Search Results (853)

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

Increased food production demands, labor shortages, and environmental concerns are driving the need for innovative agricultural technologies. However, effective adoption depends critically on aligning robot innovations with the needs of farmers. This paper examines the alignment between the needs of farmers and the robotic systems used in row crop farming. We review current commercial agricultural robots and research, and map these to the needs of farmers, as expressed in the literature, to identify the key issues holding back large-scale adoption. From initial pool of 184 research articles, 19 survey articles, and 82 commercial robotic solutions, we selected 38 peer-reviewed academic studies, 12 survey articles, and 18 commercially available robots for in-depth review and analysis for this study. We identify the key challenges faced by farmers and map them directly to the current and emerging capabilities of agricultural robots. We supplement the data gathered from the literature review of surveys and case studies with in-depth interviews with nine farmers to obtain deeper insights into the needs and day-to-day operations. Farmers reported mixed reactions to current technologies, acknowledging efficiency improvements but highlighting barriers such as capital costs, technical complexity, and inadequate support systems. There is a notable demand for technologies for improved plant health monitoring, soil condition assessment, and enhanced climate resilience. We then review state-of-the-art robotic solutions for row crop farming and map these technological capabilities to the farmers’ needs. Only technologies with field validation or operational deployment are included, to ensure practical relevance. These mappings generate insights that underscore the need for lightweight and modular robot technologies that can be adapted to diverse farming practices, as well as the need for farmers’ education and simpler interfaces to robotic operations and data analysis that are actionable for farmers. We conclude with recommendations for future research, emphasizing the importance of co-creation with the farming community to ensure the adoption and sustained use of agricultural robotic solutions. 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

Solid biomass (agro-residue) is the most important source of renewable energy. The accelerating impacts of climate change and global population growth contribute to air pollution through the use of fossil fuels. These processes increase the demand for energy. The European Union has adopted a climate action plan to address the above challenges. The main aim of this study was to assess the economic performance of the producers of biomass for energy generation in Poland. The detailed objectives were to determine land resources in the studied agricultural farms and to determine the value of fixed and current assets in the analyzed farms. We used questionnaires as the main method to collect data. Purposive sampling was used to choose the farms. We conducted various tests to analyze the revenues from biomass sales and their normality, such as the Dornik–Hansen test, the Shapiro–Wilk test, the Liliefors test, and the Jargue–Berra statistical test. Moreover, we conducted regression analysis to find factors that are the basis for the economic performance (incomes) of farms that sell biomass. Results: This study demonstrated that biomass sales had a minor impact on the performance of agricultural farms, but they enabled farmers to maintain their position on the market. The economic analysis was carried out on a representative group of Polish agricultural farms, taking into account fixed and current assets, land use, production structure, and employment. The findings indicate that a higher income from biomass sales was generally associated with better economic results per farm and per employee, although not always per hectare of land. This suggests that capital intensity and strategic resource management play a crucial role in the profitability of bioenergy-oriented agricultural production. Conclusions: We concluded that biomass sales had a negligible influence on farm income. But a small income from biomass sales could affect a farm’s economic viability. Full article

Since the end of the Civil War, Cambodia has pursued economic development to enhance livelihoods, particularly in rural areas, where land is a critical resource. Previous studies have indicated that the country has changed land use and land cover. However, they have not explained how these changes can improve the livelihoods of local communities, thereby mitigating their negative impacts through an asset-based approach. Battambang Province, in the northwestern region, was the battleground until political integration in 1996. Since then, the province has been home to immigrants exploring the lands for livelihood. Thus, this study aims to examine agricultural livelihoods in the villages of Dei Kraham and Ou Toek Thla, located west of Battambang Town. These were selected because of their common characteristics. Adopting a quantitative approach and a sustainable livelihood framework, this study employed stratified random sampling to select 123 families for interviews across three population subgroups: old settlers, new settlers, and young settlers. In situ information was collected using structured questionnaires and analyzed using Kruskal–Wallis tests to assess the livelihood assets underlying the physical, natural, human, financial, and social capital. The statistical analysis results reveal no significant differences (p-value = 0.079) in livelihood assets between the strata at the village level. Meanwhile, significant differences were observed in physical, human, and financial capital between old and young settlers when examining the subgroups (p-value 0.000). The extent of the land resources held by old settlers was associated with household income and livelihoods related to agriculture. Based on livelihood asset scores, nearly half of the new settlers (0.49–0.5) and a quarter of the young settlers (0.47) are vulnerable groups requiring support. The youth will soon face an uncertain future if they do not prioritize education. Full article

With the digital economy continuing to integrate deeply into the agricultural sector, agricultural digital transformation has emerged as a pivotal driver of rural revitalization and the development of a robust agricultural economy. Although existing studies have affirmed the positive role of agricultural digital transformation in promoting rural development and enhancing agricultural efficiency, its spatiotemporal evolution patterns, regional disparities, and underlying driving factors have not yet been systematically and thoroughly investigated. This study seeks to fill that gap. Based on provincial panel data from China spanning 2011 to 2023, this study employs the Theil index, kernel density estimation, Moran’s index, and quantile regression to systematically assess the spatiotemporal dynamics and driving factors of agricultural digital transformation at both national and regional levels. The results reveal a steady overall improvement in agricultural digital transformation, yet regional development imbalances remain prominent, with a shift from inter-regional disparities to intra-regional disparities over time. The four major regions exhibit a stratified evolutionary trajectory marked by internal differentiation: the eastern region retains its lead, while central and western regions show potential for catch-up, and the northeastern region faces a “balance trap.” Economic development foundation, human capital quality, and policy environment support are identified as the core driving forces of transformation, while other factors demonstrate pronounced regional and phase-specific variability. This study not only deepens theoretical understanding of the uneven development and driving logic of agricultural digital transformation but also provides empirical evidence to support policy optimization and promote more balanced and sustainable development in the agricultural sector. Full article

Small-scale farms deserve attention and support because they play crucial and important roles. Apart from ensuring provision of food security, they also provide other economic, environmental, and social–cultural benefits. In the United States of America, these farms are agriculturally, culturally, and geographically different. They have varied needs that trigger an array of distinct biophysical, socioeconomic, and institutional challenges. The effects of these challenges are exacerbated by economic uncertainty, technological advancements, climate change, and other environmental concerns. To provide ideal services to the small-scale farm audience, it is necessary to understand these challenges and opportunities that can be leveraged to enhance their productivity and profitability. This article reviews the challenges faced by small-scale farming in the United States of America. It then reviews possible pathways to enhance their productivity and profitability. The review revealed that U.S. small-scale farms face several challenges. They include accessing farmland, credit and capital, lack of knowledge and skills, and technology adoption. Others are difficulties to insure, competition from corporations, and environmental uncertainties associated with climate change. The paper then reviews key pathways to enhance small-scale farmers’ capacities and resilience with a positive impact on their productivity and profitability. They are enhanced cooperative extension services, incentivization, strategic marketing, annexing technology, and government support, among others. Based on the diversity of farms and their needs, responses should be targeted towards individual needs. Since small-scale farm products have an effect on human health and dietary patterns, strategies to increase productivity should be linked to nutrition and health. Full article

This research aims to analyze the evolution of productivity and efficiency in tractors featuring varying propulsion system designs through the development of a parametric modeling approach. Recognizing that large row-crop tractors represent a significant capital investment—ranging from USD 0.4 to over 0.8 million for current-generation models—and that machinery costs constitute a substantial share of farm production expenses, this study addresses the urgent need for data-driven decision-making in agricultural enterprises. Utilizing consolidated OECD Code 2 tractor test data for all large row-crop John Deere tractors from the MFWD era to the latest generation, the study evaluates tractor performance across multiple productivity and efficiency indicators. The analysis culminates in the creation of a robust, user-friendly parametric model (R² = 0.9337, RMSE = 1.0265), designed to assist stakeholders in making informed decisions regarding tractor replacement or upgrading. By enabling the optimization of productivity and efficiency while accounting for agronomic and timeliness constraints, this model supports sustainable and profitable management practices in modern agriculture. Full article

Agriculture 5.0 represents a shift towards a more sustainable agricultural model, integrating Artificial Intelligence (AI), the Internet of Things (IoT), robotics, and blockchain technologies to enhance productivity and resource management, with an emphasis on social and environmental resilience. This article explores how the evolution of wireless technologies to sixth-generation networks (6G) can support innovation in Colombia’s agricultural sector and foster rural advancement. The study follows three main phases: search, analysis, and selection of information. In the search phase, key government policies, spectrum management strategies, and the relevant literature from 2020 to 2025 were reviewed. The analysis phase addresses challenges such as spectrum regulation and infrastructure deployment within the context of a developing country. Finally, the selection phase evaluates technological readiness and policy frameworks. Findings suggest that 6G could revolutionize Colombian agriculture by improving connectivity, enabling real-time monitoring, and facilitating precision farming, especially in rural areas with limited infrastructure. Successful 6G deployment could boost agricultural productivity, reduce socioeconomic disparities, and foster sustainable rural development, contingent on aligned public policies, infrastructure investments, and human capital development. Full article

Real-time identification of insect pests is an important research direction in modern agricultural management, directly influencing crop health and yield. Recent advances in computer vision and deep learning, especially vision transformer (ViT) architectures, have demonstrated great potential in addressing this challenge. The present study explores the possibility of combining some ViT models for the insect pest classification task to improve system performance and robustness. Two popular and widely known datasets, D0 and IP102, which consist of diverse digital images with complex contexts of insect pests, were used. The proposed methodology involved training several individual ViT models on the chosen datasets, finally creating an ensemble strategy to fuse their results. A new combination method was used, based on the F1 score of individual models and a meta-classifier structure, capitalizing on the strengths of each base model and effectively capturing complex features for the final prediction. The experimental results indicated that the proposed ensemble methodology significantly outperformed the individual ViT models, observing notable improvements in classification accuracy for both datasets. Specifically, the ensemble model achieved a test accuracy of 99.87% and an F1 score of 99.82% for the D0 dataset, and an F1 score of 84.25% for IP102, demonstrating the method’s effectiveness for insect pest classification from different datasets. The noted features pave the way for implementing reliable and effective solutions in the agricultural pest management process. Full article

The adoption of agricultural technologies is paramount for enhancing global agricultural productivity and sustainability. However, widespread implementation faces significant challenges, particularly in developing regions. Using data from the China Land Economic Survey (CLES), this study examines how land certification reform affects farmers’ technology adoption behavior from an institutional perspective. Results demonstrate that land certification significantly increases agricultural technology adoption rates, with more pronounced effects observed among households possessing greater human and physical capital. A mechanistic analysis reveals that land certification facilitates technology adoption through three pathways: (1) improving credit accessibility, (2) strengthening long-term investment incentives, and (3) expanding the production and operational scale. These findings highlight land tenure security as a fundamental institutional driver of agricultural modernization, deepen the understanding of the interaction between institutions and innovation in agriculture, and offer actionable insights for integrating property rights reforms with technological advancements. Full article

Eliminating all forms of poverty is a core component of the United Nations’ Sustainable Development Goals. At the household level, poverty and income inequality significantly threaten farmers’ sustainable development and food security. Based on a sample of 1234 kiwi farmers from the Shaanxi and Sichuan provinces in China, this paper empirically examines the impact of participation in agricultural industry organizations (AIOs) on household income and income inequality, as well as the underlying mechanisms. The results indicate the following: (1) Participation in AIOs increased farmers’ average household income by approximately 19,570 yuan while simultaneously reducing the income inequality index by an average of 4.1%. (2) Participation increases household income and mitigates income inequality through three mechanisms: promoting agricultural production, enhancing sales premiums, and improving human capital. (3) After addressing endogeneity concerns, farmers participating in leading agribusiness enterprises experienced an additional average income increase of 21,700 yuan compared to those participating in agricultural cooperatives. Therefore, it is recommended to optimize the farmer–enterprise linkage mechanisms within agricultural industry organizations, enhance technical training programs, and strengthen production–marketing integration and market connection systems, aiming to achieve both increased farmer income and improved income distribution. Full article

Making clear the exact amount of carbon emissions from the planting industry is of great significance for developing low-carbon agriculture and helping achieve carbon neutrality. The current carbon emissions from the planting industry in Beijing, the capital of China, are still unclear, and there is a lack of quantitative research on the production, economic, and ecological benefits of carbon emissions. This paper used the carbon emissions factor method to study the inter-annual variation characteristics of carbon emissions and carbon benefits in Beijing’s planting industry since 2000. The results show that the carbon emissions from the planting industry in Beijing in 2023 were 256,400 tons, of which the carbon emissions from agricultural inputs, nitrous oxide (N₂O) from farmland, and methane (CH₄) from rice cultivation were 149,300, 105,200, and 2000 tons, respectively. From 2000 to 2023, the total carbon emissions from the planting industry in Beijing have shown a downward trend. Compared with 2000, the carbon emissions from agricultural inputs and N₂O in 2023 decreased by 59.88% and 74.52%, respectively. The carbon emissions of CH₄ from rice cultivation were only 2.38% of those in 2000, and the total carbon emissions from the planting industry in Beijing decreased by 70.43%. The average carbon emissions from agricultural inputs and N₂O accounted for 50.85% and 47.95% of the total level of the planting industry, respectively, and were the main sources of carbon emissions in Beijing. Chemical fertilizer and agricultural film inputs were important sources of carbon emissions from agricultural inputs. Reducing inputs for agriculture and sources of N₂O from farmland is an important way to reduce carbon emissions from agriculture in Beijing. In the end, some suggestions were proposed for reducing carbon emissions from the planting industry. Full article

The ability of the agriculture sector, which is exposed to climate hazards, to cope with climate challenges and to strive in spite of them, is conceptualized as the resilience of agriculture. In enhancing climate-resilient agriculture, the cash reserve ratio (CRR) is generally perceived to serve two crucial functions: first, encouraging banks to allocate credit to agriculturalists for climate-resilient agricultural practices; second, enhancing agriculturalists’ ability to sustain agricultural output growth in spite of climate crises. In light of this, we conducted an ex post evaluation of the effect of the currently in-use CRR on bank loans to climate-challenged Nigeria’s agriculture sector for climate-resilient agricultural practices. Additionally, this study investigates the CRR’s impact(s) on agricultural output growth amidst climate challenges. Other additional independent variables include monetary policy rate, government capital expenditures on agriculture, and government recurrent expenditures on agriculture, as well as temperature, precipitation, and the renewable energy supply. Using annual data from 1990 to 2022, the results from an autoregressive, distributed lag approach suggest that the standard CRR stipulated by the Central Bank of Nigeria in the present era of climate change cannot entirely sustain climate-resilient agriculture, evident in the present study’s discoveries on its inability to perform its two major functions (credit and growth) in enhancing agricultural resilience. These findings highlight the need for the green differentiation of the CRR to ensure its effective utilization in enhancing climate resilience. Full article

Against the backdrop of global climate change, enhancing farmers’ adaptive capacity to reduce crop production risks has emerged as a critical concern for governments and researchers worldwide. Drawing on social capital theory, this study develops a four-dimensional measurement framework comprising social networks, social trust, social norms, and social participation, utilizing survey data from 1772 households in the Yellow River Basin. We employ factor analysis to construct comprehensive social capital scores and apply ordered Probit models to examine how social capital influences farmers’ climate adaptation behaviors, with particular attention to the moderating roles of agricultural extension interaction and digital literacy. Key findings include: (1) Adoption patterns: Climate adaptation behavior adoption remains low (60%), with technical adaptation measures showing particularly poor uptake (13%); (2) Direct effects: Social capital significantly promotes adaptation behaviors, with social trust (p < 0.01), networks (p < 0.01), and participation (p < 0.05) demonstrating positive effects, while social norms show no significant impact; (3) Heterogeneous effects: Impact mechanisms differ by crop type, with grain producers relying more heavily on social networks (+, p < 0.01) and cash crop producers depending more on social trust (+, p < 0.01); (4) Moderating mechanisms: Agricultural extension interaction exhibits scale-dependent effects, negatively moderating the relationship for large-scale farmers (p < 0.05) while showing no significant effects for smaller operations; digital literacy consistently demonstrates negative moderation, whereby higher literacy levels weaken social capital’s promotional effects (p < 0.01). Policy recommendations: Effective climate adaptation strategies should integrate strengthened rural social organization development, differentiated agricultural extension systems tailored to farm characteristics, and enhanced rural digital infrastructure investment. Full article