Search Results (1,494)

Enhancing farmers’ digital literacy is both an inevitable requirement for adapting to the digital age and an important measure for promoting the sustainable development of livestock and poultry manure resource utilization. This study surveyed and obtained data from 1047 farm households in Ningxia and Gansu, two provinces in China that have long implemented livestock manure resource utilization policies, from December 2023 to January 2024, and employed the binary probit model to analyze how digital literacy influences farmers’ willingness to adopt two livestock manure resource utilization modes, as well as to analyze the moderating role of three policy regulations. This paper also explores the heterogeneous results in different village forms and income groups. The results are as follows: (1) Digital literacy significantly and positively impacts farmers’ willingness to adopt both the “household collection” mode and the “livestock community” mode. For every one-unit increase in a farmer’s digital literacy, the probability of farmers’ willingness to adopt the “household collection” mode rises by 22 percentage points, and the probability of farmers’ willingness to adopt the “livestock community” mode rises by 19.8 percentage points. After endogeneity tests and robustness checks, the conclusion still holds. (2) Mechanism analysis results indicate that guiding policy and incentive policy have a positive moderation effect on the link between digital literacy and the willingness to adopt the “household collection” mode. Meanwhile, incentive policy also positively moderates the relationship between digital literacy and the willingness to adopt the “livestock community” mode. (3) Heterogeneity analysis results show that the positive effect of digital literacy on farmers’ willingness to adopt two livestock manure resource utilization modes is stronger in “tight-knit society” rural areas and in low-income households. (4) In further discussion, we find that digital literacy removes the information barriers for farmers, facilitating the conversion of willingness into behavior. The value of this study is as follows: this paper provides new insights for the promotion of livestock and poultry manure resource utilization policies in countries and regions similar to the development process of northwest China. Therefore, enhancing farmers’ digital literacy in a targeted way, strengthening the promotion of grassroots policies on livestock manure resource utilization, formulating diversified ecological compensation schemes, and establishing limited supervision and penalty rules can boost farmers’ willingness to adopt manure resource utilization models. Full article

Foliar application of biostimulants can be a valid option to reach the goal of sustainable intensification in agriculture, especially in extensive crops such as durum wheat. However, due to the wide range of active ingredients and their mixtures available in the market, the need to select the most efficient product in a specific growing environment is of dramatic importance to achieve remarkable results in yield and grain quality. To analyze the potential of different active ingredients, a field trial was performed in two consecutive growing seasons (2023 and 2024) under Mediterranean climatic conditions. A randomized block design with three replicates was used. Durum wheat cultivar “Iride” was treated with the following five foliar biostimulants in comparison with the untreated control (T0): seaweed and plant extracts (T1); micronized vaterite (T2); culture broth of Pseudomonas protegens (T3); humic and fulvic acids (T4); organic nitrogen fertilizer (N 5%) containing glycine betaine (T5). Biostimulant treatment was applied at the end of tillering and at heading. Root length, chlorophyll content, grain yield, yield components and grain quality were measured and subjected to a one-way analysis of variance. As compared to the control, seaweed and plant extracts as well as micronized vaterite showed the best results in terms of grain yield (29% and 24% increase, respectively), root length (120% and 77% increase, respectively) and grain protein content (one percentage point increase, from approx. 12% to 13%). The results from this study can help Mediterranean farmers and researchers to develop new fertilization protocols to reach the goals of the “Farm to Fork” European strategy. Full article

The review summarizes the historical and current research on perennial grain breeding in Russia within the context of growing global interest in perennial crops. N.V. Tsitsin’s pioneering work in the 1930s produced the first wheat–wheatgrass amphiploids, which demonstrated the capacity to regrow after harvest and survive for 2–3 years. Subsequent research at the Main Botanical Garden in Moscow focused on characterizing Tsitsin’s material, selecting superior germplasm, and expanding genetic diversity through new cycles of hybridization and selection. This work led to the development of a new crop species, Trititrigia, and the release of cultivar ‘Pamyati Lyubimovoy’ in 2020, designed for dual-purpose production of high-quality grain and green biomass. Intermediate wheatgrass (Thinopyrum intermedium) is native to Russia, where several forage cultivars have been released and cultivated. Two large-grain cultivars (Sova and Filin) were developed from populations provided by the Land Institute and are now grown by farmers. Perennial rye was developed through interspecific crosses between Secale cereale and S. montanum, demonstrating persistence for 2–3 years with high biomass production and grain yields of 1.5–2.0 t/ha. Hybridization between Sorghum bicolor and S. halepense resulted in two released cultivars of perennial sorghum used primarily for forage production under arid conditions. Russia’s agroclimatic diversity in agricultural production systems provides significant opportunities for perennial crop development. The broader scientific and practical implications of perennial crops in Russia extend to climate-resilient, sustainable agriculture and international cooperation in this emerging field. Full article

Traditional seed supply chains face several hidden risks. Certain regulatory departments tend to focus primarily on entity circulation while neglecting the origin and accuracy of data in seed quality supervision, resulting in limited precision and low credibility of traceability information related to quality and safety. Blockchain technology offers a systematic solution to key issues such as data source distortion and insufficient regulatory penetration in the seed supply chain by enabling data rights confirmation, tamper-proof traceability, smart contract execution, and multi-node consensus mechanisms. In this study, we developed a system that integrates blockchain and neural networks to provide seed traceability services. When uploading seed traceability information, the neural network models are employed to verify the authenticity of information provided by humans and save the tags on the blockchain. Various neural network architectures, such as Multilayer Perceptron, Recurrent Neural Network, Fully Convolutional Neural Network, and Long Short-term Memory model architectures, have been tested to determine the authenticity of seed traceability information. Among these, the Long Short-term Memory model architecture demonstrated the highest accuracy, with an accuracy rate of 90.65%. The results demonstrated that neural networks have significant research value and potential to assess the authenticity of information in a blockchain. In the application scenario of seed quality traceability, using blockchain and neural networks to determine the authenticity of seed traceability information provides a new solution for seed traceability. This system empowers farmers by providing trustworthy seed quality information, enabling better purchasing decisions and reducing risks from counterfeit or substandard seeds. Furthermore, this mechanism fosters market circulation of certified high-quality seeds, elevates crop yields, and contributes to the sustainable growth of agricultural systems. Full article

The relationships between farmers and livestock are multifaceted. The aim of this study was to describe the sociodemographic, biogeographic, and institutional factors that influence the relationships between humans and animals in the natural savanna. Visits were made to 65 farms, followed by interviews (n = 13) and three focus group interviews (n = 24) directed at farmers and institutional representatives. The results were triangulated to extract the key findings. The following findings were obtained: (a) cultural gender transitions and the lack of generational succession have transformed livestock farming; (b) the relationships between farmers and livestock have favored the implementation of new productive practices and innovations, as well as improvements in animal welfare practices; (c) conditioning factors affecting these relationships include gender discriminatory norms, low profitability and credit access, poor sanitation, animal handling infrastructure, security, and resistance to change; and (d) improvement opportunities include the inclusion of young people and women in livestock farming, education for work practices, credit facilitation, access to technologies, governance, and improvement in the cattle logistics chain. The results are useful for enhancing the relationships between farmers and livestock, guiding training activities, and responsible governance. Full article

This qualitative case study explores Missouri-based consumers’ ethical beliefs regarding restaurant sourcing from minority farmers. Guided by the Hunt–Vitell theory of ethics (H-V model), it applies the model in a new context: culturally inclusive restaurant sourcing. Based on 15 semi-structured interviews conducted between September 2024 and October 2024, the study explores how ethical beliefs shape dining intentions. Participants generally viewed support for minority farmers as ethically appropriate. Thematic analysis revealed six key themes: (1) community-oriented social values (e.g., social responsibility toward local businesses); (2) cultural identity (e.g., traditional farming methods); (3) consumer values—food-oriented (e.g., quality); (4) consumer values—people-oriented (e.g., financial support for ethical sourcing); (5) trust-building mechanisms (e.g., sourcing transparency); and (6) barriers (e.g., lack of awareness). These findings highlight limited consumer awareness of minority farmers and the need for transparent communication and cultural education. The study contributes theoretically by extending the H-V model to the intersection of ethics, culture, and restaurant sourcing. Practically, it offers guidance for restaurant managers, marketers, and policymakers to support minority farmers, build trust, and promote inclusive and socially responsible dining. One key limitation of this study is its reliance on a small, Missouri-based consumer sample, which limits generalizability and excludes perspectives from other stakeholders. However, as a regional case study, it provides important depth and contextual insight into an underexplored aspect of sustainable sourcing. This study also highlights the need for multi-stakeholder engagement to advance equity in the food system. Full article

The European Union’s developing rural development plan places digital and precision agriculture at the centre of agricultural modernisation and economic development. This article examines how agricultural practices in rural EU regions are being influenced by smart technology, such as drones, IoT sensors, satellite-based research, and AI-driven platforms, through an analysis of recent data from sources across the European Union. This study applies a mixed-methods approach, combining quantitative analysis of strategic policy documents and EU databases, to evaluate the ways in which precision agriculture reduces input consumption, increases productivity, reduces labour shortages and rural area depopulation, and improves sustainability. By investing in infrastructure, developing communities for data exchange, and organising training for farmers, European policies such as the Strategic Plans of the Common Agricultural Policy (CAP), the SmartAgriHubs initiative, and the AgData program actively encourage the transition to digital agriculture. Cyprus is analysed as a case study to show how targeted investments and initiatives supported by the EU can help smaller countries, with limited natural resources, to realise the benefits of digital transformation in agriculture. A special focus is placed on how solutions adapted to agro-climatic and socioeconomic conditions can contribute to strengthening the competitiveness of the agricultural sector, attracting young people to get involved in this field and opening up new economic opportunities. The results of previous research indicate that digital agriculture not only improves productivity but also proves to be a strategic mechanism for attracting and retaining young people in rural areas. Thus, this work additionally contributes to the broader goal of the European Union—the development of smart, inclusive, and sustainable rural areas, in which digital technologies are not only seen as tools for efficiency but also as key means for integrated and long-term rural development. Full article

In recent decades, climate change, increasing demand, and resource scarcity have transformed the agricultural sector into a critical field of research. Farmers have been compelled to adopt innovations and new technologies to enhance production efficiency and crop resilience. This study presents a systematic literature review, supplemented by a bibliometric analysis of relevant documents, focusing on the key applications and combined techniques of artificial intelligence (AI), machine learning (ML), and digital twins (DT) in the development and implementation of cyber-physical systems (CPS) in smart agriculture and establishes whether CPS in agriculture is an attractive research topic. A total of 108 bibliographic records from the Scopus and Google Scholar databases were analyzed to construct the bibliometric study database. The findings reveal that CPS has evolved and emerged as a promising research area, largely due to its versatility and integration potential. The analysis offers researchers and practitioners a comprehensive overview of the existing literature and research trends on the dynamic relationship between CPS and its primary applications in the agricultural industry while encouraging further exploration in this field. Additionally, the main challenges associated with implementing CPS in the context of smart agriculture are discussed, contributing to a deeper understanding of this topic. Full article

Informal groundwater markets, where farmers with wells sell surplus water to neighbors, are a widespread adaptive response to water scarcity, particularly in South Asia where they are most prevalent and well-documented. This review (1990–2025) examines the evolving patterns of these markets by synthesizing global literature and viewing them through the lens of three transformative trends: energy transition (especially solar pumps), digital innovations (e.g., blockchain and IoT), and new policy pathways. We synthesize literature to evaluate market structures, contract forms, efficiency and equity outcomes, environmental impacts, and the influence of energy policies and digital tools. The review assesses whether these informal trades fulfill their promise of enhancing water productivity and equity or if new challenges are creating pitfalls. Key objectives include documenting historical evolution, analyzing market performance, discussing externalities like aquifer depletion, examining policy interactions, reviewing digital pilots, exploring social inclusion, comparing governance frameworks, identifying research gaps linked to SDGs, and proposing a policy roadmap for harnessing benefits while ensuring sustainability. Full article

(1) Background: Global grain production faces challenges such as increasing demands due to population growth, limited arable land resources, and climate change, with natural resource and environmental constraints becoming increasingly stringent. Traditional smallholder economies struggle to meet the increasing demand for grain, resulting in a tight balance between grain supply and demand. Therefore, to improve grain production efficiency (GPE), clarifying the specific effects of agricultural production services (APS), a new driving force on farmers’ GPE, is critical for ensuring grain security and achieving sustainable grain production. (2) Methods: Through the super-efficiency Data Envelopment Analysis (DEA) and Tobit models, and utilizing microdata from 747 farmers from the China Rural Revitalization Survey (CRRS), we analyzed the differences in farmers’ operating scales and types of agricultural production services to determine the extent and specific implementation effects of agricultural production services on the farmers’ GPE. (3) Results: agricultural production services enhanced the farmers’ GPE. Specifically, labor-intensive services (LIS) markedly improved the GPE of smallholder farmers but not large-scale farmers; technology-intensive services (TIS) did not have a substantial influence on either the smallholder farmers or large-scale farmers. There were significant regional differences in the threshold effect of agricultural production services on the GPE of the farmers. (4) Conclusions: Providers of agricultural production services should enhance their service capabilities to meet farmers’ diverse service needs. Government departments should establish uniform service standards and regulate industry development. Village and community organizations should leverage their grassroots coordination functions to facilitate the efficient operation of services. In addition, tailored development models should be developed for farmers of different scales, and they should be provided with financial and technical support as well as institutional guarantees. Full article

What is the potential impact on carbon storage of the native and introduced tree species commonly associated with coffee in the central Peruvian Amazon? Coffee is a pivotal crop within the Peruvian economy. Nevertheless, the establishment of new plantations—driven by the subsistence needs of smallholder farmers—has led to expansion into forested areas. Given the significance of this crop and the demonstrated ecosystem benefits of agroforestry systems (AFSs), the aim of this study was to evaluate the influence of native and introduced shade tree species on carbon storage in coffee plantations. This study was observational and exhibited characteristics of an unbalanced incomplete block design. Agroforestry systems (AFSs) with shade tree species such as Inga, Retrophyllum rospigliosii, Eucalyptus and Pinus, and three unshaded coffee plantations, were included in this study. The total carbon stored in each AFS was higher than in unshaded coffee plantations. Soil contributed between 47% and 91% to total carbon storage, shade trees (24–46%), coffee (2–7%), leaf litter (0.6–1.9%) and shrubs and herbaceous plants (0.02–0.3%). The AFS with R. rospigliosii achieved the highest carbon storage with 190.38 Mg ha⁻¹, highlighting the compatibility of this species with coffee plantations, as well as its positive effect on climate change mitigation in deforested areas. Full article

Agricultural green production (AGP) is a key strategy for ensuring stable and sustainable grain production in developing countries. However, from the perspective of technology acquisition, research on farmers’ willingness to adopt AGP remains limited. Based on this, a survey was conducted on 862 households in major grain-producing counties in the Huang Huai Hai Plain of China with a reliable and effective response rate of 97.44%. The aim was to employ Probit and mediation models to empirically analyze the direct impacts of green perception benefits and environmental regulation intensity on farmers’ AGP willingness, and further examine the intrinsic mechanisms of technology acquisition. The results demonstrated that both green perception benefits and environmental regulation intensity significantly enhanced farmers’ willingness to engage in AGP, with green perception benefits having a greater influence. Among the two-dimensional variables, economic benefits had a stronger promoting effect than identity benefits, with a difference of 0.044 units, while subjective regulation intensity outperformed objective regulation intensity by 0.173 units. This suggested the need to strengthen the subjective impact of AGP policies in practice. Further analysis revealed that technology acquisition mediated 5.87% of the effect of green perception benefits on farmers’ AGP willingness, with acquisition evaluation having the greatest mediating effect, followed by acquisition quality and acquisition channels. However, although the overall environmental regulation intensity did not significantly impact farmers’ willingness to engage in AGP, its two-dimensional indicators played a mediating role to varying degrees. The findings in this study provide valuable empirical evidence for promoting AGP among grain producers, contributing to grain production security and the sustainable development of developing countries. Thus, implementing environmental regulatory policies tailored to local conditions, enhancing farmers’ economic awareness and sense of responsibility, and expanding farmers’ channels for technology acquisition are reasonable policy choices. Full article

Tea farmers in Wuyishan National Park face the dual challenges of promoting sustainable tea production while adhering to strict ecological protection policies. This study investigates the key factors influencing tea farmers’ pro-environmental behavior and the transmission mechanisms that encourage the adoption of sustainable development. Based on the theory of planned behavior, the theory of externalities, and place attachment theory, 346 valid questionnaires were collected through household interviews across 12 villages within Wuyishan National Park and its surrounding areas. The results indicate that environmental responsibility and concern for community well-being are major motivators of pro-environmental behavior. Market orientation, production intensification, and adoption of clean technologies significantly enhance environmental outcomes at the farm level. While ecological compensation policies help offset the costs of conservation, their impact is constrained by inconsistencies in standard-setting and implementation. The establishment of the national park has enhanced pro-environmental behavior among farmers within the park and influenced those in peripheral areas by strengthening place attachment and social norms. Tea farmers in the core areas of the national park exhibit higher levels of pro-environmental behavior compared to those on the periphery. This study offers several policy recommendations and contributes new insights into understanding the mechanisms behind tea farmers’ pro-environmental behavior within national park contexts, providing valuable reference for pro-environmental practices in the global protected area system. Full article

Background/Objectives: A critical part of the maize life cycle takes place during the summer, and due to climate change, its growth and development are increasingly exposed to the irregular and unpredictable effects of drought stress. Developing and using new cultivars with increased drought tolerance for farmers is the easiest and cheapest solution. One of the concepts to screen for drought tolerance is to expose germplasm to various growth scenarios (environments), expecting that random drought will occur in some of them. Methods: In the present study, thirty-two maize hybrids belonging to four FAO maturity groups were tested for grain yield at six locations over two consecutive years. In parallel, data of the basic meteorological elements such as air temperature, relative humidity and precipitation were collected and used to compute two indices, scPDSI (Self-calibrating Palmer Drought Severity Index) and VPD (Vapor Pressure Deficit), that were assessed as indicators of drought (water deficit) severity during the vegetation period. Practical implementation of these indices was carried out indirectly by first analyzing yield data using a factor analytic model to detect latent environmental variables affecting yield and then correlating those latent variables with drought indices. Results: The first latent variable, which explained 47.97% of the total variability, was correlated with VPD (r = −0.58); the second latent variable explained 9.57% of the total variability and was correlated with scPDSI (r = −0.74). Furthermore, latent regression coefficients (i.e., genotypic sensitivities to latent environmental variables) were correlated with genotypic drought tolerance. Conclusions: This could be considered an indication that there were two different acting mechanisms in which drought affected yield. Full article

Five beetle species can occur in potato fields simultaneously, including one quarantine pest (the Colorado potato beetle (CPB)), one phytophagous pest (the 28-spotted potato ladybird beetle), and three predatory ladybird beetles (the 7-spotted lady beetle, the tortoise beetle, and the harlequin ladybird beetle). The timely detection and accurate identification of CPB and other phytophagous or predatory beetles are critical for the effective implementation of monitoring and control strategies. However, morphological identification requires specialized expertise, is time-consuming, and is particularly challenging due to the dark brown body color of these beetles when in the young larval stages. This study provides an effective solution to distinguish between phytophagous and/or quarantine and predatory beetles. This solution is in the form of a new convolutional neural network architecture, known as MSAC-ResNet. Specifically, it comprises several multiscale asymmetric convolution blocks, which are designed to extract features at multiple scales, mainly by integrating different-sized asymmetric convolution kernels in parallel. We evaluated the MSAC-ResNet through comprehensive model training and testing on a beetle image dataset of 11,325 images across 20 beetle categories. The proposed recognition model achieved accuracy, precision, and recall rates of 99.11%, 99.18%, and 99.11%, respectively, outperforming another five existing models, namely, AlexNet, MobileNet-v3, EfficientNet-b0, DenseNet, and ResNet-101. Notably, the developed field investigation mini-program can identify all the developmental stages of these five beetle species, from young larvae to adults, and provide timely management (or protection) suggestions to farmers. Our findings could be significant for future research related to precise pest control and the conservation of natural enemies. Full article