The irony of climate-smart agriculture is particularly evident in central Tanzania, where farmers cultivating millet, a crop promoted as climate change solutions, face the most difficult livelihood choices. This study examines the livelihood strategies of millet farmers in the Manyoni and Bahi districts of central Tanzania, including the factors influencing these choices. A triangulated clustering analysis based on the activity approach classified the 417 farming households into five distinct clusters, where income levels, commercialization indices, and food security scores were compared. A multinomial logit model examined the drivers of livelihood strategy choices. The results identify five distinct livelihood strategies, with the majority of farmers engaging in multiple economic activities, such as off-farm activities, livestock keeping, and cultivating commercial crops. Cluster 1 represents 28% of households, with the highest income, food security, and market participation, primarily due to finger millet cultivation. In contrast, Cluster 4, comprising farmers who grow only pearl millet, is the poorest, with low income and limited market participation. The key drivers of cluster choices included education, age, extension services, and geographical location. Findings highlight that livelihood strategies among millet-producing households yield distinct welfare outcomes; thus, policies and interventions should prioritize livelihood combinations that result in improved food security and economic resilience.
The National Key Ecological Functional Zones (NKEFZs) are responsible for the supply of agricultural products and ecological protection. This study analyzes the interplay between agricultural entrepreneurship (EN) and agricultural economic scale (AS) using county-level panel data (2010–2022). To decompose regional disparities and their sources, we employ the Dagum Gini coefficient. Spatial convergence models are applied to examine whether development gaps across NKEFZs are narrowing. Furthermore, the coupling coordination degree model and a panel vector autoregressive model are used to assess systemic synergy and dynamic interactions. The results show that there are significant differences between EN and AS among different NKEFZs, and that the regional differences among different NKEFZs are the main sources of overall differences. There is σ-convergence between AS and EN only in some NKEFZs, and the convergence of the two areas is often different. There is no absolute β-convergence of agricultural development. Although the coupling coordination degree is generally not high, there is a tendency to move to a higher stage. There exists short-term dynamic interplay between AS and EN. In the long run, both variables are predominantly shaped by their own historical trajectories, while cross-variable spillover effects remain relatively weak.
Balanced fertilisation is widely regarded as an effective agronomic strategy that enhances crop productivity and soil health, playing a vital role in sustainable agriculture, especially in salinity-affected regions. Despite their potential, the effect of balanced fertilisers on crop yield in practical agricultural contexts remains poorly understood. The aim of this study was to examine the impact of balanced fertiliser use on tomato yield, production cost, profit, average selling price, and pesticide spray times in salinity-prone areas of Bangladesh. This study employed a randomised encouragement design to establish causality while addressing endogeneity, spillover effects, and non-compliance. Results demonstrate that balanced fertilisers increased tomato yield by 3,307.35 kg/ha and elevated the average selling price by 1.09 Taka/kg. Notably, pesticide spray frequency decreased by nearly three times (2.95), and the use of chemical fertilisers declined, while organic fertiliser application increased by 3061.90 kg/ha. Although production costs rose significantly, profits increased by 33,672.99 Taka/ha; however, this increase was not statistically significant. The benefits were particularly pronounced among less experienced farmers, highlighting the potential for this practice to promote sustainability. Overall, the findings underscore that balanced fertilisation boosts yields, reduces reliance on chemical inputs, and contributes to environmentally sustainable farming practices.
The System of Environmental-Economic Accounting for Agriculture and Social Accounting Matrix multiplier model was applied to analyze the effects of a carbon tax imposed on dairy production and exports. By combining economic and environmental effects, this study evaluates the expediency and effectiveness of carbon taxes as a tool for agricultural emission reduction policy in a European area of natural constraints. In the analysis, industry-specific tax demonstrated greater efficiency in reducing emissions. Furthermore, reductions in cattle numbers, and consequently in animal manure, fertilizer, and plant protectants, would have additional positive effects on water and soil quality. However, the carbon tax resulted in a significant decline in agricultural income and employment, leading to extensive knock-on effects on the downstream and upstream industries. Additionally, implementing a unilateral tax would result in a comparative disadvantage for both agricultural production and trade. Consequently, if policymakers choose not to decrease farm production in Europe, agricultural subsidies tied to environmental performance may be a more viable option for mitigating agricultural emissions. Moreover, among agri-food stakeholders, a reform of agricultural subsidies may be socially more acceptable and, therefore, politically less contentious than a carbon tax.
Temporal crop diversification is increasingly promoted to enhance the sustainability and resilience of European agricultural systems, yet long-term field-level evidence on how crop sequences evolve remains limited. This study investigates changes in crop sequence typologies and complexity in Flanders between 2008 and 2023 using Geo-Spatial Application data, with particular attention to potato return times given this crop's growing economic importance and stringent phytosanitary requirements. Crop sequence typologies were identified for two eight-year periods, while complexity was assessed using the Rotational Complexity Index. Potato return times were analysed separately using a backward-looking approach. Flemish agriculture was dominated by a limited number of typologies, particularly permanent grassland, root crop sequences, and cereal-dominated systems. Although 38.5% of the agricultural area changed typology between the two periods, transitions occurred mainly among a restricted set of dominant systems. Changes in complexity were significant but small. Potato return times were mostly three or four years, with only modest shifts towards longer intervals, suggesting persistent agronomic and economic constraints. Overall, Flemish crop sequences are changing structurally, but without substantial increases in complexity. The proposed approach provides a transferable framework for monitoring temporal diversification and a basis for investigating the drivers of changes in crop sequence complexity.
Smallholder farmers in the Global South largely rely on seed accessed from farmer-managed seed systems (FMSS) for their seed security. Community seed banks (CSBs) have emerged to manage and enhance the diversity of plant genetic resources for food and agriculture (PGRFA) and make it accessible to farmers. However, the connections between farmers' access to crop genetic diversity and food security and the contributions of CSBs remain understudied. We address this gap by exploring the following questions: (1) How does access to PGRFA affect food security among smallholder farmers in the Global South? (2) How do CSBs contribute in this regard? (3) What are the gender-specific aspects and implications of these findings? Using Zotero, we conducted a narrative literature review with a qualitative analysis of 85 relevant peer-reviewed publications. Our findings indicate that access to PGRFA positively influences the six dimensions of food security, although to varying degrees, and that well-functioning CSBs contribute substantially to this end. Women often benefit from being CSB members. However, the technical and financial sustainability of many CSBs is poor and their outreach is limited. Enabling political, legal and institutional environments is integral to realizing the food security potential of FMSS and CSBs.
Clarifying spatiotemporal dynamics and driving mechanisms of paddy field conversion between grain and non-grain uses in the Pearl River Delta (PRD) is important for understanding agricultural sustainability in rapidly urbanizing regions. Frequent cloudy weather, fragmented farmland, and limited high-resolution data have constrained existing methods, and systematic analyses of cropland conversion pathways remain limited. We integrated multi-source remote sensing with a Random Forest model coupling optical and multi-temporal radar data to map paddy field conversions from 2016–2023 (OA: 93.92%; R2 > 0.88). Non-grain conversion areas for 2016–2018, 2018–2020, and 2020–2023 were 153,143 ha, 151,801 ha, and 135,219 ha, consistently exceeding grain re-conversion areas (134,716 ha, 117,762 ha, and 112,797 ha). Transitions were more active in peripheral than core areas. Non-grain conversion was statistically associated with agricultural labor (+1 ha/100 workers) and showed a negative association with fertilizer use (−0.06 ha/ton) and farmland aggregation (−431.55 ha/unit). Macro-level factors exerted indirect effects via labor allocation and land-use efficiency. Grain re-conversion showed strong associations with agricultural labor (+3 ha/100 workers) and farmland aggregation (+74.25 ha/unit), with weaker macro-level ties. These findings provide a technical pathway for cloudy, fragmented regions and reveals asymmetric transition patterns that may inform farmland regulation, non-grain conversion governance, and food security strategies.
Agriculture is the backbone of East African economies, yet it is highly vulnerable to climate change and rapid population growth, threatening the food security and livelihoods of millions of smallholder farmers. In response, Smart Farming Technologies (SFTs), including precision irrigation, Geographic Information System (GIS) and ICT-based extensions, have been introduced to enhance resilience and productivity. However, the widespread adoption of these technologies remains low, and there is a fragmented understanding of their actual economic and agronomic impacts on smallholders. This systematic review aimed to map the SFTs utilized in East Africa, evaluate the factors affecting their adoption, and critically assess their impact on agricultural productivity and smallholders' income. Following PRISMA guidelines, 94 articles were synthesized using a mixed-methods approach, combining quantitative analysis of the full dataset with an in-depth qualitative focus on 33 key publications. The findings revealed that small-scale irrigation, ICTs, GIS, and remote sensing are the most prevalent technologies in the region. Their adoption is dictated by a complex interplay of socio-economic, technical, and policy-related factors. Crucially, the review confirms that SFT adoption positively impacts agricultural productivity, food security, and household income, though significant barriers to equitable implementation remain. To address climate change and food insecurity in East Africa, policies must target these specific socio-technical barriers to ensure that SFTs are accessible and profitable for smallholders.
Enhancing social sustainability in agriculture has gained attention as societal expectations around food production evolve. For many in the public, dairy cows on pasture are an idealized representation of socially acceptable livestock production. Expectations regarding food safety, worker welfare, and animal well-being influence purchasing decisions and shape the dairy industry’s social license to operate. This paper examines socially sustainable dairy farming in the United States from a multi-attribute, multi-stakeholder perspective by comparing public and farmer views on six attributes: food safety, animal welfare, animal health, cattle access to grazing, rural landscape contributions, and worker livelihood. Using data from a national public survey (N = 1020) and a mail survey of Wisconsin dairy farmers (N = 279), relative importance weights were estimated and compared across groups. Seemingly Unrelated Regression models assessed how public, farm, and farmer characteristics relate to these attributes. Results show convergence between the public and farmers on the importance of food safety and animal health. However, clear divergence emerges regarding cattle access to grazing and animal welfare, which the public prioritizes more strongly than farmers. The analysis highlights that social sustainability expectations are heterogeneous and vary by farm, farmer, and individual characteristics. Reconciling these differing priorities will require multi-stakeholder engagement to improve the social sustainability of dairy farming.
Declining soil fertility remains a major constraint to agricultural productivity and livelihoods of smallholder farmers in Uganda. This study assessed the adoption of soil fertility management practices and their association with perceived soil fertility status among smallholder farmers in Kabarole District and Fort Portal City, Western Uganda. A cross-sectional survey was conducted among 300 randomly selected farmers. Descriptive statistics and binary logistic regression were used to analyze the relationship between perceived soil fertility status and adoption of management practices. Results showed that 77.3% perceived their soils as having low fertility, mainly due to continuous cropping, soil erosion, and deforestation. Conservation tillage (53%), mulching (46%), and manure application (35%) were the most adopted practices, although overall adoption remained low. Moreover, binary logistic regression revealed that conservation tillage (OR = 1.92, p = 0.037) and manure application (OR = 3.34, p = 0.002) were significantly associated with farmers reporting low soil fertility, whereas chemical fertilizers (OR = 0.36, p = 0.022) and intercropping (OR = 0.42, p = 0.011) were associated with fertile soils. These findings highlight the need to promote integrated soil fertility management practices and validate farmers' perceptions through laboratory soil analyses to guide evidence-based interventions.
This study provides a systematic literature review examining the intersection of gender, rural transformation, and the roles of institutions, policies and investments (IPIs) in Developing Countries. Rural transformation, characterized by structural changes in livelihoods, agriculture and community dynamics, offers significant opportunities for women’s empowerment but also reveals persistent gender inequalities. Our analysis draws from 104 studies published between 2015 and 2024 that focused on the specific experiences of rural women. The findings demonstrate that institutions often act as both enablers and barriers to women’s economic participation and leadership. Investments in education, healthcare, and rural infrastructure have transformative potential; however, implementation challenges persist, particularly at the local level. The policies designed to promote gender equality often lack effectiveness because of sociocultural barriers and limited community engagement. This study contributes to the discourse by addressing the gap in research linking gender-focused rural transformation and by providing evidence-based recommendations for integrated and inclusive policy approaches. The analysis highlights the importance of localized strategies that align with social and economic institutions, investment, and policy interventions to achieve equitable and sustainable rural development.
The adoption of sustainable agricultural practices remains a critical challenge in developing countries. This study moves beyond traditional linear models to employ a multi-faceted machine learning (ML) approach, aiming to predict biopesticide adoption and to uncover the most influential behavioural constructs of farmers towards biopesticide adoption intention in Bihar, India. The data were collected from 468 farmers across four districts of Bihar, using a structured questionnaire to measure behavioural constructs. An analytical framework was deployed by using seven supervised ML algorithms (including Random Forest, Support Vector Machine, Logistic Regression, K-nearest neighbors, naive Bayes, Neural Network and Decision Tree), which were trained and rigorously tested to predict adoption behaviour. The Random Forest model demonstrated the highest predictive efficacy, with an accuracy of 78.7% and a robust Kappa score of 0.571. A consistent finding across all models reported the importance of subjective norms and attitude as the primary factors associated with adoption, while perceived benefits were placed in the last position. This study provides a data-driven blueprint for designing targeted interventions. By leveraging social networks to influence subjective norms and increasing communication to address the specific attitudinal and practical barriers of farmers, the government and policymakers. This can create more effective strategies to accelerate the biopesticide adoption for sustainable agricultural practices.
While agricultural mechanization is central to rural transformation in China, its ecological implications remain unclear. This study examines whether mechanization promotes agricultural green development or induces input-intensive ecological trade-offs. Using a balanced panel of 31 Chinese provinces from 2011 to 2023, we construct an entropy-weighted Green_Ecology index based on fertilizer, pesticide, and plastic film use, as well as forest coverage. We estimate the relationship between mechanization and Green_Ecology performance with two-way fixed-effects models and conduct robustness checks using dynamic system GMM and a permutation placebo test. Results show that higher mechanization intensity is significantly associated with a lower Green_Ecology score; a one-standard-deviation increase in mechanization corresponds to an approximately 3% decline relative to the sample mean. Decomposition analysis indicates that this negative association is mainly driven by increased use of fertilizer and plastic film. Heterogeneity and threshold analyses suggest that the relationship may vary with forest endowment, although evidence for a sharp forest threshold is not decisive. These findings suggest that green-compatible mechanization should be viewed not merely as machinery expansion but as the integration of input-saving technologies, precision services, and plastic film recycling systems that decouple mechanization from chemical-input intensification.
Climate physical risk exerts complex nonlinear effects on agricultural carbon footprint pressure (ACFP), yet the underlying cost and innovation mechanisms remain insufficiently examined. Using balanced panel data from 30 Chinese provinces over the period 2000-2023, this study empirically investigates the nonlinear impact of the Climate Physical Risk Index (CPRI) on ACFP. The findings reveal a statistically significant inverted U-shaped relationship, with a turning point at CPRI = 50.15307. Below this threshold, climate physical risk intensifies ACFP, reflecting a cost effect; above it, risk mitigates ACFP, indicating an innovation effect. Mechanism analysis shows that on the left side of the inflection point, green finance moderates the cost-induced increase in ACFP, whereas on the right side, digital inclusive finance reduces ACFP through a chain mediation pathway involving agricultural digital innovation. Moreover, the inverted U-shaped relationship is more pronounced in provinces northwest of the Hu Line and under high climate policy uncertainty. The study concludes by proposing targeted policy measures, including the deployment of differentiated financial instruments and the incorporation of ACFP into local performance evaluation systems, to promote a coordinated governance framework for pollution reduction, carbon mitigation, and climate adaptation in agriculture.
Sustainable intensification is a promising way to improve agricultural productivity and environmental sustainability. However, limited studies to date have focused on its impacts on productivity, profitability, and environmental outcomes. Using survey data from 1179 households in the eastern Indo-Gangetic Plains of Nepal and an endogenous switching regression (ESR) model, we assess the impact of zero tillage (ZT) wheat on productivity, cost, profits, total energy use (TEU), and greenhouse gas emission intensity (GHGI). Under the assumption of the ESR model, we find that ZT wheat significantly increased productivity by 23% (610 kg/ha) and profitability by US$ 151 per hectare, while reducing TEU by 8% (1167 MJ/ha) and GHGI by 23% (115 kg CO2 equivalent/ton). However, these benefits are unevenly distributed: higher productivity and profitability gains are observed at the upper quantiles of these outcomes, whereas environmental improvements are more evident around the medium quantiles of TUE and GHGI. Our findings indicate that the adoption of ZT wheat depends primarily on farmers’ willingness to take risks and labour shortages. Given the findings, policy measures to promote conservation tillage are essential to mitigate the risks and promote wider adoption among smallholders in the Indo-Gangetic Plains of South Asia.
We investigated the motivations of youth in Cameroon to engage in cocoa farming, their challenges, their participation in agricultural programmes, their access to services and their performance, and the factors influencing these. A quantitative approach focused on young cocoa farmers, beneficiaries and non-beneficiaries of the New Generation Programme was used. We surveyed 309 young cocoa farmers selected through a multi-stage stratified sampling. Data were analysed using descriptive statistics, inferential tests, and regression analysis. Cocoa cultivation is mainly driven by farm inheritance, potential income, and its popularity. Major challenges were climate change, labour scarcity, capital availability, and pests and diseases. Programme participation was positively associated with age, experience, number of plots, and total cocoa lands. BMP adoption intensity was positively related to labour hiring, programme membership, and access to support. Cocoa yield and net returns were positively associated with BMP adoption intensity, age of productive plots, total cocoa land, gender, and experience. Certification was positively associated with net returns only. These findings highlight the importance of gender-responsive policies and climate adaptation strategies. They suggest that cocoa yield and profitability can be improved by providing youth with support to increase BMP adoption. We conclude with recommendations for policymakers and value chain actors.
The impact of climate change has gained extensive attention over the past few decades, while its impact on Sub-Saharan Africa (SSA), a region where agriculture is particularly vulnerable to climate variability, still requires more in-depth and focused research, including its effects on food security. Using panel data from 1980 to 2021 , this study investigates the effects of climate change (temperature and rainfall) and ecological footprints on food security in SSA and its four sub-regions, including pathways through inflation and trade. Results show that increases in temperature and ecological footprints improve food security in SSA. Increased rainfall decreases food security in Western SSA but increases it in Middle and Southern SSA. Temperature improves food security in Eastern and Western SSA, while ecological footprints improve food security in Eastern, Western and Southern SSA. Increases in temperature and ecological footprint improve trade, while an increase in rainfall and temperature reduces inflation. However, increases in ecological footprint increases inflation. we recommend climate-resilient agriculture, strengthening climate information and early warning systems and expanding irrigation infrastructure. Region-specific strategies include the adoption of flood-tolerant crops in Western SSA, sustainable resource management in Southern SSA, and the scaling up of climate-smart agriculture in Eastern SSA. fiscal and monetary policies should be put in place to stabilize food prices.
The cooperation dilemma resulting from strengthening the farmland property rights of farmers has gradually emerged, challenging certain developing countries. In this paper, the social ecosystem framework is used, and irrigation governance in rural China is taken as an example. Based on 1619 respondents survey data, an ordered regression model and propensity score matching method are used to analyze the impact of strengthening farmland property rights on rural collective action. The results show that strengthening farmland property rights can promote the formation of irrigation cooperation. Strengthening farmland property rights has induced new land management methods that enhance both village leadership and social capital. Thereby, critical factors in the irrigation social ecosystem are improved, which ultimately increases the willingness of farmers to participate in cooperative production. The research findings of this study provide insights for developing countries on how to synchronously promote land reform and boost both economic and social development.
Implementation of agroecological innovations tends to be long-term processes, with the practices of one year often linked to those of previous years. However, previous studies have focused on understanding drivers of adoption at farm level, with adoption measured at a point in time. In this study, we use a decade of panel data from the Permanent Agricultural Survey in Burkina Faso from 2010 to 2020 and machine learning approaches, to model adoption rates of agroecological innovations at the provincial level as an autoregressive process. This modeling approach allows us to exploit the time series nature of our dataset to forecast future adoption rates. Our results showcase the potential of machine learning algorithms to improve the forecasting of agroecology adoption rates and provide a model that can be used as a base for proposing interventions to support the adoption of agroecological innovations. The LSTM model reached a R & sup2; of 75% compared to 27% for the ARIMA family baseline model. The framework we proposed allows the identification of priority areas for targeted interventions and provides a foundation on which future studies can be built to predict and track agroecology adoption rates over time.
Land fragmentation and rural aging present significant challenges to sustainable agriculture in Vietnam's Red River Delta (RRD). This study examines how demographic shifts, especially an aging population, interact with land consolidation to shape farming practices and labor dynamics. Using a mixed-methods approach, we surveyed 600 households and conducted 60 in-depth interviews across 13 communes from 2020 to 2022. Using the Kruskal-Wallis test, our study highlights the declining youth interest in agricultural pursuits. A Mann-Whitney U test revealed that farmers in their early forties to early fifties expressed the high level of confidence in adopting sustainable practices. Despite consolidation efforts, average farm size remains just 0.22 ha, constraining economies of scale and accelerating youth outmigration. Based on these findings, we recommend targeted policies that increase access to consolidated land for younger farmers, including participatory land exchanges, subsidized mechanization, credit for high-value crop ventures, and tailored extension services. For older farmers, support should focus on reducing physical labor demands and improving profitability through cooperative services and simplified mechanization. Thus, addressing age-specific needs can help retain youth and enhance the long-term sustainability of smallholder agriculture in Vietnam.
