Search Results (895)

Water scarcity is a major constraint to agricultural productivity in arid and semi-arid regions, yet its implications for communal goat production systems remain insufficiently documented. This study assessed communal goat farmers’ perceptions of water scarcity and identified factors influencing this challenge in the Eastern Cape, South Africa. A structured questionnaire was administered to 218 smallholder goat farmers, and data were analysed using SPSS (v29). A ranking index was employed to prioritise production constraints, goat functions, and water sources. Additionally, water samples from dams, streams, and rainwater were analysed for key physicochemical parameters. Results showed that theft (index = 0.233) was the most important production constraint, followed by parasites/diseases (0.219), predators (0.211), and water scarcity (0.187), which consistently ranked fourth across seasons. Despite this ranking, farmers perceived water scarcity to have substantial impacts on production, including increased disease prevalence (46.3% severe), mortality (45.0% severe), reduced weight at maturity (61.9% severe), increased trekking distance to water sources (59.2% severe), and reduced feed quality (54.6% severe). Farmers generally perceived water as clean and non-saline; however, laboratory analysis revealed poor quality, with pH values ranging from 9.14 to 10.72 and turbidity exceeding recommended thresholds (<5 NTU) in most dam and stream samples. Water accessibility was limited, with goats travelling an average of 5.85 km to dams and 7.71 km to streams. Key drivers of water scarcity included reduced rainfall (50.9%), lack of government intervention (49.1%), and drying of dams (40.4%). The study highlights a critical mismatch between perceived and actual water quality and demonstrates the multidimensional impacts of water scarcity on goat health, productivity, and welfare. Future research requires longitudinal studies linking water quality to goat health outcomes, intervention research on farmer education, low-cost water-treatment technologies, governance studies of water infrastructure, and economic analyses quantifying productivity losses. Full article

Land trusteeship is an innovative agricultural management model that connects smallholder farmers with modern agriculture. It promotes large-scale agricultural operations, but still faces the impacts of conventional natural disasters. Although agricultural disaster insurance serves as a critical mechanism for farmers to mitigate these natural risks, its risk-mitigation potential remains underutilized due to the persistent challenge of low insurance participation rates. This study develops a decision-making model for farmers’ purchase of agricultural disaster insurance under land trusteeship, drawing on protection motivation theory, market failure theory, and quasi-public goods theory. Using structural equation modeling, we empirically analyze survey data from 319 land-trusteed farmers to uncover the mechanisms and pathways influencing their insurance purchase decisions. The results indicate that: (1) Vulnerability and severity are positively associated with protection motivation through perceived response efficacy and self-efficacy, and protection motivation is directly associated with purchase decisions; (2) Government support has both direct and indirect effects on purchase behavior; and (3) Individual and household characteristics are significantly associated with purchase decisions, with pure farmers, Type I part-time farmers, and farmers with larger landholdings tending to purchase agricultural disaster insurance more often. Full article

Africa’s food systems, dominated by smallholder farmers, have yet to benefit from the transformative potential of digital technologies. While large-scale farms have widely integrated digital solutions, smallholder farms have lagged behind. This disparity creates unequal opportunities in the sector. African governments are not oblivious to the severe impact of the digital divide. Therefore, several policy frameworks and strategies are being adopted to address the challenge. This article examines current policy frameworks and strategies to address the digital divide in Africa’s food systems. It also explores the impact of these policy frameworks and strategies. The article draws from a qualitative review methodology underpinned by a review of primary and secondary sources, both in grey and academic formats. The article reveals that at the regional level, policies such as the African Union (AU) Digital Transformation Strategy, the Comprehensive African Agricultural Development Programme, the AU Digital Agriculture Strategy and the African Continental Free Trade Area Digital Protocol are being adopted to address the digital divide. There are also several Regional Economic Communities Initiatives that focus on several intertwined areas to address the digital divide. In addition, countries adopt notional strategies and policies to address country-specific challenges related to the digital divide. The article concludes that policies aimed at addressing the digital divide have had a limited impact in Africa due to poor implementation. Accountability must be built into the policy lifecycle, from planning and implementation to monitoring and evaluation, to address the digital divide in Africa’s food systems effectively. This can be achieved through a combination of political oversight, legal and regulatory frameworks, civil society engagement, and the establishment of measurable performance metrics. Full article

This study seeks to explain how structural factors, farmers’ capacity, technology adoption, and market orientation jointly shape productivity in smallholder Arabica coffee farming. Primary data were collected from 152 Arabica coffee farmers in Kerinci Regency, Jambi Province, Indonesia, between June and August 2025 and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that infrastructure and government policy have positive and significant effects on technology adoption. However, infrastructure does not directly affect productivity, whereas government policy shows a negative, significant effect on productivity, suggesting a possible misalignment between policy support and farmers’ practical production needs. In contrast, digital literacy and market orientation are found to be the main determinants that significantly enhance productivity. Technology adoption does not have a significant effect, either directly or as a mediating variable, suggesting a gap between adoption and utilization at the farm level. The moderation analysis reveals that market orientation strengthens the relationship between digital literacy and productivity. Overall, these findings emphasize that productivity improvement is not solely determined by technology, but is more strongly influenced by farmers’ capacity and market orientation. Full article

Despite producing much of the world’s food, small-scale farms face severe resource shortages, climate risks, and infrastructure gaps. While digital advances ranging from IoT sensing to AI-driven analytics offer pathways to improve productivity, adoption remains uneven. This integrative review synthesizes evidence on smart-farming technologies specifically for smallholders, identifying primary barriers, enabling conditions, and design principles for successful deployment. Unlike broader smart-farming reviews, the article explicitly evaluates small-farm suitability, evidence quality, and implementation architecture rather than technological capability alone. The synthesis shows that adoption is consistently constrained by clustered barriers, notably high capital and maintenance costs, limited technical capacity, and unreliable electricity or internet access. It also finds that evidence is strongest for modular, offline-capable monitoring and alerting tools, while evidence for durable gains from highly integrated full-platform systems remains thinner and more pilot-dependent. To advance equitable innovation, the review proposes a fit-for-context deployment logic centered on co-design, local repair and advisory capacity, and financing and policy support aligned with small-farm realities. Overall, smart farming can strengthen productivity, resilience, and environmental performance on small farms, but only when technologies are embedded in inclusive service models and implementation systems. Full article

The agricultural sector in Mexico, specifically the coffee and sugarcane supply chains, faces the critical challenge of reconciling economic profitability with environmental sustainability and rural social progress. This study presents a critical literature review and conceptual framework that evaluates existing analytical models and proposes methodological integration pathways to simultaneously optimize Triple bottom line (TBL) dimensions in vulnerable smallholder systems. Unlike prior reviews that focus on generic Sustainable Supply chain management (SSCM) practices, this work explicitly addresses the suitability and limitations of multi-objective optimization (MOO) and Life cycle assessment (LCA) for regenerative supply chain objectives in the Mexican coffee and sugarcane context. A critical review of 76 core articles published between 2020 and 2025 was conducted, employing comparative evaluation criteria and narrative synthesis to assess trade-offs, data requirements, and scalability constraints. The review reveals that while agricultural intensification often exacerbates environmental degradation, the adoption of sustainable practices can impose significant financial burdens on vulnerable smallholders. However, analytical models like MOO and LCA serve as robust decision-support systems that effectively evaluate trade-offs and balance competing economic, environmental, and social objectives by identifying optimal production scenarios. The contribution of this work is threefold: (1) a critical synthesis distinguishing regenerative from sustainable supply chain paradigms, (2) a comparative assessment of analytical model applicability to smallholder contexts, and (3) a conceptual framework integrating local socioeconomic realities, traditional knowledge, and modern technological approaches. Fostering resilient supply chains in Mexico requires customized analytical frameworks that explicitly operationalize social indicators, address data limitations, and enable cross-sector collaboration. Ultimately, localized models are essential to simultaneously enhance rural livelihoods, reduce carbon footprints, and maintain economic viability. Full article

Generally, ixodid ticks are important ectoparasites of cattle, including those in smallholder production systems in the Eastern Cape Province, where varying environmental conditions influence their distribution and feeding behaviour. This study investigated ecological variation in tick species composition and attachment site preferences in Bos taurus cattle across coastal and inland areas of the Eastern Cape Province, South Africa. Ticks were collected from cattle of different ages, sexes, breeds, and body condition scores. Sampling was conducted prior to acaricide treatment, and ticks were manually removed from standard predilection sites on each animal. Specimens were preserved in 70% ethanol and later identified morphologically at the Döhne Agricultural Development Institute Laboratory. Data were analysed using generalized linear mixed models with a negative binomial distribution to assess the effects of host and environmental factors on tick burden. Descriptive statistics were used to summarise species composition, while inferential statistics were applied to evaluate differences in infestation levels across host-related and spatial variables. A total of 3250 adult ixodid ticks were collected from cattle. The most prevalent species was Rhipicephalus (Boophilus) decoloratus (39.7%), followed by Rhipicephalus evertsi evertsi (21.0%), Amblyomma hebraeum (17.7%), Hyalomma rufipes (5.8%), Ixodes pilosus (5.8%), Rhipicephalus (Boophilus) microplus (4.5%), R. appendiculatus (3.0%), and R. simus (2.5%). Tick burdens were significantly higher in the coastal zone (85 ± 7.5) than in semi-arid inland areas (62 ± 5.9). Attachment site analysis showed significantly higher infestation levels (p < 0.05) on the udder/scrotum compared to other body regions. This study provides baseline information on tick species composition and attachment site ecology in cattle, contributing to improved understanding of host–parasite interactions and supporting the development of targeted, region-specific tick control strategies. Full article

Improving crop yields while reducing environmental impacts remains a major challenge for smallholder agriculture, where heterogeneous management practices often limit the performance of technologies. This study developed a Select–Analyze–Design–Evaluate (SADE) framework to enhance the effectiveness of sustainable winter wheat technologies in smallholder farming systems. The framework was implemented in two villages on the North China Plain during a four-year field-based study (2017–2021), combining farmer follow-up surveys with field trials. During the Select stage, baseline data identified widely adopted technologies with substantial performance variability. Accordingly, delayed nitrogen application in Nanxia Village and precision seeding in Wangzhuang Village were selected as priority technologies for targeted diagnosis and improvement. During the Analyze stage, regression models identified key agronomic constraints: nutrient management in Nanxia, and sowing date and nitrogen management in Wangzhuang. Following this diagnosis, village-specific strategies were designed, implemented, and evaluated through multi-stakeholder collaboration. In Nanxia, yield, benefit–cost ratio, and nitrogen recovery efficiency increased by 7.9%, 21.5%, and 23.5%, respectively, while greenhouse gas emissions decreased by 21.5%. In Wangzhuang, the corresponding changes were 11.2%, 48.7%, 45.7%, and −22.9%, respectively. These findings demonstrate that SADE offers a practical pathway for sustainable smallholder agriculture. Full article

Climate change poses a significant threat to water resources and agricultural sustainability, particularly in semi-arid and socio-economically vulnerable regions such as South Africa. This review synthesizes empirical, modelling, and policy-based evidence on the impacts of climate change on water availability, crop production, and adaptation strategies in the country, drawing on approximately 162 peer-reviewed studies and institutional reports published between 2010 and 2025. The findings indicate that rising temperatures, shifting rainfall patterns, and an increasing frequency of extreme events, such as droughts and floods, are intensifying water stress and disrupting agricultural systems. Hydrological models consistently project declines in runoff, soil moisture, and streamflow, while crop simulation models predict reductions in the yields of major staple crops, including maize, wheat, and sorghum, particularly under high-emission scenarios. Although localized improvements in water availability and crop productivity may occur, these tend to be limited and highly context-specific. In response, South Africa has implemented a range of adaptation strategies, including climate-smart agriculture, water-efficient irrigation, ecosystem-based approaches, and policy-driven interventions. However, their effectiveness remains constrained by institutional fragmentation, limited financial capacity, and persistent socio-economic inequalities, particularly among smallholder farmers. The review underscores the need for integrated, inclusive, and context-specific adaptation strategies that strengthen governance, enhance the science–policy interface, and improve access to climate finance. The insights provided offer valuable guidance for advancing climate resilience in South Africa and other vulnerable regions across the Global South. Full article

Rainfed agriculture is the most common type of agriculture in South Africa among smallholder farmers, accounting for the majority of the arable land. In a country with so much potential, only about 8% of the arable land is under irrigation. In response, the South African post-apartheid government has invested in the establishment of irrigation schemes in rural provinces such as the Eastern Cape to promote the sustainability of smallholder farming systems. Despite these efforts, the participation of farmers in these schemes remains low. This study investigated socioeconomic and environmental factors that affect farming households’ level of participation in irrigation schemes and intensity. Cross sectional data was collected from 209 households using a multi-stage sampling procedure. Descriptive statistics was used to analyse the socio-economic and environmental factors. A double hurdle model was used to analyse both participation in irrigation and the intensity of participation. The study results reveal that agriculture is largely practised by elderly farmers with an average age of 54 years and largely female-dominated (58%). On average, farmers have 7.5 years of schooling and 12 years of farming experience. Econometric findings demonstrate that participation is significantly influenced by market access, whereas participation intensity is driven by market access, market information and the level of education. The study recommends strengthening gender-targeted agricultural support systems, improved water access through expanded and well-maintained irrigation infrastructure and improving market access. In addition, enhanced extension training support and youth-focused agricultural programmes are required to build productive capacity and ensure the long-term sustainability of irrigation schemes. Full article

The livestock sector underpins food security, employment, and rural livelihoods across the Southern African Development Community (SADC), contributing up to 50% of agricultural GDP and supporting more than 60% of rural households. Yet climate change poses escalating threats through heat stress, declining pasture productivity, water scarcity, and vector-borne diseases that compromise productivity and economic resilience. This review identifies and locates effective climate change mitigation strategies along the livestock value chain, spanning production, processing, transport, and consumption, to promote sustainable, low-emission, and inclusive growth in the SADC region. A broad review of 46 peer-reviewed and institutional sources (2000–2024) was undertaken, focusing on livestock-related mitigation within SADC and comparable agro-ecological systems. Strategies were thematically categorized by value-chain stage and assessed for their emission-reduction and livelihood-enhancement potential. Local strategies include genetic improvement for low-methane and heat-tolerant breeds, adaptive rangeland and feed management, renewable-energy adoption in processing, climate-resilient transport infrastructure, and consumer awareness of low-emission products. Evidence suggests potential GHG-emission reductions of 18–30%, coupled with productivity gains and improved smallholder incomes. Coordinated implementation through the SADC Regional Agricultural Investment Plan (2021–2030) and national policies can transform the livestock sector into a climate-resilient driver of inclusive growth. Further research should quantify the socioeconomic feasibility and scaling potential of these strategies across production systems. Successful integration of climate change mitigation imperatives must be tailored to local biophysical conditions (e.g., rainfall, soil type) and socioeconomic contexts (e.g., market access, cultural practices). Full article

Water scarcity is a global phenomenon, and Pakistan is no exception to it. This study aims to assess the techno-economic efficiency of the irrigation system for guava orchard and melon crop in the Hafizabad District of Punjab province in Pakistan. The study has employed efficiency theory for a comparative analysis of modern and high-efficiency irrigation methods in contrast to old traditional methods of irrigation to estimate differentiating impacts on technical efficiency (TE), economic efficiency (EE), water productiveness, and crop yield. The mixed method approach is exercised on data collected from 108 stratified farmers (large, medium and smallholders) using structured surveys and qualitative insights. Beta-regression models using Cauchit link function are applied to translate determinants of TE/EE by taking into account predictor factors such as farming experience, operational costs and water productivity. Results show that solar irrigation systems have significantly better performance than the conventional system by having better TE and EE scores than conventional system performance. Farming experience and water productivity also have positive effects on efficiencies. Results also show that solar systems increase water productivity, lower costs and increase guava and melon productivity to a significant extent, which in turns aid in reducing the effects of salinity and evaporation in arid conditions. The overall finding supports and emphasizes solar’s supremacy for sustainable horticulture. Findings highlight the importance of incentivizing solar adaptation and agrivoltaic integration in Pakistan to ensure sustainable agriculture in water-stressed areas such as Punjab for food security and resource conservation for the production of guava and melons. Full article

South African irrigation schemes face critical challenges of water scarcity, infrastructure deterioration, and limited monitoring capacity, threatening agricultural productivity and food security. This scoping review systematically analyses 59 peer-reviewed publications (2000–2025) on sensor-based and acoustic irrigation monitoring technologies in South Africa, using transformer-based natural language processing (Sentence-BERT embeddings), unsupervised Machine Learning (UMAP dimensionality reduction, HDBSCAN clustering), and geospatial mapping applied to literature retrieved from Web of Science and Scopus. Results show that water quality monitoring (42.4% of studies) and remote sensing (25.4%) dominate the national research landscape, while soil moisture sensing and modelling remain comparatively limited. Notably, no peer-reviewed studies applying acoustic monitoring technologies to irrigation were identified, representing a critical gap despite proven international applications for leak detection (95–98% accuracy), widespread infrastructure aging (over 50% of schemes exceeding 30 years), and reported water losses of 30–60% in poorly managed systems. Reported experimental water savings range from 15% to 30%, yet applications remain largely confined to pilot-scale implementations concentrated within a limited number of Water Management Areas. Persistent adoption barriers include infrastructure unreliability, financial inaccessibility, limited digital literacy, and weak institutional coordination. The review recommends: (i) expanding research coverage across underrepresented regions and Water Management Areas; (ii) strengthening extension support and technical training to enable broader adoption; and (iii) integrating low-cost sensor networks with predictive, data-driven irrigation advisory systems. These priorities aim to support scalable, context-sensitive irrigation modernisation under increasing water scarcity pressures. Full article

Effective crop monitoring during monsoon growing seasons in Central India faces challenges from persistent cloud cover that limits optical remote sensing during critical agricultural periods. This study presents the first attempt to develop a novel set of SAR-derived phenological metrics organized into five thematic categories for monsoon crop discrimination in smallholder agricultural systems. Five major monsoon crops (cotton, rice, maize, soybean, and urad) were analyzed across five different agroclimatic zones in Central India using Sentinel-1 data for the 2021 growing season. Phenological features were extracted from VV, VH polarizations, and their ratio, including seasonal extrema, threshold crossings, duration measures, curve shape descriptors, and area under the curve. Distinct crop-specific signatures were observed, with cotton showing extended phenology and cereal–legume crops displaying compressed, overlapping growth patterns. VV polarization achieved the highest statistical discrimination for intensity-based metrics, with 75% thresholds (VV_HP75V: F = 1287) providing higher separability than other thresholds by capturing near-peak biomass differences. VH performed best for duration and integration-based metrics, while VH/VV provided limited additional separability across metric types. For area-under-the-curve metrics, AUC25 outperformed AUC50 and AUC75 by capturing cumulative backscatter across the broader growing season while remaining robust to soil- and residue-dominated backscatter variability at sowing and harvest. Multiclass classification achieved 48.3% overall accuracy with systematic cereal–legume confusion, reflecting fundamental phenological convergence among monsoon-aligned crops. Cotton achieved the highest performance (F1: 0.79), with VH polarization dominating feature importance (65% of top 20 features). Binary classification revealed crop-specific discrimination patterns: cotton was best separated using VV intensity metrics, maize using the VH/VV ratio, and rice using timing-based features. Cross-district transferability showed the highest mean overall accuracy for rice (74%) and cotton (72%), while the remaining crops showed lower accuracy due to their phenological similarity. These findings highlight both the potential and limitations of SAR phenological metrics for monsoon crop discrimination, with effective results for structurally distinct crops but persistent cereal–legume confusion, requiring further investigation with multi-sensor approaches. Full article

Decades of traditional fertilizer subsidies have yielded modest maize productivity gains for Malawian farmers, mainly due to the twin challenges of soil degradation and intermittent weather patterns. Increasing nitrogen intake through subsidies without addressing these structural constraints has failed to close the country’s yield gap. Although climate-smart agriculture (CSA) technologies offer options for sustainable productivity growth, low and inconsistent adoption among farmers has led to insufficient evidence. Most existing studies that have examined the complementarity between CSA and inorganic fertilizers rely on experimental plot data, with limited evidence from actual farmer-managed fields. We use farm-level data collected in 2022 from 307 smallholder farmers across central and southern Malawi to investigate whether integrating CSA technologies with subsidized inorganic fertilizers enhances maize productivity. We apply the Inverse Probability Weighted Regression Adjustment (IPWRA) model to estimate the effects of CSA adoption and its integration with subsidized fertilizer. Results indicate that CSA adoption increased maize yields by 30%, confirming significant productivity gains from technologies such as mulching, agroforestry, and organic manure. However, integrating these technologies with subsidized fertilizers produced no additional yield advantage, suggesting that farmers often substitute CSA with inorganic inputs rather than combining them effectively. These findings imply that the potential synergies between CSA and subsidy programs remain unrealized under current practices. Policy reforms under Malawi’s current farm input subsidy program (FISP) should therefore emphasize extension and incentive mechanisms that promote complementary—not substitutive—use of CSA technologies and fertilizers at recommended application rates. Full article