Search Results (9,874)

The agro-pastoral ecotone in Yinshanbeilu is the main potato-producing region. In recent years, the shift from rainfed to irrigated agriculture has created challenges in understanding potato water consumption patterns, water use efficiency, and irrigation optimization. This study utilized the DSSAT model to simulate soil moisture, leaf area index, and potato yield based on a two-year in situ observational experiment. The study showed that simulated values of the soil water moisture, leaf area index, and yield, with Absolute Relative Error (ARE) of 4.18–5.27%, Normalized Root Mean Square Error (nRMSE) of 5.64–8.65%, and Coefficient of Determination (R²) values of 0.86–0.921, exhibited acceptable accuracy. Simulated results pointed out that potato water consumption ranged between 375.2 and 414.2 mm, with 50–52% occurring during tuber formation to bulking stages, and the average water consumption intensity was 2.62~2.81 mm/d. Based on DSSAT model simulation, this study found that water use efficiency (WUE) reached 162.17–166.20 kg/(hm²·mm), while irrigation water use efficiency (IWUE) varied between 86.1 and 108.1 kg/(hm²·mm). With the highest yield as the target, the recommended irrigation amounts for potato in normal year and dry year were 180 mm and 240 mm. With the highest utilization rate of groundwater resources as the target, the recommended irrigation amounts in normal year and dry year were 162 mm and 192 mm. These findings offer valuable insights for promoting sustainable groundwater use and enhancing water conservation practices in the Yinshanbeilu agro-pastoral ecotone. Full article

Hyperspectral imaging (HSI) is a swiftly developing intraoperative and diagnostic technique in several clinical specialties. By monitoring oxygenation and biochemical markers, it helps with tissue viability, burn depth measurement, wound healing, and tumor detection. HSI facilitates real-time, harmless diagnosis throughout surgeries or outpatient settings, and allows for the detection of tumor boundaries with over 90% accuracy, according to clinical studies. Originally developed for remote sensing and aerospace applications, HSI has rapidly evolved and found increasing relevance across diverse sectors, including agriculture, environmental monitoring, food safety, pharmaceuticals, defense, and especially medical diagnostics. This review explores the origins, development, and expanding applications of HSI, with a particular emphasis on its role in healthcare. It discusses the operational principles and unique features of hyperspectral systems, such as their ability to produce spectral data cubes, perform non-destructive analysis, and integrate with emerging technologies like artificial intelligence and drone-based platforms. By comparing hyperspectral imaging to traditional and multispectral techniques, the review highlights its superior spectral resolution and versatility. Key challenges, including data volume, sensor calibration, and real-time processing, are also addressed. Finally, emerging trends such as miniaturization, integration with the Internet of Things, and sustainable system designs are examined, offering insights into the future directions and interdisciplinary potentials of HSI in both scientific research and practical applications. Full article

Pesticide residues from agrochemicals pose significant environmental and public health risks due to their persistence and widespread contamination of soil, water, and crops. The persistent challenge of pesticide contamination requires innovative and sustainable treatment strategies to safeguard public health and environmental integrity. Although wastewater treatment plants (WWTPs) are designed to mitigate these pollutants, their efficiency varies, and certain pesticides persist or transform into more toxic by-products during treatment. Therefore, developing alternative methods for the effective removal of pesticide residues is imperative. This review critically evaluates the potential of adsorption, particularly using green adsorbents, as a sustainable and efficient approach for removing pesticide contaminants from soil and wastewater. Green adsorbents, derived from agricultural and industrial by-products such as sea materials, biomasses, humic acid, spent mushroom substrate, biochar, and cellulose-based adsorbents, offer a cost-effective, abundant, and environmentally friendly solution for soil treatment and water purification. Their high pollutant-binding capacity, selectivity, and affinity make them promising candidates for widespread application in soil and wastewater treatment. Ongoing research focuses on optimizing the scalability and real-world application of these adsorbents for large-scale remediation efforts. In conclusion, addressing the risks posed by pesticide residues necessitates revisiting agricultural practices and wastewater treatment strategies. The integration of green adsorbents offers a sustainable approach to mitigating pesticide contamination, thereby protecting public health and supporting environmental sustainability. This review highlights the importance of adopting green adsorbents as viable alternatives to conventional treatment methods, emphasizing their potential to revolutionize wastewater management and mitigate the adverse impacts of pesticide residues on ecosystems and human well-being. Full article

Phosphate rock is a vital natural resource classified by the European Commission as a critical raw material (CRM), extensively mined for its agricultural, industrial, and technological applications. While primarily used in fertilizer production, phosphate deposits also contain significant concentrations of trace metals, notably rare earth elements (REE), which are essential for renewable energy, electronics, and defense technologies. In response to growing demand, the recovery of REE from phosphate ores and processing by-products, particularly phosphogypsum (PG), has gained international attention. This review provides a comprehensive analysis of the global phosphate industry, examining production trends, market dynamics, and the environmental implications of phosphate processing. Special focus is placed on the geochemical behavior and mineralogical associations of REE within phosphate ores and industrial residues, namely PG and purification sludge. Although often treated as waste, these by-products represent underexplored secondary resources for REE recovery. Technological advancements in hydrometallurgical, solvometallurgical, and bioleaching methods have demonstrated promising recovery efficiencies, with some pilot-scale studies exceeding 70%–80%. However, large-scale implementation remains limited due to economic, technical, and regulatory constraints. The circular economy framework offers a pathway to enhance resource efficiency and reduce environmental impact. By integrating innovative extraction technologies, strengthening regulatory oversight, and adopting sustainable waste management practices, phosphate-rich countries can transform environmental liabilities into strategic assets. This review concludes by identifying key knowledge gaps and suggesting future research directions to optimize REE recovery from phosphate deposits and associated by-products, contributing to global supply security, economic diversification, and environmental sustainability. Full article

Beeswax is widely used in apiculture and can accumulate neonicotinoid residues due to the intensive use of systemic pesticides in agriculture. These contaminants pose potential risks to honeybee health and may indirectly affect the quality and safety of hive products such as honey, pollen, and royal jelly. This study evaluates several decontamination methods for neonicotinoid removal from contaminated beeswax, including modern techniques (microwaves, ultrasonic baths, and magnetic stirring with heating) and conventional approaches based on heat, agitation, and water—either pure or acidified. Among these, the traditional method that uses an aqueous oxalic acid solution proved highly effective, removing over 99% of neonicotinoid residues after two treatment cycles, even at wax quantities up to 200 g. The treatment also improved the colour and physical properties of the wax and was well tolerated by bees, according to a qualitative acceptance test. The simplicity, low cost, and absence of hazardous by-products make this method suitable for scale-up and adoption in real apicultural practices. These findings support the development of accessible and sustainable strategies for the decontamination of wax matrices that may otherwise act as long-term reservoirs of pesticide residues in the food chain. Full article

Climate change adaptation in ecologically sensitive agriculture remains underexplored, especially regarding whether farmers’ climate perceptions translate into ecological production behaviors (EPBs). Using survey data from 730 tea farmers in China’s Wuyi Mountains National Park, this study examines how general and extreme climate change perceptions relate to EPB adoption. Employing Ordered Probit models and Karlson-Holm-Breen (KHB) mediation analysis, we estimate perception–behavior associations and test indirect effects through information-seeking and policy participation, alongside moderation by ecosystem service cognition and ecological production benefit cognition. The results indicate that both general and extreme climate perceptions are positively associated with EPB adoption (β = 0.406 and 0.626, p < 0.01), with extreme perceptions showing significantly stronger effects. Climate perceptions influence EPB adoption across all dimensions (green production, ecological management, and market-based practices). Information-seeking and policy participation function as complementary mediating pathways (combined indirect effects = 0.101 and 0.117), linking climate perceptions to ecological actions. Moreover, higher ecosystem service cognition and ecological production benefit cognition strengthen the perception–behavior relationships across multiple EPB dimensions. Overall, the findings suggest that climate change perceptions are an important driver of farmers’ ecological production choices in high-ecological-value contexts. Interpreted alongside existing adaptation strategies, EPB may enhance resilience by leveraging ecosystem functions while aligning with market incentives for ecological products. These results underscore the value of policies that improve access to ecological training and market information and support demonstration programs that facilitate experiential learning. Full article

Large language models (LLMs) are increasingly consulted by amateur gardeners who rely on them for diagnosing plant problems and selecting management strategies. This study evaluates whether such AI systems promote environmentally sustainable or chemically oriented practices. Fifteen real images of edible plants showing typical health issues were collected during 2024–2025, and four major models—ChatGPT 5.0, Gemini 2.5 Pro, Claude Sonnet 4.5, and Perplexity AI (standard version)—were queried in October 2025 using an identical user-style prompt. Each response was coded across four sustainability dimensions (ecological prevention, diagnostic reasoning, nutrient management, and chemical control) and aggregated into a composite Eco-Score (−1 to +1). Across cases, all models prioritized preventive and low-impact advice, emphasizing pruning, hygiene, compost, and organic sprays while recommending synthetic fungicides or pesticides only occasionally. The highest sustainability alignment was achieved by Perplexity AI (Eco-Score = 0.71) and Gemini 2.5 Pro (0.69), followed by ChatGPT 5.0 (0.57) and Claude Sonnet 4.5 (0.41). Although the models frequently converged in general reasoning, no case achieved full agreement in Eco-Score values across systems. These findings demonstrate that current LLMs generally reinforce sustainable reasoning but vary in interpretative reliability. While they can enhance ecological awareness and accessible plant care knowledge, their diagnostic uncertainty underscores the need for human oversight in AI-assisted amateur food production. Full article

Low-temperature (LT) stresses (cold and frost) are major abiotic factors limiting plant growth and productivity. LT induces numerous physiological and biochemical changes in plants, changes hormonal balance and photosynthetic efficiency. Stress induced by LT often leads to yield losses in crops. While plants like maize and cucumber are highly sensitive to cold, winter cereals such as wheat and rye suffer mainly from severe frosts. Ongoing climate change and temperature fluctuations further increase the risk of LT-induced damage. To counteract the problems connected with LT stress, multiple strategies have been developed to enhance plant tolerance. Agrotechnical practices and biochemical treatments involving the application of phytohormones or osmoprotectants are designed to improve plant tolerance to LT. Beneficial plant–microbe interactions also contribute to alleviating LT stress. In addition, genetic engineering offers powerful tools for creating new cultivars that are more tolerant to LT. The CRISPR/Cas system, in particular, enables precise modifications and represents a promising tool for advancing sustainable agriculture. Integrated methods of protection are crucial for securing food supplies, especially under conditions of a changing climate. This mini-review summarises strategies for protecting plants against LT stress, with special attention paid to crop plants. Full article

Soil-dwelling beetles, including native and invasive species such as Popilia japonica Newman (Coleoptera: Scarabaeidae), are persistent and damaging agricultural pests worldwide. Mass trapping, using pheromone-, light-, or food-based lures to attract and remove adults, is being developed as an environmentally sustainable alternative within integrated pest management (IPM). Scarab beetles respond positively to attractant-based traps, and large-scale programs against P. japonica in North America provide valuable insights for global applications. The efficacy of mass trapping depends on species biology, trap density, environmental conditions and landscape structure. Capturing adults does not always immediately reduce larval populations, as underground stages persist in soil for multiple years. Light traps are effective but often attract many non-target insects, whereas pheromone traps are more selective but require careful optimization of lure composition, release rate and placement. To achieve reliable suppression, mass trapping should be integrated with complementary strategies such as biological control agents (Beauveria spp., Metarhizium spp.), crop rotation, tolerant crop varieties and soil management. Future research should focus on refining lure design, optimizing deployment, testing predictive models and evaluating multi-bait systems. Overall, mass trapping represents a promising and environmentally sustainable tool that, when incorporated into integrated approaches, can enhance the management of soil-dwelling scarab beetles across diverse agroecosystems worldwide. Full article

Temperature plays a vital role in plant metabolism, and effective crop temperature appears to be influenced by variables related to climate change. While extreme weather events are widely discussed, the effects of moderate temperature changes pose consistent yet underexplored challenges for farmers. The “growing degree days” (GDD) also termed “heat unit”, is the most widely used approach in agricultural and ecological studies to quantify the relationship between temperature and plant development. This review provides a comprehensive examination of GDD methodology as applied to horticultural crop production, specifically from initial fruit development to fruit maturity, and postharvest. It is the first integrated synthesis of the conceptual evolution, methodological refinement, and broad application of GDD, thereby highlighting the need to optimize GDD approaches in light of emerging technological tools. While the GDD model is valuable for predicting crop development based on heat accumulation, it has limitations in capturing the effects of other environmental factors. Additionally, air temperature may not provide precise data on each plant organ. Recent advances in remote sensing, such as the integration of thermal imaging, RGB cameras, and lidar have enabled the measurement of spatially resolved temperature distribution within crop canopies, including fruit surface temperature. Recent advances, highlighted in the literature, suggest that integrating sensor innovations with machine learning approaches holds high potential for improving the precision of modeling temperature-dependent growth responses and their interactions with other environmental variables. By addressing these challenges and expanding its applications, GDD can continue to serve as an essential tool in promoting sustainable horticultural practices and adapting to global warming. Full article

LoRa has emerged as a cornerstone of low-power, long-range IoT communication. While highly effective for scalar sensing, its extension to multimedia remains constrained by limited bitrate, payload size, and duty-cycle regulations. This survey reviews research on multimedia transmission over LoRa, revealing that most current efforts are image-centric, with only a few preliminary studies addressing video or audio. We propose a structured taxonomy encompassing compression and fragmentation methods, cooperative and multi-hop architectures, MAC and cross-layer optimizations, and hybrid network designs. These strategies are analyzed in the context of IoT domains such as agriculture, surveillance, and environmental monitoring. Open challenges are highlighted in extending beyond static images, ensuring energy-efficient delivery, and developing spectrum- and ML-aware protocols. The survey provides IoT researchers with both a consolidated reference and a roadmap toward practical and scalable multimedia systems over LoRa. Full article

Agroecology is recognized as a resilient agricultural system amid the ecological crisis, but also as a social movement working towards better livelihoods for farmers. In Burkina Faso, the dynamics among actors promoting agroecology are not well understood. Effective governance of the agroecological transition necessitates a deeper comprehension of the interactions and networks involved. This study aims to identify, characterize, and analyze local actors and their networks to enhance governance for agroecological transition, focusing on two north and south-west regions of Burkina Faso to highlight regional differences. Using the Agricultural Knowledge and Information Systems (AKIS) as a conceptual framework, we conducted a literature review and facilitated focus group discussions during a workshop with stakeholders. Key participants include farmers, service providers, researchers, policymakers, NGOs, and organizations, which engage in political and technical interactions. The results show that the governance landscape is fragmented with public policies at both strategic and operational levels failing to effectively engage mainstream actors or translate into actionable support for agroecological practices. To transition agroecology from a fragmented niche to a widely adopted system, there is a critical need for consistent support for farmers, including knowledge sharing, networking opportunities, and marketing strategies. Full article

The increasing rate of land use change, particularly deforestation and agricultural expansion, has intensified soil degradation, leading to reduced sediment retention and accelerated soil erosion. This study aims to analyze soil erosion and sediment retention in the Lam Phra Phloeng (LPP) watershed, Thailand, using a coupled modelling approach integrating the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Delivery Ratio (SDR) model from the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) suite. Six land use classes (forest, cropland, rangeland, flooded vegetation, built-up areas, and water bodies) were identified using Sentinel-2 MSI satellite data, with a Random Forest (RF) classification algorithm achieving an overall accuracy of 91.3% (Kappa coefficient = 0.89). The results indicate that forested areas exhibit the highest sediment retention, whereas croplands and rangelands experience the most significant soil loss due to erosion. The RUSLE model estimated an average annual soil loss ranging between 50 and 90 tons/ha/year, with the highest erosion rates observed in agricultural lands with steep slopes and minimal vegetation cover. The InVEST SDR model further corroborates these findings, showing that sediment retention is predominantly concentrated in densely vegetated areas, reinforcing the crucial role of natural forests in preventing soil displacement. This complementary modelling approach identifies priority areas for soil conservation practices. This study is the first study to integrate the RUSLE and InVEST models for the Lam Phra Phloeng watershed, providing a coupled assessment of erosion risk and sediment retention capacity and offering a novel and transferable framework for watershed-scale conservation planning and soil management in tropical monsoonal environments. Full article

Banana plantations are important tropical agro-ecosystems, and quantifying their greenhouse gas emissions is essential for developing low-carbon agriculture and mitigating global warming. The carbon balance of two banana cultivars (Musa paradisiaca AA (MA) and M. AAA Cavendish var. Brazil (MB)) was evaluated using the life cycle assessment (LCA) approach, based on field trials and farmer surveys in Chengmai County, Hainan Province, China. The results indicated that (1) both cultivation systems functioned as net carbon sinks, and the MB cultivar demonstrated a superior carbon balance, with a net sequestration of 21,652.88 kg CO₂ eq·ha⁻¹, significantly higher than the MA cultivar (15,197.96 kg CO₂ eq·ha⁻¹); (2) fertilizer management was the dominant source of anthropogenic emissions, contributing 74.03–81.76% of the carbon footprint from agricultural inputs; and (3) the MB cultivar’s enhanced carbon fixation capacity outweighed its higher emissions, resulting in a more favorable carbon balance than the MA cultivar. Concurrently, the banana plantations significantly increased soil carbon sequestration by 13.47–24.48%. Thus, within the studied system boundary, banana agro-ecosystems serve as net carbon sinks, a function that can be enhanced by optimizing fertilizer management to reduce emissions and by increasing both plant biomass and soil carbon sequestration. These results provide a scientific basis for low-carbon practices and promoting a more sustainable banana industry. Full article

The expansion of global agriculture has intensified the use of herbicides such as atrazine (ATZ), resulting in widespread environmental contamination. Given its documented harmful effects, the development of effective treatment strategies is crucial. This review synthesizes the fundamental mechanisms behind ATZ adsorption, identifying it as a spontaneous and energetically favorable process, predominantly governed by specific physicochemical interactions. The analysis reveals that adsorption efficiency is critically influenced by the pH of the medium, since this parameter determines the charge state of the adsorbent surface and the ATZ molecule itself, thus modulating the attractive forces. The high adsorption capacity observed in various materials is intrinsically linked to their porous architecture and surface area, which facilitate the capture and retention of molecules. The desorption process, in turn, demonstrates the reversible nature of certain interactions, allowing for the regeneration and reuse of materials. The unique contribution of this analysis lies in its mechanistic approach, which transcends the mere presentation of data to offer guiding principles for the design of adsorbents. By connecting operational parameters to molecular phenomena, the review establishes a critical basis for translating promising laboratory results into real-world applications, providing a roadmap for developing practical and sustainable solutions against ATZ contamination. Full article