Search Results (7,484)

Precise recognition of individual ovine specimens plays a pivotal role in implementing smart agricultural platforms and optimizing herd management systems. With the development of deep learning technology, sheep face recognition provides an efficient and contactless solution for individual sheep identification. However, with the growth of sheep, their facial features keep changing, which poses challenges for existing sheep face recognition models to maintain accuracy across the dynamic changes in facial features over time, making it difficult to meet practical needs. To address this limitation, we propose the lifelong biometric learning of the sheep face network (LBL-SheepNet), a feature decoupling network designed for continuous adaptation to ovine facial changes, and constructed a dataset of 31,200 images from 55 sheep tracked monthly from 1 to 12 months of age. The LBL-SheepNet model addresses dynamic variations in facial features during sheep growth through a multi-module architectural framework. Firstly, a Squeeze-and-Excitation (SE) module enhances discriminative feature representation through adaptive channel-wise recalibration. Then, a nonlinear feature decoupling module employs a hybrid channel-batch attention mechanism to separate age-related features from identity-specific characteristics. Finally, a correlation analysis module utilizes adversarial learning to suppress age-biased feature interference, ensuring focus on age-invariant identifiers. Experimental results demonstrate that LBL-SheepNet achieves 95.5% identification accuracy and 95.3% average precision on the sheep face dataset. This study introduces a lifelong biometric learning (LBL) mechanism to mitigate recognition accuracy degradation caused by dynamic facial feature variations in growing sheep. By designing a feature decoupling network integrated with adversarial age-invariant learning, the proposed method addresses the performance limitations of existing models in long-term individual identification. Full article

Forests play a crucial role in storing excess carbon released into the atmosphere. By mitigating climate change, forest carbon stocks play a vital role in achieving green transitions. However, limited information is available regarding the factors that affect forest carbon stocks. The primary objective of this analysis is to investigate the impact of green agricultural technologies and bioenergy on forest carbon stocks. The empirical investigation was conducted using the method of moments quantile regression (MMQR) technique. Results using the MMQR approach indicate that bioenergy is beneficial in augmenting forest carbon stores at all levels. A 1% increase in bioenergy is associated with an increase in forest carbon stocks ranging from 3.100 at the 10th quantile to 1.599 at the 90th quantile. In the context of developing economies, similar findings are observed; however, in developed economies, bioenergy only fosters forest carbon stocks at lower and middle quantiles. In contrast, green agricultural technologies have an adverse effect on forest carbon stocks. Green agricultural technologies have a significant negative impact on forest carbon stocks, particularly between the 10th and 80th quantiles, with their influence declining in magnitude from −2.398 to −0.619. This negative connection is observed in both developed and developing countries at most quantiles, except for higher quantiles in developed economies. Gross domestic product (GDP) has an adverse effect on forest carbon stores only in developing countries, whereas human capital diminishes forest carbon stocks in both developed and developing nations. Governments should provide support for the creators of bioenergy and agroforestry technologies so that forest carbon stocks can be increased. Full article

This paper presents the design and implementation of a SLAM-based online mapping and autonomous trajectory execution system for the Nimbulus-e, a concept vehicle designed for agile maneuvering in confined spaces. The Nimbulus-e uses individual steer-by-wire corner modules with in-wheel motors at all four corners. The associated eight joint variables serve as control inputs, allowing precise trajectory following. These control inputs can be derived from the vehicle’s trajectory using nonholonomic constraints. A LiDAR sensor is used to map the environment and detect obstacles. The system processes LiDAR data in real time, continuously updating the environment map and enabling localization within the environment. The inclusion of vehicle odometry data significantly reduces computation time and improves accuracy compared to a purely visual approach. The A* and Hybrid A* algorithms are used for trajectory planning and optimization, ensuring smooth vehicle movement. The implementation is validated through both full vehicle simulations using an ADAMS Car—MATLABco-simulation and a scaled physical prototype, demonstrating the effectiveness of the system in navigating complex environments. This work contributes to the field of autonomous systems by demonstrating the potential of combining advanced sensor technologies with innovative control algorithms to achieve reliable and efficient navigation. Future developments will focus on improving the robustness of the system by implementing a robust closed-loop controller and exploring additional applications in dense urban traffic and agricultural operations. Full article

Micronutrients play a prominent role in plant growth and development, and their bioavailability is a growing global concern. Zinc is one of the most important micronutrients in the plant life cycle, acting as a metallic cofactor for numerous biochemical reactions within plant cells. Zinc deficiency in plants leads to various physiological abnormalities, ultimately affecting nutritional quality and posing challenges to food security. Biofortification methods have been adopted by agronomists to increase Zn concentrations in crops through optimal foliar and soil applications. Changing climatic conditions and conventional agricultural practices alter edaphic factors, reducing zinc bioavailability in soils due to abrupt weather changes. Precision agriculture emphasizes need-based and site-specific technologies to address these nutritional deficiencies. Nanoscience, a multidimensional approach, reduces particle size to the nanometer (nm) scale to enhance their efficiency in precise amounts. Nanoscale forms of Zn⁺² and their broad applications across crops are gaining attention in agriculture under varied application methods. This review focuses on the significance of Zn oxide (ZnO) nanoparticles (ZnONPs) and their extensive application in crop production. We also discuss optimum dosage levels, ZnONPs synthesis, application methods, toxicity, and promising future strategies in this field. Full article

Climate change has a significant negative impact on agriculture and food production. This trend requires technological development and the adaptation of new technologies in both the grapevine production and winemaking sectors. High temperatures and heat accumulation during the growing season result in faster ripening and a higher sugar content, leading to a higher alcohol content during fermentation. The negative consequences are an imbalanced wine character and consumer reluctance, as lower alcoholic beverages are now in high demand. Over the last decade, several methods have been developed to handle this impact and reduce the alcohol content of wines. In this study, we used the MASTERMIND^® REMOVE membrane-based dealcoholization system to reduce the alcohol concentration in of Pinot gris wines from 12.02% v/v to 10.69% v/v and to investigate the effect on analytical parameters in three steps (0.5%, 1%, and 1.5% reductions) along the treatment. To evaluate the impact of the partial alcohol reduction and identify correlations between the wine chemical parameters, data were analyzed with ANOVA, PCA, multivariate linear regression and cluster analysis. The results showed that except for the extract, sugar content and proline content, the treatment had a significant effect on the chemical parameters. Both free and total SO₂ levels were significantly reduced as well as volatile acid, glycerol and succinic acid levels. It must be highlighted that some parameters were not differing significantly between the untreated and the final wine, while the change was statistically verified in the intermediate steps of the partial alcohol reduction. This was the case for example for n-Propanol, i-Amylalcohol, Acetaldehyde, and Ethyl acetate. The multivariate linear regression model explained 18.84% of the total variance, indicating a modest but meaningful relationship between the alcohol content and the investigated analytical parameters. Our results showed that even if the applied instrument significantly modified some of the wine chemical parameters, those changes would not influence significantly the wine sensory attributes. Full article

South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments with heavy metals (HMs). This study investigated the distribution, mobility, and influencing factors of HMs at the sediment–water interface. To this end, sediment samples were analyzed from three key regions (Xiangjiang River estuary, Zishui River estuary, and northeastern South Dongting Lake) using traditional sampling methods and Diffusive Gradients in Thin Films (DGT) technology. Analysis of fifteen HMs (Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, V, Cr, Cu, Tl, Co, and Fe) revealed significant spatial heterogeneity. The results showed that Cr, Cu, Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, and Fe exhibited high variability (CV > 0.20), whereas V, Tl, and Co demonstrated stable concentrations (CV < 0.20). Concentrations were found to exceed background values of the upper continental crust of eastern China (UCC), Yangtze River sediments (YZ), and Dongting Lake sediments (DT), particularly at the Xiangjiang estuary (XE) and in the northeastern regions. Speciation analysis revealed that V, Cr, Cu, Ni, and As were predominantly found in the residual fraction (F4), while Pb and Co were concentrated in the oxidizable fraction (F3), Mn and Zn appeared primarily in the exchangeable fractions (F1 and F2), and Cd was notably dominant in the exchangeable fraction (F1), suggesting a high potential for mobility. Additionally, DGT results confirmed a significant potential for the release of Pb, Zn, and Cd. Contamination assessment using the Pollution Load Index (PLI) and Geoaccumulation Index (Igeo) identified Pb, Bi, Ni, As, Se, Cd, and Sb as major pollutants. Among these, Bi and Cd were found to pose the highest risks. Furthermore, the Risk Assessment Code (RAC) and the Potential Ecological Risk Index (PERI) highlighted Cd as the primary ecological risk contributor, especially in the XE. The study identified sediment grain size, pH, electrical conductivity, and nutrient levels as the primary influencing factors. The PMF modeling revealed HM sources as mixed smelting/natural inputs, agricultural activities, natural weathering, and mining/smelting operations, suggesting that remediation should prioritize Cd control in the XE with emphasis on external inputs. Full article

The use of chemical fertilizers has significantly increased crop yields but has also led to soil problems such as nutrient imbalance and salinization. In response, organic fertilizers have emerged as a crucial component for sustainable agricultural development. This study was designed to develop an easily applicable organic suspension fertilizer using peanut bran, the primary by-product of peanut oil extraction, as the main raw material. Fourier-transform infrared (FTIR) analysis revealed that 80 °C is the optimal heating temperature for forming a stable peanut-bran suspension. A comprehensive experimental investigation was conducted to evaluate the effects of different peanut bran addition levels, stabilizers, emulsifiers, and suspending agents on the stability of suspension fertilizers. The results identified the optimal suspension fertilizer formulation as comprising 20% peanut bran, 0.5% sodium bentonite, 0.1% monoglyceride, 0.2% sucrose ester, 0.02% carrageenan, and 0.3% xanthan gum. This formulation ensures good stability and fluidity of the suspension fertilizer while maintaining a low cost of 0.134 USD·kg⁻¹. The findings provide a scalable technological framework for valorizing agro-industrial waste into high-performance organic fertilizers. Full article

In many developing African countries, milk safety is often managed through traditional methods such as fermentation or boiling over firewood. While these approaches reduce some microbial risks, they present critical limitations. Firewood dependency contributes to deforestation, depletion of agricultural residues, and loss of soil fertility, which, in turn, compromise environmental health and food security. Solar pasteurization provides a reliable and sustainable method for thermally inactivating pathogenic microorganisms in milk and other perishable foods at sub-boiling temperatures, preserving its nutritional quality. This study aimed to evaluate the thermal and microbial performance of a low-cost solar milk pasteurization system, hypothesized to effectively reduce microbial contaminants and retain milk quality under natural sunlight. The system was constructed using locally available materials and tailored to the climatic conditions of the Savanna ecological zone in West Africa. A flat-plate glass solar collector was integrated with a 0.15 cm thick stainless steel cylindrical milk vat, featuring a 2.2 cm hot water jacket and 0.5 cm thick aluminum foil insulation. The system was tested in Navrongo, Ghana, under ambient temperatures ranging from 30 °C to 43 °C. The pasteurizer successfully processed up to 8 L of milk per batch, achieving a maximum milk temperature of 74 °C by 14:00 GMT. Microbial analysis revealed a significant reduction in bacterial load, from 6.6 × 10⁶ CFU/mL to 1.0 × 10² CFU/mL, with complete elimination of coliforms. These results confirmed the device’s effectiveness in achieving safe pasteurization levels. The findings demonstrate that this locally built solar pasteurization system is a viable and cost-effective solution for improving milk safety in arid, electricity-limited regions. Its potential scalability also opens avenues for rural entrepreneurship in solar-powered food and water treatment technologies. Full article

Lettuce (Lactuca sativa L.) is one of the main leafy vegetables in the world, being present in several countries. Due to its composition, which includes a substance with antioxidant action and beneficial effects on health, it is consumed constantly. However, due to ongoing climate change that has had global effects, the crop has been suffering a reduction in productivity and quality. Thus, technologies aiming to mitigate the effects of climate extremes have been developed. In lettuce production, biostimulants make it possible to improve the growth and sustainable development of plants. This is due to their ability to activate physiological and biochemical processes in plants, resulting in an increase in the production of bioactive compounds such as vitamins, amino acids, and antioxidants. In addition, biostimulants contribute to improving the nutritional quality of lettuces, making them more resistant and adapted to different environmental conditions, resulting in a more sustainable development for the crop. This review aims to compile and discuss the available scientific evidence on the use of biostimulants in lettuce cultivation, addressing their mechanisms of action, the types of substances used, the results obtained in different cultivation systems, and their potential to promote more efficient and adaptable agriculture in the face of environmental changes. Full article

Based on a comprehensive review of the current research status of ecological compensation both domestically and internationally, combined with field survey data, this study delves into the issue of multi-stakeholder participation in the ecological compensation mechanisms of the Xin’an River Basin. This research reveals that the joint participation of multiple stakeholders is crucial to achieving the goals of ecological compensation in river basins. The government plays a significant role in macro-guidance, financial support, policy guarantees, supervision, and management. It promotes the comprehensive implementation of ecological environmental protection by formulating relevant laws and regulations, guiding the public to participate in ecological conservation, and supervising and punishing pollution behaviors. The public, serving as the main force, forms strong awareness and behavioral habits of ecological protection through active participation in environmental protection, monitoring, and feedback. As participants, enterprises contribute to industrial transformation and green development by improving resource utilization efficiency, reducing pollution emissions, promoting green industries, and participating in ecological restoration projects. Scientific research institutions, as technology enablers, have effectively enhanced governance efficiency through technological research and innovation, ecosystem value accounting to provide decision-making support, and public education. Social organizations, as facilitators, have injected vitality and innovation into watershed governance by extensively mobilizing social forces and building multi-party collaboration platforms. Communities, as supporters, have transformed ecological value into economic benefits by developing characteristic industries such as eco-agriculture and eco-tourism. Based on the above findings, further recommendations are proposed to mobilize the enthusiasm of upstream communities and encourage their participation in ecological compensation, promote the market-oriented operation of ecological compensation mechanisms, strengthen cross-regional cooperation to establish joint mechanisms, enhance supervision and evaluation, and establish a sound benefit-sharing mechanism. These recommendations provide theoretical support and practical references for ecological compensation worldwide. Full article

Against the backdrop of increasingly frequent extreme weather events and heightened market price volatility, investigating the relationship between agricultural insurance and farmers’ livelihood resilience is crucial for ensuring rural socioeconomic stability. This study utilizes field survey data from 1196 households across twelve county-level divisions (three cities and nine counties) from China’s Hainan and Yunnan provinces, specifically in natural rubber-producing regions. Using propensity score matching (PSM), we empirically examine agricultural insurance’s impact on household livelihood resilience. The results demonstrate that agricultural insurance increased the effect on farmers’ livelihood resilience by 1%. This effect is particularly pronounced among recently poverty-alleviated households and large-scale farming operations. Furthermore, the analysis highlights the mediating roles of credit availability, adoption of agricultural production technologies, and production initiative in strengthening insurance’s positive impact. Therefore, policies should be refined and expanded, combining agricultural insurance with credit support and agricultural technology extension to leverage their value and ensure the sustainable development of farm households. Full article

Direct seeding has gained prominence as a labor-efficient and environmentally sustainable alternative to conventional transplanting in rice cultivation. In direct seeding systems, early-stage management is crucial for stable seedling establishment, with sowing uniformity measured by seed counts being a critical indicator of success. However, conventional manual seed counting methods are time-consuming, prone to human error, and impractical for large-scale or repetitive tasks, necessitating advanced automated solutions. Recent advances in computer vision technologies and precision agriculture tools, offer the potential to automate seed counting tasks. Nevertheless, challenges such as domain discrepancies and limited labeled data restrict robust real-world deployment. To address these issues, we propose a density estimation-based seed counting framework integrating semi-supervised learning and background augmentation. This framework includes a cost-effective data acquisition system enabling diverse domain data collection through indoor background augmentation, combined with semi-supervised learning to utilize augmented data effectively while minimizing labeling costs. The experimental results on field data from unknown domains show that our approach reduces seed counting errors by up to 58.5% compared to conventional methods, highlighting its potential as a scalable and effective solution for agricultural applications in real-world environments. Full article

Cultured meat is emerging as a sustainable alternative to conventional animal agriculture, with scaffolds playing a central role in supporting cellular attachment, growth, and tissue maturation. This review focuses on the development of gel-based hybrid biomaterials that meet the dual requirements of biocompatibility and food safety. We explore recent advances in the use of naturally derived gel-forming polymers such as gelatin, chitosan, cellulose, alginate, and plant-based proteins as the structural backbone for edible scaffolds. Particular attention is given to the integration of food-grade functional additives into hydrogel-based scaffolds. These include nanocellulose, dietary fibers, modified starches, polyphenols, and enzymatic crosslinkers such as transglutaminase, which enhance mechanical stability, rheological properties, and cell-guidance capabilities. Rather than focusing on fabrication methods or individual case studies, this review emphasizes the material-centric design strategies for building scalable, printable, and digestible gel scaffolds suitable for cultured meat production. By systemically evaluating the role of each component in structural reinforcement and biological interaction, this work provides a comprehensive frame work for designing next-generation edible scaffold systems. Nonetheless, the field continues to face challenges, including structural optimization, regulatory validation, and scale-up, which are critical for future implementation. Ultimately, hybrid gel-based scaffolds are positioned as a foundational technology for advancing the functionality, manufacturability, and consumer readiness of cultured meat products, distinguishing this work from previous reviews. Unlike previous reviews that have focused primarily on fabrication techniques or tissue engineering applications, this review provides a uniquely food-centric perspective by systematically evaluating the compositional design of hybrid hydrogel-based scaffolds with edibility, scalability, and consumer acceptance in mind. Through a comparative analysis of food-safe additives and naturally derived biopolymers, this review establishes a framework that bridges biomaterials science and food engineering to advance the practical realization of cultured meat products. Full article

Agricultural nondestructive testing technology is pivotal in safeguarding food quality assurance, safety monitoring, and supply chain transparency. While conventional optical methods such as near-infrared spectroscopy and hyperspectral imaging demonstrate proficiency in surface composition analysis, their constrained penetration depth and environmental sensitivity limit effectiveness in dynamic agricultural inspections. This review highlights the transformative potential of microwave technologies, systematically examining their operational principles, current implementations, and developmental trajectories for agricultural quality control. Microwave technology leverages dielectric response mechanisms to overcome traditional limitations, such as low-frequency penetration for grain silo moisture testing and high-frequency multi-parameter analysis, enabling simultaneous detection of moisture gradients, density variations, and foreign contaminants. Established applications span moisture quantification in cereal grains, oilseed crops, and plant tissues, while emerging implementations address storage condition monitoring, mycotoxin detection, and adulteration screening. The high-frequency branch of the microwave–millimeter wave systems enhances analytical precision through molecular resonance effects and sub-millimeter spatial resolution, achieving trace-level contaminant identification. Current challenges focus on three areas: excessive absorption of low-frequency microwaves by high-moisture agricultural products, significant path loss of microwave high-frequency signals in complex environments, and the lack of a standardized dielectric database. In the future, it is essential to develop low-cost, highly sensitive, and portable systems based on solid-state microelectronics and metamaterials, and to utilize IoT and 6G communications to enable dynamic monitoring. This review not only consolidates the state-of-the-art but also identifies future innovation pathways, providing a roadmap for scalable deployment of next-generation agricultural NDT systems. Full article

The extensive use of conventional pesticides has been a fundamental strategy in modern agriculture for controlling pests and increasing crop productivity; however, their improper application poses significant risks to human health and environmental sustainability. This review compiles scientific evidence linking pesticide exposure to oxidative stress and genotoxic damage, particularly affecting rural populations and commonly consumed foods, even at levels exceeding the maximum permissible limits in fruits, vegetables, and animal products. Additionally, excessive pesticide use has been shown to alter soil microbiota, negatively compromising long-term agricultural fertility. In response to these challenges, recent advances in nanotechnology offer promising alternatives. This review highlights the development of nanopesticides designed for controlled release, improved stability, and targeted delivery of active ingredients, thereby reducing environmental contamination and increasing efficacy. Moreover, emerging nanobiosensor technologies, such as e-nose and e-tongue systems, have shown potential for real-time monitoring of pesticide residues and soil health. Although pesticides are still necessary, it is crucial to implement stricter laws and promote sustainable solutions that ensure safe and responsible agricultural practices. The need for evidence-based public policy is emphasized to regulate pesticide use and protect both human health and agricultural resources. Full article