Search Results (684)

In countries facing physical water shortages, the safe use of treated wastewater can increase agricultural yields. However, farmers’ willingness to reuse water in agriculture is very low. Therefore, the purpose of this study is to determine the factors that influence 217,215 Iranian farmers who use treated wastewater to adopt safe irrigation practices. This study, which developed the Theory of Planned Behavior (TPB) by including risk perception (RP) and knowledge factors, is a groundbreaking endeavor in the field of the safe use of treated wastewater at the farm level in Iran and around the world. The final model analysis was conducted based on structural equation modeling (SEM). The findings reveal that attitudes, perceived behavioral control (PBC), RP, and knowledge significantly influence farmers’ behaviors regarding safe wastewater use, while subjective norms did not impact intentions. The subjective norm in this study includes the perceived social pressure by farmers (through family, friends, the farming community, and local authorities) to perform or not perform safe behavior in using treated wastewater for irrigation. Notably, PBC was the most important component in the original TPB model, because intention has a beneficial impact on behavior. In the extended model, knowledge and risk perception emerged as critical elements. Therefore, intervention policies should prioritize enhancing farmers’ knowledge, risk perception, and perceived behavioral control to promote safe treated wastewater usage. This study offers valuable insights for developing countries in agricultural practices. Full article

Cotton is a crucial economic crop, and timely and accurate acquisition of its spatial distribution information is of great significance for yield prediction, as well as for the formulation and adjustment of agricultural policies. To accurately and efficiently extract cotton cultivation areas at a large scale, in this study, we focused on the Santun River Irrigation District in Xinjiang as the research area. Utilizing Sentinel-2 satellite imagery from 2019 to 2024, four cotton extraction models—U-Net, SegNet, DeepLabV3+, and CBAM-UNet—were constructed. The models were evaluated using metrics, including the mean intersection over union (mIoU), precision, recall, F1-score, and over accuracy (OA), to assess the models’ performances in cotton extraction. The results demonstrate that the CBAM-UNet model achieved the highest accuracy, with an mIoU, precision, recall, F1-score, and OA of 84.02%, 88.99%, 94.75%, 91.78%, and 95.56%, respectively. The absolute error of the extracted cotton areas from 2019 to 2024 ranged between 923.69 and 1445.46 hm², with absolute percentage errors of less than 10%. The coefficient of determination (R²) between the extracted results and statistical data was 0.9817, indicating the best fit. The findings of this study provide technical support for rapid cotton identification and extraction in large- and medium-sized irrigation districts. Full article

Lebanon’s cereals production holds historical importance in the Bekaa region, which has served as Lebanon’s agricultural heartland for centuries. Today, this vital area for food security faces environmental challenges that threaten the viability of its cereals farming sector. This study examines the current state of agricultural resources and territorial features of cereals through the lens of farmers and the local community using Perception-Based Regional Mapping (PBRM). The resulting maps were digitized and analyzed using QGIS to highlight spatial disparities across the region. The study was conducted during the summer of 2023. A total of 36 maps were developed with local farmers who first identified the areas relevant to cereals cultivation, and then reflected the spatialized perceptions covered 93% of the total study area and delineated it into distinct zones based on eight criteria identified by farmers: water availability, water quality, type of water resources, soil type, soil fertility, agricultural productivity, landform, and size of arable land. The primary cereal crops grown in the region are wheat, barley, and corn, with wheat dominating cultivation. Farmers use both traditional and mechanized methods, apply nitrogen-based fertilizers and herbicides, and rely on rainfall or limited irrigation. The resulting maps highlighted the distinct agricultural zones within the basin, of which 1030 km² (74%) were identified as appropriate for cereals cultivation. The findings underscore the value of local knowledge in identifying environmentally and economically favorable zones for cereals production, and contribute to the design of targeted, region-specific policies and interventions aimed at enhancing the resilience of cereals farming systems in the Bekaa—especially in light of ongoing socio-environmental pressures. Full article

Agronomic practices and future climate change lead to divergent responses in crop growth and greenhouse gas (GHG) emissions, which challenge a sustainable low-carbon agricultural economy. Therefore, this study developed a simulation-optimization hybrid model to identify long-term best management practices (BMPs) for economic and social benefits under the effects of future climate change. This model, i.e., RZWQM2 coupled with an orthogonal optimization algorithm (RZWQM2-OOA), integrates four core components, including an orthogonal sampling module, climate prediction module, RZWQM2 simulation module, and optimization analysis module. The model enabled a high-fidelity simulation of crop growth and carbon emissions across complex management practice-climate combinations, while efficiently identifying BMPs and circumventing dimensionality challenges through orthogonality and balanced dispersion mechanisms. To validate the applicability of the developed model, it was applied to a real-world, irrigated, continuous corn (Zea mays L.) production system in the USA. Results indicated that the maximum increases in direct and indirect economic benefits (F₁ and F₂) and potential social benefits (F₃) were 35.7%, 42.6%, and 155.5%, respectively, compared to the actual practice. Fertilization amount was the key regulating factor for direct economic and potential social benefits, which exhibited the largest contribution rates (44.3% for direct economic benefit and 53.9% for potential social benefit). Irrigation exerted the most significant influence on indirect economic benefits (Contribution rate = 53.9%). This study provides a replicable and scalable methodology for policy-makers to balance the trade-offs between the economy and carbon emissions in agricultural sustainability. Full article

Global water scarcity has emerged as a critical barrier to sustainable socio-economic development, stimulating water rights trading to serve as a policy instrument designed to enhance water use efficiency. This study systematically evaluates the impact of water rights trading (WRT) on agricultural water use efficiency (AWE) using panel data from 30 provinces (2011–2022) and a difference-in-difference (DID) model, while thoroughly investigating the underlying mechanisms and spatial spillover effects. The following are primary conclusions: (1) WRT significantly improves efficiency, reducing water consumption per unit of agricultural output by 4.5% in pilot regions, with robustness checks confirming reliability; (2) the policy’s effects on agricultural water use efficiency vary across regions; (3) mechanism analysis suggests that efficiency improvements are primarily driven by optimized crop planting patterns, adoption of water-saving irrigation technologies, advancements in agricultural mechanization, and strengthened environmental regulations; and (4) the policy exhibits notable spatial spillover effects. These findings contribute to the evaluation of WRT policy and offer practical insights for market-based water allocation reforms, suggesting further expansion of WRT with an emphasis on regional coordination and cross-regional cooperation mechanisms. Full article

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

Water systems serve as multifaceted environmental pools for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs), influencing human, animal, and ecosystem health. This review synthesizes current understanding of how antibiotics, ARB, and ARGs enter surface, ground, and drinking waters via wastewater discharge, agricultural runoff, hospital effluents, and urban stormwater. We highlight key mechanisms of biofilm formation, horizontal gene transfer, and co-selection by chemical stressors that facilitate persistence and spread. Case studies illustrate widespread detection of clinically meaningful ARB (e.g., Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae) and mobile ARGs (e.g., sul1/2, tet, bla variants) in treated effluents, recycled water, and irrigation return flows. The interplay between treatment inefficiencies and environmental processes underscores the need for advanced treatment technologies, integrated monitoring, and policy interventions. Addressing these challenges is critical to curbing the environmental dissemination of resistance and protecting human and ecosystem health. Full article

This study employs k-means clustering to analyze local organizations responsible for land improvement in Greece, identifying four distinct groups with consistent geographic patterns but divergent financial and operational characteristics. By integrating unsupervised machine learning with spatial analysis, the research offers a novel perspective on irrigation water pricing and cost recovery. The findings reveal that organizations located on islands, despite high water costs due to limited rainfall and geographic isolation, tend to achieve relatively strong financial performance, indicating the presence of adaptive mechanisms that could inform broader policy strategies. In contrast, organizations managing extensive irrigable land or large volumes of water frequently show poor cost recovery, challenging assumptions about economies of scale and revealing inefficiencies in pricing or governance structures. The spatial coherence of the clusters underscores the importance of geography in shaping institutional outcomes, reaffirming that environmental and locational factors can offer greater explanatory power than algorithmic models alone. This highlights the need for water management policies that move beyond uniform national strategies and instead reflect regional climatic, infrastructural, and economic variability. The study suggests several policy directions, including targeted infrastructure investment, locally calibrated water pricing models, and performance benchmarking based on successful organizational practices. Although grounded in the Greek context, the methodology and insights are transferable to other European and Mediterranean regions facing similar water governance challenges. Recognizing the limitations of the current analysis—including gaps in data consistency and the exclusion of socio-environmental indicators—the study advocates for future research incorporating broader variables and international comparative approaches. Ultimately, it supports a hybrid policy framework that combines data-driven analysis with spatial intelligence to promote sustainability, equity, and financial viability in agricultural water management. Full article

Understanding the carbon emission efficiency (CEE) of maize production and its determinants is critical to supporting China’s dual-carbon goals and advancing sustainable agriculture. This study employs a super-efficiency slack-based measure model (SBM) to evaluate the CEE of five major maize-producing regions in China from 2001 to 2022. Kernel density estimation and the Dagum Gini coefficient are used to analyze spatiotemporal disparities, while a geographically and temporally weighted regression (GTWR) model explores the underlying drivers. Results indicate that the national average maize CEE was 0.86, exhibiting a “W-shaped” fluctuation with turning points in 2009 and 2016. From 2001 to 2015, the Southwestern Mountainous Region led with an average efficiency of 0.76. Post-2015, the Northern Spring Maize Region emerged as the most efficient area, reaching 0.90. Efficiency levels have generally become more concentrated across regions, though the Southern Hilly and Northwest Irrigated Regions showed higher volatility. Inter-regional differences were the primary source of overall CEE disparity, with an average annual contribution of 46.66%, largely driven by the efficiency gap between the Northwest Irrigated Region and other areas. Spatial heterogeneity was evident in the impact of key factors. Agricultural mechanization, cropping structure, and environmental regulation exhibited region-specific effects. Rural economic development and agricultural fiscal support were positively associated with CEE, while urbanization had a negative correlation. These findings provide a theoretical foundation and policy reference for region-specific emission reduction strategies and the green transition of maize production in China. Full article

Precision irrigation plays a crucial role in managing crop production in a sustainable and environmentally friendly manner. This study builds on the results of the GreenWaterDrone project, aiming to estimate, in real time, the actual water requirements of crop fields using the crop water stress index, integrating infrared canopy temperature, air temperature, relative humidity, and thermal and near-infrared imagery. To achieve this, a state-of-the-art aerial micrometeorological station (AMMS), equipped with an infrared thermal sensor, temperature–humidity sensor, and advanced multispectral and thermal cameras is mounted on an unmanned aerial system (UAS), thus minimizing crop field intervention and permanently installed equipment maintenance. Additionally, data from satellite systems and ground micrometeorological stations (GMMS) are integrated to enhance and upscale system results from the local field to the regional level. The research was conducted over two years of pilot testing in the municipality of Trifilia (Peloponnese, Greece) on pilot potato and watermelon crops, which are primary cultivations in the region. Results revealed that empirical irrigation applied to the rhizosphere significantly exceeded crop water needs, with over-irrigation exceeding by 390% the maximum requirement in the case of potato. Furthermore, correlations between high-resolution remote and proximal sensors were strong, while associations with coarser Landsat 8 satellite data, to upscale the local pilot field experimental results, were moderate. By applying a comprehensive model for upscaling pilot field results, to the overall Trifilia region, project findings proved adequate for supporting sustainable irrigation planning through simulation scenarios. The results of this study, in the context of the overall services introduced by the project, provide valuable insights for farmers, agricultural scientists, and local/regional authorities and stakeholders, facilitating improved regional water management and sustainable agricultural policies. Full article

The integration of water resources, water environment, and water ecology (hereinafter “three-water”) is essential not only for addressing the current water crisis but also for achieving sustainable development. Chaohu Lake is an important water resource and ecological barrier in the middle and lower reaches of the Yangtze River, undertaking such functions as agricultural irrigation, urban water supply, and flood control and storage. Studying the performance of “three-water” in the Chaohu Lake Basin will help to understand the pollution mechanism and governance dilemma in the lake basin. It also provides practical experience and policy references for the ecological protection and high-quality development of the Yangtze River Basin. We used the DPSIR-TOPSIS model to analyze the performance of the river–lake system in the Chaohu Lake Basin and employed an obstacle model to identify factors influencing “three-water.” The results indicated that overall governance and performance of the “three-water” in the Chaohu Lake Basin exhibited an upward trend from 2011 to 2022. Specifically, the obstacle degree of driving force decreased by 19.6%, suggesting that economic development enhanced governance efforts. Conversely, the obstacle degree of pressure increased by 34.4%, indicating continued environmental stress. The obstacle degree of state fluctuated, showing a decrease of 13.2% followed by an increase of 3.8%, demonstrating variability in the effectiveness of water resource, environmental, and ecological management. Additionally, the obstacle degree of impact declined by 12.8%, implying the reduced efficacy of governmental measures in later stages. Response barriers decreased by 5.8%. Variations in the obstacle degree of response reflected differences in response capacities. Spatially, counties and districts at the origins of major rivers and their lake outlets showed lower performance levels in “three-water” management compared to other regions in the basin. Notably, Wuwei City and Feidong County exhibited better governance performance, while Feixi County and Chaohu City showed lower performance levels. Despite significant progress in water resource management, environmental improvement, and ecological restoration, further policy support and targeted countermeasures remain necessary. Counties and districts should pursue coordinated development, leverage the radiative influence of high-performing areas, deepen regional collaboration, and optimize, governance strategies to promote sustainable development. Full article

Amid the global push for agricultural green transformation, sustainable agriculture requires not only technological innovation but also market mechanisms that effectively incentivize green practices. Agricultural e-commerce is increasingly viewed as a potential driver of green technology diffusion among farmers. However, the extent and mechanism of e-commerce’s influence on farmers’ green production remain underexplored. Using survey data from 346 rural households in Inner Mongolia, China, this study develops a conceptual framework of “e-commerce participation–green cognition–green adoption” and employs propensity score matching (PSM) combined with mediation analysis to evaluate the impact of e-commerce participation on green technology adoption. The empirical results yield four main findings: (1) E-commerce participation significantly promotes the adoption of green production technologies, with an estimated 29.52% increase in adoption. (2) Participation has a strong positive effect on water-saving irrigation and pest control technologies at the 5% significance level, a moderate effect on straw incorporation at the 10% level, and no statistically significant impact on plastic film recycling or organic fertilizer use. (3) Compared to third-party sales, the direct e-commerce model more effectively promotes green technology adoption, with an increase of 21.64% at the 5% significance level. (4) Green cognition serves as a mediator in the relationship between e-commerce and green adoption behavior. This study makes contributions by introducing e-commerce participation as a novel explanatory pathway for green technology adoption, going beyond traditional policy-driven and resource-based perspectives. It further highlights the role of cognitive mechanisms in shaping adoption behaviors. The study recommends that policymakers subsidize farmers’ participation in e-commerce, invest in green awareness programs, and support differentiated e-commerce models to enhance their positive impact on sustainable agricultural practices. Full article

Amid global efforts to balance sustainable development and food security, ecosystem service value (ESV), a critical bridge between natural systems and human well-being, has gained increasing importance. This study explores the spatiotemporal dynamics and driving factors of land use changes and ESV from a food security perspective, aiming to inform synergies between ecological protection and food production for regional sustainability. Using Guangdong Province as a case study, we analyze ESV patterns and spatial correlations from 2005 to 2023 based on three-phase land use and socioeconomic datasets. Key findings: I. Forestland and cropland dominate Guangdong’s land use, which is marked by the expansion of construction land and the shrinking of agricultural and forest areas. II. Overall ESV declined slightly: northern ecological zones remained stable, while eastern/western regions saw mild decreases, with cropland loss threatening grain self-sufficiency. III. Irrigation scale, forestry output, and fertilizer use exhibited strong interactive effects on ESV, whereas urban hierarchy influenced ESV independently. IV. ESV showed significant positive spatial autocorrelation, with stable agglomeration patterns across the province. The research provides policy insights for optimizing cropland protection and enhancing coordination between food production spaces and ecosystem services, while offering theoretical support for land use regulation and agricultural resilience in addressing regional food security challenges. Full article

Improper stakeholder practices are considered a primary driver of food loss. This study aims to investigate the consequences of pre- and post-harvest practices on extending the shelf life of agro-food products, identifying which practices yield the highest marginal returns for quality. Using Fractional Regression Models (FRM) and Ordinary Least Squares (OLS), the research analyzed data from 343 Egyptian grape farmers and intermediaries. Key findings at the farmer level include significant food loss reductions through drip irrigation (13.9%), avoiding maturity-accelerating chemicals (24%), increased farmer-cultivated area (6.1%), early morning harvesting (8.7%), and improved packing (13.7%), but delayed harvesting increased losses (21.6%). For intermediaries, longer distances to market increased losses by 0.15%, while using proper storage, marketing in the formal markets, and using an appropriate transportation mode reduced losses by 65.9%, 13.8%, and 7.9%, respectively. Furthermore, the interaction between these practices significantly reduced the share of losses. The study emphasizes the need for increased public–private partnerships in agro-food logistics and improved knowledge dissemination through agricultural extension services and agri-cooperatives to achieve sustainable food production and consumption. This framework ensures robust, policy-actionable insights into how stakeholders’ behaviors influence postharvest losses (PHL). The findings can inform policymakers and agribusiness managers in designing cost-efficient strategies for reducing PHL and promoting sustainable food systems. Full article

Climate change (CC) is a major threat to agriculture, the sector that supports the territorial economy in the Pays Haut Languedoc et Vignoble (PHLV) region (south France). In this region, farms have been facing the negative effects of CC for several decades. The implementation of agriculture adaptation policies requires a coherent and integrated tool that mobilizes approaches for territorial development, vulnerability assessments, and feasibility. The purpose of this research is to provide a multi-criteria assessment of farm vulnerability to CC in the PHLV region. An index of farm vulnerability was developed based on the classic model of vulnerability, which is the product of exposure and sensitivity divided by adaptive capacity. This assessment was conducted at the farm level, by combining biophysical variables (such as soil type and irrigation) and socioeconomic variables (such as agricultural experience and crop insurance), selected based on a literature review and interviews with local stakeholders and local experts. To solve the weighting problem, we differentiated between a “calculated vulnerability”, without any specific weighting of the vulnerability variables, and a “declared vulnerability” that integrates the scores assigned to the importance of each variable for each farmer surveyed, based on their awareness. Afterward, a discriminant analysis was used to identify the factors that determine the vulnerability classes. Our results show that (i) the majority of the surveyed farms have a relatively high vulnerability index, but wine farms and cereal farms are the most vulnerable; (ii) for all farms the “declared vulnerability” is lower than the “calculated vulnerability”, showing that farmers underestimate their vulnerability; (iii) there is an interesting link between the low level of vulnerability and the adaptation efforts already made over the past ten years by certain farms that have changed or introduced crops and improved their agricultural practices. Full article