Search Results (3,530)

Reflection on sustainable economic models, such as the civil economy, has led to the development of alternative food supply chains grounded in ethical values and practices. From this perspective, the Food Village model was proposed to meet stakeholders’ needs, overcome the limitations of Alternative Food Networks, and scale up. In this study, a Discrete Choice Experiment on hypothetical Food Village participation scenarios was combined with the Portrait Values Questionnaire to analyse preferences for the model’s attributes in relation to personal values. The results indicate that consumers appreciate the ethical and territorial characteristics of Food Village, such as local and organic products and cooperative governance, as long as convenience is guaranteed (product variety, flexible hours). Furthermore, they prefer moderate forms of participation, while excessively burdensome involvement reduces their willingness to participate. Individual values influence preferences: values of “self-transcendence” and conservation are associated with greater willingness, while those of “self-affirmation” correlate with lower adherence to Food Village. This evidence suggests implications for policy and scalability: initiatives like Food Village, if supported by public incentives and flexible participatory schemes, can contribute to more sustainable food systems at scale. Full article

Remote Indigenous communities experience persistent inequities in access to fresh and nutritious foods due to the fragility of perishable food supply chains (PFSCs). Disruptions across procurement, transportation, storage, retail, and limited local production restrict access to perishable foods, contributing to food insecurity and diet-related health risks. This scoping literature review synthesizes evidence from 84 peer-reviewed, grey, and unpublished sources across fourteen countries to map PFSC management (PFSCM) challenges affecting food access in remote Indigenous communities worldwide and to synthesize reported practices implemented to address these challenges. PFSCM challenges were identified across all supply chain levels, and five categories of reported practices emerged: PFSC redesign strategies, forecasting and decision-support models, technological innovations, collaboration and coordination mechanisms, and targeted investments. These findings informed the development of a multi-scalar conceptual framework comprising seven interconnected PFSCM clusters that organize how reported practices are associated with multiple food access dimensions, including quantity, affordability, quality, safety, variety, and cultural acceptability. This review contributes an integrative, system-oriented synthesis of PFSCM research and provides a conceptual basis to support future scholarly inquiry, comparative inquiry, and policy-relevant discussion of food access and health equity in remote Indigenous communities. Full article

PIN-LIKES (PILS) auxin transport genes play key roles in plant development, but their functions and molecular mechanism in soybean yield remain unclear. Here, we characterized the 44-member soybean GmPILS genes via comprehensive analyses. Phylogenetic analysis classified GmPILS into three subfamilies, with most proteins being hydrophobic, stable, and membrane-localized. Chromosomal distribution showed random scattering across 17 chromosomes, with gene duplication driving family expansion. Expression profiling identified GmPILS36 and GmPILS40 as seed-specific and differentially expressed between cultivated Suinong14 (SN14) and wild ZYD00006 (ZYD06) soybeans. Population genetic analyses revealed GmPILS40 experienced a domestication bottleneck without yield-related superior haplotypes, while GmPILS36 underwent selection during landrace-to-improved variety domestication. A coding region CC/TT natural variation in GmPILS36 (S/A substitution) was significantly associated with seed weight per plant and 100-seed weight, with the TT genotype conferring superior traits. This study provides insights into GmPILS genes’ evolution and identifies GmPILS36 as an important candidate gene for further functional study and investigation of the molecular mechanisms regulating soybean yield. Full article

Orchard crops generate substantial quantities of diverse biomass each year, with grapevines being among the most economically significant species worldwide. Considering the scale of this biomass, there is a growing need to explore rational strategies for its utilisation, for example, for energy production or other value-added applications. Such approaches may contribute to improving resource efficiency and reducing the environmental burden associated with agricultural waste. The aim of this study was to examine the energy potential of woody post-production waste from wine processing, with particular emphasis on grape stems of four cultivars—Chardonnay, Riesling, Merlot, and Zweigelt—grown in two contrasting climatic regions: south-eastern Poland and Moravia (Czech Republic). The results demonstrated that both the grape variety and cultivation site significantly influenced the majority of bunch biometric traits, including bunch and berry weight, berry number, and stem dimensions. A moderately warm climate promoted the development of larger and heavier bunches as well as more robust stems across all examined cultivars. Energy analyses indicated that Zweigelt stems produced under moderately warm conditions and Chardonnay stems from a temperate climate exhibited the most favourable combustion properties. Nonetheless, certain constraints were identified, such as increased ash (12.20%) and moisture content (11.51%) in Chardonnay grown in warmer conditions, and elevated CO and CO₂ emissions observed for Zweigelt (1333.26 kg·mg⁻¹). Overall, the findings confirm that grape stems constitute a promising local source of bioenergy, with their energy performance determined predominantly by varietal characteristics and climatic factors. Their utilisation aligns with circular-economy principles and may help reduce the environmental impacts associated with traditional viticultural waste management. Full article

Shear lag is the phenomenon that occurs when a supported slender member undergoes deformation from lateral loading, causing in-plane non-uniform distribution of stresses that results in reducing the member’s minimum strength capacity. This paper investigates the behaviour of shear distribution in steel I-section and box girders when subjected to both static and impact loadings. Three-dimensional finite element analysis models were prepared in Strand7 and validated against experimental results providing a basis for further comparison research into shear lagging effects. A parametric study was conducted comparing the effects of impact loading through certain specified velocities at the midspan of restrained ends. It provided new insights into the distribution of shear lag and prevalence of loading locality when considering unique impact scenarios. Impact loads provided different shear-lag results compared to static loads as the material’s properties absorb energy through deformation and distribution of stress. Furthermore, the study highlights the need for additional investigation into a variety of impact scenarios and possible factors for designers to consider when implementing members in structures. Full article

Korla fragrant pear (Pyrus sinkiangensis), valued for its unique flavor, suffers from freezing damage in its native Xinjiang. Previous studies indicated a strong correlation between low-temperature stress and the expression of LEA genes, particularly PsLEA4. This study cloned PsLEA4 from P. sinkiangensis and overexpressed it in paper mulberry (Broussonetia papyrifera). The encoded 368-amino-acid protein is localized to the endoplasmic reticulum. Under −4 °C stress, the proline and soluble protein contents in the overexpressing lines increased to 1.21-fold and 1.36-fold, respectively, compared to the wild type, while relative water content (RWC) reached 1.58-fold. And catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) activities increased by 9%, 16%, and 38%, respectively. During overwintering, the transgenic line exhibited soluble protein content and RWC at 1.78-fold and 1.49-fold compared to those of the wild type, respectively. Malondialdehyde (MDA) and relative electrolyte leakage (REL) levels were only 66% and 63% of the wild type, while CAT and POD activities reached 1.87-fold, and SOD activity peaked at 2.49-fold. These adaptations were associated with improved cold tolerance and with bud break occurring 7–10 days earlier than in WT the following year. These findings could help to understand the molecular mechanisms of P. sinkiangensis for overwintering and provide new genetic resources to breed varieties of pear that can resist cold temperatures. Full article

From a configuration perspective, by using 99 prefecture-level cities in the Yellow River basin as a sample, this paper reveals a variety of pathways through which digital and intelligent technologies, in synergy with multiple factors, strengthen the resilience of agricultural industrial chains. The research findings are as follows: First, none of the antecedent conditions are essential for strengthening the resilience of the high agricultural industrial chain in the Yellow River Basin. Nevertheless, digital and intelligent technologies and digital infrastructure are central conditions in all four configurations that enhance the resilience of the agricultural industrial chain. Second, the four configurations that produce high agricultural industrial chain resilience are enabled by technology, driven by information, facilitated through multi-stakeholder collaboration, and guided by policy, and there are certain complementary and substitutive relationships among these conditions. Third, the configuration which is empowered by technology fits regions with well-developed digital infrastructure and established goose-formation agricultural entities; the configuration that is driven by information fits areas with limited fiscal support but robust digital infrastructure; the multi-stakeholder collaborative configuration fits regions with strong economic foundations, robust fiscal support, and advanced digital infrastructure; and the configuration which is guided by policy fits areas with weaker economic foundations but advanced digital infrastructure and diverse agricultural entities. The above conclusions, by revealing the diverse pathways by means of which digital technologies strengthen the resilience of the agricultural industrial chain in the Yellow River Basin, demonstrate that regional development must adopt tailored methods which are suited to local conditions. They also provide novel solutions for sustainable agricultural development. Full article

To address the issue of drought level confusion in the detection of drought stress during the seedling stage of the Yunnan large-leaf tea variety using the traditional YOLOv13 network, this study proposes an improved version of the network, MC-YOLOv13-L, based on animal vision. With the compound eye’s parallel sampling mechanism at its core, Compound-Eye Apposition Concatenation optimization is applied in both the training and inference stages. Simulating the environmental information acquisition and integration mechanism of primates’ “multi-scale parallelism—global modulation—long-range integration,” multi-scale linear attention is used to optimize the network. Simulating the retinal wide-field lateral inhibition and cortical selective convergence mechanisms, CMUNeXt is used to optimize the network’s backbone. To further improve the localization accuracy of drought stress detection and accelerate model convergence, a dynamic attention process simulating peripheral search, saccadic focus, and central fovea refinement in primates is used. Inner-IoU is applied for targeted improvement of the loss function. The testing results from the drought stress dataset (324 original images, 4212 images after data augmentation) indicate that, in the training set, the Box Loss, Cls Loss, and DFL Loss of the MC-YOLOv13-L network decreased by 5.08%, 3.13%, and 4.85%, respectively, compared to the YOLOv13 network. In the validation set, these losses decreased by 2.82%, 7.32%, and 3.51%, respectively. On the whole, the improved MC-YOLOv13-L improves the accuracy, recall rate and mAP@50 by 4.64%, 6.93% and 4.2%, respectively, on the basis of only sacrificing 0.63 FPS. External validation results from the Laobanzhang base in Xishuangbanna, Yunnan Province, indicate that the MC-YOLOv13-L network can quickly and accurately capture the drought stress response of tea plants under mild drought conditions. This lays a solid foundation for the intelligence-driven development of the tea production sector and, to some extent, promotes the application of bio-inspired computing in complex ecosystems. Full article

The present paper examines the degree of acceptance of eco-schemes by farmers. Specifically, eco-schemes, the new form of direct subsidies under the current Common Agricultural Policy (CAP) 2023–2027, are the focus of investigation regarding the motivations for participation, barriers to inclusion and advisory requirements for their successful implementation. This study was conducted at the regional unit (RU) of Serres (Central Macedonia, Greece) and combines both qualitative and quantitative research on the participation of local producers in eco-schemes during the years 2023 and 2024. Taking into account both statistical data on participation in eco-schemes in the Serres regional unit, as well as the members of the Agricultural Cooperative and the results of a survey conducted through a questionnaire, a variety of motivations and barriers for participation emerge. These include factors related to the personal characteristics of the producers, the structural features of their agricultural enterprises, as well as the type of commitments associated with eco-schemes. Finally, specific training/advice needs have been identified for their successful implementation. Full article

The research for crop improvement is a continuous process that enhances plant quality, yield, and ameliorates their adaptability to changing climatic conditions. Chilli is cultivated worldwide as a vegetable, spice, or natural colour additive and is an economically and medicinally important crop. A basic requirement for crop improvement in breeding programmes is the presence of genetic diversity within the crop. Smallholder farmers of chilli usually face challenges in acquiring commercial hybrid seeds because of their high cost and the need for annual purchases. Open-pollinated varieties (OPVs) can serve as a sustainable alternative that provides broader genetic variability, allowing adaptation to local growing conditions, and enabling farmers to save seeds for successive planting season. These characteristics make OPVs economically viable and valuable genetic resources for future chilli cultivation and breeding programmes. This review highlights the potential of OPVs in promoting sustainable chilli cultivation, enhancing genetic diversity, and supporting breeding to develop resilient and economically viable cultivars. Full article

Our work develops the structural mathematical framework of the REGENerative Agriculture (REGENA) Production Function, contributing to the limited global literature of regenerative farming production functions with consistency to the 2nd Law of Thermodynamics and the underlying biophysical processes for ecosystem services’ generation. The accurate structural economic modeling of regenerative farming practices comprises a first vital step for the shift of global agriculture from conventional farming—utilizing petrochemical fertilizers, pesticides and intensive tillage—to regenerative farming—utilizing local agro-ecological capital forms, such as micro-organisms, organic biomasses, no-tillage and resistant varieties. In this context, we empirically test the REGENA structural change patterns with data from eight experimental plots in six Mediterranean countries in Southern Europe and Northern Africa for three crop compositions: (a) with exclusively conventional practices, (b) with exclusively regenerative practices and (c) with mixed conventional and regenerative practices. Finally, we discuss in detail the scientific, institutional, economic and financial engineering challenges for the market uptake of regenerative farming and the contribution of REGENA for the achievement of this goal. In addition, as regenerative farming is knowledge-intensive, we review the vital aspect of Open Innovation (OI) and protected Intellectual Property (IP) business models as essential parts of regenerative farming knowledge-sharing clusters and trading alliances. Full article

This article presents a historiographical survey of scholarship on Islamic law and legal authority in Central/Inner Asia under Russian Imperial rule. It analyzes the debates, paradigms and assumptions that have dominated the field up to the present. The binaries that have dominated the field—between cooperation and insulation, rupture and continuity—disguise the complex legal history of the region. The historiography has shifted to emphasize a more pluralistic legal landscape, shaped by imperial intervention, local custom, practical considerations, and agency of ordinary Muslims. I suggest that by integrating a variety of sources, both archival and Islamic, scholars can take a bolder anthropological turn to develop new directions in historiography that will involve studying the lived experiences of legal actors and ordinary Muslims, gendered dimensions of legal practice, the meanings of socio-legal institutions, and the daily interaction between religious scholars and their communities. Full article

Mango is the second most widely cultivated tropical fruit in the world. Its harvesting mainly relies on manual labor. During the harvest season, the hot weather leads to low working efficiency and high labor costs. Current research on automatic mango harvesting mainly focuses on locating the fruit stem harvesting point, followed by stem clamping and cutting. However, these methods are less effective when the stem is occluded. To address these issues, this study first acquires images of four mango varieties in a mixed cultivation orchard and builds a dataset. Mango detection and occlusion-state classification models are then established based on YOLOv11m and YOLOv8l-cls, respectively. The detection model achieves an AP_0.5–0.95 (average precision at IoU = 0.50:0.05:0.95) of 90.21%, and the accuracy of the classification model is 96.9%. Second, based on the mango growth characteristics, detected mango bounding boxes and binocular vision, we propose a spatial localization method for the mango grasping point. Building on this, a mango-grasping and stem-cutting end-effector is designed. Finally, a mango harvesting robot system is developed, and verification experiments are carried out. The experimental results show that the harvesting method and procedure are well-suited for situations where the fruit stem is occluded, as well as for fruits with no occlusion or partial occlusion. The mango grasping success rate reaches 96.74%, the stem cutting success rate is 91.30%, and the fruit injury rate is less than 5%. The average image processing time is 119.4 ms. The results prove the feasibility of the proposed methods. Full article

Nelumbo nucifera (Lotus) is an economically important aquatic crop frequently challenged by abiotic stresses. The plant cell wall, a primary interface with the environment, undergoes dynamic remodeling to balance structural integrity with adaptation. UDP-glucuronic acid decarboxylase (UXS), a key enzyme synthesizing the nucleotide sugar precursor UDP-xylose, exists in distinct membrane-bound (e.g., Golgi) and cytosolic forms, channeling substrates into compartmentalized polysaccharide biosynthesis pathways and positioning the UXS family as a crucial regulator linking cell wall metabolism to plant adaptation. Here, we systematically characterized the NnUXS gene family in lotus through genome-wide identification, evolutionary synteny analysis, and functional validation. Integrated bioinformatic analysis revealed their physicochemical properties, motif patterns, and regulatory cis-elements, suggesting potential roles in growth and salt stress responses. Among the family, NnUXS3 was prioritized due to its preferentially upregulated in small plant architecture (SPA) varieties, its early induction under salt stress (0.5 days, 200 mM NaCl), and its highest predicted binding affinity for UDP-GlcA (−8.9 kcal/mol). Subsequent functional validation confirmed its dual role: heterologous overexpression in tobacco reduced plant height (47.22%) and leaf area (67.61%), while transient overexpression in lotus enhanced salt tolerance and shortened the petioles. This enhanced tolerance was achieved by upregulating key genes involved in polysaccharide biosynthesis (NnCSLC4, NnXTH22, NnCESA1) and antioxidant defense (NnSOD, NnPOD). Our findings establish NnUXS3 as a key mediator in balancing plant architecture and abiotic stress resilience. This work not only identifies a valuable genetic target for lotus breeding but also provides insights into the growth-stress trade-off, highlighting the importance of UXS subcellular localization in tailoring cell wall remodeling for environmental adaptation. Full article

Residues in the grain tank of seed-production wheat harvesters often cause varietal admixture, challenging seed purity maintenance above 99%. To address this, an intelligent cleaning system was developed for automatic residue recognition and removal. The system utilizes an RGB-D camera and an embedded AI unit paired with an improved lightweight object detection model. This model, enhanced for feature extraction and compressed via LAMP, was successfully deployed on a Jetson Nano, achieving 92.5% detection accuracy and 13.37 FPS for real-time 3D localization of impurities. A D–H kinematic model was established for the 4-DOF cleaning manipulator. By integrating the PSO and FWA models, the motion trajectory was optimized for time-optimality, reducing movement time from 9 s to 5.96 s. Furthermore, a gas–solid coupled simulation verified the separation capability of the cyclone-type dust extraction unit, which prevents motor damage and centralizes residue collection. Field tests confirmed the system’s comprehensive functionality, achieving an average cleaning rate of 92.6%. The proposed system successfully enables autonomous residue cleanup, effectively minimizing the risk of variety mixing and significantly improving the harvest purity and operational reliability of seed-production wheat. It presents a novel technological path for efficient seed production under the paradigm of smart agriculture. Full article