Agricultural production necessitates sustainable practices to ensure long-term and sustained food security. Water is a key ingredient for food production. Ensuring sustainable water management in agriculture is thus essential for global wellbeing. But how do we make sure that our practices are sustainable? A large variety of sustainability assessments abound. Their results may even show conflicting results. In this study, we demonstrate the application of three sustainability assessment methods – Water Footprint Assessment, Cost-Benefit Analysis and Life Cycle Assessment – for the use of a water retainer product on different soil types, crops and growing seasons in a farm in Poland. In addition, we aggregate the results of these assessments through a Multi-Criteria Decision Analysis (PROMETHEE) to facilitate decision making. Our findings suggest that yields of all crops, on all soils in both growing seasons increased. However, yield gain was insufficient in most cases to offset the increased costs of using the water retainer product. The Multi-Criteria Decision Analysis showed that soil type and crops used had a larger effect on rank than the application of the water retainer. Overall, the conclusion from the various methods is to not recommend the use of the water retainer as an efficient water saving technology for the specific case. Our analysis showed the effects on the economic and environmental dimension of sustainability but does not include the social dimension due to the lack of data, leaving an incomplete picture of sustainability. • The aim was to evaluate how sustainability assessments inform decision-making. • WR increased yields across crops and soils, even during 2022’s severe drought. • LCA showed minimal environmental impacts, with reductions in key categories. • CBA revealed that increased yields did not offset WR costs for low-value crops. • Multi-criteria assessments capture broader societal benefits, beyond economic costs.

Solar-induced chlorophyll fluorescence (SIF) tracks variations in the soil-plant available water (PAW): a multiyear analysis on three crops

A hybrid analytics-driven optimization framework for site-specific zone management in precision agriculture

Gendered time poverty in rice farming households: Evidence from the haor ecosystem of Bangladesh

Practices, management, and typology of dromedary livestock systems and health constraints in southwestern Tunisia: The case of the Gafsa region.

Composting is widely used for agricultural waste management, and the composting method significantly influences composting processes. This study compared static composting (SC), turning composting (TC), forced aeration composting (AC), and membrane-covered forced aeration composting (MAC) to evaluate which method is more effective for mitigating carbon emissions and promoting humification. Compared to the other methods, MAC shortened the composting period and reduced cumulative CH 4 emissions by 53.4%–99.7% and cumulative CO 2 emissions by 25.7%–66.2%. Moreover, MAC promoted the formation and transformation of humic precursors, achieving the highest degree of humification among the methods. Microbial–physicochemical association networks suggested that MAC had more microorganisms associated with humic-precursor-related processes than with carbon-emission-related processes. Microbial co-occurrence networks further revealed that MAC enhanced microbial cooperation, particularly bacterial–fungal interactions, which played a critical role in humification. Notably, MAC increased the relative abundance of bacterial pathways associated with substrate metabolism in the early stage and enriched pathways for secondary metabolite biosynthesis in the late stage, while shifting the fungal community toward saprotroph dominance. Overall, by combining a parallel comparison of composting methods with the elucidation of the underlying microbial mechanisms, this study reinforced the application potential of MAC. • Membrane-covered forced aeration composting (MAC) reduced carbon emissions. • MAC resulted in the highest degree of polymerization (DP = 1.91). • More microorganisms processed humus precursors than carbon emissions in MAC. • MAC enhanced microbial cooperation intra- and inter-domain. • MAC enhanced humification-related bacterial metabolic pathways.

Assessing historical and future spatio-temporal dynamics of water footprints across climatically diverse zones of an agriculturally dominant river basin

From near surface to root zone soil water losses: a new model validated with field TDR and remotely sensed data

Spatiotemporal dynamics and suitability of greenhouse agriculture in China: A GEE-based analysis for sustainable land use planning in Henan Province

Rainwater harvesting systems (RWHS) play a vital role in water resource management, particularly in developing countries such as Iran. Amid declining rainfall and increasing drought conditions, these systems offer a sustainable solution for agricultural water supply, reduce financial costs, and lessen reliance on surface and groundwater resources. However, limited adoption of RWHS by farmers remains a significant challenge for policymakers seeking to promote sustainable water practices. This study aimed to examine the factors influencing Iranian farmers’ intention to adopt RWHS, focusing on farmers in Hamidieh County, located in southwestern Iran. To guide the analysis, an extended Theory of Planned Behavior (TPB) model was employed, incorporating three additional constructs—response efficacy (RE), risk perception (RP), and place attachment (PA)—alongside the original components: attitude toward behavior (ATT), subjective norms (SN), and perceived behavioral control (PBC). The findings revealed that the proposed framework demonstrated strong explanatory power, accounting for 74.2% of the variance in farmers’ intention to adopt RWHS. These results underscore the model’s effectiveness and offer valuable insights for policymakers aiming to enhance sustainable water resource strategies and boost agricultural productivity. Overall, the study contributes meaningfully to the discourse on agricultural water management and provides practical guidance for designing targeted interventions to encourage RWHS adoption among farmers. • Sustainable management of agricultural water • Rainwater harvesting for irrigation • Developing a planned behavior model using place attachment theory.

This research develops a water-centric nexus assessment framework for Thailand’s major crops: rice, sugarcane, and cassava, within shared cultivation areas. The framework examines interaction among water use, agricultural productivity, and economic performance, positioning water as the central analytical dimension. A 10-year monthly dataset (2013–2022) from official sources was examined, and farmer interviews confirmed the relevance of variables, cost structures, and adaptive capacity. Applying a system-thinking approach using VENSIM software to construct causal loop diagrams and perform scenario-based analyses rather than full dynamic simulations. The framework integrates three normalized components: water mass productivity, economic water productivity, and water security, into a composite nexus index. Results indicate that sugarcane has the highest water productivity (0.010 tons/m 3 ), followed by cassava (0.004 tons/m 3 ) and rice (0.00031 tons/m 3 ). Sugarcane also demonstrates superior economic water productivity, yielding higher profits per unit of water consumed. Sensitivity analysis reveals that expanding cultivation areas generally reduces water security; however, productivity and water-use efficiency improvements can offset these impacts up to crop-specific land-use thresholds. The sustainable annual expansion rates are estimated at 0.68% for sugarcane and 0.75% for cassava, while rice requires a 0.26% reduction in cultivated area to sustain a positive Water–Economy–Food nexus. Beyond these thresholds, the nexus turns unfavorable. Overall, the findings highlight the importance of demand-side water management, strategic crop allocation, and farmer adaptability in sustaining a stable water-centric nexus. The proposed framework provides a practical decision-support tool for integrated agricultural water management and policy development in Thailand. • Developed a validated WEF Nexus framework using 10 years of real data for Thailand’s agricultural systems. • Sugarcane shows the highest water productivity and economic return, highlighting its resource efficiency potential. • Identified critical crop area thresholds beyond which WEF Nexus stability declines, guiding sustainable land use. • Farmers show moderate-high adaptability, with advanced varieties and controlled irrigation improving system resilience.

North African countries are increasingly facing climate change, natural resource degradation, and food crises. Algerian regions such as Laghouat are one of the hotspots where problems such as soil degradation, desertification, and water scarcity are experienced. Current agricultural production systems are not responding to future needs and are inadequate to address these problems. Agroecology emerges as a promising alternative that can respond to growing future needs by providing resilient and sustainable production systems. This study investigates the factors affecting farmers’ adaptation to agroecology in Laghouat, Algeria, using Elinor Ostrom’s Social Ecological Systems Framework (SESF). We apply our mixed-methods methodology in the field to systematically examine the complex relationships of the system, resource systems and, governance, and actors. Our findings suggest that the negative impacts of unsustainable agricultural practices, combined with climate change and misguided policies, are leading to a problematic trend that results in a system that is losing its resilience and sustainability and is becoming increasingly vulnerable. However, the study also highlights that farmer training, incentives to support the adoption of environmentally friendly practices, and strong social networks can significantly increase the transition to sustainable agroecology. These insights underline the need for integrated and collaborative strategies to achieve sustainable soil management, and hence more resilient agricultural system. • Agroecology can induce sustainable agricultural land management and improve soil health in a systematic manner. • Transdisciplinary approach helps understand SES by integrating social, ecological and economic aspects of soil and land use. • Participatory and site-specific methodology has been developed to implement Social Ecological Systems framework.

Design constraints governing household-scale rice-straw biochar systems: The role of feedstock densification and particle-size selection

Effective agricultural pest management, crucial for global food security and ecosystem balance, demands robust identification systems capable of adapting to dynamic environments. While deep learning shows promise, current methods often fail in practical class incremental learning scenarios, suffering catastrophic forgetting when encountering learning new pest species. This limitation hinders the development of truly adaptive tools for incremental pest recognition. Addressing this gap, we aimed to create a framework integrating advanced artificial intelligence (AI) with ecological needs for continuous and reliable pest recognition. We propose PestCLIP, a framework for incremental pest recognition leveraging contrastive language-image pretraining (CLIP) model. To combat forgetting, PestCLIP employs dual-prompt tuning and a unique Concept Pool strategy that captures essential class features without extensive data replay. Crucially, it incorporates Prediction Distribution Calibration through incremental logit adjustment. Tested across diverse agricultural pest datasets (Li's, AgriInsect200, and Farm Insect) and general benchmark (mini-ImageNet), PestCLIP demonstrated superior class incremental learning performance, achieving 97.50% accuracy on Li's dataset with only a 5.55% drop when integrating new pest classes. Extensive testing on diverse agricultural pest datasets demonstrates the superiority of PestCLIP in incremental pest recognition tasks. The visualization results confirm that PestCLIP effectively preserves class-specific concepts and mitigates prediction bias through distribution calibration. The proposed PestCLIP marks a pivotal step in advancing incremental pest recognition, enhancing the adaptability and reliability of smart pest management systems in dynamic agricultural environments. © 2026 Society of Chemical Industry.

A scalable, end-to-end IoT and remote sensing platform for precision rangeland and livestock management

• Farm-scale ecosystem accounting was developed combining spatial, field and farm data within a standard framework. • Spatial datasets offered acceptable accuracy for assessing extent, conditions, and services flow at the farm level. • Accuracy limitations were primarily observed for above ground biomass in dense forests and for carbon in soil. • Farm-provided data were essential for evaluating cropland condition indicators and service flow. • Farm level ecosystem accounts provide helpful information for farm management. Demand for monitoring the supply and use of natural resources in agriculture is growing. Farming depends on ecosystem services yet contributes to their loss. Ecosystem accounting frameworks help to integrate nature into decision-making by consistently revealing those impacts and dependencies. We apply the United Nations’ System of Environmental-Economic Accounting – Ecosystem Accounting (SEEA EA) to a 38,603-hectare farm in southern Amazonia, Brazil. We assess uncertainties in spatial datasets compared to field data, and evaluate their suitability for the accounts. Our results show that combined spatial and field data allow farm-level monitoring of ecosystem extent, integrity, and services that is consistent with SEEA EA. Farm data effectively capture nitrogen use efficiency and pesticide-related biodiversity risks. Land-use and carbon flows could be tracked with acceptable accuracy with spatial data, while soil variables had to rely solely on field data. Despite these uncertainties, the accounts deliver actionable insights. For farmers who often perceive forest as a burden, the accounts clarify the role of forests in sustaining key services for their rainfed crops, such as rainfall regulation and carbon sequestration with associated climate regulation benefits. Consistent yearly monitoring also supports informed decisions on managing and financing agriculture for better use of natural capital.

Investigating attributes for selecting nurse sows in swine herds of Minnesota, USA, using Best-Worst Scaling analysis.

Soil characteristics and agricultural management shape the community composition of the white grub complex (Coleoptera: Melolonthidae) in native maize agroecosystems

Comparative analysis of SAR-based soil moisture inversion methods for crop-covered under cloudy, rainy, and irrigation conditions

To overcome the inherent limitations of pristine red mud, such as low adsorption capacity and the risk of secondary toxic leaching, a red mud-sodium alginate (RMSA) hydrogel was synthesized via a calcium chloride cross-linking method for heavy metal remediation. Batch experiments and characterization analyses revealed that the sequestration of heavy metals is driven primarily by ion exchange and complexation, accompanied by specific mineral precipitation for Pb(II). Compared to pristine red mud, the RMSA composite exhibited significantly enhanced maximum adsorption capacities of 454.5, 151.0, and 86.8 mg g-1 for Pb(II), Cd(II), and Cu(II), respectively, well-described by the Langmuir and PSO models. In multimetal systems, RMSA demonstrated preferential uptake of Pb(II) due to its smaller hydration radius. Importantly, practical application tests validated the robust performance of RMSA in complex real wastewater, achieving an 85.5% removal rate for Pb(II). Furthermore, TCLP tests confirmed the absolute environmental safety of the spent hydrogel with a negligible leaching rate (<0.03%), effectively reducing secondary pollution risks. Combined with its moderate reusability over five regeneration cycles and a production cost that is 67.5% lower than that of commercial alternatives, RMSA represents a sustainable and cost-effective strategy for using waste to treat waste in practical wastewater purification and agricultural water management.