Search Results (1,866)

The rainfed paddy farming system faces profound vulnerabilities due to daily climate non-stationarity. This mixed-methods study in Central Java analyses daily climate signals, total rice production, and household adaptation over 25 years (2001–2025). Moving beyond simple correlation, a Principal Component Regression model integrating five climate variables and three agronomic confounders reveals a profound climate–production decoupling. The composite climate index explains only 7.9% of total production variation, while non-climate factors account for 92.1%. Physical stability is maintained through asymmetric temporal scheduling and a distinct hierarchy of responses, employing active, planned adaptations alongside passive, reactive coping. However, quantitative household evaluation reveals this tonnage stability incurs severe hidden costs; the titip gabah post-harvest system maintains a high Yield Stability Index (0.93) but yields a negative Return on Storage (−7.15%), functioning as a risk-mitigation buffer rather than a profit-maximising tool. Furthermore, climate anomalies drive the progressive alienation of traditional ethnoclimatological knowledge, forcing a cognitive shift toward hybridised decision-making. To prevent passive coping from evolving into systemic maladaptation, we propose a stratified policy framework ranging from village-level knowledge integration and Subdistrict daily risk warnings to regency-level subsidies targeted at smallholders (<0.5 ha). Full article

Accurate maize distribution information is critical for crop-area statistics, food-security assessment, and agricultural monitoring, but large-scale maize-mapping remains difficult in regions with limited reference samples, heterogeneous crop calendars, and frequent optical data gaps. This study proposes a phenology-adaptive maize mapping framework based on Sentinel-2 time-series imagery and an Enhanced Red-edge NDVI (ENDVIre). ENDVIre was constructed from the Sentinel-2 red-edge 4 and red-edge 2 bands to enhance the spectral response of maize during the silking-to-grain-filling stage, when maize develops a dense canopy and high chlorophyll content but is often confused with soybean. The framework first reconstructed the NDVI time series using an upper-envelope-constrained Whittaker smoother to identify key phenological stages, including sowing–emergence, vigorous growth, and maturity–harvest. NDVI, ENDVIre, and LSWI were then integrated into an interpretable decision-tree model with phenology-aligned time windows to distinguish maize from soybean, rice, wheat, and other non-maize backgrounds. The method was evaluated in six representative maize-growing regions across the United States, Brazil, China, Kenya, and Ukraine, covering different crop calendars, field sizes, and agricultural systems. The mean overall accuracy, F1-score, and Kappa coefficient across the six regions reached 93.27%, 93.14%, and 0.8652, respectively. Cross-year experiments in a winter-wheat–summer-maize rotation region from 2020 to 2024 achieved overall accuracies of 89.80–96.80%, while spatial-transfer experiments in six independent regions achieved overall accuracies of 87.40–95.40%. A comparison with existing high-resolution maize products in the Huang-Huai-Hai Plain further showed that the proposed method better balanced omission and commission errors. These results indicate that ENDVIre-based phenology rules provide an interpretable and transferable solution for maize mapping under limited-sample conditions, although persistent cloud contamination and fragmented smallholder landscapes remain important challenges. Full article

Calibrating compensation programs for chemical-fertilizer reduction requires reliable evidence on farmers’ preferences across reduction practices and policy instruments. Existing choice-experiment evidence treats reduction as either a single aggregate attribute or mutually exclusive practices, specifies compensation independently of the practice bundle, and underuses the distinction between smallholders and new agricultural operating entities (NAOEs) in heterogeneity analysis. We surveyed 1066 rice farmers across six counties and districts of Jiangsu Province using a multi-binary-attribute choice experiment that represented five fertilizer-reduction measures (soil-testing-based fertilization, deep placement, organic substitution, crop rotation, and straw return) as separate binary attributes, with a cost-proportional compensation rate; estimation used mixed logit. Non-monetary preferences vary qualitatively across measures: soil-testing-based fertilization is intrinsically valued (willingness to pay 24 CNY/mu), while crop rotation imposes the largest non-monetary cost (willingness to accept 152 CNY/mu). Existing Jiangsu flat rates approximate farmer mobilization thresholds for low- and medium-cost practices but under-incentivize rotation. Income subsidies dominate non-income alternatives. Smallholders are more inertial and more compensation-responsive than NAOEs, requiring more compensation for crop rotation and showing a stronger income-subsidy preference. The findings support differentiated compensation by measure and farmer type; the methodological template extends to other agri-environmental contexts in which adoption is genuinely combinatorial. Full article

Madura cattle are a nationally important indigenous Indonesian beef cattle breed and a locally adapted genetic resource that supports smallholder livelihoods and beef production under tropical dryland, low-input farming conditions. As an indigenous Indonesian beef cattle breed raised predominantly by smallholder farmers in dryland and low-input systems, Madura cattle require integrated management practices that combine resource management, technical management, environmental management, and operational efficiency to improve farm performance. A quantitative survey was conducted with 400 farmers from Madura Island. Data were collected through structured interviews using a five-point Likert-scale questionnaire and analyzed using SEM-PLS by evaluating the measurement and structural models. The results show that all constructs met validity and reliability criteria. The model demonstrated adequate explanatory power, with adjusted R² values of 0.369 for Operational Efficiency and 0.522 for Farm Performance. Resource Management, Technical Management, and Environmental Management had positive and significant effects on Operational Efficiency. Operational Efficiency also had a positive and significant effect on Farm Performance and partially mediated the relationships between the three management variables and Farm Performance. These findings indicate that improving Madura cattle farming performance requires stronger resource, technical, and environmental management supported by operational efficiency as a strategic mechanism to enhance production, reproduction, and economic performance sustainably. Full article

Farm-scale expansion is widely viewed as a means of improving agricultural efficiency and linking smallholders to modern agriculture. Yet whether it improves the conditions under which smallholders participate in grain production remains unclear. Using panel data from the China Rural Revitalization Survey (CRRS) for 2020 and 2022, this study examines how village-level farm-scale expansion affects smallholder grain production. The results show that a 0.1 increase in village-level farm-scale expansion intensity is associated with a 0.81-percentage-point higher grain-sown share, but without corresponding improvements in production conditions. Farm-scale expansion is also associated with lower mechanization, a lower share of spending on purchased agricultural services, greater reliance on household-owned machinery, and higher family labor input. We describe this pattern as constrained grain-oriented adjustment: an increase in grain-sown share without corresponding improvements in mechanization or external service support, leaving production more dependent on household-based resources. Cooperative membership is associated with less severe mechanization and cost pressures. Overall, a higher grain-sown share under farm-scale expansion does not necessarily imply improved conditions for smallholder grain production. To promote inclusive agricultural modernization, policy efforts should focus not only on farm-scale operations, but also on strengthening smallholders’ access to mechanized, service-based, and organizational support. Full article

This study examines the impact of agricultural insurance on farm household resilience and explores the underlying mechanisms through which this effect operates. Using survey data from 1242 farm households collected in 2021 across three major grain-producing provinces in China—Heilongjiang, Henan, and Hunan—this study constructs a multidimensional index of household resilience based on resistance, recovery, and regeneration using the entropy method. An instrumental variable approach is employed to address endogeneity concerns, and a mediation model is used to identify the mechanisms of influence. The results show that agricultural insurance significantly enhances farm household resilience, with the strongest effect observed in the recovery dimension. Mechanism analysis reveals that this effect operates through reducing risk aversion, improving income security, and promoting crop innovation. Heterogeneity analysis indicates that the resilience-enhancing effect is more pronounced among large-scale farmers and those who have not adopted climate adaptation measures. These findings suggest that agricultural insurance plays a critical role in strengthening farm household resilience through multiple channels. Policy efforts should focus on improving insurance accessibility, particularly for smallholder farmers, and promoting complementary measures such as risk management education and technological innovation. Full article

Sustainable management of the invasive tree Hovenia dulcis (H. dulcis) in the Mixed Ombrophilous Forest (MOF) is crucial for reconciling biodiversity conservation with income generation for smallholders. This study developed a species-specific predictive growth model for H. dulcis and simulated management scenarios across three properties with contrasting invasion intensities. By integrating stem quality, phytosanitary status, and individual growth rates into tree selection criteria, we evaluated trade-offs between timber yield and structural recovery under Continuous Cover Forestry (CCF) principles. The mixed-effects growth model demonstrated high predictive performance (marginal R² = 0.89, RMSE = 2.05 cm), confirming H1 and validating its application as a decision-support tool for long-term silvicultural planning. Results confirmed H2: no single standardized management approach proved appropriate across all sites, as invasion intensity, stand density, and diameter distribution varied substantially among properties and directly determined the most suitable harvesting strategy. In highly invaded stands (Property I), intensive harvesting of 61 trees yielded the highest commercial volume (Vc = 21.84 m³), while in more preserved forests (Property II), conservative selection of 26 trees (Vc = 9.53 m³) prioritized structural quality. Structural recovery periods ranged from 1 to 7 years depending on harvesting intensity, with removal of stagnant large-diameter trees reducing passage time for remaining individuals. Targeting sawlog-quality trees (dbh > 25 cm) was 3.35 times more profitable than firewood production, providing a significant economic incentive for smallholders. These findings demonstrate that property-specific H. dulcis management can transform a biological threat into a productive resource, fostering MOF restoration through active and sustainable use. Full article

Agriculture plays a fundamental role in ensuring global food security in the context of a growing population; however, it is also responsible for the substantial consumption of natural resources and greenhouse gas emissions. In this context, the adoption of sustainable practices represents a key strategy to improve agri-food supply chains, including the citrus sector. This study applies the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to conduct a systematic review aimed at assessing the economic value generated by environmental, social, and economic sustainability practices along the citrus supply chain. The analysis focuses in particular on the role of sustainability certifications, examining both their potential benefits and the constraints associated with their adoption for producers and markets. Positioned at the beginning of the supply chain, producers play a pivotal role in the adoption of sustainable practices, whereas consumers, at the end, are instrumental in assigning market value to sustainability attributes through their purchasing decisions. The results highlight that, although consumer interest in ethical and environmentally friendly citrus products is increasing, this demand is often constrained by the lack of clear, standardized, and easily interpretable sustainability indicators. The review also reveals a significant imbalance in the existing literature, with economic assessments predominantly focused on environmental and production-related outcomes, while the economic value generated by social sustainability practices remains largely unexplored. Moreover, the review emphasizes the strategic role of policymakers in fostering sustainable transitions by providing economic incentives and facilitating access to finance, particularly for smallholders. Overall, the findings suggest that sustainability can generate economic value in the citrus supply chain; however, its effectiveness strongly depends on market recognition, certification credibility, supply chain organization, and institutional support. Full article

This study examines how corporate resilience is developed through inclusive and sustainable cocoa partnerships within integrated value chain governance in Sulawesi, Indonesia. Using an interpretive qualitative multiple-case study design, the research compares PT Mars Symbioscience Indonesia in Luwu Timur and PT Papandayan Cocoa Industries (Barry Callebaut) in Polewali Mandar. Data were collected from January to May 2025 through semi-structured interviews with 21 actors representing corporate, intermediary, farmer, financial, and local government stakeholders, and were triangulated with company documents, policy texts, and the relevant literature. The data were analyzed thematically using NVivo, supported by process tracing and cross-case comparison. The findings show that both firms combine certification, traceability, procurement arrangements, monitoring, and knowledge transfer, but organize these instruments through different partnership architectures. Mars follows a vertically integrated capability-building model involving 4250 farmers and 17 trained collectors, whereas Barry Callebaut relies on an intermediary- and standards-centered model through PT Bumi Surya Selaras, involving 3125 farmers in 126 farmer groups. These findings suggest that inclusive and sustainable cocoa partnerships function not only as supply-chain coordination mechanisms but also as institutional arrangements for governing smallholder-based production resources and long-term supply sustainability. Across cases, these partnerships were reported and interpreted as supporting supply stability, cocoa bean quality improvement, and risk mitigation. This suggests that corporate resilience in smallholder-based cocoa value chains is co-produced through the integration of governance mechanisms, farmer capacity building, intermediary coordination, and sustainable resource management. Full article

Globally, mycotoxin contamination of maize is a fundamental concern due to significant economic losses and toxic health effects on humans and animals. This study analyses the perceived effects of mycotoxin contamination and the use of control measures among smallholder maize farmers in South Africa using Mbombela as a case study. A two-stage sampling procedure was used to select 152 registered smallholder maize farmers in Mbombela, South Africa. Data was collected with a structured questionnaire administered by trained enumerators. Descriptive and multiple linear regression analyses were carried out using SPSS (Version 28). The findings revealed that many farmers had a high perception of the effects of mycotoxin contamination, and the most prominent prevention and control practices were good field management, storage of maize in clean, well-ventilated stores, and proper sorting of harvested grains. Multiple linear regression results revealed that farming experience, media exposure, extension visit, mycotoxin-related training, mycotoxin awareness, and perception index significantly influenced farmers’ utilization of mycotoxin prevention and control practices. The study recommended that agricultural professionals develop robust mycotoxin-related training and advisory services to enhance and strengthen farmers’ awareness and perceptions, and to promote the sustained use of effective agricultural practices to combat mycotoxin contamination. Full article

Agricultural production is increasingly threatened by climate variability, limited access to quality inputs, and market shocks in developing countries. Insurance–input bundles, which integrate crop insurance with inputs like fertiliser and seed, have emerged as a promising tool for improving productivity and resilience among smallholder farmers. This study adopts a structured (systematic narrative) literature review approach, synthesising evidence from 152 studies to examine farmers’ awareness, attitudes, willingness to pay, participation, satisfaction, and productivity outcomes associated with insurance–input bundles. The findings show that awareness remains uneven and often limited by weak extension systems and low financial literacy, while farmers’ attitudes are strongly shaped by past experiences, cultural perceptions, and institutional trust. Furthermore, affordability constraints and risk misinterpretation reduce willingness to pay, whereas perceived value and institutional credibility significantly enhance demand for bundled products. Across the reviewed literature, adoption is shown to be a non-linear and interdependent process influenced by behavioural, economic, and institutional factors, where breakdowns in trust, affordability, or information can limit participation. Evidence further indicates that insurance–input bundles promote the adoption of improved inputs, increase yields, and enhance income stability, although these impacts are highly context-dependent and mediated by implementation quality, including timely payouts and effective service delivery. The review contributed to the literature by advancing a systems-based understanding of bundled insurance adoption, highlighting the central role of institutional reliability, behavioural responses, and implementation quality. Lastly, the review underscores the need for strong institutions, integrated extension systems and farmer-centred design to ensure sustainable scaling. Full article

Agricultural socialized services (ASS) play an important role in connecting smallholders with modern agriculture and in strengthening agricultural economic resilience (AER). Using panel data from 30 Chinese provinces for 2011–2022, this study applies two-way fixed-effects, mediation, and threshold models to examine the effect of ASS on AER and the associated mechanisms. The results show that: (1) ASS significantly enhances AER, and this finding remains robust after excluding municipalities and the COVID-19 period; (2) the positive effect of ASS is more pronounced in non-major grain-producing regions than in major grain-producing regions; (3) ASS strengthens AER by reducing agricultural product import dependence and expanding agricultural operation scale; and (4) agricultural industrial restructuring exhibits a threshold effect, with the effect of ASS becoming positive when the restructuring coefficient exceeds 0.0057. Based on these findings, this study recommends improving the agricultural socialized service system, strengthening domestic agricultural supply capacity, diversifying supply channels, promoting land transfer and moderate-scale operations, and aligning service policies with regional industrial restructuring. Full article

Shaded Arabica coffee production in agroforestry systems, as opposed to full-sun production, is a nature-based solution improving soil water balance, reducing heat exposure of coffee plants, and supporting sustainable forest management as opposed to deforestation. For this coffee production system in Mexico, which is dominated by smallholders as the largest group of coffee producers, we herein analyze current and estimate future yields. For the first time, to our best knowledge, this is done with a process-based coffee agroforestry model CAF2014 that we adapted for geo-spatial applications and named CAF2014-Rhaobi. Modeling of smallholders’ representative management is based on tree thinning, pruning frequency, and nitrogen supply through fertilizer and litter from nitrogen-fixing shade trees. Modeled historical yields generally agree with the reported numbers; however, there are discrepancies explained by modeling assumptions and simplifications. While shade trees help sustain coffee production, the projected drop in yields under present management is about 30% at the end of the century compared to the present as estimated using an ensemble of CMIP6 SSP5-8.5 climate projections. Economic analysis for three typologies of Mexican small coffee producers (conventional low, high-efficiency, and organic) reveals the major role of farmer associations and organic coffee price premiums in making production economically sustainable. This emphasizes the need for innovative marketing approaches and policies supporting farmers opting for certified production. Full article

Modern agriculture in developing regions faces significant challenges due to labor scarcity and the health hazards associated with the manual application of chemical treatments. This study presents the design, development, and techno-economic evaluation of an experimental hexacopter unmanned ariel vehicle (UAV) platform specifically tailored for crop protection on fragmented, smallholder farmlands. The research aims to bridge the gap between expensive imported technology and the practical needs of small-scale farmers by providing a cost-effective, locally manufacturable solution. The methodology involved the integration of a modular spraying system and optimized control architecture into a high-stability hexacopter frame. Experimental evaluations focused on flight stability, payload capacity, and spray uniformity using water-sensitive media. The results indicate that the developed platform achieves high coverage efficiency while significantly reducing chemical waste compared to traditional manual methods. Furthermore, the economic analysis suggests that the operational costs are substantially lower than those of comparable imported systems, offering a favorable payback period within a few crop seasons. These findings demonstrate that an indigenous UAV spraying platform can enhance both operational safety and economic feasibility for smallholder agriculture. Full article

Cassava is a critical staple crop for food security and rural livelihoods in Sub-Saharan Africa, yet high-resolution maps of its distribution remain scarce, particularly for smallholder systems. In this study, we generated a 10 m resolution cassava presence map for Uganda (CM24) by fine-tuning a Random Forest classifier on TESSERA foundation model embeddings derived from Sentinel-1 and Sentinel-2 time series. Using field survey data from the Copernicus4GEOGLAM campaign for training and validation, the model achieved excellent discriminative ability (validation AUC = 0.9532, test AUC = 0.9524). Visual validation against high-resolution satellite imagery confirmed good spatial agreement, capturing both large contiguous fields and small fragmented plots. Comparison with two existing global products (CassavaMap and SPAM2020) and two seasons of national survey data conducted by the Uganda Bureau of Statistics showed that CM24 produced national harvested area estimates that fell between the two survey totals, whereas CassavaMap and SPAM2020 systematically overestimated harvested area by factors of two to three. Our results demonstrate that foundation-model embeddings offer a robust and scalable approach for mapping cassava in heterogeneous smallholder landscapes. The resulting CM24 map provides a spatially explicit tool to support disease surveillance, agricultural monitoring, and food security planning in Uganda and beyond. Full article