Search Results (3,223)

In the current era, Indian agriculture faces a significant demand for increased food production, which has led to the integration of advanced technologies to enhance efficiency and productivity. Drones have emerged as transformative tools for enhancing precision agriculture, reducing costs, and improving sustainability. This study provides a comprehensive review of drone adoption in Indian agriculture by examining its effects on precision farming, crop monitoring, and pesticide application. This research evaluates technological advancements, regulatory frameworks, infrastructure, farmers’ perceptions, and the financial accessibility of drone technology in the Indian agricultural context. Key findings indicate that, while drone adoption enhances efficiency and sustainability, challenges such as high costs, lack of training, and regulatory barriers hinder widespread implementation. This paper also explores the growing market for agricultural drones in India, highlighting key industry players and projected market growth. Furthermore, it addresses regional differences in adoption rates and emphasizes the increasing social acceptance of drones among Indian farmers. To bridge the gap between potential and practice, the study proposes several policy and institutional recommendations, including government-led financial incentives, training programs, and public–private partnerships to facilitate drone integration. Moreover, this review article also highlights technological advancements, such as AI and IoT, in agriculture. Finally, open issues and future research directions for drones are discussed. Full article

With the rapid development of the social economy, human activities have increasingly disrupted water environments, and the continuous input of pollutants poses significant challenges for water environment management. Taking the Xiaoxingkai Lake basin as the study area, this paper develops a social–economic–water environment model based on the system dynamics methodology, incorporating subsystems for population, agriculture, and water pollution. The model focuses on four key indicators of pollution severity, namely, total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), and ammonia nitrogen (NH₃-N), and simulates the changes in pollutant loads entering the river under five different scenarios from 2020 to 2030. The results show that agricultural non-point sources are the primary contributors to TN (79.5%) and TP (73.7%), while COD primarily originates from domestic sources (64.2%). NH₃-N is mainly influenced by urban domestic activities (44.7%) and agricultural cultivation (41.2%). Under the status quo development scenario, pollutant loads continue to rise, with more pronounced increases under the economic development scenario, thus posing significant sustainability risks. The pollution control enhancement scenario is most effective in controlling pollutants, but it does not promote socio-economic development and has high implementation costs, failing to achieve coordinated socio-economic and environmental development in the region. The dual-reinforcement scenario and moderate-reinforcement scenario achieve a balance between pollution control and economic development, with the moderate-reinforcement scenario being more suitable for long-term regional development. The findings can provide a scientific basis for water resource management and planning in the Xiaoxingkai Lake basin. Full article

This study contributes to scientific theory by analyzing the models proposed within the framework of circular agriculture to determine how the three dimensions of sustainability—environmental, economic, and social—are integrated into their implementation. A systematic review was conducted on articles published between 2016 and 2025, indexed in the Scopus and Web of Science databases, as well as the relevant grey literature. The methodology employed an extensive content analysis designed to minimize bias, applying filters related to specific knowledge areas to delimitate the search scope and enhance the precision of the research. The findings reveal that the research on circular agriculture models is predominantly grounded in the principles of the circular economy and its associated indicators. Moreover, these models tend to focus on environmental metrics, often neglecting a comprehensive exploration of the social and economic dimensions of sustainable development. It can be concluded that a significant gap persists in the literature regarding the circularity of agriculture and its socio-economic impacts and the role of regulatory frameworks, aspects that future research must address in order to achieve sustainability in circular agriculture. Full article

Wellington, New Zealand, is highly vulnerable to disaster-induced food security crises due to its geography and geological characteristics, which can disrupt transportation and isolate the city following disasters. Urban agriculture (UA) has been proposed as a potential alternative food source for post-disaster scenarios. This study examined the potential of urban agriculture for enhancing post-disaster food security by calculating vegetable self-sufficiency rates. Specifically, it evaluated the capacity of current Wellington’s community gardens to meet post-disaster vegetable demand in terms of both weight and nutrient content. Data collection employed mixed methods with questionnaires, on-site observations and mapping, and collecting high-resolution aerial imagery. Garden yields were estimated using self-reported data supported by literature benchmarks, while cultivated areas were quantified through on-site mapping and aerial imagery analysis. Six post-disaster food demand scenarios were used based on different target populations to develop an understanding of the range of potential produce yields. Weight-based results show that community gardens currently supply only 0.42% of the vegetable demand for residents living within a five-minute walk. This rate increased to 2.07% when specifically targeting only vulnerable populations, and up to 10.41% when focusing on gardeners’ own households. However, at the city-wide level, the current capacity of community gardens to provide enough produce to feed people remained limited. Nutrient-based self-sufficiency was lower than weight-based results; however, nutrient intake is particularly critical for vulnerable populations after disasters, underscoring the greater challenge of ensuring adequate nutrition through current urban food production. Beyond self-sufficiency, this study also addressed the role of UA in promoting food diversity and acceptability, as well as its social and psychological benefits based on the questionnaires and on-site observations. The findings indicate that community gardens contribute meaningfully to post-disaster food security for gardeners and nearby residents, particularly for vulnerable groups with elevated nutritional needs. Despite the current limited capacity of community gardens to provide enough produce to feed residents, findings suggest that Wellington could enhance post-disaster food self-reliance by diversifying UA types and optimizing land-use to increase food production during and after a disaster. Realizing this potential will require strategic interventions, including supportive policies, a conducive social environment, and diversification—such as the including private yards—all aimed at improving food access, availability, and nutritional quality during crises. The primary limitation of this study is the lack of comprehensive data on urban agriculture in Wellington and the wider New Zealand context. Addressing this data gap should be a key focus for future research to enable more robust assessments and evidence-based planning. Full article

Today, ‘social sustainability’ is a key feature of many organisations’ environmental, social, and governance strategies, as well as underpinning sustainable development goals. The term refers to the implementation of targets such as reduced societal inequalities, the promotion of social well-being, and the practice of positive community relations. Building a meaningful, accountable, and quantifiable evidence-base from which to translate these high-level concepts into tangible and achievable goals is, however, challenging. The complexities of measuring social capital—often described as a building block of social sustainability—have been documented. The challenge lies in measuring the person, group, or collective in interaction with the context under investigation, whether that be a climate goal, an institution, or a national policy. Social identity theory is a social psychological approach that articulates the processes through which an individual internalises the values, norms, and behaviours of their contexts. Levels of social identification—a concept capturing the state of internalisation—have been shown to be predictive of outcomes as diverse as communication and cognition, trust and citizenship, leadership and compliance, and health and well-being. Applying this perspective to the articulation and measurement of social sustainability provides an opportunity to build an empirical approach with which to reliably translate this high-level concept into achievable outcomes. 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

Nigerian poverty research is often fragmented and focuses on samples with minimal actionable strategies. This study aims to identify essential poverty alleviation and climate change strategies by synthesizing existing research, extracting the most critical poverty alleviation and climate change factors, and assessing strategies to combat poverty and climate change in Nigeria. We obtained, utilizing the centrality measures of social network analysis and the visualization tools of bibliometric analysis, the research hotspots extracted from 119 articles from the SCOPUS database for the period 1994–2023, compared outcomes with other countries, and analyzed their implications for eradicating poverty in Nigeria. We find that low agricultural productivity and food insecurity are some of the essential poverty-engendering factors in Nigeria, which are being intensified by climate change irregularities. Also, researchers demonstrate weak collaboration and synergy, as only 0.02% of researchers collaborated. Our findings highlight the need to direct poverty alleviation efforts to the key areas identified in this study and increase cooperation between poverty alleviation and climate researchers. Full article

Tropical forests continue to experience high levels of habitat loss and degradation, with wildfires becoming a frequent component of human-modified landscapes. Here we investigate the response of palm species to the conversion of old-growth forests to successional mosaics, including forest patches burned during wildfires. Palms (≥50 cm height) were recorded once in 2023–2024, across four habitat classes: terra firme old-growth stands, regenerating forest stands associated with slash-and-burn agriculture, old-growth stands burned once and twice, and active cassava fields, in the Tapajós-Arapiuns Extractive Reserve, in the eastern Brazilian Amazon. The flammability of palm leaf litter and forest litter were also examined to assess the potential connections between palm proliferation and wildfires. A total of 10 palm species were recorded in this social forest (including slash-and-burn agriculture and resulting successional mosaics), with positive, negative, and neutral responses to land use. Species richness did not differ among forest habitats, but absolute palm abundance was greatest in disturbed habitats. Only Attalea spectabilis Mart. (curuá) exhibited increased relative abundance across disturbed habitats, including active cassava field. Attalea spectabilis accounted for almost 43% of all stems in the old-growth forest, 89% in regenerating forests, 90% in burned forests, and 79% in crop fields. Disturbed habitats supported a five-to-ten-fold increment in curuá leaves as a measure of habitat flammability. Although curuá litter exhibited lower flame temperature and height, its lower carbon and higher volatile content is expected to be more sensitive to fire ignition and promote the spread of wildfires. The conversion of old-growth forests into social forests promotes the establishment of palm-dominated forests, increasing the potential for a forest transition further fueled by wildfires, with effects on forest resilience and social reproduction still to be understood. Full article

The swift advancements in autonomous vehicle systems have facilitated their implementation across various industries, including agriculture. However, studies primarily focus on passenger vehicles, with fewer examining autonomous trucks. Therefore, this study reviews autonomous truck systems implementation in North Dakota’s agricultural industry to develop comprehensive technology readiness frameworks and strategic deployment approaches. The review integrates systematic literature review and event history analysis of 52 studies, categorized using Social–Ecological–Technological Systems framework across six dimensions: technological, economic, social change, legal, environmental, and implementation challenges. The Technology Readiness Level (TRL) analysis reveals 39.5% of technologies achieving commercial readiness (TRL 8–9), including GPS/RTK positioning and V2V communication demonstrated through Minn-Dak Farmers Cooperative deployments, while gaps exist in TRL 4–6 technologies, particularly cold-weather operations. Nonetheless, challenges remain, including legislative fragmentation, inadequate rural infrastructure, and barriers to public acceptance. The study provides evidence-based recommendations that support a strategic three-phase deployment approach for the adoption of autonomous trucks in agriculture. Full article

Global policy narratives on livestock development increasingly emphasize environmental concerns, often overlooking the social dimensions of the sector. In the case of dairy, the world’s most valuable agricultural commodity, its role in social and economic development remains poorly quantified. Our study contributes to a more balanced vision of the UN SDGs thanks to the inclusion of a socio-economic dimension. Here we present a novel empirical approach to assess the socio-economic impacts of dairy development using a new global dataset and non-parametric modelling techniques (local polynomial regressions), with yield as a proxy for sectoral performance. We find that as dairy systems intensify, the number of farm households engaged in production declines, yet household incomes rise. On-farm labour productivity also increases, accompanied by a reduction in employment but higher wages. In dairy processing, employment initially grows, peaks, and then contracts, again with rising wages. The most substantial impact is observed among consumers: an increased milk supply leads to lower prices and improved affordability, expanding the access to dairy products. Additionally, dairy development is associated with greater agricultural value added, an expanding tax base, and the increased formalization of the economy. These findings suggest that dairy development, beyond its environmental footprint, plays a significant and largely positive role in social transformation, yet is having to adapt sustainably while tackling labour force relocation, and that dairy development’s social impacts mimic the general agricultural sector. These results might be of interest for the assessment of policies regarding dairy development. Full article

Background/Objectives: Agricultural workers in Spain with a migratory background face challenging working and living conditions that significantly affect their health. This study aimed to explore how professionals in healthcare, social services, civil society organisations, and labour institutions perceive that the working conditions affect the physical health of this population. Methods: A qualitative descriptive study was conducted through 92 semi-structured interviews with professionals from six provinces in Spain. Data were analysed using thematic analysis following Braun and Clarke’s six-phase framework. Rigour was ensured through triangulation, independent coding, and interdisciplinary consensus. Results: Two overarching themes were identified: (1) the health consequences of workplace demands and environmental hazards, and (2) navigating health services such as sick leave and disability permits. These findings highlight how the impact of precarious working conditions and limited access to healthcare affect the physical health of migrant agricultural workers. Conclusions: The professionals interviewed described and relate precarious working conditions with adverse health outcomes among migrant agricultural workers. Their insights reveal the need for systemic reforms to enforce labour rights, ensure access to health services, and address the structural factors that contribute to exclusion and vulnerability. Full article

Mozambique soils are known for having an unbalanced agronomic and environmental composition that results in poor agricultural production yields. However, agriculture is the main economic activity of Mozambique, and soils must be characterised for their elemental deficiencies and/or excesses. This paper sampled nine farms from the Manica and Sussundenga districts (Manica province) in three campaigns in 2021/2022, 2022/2023, and 2023/2024 (before and after the rainy seasons). They were subjected to a physical–chemical analysis to assess their quality from the fertility and environmental contamination point of view. Attending to the physical–chemical properties analysed, and for all the soils and sampling campaigns, a low concentration below the limit of detection for B of <0.2 mg/Kg for the majority of soils and a low concentration of Al < 0.025 mg/Kg for all the soils were obtained. Also, higher concentrations for the majority of soils for the Ca between 270 and 1634 mg/Kg, for the Mg between 41 and 601 mg/Kg, for the K between 17 and 406 mg/Kg, for the Mn between 13.6 and 522 mg/Kg, for the Fe between 66.3 and 243 mg/Kg, and for the P between <20 and 132 mg/Kg were estimated. In terms of texture and for the sand, a high percentage between 6.1 and 79% was found. In terms of metal concentrations and for all the soils of the Sussundenga district and sampling campaigns, a concentration above the reference value concentration for the Cr (76–1400 mg/Kg) and a concentration below the reference value concentration for the Pb (5–19 mg/Kg), Ba (13–120 mg/Kg) and for the Zn (10–61 mg/Kg) were evaluated. A multivariate data analysis methodology was used based on cluster and discriminant analysis. The analysis of twenty-three physical–chemical variables of the soils suggested four clusters of soils characterised by deficiencies and excess elements that must be corrected to improve the yield and quality of agricultural production. Moreover, the multivariate analysis of the metal composition of soil samples from the second and third campaigns, before and after the rainy season, suggested five clusters with a pristine composition and different metal pollutant compositions and concentrations. The information obtained in this study allows for the scientific comprehension of agricultural soil quality, which is crucial for designing agronomic and environmental corrective measures to improve food quality and quantity in the Manica and Sussundenga districts and ensure environmental, social, and economic sustainability. Full article

Information and communication technologies (ICTs) are becoming increasingly important for sustainable rural development through the smart village concept. This study aims to model ICT’s potential for public services management in European rural areas. It identifies ICT applications across rural service domains, analyzes how these technologies address specific rural challenges, and evaluates their benefits, implementation barriers, and future prospects for sustainable rural development. A qualitative content analysis method was applied using purposive sampling to analyze 79 peer-reviewed articles from EBSCO and Elsevier databases (2000–2024). A deductive approach employed predefined categories to systematically classify ICT applications across rural public service domains, with data coded according to technology scope, problems addressed, and implementation challenges. The analysis identified 15 ICT application domains (agriculture, healthcare, education, governance, energy, transport, etc.) and 42 key technology categories (Internet of Things, artificial intelligence, blockchain, cloud computing, digital platforms, mobile applications, etc.). These technologies address four fundamental rural challenges: limited service accessibility, inefficient resource management, demographic pressures, and social exclusion. This study provides the first comprehensive systematic categorization of ICT applications in smart villages, establishing a theoretical framework connecting technology deployment with sustainable development dimensions. Findings demonstrate that successful ICT implementation requires integrated urban–rural cooperation, community-centered approaches, and balanced attention to economic, social, and environmental sustainability. The research identifies persistent challenges, including inadequate infrastructure, limited digital competencies, and high implementation costs, providing actionable insights for policymakers and practitioners developing ICT-enabled rural development strategies. Full article

The transition to sustainable agriculture is a critical challenge for the U.S. food system. A sustainable food system must support the production of healthy and nutritious food while ensuring economic sustainability for farmers and ranchers. It should also reduce negative environmental impacts on soil, water, biodiversity, and climate, and promote equitable and inclusive access to land, farming resources, and food. This narrative review synthesizes U.S. social science literature to identify the key factors that support or impede the adoption of sustainable agricultural practices in the U.S. Our analysis reveals seven overarching factors that influence producer decision-making: awareness and knowledge, social factors, psychological factors, technologies and tools, economic factors, implementation capacity, and policies and regulations. The review highlights the critical role of social science in navigating complexity and uncertainty. Key priorities emerging from the literature include developing measurable, outcome-based programs; ensuring credible communication through trusted intermediaries; and designing tailored interventions. The findings demonstrate that initiatives will succeed when they emphasize measurable benefits, address uncertainties, and develop programs that capitalize on identified opportunities while overcoming existing barriers. Full article

Agriculture is the foundational industry for human survival, profoundly impacting economic, ecological, and social dimensions. In the face of global challenges such as rapid population growth, resource scarcity, and climate change, achieving technological innovation in agriculture and advancing smart farming have become increasingly critical. In recent years, deep learning and computer vision have developed rapidly. Key areas in computer vision—such as deep learning-based image processing, object detection, and multimodal fusion—are rapidly transforming traditional agricultural practices. Processes in agriculture, including planting planning, growth management, harvesting, and post-harvest handling, are shifting from experience-driven methods to digital and intelligent approaches. This paper systematically reviews applications of deep learning and computer vision in agricultural growth management over the past decade, categorizing them into four key areas: crop identification, grading and classification, disease monitoring, and weed detection. Additionally, we introduce classic methods and models in computer vision and deep learning, discussing approaches that utilize different types of visual information. Finally, we summarize current challenges and limitations of existing methods, providing insights for future research and promoting technological innovation in agriculture. Full article