1. Introduction
Climate change modifies agricultural production and food systems, introducing uncertainty and vulnerability risks within farmers and policy decision-makers [1]. There is no doubt that impacts of climate change pose significant challenges to global food security, and this is envisaged to exacerbate over the coming years due to livelihood pressures such as the rise in population, economic development, urbanization, and the frequent occurrences of natural hazards such as extreme temperatures, drought, and floods, among others. It is estimated that the living conditions of about 9 billion people globally will worsen by 2050, whereby hunger and poverty will be taking the lead, making it substantially hard to put food on the table [2,3,4]. Consequently, various international institutions are working together with the World Bank and the Food and Agricultural Organization (FAO) groups to devise agricultural systems that will enhance and boost food production at all levels, from global to local. Subsequently, a global shift to climate-smart agriculture (CSA) has been applauded by various institutions, including stakeholders such as research, policymakers, and investments, and across private, public, and civil society sectors [5,6].
While the definition of CSA is dispersed in scientific and technical publications, numerous definitions have been proposed by, e.g., climate change organizations, agricultural scholars, and research organizations. Considering the diversity of definitions reported in the literature, Adesipo et al. [7] compiled a set of keywords that characterize the key attributes of CSA. These keywords include capacity building, sustainability, emission and vulnerability reduction, profit, food security, transformation, new knowledge, technology, and productivity. Although the suggested keywords are not exhaustive, most definitions of CSA are built around them, with at least two of the words considered in the definition. For instance, Engel and Muller [8] defined CSA as a sustainable approach that can enhance agricultural productivity and income through adopting adaptation strategies while promoting resilience to climate change and minimizing greenhouse gas emissions. Campbell et al. [9] defined CSA as methods that transform agricultural systems to enhance food production and security under the changing climate. Similarly, Adesipo et al. [7] comprehensively defined CSA as a transformative and sustainable form of agriculture that aims to improve productivity in food security and production systems, based on coupling the key pillars of climate change (e.g., adaptation, resilience, and mitigation) in addition to smart and advanced technological knowledge, thereby increasing profit, and to minimize vulnerability through reducing greenhouse gas emissions.
The CSA approach, as presented in the literature, advocates the integration of climate change towards the planning and implementation of sustainable agricultural strategies, thus identifying synergies and trade-offs within the three pillars of CSA (known as food security, adaptation, and mitigation), in support of climate change-related policy and decision making [10]. In particular, CSA aims to support efforts that promote food and nutrition security, thereby assimilating essential adaptation and mitigation measures, as per its definition [6]. It provides enabling tools where different technologies and practices can be evaluated concerning their outcomes, specifically national development and food security objectives under the changing climate. In addition, CSA integrates sustainable agricultural development experience and knowledge as well as participatory community-driven approaches [10], taking into account sustainable intensification as the fundamental basis of on-farm productivity and income, in addition to existing agricultural land protection measures. Furthermore, CSA stresses the use of low-income agricultural systems such as conservation of agriculture; agroecology; ecosystems services; small-scale irrigation; aquaculture and agroforestry systems; soil/water conservation and nutrient management; integrated crops; livestock; landscape approaches; grassland and forestry management; and best practices of minimizing tillage and breeds, all in order to enhance food productivity, adaptation, and mitigation measures [11].
Most of these CSA best practices have been tested and promoted in various countries in Africa, as documented in the literature. These include the use of an integrated soil fertility management framework (e.g., combined organic and mineral fertilizers) to increase maize yields in sub-Saharan Africa [12], Uganda [13], Nigeria [14], and Kenya [15]. Successful stories have been reported on the use of soil conservation and multiple stress crop practices in Nigeria [16], South Africa [17], Ethiopia [18], Mozambique [19], Zimbabwe [20], and Ghana [21], resulting in a significant increase in drought-tolerant maize variety yields as well as improving small-scale farmers’ and smallholder households’ overall income. The importance of socio-economic, integrated biodiversity, and gender aspects was also explored in Nigeria [22], highlighting the empowerment gap between men and women.
In recent years, CSA has substantially become a fundamental notion for most global organizations at the center of the climate change, agriculture, and development nexus [3]. In addition, CSA has been considered an essential mechanism for achieving the Sustainable Development Goals (SDGs) [23]. Most of all, CSA comes in handy to mostly rural African farmers, who are more vulnerable to extreme weather and climate conditions. Most of the developing countries are exploring different ways to create cheap and reliable weather monitoring and forecasting systems and integrate such systems with advanced smart technologies such as agricultural drones, bio-sensors, IoT-based sensors, remote sensing, and husbandry, among others, in order to upscale crop and livestock management as well as increasing food security [24,25]. Precision agriculture, also within the umbrella of smart agriculture and CSA, has significantly contributed to smart agricultural farming in, for instance, Ghana [26], Kenya [27], Nigeria [28], and South Africa [29], ensuring greater agricultural productivity and minimizing farming losses [24]. While the concept of CSA is well articulated in the literature and has been substantially applauded by various institutions worldwide, the scope of research within this subject matter, especially in Africa, is not exhaustive. Various aspects of CSA research, including the aspect of integration of the three pillars of CSA, have been relatively reported in the literature. In a recent review study by Chandra et al. [11], research on CSA was classified as relatively new, with its progressions still at the policy level and framework description. For Africa to successfully implement CSA, there is a need to understand the current developments and activities conducted within the CSA research field. For this purpose, the current review aims to conduct a scientific mapping and analysis on CSA research studies in Africa to understand thematic trends, developments, the nature of collaboration networks, and general narratives supporting the CSA scientific domain. Consequently, this study will make an important (a) scientific contribution through an exposition of the evolution of CSA research themes and methodology, a fundamental aspect necessary to build the CSA body of science, and (b) practical contribution in terms of keeping the community of practice abreast with current hot topics and the future direction of CSA in support of climate-related policy decision making.
2. Materials and Methods
The current review study considered various search topics to retrieve scientific documents relating to CSA research in Africa. The search themes were widely defined to cover the scope and research topics within the CSA subject matter as much as possible. Consequently, these search topics covered aspects of climate change and areas around policy and decision making, governance, best practices in farming, and technologies involved. Relevant scientific published documents were retrieved using the Web of Science (WoS) and Scopus core collection databases. These databases are widely used in most review studies. They provide a wide range of peer-reviewed research documents, including scientific articles, books/book chapters, and conference proceedings, among others, in almost all scientific disciplines. Documents were searched by entering the keywords “climate-smart agriculture*”, “precision agriculture”, or “precision farming” coupled with “climate change*”, “governance”, “smart farming”, or “technologies” as well as with “Africa”, for areal restriction (see Table 1 for a complete set of the search topics). While the study area was restricted to Africa, the search was open-ended regarding the study period. The retrieved documents contained key information such as authors, title, keywords, abstract text, countries, institutions, journals, and cited references. These document types including articles, book chapters, and conference proceedings are shown in Figure 1. The resulting output consisted of 249 documents, spanning from 2000 to 2020. These scientific documents were co-authored by 869 researchers across different countries, including those from outside the African continent.
The review was based on bibliometric analysis; a technique commonly used to study the structural and dynamic aspects of research topics using scientific mapping [30,31]. Consequently, CSA science mapping undertaken in this review study assessed the following themes: (1) annual publication growth and trends; (2) leading countries contributing to the CSA body of knowledge; (3) collaborations; (4) keyword co-occurrences; and (5) emerging themes. In addition, the VOSviewer program was used to create network visualization output maps for both country collaborations and keyword analysis. The strength of country collaboration was measured based on the total link strength given by VOSviewer. VOSviewer also assigns items (e.g., countries and keywords) into specific clusters, where the size of the cluster represents the collaboration strength or high frequency of keywords.
3. Results
3.1. Scientific Mapping of Climate-Smart Agriculture Research in Africa
3.1.1. Growth Patterns in Climate-Smart Agriculture Research
Figure 2 depicts the yearly scientific publications of climate-smart agriculture outputs. As depicted in Figure 2, research in CSA in Africa started to gain momentum from 2014. Since then, there has been a relative increase in scientific publications, suggesting a growing interest in the CSA subject matter. The scientific production of CSA published articles significantly increased from 2017, reaching the highest number of 56 articles in 2020. Overall, CSA research in Africa is relatively growing, with an annual percentage growth rate of approximately 22.3%. This significant growth rate suggests that CSA is gradually borne out of necessity as the effects of climate change continue to impact people’s lives negatively. Consequently, the greater scientific community has explored more innovative farming methods to mitigate inherent future climate impacts on agriculture.
3.1.2. Most Productive Countries in Climate-Smart Agriculture Research
The top ten countries that have significantly contributed to the CSA research output in Africa are shown in Figure 3. It can be observed that only ~40% of the African countries appear in the top ten list. These include Kenya, taking the lead with 20 scientific publications, followed by South Africa with 12, and Zimbabwe and Mali with 11 and 10 scientific outputs. The leading countries are ranked based on the author’s correspondence country.
The results shown in Figure 3 also show that developed countries such as the United Kingdom (UK), the Netherlands, the United States of America (USA), and Germany appear in the top ten list, suggesting that authors in these countries have collaborated in CSA research projects in Africa, resulting in the research work being disseminated through scientific publications. In general, the 249 CSA documents were co-authored by 849 researchers through multi-country publications (MCP), with only 20 researchers publishing through single-country publications (SCP). In the top ten list of the leading countries, the orange and silver indicate publications achieved through SCP and MCP processes, respectively. It is noted that Africa needs to enhance its collaborations to contribute to the CSA scientific domain significantly.
The published CSA research is well recognized globally, as attested by the citation scores provided in Table 2. Over the study period, the Netherlands has received the highest citations (683), followed by Kenya, Zimbabwe, and Mali, with 159, 154, and 136 total citations. The rest of the countries have received less than 100 citations over the same period, including Burundi and Zambia, with 61 and 46 total citations. Column 3 of Table 2 shows the ten main sources that have published scientific documents related to CSA. The ranking of these sources is based on the total number of the published documents. Most of the sources are journals, reflecting a great interdisciplinary nature of the CSA research field in Africa. Approximately 25% of the documents were published in journals, with Agricultural Systems leading with ten published scientific articles, followed by Frontiers in Sustainable Food Systems (nine), Climate Change Management (eight), and Sustainability (Switzerland), with seven published articles. Food Security, Agronomy for Sustainable Development, International Journal of Agricultural Sustainability, and Field Crops Research also emerge as key multidisciplinary sources in the CSA research topic.
3.1.3. Country Collaboration Network
Figure 4 depicts the top 45 countries’ collaboration network of the retrieved CSA documents, assigned into nine clusters. Detailed information on these clusters and the corresponding countries is given in Table 3. The size of the cluster represents the most collaborative country. As noted in Figure 4, Kenya (26) in the light blue cluster is the most collaborative country, followed by Tanzania with 13 links. Similarly, Germany (13) and South Africa (11) are the most collaborative countries in the red cluster, whereas Colombia (13), India (11), and Morocco (10) are the most influential countries in the light brown cluster. Zimbabwe (16) takes the lead in the yellow cluster, followed by the United Kingdom and Zambia, with 11 and 9 country links. Ghana, Switzerland, and Italy are the most influential countries in the green cluster, with 13, 9, and 9 association links, respectively. Furthermore, the Netherlands (21) and Mali (8) are the most collaborative countries in the purple cluster.
3.1.4. Main Keywords
Figure 5 depicts the frequently used keywords in the CSA published scientific articles. The core collection databases used in this review study provide two categories of keywords, namely, the author keywords and the keywords-plus (extracted from the titles of the cited references). Table 4 gives the topmost author keywords and keywords-plus generated using CSA published articles. Based on the author keywords analysis, the climate-smart agriculture keyword was used by approximately 58 authors, making it the most used keyword in CSA published scientific articles. Climate change, food security, and adaptation keywords were mostly used, appearing in 38, 23, and 19 CSA articles, respectively.
On the other hand, climate change is the most frequently used keyword-plus, appearing in 51 titles of cited references, followed by Africa, agriculture, sub-Saharan Africa, and food security, appearing in 47, 45, 32, and 30 titles of the cited references. The mapping of keyword occurrences resulted in four clusters, as shown in Figure 5. As noted in the figure, climate change, the leading keyword in the yellow cluster, is linked with other important keywords in CSA such as agriculture (red), food security (blue), crop production (green), farming systems, and smallholder (both in the yellow cluster). Such linkages suggest that the scientific community is increasingly paying attention to these keywords, with a common interest in advancing CSA research in Africa. Overall, the identified keywords are a combination of the three pillars of CSA and agricultural best practices.
3.1.5. Thematic Network
A thematic map is used to assess the evolution of themes or topics in the CSA research field. As shown in Figure 6, the thematic map is sub-divided into four quadrants, where the upper-right quadrant indicates the motor themes (hot topics); themes appearing in the upper-left quadrant are considered very specialized topics; and words in the lower right and lower left are termed basic themes and emerging/disappearing themes, respectively. Consequently, the scientific community pays greater attention to the hot topics appearing in the upper-right quadrant of Figure 6 within the CSA subject matter. These motor themes include “conservation agriculture”; “sustainable development”; “sustainable land development”; “breeding”; “broomrape”; and “chemical control”, among others. Similarly, “precision agriculture”; “remote sensing”; “aquaponics”; “agro-ecological gradient”; “farming systems”; “maize production”; “minimum tillage”; and “soil degradation”, in the upper-left quadrant, are well-developed and integral topics to the advancement of CSA research in Africa. Themes in the lower-left quadrant such as “pearl millet”; “agricultural intensification”; “sorghum”; “crop modelling”; “small farms”; “food systems”; “greenhouse gas emissions”; “agricultural transformation”; and “agroecology” are considered as emerging or disappearing with a low density and centrality These themes are considered to have marginal relevance to the CSA research field. Basic themes in the lower-right quadrant cover words such as “climate-smart agriculture”; “climate change”; “food security”; “climate change adaptation”; “precision farming”; “gender”; and “livestock”, among others.
4. Discussion
4.1. Salient Features of Climate-Smart Agriculture Research in Africa
Food security is at the greatest risk, particularly in sub-Saharan Africa, due to various factors that include, but are not limited to, uncertainties of climate change, market fluctuations, and land degradation [32], as well as the region’s ongoing population growth, which is projected to double by 2050 [3,4]. Several African countries have accepted a proposed solution of implementing CSA to tackle agricultural productivity challenges, thereby increasing food productivity, supporting adaptation strategies, building resilience to climate change, and minimizing the effects of greenhouse gas emissions [4]. There is substantial evidence that CSA has been welcomed in Africa. This notion is attributed to the number of countries that have already conceptualized and implemented the framework of CSA and the significant research output available from published agricultural-related scholars. Based on the current review study, CSA research in Africa commenced in 2000, as reported in Gandah et al. [33]. In the Gandah et al. [33] study, the authors explored the possibilities of using a simplified scoring approach in the context of low-tech precision farming to estimate millet yields, and the results were greatly encouraging. While CSA research progressed at a very minimal rate between 2000 and 2013, the research began to gain momentum from 2014, reaching a tremendous achievement in 2020, resulting in 56 published articles. There is no doubt that such significant growth can be attributed to African countries paying greater attention to the impacts of climate change, which manifests in drought, floods, and extreme temperatures on agriculture, and wanting to find possible solutions to minimize such impacts to increase productivity. This great progression suggests that the scientific community and all relevant stakeholders in the African continent are becoming more familiar with CSA applications and exploring avenues to enhance their knowledge for implementing the CSA framework. Implementation of CSA is also encouraging, particularly at a country level, where integration of both agricultural practices/technologies and the local relevant innovations that tend to uplift the three pillars of CSA can be fully realized [34].
Although the interest in CSA research in Africa is notable, only a few countries have taken the lead in advancing the research domain. For instance, considering the top ten leading countries in CSA research publications, only 40% of the countries appeared on the list. The corresponding author is usually based in Africa (e.g., Kenya, South Africa, Zimbabwe, and Mali). This can be seen to suggest that CSA research in Africa is still nascent, as it has been reported in Chandra et al. [11]. In general, there is a wealth of evidence available on CSA research in East Africa, particularly in Kenya, Ethiopia, Uganda, Burundi, and Tanzania; West Africa in Nigeria, Mali, and Ghana; and Southern Africa in South Africa and Zimbabwe. This plethora of evidence suggests that Africa can do much better if its countries expand and extend collaborations with neighboring countries and those abroad, particularly outside the continent. This review has shown that Africa still lacks in terms of international collaborations. It is also alarming to note that such collaborations are mostly between developing countries, such as South Africa, Kenya, Tanzania, and Zimbabwe, with strong collaborations with international countries such as the USA, Germany, the Netherlands, and Australia. While these collaborations are well appreciated, it is imperative to include under-developed countries in the CSA subject matter. This will be a stepping stone to implementing the CSA concept, realizing its benefits, and, consequently, achieving the much-needed agricultural transformation in sub-Saharan Africa.
According to keywords analysis, most research studies reported in Africa have focused on potential CSA technologies and practices, summarized in Table A1 of Appendix A. Much of these production systems are reflected in the main keywords network shown in Figure 5. The keywords are mostly under the low-cost sustainable agriculture practices umbrella, such as crop conservation, maize (Zea mays), fertilizers, precision agriculture, soil conservation, agronomy, agroforestry, legumes, remote sensing, and grazing land management, among others. The frequency of these keywords’ frequency agrees with the notion that most farmers/farming communities in Africa are exploring advanced technologies as part of good farming practices. Most of the low-cost sustainable agriculture practices identified in this review study are available. They have been implemented in some African countries, as evidenced in the selected scientific publications summarized in Table A1. In particular, there is a wealth of evidence of positive impacts of CSA on agricultural productivity, including applications of maize production systems, especially in South Africa [35,36], Zimbabwe [37,38], and Kenya [39,40].
CSA research in Africa has focused on conservation agriculture, sustainable development, sustainable land development, animal breeding, broomrape, and chemical control, which build on top of CSA practices. According to the documents assessed in this review, we have noted topics such as the precision agriculture; remote sensing; aquaponics; agro-ecological gradient; farming system; maize production; minimum tillage; and soil degradation parts of CSA research in Africa. As CSA research continues to progress in Africa, new emerging issues and more scientific knowledge are becoming imperative. Emerging issues identified in this review study include agricultural extension/intensification/transformation, farming systems, crop modeling, agroecology, pearl millet, and sorghum, among others. While these topics are not completely new in the CSA subject matter, they are considered important issues that constantly emerge during CSA conceptual framework discussions, mostly at country levels.
4.2. Progression and Adoption of Climate-Smart Agriculture Technologies in Africa
Forty-eight countries share mainland Africa and six islands totaling 54 sovereign African countries. According to the World Bank, only 14 (26%) have developed CSA country profiles. These are Benin, Côte d’Ivoire, Ethiopia, Kenya, Lesotho, Malawi, Mozambique, Rwanda, Senegal, Tanzania, The Gambia, Uganda, Zambia, and Zimbabwe. Despite the slow uptake, there are two highlights among the early adopters of CSA, demonstrating that the approach is beneficial [41].
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The current agricultural production pathway in Lesotho focuses on extensive animal grazing and expansion of cropland. It is characterized by a monoculture cropping system dominated by maize, which is unsustainable. The Lesotho Climate-Smart Agriculture Investment Plan (CSAIP) offered two alternative pathways for scaling up CSA by focusing on commercialization and a resilient landscape. The latter combines modern scientific knowledge with a traditional farming system, the Machobane Farming System. The MFS uses crop rotation, relay cropping, and intercropping practices to apply manure and plant ash to conserve soil moisture and replenish soil fertility that is highly adapted and resilient to climate change. As a result, CSA achieved increased productivity and incomes; enhanced food security and dietary diversity; reduced impacts of climate change on agricultural produce; and improved commercialization, employment opportunities, and rural livelihoods.
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Further, the CSA approach enhanced the reduction in soil erosion, addressed generation and carbon sequestration, promoted conservation biodiversity, and provided other public goods that accrue to society. Upon its success, the Government of Lesotho is currently implementing the second phase, referred to as the Smallholder Agricultural Development Project (SADP II). This phase supports transformative interventions for agricultural productivity and resilience at the farm and landscape levels; provides solutions at the institutional level to ensure the sustainability of agricultural outcomes; encourages commercialization that would contribute to improved livelihoods; and promotes better nutritional outcomes towards improved human capital development [41].
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Mali was involved in a multi-country effort coordinated by the World Bank to develop a national Climate-Smart Agriculture Investment Plan (CSAIP). The Malian CSAIP uses an established framework and builds on programs, policies, national strategic plans, and local, national, regional, and international institutions. Mali prioritized a set of 12 investments and actions required to boost crop resilience and enhance yields for over 1.8 million beneficiaries and their families by helping them adapt to climate change. The process used to develop this plan also supports engagement and capacity strengthening [41].
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Kenya established the Kenya Climate-Smart Agriculture Program (2015–2030) to deal with increased productivity, adaptation, and mitigation across production systems. Kenya’s demographics also indicate that 74% of the population reside in rural areas and that 11 million people are actively employed in primary production agriculture [42,43]. The agricultural sector in Kenya is categorized as Very Small Landholdings (0.3–3.0 ha), Medium Scale Production (3–49 ha), and Large-Scale Production of >50 ha of crops or >30,000 ha of livestock [44]. Most farmers still rely on traditional agricultural practices, and nearly 24% of the population is undernourished. The other key factor is that agriculture contributes 28% of the gross domestic product (GDP), and 80% of the total agricultural production units are at the small scale (<3 ha) of land area [2,4,42,43,45] (Kenya, therefore, had to develop the Kenya Climate-Smart Agriculture Program (2015–2030) to coordinate domestic and international CSA interventions to address a socio-economic challenge). Such long-term strategic policies are lacking in most African countries. It was noted that many initiatives in Kenya have elements of CSA but are not referred to as CSA, nor do they address them using a climate change perspective. Still, socio-economic considerations were more important in making decisions than climatic and environmental factors [46]. Nonetheless, given that Kenya has an existing framework, it is much easier to incorporate CSA concepts into existing practices.
Thus, the positive outcomes in the sampled projects that emphasize CSA have proven that the approach in agricultural production is sustainable and can uplift the living standards of smallholder farmers. The projects, however, have had a short lifespan of only 2–5 years. This, therefore, leaves a gap as there is little literature regarding follow-ups or sustained support to enable farmers to become self-reliant. For CSA to be more beneficial, CSA needs to be embedded into policy or long-term strategic plans. The benefits have addressed all the main pillars of CSA: sustainability and increasing productivity, adaptability and resilience, mitigation, and the spinoff benefit of gender mainstreaming. The overall effect has been changing in smallholder farmers’ mindset to deviate to crops suited for their respective agro-ecological zones for both consumption and cash crops.
A major theme of CSA technology that has witnessed rapid growth is precision farming [26]. The integration of Earth observation satellites, the Global Positioning System (GPS), and geographical information system (GIS) technologies has provided the expanded scope of precision agriculture practices vital for fine-scale (at the field) monitoring and mapping of crop phenology parameters and yield. In this regard, the review results show evidence that these precision agriculture practices have continued to provide more data to farmers supporting robust decision making under changing economic and environmental factors. The reality of climate change and its negative impact on the environment, socio-economic activities, and food security cannot be emphasized. Various approaches to CSA have been proposed and implemented on the continent. However, there is a missing link: the fusion of information technology into CSA suited for smallholder farmers. In this regard, the use of unmanned aerial vehicles (UAVs) or drones is proposed.
Regarding the adoption of drones for sustainable agricultural management, the uptake of drone technology has steadily grown from a global perspective, e.g., [7]. Notwithstanding this noticeable drone technology adoption growth globally, the present review results illustrate that drone use in the agriculture industry in the African continent remains minuscule, especially among the smallholder farmers, who have been identified as critical in ensuring food security on the African continent. It is opined that the continent’s agriculture industry stands a chance to be revolutionized and thereby lift the African populace out of poverty if the various barriers impeding the adoption of drone technology (such as cost, infrastructure, legislation, and human capital) are addressed.
4.3. Implications of Climate-Smart Agriculture Research for Policy and Decision Making
Nearly 74% of the continent’s countries do not have national Climate-Smart Agriculture Investment Plans (CSAIPs). Only 5%, namely, Ghana, Mali, and Niger, have CSAIPs under development. For a successful implementation of CSA, a framework provided by the CSAIPs must be established to guide the processes. However, CSA focuses specifically on agriculture, a multi-dimensional approach that includes commitments to enhancing livelihood benefits, ensuring food security, and promoting sustainability. Thus, CSAIPs provide a framework and processes and then incorporate the government programs, policies, and strategic plans by combining other inputs from stakeholders locally, nationally, regionally, and globally. Without CSAIPs, most CSA-based projects will be ad hoc and short-lived. CSA policies in the sampled African countries are anchored on the United Nations Framework Convention on Climate Change (UNFCCC) 22nd Conference of Parties in Marrakech, Morocco [47]. The Moroccan government launched the Adaptation of African Agriculture (AAA) Initiative, emphasizing investment needs for helping African countries cope with climate change risks to agriculture and best position themselves for a future of higher temperatures and uncertain precipitation. The AAA Initiative also builds on the Comprehensive African Agriculture Development Programme (CAADP), first launched in 2003 through the African Union. All the African countries featured in the analysis are signatories to the UNFCCC Paris Agreement. They have submitted their Nationally Determined Contributions (NDC), committing to adaptation to climate change and reducing greenhouse emissions [41]. These countries have also mainstreamed CSA as a core aspect of their long-term strategic plans in agriculture and formulated policies that govern the establishment, administration, collaboration, and funding aspects. The real benefits of CSA can only be achieved in the long term after understanding and mitigating any challenges as the new paradigm shifts. It is hoped that the African CSA investment strategies will be developed with urgency and with strong stakeholder engagement, expert input, and scientific evidence.
5. Conclusions
A bibliometric analysis study was conducted to assess and systematically synthesize the nature of CSA research’s salient features, such as developmental patterns, research collaborations, keywords, and emerging themes within the subject matter, in Africa. Annual scientific publications have substantially increased from 2014, reaching the highest number of outputs in 2020. African countries need to uplift their collaborations with sister countries as well as international organizations. Most collaborations are between developed countries, implying that under-developed countries are being left behind, yet the impacts of climate variability and change cut across the countries, with no regard to the country status. Adopting and integrating new CSA technologies (including drones) and big data applications (such as artificial intelligence and machine learning) is still nascent. The key implications of this study include (a) putting forth the argument that there is evidence that adopting CSA throughout the agricultural industry could revolutionize the sector, thereby lifting the African populace out of poverty, and (b) the CSA technologies are expected to change and be diversified, especially with the advent of the Fourth Industrial Revolution. The eminent changes in CSA technologies are expected to radically change the agricultural industry, suggesting that all the stakeholders, including policymakers, should be prepared to embrace these disruptive technologies. While CSA research in Africa has shown substantial progression in multidisciplinary aspects, there is still a gap in policy implementation. For the sub-Saharan region to reap the benefits of CSA, concrete actions must be undertaken to, among other things, promote the implementation of context-specific CSA technologies by farmers, avail appropriate funds to farmers, promote investments, and develop policy frameworks that are supportive of CSA.
Author Contributions
Conceptualization, all authors; methodology, P.M.B. and C.M.B.; software, P.M.B. and C.M.B.; validation, all authors; formal analysis, P.M.B. and C.M.B.; investigation, all authors; resources, P.M.B. and T.M.; writing—original draft preparation, P.M.B. and C.M.B.; writing—review and editing, all authors; visualization, P.M.B. and C.M.B.; supervision, T.M. and J.O.B.; funding acquisition, T.M. All authors have read and agreed to the published version of the manuscript.
Funding
The Centre for Transformative Agricultural and Food Systems (CTAFS) funded this research. The APC was funded by the Centre for Transformative Agricultural and Food Systems (CTAFS).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
The authors would like to thank the uMngeni Resilience Project and the South African Weather Service for supporting the writing of this paper. The authors wish to thank the anonymous reviewers for comprehensive feedback, that assisted to improve the quality of the manuscript. The views expressed in this paper are those of the authors.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A
Table A1
A summary of selected scientific publications on climate-smart agriculture studies in Africa published from 2000 to 2020. The information is only limited to published scientific articles. Hence, conference papers, proceedings, reviews, and books/book chapters are excluded in the summary. CA—corresponding author; PY—publication year, Ref #—reference number.
Ref # | CA, (PY) | Country | CSA Technology | Key Findings and Future Research Direction |
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[26] | Zakaria A, 2020 | Ghana | Precision agricultural farming |
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[48] | Musafiri CM, 2020 | Kenya | Farm-level soil fertility management and greenhouse gas emission (nitrogen application rate) |
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[49] | Shilomboleni H, 2020 | Kenya |
|
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[50] | Kganyago M, 2020 | South Africa | Snap-derived leaf area index (precision agriculture) |
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[12] | Gram G, 2020 | Uganda | Organic and mineral nitrogen applications |
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[51] | Ogada MJ, 2020 | Kenya | Livestock breeding |
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[27] | Maindi NC, 2020 | Kenya | Multivariate probit and ordered probit models (precision agriculture) |
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[16] | Oladimeji TE, 2020 | Nigeria | Soil conservation practices (e.g., animal manure, crop residue retention, inter-cropping, and crop rotation) |
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[35] | Abegunde VO, 2020 | South Africa | Social, technical, economic, and environmental compatibility |
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[15] | Paul BK, 2020 | Kenya | livestock intensification (on-farm forage cultivation, dairy breedings) |
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[17] | Ighodaro ID, 2020 | South Africa | Soil conservation |
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[52] | Abegunde VO, 2020 | South Africa | Organic manure, crop rotation, and crop diversification |
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[53] | Dadzie SKN, 2020 | Ghana | Precision farming |
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[13] | Rware H, 2020 | Uganda | Fertilizer optimization tool (components: an optimizer tool, a nutrient substitution table, and a fertilizer calibration tool) |
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[22] | Oyawole FP, 2020 | Nigeria | Gender and women empowerment |
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[28] | Olajire MA, 2020 | Nigeria | Precision farming (indigenous adaptations and climate-crop modeling system) |
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[39] | Kurgat BK, 2020 | Kenya | Crop and livestock diversity, irrigation, chemical fertilizers, and agroforestry |
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[29] | Mazarire TT, 2020 | South Africa | Precision agriculture |
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[54] | Mudereri BT, 2020 | Kenya | Precision agriculture |
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[55] | Moshia ME, 2019 | South Africa | Crop management, agronomy, precision farming |
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[56] | Zougmor RB, 2019 | Mali | Adaptability, adoption, mitigation, resilience |
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[37] | Mutenje MJ, 2019 | Zimbabwe | Productivity, sustainability, resilience (risk management), soil and water management |
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[57] | Sanou L, 2019 | Burkina Faso | Land use, conservation of biodiversity, agroforestry, soil management |
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[58] | Makate C, 2019 | Ethiopia | Institutional credit (financing) and extension services |
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[18] | Makate C, 2019 | Ethiopia | Conservation agriculture, drought-tolerant maize, and improved legume varieties, adaptation, productivity |
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[14] | Hammed TB, 2019 | Nigeria | Productivity, organic fertilizer |
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[21] | Bashagaluke JB, 2019 | Ghana | Soil and crop management |
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[59] | Otieno NE, 2019 | South Africa | Productivity, pest control, crop management, organic farming |
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[40] | Kiwia A, 2019 | Kenya | Sustainability, intercropping |
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[60] | Kamara A, 2019 | Sierra Leone | Productivity |
|
[38] | Baudron F, 2019 | Zimbabwe | Productivity |
|
[61] | Kpadonou RAB, 2019 | Ethiopia | Adoption of modern seeds and the use of manure |
|
[62] | Antwi-Agyei P, 2018 | Ghana | Adaptation, mitigation |
|
[63] | Mango N, 2018 | Zimbabwe | Irrigation farming |
|
[64] | Paul BK, 2018 | Kenya | Environmental degradation, productivity, crop intensification, inorganic fertilizer, improved seeds, zero-grazing, crossbreeds, GHG emissions |
|
[36] | Oosthuizen PL, 2018 | South Africa | Animal husbandry, sustainability |
|
[65] | Makate C, 2018 | Zimbabwe | Adoption rates of CSA, socio-economic analysis |
|
[66] | Chakona G, 2018 | South Africa | Productivity |
|
[67] | Mathews JA, 2018 | South Africa | Resilience, sustainability |
|
[68] | Bhatasara S, 2018 | Zimbabwe | Resilience, adaptation, sustainability |
|
[20] | Setimela P, 2018 | Zimbabwe | Mitigation, drought-tolerant maize varieties, multi-stress maize germplasm, conservation agriculture |
|
[69] | Thornton PK, 2018 | Kenya | Framework, research investments, adaptability |
|
[70] | Magombeyi MS, 2018 | South Africa | Water management, resilience. |
|
[71] | Hammond J, 2017 | Kenya | Adaptation, productivity, GHG emissions |
|
[72] | Notenbaert A, 2017 | Kenya | Innovation, food security, adaptation, mitigation, investment |
|
[73] | Shikuku KM, 2017 | Kenya | Productivity, adaptation, livestock management |
|
[74] | Nyasimi M, 2017 | Tanzania | Innovation, adaption, agroforestry, weather information |
|
[19] | Thierfelder C, 2016 | Zimbabwe | Soil degradation, conservation agriculture, manual seeding systems |
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[75] | Kimaro AA, 2016 | Tanzania | Conservation agriculture, productivity, environmental sustainability, resilience, adaptability, GHG emissions |
|
[76] | Schut M, 2016 | Burundi | Innovation, sustainability, intensification, constraints, productivity |
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[77] | Ncube M, 2016 | South Africa | Adaptation, mitigation |
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[78] | Thierfelder C, 2016 | Zimbabwe | Conservation agriculture, direct seeding |
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[79] | Murage AW, 2015 | Kenya | Productivity, gender mainstreaming, push and pull technology, crop management, soil management |
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[80] | Nyamadzawo G, 2015 | Zimbabwe | Soil management (fertility), adaptation, sustainability, variability |
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[81] | Gyau A, 2014 | Kenya | Cocoa agroforestry systems and trees plantation and shades |
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[82] | Maine N, 2010 | South Africa | Precision farming (variable-rate nitrogen application) |
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[83] | Cho MA, 2010 | South Africa | Precision farming (hyperspectral remote sensing) |
|
[84] | Maine N, 2007 | South Africa | Precision farming (maize yield modeling) |
|
[33] | Gandah M, 2000 | Niger | Low-tech precision agriculture (manure) |
|
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Figures and Tables
Figure 1. Number and type of documents retrieved and analyzed in the review study of climate-smart agriculture research in Africa.
Figure 2. Annual publications of climate-smart agriculture research articles showing a steady increase from an average of 1 publication per year between 2000 and 2010 to 56 publications in the year 2020.
Figure 3. Top ten leading countries in climate-smart agriculture research publications. The ranking is based on the corresponding author’s country. SCP: single-country publications; MCP: multiple-country publications.
Topics used in Scopus and Web of Science collection databases to search and retrieve published documents on climate-smart agriculture in Africa.
Search Topic | Areal Restriction | Areal Restriction |
---|---|---|
“climate-smart agriculture” | [AND] “climate change” | [AND] “Africa” |
“climate-smart agriculture” | [AND] “smart farming” | [AND] “Africa” |
“climate-smart agriculture” | [AND] “governance” | [AND] “Africa” |
“climate-smart agriculture” | [AND] “farmers” | [AND] “Africa” |
“climate-smart agriculture” | [AND] “decision making” | [AND] “Africa” |
“climate-smart agriculture” | [AND] “agricultural policies” | [AND] “Africa” |
“ climate-smart agriculture “ | [AND] “technologies” | [AND] “Africa” |
“Precision agriculture” | [AND] “Africa” | |
“Precision farming” | [AND] “Africa” |
Top ten total citations per country and top publication sources.
Country | Total Citations (Average Article Citations) | Top Relevant Sources (Number of Articles) |
---|---|---|
Netherlands | 683 (48.8) | Agricultural Systems (10) |
Kenya | 159 (8.0) | Frontiers in Sustainable Food Systems (9) |
Zimbabwe | 154 (14.0) | Climate Change Management (8) |
Mali | 136 (13.6) | Sustainability (Switzerland) (7) |
United Kingdom | 82 (4.6) | Food Security (6) |
Italy | 68 (11.3) | Agronomy for Sustainable Development (5) |
Spain | 63 (63.0) | International Journal of Agricultural Sustainability (5) |
Burundi | 61 (61.0) | Agriculture and Food Security (4) |
USA | 49 (5.0) | Field Crops Research (4) |
Zambia | 46 (11.5) | Journal of Cleaner Production (3) |
Clusters of countries’ collaborations in climate-smart agriculture research in Africa.
Cluster | Leading Countries Per Cluster | Remarks |
---|---|---|
Red | Germany (13), South Africa (11) | Countries in this cluster have significantly collaborated with countries in yellow, green, and light blue clusters |
Green | Ghana (13), Switzerland (9), Italy (9) | Ghana, as the leading country in this cluster, has collaborated with countries in the same cluster and the yellow, red, purple, and light blue clusters |
Dark blue | USA (20), Ireland (12) | The USA has collaborated with most countries across the clusters |
Yellow | Zimbabwe (16), UK (11), Zambia (9) | Zimbabwe has collaborated with most countries across the clusters, except for the dark brown cluster |
Purple | Netherlands (21), Mali (8) | The Netherlands has shown a significant collaboration across most countries and clusters |
Light blue | Kenya (26), Tanzania (13) | Kenya is the most leading country in collaborations across all the clusters |
Light brown | Colombia (13), India (11) | Countries in this cluster have collaborated with most African countries, including Zimbabwe in the yellow cluster and Tanzania in the light blue cluster |
Dark brown | Mexico (5), Brazil (5) | Collaborations in this cluster are mostly with Kenya, the Netherlands, the USA, and Australia |
Pink | Australia (14) | Significant collaborations between Australia and African countries such as Kenya, Zimbabwe, Morocco, and Tanzania |
Most relevant keywords.
Author Keywords (Number of Articles) | Keywords-Plus (Number of Articles) |
---|---|
Climate-smart agriculture (58) | Climate change (51) |
Climate change (38) | Africa (47) |
Food security (23) | Agriculture (45) |
Adaptation (19) | Sub-Saharan Africa (32) |
Sub-Saharan Africa (18) | Food security (30) |
Agriculture (17) | Smallholder (25) |
Mitigation (14) | Precision agriculture (24) |
Precision agriculture (14) | Maize (20) |
Sustainable intensification (12) | Adaptation (18) |
Conservation agriculture (11) | Sustainable development (15) |
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© 2021 by the authors.
Abstract
Funders and governments are promoting climate-smart agriculture (CSA) as key to agricultural adaptation under climate change in Africa. However, with its progressions still at the policy level and framework description, there is a need to understand the current developments and activities conducted within the CSA research field. We conducted a scientific mapping and analyses of CSA research studies in Africa to understand the (i) thematic trends, (ii) developments, (iii) nature of collaboration networks, and (iv) general narratives supporting the adoption and application of CSA in Africa. Results show that several African countries had endorsed CSA as an approach to addressing agricultural productivity challenges, supporting adaptation strategies, and building resilience to climate change. However, a majority do not have national Climate-Smart Agriculture Investment Plans (CSAIPs). Additionally, CSA research in Africa is still developing, with only a few countries dominating the research outputs. For a successful implementation of CSA, a framework provided by the CSAIPs must be established to guide the processes. This will provide a framework to guide the integration of government programs, policies, and strategic plans by combining other inputs from stakeholders to support decision making and implementation of CSA.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details




1 Centre for Transformative Agricultural and Food Systems, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa;
2 South African Weather Service, Private Bag X097, Pretoria 0001, South Africa;
3 Centre for Transformative Agricultural and Food Systems, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Scottsville, Pietermaritzburg 3209, South Africa;