knowledge synthesis from included studies that could lead to a better understanding of the types, usage and effectiveness of the technology used in agricultural extension. By synthesizing existing knowledge, the review will identify areas where additional research is needed, thereby paving the way for further exploration and discovery. This contribution will advance the application of technology in agricultural extension and shape the future direction of the rapidly evolving field, ultimately leading to improved agricultural outcomes and sustainable development in farming communities worldwide.

2. Literature review

2.1. agricultural extension.

Throughout the history of agricultural extension, there have been a variety of definitions of agricultural extension based on who is involved, the location, and the method used. For example, Msuya et al. [ 5 ] described agricultural extension as a way for small farmers to access new technologies, while Birkhaeuser et al. [ 6 ] viewed it as a common form of public-sector support for spreading knowledge. Rivera et al. [ 7 ] (5) on the other hand explained how agricultural extension serves as a link to increase productivity and efficiency for farmers and researchers and makes it easier to share innovations among farmers. Of all these, however, the most often cited is Maunder’s [ 8 ] comprehensive definition where agricultural extension was defined as “a service or system which assists farm people, through educational procedures, in improving farming methods and techniques, increasing production efficiency and income, bettering their levels of living, and lifting the social and educational standards of rural life.” From these definitions, to achieve its goals, agricultural extension must incorporate key components such as farmers and/or farming households, knowledge diffusion/education, and willingness to change on the part of the farmer.

This scoping review will align with the definition given by Maunder [ 8 ] within the framework that the studies included involve farmers and/or farming households with the aim of mobilizing resources towards their farming objectives.

2.2. Technology application in agricultural extension

The importance of technology in enhancing agricultural productivity cannot be overstated, and agricultural extension plays a crucial role in achieving this objective. Technology, with its innovative tools and applications, has been identified as a game-changer in the agricultural sector [ 9 ]. It has revolutionized farming practices, empowered farmers to increase productivity [ 10 – 12 ], optimized resource utilization [ 13 , 14 ], and addressed sustainability challenges [ 15 – 17 ].

Technology application (TA) in agriculture has been extensively explored from two distinct yet interconnected perspectives. The first viewpoint focuses on the use of technology/innovation as a factor or component of production. Studies falling under this theme investigate aspects such as improved seed varieties [ 18 – 20 ]; farm machinery, including tractors, plows, harvesters, and similar equipment [ 21 , 22 ]; drones, animal trackers [ 23 ] and more recently robots [ 24 ]; and the Internet of Things (IoT) [ 25 ]. These studies perceive these technologies as resources that are consumed or incorporated into the farming system, recognizing that their absence may hinder one or more crucial stages of the production process.

The second perspective regards technology in agriculture primarily as a means of enhancing knowledge transfer and skills development, often referred to as educational technology (ET). These studies, which often focus on technology-enabled information dissemination, training, and capacity building, incorporate technologies such as virtual reality (VR) and augmented reality (AR), Information and Communication Technology (ICT) [ 26 – 29 ], smartphones/mobile applications [ 30 – 32 ], online platforms and websites [ 33 , 34 ], e-learning and webinars [ 35 – 37 ], and social media and online communities [ 38 – 40 ].

In this scoping review, we categorize the TA in agricultural extension into two groups: 1) agricultural technologies/innovations used during production and 2) educational technologies employed for training and facilitating the adoption of these agricultural technologies.

By integrating ET tools such as videos, smartphones, online training, and tablets, agricultural extension services/agents can significantly enhance the effectiveness of information transfer while reducing costs. This approach helps farmers in remote areas easily access timely information, such as weather variables and market factors. Studies have demonstrated the efficacy of these tools, including videos, smartphones, and tablets, in improving agricultural practices among farmers [ 38 – 41 ].

The potential of combining ET and agricultural technology/innovations is highly promising. However, a comprehensive review of previous studies to ascertain the practical outcomes is still lacking. By examining the existing literature, this scoping review aims to bridge the gap in understanding the practical implications of integrating ET and agricultural technology/innovations (ATI). The findings of this study will shed light on the effectiveness and impact of these combined approaches in agricultural extension services.

2.3. Previous studies and research gap

While previous studies have explored agricultural extension and TA separately [ 42 ], there is a lack of examination of the relationship between these two topics. This scoping review aims to address this gap by examining them simultaneously. Existing literature reviews have touched upon related aspects, such as the role of agricultural extension in the transfer and adoption of AT [ 43 ] and the use of ICT for agricultural extension in developing countries [ 44 ]. However, these prior reviews do not fully examine the relationship between agricultural extension and TA. Altalb et al. [ 43 ] highlight the importance of agricultural extension in the development of the agricultural sector and how it aids in transferring necessary knowledge to farmers. Although Altalb et al. [ 43 ] discussed various technologies and innovations in the agricultural sector, their objective was to explore how agricultural extension could transfer that information to the farmers. In contrast, our study focuses on not just information transfer but goes ahead to examine the extension system.

Aker [ 44 ] highlights the need to adopt better AT like fertilizer, seeds, and other farming methods in developing countries and the potential of technology mechanisms, such as voice, text, internet, and mobile phone, to reach farmers and enhance knowledge, ultimately leading to an increase in the economy. However, the study did not delve into the direct TA within agricultural extension; and failed to provide examples or results that demonstrate how technology can be implemented through agricultural extension.

By addressing these gaps and incorporating potential recommendations derived from a comprehensive analysis of previous studies, this scoping review aims to contribute to enhancing productivity and bridging the divide between TA and agricultural extension practices by providing empirical evidence of amongst other things, the impact technology can make in agricultural extension.

3. Research questions

This present scoping review aims to investigate the effect of technology application on agricultural extension by examining existing empirical studies. The study focuses on analyzing the substantive features, methodological features, and characteristics of technology application in the context of agricultural extension. The research questions guiding this study are as follows:

• What are the substantive features of the included studies, including publication information (year of publication and journal name), country/region information, and agricultural field?
• What are the methodological features of the included studies, such as the research methods employed, data collection approaches, and sample size?
• What are the characteristics of the technology used in agricultural extension, including the type of educational technology, agricultural technology, and the overall effect of technology on agricultural extension?

4. Research method

4.1. search strategies.

To comprehensively search for studies, we searched five databases: CAB Abstracts (Ovid), AGRICOLA (EBSCO), ERIC (EBSCO), Education Source (EBSCO), and Web of Science Core Collection. These databases cover literature in the agriculture, applied life sciences, and education disciplines. The database search was developed in CAB Abstracts and run on October 28, 2022. The original search was modified for the additional databases, and the additional databases were searched on November 1, 2022. The search consisted of subject terms and keywords related to the two core concepts of educational technology and agricultural extension. Keywords were searched for in the title and abstract fields. The full search strategies for CAB Abstracts and the other four databases can be found in Appendix A in S2 File .

4.2. Inclusion and exclusion criteria

This scoping review used specific inclusion and exclusion criteria to identify studies examining the impact of technology application on agricultural extension.

• The included studies must have examined the effect of technology application on agricultural extension. Articles were excluded if they were not about technology, were not within the agricultural extension context, and did not examine the effect of technology on agricultural extension.
• Technologies for this study were defined as the educational technology such as multimedia, smartphones, iPads and tablets, digital simulation devices and others used by the agricultural extension services/specialists/agents to facilitate educational training under which knowledge, skills, and content are transferred in the form of agricultural technology/innovations such as seed planting knowledge, disease and pest prevention practices, improved varieties, record keeping and others to the farmers and other stakeholders in an agricultural extension setting. Unless agricultural technology also qualifies as an educational technology (e.g., GPS), such studies were excluded.
• Included studies must have been conducted under the context of agricultural extension programs, which take place in an informal, out-of-school setting; directly involve farmers and/or farming households; and pertain to their farming enterprises.
• Included studies must report detailed information on the effect of technology on agricultural extension, which should include the sample size, experimental design, and detailed results (either quantitative or qualitative). Conference abstracts on this topic will be excluded.
• Included studies must have reported an assessment of technology’s impact/effect on agricultural extension, qualitatively or quantitatively, such as an empirical study (intervention or case studies). Articles that generally discuss the trends or the importance of technology in agricultural extension were excluded.
• The included studies must have been published in a journal, as a conference proceeding, or policy paper from January 1, 2000, to November 1, 2022, and available in English. We selected this period to ensure that we covered the latest studies and documented the rapid progressions of technology in agricultural extension since 2000 [ 45 , 46 ]. Secondary data analysis, literature reviews, book reviews, book chapters, and reports were excluded.

4.3. Coding scheme

To ensure efficient data extraction and analysis, a comprehensive coding system was developed to categorize and organize the information from the included studies. The coding system facilitated the examination of substantive and methodological features of the studies, specifically focusing on the impact of technology application on agricultural extension. Sub-categories were created within the coding system to distinguish between agricultural technologies and educational technologies, enabling a detailed analysis of the key features of each. This coding played a crucial role in understanding and interpreting the findings of the included studies.

4.3.1 Substantive features of the studies

The substantive features of the studies included their publication information, geographic location (country/region), and the included studies’ agricultural field/enterprise concentrations. Our primary objective was to comprehensively analyze publication patterns within the discipline. We aimed to identify journals that had a significant impact based on their titles and publication dates. Furthermore, we sought to compare agricultural extension technology trends across various countries and regions.

We categorized the agricultural fields/enterprises in which educational technologies were predominantly utilized. The coding scheme ( Table 1 ) classified the agricultural fields/enterprise as follows: agricultural economics, including food processing such as making raisins and any value-addition processing; agricultural engineering, including mechanization; agronomy, encompassing crop production and other crop-related enterprises; animal husbandry, incorporating animal production, fisheries, and other livestock-related enterprises; and mixed when the agricultural field/enterprise included more than one.

4.3.2 Methodological features of the studies

The methodological features of the included studies encompassed several aspects, including the research methods employed, data collection approaches, the use of inferential statistics, and units of sample size. These components were examined to gain insights into the study design and methodology employed in investigating the impact of technology on agricultural extension.

The research methods were grouped into quantitative, qualitative, and mixed methods. Quantitative studies used descriptive and inferential statistics, while qualitative studies followed Denzin & Lincoln’s [ 47 ] definition of interpretive practices across different disciplines. We categorized the research methods into quantitative and qualitative because these are the primary categories of educational research. Since studies use both quantitative and qualitative methods, we categorized mixed methods studies as those studies that used both quantitative and qualitative approaches to collect and analyze data.

The data collection approaches included surveys, questionnaires, interviews, focus group discussions (FGD), and assessments. If the study applied more than one data collection approach, it was coded as a mixed method. We also documented whether the researchers employed inferential statistics to examine the impact of educational technology on agricultural extension.

We also considered the sample size units for the selected studies. The sample units were varied, making it difficult to unify the sample sizes. Therefore, we coded the sample size units as households, individuals, and villages, and in studies that used more than one unit, we coded them as mixed.

4.3.3 Characteristics of technology in agricultural extension

We categorized the characteristics of the technology applications used in agricultural extension. The types of educational technologies were coded under the following categories: multimedia (video, audio, photographs, video animation, radio); mobile apps/smartphones; online/web-based; digital simulations; and mixed for those studies that used more than one.

We distinguished between ET and an AT/I were being transferred to the farmers. We categorized the agricultural technology/innovation into various groups: crop cultivation/harvesting practices, product processing, pest and disease control, and knowledge/skill/general agricultural education. The first category was crop cultivation/harvesting practices including spacing and fertilizer application, castor cultivation, cotton production, protection technology, rice intensification system, integrated soil fertility management, soil modules, and sugarcane ratoon management practices. Another category pertained to product processing, specifically the storage of beans in jerrycans. Furthermore, we grouped pest and disease control methods such as the use of neem as an insecticide, disease management, weed control practices, and the management of Fall armyworms. Knowledge/skill/general agricultural education was another category, including topics like insurance advisory, record keeping, knowledge sharing and joint decision making, climate adaptation strategies, and practices. In cases where multiple agricultural technologies/innovations were identified, they were classified under a mixed category.

For characteristics of the intervention, we coded the duration (how long) and the intensity (how often) of the technology intervention as well as the timing of the measurement of the impact /effect. For the duration and intensity of the intervention, we considered how many studies provided the information and reported how they were reported. The interval between intervention and measurement of effect was coded as immediate, short-term, long-term, mixed, and unspecified for those studies that did not clearly state the timing for the measurement. Additionally, we coded whether the use of technologies had a positive, negative, non-significant, or mixed impact and whether the effect sizes were reported.

4.4. Data collection and data analysis

To identify eligible studies, we followed the screening process illustrated in Fig 1 . After removing duplicates, we screened 4,170 unique references for eligibility. The research team screened the article titles and abstracts using the inclusion/exclusion criteria. After the first round of screening, 69.71% (2,808 articles) were excluded. After an initial screening, the authors reviewed the full text of 1,319 articles. Out of these, 61 articles were found to be eligible for inclusion in the review. During the coding process, seven articles were excluded for different reasons. Finally, 54 articles were included in the final coding stage.

The coding scheme was created by the first two authors, who independently coded a set of 20 randomly selected articles. Subsequently, the coding scheme was employed by the first five authors to code the articles using Microsoft Excel. As noted by Belur et al. [ 48 ], the interrater reliability (IRR) of a good systematic review strengthens the transparency and replicability of the process leading to the results from such reviews. Thus, to calibrate the coding, the 54 articles were initially coded independently, resulting in an initial round of IRR of 81.30% which was calculated by the percentage of agreement between the coders. In case of conflicts, the first author acted as the arbiter and resolved the discrepancies. Eventually, a unanimous agreement was achieved regarding the coding of the articles. Descriptive statistical analyses were conducted to address our research questions.

For the data analysis, simple descriptive statistics such as frequencies, percentages, charts, and graphs were used to analyze and present the results for an understanding of the substantive and methodological features of the studies. For the characteristics of technology in agricultural extension, we conducted a crosstabulation and Chi-square analyses of the type of educational and agricultural technology used on the effect/impact of the intervention.

5. Results and discussion

5.1. substantive features of the studies, publication information.

Among the 54 included studies, a noteworthy observation was the concentrated distribution of publications within the past six years (2016–2022). As depicted in Fig 2 , two studies (3.70%) were published from 2001–2005. Six studies (11.11%) were published from 2006 to 2010; eight studies (14.81%) were published from 2011–2015. The majority of publications, comprising 38 studies (70.38%), were published between 2016 and 2022. This trend indicates a significant increase in research activity from 2001 to 2022, with a surge in studies focusing on educational technology after 2016. The rapid development and adoption of various training platforms for farmers accentuated by the global impact of the Covid-19 pandemic, has underscored the pressing need for technology-assisted agricultural extension [ 49 – 51 ].

Out of the 54 studies examined, the majority (n = 49; 90.74%) were published in journals. Policy/discussion papers constituted 7.41% (n = 4) of the studies, while conference papers represented 1.85% (n = 1). Notably, no theses nor dissertations were included in the present scoping review. The absence of such works highlights a potential avenue for graduate students to explore the intersection of educational technology and agricultural extension. Among the journals, 61.22% (n = 30) appeared only once, while the remaining 38.78% (n = 19) published multiple articles included in this review. Details on the number of articles per journal can be found in Table 2 . The journals that published the most papers in the field are: The Journal of Agricultural Education and Extension (JAEE) (n = 4), JIAEE (Journal of International Agricultural and Extension Education) (n = 3), International Journal of Agricultural Sustainability (n = 3), Information Technology for Development (n = 3), International Food Policy Research Institute (n = 3).

Note: *other articles only appear once but in separate journals.

The included studies encompassed a diverse range of countries, with notable concentrations in India, Uganda, Benin, and the U.S.A. Overall, research were conducted in 17 different countries. India accounted for 29.63% (n = 16) of the studies, while Uganda represented 16.67% (n = 9). Both Benin and the U.S.A. had five studies (9.25%) conducted in each country. Kenya accounted for 7.40% (n = 4) of the studies, while Mali, Ethiopia, and Bangladesh each had two studies (3.70%) conducted in each of these countries. The other 16.67% (n = 9) of the studies were conducted in Nigeria, Mozambique, Malawi, Bolivia, Ghana, France, Senegal, China, and Burkina Faso, with one study in each country respectively. The prevalence of studies conducted in the predominantly developing countries (excluding USA), is indicative of the high number of farm families in these regions compared to extension services. Technology therefore plays a crucial role in bridging the gap in effectively reaching a large population of farmers in these areas within a short period [ 52 – 54 ].

The research primarily focused on the regions of Africa, Asia, and North America. Out of 54 studies analyzed, 28 studies (51.85%) were conducted in Africa, while 19 studies (35.19%) were carried out in Asia. Additionally, five studies (9.26%) were conducted in North America, only one study (1.85%) was conducted in South America, and one study (1.85%) was conducted in Europe. Notably, no studies specifically targeted Antarctica or Australia/Oceania. These findings highlight the active contributions of Africa, Asia, and North America to research in the field of educational technology in agricultural extension. However, the dearth of research from Australia/Oceania and Europe in our included studies suggests a need for further investigation in these regions. For instance, Australia/Oceania, renowned for its expertise in animal husbandry due to the combination of large land areas, a substantial livestock population but relatively limited investment in infrastructure and human resources [ 55 ], presents a particularly interesting area for future researchers to explore.

Agricultural field

The majority of the included studies exhibited a strong focus on agronomy. As shown in Fig 3 , 43 studies (79.63%) were centered around agronomy. Additionally, six studies (11.11%) pertained to animal husbandry, three studies (5.56%) involved a mixed focus, and two studies (3.70%) were related to agricultural economics. The imbalance in the distribution of studies suggests a potential opportunity to explore and utilize educational technology in fields such as animal husbandry, agricultural economics and engineering, and other mixed areas. By expanding the application of technology to these underrepresented domains, a more comprehensive and inclusive approach can be adopted within the agricultural extension.

5.2. Methodological features of the studies

Research methods.

The analysis of the research methods employed in the included studies indicated a predominant use of the quantitative research method. Thirty-seven studies (68.52%) utilized the quantitative method, while 14 studies (25.93%) employed a mixed-method approach. Only three studies (5.55%) used the qualitative method. These findings align with a scoping review (authors, under review) on educational technology in agricultural education, which also observed a prevalence of quantitative and mixed methods research as the commonly adopted approaches in this field. The rationale behind the prevalent use quantitative research methods may stem from several factors. Firstly, researchers may have already recognized the importance and advantages of educational technology in the agricultural extension field, largely owing to the extensive body of research on the of educational technology in general education. Consequently, their inclination might have been to substantiate their existing hypotheses within the extension field. It is worth noting that quantitative research often leans towards a confirmatory and deductive approach, in contrast to the more exploratory nature often associated qualitative research [ 56 ]. Additionally, another possible reason for favoring quantitative methods could be attributed to the inherent limitations of qualitative methods. Qualitative findings are typically context-specific and may not readily generalize to a broader population [ 56 ].

We recommended that researchers employ more mixed methods research designs, which combine both quantitative and qualitative approaches, because it offers additional advantages in social science research [ 57 ]. For example, mixed methods research allows researchers to obtain a more comprehensive understanding of complex social phenomena by integrating numerical data with in-depth qualitative insights. The predominant use of mixed research methods in social sciences research is driven by the need for empirical evidence, objectivity, generalizability, and the ability to establish causal relationships and test theories [ 57 , 58 ].

Data collection approaches

The analysis of data collection approaches revealed that mixed approaches were the most utilized among the included studies. Out of the 54 studies, 19 studies (35.19%) used mixed approaches, 13 studies (24.07%) relied on assessments as their primary data collection approach, and 11 studies (20.37%) utilized surveys. Additionally, eight studies (14.81%) used interviews, two studies (3.70%) employed questionnaires, and one study (1.86%) did not specify the data collection method used. This diversity in data collection methods highlights the importance of employing a range of approaches to gather comprehensive and nuanced information within the field of educational technology in agricultural extension.

Inferential statistics

The analysis of inferential statistics showed that a majority of the studies included employed this statistical approach. Among the 54 included studies, 70.37% ( n = 38) of the studies utilized inferential statistics to analyze their data. On the other hand, 29.63% ( n = 16) of the studies did not use inferential statistics in their data analysis. The prevalent use of inferential statistics reflects the researchers’ intention to make inferences and draw broader conclusions about the relationship between educational technology and agricultural extension based on their data.

Unit of sample size

The included studies employed a variety of units for reporting sample size, with individuals being the most prevalent sample size unit. Out of the 54 included studies, 41 studies (75.94%) used individuals as the sample size unit. Additionally, six studies (11.11%) used households, four studies (7.40%) employed mixed units, one study (1.85%) used villages, and two studies (3.70%) did not report the sample size unit. The diversity in sample size units may be attributed to the specific characteristics of the agricultural field and the grouping involved, such as considering households or villages as a whole when studying agricultural practices. In future research endeavors, it would be beneficial to adopt a diverse array of sample size units, given the intricacy and distinctiveness of the agricultural extension field. Furthermore, there is room for investigation into the effectiveness of employing various sample size units. It is worth considering that social interaction within the households, villages, or communities within the group might be a significant factor contributing to the learning outcomes, in addition to individual interactions with technology. To gain a deeper understanding of this aspect, both quantitative or qualitative research approaches can be employed to explore the dynamics of human interaction within a shared learning community in the context of agricultural extension.

Among the 41 studies that employed individuals as the sample size unit, we adhered to the commonly used quantitative research guidelines: studies with less than 100 participants were considered small samples, studies between 100–250 participants were classified as medium samples, and studies with over 250 participants were considered large samples [ 59 , 60 ]. The sample size for studies using individuals as the unit ranged from 6 to 58872 participants. Among these studies, 58.54% ( n = 24) of the studies had a medium sample size, 24.39% ( n = 10) of the studies had a small sample size, and 17.07% ( n = 7) of the studies had a large sample size. Our findings suggest that most studies used a medium sample size when using individuals as the sample size unit. However, specific studies focusing on ET in educational settings suggested a prevalence of small sample size studies (60). This divergence could be attributed to contextual variations, particularly since agricultural extension studies typically involve a larger number of participants.

5.3. Characteristics of technology in agricultural extension

Educational technology.

In our review of 54 studies, we discovered the utilization of various ET in agricultural extension. As shown in Fig 4 , multimedia emerged as the most frequently used ( n = 27, 50.00%), followed by studies that incorporated multiple types ( n = 15, 27.78%). Additionally, mobile apps/smartphones were used in nine studies (16.67%), online/web-based applications in two studies (3.70%), and digital games/simulations in only one study (1.85%).

These findings differ from a similar review conducted on the use of ET in agricultural education by Xu et al. [ 61 ] Among the 83 included studies in their review, they found that the most used ET was online/distance education, followed by simulation/digital games and then, multimedia and traditional technology. This stark contrast may be attributable to the different contexts or settings in which agricultural education and agricultural extension are practiced. Agricultural education primarily takes place within formal educational institutions, involving students, academics, and professionals with higher levels of academic qualifications. On the other hand, agricultural extension often occurs in non-formal settings, predominantly involving farmers who may have varying levels of academic attainment. This is further supported by Mwololo et al.’s [ 62 ] finding that socio-economic factors such as age, education, and gender influenced farmers’ preference for agricultural extension methods, specifically farmers’ field schools (FFS), farmer to farmer (F2F), or mass media. In addition, the role and characteristic of multimedia contributed to the most frequent use as ET for farmers in the extension field. Multimedia plays an important role in agricultural extension serving as the most powerful opinion maker in this information era, and can help transfer agricultural information [ 63 ]. Multimedia is simple, direct, and intuitive in nature thereby making it very comprehensive for farmers who have limited educational level and technology literacy to attain knowledge and skills competency. The majority of our included studies were conducted in Africa and Asia with representative countries like India and Nigeria. In developing countries, farmers’ educational level and current technology literacy remains limited due to the lag of development of the whole country economically, socially and technology and limited funding opportunities/resources for further improvement. Simple and cost-effective ET like multimedia would be preferred compared to complex ones.

Among the various forms of ET used in agricultural extension, video or video-mediated extension emerged as the most prominent. Horner et al. [ 64 ] conducted an experimental study in Ethiopia to assess the effectiveness of video-based extension. They compared traditional agricultural extension methods with the incorporation of videos and found that the latter was more effective in increasing farmers’ knowledge and adoption of complex agricultural technologies such as composting, blended fertilizer, improved seeds, line seeding, and lime. Chowdhury et al. [ 65 ] conducted a study in Bangladesh focusing on enhancing farmers’ capacity for botanical pesticide innovation through video-mediated learning. They observed a significant increase in knowledge about botanical pesticides in both male and female farmers who participated in the video-mediated group. Several other studies [ 38 , 66 – 70 ] have also incorporated video-based multimedia in their agricultural extension programs.

The prevalence of video-mediated extension in agricultural extension programs underscores its effectiveness in delivering information and promoting knowledge acquisition among farmers. By utilizing videos, extension practitioners can visually demonstrate agricultural techniques, showcase best practices, and present success stories, thereby enhancing farmers’ understanding and motivation to adopt agricultural practices. This multimedia approach is particularly beneficial in non-formal settings where farmers may have varying levels of education and diverse learning preferences.

In our analysis of 54 articles exploring the use of educational technology for transmitting agricultural technology/innovation to farmers, we identified multiple themes in the types of agricultural technologies. Most of the articles ( n = 21, 38.89%) discussed a combination of agricultural technologies, indicating a mixed approach. Pest/disease control technology was the next most used agricultural technology ( n = 11, 20.37%). Another 10 articles (18.52%) focused on crop cultivation/harvesting practices, six articles (11.11%) covered product processing technology, and the remaining six articles (11.11%) focused on knowledge/skill/general agricultural education.

The agricultural technology and innovations covered in our included studies varied. Some studies incorporated a combination of technologies like row planting, precise seeding rates, and urea dressing [ 68 ]; tillage and sowing machinery [ 71 ], planting methods, weeding and fertilizer application [ 72 , 73 ]; identifying growth stages and improving yield predictions [ 74 ]; and seed selection, storage and handling [ 67 ].

Several studies also examined technologies and innovations for controlling pests and diseases. For instance, Chowdhry et al. [ 65 ] explored the use of botanical pesticides, Bentley et al. [ 75 ] investigated methods for controlling bacterial wilt (BW) in potatoes, and Dione et al. [ 76 ] focused on biosecurity messages for managing African swine fever. Other studies have been conducted on crop cultivation and harvesting practices. Dechamma et al. [ 77 ] studied the production practices of tomato crops, and Ding et al. [ 78 ] focused on nitrogen management practices in crop production. Additionally, Bello-Bravo et al. [ 79 ] and Sidam et al. [ 80 ] researched technologies related to product processing, such as storing beans in jerry cans and making raisins.

The last category of studies included those that focused on knowledge and skills/general agricultural education such as knowledge and awareness about agricultural credit [ 31 ], climate information [ 81 ], information about cattle handling [ 82 ], and backyard poultry farming [ 83 ].

Intervention characteristics of technology

We classified the duration of the technology intervention, the intensity of the intervention, and the interval between the intervention and the measurement of its effect. Regarding the duration of the technology intervention, nine studies (16.68%) did not provide information on the duration. Eight studies (14.81%) implemented interventions that lasted less than a week, while seven studies (12.96%) had interventions that ranged from one week to 12 weeks (3 months). Eleven studies (20.37%) reported interventions lasting between 13 weeks to 24 weeks (6 months), while eight studies (14.81%) had interventions lasting between 25 weeks to 48 weeks (1 year). Furthermore, eleven studies (20.37%) documented interventions lasting from 48 weeks (1 year) to 192 weeks (4 years).

As for the intensity of the intervention, 64.81% ( n = 35) of the studies did not provide information on the intensity, while 35.19% ( n = 19) did include details on the intensity. Out of the 19 studies that reported the intensity of the intervention, six (31.58%) specified the frequency of the intervention, such as two sessions per week or two messages per week. Thirteen studies (68.42%) provided precise information on the exact time of each session or video of the intervention, which varied from two minutes to as long as two days. These findings indicate that a significant majority of studies should have included more detailed information on the intensity and duration of the intervention. As the intensity and duration are crucial components of an intervention, they play a significant role in interventions’ effectiveness. Future research should place greater emphasis on exploring intensity and duration in greater depth and on detailed reporting of intervention components.

Regarding the interval between the intervention and the measurement of its effect, researchers exhibited a preference for measuring immediate effects, followed by long-term effects, short-term effects, and a mixed approach. Among the reviewed studies, 22 studies (40.74%) measured the immediate effect, 16 studies (29.64%) focused on the long-term effects (more than three months), seven studies (12.96%) assessed the short-term effects (within three months), two studies (3.70%) used a mixed interval between the intervention and the measurement of its effect, and seven studies (12.96%) did not specify the interval between the intervention and the measurement of its effects.

Effect of technology application in agricultural extension

The effect or impact of using technologies in agricultural extension showed diverse outcomes across the 54 studies. Among those studies, 35 articles (64.82%) recorded positive outcomes, while 15 articles (27.78%) documented mixed outcomes, suggesting a combination of positive and potentially less favorable results. Two articles (3.70%) reported non-significant outcomes, indicating that the technologies did not have a statistically significant impact on agricultural extension. Finally, the last two articles (3.70%) did not specify the outcomes achieved.

In one study with mixed outcomes, Bentley et al. [ 75 ] compared three agricultural extension methods (FFS, community workshops, and radio) for their effectiveness in teaching Bolivian farmers about BW of potato. Their findings found that while radio listeners received information about topics like diagnosing BW, crop sanitation practices, use of healthy seed, crop rotation, and incorporation of manure first from the radio, they never took any concrete action that led to the actual adoption of those agricultural technologies when compared to the FFS groups and the workshop attendees. So, while radio increased awareness about the AT, it fell short in the actual adoption.

Another study that reported mixed outcomes was that of Ding et al. [ 78 ] where ICT-based agricultural advisory services were used for nitrogen management in wheat production in China. The study sought to examine the effects of ICT-based extension services on the adoption of sustainable farming practices like nitrogen control in wheat production and found that while there was no reduction in the use of N-fertilizer for wheat production, the ICT-based services prompted farmers to adopt N-fertilizer use towards site-specific management. So, whereas the educational technology fell short of convincing the farmers to reduce their N-fertilizer usage in wheat production, it achieved the unintended goal of making the farmers adopt some site-specific management practices of N-usage.

In addition, we conducted cross-tabulation analyses and employed Chi-square tests to assess the associations between different types of educational technology, agricultural technology, and the resulting effects or impacts of the implemented technology interventions. Among the 54 articles, two articles did not specify the intervention effect.

Based on the findings presented in Table 3 , a significant relationship was observed between the type of educational technology utilized and the resulting effect or impact of the intervention. The statistical analysis revealed a significant result of χ2 (8, n = 52) = 28.67, p < .001, indicating that the type of educational technology employed influenced the outcomes of the interventions. Interestingly, articles that predominantly utilized multimedia and a combination of multiple ET ( n = 30) recorded more positive intervention outcomes. Research studies, such as those conducted by Chowdhury et al. [ 65 ] in Bangladesh, which used video-mediated learning to improve farmers’ understanding of botanical pesticide usage, and by Bello-Bravo et al. [ 79 ], which found an 89% adoption rate when animated agricultural videos was used for the dissemination of postharvest bean storage, clearly demonstrate the effectiveness of multimedia as a reliable tool for promoting the adoption of agricultural technologies. Several studies have examined the effectiveness of mobile apps and smartphones, and four of them reported positive results. One such study was conducted by Dione et al. [ 76 ], where the use of interactive voice response (IVR) was found to significantly enhance the knowledge gains of 408 smallholder pig farmers who received biosecurity messages. While the results of the other four were mixed, one study conducted using digital games/simulation also reported a positive outcome which was the study by Dernat et al. [ 84 ] where a game-based methodology was found to be very effective in facilitating farmers’ collective decision making and continued engagement. Notably, the only article that did not report a positive outcome was a single study that used online/web-based applications. The implications of these findings are that stakeholders in the field of agriculture can collaboratively work together to design a targeted, cost-effective and guaranteed communication channels that could yield greater positive results in the nearest future.

Note *** = p < .001.

In contrast to the analysis on educational technology, the cross-tabulation and Chi-square analysis examining the relationship between the type of agricultural technology provided to farmers and the resulting impact of the intervention did not yield a statistically significant result χ2 (8, n = 52) = 7.52 ( p = .482), as shown in Table 4 . Despite the lack of statistical significance, patterns can still be observed between the two variables. Out of the 52 articles, 35 reported a positive outcome, while 15 reported mixed results, regardless of the specific agricultural technology/innovation utilized. These findings suggest that, in the context of agricultural extension, the method of communication or transmission of agricultural information through educational technology may play a more crucial role in determining the overall success of the interventions than the specific agricultural technology employed.

Note: χ 2 (8, n = 52) = 7.52, p = .482.

The previous research (44) focused on explaining the process of transferring and adoption of agricultural technology while our study focused on the application/usage of the AT. This study found that simple technology like multimedia served as the most frequently used and video/video-mediated extension served as the most prominent, which is consistent with the previous research [ 43 ] stating that technologies that are more complex to comprehend and use have lower rates of adoption. Previous review [ 44 ] focused on how one specific type of ET (ICT) affects AT adoption in developing countries while our study investigated diverse kinds of educational technology. Our findings suggested that the use of multimedia as an ET might be due to the characteristics of limited educational level and economic level of farmers in developing countries. It is consistent with previous review [ 44 ] indicating that farmers have limited access to resources and infrastructure investments remain low in many developing countries. While these reviews concentrated on measuring the impact of ICT-based agriculture extension programs, our study focused on summarizing the effect/impact of using technologies in agricultural extension with most studies reporting positive outcomes.

6. Conclusion and future directions

In conclusion, this scoping review underscores the critical role of TA in agricultural extension, presenting valuable insights into technology’s potential to enhance extension programs and stimulate future research. Maunder’s [ 8 ] definition of agricultural extension guided this scoping review, emphasizing the characteristics of the service and its potential impact on improving and educating farmers. As explained by Rivera et al. [ 7 ], agricultural extension serves as a vital link to increase productivity and efficiency among farmers and researchers, facilitating the sharing of innovations. Technological applications within agricultural extension have the power to transform farming practices [ 12 , 13 , 16 ].

Through our comprehensive coding, we categorized the TA within agricultural extension into two domains: use of technology/innovation as a factor of production and as an ET. While our study included various agricultural fields, such as agricultural economics, agricultural engineering, animal husbandry, and agronomy, it should be noted that some studies lacked detailed information that could have provided valuable insights into the impact of technology applications on farmers through agricultural extension programs.

Furthermore, this research establishes a foundation for future studies, innovation, and informed practices by identifying areas that warrant further exploration and discovery. The significant increase in research activity in technology applications, particularly after 2016, highlights its growing importance. Advancing the application of technology in agricultural extension contributes to improved agricultural outcomes and sustainable development in farming communities worldwide. Future research on technology applications in agricultural extension should address limitations that may be inherent in the research designs, data collection instruments and the units for the measurement of the intervention outcomes. Future studies should also identify technological effectiveness, delve into mechanisms and contextual factors related to positive outcomes, and aim to support farmers and farm households more effectively.

Supporting information

Funding statement.

The author(s) received no specific funding for this work.

Data Availability

• PLoS One. 2023; 18(11): e0292877.

Decision Letter 0

14 Aug 2023

PONE-D-23-20077A scoping review on technology applications in agricultural extensionPLOS ONE

Dear Dr. Xu,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Additional Editor Comments:

Dear Authors,

I hope this letter finds you well. I would like to extend my gratitude to you for submitting your article to the PLOS ONE journal. Your work has been reviewed by two experts in the field, and I have taken their comments into consideration for the following decision.

Your article presents a compelling exploration of the role of technology in agricultural extension programs. Based on the feedback from the reviewers, the consensus is that your paper is of considerable value to the academic community. The depth of your research, the rigor of your methodology, and the clarity of your writing have been particularly appreciated.

However, both reviewers have pointed out specific areas that could benefit from further clarity, elaboration, or adjustment. These comments are aimed at refining your manuscript to ensure that it provides the most significant value to our readers and the broader academic community.

Reviewer 1:

Reviewer 1 was quite impressed with your manuscript and recommends its acceptance in its current form. They particularly commended the depth of your research, the clarity of writing, and the logical flow of your arguments.

Reviewer 2:

Reviewer 2 provided a detailed breakdown of suggestions and potential areas of improvement. Their feedback spans across several sections of your manuscript, including:

Abstract: Emphasizing the significance of your focus, justifying database choices, providing more context on regional mentions, clarifying the distinction between research methods, and expanding on the impacts and limitations.

Introduction: Incorporating a historical perspective, giving examples of technological integrations, ensuring accurate references, and refining the presentation of objectives.

Literature Review: Streamlining definitions, elaborating on technological impacts, and refining the presentation to avoid redundancy.

Research Questions: Enhancing the specificity of your questions and ensuring that the breadth is maintained throughout the manuscript.

Research Method: Expanding on the search strategy, clarifying methodological choices, incorporating a PRISMA flow diagram, and reflecting on challenges faced during research.

Results and Discussion: Providing insights on publication platforms, discussing regional research discrepancies, interpreting statistical results, and drawing comparisons with other literature.

In light of the above, I am returning your manuscript with a decision of "Revise". I believe that by addressing the reviewers' comments, your manuscript can be further enhanced, making it an even more valuable contribution to our journal and the field at large.

Please ensure that you address each point raised by the reviewers. Upon resubmission, kindly include a detailed point-by-point response indicating how you have addressed the reviewers' comments or provide a rationale if certain suggestions were not incorporated.

We appreciate the time and effort you have put into your research and manuscript. I hope you find the reviewers' feedback constructive. I am looking forward to receiving your revised manuscript.

Warm regards,

Mojtaba Kordrostami

PLOS ONE Journal

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

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Reviewer #1: Yes

Reviewer #2: Yes

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: No

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is a very interesting article. The author has delved deep into the subject matter, presenting well-researched insights and thoughtful arguments. The clarity of writing and logical flow make it an engaging read. The article effectively captures the reader's attention from the beginning till the end. The supporting evidence and references add credibility to the claims made. Overall, it's a valuable contribution to the field. I highly recommend accepting it in the current form. Great work!

Reviewer #2: Dear Editor

Please find my comment below:

General Comments

The abstract presented offers an in-depth scoping review of technology's role in agricultural extension programs. The approach is comprehensive, and the narrative effectively captures the integration of both agricultural and educational technologies. The use of multiple databases for sourcing articles provides a robust foundation for the findings. The structured presentation of findings is also commendable.

However, certain aspects of the abstract would benefit from added clarity or additional information. Specific details and clearer articulation in some areas would enhance the reader's understanding and make the abstract even more impactful.

Specific Comments

1. The abstract briefly touches upon the lack of previous reviews on the impact of technology in agricultural extension. It would be beneficial if the authors briefly indicate why this particular focus is of significance.

2. Justifying the choice of the five databases, or mentioning if these are the most prominent databases in this field, would enhance the credibility of the study.

3. The mention of India and Africa requires more context. It would be useful to know if this observation indicates a trend or if it merely represents the scope of available literature.

4. The distinction between the quantitative research method being the most employed and the mixed methods being the most used data collection approach might be confusing. It would be helpful if the authors could provide a brief explanation or example of this distinction.

5. While the most widely used educational technology is mentioned, the abstract could benefit from highlighting a few of the most common agricultural technologies that appeared in the reviewed studies.

6. The statement that the impacts were "mostly mixed" requires further specificity. Providing a brief example or elaborating on what areas showed positive or negative impacts would be beneficial.

7. It's commendable to acknowledge potential limitations. A brief mention of one or two key limitations would be insightful.

8. The abstract concludes with an emphasis on gaps in the literature. Mentioning one or two primary gaps or areas for future research would provide readers with a clear takeaway.

Introduction

The introduction offers a clear context and rationale for the importance of integrating technology into agricultural extension programs. The progression from the significance of technology in enhancing extension programs to the purpose of the scoping review is logical. The emphasis on the potential benefits for policymakers, researchers, and practitioners provides a broad perspective on the review's relevance.

However, some areas could benefit from further elaboration, and the structure might be enhanced to offer a more concise and direct presentation of the main points.

1. The introduction starts strongly by emphasizing the importance of agricultural extension programs. However, it could benefit from a brief mention of the historical or traditional methods of agricultural extension for context.

2. While the importance of technology in agricultural extension is emphasized, it would be beneficial to provide examples or categories of such technologies. This would offer readers a clearer picture of what technological integrations are being discussed.

3. The references (1) and (2) are placeholders. In the final manuscript, it would be crucial to ensure that these references are accurately representing the claims made.

4. The statement about shedding light on the "current state of research" and mapping the field is clear. However, distinguishing between the broader goals of the review and the specific objectives could provide more clarity.

5. The mention of policymakers, researchers, and practitioners is appropriate. Still, it might be enhanced by briefly discussing the specific challenges or questions each of these groups faces that the review can address.

6. The final part of the introduction discusses the research's aims to lay a foundation for future studies. While this is a strong ending, it might be enhanced by presenting a more concise summary of the intended contributions and outcomes of the review.

Literature Review

General Comment

The literature review offers a comprehensive overview of the integration of technology in agricultural extension programs. The authors have meticulously categorized the research into the historical perspectives of agricultural extension, the role of technology in agriculture, and the intersection of both. The reference to prior studies and the identification of gaps in existing literature lend robustness to the review.

However, some areas could benefit from further clarity, and the structure might be enhanced to offer a more concise presentation of the main points.

1. Agricultural Extension Definitions: The various definitions of agricultural extension provided are comprehensive. However, the transition to the definition that the review aligns with could be smoother. Perhaps a brief rationale for choosing Maunder’s definition would be beneficial.

2. Technological Integration: The distinction between agricultural technology as a component of production and as an educational tool is clear. Yet, more explicit connections between the tools and their practical impacts would enhance understanding. For instance, how do drones or IoT directly influence agricultural extension?

3. Previous Studies and Research Gap: While the section thoroughly identifies gaps in existing research, it could benefit from a more streamlined presentation. The repeated mention of "technology application in agricultural extension" and the emphasis on the review's unique approach can be condensed to avoid redundancy.

4. Citation and Referencing: The placeholders for references are well-placed, providing a strong foundation for the claims made. In the final manuscript, ensuring that these references are comprehensive and up-to-date will be critical.

5. Relevance of Previous Studies: The review does well to distinguish itself from the works of Altalb et al. and Aker. However, a brief mention of why these studies are particularly relevant or how they shaped the current review's approach might provide more context.

6. The literature review concludes with a forward-looking statement about enhancing productivity and bridging divides. This is effective but could be enhanced with a brief mention of the expected outcomes or implications of the scoping review.

Research Questions

The research questions section offers a structured breakdown of the areas that the scoping review aims to address. The categorization into substantive features, methodological features, and characteristics of technology application provides a clear roadmap of the study's approach. The questions themselves are well-formulated and adequately detailed, promising a comprehensive exploration of the topic.

However, certain areas could benefit from further specificity or clarity to ensure that the subsequent sections of the manuscript align seamlessly with these guiding questions.

1. While the query about publication information is clear, it might be helpful to specify what particular publication information is of interest (e.g., publisher, year, journal name). Additionally, the inclusion of "agricultural field" is relevant, but the term might benefit from elaboration or examples for clarity.

2. The question is comprehensive in covering research methods, data collection approaches, and sample size. However, it might be enhanced by adding inquiries about potential research biases, limitations, or challenges identified in the included studies.

3. The distinction between educational technology and agricultural technology is clear and aligns with the literature review. Yet, the question might benefit from an exploration of the integration or interaction of these technologies. For instance, how does the use of educational technology influence the adoption or effectiveness of agricultural technology?

4. The query about the "overall effect of technology on agricultural extension" is broad. It would be beneficial to specify if this effect is being measured in terms of productivity, knowledge transfer, farmer satisfaction, or any other specific metrics.

5. The research questions set a broad scope for the review. Ensuring that this breadth is maintained throughout the manuscript will be crucial, especially in the results and discussion sections.

Research Method

The research method section is comprehensive, providing detailed insights into the procedures followed in the scoping review. The use of multiple databases, clearly defined inclusion and exclusion criteria, and a structured coding scheme reflects the systematic approach the authors have taken. The use of PRISMA flow and the description of inter-rater reliability further emphasize the rigor with which the study has been conducted.

While the overall methodology appears robust, certain areas could benefit from further clarity or elaboration to ensure the methodological choices are entirely transparent and replicable.

o It is commendable that the authors have provided the date of the search to ensure the recency of the data.

o While the Appendix A contains the full search strategy for CAB Abstracts, the modifications made to fit other databases would be useful for replication. It would be beneficial to briefly describe or provide these modified strategies in an additional appendix.

o The criteria are well-defined and comprehensive. However, the delineation between what qualifies as an educational technology versus agricultural technology might benefit from additional examples or elaboration.

o It would be helpful to know why the authors chose the specific date range of January 1, 2000, to November 1, 2022. While technological advancements since 2000 are mentioned, a brief rationale for this specific range could enhance clarity.

o The coding scheme is extensive and well-structured. However, the categorization of agricultural field/enterprise could benefit from a more exhaustive list or examples, given that only a few are mentioned.

o Under the section on methodological features, while the grouping of research methods is clear, a brief rationale for these groupings (especially what constitutes mixed methods) would be useful.

o The distinction between educational technology and agricultural technology/innovation is clear. However, the list of technologies and their sub-categories might benefit from further examples or references to ensure clarity.

o The PRISMA flow diagram, while mentioned, is not provided within the section. If feasible, it would be helpful to include this diagram directly within the manuscript or provide a clearer direction to its location.

o The inter-rater reliability is commendably high, but a brief discussion on how discrepancies were resolved (other than the first author acting as arbiter) would provide additional transparency.

o It might be helpful to provide a brief overview of the descriptive statistical analyses planned or executed to address the research questions.

o The section could benefit from a brief discussion or reflection on any anticipated or encountered challenges during the research method, especially during data collection or coding.

Results and Discussion

The Results and Discussion section is extensively detailed, covering a wide range of aspects concerning the substantive features, methodological features, and characteristics of educational technology in agricultural extension. The use of figures, tables, and statistical analyses enhances the rigor and depth of the presented findings. The section is well-organized, with clear sub-sections that aid in understanding the progression of results.

However, there are areas that could benefit from further elaboration or explanation to ensure clarity and completeness.

o The graphical representation of publication distribution (Fig 2) and the breakdown of journals, conferences, and policy papers (Table 2) provide a clear overview of the landscape of research in the field. It would be beneficial to include comments or insights on the top journals or platforms publishing in this area.

o The distribution by country and region paints a clear picture of where the research is focused. Some insight into the potential reasons behind the lack of research from certain regions, like Europe or Australia/Oceania, beyond what is provided, might enhance the discussion.

o The breakdown of research methods, data collection approaches, inferential statistics, and sample size units are comprehensive. It would be interesting to see a further discussion on the implications or reasons behind the prevalent use of quantitative methods over qualitative ones.

o The discussion on sample size units and the categorization based on the number of participants adds depth to the results. However, a brief discussion on the implications of these findings for future research would enhance this section.

o The breakdown of different types of educational technologies and agricultural technologies is detailed and clear. It would be helpful to delve deeper into the reasons behind the prevalent use of certain technologies over others.

o The findings on the intervention characteristics of technology are insightful. The relationship between the duration, intensity, and outcomes of interventions could benefit from further exploration.

o The cross-tabulation analyses and the Chi-square tests add depth to the results, providing a clear understanding of the relationships between variables. However, some additional interpretation of these results in the context of the broader research landscape would be useful.

o The section might benefit from a summarization of the main findings and their implications for both researchers and practitioners in the field.

o While the section is quite detailed, it would be beneficial to see more connections or comparisons with other studies or literature in the field, providing a broader context for the presented findings.

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Reviewer #1:  Yes:  Cristiano Matos

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Author response to Decision Letter 0

28 Sep 2023

Dear reviewers,

We are delighted to revise our manuscript based on the excellent feedback from the reviewers and you. We believe the suggestions and corresponding revisions have significantly improved our research, findings, and manuscript. We responded to the comments one by one and highlighted what we revised in the manuscript. We also created a comments and response table to explain how we addressed all of the comments. We will be happy to receive any additional comments and make revisions if necessary. Thanks again for the opportunity to revise and resubmit.

Detailed information can be found in our Comments and Response table and the revised manuscript.

Submitted filename: comments and response table.docx

Decision Letter 1

PONE-D-23-20077R1

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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The manuscript can be accepted now.

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Reviewer #2: All comments have been addressed

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Reviewer #2: DEAR EDITOR

THE MANUSCRIPT IS IMPROVED SIGNIFICANTLY AND CAN BE ACCEPTED NOW.

It can be accepted now.

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Acceptance letter

27 Oct 2023

Dear Dr. Xu:

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Dr. Mojtaba Kordrostami

Kelp wanted: Why researchers are adding seaweed to cattle's diet

Federal study found feeding beef cows kelp lowered their emissions by up to 15 per cent.

Social Sharing

Cows are not known to have seafood in their diet, but a team of federal scientists in Nova Scotia started introducing some to seaweed in hopes it could help in the fight against climate change.

The focus? The cattle's burps. 

The Agriculture and Agri-Food Canada project involved feeding 16 cows varying amounts of seaweed at a research farm in Nappan, N.S. It found that by replacing only one percent of the cows' regular feed with kelp, researchers discovered that it reduced the methane emissions from cow burps by as much as 15 percent.

"That's a fairly significant result," said John Duynisveld, the lead biologist.

He said when cows consume food, it enters the first stomach, called the rumen, where various microbes break down the food. That process results in methane, a greenhouse gas linked to global warming, which gets released through burps.

Bryanna Richardson, one of the researchers, said to measure the emissions, they put the cows in respiratory chambers connected to a computer system that tracked gases coming from the animals. 

First the cows needed to get used to the chambers, which is why researchers left them in the room for a few hours at a time. Eventually they were left there for 24 hours straight so their daily methane emissions could be tracked.

"There's a vacuum pump that's attached to it [the chamber] and it pulls all the air that they're breathing out up into the computer system, which measures methane, carbon dioxide and oxygen," said Richardson. 

Kelp contains bio-components such as tannins that Duynisveld said might be changing the composition of cow's burps. Meaning the cows he studied didn't belch less, but their burps were less potent . 

Duynisveld said on average, a beef cow emits approximately 100 kilograms of methane annually, so this research aimed to make a small contribution toward addressing climate change. 

Methane, which is produced by the agriculture industry, landfills and oil and gas activities, is responsible for about 14 per cent of Canada's greenhouse gas emissions

Shannon Arnold, with the marine program at the Ecology Action Centre in Halifax, said the study is different from others done internationally as it focuses on using locally sourced kelp species that could be farmed with a reduced ecological impact. 

Duynisveld's study used kelp that comes from the North Shore of Prince Edward Island and some areas of Nova Scotia, commonly known as shore weed. 

Arnold said shore weed can be easily farmed locally with little land-use disruption, and she'd like to see more collaboration between cattle farms and local kelp growers.

She said the cultivation of kelp is relatively simple, as it can be grown in small spaces, with the potential to harvest around 10 kilograms of kelp per meter. Growing it could have the added benefit of being a substitute for some more environmentally burdensome crops and fertilizers, she said.

"There's lots of interest [in kelp] from new farmers and small farmers and folks all around our coastal areas," Arnold said. "This would be a great opportunity."

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ABOUT THE AUTHOR

Giuliana is a journalist originally from Lima, Peru. She arrived in Canada in 2022 to study journalism at St. Thomas University and was selected as one of the Donaldson Scholars in 2024. If you have any story tips, you can reach her at [email protected].

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