Search Results (26,579)

Improving the nutritional quality of food through advanced and sustainable agricultural practices has become a key objective of modern vegetable crop production. Emphasis is placed on increasing the content of health-promoting bioactive compounds, such as vitamins and polyphenols, particularly flavonoids whose accumulation is strongly affected by various biotic and abiotic stress factors. To mitigate stress-induced limitations and enhance plant performance, biostimulants are increasingly applied. Among them, Trichoderma spp. are widely recognized for their ability to promote plant growth and resilience, primarily through enzymatic activity and the production of bioactive metabolites. The aim of this study was to evaluate the potential of the native Trichoderma sp. strain STP8 to enhance the production of bioactive compounds through seed and soil applications at planting and 26 days after planting (DAP), applied individually or in combination. A spore suspension (4 × 10⁶ spores mL⁻¹) was used. The experiment was arranged in a randomized complete block design with five replicates. At harvest (43 DAP), dry matter, ascorbic acid, chlorophyll, and carotenoid contents were determined. Additionally, flavonoids and non-flavonoids, total phenolics, individual phenolic compounds, and antioxidant capacity were analyzed. Achieved results demonstrate that the effects of the native Trichoderma sp. strain STP8 on lettuce secondary metabolism and antioxidant properties are strongly dependent on the developmental stage at which inoculation is performed, providing further insight into the stage-specific interactions between plans and Trichoderma. Practically, a single application at planting proved to be the most effective strategy for enhancing the accumulation of bioactive compounds, indicating that optimized application timing may improve the efficacy of Trichoderma-based biostimulants, while avoiding unnecessary repeated applications. These findings support the potential use of native Trichoderma strains as sustainable tools for improving the nutritional and functional quality of lettuce. Further research integrating physiological, biochemical, and molecular analyses is required to elucidate the mechanisms by which the native Trichoderma sp. strain STP8 regulates the biosynthesis of bioactive compounds in lettuce. Full article

This paper illustrates the theoretical framework, the methodological approach, and the primary findings of a project titled MASSTER (Managing(South)Africa-and-Senegal-Sustainability-Targets-through-Economic-diversification-of-Rural-areas), in which higher educational institutions (HEIs) and organizations from Senegal, South Africa, and Europe collaborate with the aim of addressing the nexus between migration, agriculture and development in Sub-Saharan Africa by co-creating evidence-based training, tools, and actions to foster development and co-development while targeting several Sustainable Development Goals (SDGs), namely Zero-hunger, Good-Health-and-Wellbeing, Gender-Equality, Quality-education, Decent-work-and-economic-growth, Responsible-consumption-and-production, all within the frame of Partnership-for-the-Goals. The MASSTER project employs a transdisciplinary and bottom-up approach based on a cross-sectional study conducted in South Africa and Senegal to identify actual challenges, needs, and resources from farmers (n = 737) and students enrolled in agricultural courses (n = 1.013). Findings underpinned the co-creation of the primary project outcomes: training on agritourism development, farm management, income-generating activities, climate change resilience, and food value chain; toolkits designed to boost the adoption of the Whole of Society Approach and to strengthen cooperation between HEIs and local communities; MASSTER Student-and-alumni-tracking-procedure-with-early-warning-mechanism-for-brain-drain; and a MOOC on critical-thinking-and-empowerment. The MASSTER project can have a relevant impact at local and international levels, providing evidence-based tools to be used by HEIs, stakeholders/policymakers, and the scientific community to actively foster development and co-development. Full article

Assessing the capacity conditions that support agricultural responses to climate-related risks is important for strengthening agricultural systems and ensuring food security. Using panel data from 31 Chinese provinces during 2011–2024, this study introduces the WSR methodology and constructs a capacity-oriented ACR index comprising resistance, adaptation, and transformative capacities. It examines the spatio-temporal evolution, spatial effects, convergence, and nonlinear driving mechanisms of the capacity-oriented ACR index. The results show that: (1) China’s capacity-oriented ACR index increased from 0.3318 in 2011 to 0.4525 in 2024, with higher levels in eastern and central China and lower levels in western China. Provinces with higher ACR index scores were concentrated in the Major Grain-Producing Areas (MGPA). (2) Spatial differences in ACR index scores were mainly attributable to grain functional areas, with the largest gap between the MGPA and the Balanced Grain Production and Consumption Areas (BGPCA). (3) ACR index scores exhibited significant spatial dependence, convergence, and positive spillover effects nationally and in most grain functional areas, whereas the Major Grain-Consuming Areas (MGCA) had not formed a stable convergence trend. (4) Multiple factors were nonlinearly associated with ACR index scores, with dominant drivers varying across grain functional areas. These findings support differentiated regional governance and optimized resource allocation. The findings reflect China’s specific institutional context, and the ACR index captures broad capacity conditions supporting agricultural responses to climate-related risks, which may limit generalizability. Full article

Legume–rhizobium symbiosis is fundamental to sustainable agriculture because it supplies biologically fixed nitrogen, improves soil fertility, and reduces reliance on synthetic fertilizers. However, abiotic and chemical stresses, including drought, salinity, flooding, temperature extremes, heavy metals, and organic pollutants, disrupt nodulation and biological nitrogen fixation, limiting crop productivity and ecosystem sustainability. This review synthesizes current knowledge of the regulatory networks that enable legume–rhizobium symbiosis to adapt to environmental stress. We discuss how stress influences symbiotic signaling, infection, oxygen homeostasis, nitrogenase protection, phytohormonal regulation, antioxidant defenses, exopolysaccharide production, and plasmid-mediated adaptation. We further highlight the roles of root nodule-associated microorganisms and microbial interactions in maintaining symbiotic stability under adverse conditions. Finally, recent advances in multi-omics, genome editing, synthetic biology, and microbial consortia are evaluated for their potential to improve stress-resilient bioinoculants. Collectively, this review emphasizes that resilience of the legume–rhizobium symbiosis is an integrated property of both plant and microbes and identifies key regulatory mechanisms that can be exploited to develop climate-resilient and sustainable agricultural systems. Full article

Accurate land-use polygon mapping for forest-oriented natural resource monitoring requires both image-based class prediction and the reconciliation of heterogeneous geospatial semantics. In operational mapping, land survey, forestry survey, and natural resource monitoring datasets often differ in classification systems, management objectives, boundary rules, and mapping scales, causing semantic conflicts when overlaid or forced into one-to-one categories. To address this issue, this study proposes a topology-aware land-use polygon-mapping framework that integrates multi-source semantic representation learning, semantically guided relation learning, and topology-constrained polygon optimization. In the experiments, remote sensing imagery provides visual evidence, the Third National Land Survey (TNLS) and forestry survey (FS) datasets are encoded as source-specific auxiliary semantic priors, and the natural resource integrated monitoring (NRIM) data serve only as reference labels for training and evaluation. Rather than resolving cross-source conflicts using predefined rules, the framework learns a unified land-use representation, transforms semantic boundary cues into a vertex-edge topology graph, and reconstructs GIS-compatible polygons through topology-constrained polygon optimization. In a representative forest–agricultural landscape, the method achieved an mIoU of 79.86%, an APLS of 56.82%, and a TOPO-F1 of 54.56%. These results suggest that learnable semantic harmonization and topology-aware polygon generation can improve the semantic consistency and vector reliability of land-use products for forest and natural resource monitoring. Full article

The probability estimation of agrometeorological damage risk is the core technical support for consolidating the agricultural disaster prevention and reduction system and ensuring the sustainable development of national agriculture. It has been widely applied in agricultural production and agricultural insurance. Based on the crop planting area data, as well as the damaged crop area data (damage-affected, damage-stricken, and dead harvest) of 31 provinces and municipalities from 1980 to 2018, this study creatively builds a comprehensive damage strength index. After that, this study obtains accurate risk probability estimation results of five meteorological damage types by using the parameters of the nonparametric normal information diffusion model. The results show that the risk probability of comprehensive meteorological damage is the largest, followed by drought, flood, wind and hail, and freezing. Flood in Hubei, drought in NeiMenggol, windstorm and hailstorm in Qinghai, freezing damage in Hainan, and comprehensive meteorological damage in NeiMenggol have the highest risk probability. The regions where various meteorological damage occur show different distribution characteristics, which is closely related to the latitude and longitude and topography of China. These findings indicate that it is necessary to understand the overall patterns of agrometeorological damage risks and consider their internal heterogeneity, in order to take targeted prevention and control measures to avoid systemic risks in agricultural production and safeguard sustainable and high-quality agricultural development. Full article

This study investigates how smallholder farmers and vendors in Piracicaba, Brazil, navigate the tensions between standardized spatial governance and heterogeneous livelihood strategies in the rural–urban transition. Based on 25 semi-structured interviews with participants in municipal open-air markets (varejões), we analyze how policies implemented by the Municipal Secretariat of Agriculture and Food Supply (SEMA), including rigid price controls, mandatory MEI registration, and inflexible infrastructure rules, clash with the realities of organic, family-based, and mixed production systems. The findings reveal that SEMA’s one-size-fits-all approach fails to account for real production costs, quality differentiation, and informal cooperation, thereby penalizing innovation and marginalizing vulnerable producers. Rather than passive recipients, vendors actively resist and reshape governance through income diversification, informal cooperatives, direct sales, and ethical redefinitions of agricultural work. We argue that effective spatial governance must move beyond technical standardization and instead recognize productive heterogeneity and local agency as central to sustainable rural–urban transitions. This Brazilian case offers a critical counterpoint to top-down models and underscores the need for flexible, participatory, and context-sensitive policy design. Full article

Using balanced panel data for 30 Chinese provinces from 2014 to 2023, this study examines the relationship between digital village development and input-related agricultural carbon emissions in China. A composite digital village index is constructed from eight standardised indicators, and PCA diagnostics together with a PCA-based alternative index are used to assess index validity and sensitivity. Two-way fixed-effects models are used for empirical estimation. The results show that digital village development is significantly associated with lower agricultural carbon emissions after controlling for economic, fiscal, technological, regulatory, provincial, and temporal factors. The finding remains robust when using a rural e-commerce proxy and alternative specification checks. The lagged digital index has a negative coefficient but is less precisely estimated after the first-year observations are excluded. Heterogeneity analysis shows that the association is stronger in provinces with higher rural educational attainment, in Central China, and in major grain-producing areas, while the coefficient for grain-balanced areas is negative but not statistically significant. Mechanisation-based subgroup results further show that the negative association is more pronounced where agricultural mechanisation is relatively advanced. These findings suggest that rural digitalisation can support a low-carbon agricultural transition, particularly when digital infrastructure is transformed into effective industrial applications, public services, human capital development, and improved production organisation. This study focuses on input-related and field-operation-related agricultural carbon emissions rather than a complete agricultural greenhouse gas inventory including methane, nitrous oxide, and manure management and land use change emissions. Full article

Salinity poses a major threat to sustainable agriculture and coastal ecosystems, resulting in a substantial loss of plant productivity and biodiversity. Although some coastal grass species exhibit natural adaptation to saline conditions, the physiological mechanisms underlying salt tolerance remain incompletely understood, particularly regarding the contribution of plant-associated microorganisms. In a previous study, a commercial cultivar of red fescue (Festuca rubra ssp. rubra cv. Rafael) was shown to be salt sensitive when grown hydroponically, whereas wild populations of F. rubra commonly occur in coastal salt marshes (possibly ssp. litoralis). We hypothesized that this difference in salt tolerance is partly associated with beneficial fungal plant interactions. To test this hypothesis, we investigated whether inoculation with a fungal isolate designated Fusarium sp. 1 and isolated from F. rubra growing on a salt marsh along the Dutch Wadden Sea coast could improve the salinity tolerance of the commercial cultivar. The results showed that inoculation with Fusarium sp. 1 alleviated the salt-induced growth inhibition. At 100 mM NaCl, shoot and root biomass were partially restored relative to non-inoculated controls, accompanied by a significant increase in the shoot-to-root ratio. To investigate the physiological basis of this response, we applied the Microelectrode Ion Flux Estimation (MIFE) technique to quantify Na⁺ -induced K⁺ efflux in roots. Inoculated plants exhibited improved K⁺ homeostasis, characterized by a reduced instantaneous Na⁺-induced K⁺ efflux and a faster recovery of root fluxes. Moreover, inoculated plants grown at 50 and 100 mM NaCl displayed 333% and 397% greater net K⁺ influx, respectively, compared with non-inoculated controls. Our results indicated that inoculation with Fusarium sp. 1 improves the salinity tolerance of F. rubra, likely through enhanced root K⁺ retention. These findings suggest that commercial F. rubra cultivars remain responsive to beneficial microbial associations and highlight the potential of exploring plant–microbe interactions from naturally salt-adapted environments to improve salinity resilience in grasses and potentially other crops. Full article

The increasing pressure on water resources is one of the most critical challenges of the 21st century. Demographic, industrial, and climatic factors are drastically reducing the availability of fresh water, with particularly pronounced effects in arid regions and the Mediterranean basin. Agriculture, which accounts for about 70% of global water withdrawals, is at the centre of this crisis, making it essential to explore unconventional sources such as brackish water. Desalination emerges as a key technology to address this challenge. Electrodialysis offers an attractive alternative, particularly suitable for moderately salty water (1000–5000 mg/L of total dissolved solids), thanks to its energy efficiency within specific salinity ranges and the ability to precisely control the quality of the produced water. At the same time, agrivoltaic systems that integrate energy production and agriculture are spreading, requiring compact, modular treatment devices that can be integrated with renewable sources. This research objective is the design and building of an affordable and reproducible electrodialysis (ED) prototype, equipping the system with automated sensor-based control, validating the device performance on brackish water and analyzing the feasibility of integration in agrivoltaic contexts. Full article

Animal transport connects farms with slaughterhouses, breeding units and production sites, but remains one of the most debated animal welfare issues of recent decades. These debates also touch on the EU–Mercosur agreement in the areas of agribusiness and animal farming. The aim of this article is to examine the legislation of Brazil and Germany and the European Union (EU) regarding animal transport, using specific examples to identify differences and similarities that may form the basis for joint discussions on this area of animal welfare. The EU Transport Regulation for the Protection of Farm Animals applies in all EU member states (Council Regulation (EC) No 1/2005). In Germany, the Animal Welfare Transport Ordinance transposes EU law into national law. The transport times depend on vehicle type and equipment and vary according to the animal species to be transported. The basic maximum travel time is 8 h for commercial transport and distances longer than 65 km. In Brazil, there exists a wide range of laws, regulations, decrees and guidelines governing the protection of animals during transport in the different Brazilian states, mostly coordinated by the Brazilian Ministry of Agriculture and Livestock (MAPA). Allowed transport times in Brazil vary largely from 4 to 12 h between single state regulations and are less regulated in detail. Maximum Transport durations can be repeated several times after appropriate stops for animal feeding and watering. Similarly to Germany/EU, only animals “fit for travel” are allowed to be transported and the responsibility for the transported animals ends once the last animal has been unloaded at its place of destination. Temperatures in Germany/EU are generally moderate, whereas Brazil and South America have tropical and subtropical climates. Furthermore, the distances between farms and abattoirs in Brazil are generally greater, and transport vehicles often have to travel on unpaved (gravel) roads, e.g., to reach the farms. The key to animal-friendly transport lies in loading healthy, “transport-fit” animals on suitable vehicles with sufficient space and necessary equipment, and licensed and committed drivers. This has to be supported by appropriate legal provisions. Animal welfare laws in both Brazil and Germany/EU aim to ensure the best possible welfare of animals during transit under the given circumstances of transport, in order to prevent pain, suffering and injury. This shared commitment to animal welfare provides a substantiated basis for mutual understanding and cooperation in livestock farming, which may prove helpful in the discussions on the agricultural chapter of the EU–Mercosur Agreement. Full article

Soil quality is a critical factor impacting agricultural productivity and ecosystem functions. Accurate assessment of soil quality is crucial for sustainable agricultural development. Xinjiang is the primary cotton-producing region in China. Its unique geographical condition, characterized by two basins surrounded by three mountains, results in distinct climatic conditions, soil-forming factors, and soil physical and chemical properties across different cotton-growing areas. The spatial differentiation patterns of soil quality and their primary factors in cotton-growing regions of different river basins are not yet fully understood. This study focused on four typical cotton-growing areas of Xinjiang, China. A total of 1588 plow-layer soil samples were collected, and 21 indicators covering soil physical, chemical, and environmental properties were measured. By constructing a minimum data set (MDS) and comparing the performance of linear (LS) and non-linear (NLS) scoring functions, the effects of geographical environmental factors on the spatial distribution patterns of soil quality in cotton fields of different basins were analyzed. The results showed the MDS, composed of data on soil bulk density and the contents of organic matter, available iron, available zinc, nickel, sand, and silt, could replace the total data set. The NLS-MDS was identified as the optimal assessment model. Its Nash–Sutcliffe efficiency coefficient (E_f = 0.84) and coefficient of determination (R² = 0.70) were both higher than those of the linear model (E_f = 0.79, R² = 0.66). The study also revealed significant spatial heterogeneity in soil quality across different cotton-growing areas. The average soil quality index (SQI) in the Aksu River Basin (SQI_NLS-MDS = 0.53) and Xiaohaizi Basin (SQI_NLS-MDS = 0.50) was significantly higher than that in the Kuitun River Basin (SQI_NLS-MDS = 0.44) and Manas River Basin (SQI_NLS-MDS = 0.41). Random forest analysis demonstrated that the relative importance of topographic (digital elevation model) and climatic factors (annual mean temperature, annual mean precipitation) on SQI was higher than that of the vegetation factor (normalized difference vegetation index). The strong interaction between topographic and climatic factors was the primary driver of the spatial distribution of soil quality. This study confirms significant spatial heterogeneity of soil quality in cotton fields across different river basins in Southern and Northern Xinjiang, and identifies the synergistic interaction between topographic and climatic factors as the dominant driver of this heterogeneity in arid regions. These findings provide a scientific basis for implementing site-specific agricultural management in arid regions. Full article

Decision support systems (DSSs) help farmers and decision-makers to find cropping systems which increase productivity while decreasing the use of fertilizers and irrigation; however, few DSSs exist which integrate soil carbon models, especially in Mediterranean climate. Here, we test whether RothC20_N, a version of the widely used RothC model adapted for Mediterranean and arid climates, can estimate the soil water content (SWC), soil organic carbon (SOC), and soil respiration (Rs), observed in two different cropping systems, one traditional and the other informed by the DSS by Horta Srl. The model was calibrated and tested against two long-term (8 years) field experiments in two different areas in Italy. The two sites showed characteristically dry soils during the summer period; RothC20_N was able to predict correctly the soil water content time series observed in both sites. RothC20_N could predict the measured SOC and heterotrophic respiration time series with Nash–Sutcliff efficiency ~0.3, normalized root mean squared error ~0.4, and Kling–Gupta efficiency > 0. This study shows that the multi-objective calibrated RothC20_N is an interesting candidate for inclusion in a DSS to broaden the potential of the DSS to increase the sustainability of agricultural practices by also addressing soil carbon dynamics while maintaining high agricultural productivity. Full article

As a vital grain production base in China, soil health and crop productivity in Northeast China are critical to national food security. Straw return is a key practice for improving soil fertility and crop yield, yet its effectiveness is subject to complex regulation by regional environmental and management factors. In this study, a meta-analysis was conducted to systematically evaluate the effects of straw return on soil organic carbon (SOC) stocks and maize yield in croplands of Northeast China, and to quantify the moderating roles of climatic conditions, soil properties, fertilization management, and straw return techniques. The results showed that straw return increased topsoil (0–20 cm) SOC stocks by an average of 10.1–18.1%. Among the evaluated categories, comparatively greater mean SOC responses were observed under low temperature (mean annual temperature < 5 °C), low precipitation (annual precipitation of 300–400 mm), low initial SOC concentration (20–30 g kg⁻¹), and Chernozems. For maize yield, comparatively high mean responses were observed under a mean annual temperature of 5–10 °C, annual precipitation of 600–700 mm, moderate initial SOC concentration, and brown soils. Regarding fertilization management, N application at 200–250 kg ha⁻¹ was associated with a comparatively greater mean maize-yield response in the subgroup analysis, whereas SOC responses varied among N, P, and K application rates and fertilization methods. Therefore, the identified environmental and management ranges represent category-specific associations within the available dataset rather than causal or universally applicable optima. In terms of straw return practices, a duration of 5–10 years, incorporation of chopped straw, and full straw return were associated with relatively favorable responses among the evaluated categories. Structural equation modeling revealed that the direct path from SOC stock to maize yield was not significant (path coefficient = 0.07), being masked primarily by the fertilization effect (path coefficient = 0.67) and the carbon saturation mechanism (negative contribution of initial SOC, −0.83). This study uncovers a complex relationship between SOC stocks and crop yield. In practice, agricultural producers should select straw-return methods and amounts according to local climatic and soil conditions, consider chopped-straw incorporation under suitable local conditions, and coordinate straw inputs with soil-test-based, balanced N, P, and K fertilization and field monitoring rather than applying a single universal recommendation. Full article

This study evaluated a cost-effective UAV-based multi-sensor approach for characterizing river corridor conditions during and after moderate floods in two mountain river corridors in Northern Utah, USA: the Logan River and Blacksmith Fork River. These study reaches included urban, rural, and agricultural areas, hydraulic structures and bridges, and fish passage structures. A DJI Matrice 300 UAV was used with two separate payloads: an AgEagle Altum-PT multispectral camera and an R3 Pro V2 two-return LiDAR system. The workflow included UAV flight planning and data collection, post-processing of the multi-spectral and LiDAR sensor data, spatial resolution and accuracy assessment, and interpretation of the resultant data. The multi-spectral post-processing produced pansharpened orthomosaics with a spatial resolution of 0.0432 m, while the UAV LiDAR produced DSM/DTM products at 0.05 m resolution. LiDAR accuracy assessment showed vertical RMSE values of approximately 0.0602 m for the Blacksmith Fork and 0.0782 m for the Logan River. The results showed that multispectral imagery and 2-band LiDAR provided a cost-effective means for detailed remote sensing with each sensor providing complementary information for flood and river corridor assessment. Multispectral imagery supported interpretation of flood extent, vegetation condition, relative turbidity, and thermal patterns, while LiDAR captured terrain and surface features such as banks, levees, floodplain surfaces, channel modifications, and structures. The integrated datasets supported maximum flood extent mapping and flood-level estimation. These datasets can support reach-scale hydraulic modeling, catchment hydrology, river corridor ecology, floodplain conditions, and real-time monitoring of floods, in addition to quantification of flood hazards or post-flood impacts for municipalities and insurers. Full article