State of Research on Agroecology Transition

Version	Summary	Created by	Modification	Content Size	Created at	Operation
1		Théodore NIKIEMA	--	2648	2023-11-09 09:14:41	\|
2	Reference format revised.	Lindsay Dong	-4 word(s)	2644	2023-11-13 02:11:11	\| \|
3	Description revised	Lindsay Dong	+ 1 word(s)	2645	2023-11-20 04:08:03	\|

This entry is adapted from the peer-reviewed paper 10.3390/su152115616

As a sustainable and holistic approach to agriculture, agroecology has received considerable attention because of its potential to address the environmental, economic, and social challenges of agricultural systems. In order to identify key trends, influential authors, impactful journals, emerging research themes and gap in research on agroecological adoption, a bibliometric analysis based on the metadata of documents is performed to deal with agroecology adoption and the methods used for its evaluation over the period from January 1990 to July 2023, extracted from the Web of Science database.

farms machine learning bibliometric method African countries metadata agroecology adoption

1. Introduction

A paradigm shift in agricultural production systems is urgently required for our planet. Due to the numerous negative effects induced by the extensive use of chemical treatments, the conventional production system from the 1950s, which is still in use in many countries, has reached its limits ^[1]^[2]^[3]^[4]. Nowadays, the question of how to satisfy the needs of the present without compromising the capacity of future generations to satisfy their own needs is one that is currently being asked by a large number of researchers and international organizations. Several alternative production systems exist in the literature ^[5]^[6] and agroecology is identified as one of the most promising alternatives ^[7]^[8]^[9]^[10].

The issue of agroecological transition emerged to address the need for adaptation for all of the world’s agriculture to meet social demands, environmental challenges, climate disruption ^[11] (p. 335), and the gap between the scale at which most agroecological information is currently produced and the scale at which most decisions about farming systems are made ^[9].

Agroecological transition can be defined as “the set of linked technical and organizational processes by which new production modes based on agroecological principles gradually and sustainably replace systems resulting from conventional intensification that have led to the massive use of synthetic inputs, or allow very low productivity farmers to intensify their production without reproducing this conventional intensification scheme”. In either case, the objective is to develop an agriculture that can sustainably ensure both local and global food security across all relevant dimensions ^[11] (p. 337).

2. State of Research on Agroecology

2.1. Publication Trends and Journal Landscape

Since 1990, there has been an increasing number of publications on agroecological adoption and its methods. In contrast to the period 1990–2000, when fewer than 10 articles were produced annually, since 2015 people are currently seeing a high number of productions of more than 50 documents annually. The agroecological transition is becoming more and more important when discussing the broad agroecology study field. Agroecology adoption on a large scale is being sought after by researchers and farmers in various nations. The number of publications on agroecological transition over time is depicted in Figure 1.

Figure 1. Number of publications on agroecological adoption per year from 1990 to 2023.

The most significant sources in the literature were determined using both Bradford’s Law and the H-index approach. The number of journals (470) used for publications indicates that there are many options to publish articles related to agroecological adoption or methods to achieve this. Regarding journal performances, the decomposition provided by Bradford’s law results in a core group of 16 journals (i.e., a group of journals with high added value on the research topic, cluster 1) with 435 publications. For clusters 2 and 3, 427 and 424 articles were published, respectively, and consisted of 88 and 366 journals, respectively. The sixteen (16) publication sources that make up the core group are shown in Figure 2. Six (06) of them stand out among the rest, with more than 30 publications each. These journals cover topics like food security, ecosystem and land management, agricultural economics, and sustainability. Except for “Agronomy for Sustainable Development,” which is from North America, the majority of them are Western European journals.

Figure 2. Distribution of the core group’s journals using Bradford’s law from 1990 to 2023.

At some levels, the rank according to the h index (Figure 3) shows a different hierarchy from that obtained using Bradford’s law. However, four of the top five sources identified by the Bradford law are also those with the highest h index. Agricultural System remains the top-ranked journal with an index of 23.

Figure 3. Distribution of the 16 most important publications, according to the h-index, from 1990 to 2023.

2.2. Top Authors and Affiliations

The analysis of the authors’ citation performance was based on the guidelines prescribed by Lotka’s law. As a result, three different categories of authors can be defined: occasional authors (those with a single publication during the study period), authors in the intermediate group (those with between two and four publications during the study period), and influential authors, or the core group (those with at least five publications during the study period). Figure 4 shows that Theron O is one of the authors who has published the greatest number of articles (14) on agroecological practices adoption, and some of the related methods over the study period. He is followed by Tittonell P, Tello E, and Duru M with 11 and 10 publications, respectively. Theron’s key research has focused on the evaluation and modeling of the agroecological transition at the territorial or local level ^[12]^[13]^[14], while the main work carried out by Tittonell has focused on establishing typologies and identifying levers for the agroecological transition of farms ^[15]^[16]^[17]^[18]. Tello and Duru’s main studies focus on land use and issues related to methodology for designing agroecology transitions and their application at the territorial or local level ^[19]^[20]^[21]^[22]^[23]. Core groups make up no more than 5% of the total authors, while occasional authors account for 88% of the total. Figure 4 lists the 10 most influential authors of the series according to Lotka’s law.

Figure 4. The 10 authors with the highest number of articles through Lotka’s law, from 1990 to 2023.

Regarding the institutional affiliations of the various authors of the study articles, a total of 1796 affiliations were identified. Over 85% of these institutions published fewer than 5 articles, while less than 2% of institutions each published more than 20 publications over the study period. The top twenty institutions are listed in Figure 5. With 110, 69, and 56 publications, respectively, Montpellier and Toulouse Universities in France and Wageningen University in the Netherlands top the list. Some African universities, such as Addis Ababa University and Haramaya University in Ethiopia, the University of Sokoine in Tanzania, the University of Abomey-Calavi in Benin, and the University of Ghana, are among the top institutions with an average number of publications of around 23.

Figure 5. Distribution of the top 20 institutions from 1990 to 2023 according to publication number.

2.3. Most Cited Documents in the Literature

An overview of the most frequently cited papers is shown in Figure 6. On this graph, the importance of the number of citations for a given document is indicated by the size of the circle around its author. By cross-referencing the most cited articles with authors with a high number of published articles, only an article by Tittonell ^[24] entitled “Ecological Intensification of Agriculture—Sustainable by Nature”, with 378 citations, and an article written by Duru et Theron ^[23] entitled “Designing Agroecological Transitions: A Review”, with 337 citations, could be identified, indicating that only these works belong to these two categories.

Figure 6. An illustration of works from 1990 to 2023 that have received at least 200 citations ^[23]^[24]^[25]^[26]^[27]^[28]^[29]^[30]^[31]^[32]^[33]^[34]^[35]^[36]^[37]^[38].

2.4. Countries Production

Corresponding author’s countries highlight the production of authors affiliated with each country of the study. From January 1990 to July 2023, 20 out of the 115 countries covered by the study produced about 80% of the publications on the subject. With 217 and 165 articles, respectively, France and the United States have the highest number of articles produced on the topic (Figure 7). With an average of fewer than 50 publications, only five (05) African countries (English-speaking countries) are in the top 20. This suggests that the English language deficit is a factor that affects how well-known African countries’ productions are in the area of agroecological transition. The abbreviations SCP and MCP stand, respectively, for “single country publications” and “multiple country publications”. The least number of papers with co-authors are published in Brazil and Nigeria, while multi-author collaborations are most common in Kenya and China. Despite their large number of publications, the collaborations made by French and American authors with others remain weak. The overall scientific production of African countries is 16% and remains low, despite the predominance of traditional agriculture in these countries. The sustainability of traditional farming systems and their potential as a basis for agroecological transition are well known ^[39]^[40]^[41]. However, scientific production in African countries regarding agricultural issues suffers from the unavailability of timely data ^[42]^[43]^[44].

Figure 7. Number of documents published by the 20 most influential countries from 1990 to 2023.

Looking specifically at the issue of agroecological adoption, a lack of institutional frameworks to promote agroecological practices has been noted in some West African nations, and agroecology is primarily driven by farmer organizations and non-governmental organizations ^[11]^[45]^[46]^[47]. Also, the majority of agricultural policies in African nations continue to support initiatives for intensification that are based on 1950s green revolution techniques ^[45]^[47] and the conclusions of the 2006 African summit on fertilizers. However, with the adoption of new agroecology programs in recent years, such as the “program to support agroecological transition” (PATAE) in some West African countries such as Burkina Faso and Mali ^[47], the Great Green Wall ^[48], the “dynamic for agroecological transition in Senegal” (DyTAES) ^[49], etc., and the action of a large number of NGOs, the issue of agroecology is gaining in importance in African countries.

2.5. Keywords Analysis

2.5.1. Trend Topics and Co-Occurrence Analysis

The result of the co-word analysis ^[50], using Biblioshiny ^[51], based on keyword co-occurrence, gives the different methodological approaches that are used to promote agroecology adoption and the main themes/issues studied in this context. Figure 8 shows trend topics, and apart from the keywords related to agricultural systems management with a frequency usually reaching 150, the trendiest keywords are models, technology, classification, challenges, preferences, simulation, and the overall methodological framework with frequencies usually between 50 and 100. The issues of avoiding deforestation, the use of technology, and assessing the consequences of the agricultural system are among the topics that have been studied consistently over the years.

Figure 8. Most trendy keywords and topics.

2.5.2. Themes Relevance and Degree of Development Resulting from Keywords Clustering

Using clustering algorithms provided by the bibliometrix package, It is able to link the various themes based on selected article keywords. This clustering resulted in five primary thematic classes covering: global agriculture, adoption of agroecology, climate change, management of agricultural landscapes, and the development of farmers’ knowledge.

2.6. Research Gaps: Methodology for Agroecological Transition Modeling

Although questions relating to the identification of the determinants and strategies of agroecological adoption are omnipresent in the literature, research with a view to developing robust and comparable methods to achieve this from one geographical area to another has yet to be carried out. For instance, keyword analysis revealed that machine learning methods and econometric ones are not widely used to model the process of farm agroecological adoption. Most methodological studies have focused on developing a framework for evaluating the process of adopting agroecology using indicators or a multi-criteria approach ^[2]^[8]^[52]^[53].

Agroecological transition can occur at any scale (plots, fields, farms, nations, etc.). However, analyzing this transition at the country scale can be more complex than at a plot scale, and the transition from one scale to another is not always obvious ^[54]. The spatial dimension, or scale at which agroecology is to be adopted, must be clearly defined as part of the analysis of the agroecological transition. Plot scale, farm scale, and territorial scale, such as the country or region, can be distinguished as the three main scales ^[2]^[8]^[55]. To date, the farm transition has not received much attention as a research topic ^[56]^[57]. Transition is generally studied at the scale of the territory or landscape, as shown in the keyword analysis section. Thus, despite the fact that the farm is the core of the agricultural production system, only a small number of studies concentrate on this level ^[58]. Additionally, a time dimension must be included in the transition analysis to enable performance comparison and horizon forecasting ^[59]. The results will be even more significant if the time dimension is taken into account when comparing the economic performance of agroecological farms with that of other production systems, such as the conventional system. In fact, the adoption time increases with increasing spatial dimensions. Therefore, in order to plan the technical and financial resources required to achieve the desired results in a timely manner and use a method that is appropriate, modeling work will need to take into account the correlation between time and space.

Agroecological practices can be viewed as innovations that directly involve stakeholders in the innovation process while mobilizing a variety of local knowledge sources and the most cutting-edge scientific knowledge to optimize farm production ^[60]. According to the general framework of the theory of the “diffusion of innovation”^[61], The adoption function would take the shape of an ‘S’, characteristic of the logistic function. In this regard, econometric methods may prove useful for simulating the adoption of agroecology and its scaling up. More broadly, automatic learning models can be used through the multiple algorithms they provide, such as multiple logistic regression (LRM), ensemble methods (decision trees), and non-parametric methods (naïve Bayes, k nearest neighbors), to learn from features and make efficient modeling ^[62]^[63]^[64]^[65].

3. Summary

The agroecological transition issue’s significance is growing over time. Indeed, the rise in the number of publications on the topic attests to its significance and can be interpreted as a sign that it is reaching a certain stage of development. Additionally, the inclusion of agroecology in the research domains of international organizations, such as the Food and Agriculture Organization of the United Nations (FAO), demonstrates that its status as a significant scientific and research field is expanding significantly ^[66].

The walktrap clustering algorithm was used to group keywords into five main thematic classes: agriculture, landscape, adoption, climate change and knowledge. Apart from the question related to agriculture and biodiversity management, other studies, such as ^[67]^[68]^[69], had not previously identified climate change, knowledge development, and adoption as research fronts. Adoption, knowledge development, and climate change are some of the trendiest issues and are identified as central issues. Although the importance of the themes varies from period to period, some of them, such as those dealing with the management of agricultural landscapes or biodiversity, have remained constant over time. Given the topicality of climate change issues, in the process of modeling the adoption of agroecology, it would be interesting to quantify the role of agroecological practices in mitigating the effects of climate change.

One of the challenges facing current agricultural research is finding the best strategies for the sustainable transformation of current production systems. Agroecology is proving to be one of the most suitable alternatives to the problem. Although significant progress is being made around the world, large-scale adoption of agroecology is not yet being observed, and African states should document the wide range of traditional knowledge (linked to agroecology) practiced on the continent in order to promote its adoption. The study demonstrates that while farming systems management, agricultural intensification, and biodiversity management have long been addressed in the past, those relating to the study of strategies and determinants around the adoption of agroecology, the development of knowledge and innovations for food sovereignty, and the study of climate change impacts on farm productivity still need to be explored in depth. Furthermore, there is no universal agreement on the best way to model the transition of farms to an agroecological system, as each stage of this process may require a specific methodological approach, and machine learning methods reputed for their robustness and objectivity are still unexploited. Comparisons between conventional and agroecological production systems, based on real and high data quality, could allow a real transition to take place in the world and Africa in particular. One of the limitations of performance evaluation is the inability to classify farms in a reliable and consensus-based manner. Using machine learning techniques (such as decision trees, naïve Bayesian classification, multinomial logistic regression, and more) will help to overcome this limitation and complete the other evaluation and modeling steps that are still closely related to classification. Finally, future research can cover other databases, such as Scopus, to make comparisons with the findings of the present study.

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Théodore Nikiema

Eugène C. Ezin

Sylvain Kpenavoun Chogou

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