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Summary: Agriculture has been affected by several global trends raising the concern for food security. Agri‐food demands are amplifying due to the ever‐escalating population numbers. Thus, the notion of extending the use of smart innovative technology in managing agricultural practices has emerged rapidly over the last decade. Technological innovations have contributed significantly to shape modern agriculture as smart agriculture. Smart agriculture unfolds various benefits such as increased production, real time data and production insights and remote monitoring. The rising advancements in Information and Communication Technologies (ICT) have paved the way for researchers to use these technologies in managing agricultural practices, leading to greater benefits for farmers and society. These innovations are the key to establishing agriculture as a research discipline. The purpose of this article is to conduct a scientometric analysis to study the structure and evolution of research activities in the field of smart agriculture. The scientometric analysis aims to empirically map the scientific knowledge and identify any possible challenges in the field. This study performs elementary analysis to study publication growth over the years, impact analysis to assess the leading journals, authors, and countries, and articles analysis for findings patterns among the citations over the years and among the keyword‐based clusters. There has been a considerable increase of more than 200% in the number of publications from 2011 to 2022. However, around 60% of authors have contributed with a single publication. The findings of the study reveal the research trends and hot topics for future research fronts. Deep learning, digital agriculture, object detection, blockchain, and semantic segmentation have been identified as trending topics in smart agriculture. Comprehensively, an intellectual view of the agriculture domain is presented as a scientific field in this article. [ABSTRACT FROM AUTHOR]

National Innovations on Climate Resilient Agriculture (NICRA) is a flagship project of the Indian Council of Agricultural Research (ICAR) to mitigate climate change in vulnerable districts of India. The present study assessed farmers’ satisfaction with climate-resilient agricultural technologies following their adoption in two vulnerable districts of Telangana, India, identified under the NICRA project. Results showed that most farmers in the Suryapet and Khammam (62.67% and 90.00%) districts of Telangana state expressed high satisfaction with these technologies. Additionally, a significant proportion had a highly favourable perception of the technology promoters (71.33% and 82.00%), high perceived expectations (52.67% and 74.00%), high perceived quality (58.00% and 86.00%), and a high perceived value (68.00% and 84.00%) associated with climateresilient agricultural technologies. Importantly, the vast majority of the farmers in both districts expressed their intent to use these technologies when the need arises. Path analysis revealed that variables like perceived image, perceived expectation, perceived quality and perceived value had a significant direct impact on satisfaction, while there was no indirect effect on behavioural intention. [ABSTRACT FROM AUTHOR]

Information accessibility is a pivotal factor influencing farmers' adoption of Agricultural Green Production Technologies (AGPT). However, the widespread issue of information poverty presents a significant obstacle to this adoption process, thereby hindering the progression towards sustainable agricultural development. To address this information deficit, farmers have begun to utilize the Internet and participate in government-led onsite assembly training programs to acquire the necessary knowledge. Yet there is still a lack of research evidence on the effectiveness and comparative advantages of internet and offline training. This study explores the impact of various information access channels on farmers' adoption of green production technologies in agriculture, focusing on a sample of 731 family farms located in Sichuan Province. The issue of endogeneity was addressed using the Conditional Mixed Process Estimation Method. The sample underwent a t-test and heterogeneity analysis. The findings revealed that both internet-based information access and participation in training significantly bolstered farmers' adoption of AGPT, with the former proving to be more effective. Notably, heterogeneity was observed among farmers, differentiated by age and the number of village cadres within their family units. [ABSTRACT FROM AUTHOR]

Since the 1980s, Geographical Information Systems (GIS) have been integrated into animal farming technologies for purposes such as enhancing production performances and veterinary epidemiology. In aquaculture, however, there seems to be limited application of GIS, and its potential is widely overlooked, especially for aquatic animal health management. This study describes the results of a world expert opinion elicitation on the current implementation of GIS for surveillance and disease response in the aquatic animal health domain. An online survey was submitted in autumn 2023, including both closed and open questions. With a response rate of 41.2% (21 out of 51), the answer analysis highlighted that, especially when knowledge and practical skills in geomatics, information technology and remote sensing are required, a group of advanced GIS technologies is underutilized (web-based solutions, SDI, citizen science). An artificial intelligence-based inductive text analysis was performed confirming a limited exploitation of GIS mainly due to management (financial support, training, collaboration) and methodology (data suitability, modelling analyses and integration) constraints. Furthermore, despite acknowledging the importance of planning in GIS project development, most experts did not follow any written or unwritten procedures that, according to their answers, should in fact encompass sustainable principles (integration of GIS solutions into other applications or processes), and reuse of resources (guidelines and best practices, data, methods, layouts). Shared guidelines for developing GIS projects, identifying available data sources, and long-term-maintenance planning of GIS and related geospatial data, should be pursued for using GIS technologies more effectively in the aquatic animal health domain. [ABSTRACT FROM AUTHOR]

This article discusses the development of guanine base editors (GBEs) for G-to-T editing in rice. The researchers created two GBEs using an engineered N-methylpurine DNA glycosylase with CRISPR systems, achieving targeted G-to-T editing with an efficiency of 4.94-12.50% in rice. They also explored the potential of derivative base editors by combining the DNA glycosylase with various nucleotide deaminases, resulting in co-editing of target guanines with adenines or cytosines. The study demonstrates the potential of GBEs and derivative base editors for genome editing in rice, providing new tools for both basic research and genetic improvement of the crop. [Extracted from the article]

A study published in the Journal of Integrative Plant Biology explores the potential for fortifying foxtail millet with bioactive folates. The researchers found that by knocking out two genes, SiGFT1 and SiGFT2, in foxtail millet, the accumulation of bioactive folates increased significantly while levels of the bioinactive oxidation product MeFox decreased. This research provides a promising method for biofortifying cereal crops with folates, which are essential micronutrients for human health. The study suggests that consuming folate-fortified cereals could be particularly beneficial for pregnant women and the elderly in regions where dietary diversification is challenging. [Extracted from the article]

Nanotechnology has offered numerous growing opportunities in pharmaceutical, biomedical, cosmetics, textiles, electronics, automobiles, and agriculture. The broader implications on the commercial side are only recommended when a significant understanding of nano-triggered environmental toxicities is minimal or within acceptable limits. The agricultural outcomes are primarily based on the crop plantʼs performance in the growing areas. Therefore, productivity needed to be predicted by the plant responses under normal and stressed conditions. Here, the reactive oxygen species (ROS) level is a crucial and decisive factor for the overall performance of the desired genotype of particular crop plants. Since the entity is reactive and causing significant damage to the bio-machinery. Hence, regulation at the nano-dimension by the engineered nanomaterials (ENMs) is the most effective approach to mitigate the negative consequences. The preference for ENMs is strong because of having unique diversity in physical properties. Furthermore, the behavior of ROS is conditioned by hormonal concentration, secondary metabolites, and anti-oxidative systems. Therefore, a comprehensive study is needed to shed light on the ROS activity with the application of ENMs to direct research on the lesser exploited side. [Display omitted] • Reactive oxygen species (ROS) are central to every abiotic stress limiting plantʼs productivity. • In the present field of plant sciences, mitigating the effects of abiotic stresses by maintaining ROS level is a prerequisite. • Integrating nanomaterials (NMs) into plant redox biology is a new avenue and seems useful in enhancing crop production. • The designing of more efficient and targeted NMs to trigger more precise and specified resistance in plants. • Molecular dissection provides valuable insights into the application of NMs in modern-day agriculture. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. For successful development and adoption of technology on dairy farms, farmers need to be included in the innovation process. However, the design of agricultural technologies usually takes a top-down approach with little involvement of end-users at the early stages. Living Labs offer a methodology that involve end-users throughout the development process and emphasize the importance of understanding users' needs. Currently, exploration of dairy farmers' technology needs has been limited to specific types of technology (e.g., smartphone apps) and adult cattle. The aim of this study was to use a Living Lab approach to identify dairy farmers' data and technology needs to improve herd health and inform innovation development. We conducted 18 focus groups with a total of 80 dairy farmers from Belgium, Ireland, the Netherlands, Norway, Sweden, and the United Kingdom. Data were analyzed using Template Analysis, and 6 themes were generated representing the fundamental needs of autonomy, comfort, competence, community and relatedness, purpose, and security. Farmers favored technologies that provided them with convenience, facilitated their knowledge and understanding of problems on farm, and allowed them to be self-reliant. Issues with data sharing and accessibility and usability of software were barriers to technology use. Furthermore, farmers were facing problems around recruitment and management of labor and needed ways to reduce stress. Controlling aspects of the barn environment, such as air quality, hygiene, and stocking density, were particular concerns in relation to youngstock management. Overall, the findings suggest that developers of farm technologies may want to include farmers in the design process to ensure a positive user experience and improve accessibility. The needs identified in this study can be used as a framework when designing farm technologies to strengthen need satisfaction and reduce any potential harm toward needs. [ABSTRACT FROM AUTHOR]

Precision agriculture technologies (PATs) are believed to be able to ensure the sustainability of rice production. However, the adoption of PATs in developing countries is much lower than in developed countries. The basic question of our research is how Indonesian rice farmers are ready to adopt precision agriculture since they are smallholder farmers. Data was collected from 521 rice farmers in five Indonesian provinces, i.e. North Sumatra, West Java, Yogyakarta, South Sulawesi, and East Nusa Tenggara, in 2023. Farmers were interviewed face to face using structured questionnaires. The data were analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) through the Python software. The results showed that Indonesian rice farmers have a moderate level of readiness. The mean value of the capabilities and opportunities indicators were 2.54 to 3.8, while the range for the opportunity's indicator is 3.23 to 4.11, larger than the capabilities indicators. The level of precision agriculture implementation on Indonesian rice farmers was significant influenced by management (β = 0.42, t = 7.11, p < 0.05), environment (β = 0.17, t = 3.63, p < 0.05), readiness (β = 0.14, t = 2.51, p < 0.05), and technology (β = 0.10, t = 2.12, p < 0.05), economy (β = 0.09, t = 3.63, p < 0.05), and technology2 (β = -0.072, t = 3.5, p < 0.05). Meanwhile, farmer readiness was significantly influenced by opportunity (β = 0.39, t = 6.64, p < 0.05) and capabilities (β = 0.43, t = 6.82, p < 0.05). This research provides information on the status of human resource capacity in exploiting opportunities for implementing precision agriculture and technical policy advice. The Indonesian government should improve farmers' skills in information technology, Global Positioning Systems (GPS), and sensor technology in agricultural sectors, and facilitate access to technology and resources in order to increase rice farmers' readiness to adopt PATs. For opportunity indicators, however, further research is needed to determine which components require immediate attention for construction or development. [ABSTRACT FROM AUTHOR]

Nanotechnology is a rapidly developing discipline that has the potential to transform the way we approach problems in a variety of fields, including agriculture. The use of nanotechnology in sustainable agriculture has gained popularity in recent years. It has various applications in agriculture, such as the development of nanoscale materials and devices to boost agricultural productivity, enhance food quality and safety, improve the efficiency of water and nutrient usage, and reduce environmental pollution. Nanotechnology has proven to be very beneficial in this field, particularly in the development of nanoscale delivery systems for agrochemicals such as pesticides, fertilizers, and growth regulators. These nanoscale delivery technologies offer various benefits over conventional delivery systems, including better penetration and distribution, enhanced efficacy, and lower environmental impact. Encapsulating agrochemicals in nanoscale particles enables direct delivery to the targeted site in the plant, thereby reducing waste and minimizing off‐target effects. Plants are fundamental building blocks of all ecosystems and evaluating the interaction between nanoparticles (NPs) and plants is a crucial aspect of risk assessment. This critical review therefore aims to provide an overview of the latest advances regarding the positive and negative effects of nanotechnology in agriculture. It also explores potential future research directions focused on ensuring the safe utilization of NPs in this field, which could lead to sustainable development. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

In Korea, greenhouses are traditionally used for crop cultivation in the winter. However, due to diverse consumer demands, climate change, and advancements in agricultural technology, more farms are aiming for year-round production. Nonetheless, summer cropping poses challenges such as high temperatures, humidity from the monsoon season, and low light conditions, which make it difficult to grow crops. Therefore, this study aimed to determine the best planting time for summer tomato cultivation in a Korean semi-closed greenhouse that can be both air-conditioned and heated. The experiment was conducted in the Advanced Digital Greenhouse, built by the National Institute of Agricultural Sciences. The tomato seedlings were planted in April, May, and June 2022. Growth parameters such as stem diameter, flowering position, stem growth rate, and leaf shape index were measured, and harvesting was carried out once or twice weekly per treatment from 65 days to 265 days after planting. The light use efficiency and yield per unit area at each planting time was measured. Tomatoes planted in April showed a maximum of 42.9% higher light use efficiency for fruit production and a maximum of 33.3% higher yield. Furthermore, the growth form of the crops was closest to the reproductive growth type. Therefore, among April, May, and June, April is considered the most suitable planting time for summer cultivation, which is expected to contribute to reducing labor costs due to decreased workload and increasing farm income through increased yields. Future research should explore optimizing greenhouse microclimates and developing crop varieties tailored for summer cultivation to further enhance productivity and sustainability in year-round agricultural practices. [ABSTRACT FROM AUTHOR]

Indoor farming technologies, such as aquaponics and hydroponics, are crucial for advancing sustainable agriculture, especially in urban areas with limited land for conventional agriculture. As studies comparing these two systems are limited, this study explored the cultivation of five leafy vegetables--white leaf beets (Beta vulgaris var. cicla), hooker chives (Allium hookeri), basil (Ocimum basilicum), lemon balm (Melissa officinalis), and spearmint (Mentha spicata)--in an indoor greenhouse facility using two different food production platforms: an aquaponic system (AS) with catfish (Silurus asotus) and a conventional hydroponic system (HS). The results showed that the plant growth in AS outperformed that in HS, while the general growth patterns in AS were significantly affected by the different light sources. In addition, the leaf yield of the herbal plants (basil and lemon balm) in AS was 60%-70% more than that in HS. The leaf growth of hooker chives in AS also showed significant improvement (200%) compared with that in HS. It appears that the nutrient sources provided by fish were remarkable, as the average concentration of NO3-N (64 mg/L) was easily achieved in AS. The proposed AS, therefore, would be a promising alternative to the production and supply of supplement organic food, ultimately contributing to promoting sustainable agriculture in a changing climate. [ABSTRACT FROM AUTHOR]

Purpose: Artificial Intelligence-based smart farming technologies have brought impressive changes in farming. This paper aims at exploring the farmers' intention to adopt smart farming technologies (SFT). Also, the authors intend to know how far the belief of farmers on land as God influences their decision to adopt SFT. Design/methodology/approach: The data were gathered from 500 farmers chosen purposively. A well-crafted survey instrument was employed to amass data from farmers for measuring their adoption of SFT. As the authors sought to measure the farmers' behavioural intention (BI) towards the adoption of SFT, the technology acceptance model developed by Davis (1989) came in handy, including perceived usefulness (PU), perceived ease of use (PEU) and BI. The authors have adopted this model as it was considered a superior model. The items on the attitude of confidence (AC) were adapted from Adrian et al. (2005). Survey instruments of Thompson and Higgins (1991) and Compeau and Higgins (1995) were also referred to finalize the statements relating to attitude towards use. Moreover, the authors developed items relating to the perceived belief of land as God based on frequent interaction with the farmers. Findings: The study results divulged that attitude to use (AU) is directly influenced by the rural farmers' PU, PEU and AC. Similarly, this investigation has observed behaviour intention directly influenced by the AU of farmers. It is observed that AU was the most influential variable, which ultimately influenced the BI to use SFT. Research limitations/implications: This study has an important limitation in the form of representing only the culture, belief and value system of farmers in India. Practical implications: The outcome of this study will facilitate the policymakers to draw suitable policy measures keeping the sensitivities of the farmers in mind in their technology adoption drive. The agricultural officers can encourage farmers to take logical decisions by supplying adequate information in a time-bound manner. Marketers can make suitable adjustments in their sales and promotion activities that focus on farmers. Social implications: The belief of farmers on land as God has a small yet unmissable influence on farmers' AU and BI in their technology adoption decision. Based on the above evidence, the authors recommend that marketers fine-tune their product design, product packaging and promotional activities keeping the belief and sensitivities of farmers at the core of their marketing campaign. Originality/value: This article provides original insights by demonstrating the positive influence of PU, PEU and AC on technology adoption by farmers. This research is the first of a kind linking the belief of farmers on land as God with smart farming technology adoption in farming. [ABSTRACT FROM AUTHOR]

Introduction: Advances in farming technologies and practices have helped farmers to increase crop yields, but continued production increases - while needed to feed a growing global population - are being hindered by climate change and other environmental challenges. Kansas, a globally important region for wheat production, is already experiencing threats to staple crop production. This study explores one possible alternative future for Kansas crop production in which farmers could, by crop switching, continue to grow nutrient-rich crops while responding to hotter temperatures and increasing water demand. Methods: We used a combination of climate and crop modeling with simple water budgets to identify optimal crop mixes under anticipated climatic and water constraints. Interviews with Kansas farmers helped identify feasible crop switching options: sorghum instead of corn (maize), winter rye and winter oats instead of winter wheat, and millet instead of soybeans. Results: Our analysis suggests that a sizeable proportion of current Kansas cropland would need to shift to these alternative crops by 2050 to meet anticipated water constraints and produce equivalent nutritional value under projected climate conditions. Alternative crops could increase from 16% of Kansas' crop area in 2021 to 43% of the area in 2050, resulting in a reduction in 2050 crop water demand of 12% relative to that of the current cropmix. This crop water demand reduction would be concentrated in parts of the state that will experience the greatest change in water needs between today and mid-century due to changing climate conditions. Discussion: Our analysis shows that, by changing (diversifying) the mix of crops grown, it is biophysically possible for crop production in Kansas to be both sustainable and resilient under future climate conditions. However, achieving a more climate-resilient crop mix on the ground, in Kansas and elsewhere, will require major shifts in the broader agricultural system. Food companies, agricultural lenders, and policymakers can play a key role in enabling farmers to adapt cropping systems in the face of climate and environmental challenges. [ABSTRACT FROM AUTHOR]

Background Aims Methods Results Conclusions Nanotechnology, utilizing nanoparticles (NPs) with unique physicochemical properties, has significant potential in enhancing sustainable agriculture through innovations in plant nutrition, growth, and protection.This review aims to assess how nanotechnology, particularly NPs, contributes to sustainable agriculture by improving plant nutrition and growth, enhancing stress resistance, and offering solutions for phytoremediation and agricultural efficiency.We examine studies showcasing the application of NPs in agriculture, focusing on their effects on plant growth, nutrient delivery, stress mitigation, pollutant removal, and the enhancement of food shelf life through nano‐encapsulated fertilizers and nano‐sensors.NPs have demonstrated promising results in slow‐release fertilizers for targeted nutrient delivery, improved germination and physiological activity under stress, and enhanced efficiency in phytoremediation by aiding the removal of pollutants. Nano‐sensors in food packaging detect deterioration and extend food shelf life, whereas nano‐encapsulation of agrochemicals offers environment‐friendly pest and nutrient management solutions.Nanotechnology presents a forward‐looking approach to sustainable agriculture by enhancing crop productivity, resource use efficiency, and environmental protection. Continued research is essential to unlock the full potential of NPs in agriculture, emphasizing safe and efficient application methods to mitigate abiotic and biotic stresses and promote sustainability. [ABSTRACT FROM AUTHOR]

Summary: The main goal of this strategy is to detect the occurrence of wild animals in farmsteads and human habitats using an improved deep learning in order to avoid loss of life and damage to agricultural crops. This paper formulates a technique for recognizing wild animals in an Internet of Things (IoT) environment utilizing deep batch normalized exponential linear unit AlexNet (DbneAlexnet) and the Gazelle Hunting Optimization Algorithm (GHOA). The IoT‐Multimedia Sensor Networks (WMSN) network is first simulated, with the IoT nodes capturing the images needed for wild animal identification. The suggested GHOA is used for routing, which sends the captured images to the base station (BS). The input wild animal image is transmitted to image preprocessing at the BS, where it is processed using the Weiner filter (WF) to remove undesirable noise from the image. The denoised output is sent into salient map extraction, which extracts salient map to determine the regions that are conspicuous or noticeable at every place in the field of vision and guides the selection of attended location. Finally, the saliency map is forwarded to DbneAlexnet for detecting the wild animals, where the DbneAlexnet is trained using proposed GHOA. The suggested GHOA algorithm is created by combining the Gazelle Optimization Algorithm (GOA) and the deer hunting optimization algorithm (DHOA). Furthermore, detection is appraised by precision, recall, and f1‐score, which provide values of 90.2%, 89.1%, and 89.6%, respectively. [ABSTRACT FROM AUTHOR]

Background: Climate change is one of humanity's biggest problems. CSA offers a once-in-a-lifetime chance to adapt to global climate change and reduce greenhouse gas emissions. UA can improve food security by providing affordable, nutritious alternatives to commercially produced food, especially for economically disadvantaged people. This study examined the factors influencing the adoption of UA as CSA practices, as well as their effects on food security in Wolaita Sodo City, South Ethiopia. Methods: Data was collected from primary and secondary sources, both qualitative and quantitative form. A structured and semi-structured questionnaire was used to gather data from 384 randomly chosen urban households through surveys/interviews, focus group conversations, and observation. The percentage and mean differences between UA adopters and non-adopters were calculated using the chi-square test and t-test. A propensity score matching (PSM) model assessed UA's impact on food security. A binary logistic regression model was used to determine factors influencing adoption of UA as CSA practice in the study area. Results: The descriptive analysis showed that 53.53% of respondents used UA. Statistics showed the existence of a significant mean differences between adopters and non-adopters in employment level, UA attitudes, and household size. Logit model computations showed that family size, home ownership, the household head's occupation, perceptions of UA, market demand, and access to training and support influenced UA adoption as a climate-smart farming practice. Conclusions: As per the study's findings, there could be a correlation between specific factors and the adoption of UA as CSA in the studied area. The PSM study confirmed that UA deployment significantly improves food security. UA adoption increased food security by 0.685-fold. The report recommends that municipal education offices, UA offices, and cooperative offices create an integrated functional adult education programme for urbanites. Since UA is vital to fighting food insecurity, it suggests increasing support for cooperative entities. [ABSTRACT FROM AUTHOR]

Molecular farming, the practice of engineering plants to produce recombinant proteins, presents novel challenges and opportunities for domestic markets and international trade. This article explores the multifaceted risks associated with these biotechnological advancements, including public health concerns related to recombinant animal proteins produced in plants, cross-contamination and unintended allergens, and the necessity for stringent identity preservation systems to avoid past failures. On the global stage, the trade of such genetically engineered crops brings about unique regulatory concerns, underscoring the need for internationally harmonized policies and reevaluating existing low-level presence (LLP) thresholds to address unexpected allergens. Moreover, molecular farming ventures into complex religious and ethical territories, particularly affecting communities with strict dietary laws, such as Islamic, Jewish, and those following vegan or vegetarian lifestyles. Addressing these concerns requires a collaborative approach among scientists, regulatory bodies, industry leaders, and religious figures, aiming to foster an inclusive dialogue that navigates the ethical, religious, and environmental implications of integrating animal proteins into plant-based systems. Such efforts are essential for ensuring the responsible development of molecular farming technologies, contributing to a future of sustainable, secure, and inclusive food systems that respect diverse cultural and ethical values. [ABSTRACT FROM AUTHOR]

Introduction: Digital agricultural technology service has the characteristics of high efficiency, convenience and flexibility, and plays an important role in the process of Chinese agricultural digitalization, which is of great significance for realizing the modernization and intelligent development of agricultural production. Methods: Based on micro-survey data of small-scale farmers in Sichuan Province, this study utilizes the OLS method and the mediation effect model to investigate the impact of digital agricultural technology services on farmers' willingness to adopt digital production technologies and its underlying mechanisms. Results: The results indicate that digital agricultural technology services effectively enhance farmers' willingness to adopt digital production technologies, especially among those engaged in cooperative. Further analysis of mechanisms suggests that digital agricultural technology services influence farmers' choices of household production and management methods by expanding their information channels, enhancing their cognition of digital production technologies, and facilitating access to technology. Moreover, heterogeneous analysis reveals significant differences in the willingness of farmers with varying levels of digital literacy to adopt digital production technologies. Digital agricultural technology services have a more pronounced impact on the willingness of highly digitally literate farmers. Discussion: The findings of this paper deepen our comprehension of the operational mechanisms of digital agricultural technology services in the context of agricultural development, and advocate for policy recommendations such as enhancing the supply of digital agricultural technology services, strengthening the role of new agricultural entities, improving farmers' digital literacy training, and enhancing policy support systems. [ABSTRACT FROM AUTHOR]

Based on the learning characteristics of the higher quality professional farmer students, this article had taken the course of production technology and equipment of facility agriculture as an example, which was one of the core curriculum of the major of facility agriculture of Beijing Vocational College of Agriculture. The course teaching overall plan was elaborated in this paper in terms of teaching objectives, course content, teaching mode, curriculum politics and assessment program. Also, with the teaching implementation process analysis of the learning module task of installation and operation of soilless culture facilities, the teaching exploration and practice of the teaching team for this course was displayed in the paper, which provided profitable experience and reference for the deeper curriculum reform. [ABSTRACT FROM AUTHOR]

In order to better develop green agricultural products in Jining and promote high-quality agricultural development, this paper based on SWOT to analyze and conclude that there are five advantages to develop green agricultural products in Jining including natural resources, advantageous agricultural industry, modern agricultural technology, human resources, and green agricultural development model, and there are four disadvantages of green agricultural products on small scale of green agricultural products, low popularization rate of green agricultural products production technology, backward management mode of green agricultural products and relatively backward supervision of green agricultural products, and there are three opportunities; the need of the new era, policy guidance and support, and the transformation of consumption concept, and it is threatened by the slowdown of investment in agriculture, the lack of competitiveness of green agricultural products, and the uncertainty of international trade. Strategic suggestions were put forward; in order to develop well green agricultural products in Jining, it was necessary to enlarge and strengthen the superior and high-quality agricultural products industry, improve the quality of agricultural products of small and medium-sized farmers, and continuously improve the certification of "pollution-free, green and organic" products, attach importance to the application and implementation of advanced cultivation technologies and expand effective investment in agriculture, and effectively solve the quality problems in the development of green agricultural products. [ABSTRACT FROM AUTHOR]

Due to its readily soluble nature in groundwater and surface water, an excess accumulation of soluble salts in the soil, especially sodium chloride (NaCl), could pose serious threats to crop growth and development by disrupting physiological and biochemical processes in plants. The excess of soluble salt could originate from natural processes, such as weathering (physical or chemical) of parent rock materials, wind, and rainfall, and is thus termed as primary soil salinization. Besides, various anthropogenic activities, such as irrigation with brackish or saline water, poor land and water management, overuse of synthetic fertilizers, overextraction of groundwater, and saltwater intrusion into coastal aquifers as a result of sea level rise, could also create a salinity problem, which is known as secondary soil salinization. The salinity problem in soil and land of arid and semi-arid regions is even more severe. The concentration of salt is referred to as the sum of cation and anion or only cation or anion and is expressed as mg L-1. However, it is commonly measured as electrical conductivity (EC) of saturated soil extract (ECe) for scientific and analytical purposes and is expressed with a unit of decisiemens per meter (dS m-1). Salinity is a multi-dimensional stress for plants, impairing plant growth and development through cytotoxicity caused by excessive uptake of Na+ and Cl- ions, water stress, and nutritional imbalance. In addition, salinity is generally accompanied by oxidative stress because of the overproduction of reactive oxygen species. The water scarcity phase of salinity results in substantial yield loss through rapid inhibition of growth and development, while the ionic toxicity phase causes rapid leaf senescence through a variety of adverse impacts on cellular components simultaneously. Moreover, prooxidants generation at higher levels of salt stress threatens standard metabolic processes and poses a risk of irreversible damage on biomembranes, cellular organelles, nucleic acids, and proteins. Such constraints make cropping a great challenge in salt-affected areas; however, naturally salt-tolerant plants, also known as halophytes or semi-halophytes, can easily withstand comparatively higher salt concentrations because of their adaptive morpho-physiological and molecular mechanisms. Unlike halophytic or semi-halophytic plants, most of the commonly cultivated crops fail to tolerate salt stress as they fall under glycophyte or salt-susceptible category. However, the process of natural selection coupled with developing agricultural technologies has played a substantial role in imparting greater tolerance of crops to salt stress over the past few decades. Nevertheless, rapid sea level rise driven by anthropogenic climate change affecting the salinity of surface and groundwater in coastal areas and persistent spreading of salinity both in terms of land area and concentration call for a combined approach of compatible cultivar development and adoption of suitable management strategies. This necessitates a systematic and in-depth understanding of existing adaptations, tolerance mechanisms, and cultivation methods for stepping forward in strategizing future crop yield improvement programs. Therefore, the present review focuses on highlighting (i) the factors intensifying salinity problem in soils, (ii) salinity dynamics in plants including its uptake, transport, storage, and development of stress, (iii) salinity sensing mechanism in plants, (iv) naturally occurring adaptations, (v) genetic variabilities, and (vi) tolerance mechanisms available within cultivable crop germplasms with specific emphasis on morphological and anatomical tolerance, physiochemical tolerance, and role of genetic resources in enhancing tolerance against salinity. A number of agronomic, cultural, and technological management options to alleviate the adverse impacts of salt stress on crop plants are also discussed in this review, which could potentially offer invaluable information for the development of salt-tolerant crop improvement programs and optimized land and water management practices. [ABSTRACT FROM AUTHOR]

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods. [ABSTRACT FROM AUTHOR]

With the increasing number of patients with chronic kidney disease (CKD) and the improved recognition of nutritional therapy, research on low-potassium (LK) fruits and vegetables for CKD patients has gained global attention. Despite its already commercial availability primarily in Japan, public awareness remains limited, and cultivation methods lack a comprehensive strategy. This review offers an extensive examination of the developmental significance, current cultivation techniques, and existing limitations of functional LK fruits and vegetables with the objective of providing guidance and inspiration for their exploitation. Additionally, this review investigates various factors influencing K content, including varieties, temperature, light, exogenous substances, harvest time, and harvest parts, with a focus on optimizing production methods to enhance potassium utilization efficiency (KUE) and decrease the K content in plants. Finally, the review outlines the shortcomings and prospects of research on LK fruits and vegetables, emphasizing the importance of interdisciplinary research (in agriculture technology, medicine, and business) for patients with CKD and the future development of this field. [ABSTRACT FROM AUTHOR]

With the advancements in nanotechnology, the interaction between nanotechnology, society and environment has increased. Nanotherapeutics and nanopharmaceuticals have allowed facilitation of earlier and more precise diagnosis, reduced side effects, improved targeted therapies and efficacy of drugs. Likewise, nanotechnology has helped in improving the quality of environment by solving issues of air pollution, water remediation and waste management with the help of nanoproducts such as nanofilters, nanophoto catalysts, nanoadsorbents and nanosensors. Moreover, nanopesticides, nanofood, anti-bacterial nanopackaging, nanofertilizers and many other products have helped food and agriculture sector to grow. There are innumerable products on shelf based on nanotechnology impacting almost every sector. However, nanotechnology like any other technology if used unchecked and unregulated can be a cause of social, environmental, legal and ethical concerns. Therefore, it is crucial to consider these challenges in addition to the promises and opportunities nanotechnology has to offer. This review has highlighted the immense importance of nanotechnology by discussing its applications especially in medicine, environmental sciences and food and agriculture sectors. Closely studying these aspects will allow us to discover gaps, obstacles and potential solutions for responsible nanotechnology development and deployment. Understanding these concerns and challenges is also critical for policymakers, researchers, industrialists and society as a whole in order to promote ethical practices and informed decision-making. This review will help to contribute to the continuing discourse and raise ethical awareness in the field of nanotechnology thence minimizing the harm while maximizing the benefits. [ABSTRACT FROM AUTHOR]

To meet the objectives of the Paris Agreement, which aims to limit the increase in global temperature to 1.5°C, significant greenhouse gas (GHG) emission reductions will be needed across all sectors. This includes agriculture which accounts for a significant proportion of global GHG emissions. There is therefore a pressing need for the uptake of new technologies on farms to reduce GHG emissions and move towards current policy targets. Recently, precision livestock farming (PLF) technologies have been highlighted as a promising GHG mitigation strategy to indirectly reduce GHG emissions through increasing production efficiencies. Using Scotland as a case study, average data from the Scottish Cattle Tracing System (CTS) was used to create two baseline beef production scenarios (one grazing and one housed system) and emission estimates were calculated using the Agrecalc carbon footprinting tool. The effects of adopting various PLF technologies on whole farm and product emissions were then modelled. Scenarios included adoption of automatic weigh platforms, accelerometerbased sensors for oestrus detection (fertility sensors) and accelerometer-based sensors for early disease detection (health sensors). Model assumptions were based on validated technologies, direct experience from farms and expert opinion. Adoption of all three PLF technologies reduced total emissions (kg CO2e) and product emissions (kg CO2e/kg deadweight) in both the grazing and housed systems. In general, adoption of PLF technologies had a larger impact in the housed system than in the grazing system. For example, while health sensors reduced total emissions by 6.1% in the housed system, their impact was slightly lower in the grazing system at 4.4%. The largest reduction in total emissions was seen following the adoption of an automatic weight platform which reduced the age at slaughter by 3 months in the grazing system (6.8%) and sensors for health monitoring in the housed system (6.1%). Health sensors also resulted in the largest reduction in product emissions for both the housed (12.0%) and grazing systems (10.5%). These findings suggest PLF could be an effective GHG mitigation strategy for beef systems in Scotland. Although this study utilised data from beef farms in Scotland, comparable emission reductions are likely attainable in other European countries with similar farming systems. [ABSTRACT FROM AUTHOR]

Summary: Smart Farming has become a cornerstone of modern agriculture, offering data‐driven insights and automation that optimize resource utilization and increase crop yields. The use of cutting‐edge technologies in agriculture has given rise to Smart Farming, which has transformed traditional farming practices into efficient, data‐driven operations. This paper explores the synergy between high‐performance computing (HPC) systems, Kubernetes orchestration, GoogleNet architecture, and containerization to redefine the future of farming. At the heart of this transformation lies the GoogleNet architecture, a deep learning powerhouse recognized for its efficiency and accuracy in image recognition tasks. The orchestration capabilities of Kubernetes, a versatile tool for managing containerized workloads efficiently on HPC clusters. Hence, in this work, we investigate the intricacies of deploying GoogleNet‐based deep learning models within containerized environments orchestrated by Kubernetes on HPC infrastructure. It explores resource optimization, scalability, security, and adaptability, all tailored to the unique demands of the agricultural domain to evaluate the effectiveness of the given technique it is compared with the existing techniques namely Hermes, Horus, CYBELE, and RZ‐SHAN. The attained ranges of proposed method of various measures of accuracy, precision, recall, and F1‐score are 98.65%, 97.45%, 97.87%, and 98.12% for the Pilot Wheat Ear dataset. Also, the processing time for the proposed approach is 181.50 and 120.2 m for the Pilot Wheat Ear Dataset and the Pilot soya bean farming dataset. The latency of the proposed approach attains a lower value of 1.5 and 1.1 s pilot soya bean farming dataset and Pilot Wheat Ear dataset. The experimental outcome demonstrates the efficiency of the proposed approaches to improve Smart Farming agriculture. [ABSTRACT FROM AUTHOR]

Complex contextual and sociopsychological factors influence the adoption of agricultural technologies like irrigation. This study used the sociopsychological Risk-Attitude-Norms-Abilities-Self-Regulation (RANAS) framework to examine the factors impacting irrigation adoption in Maharashtra (India). Logistic regression modelling was conducted based on cross-sectional surveys in 2019 and 2022, with interim interventions promoting risk-awareness and irrigation technology training. Effects of the interventions on the psychological variables in 2022 were corrected using instrumental variable regression. While micro-irrigation adoption rose from 36.9% to 62.8%, overall irrigation counterproductively decreased from 81.6% to 70.4%. Results indicated that wealth and risk-aversion remained relevant, while self-perceived ability and attitude towards irrigation became non-significant to irrigation adoption. This study highlights the unintended consequences of interventions and the necessity to also transform attitudes, and promote psychological ownership and trust to sustain irrigation technology adoption behaviour. These results could support stakeholders (e.g., policy makers, water authorities) in designing and implementing more sustainable interventions. [ABSTRACT FROM AUTHOR]

Globally, the carbon footprint (CF) is constantly increasing, contrasting with the decreasing trend observed for decades in the European Union (EU) countries, where EU guidelines are responsibly followed and outlined in its strategic documents. Information and communication technology (ICT) carbon emissions have historically increased in parallel with global emissions, contributing to continuous increases in ICT's CF over time, even when excluding full life cycle emissions. This study examines the impact of ICT on household electricity consumption, aiming to quantify the potential reduction of greenhouse gas (GHG) emissions through improved household energy efficiency. The methodology includes the data collection on ICT device usage in households within the city of Novi Sad (Republic of Serbia), employing the survey method that queries respondents on device quantities and their usage patterns. This study provides results for decision-makers to recognize concrete benefits from the transition to a circular economy (CE) and low-carbon emissions, which are reflected as benefits for the local community and socio-economic environment. [ABSTRACT FROM AUTHOR]

The growing demand for agricultural products, driven by the Green Revolution, has led to a significant increase in food production. However, the demand is surpassing production, making food security a major concern, especially under climatic variation. The Indian agriculture sector is highly vulnerable to extreme rainfall, drought, pests, and diseases in the present climate change scenario. Nonetheless, the key agriculture sub-sectors such as livestock, rice cultivation, and biomass burning also significantly contribute to greenhouse gas (GHG) emissions, a driver of global climate change. Agriculture activities alone account for 10–12% of global GHG emissions. India is an agrarian economy and a hub for global food production, which is met by intensive agricultural inputs leading to the deterioration of natural resources. It further contributes to 14% of the country's total GHG emissions. Identifying the drivers and best mitigation strategies in the sector is thus crucial for rigorous GHG mitigation. Therefore, this review aims to identify and expound the key drivers of GHG emissions in Indian agriculture and present the best strategies available in the existing literature. This will help the scientific community, policymakers, and stakeholders to evaluate the current agricultural practices and uphold the best approach available. We also discussed the socio-economic, and environmental implications to understand the impacts that may arise from intensive agriculture. Finally, we examined the current national climate policies, areas for further research, and policy amendments to help bridge the knowledge gap among researchers, policymakers, and the public in the national interest toward GHG reduction goals. [ABSTRACT FROM AUTHOR]

Introduction: As an advanced agricultural technology equipment, the functional integration design and appearance aerodynamic characteristics of hexacopter agricultural UAV are significant for improving the efficiency of agricultural production. Methods: Firstly, the study carried out the functional integration design of the hexacopter agricultural UAV, and completed the matching analysis and selection of the relevant components of the power system. Then, the numerical simulation method of computational fluid dynamics was used to analyze the aerodynamic characteristics of the UAV. Finally, the role of different propeller pitch on important parameters such as lift and range time of the UAV was verified. Results and discussion: The results showed that in the XY section of the UAV, namely, the surface parallel to the flight direction, the areas with high streamline velocityweremainly concentrated at the intersection of the airflowwith the landing gear and the motor. The streamlines in the front of the UAV were tightly and neatly distributed, while those in the rearwere sparser. Themotor force efficiencies of the UAVswith different propeller pitches ranged from7.05 to 7.25 g/w. At a flight speed of 5m/s, themotor force effect of theUAV with a pitch of 260mmreached 7.25 g/w, which was the highest value among all models. Meanwhile, it had the longest endurance time of 19.14 min, indicating the best performance. The results suggested that it not only promoted the modernization of agricultural UAVs but also effectively enhanced the efficiency of agricultural production. [ABSTRACT FROM AUTHOR]

In the last decade, advances in soil bacterial ecology have contributed to increasing agricultural production. Brazil is the world leading agriculture producer and leading soil biodiversity reservoir. Meanwhile, there is still a significant gap in the knowledge regarding the soil microscopic life and its interactions with agricultural practices, and the replacement of natural vegetation by agroecosystems is yet to be unfolded. Through high throughput DNA sequencing, scientists are now exploring the complexity of soil bacterial communities and their relationship with soil and environmental characteristics. This study aimed to investigate the progress of bacterial ecology studies in Brazil over the last 10 years, seeking to understand the effect of the conversion of natural vegetation in agricultural systems on the diversity and structure of the soil microbial communities. We conducted a systematic search for scientific publication databases. Our systematic search has matched 62 scientific articles from three different databases. Most of the studies were placed in southeastern and northern Brazil, with no records of studies about microbial ecology in 17 out of 27 Brazilian states. Out of the 26 studies that examined the effects of replacing natural vegetation with agroecosystems, most authors concluded that changes in soil pH and vegetation cover replacement were the primary drivers of shifts in microbial communities. Understanding the ecology of the bacteria inhabiting Brazilian soils in agroecosystems is paramount for developing more efficient soil management strategies and cleaner agricultural technologies. [ABSTRACT FROM AUTHOR]

The study aims to analyse the current mechanisms of state regulation of food security in Kazakhstan and Azerbaijan to identify and assess their effectiveness. Among the methods used were analytical, statistical, functional, method of system analysis, deduction, synthesis, and comparison. A comparative analysis of state regulation of food security in Kazakhstan and Azerbaijan was conducted, leading to recommendations for enhancing regulatory measures. Suggestions include integrating new agricultural technologies, fostering international partnerships, and learning from other nations' exfperiences. The study also highlighted opportunities for sustainable agricultural development, product quality improvement, and ensuring food accessibility across various population segments in both regions. [ABSTRACT FROM AUTHOR]

The purpose of the study is to assess the food security of Kazakhstan and analyze the production and consumption of food. The methods that were used are the dialectical method of scientific knowledge, general scientific, special methods, and statistical analysis. The article identifies such priority areas: the production of their own food, the use of innovative, resource-saving technologies in agriculture; integrated use of land resources, solving the problems of degraded pastures; attracting human resources, investments, and technologies to the industrial sector; implementation of the consolidation of agricultural land and the development of animal husbandry; opening of new export markets. [ABSTRACT FROM AUTHOR]

Good land management provides protection against land degradation for long-term and effective use. A survey was conducted among students in Kazakhstan for an internal assessment of the education quality. It was found that for ensuring competent land management, state financial support and external investment have to meet the needs for working capital and improve the quality of the material and technical base and staff; the quality education of new experts and their motivation have to be ensured; innovations introduction in the agricultural sector and long-term planning with centralized control have prospects for increasing economic efficiency. [ABSTRACT FROM AUTHOR]

The accurate identification of corn leaf diseases is crucial for preventing disease spread and improving corn yield. Plant leaf images are often affected by factors such as complex backgrounds, climate, light, and sample data imbalance. To address these issues, we propose a lightweight convolutional neural network, ICS-ResNet, based on ResNet50. This network incorporates improved spatial and channel attention modules as well as a deep separable residual structure to enhance recognition accuracy. (1) The residual connections in the ResNet network prevent gradient loss during deep network training. (2) The improved channel attention (ICA) and spatial attention (ISA) modules fully utilize semantic information from different feature layers to accurately localize key features of the network. (3) To reduce the number of parameters and lower computational costs, we replace traditional convolutional computation with a depth-separable residual structure. (4) We also employ cosine annealing to dynamically adjust the learning rate, enhancing the network's training stability, improving model convergence, and preventing local optima. Experiments on the corn dataset in Plant Village compare the proposed ICS-ResNet with eight popular networks: CSPNet, InceptionNet_v3, EfficientNet, ShuffleNet, MobileNet, ResNet50, ResNet101 and ResNet152. The results show that the ICS-ResNet achieves an accuracy of 98.87%, which is 5.03%, 3.18%, 1.13%, 1.81%, 1.13%, 0.68%, 0.44% and 0.60% higher than the other networks, respectively. Furthermore, the number of parameters and computations are reduced by 69.21% and 54.88%, respectively, compared to the original ResNet50 network, significantly improving the efficiency of corn leaf disease classification. The study provides strong technical support for sustainable agriculture and the promotion of agricultural science and technology innovation. [ABSTRACT FROM AUTHOR]

Citrus pests pose a major threat to both citrus yield and fruit quality. The early prevention of pests is essential for sustainable citrus cultivation, cost savings, and the reduction of environmental pollution. Despite the increasing application of deep learning techniques in agriculture, the performance of existing models for small target detection of citrus pests is limited, mainly in terms of information bottlenecks that occur during the transfer of information. This hinders its effectiveness in fully automating the detection of citrus pests. In this study, a new approach was introduced to overcome these limitations. Firstly, a comprehensive large-scale dataset named IP-CitrusPests13 was developed, encompassing 13 distinct citrus pest categories. This dataset was amalgamated from IP102 and web crawlers, serving as a fundamental resource for precision-oriented pest detection tasks in citrus farming. Web crawlers can supplement information on various forms of pests and changes in pest size. Using this comprehensive dataset, we employed the SPD Module in the backbone network to preserve fine-grained information and prevent the model from losing important information as the depth increased. In addition, we introduced the AFFD Head detection module into the YOLOv8 architecture, which has two important functions that effectively integrate shallow and deep information to improve the learning ability of the model. Optimizing the bounding box loss function to WIoU v3 (Wise-IoU v3), which focuses on medium-quality anchor frames, sped up the convergence of the network. Experimental evaluation on a test set showed that the proposed SAW-YOLO (SPD Module, AFFD, WIoU v3) model achieved an average accuracy of 90.3%, which is 3.3% higher than the benchmark YOLOv8n model. Without any significant enlargement in the model size, state-of-the-art (SOTA) performance can be achieved in small target detection. To validate the robustness of the model against pests of various sizes, the SAW-YOLO model showed improved detection performance on all three scales of pests, significantly reducing the rate of missed detections. Our experimental results show that the SAW-YOLO model performs well in the detection of multiple pest classes in citrus orchards, helping to advance smart planting practices in the citrus industry. [ABSTRACT FROM AUTHOR]

This study was conducted on Xanthomonas axonopodis pv, which causes significant economic losses in the agricultural sector. Here, we study a common bacterial blight disease caused by the phaseoli (XaP) bacterial pathogen on Üstün42 and Akbulut bean genera. In this study, a total of 4000 images, healthy and diseased, were used for both bean breeds. These images were classified by AlexNet, VGG16, and VGG19 models. Later, reclassification was performed by applying pre-processing to the raw images. According to the results obtained, the accuracy rates of the pre-processed images classified by the VGG19, VGG16 and AlexNet models were determined as 0.9213, 0.9125 and 0.8950, respectively. The models were then hybridized with LSTM and BiLSTM for raw and pre-processed images and new models were created. When the performance of these hybrid models was evaluated, it was found that the models hybridized with LSTM were more successful than the simple models, while the models hybridized with BiLSTM gave better results than the models hybridized with LSTM. In particular, the VGG19+BiLSTM model attracted attention by achieving 94.25% classification accuracy with pre-processed images. This study emphasizes the effectiveness of image processing techniques in agriculture in the field of disease detection and is important as a new dataset in the literature for evaluating the performance of hybridized models. [ABSTRACT FROM AUTHOR]

Corn crop row recognition during different growth stages is a major difficulty faced by the current development of visual navigation technology for agricultural robots. In order to solve this problem, an algorithm for recognizing corn crop rows during different growth stages is presented based on the ST-YOLOv8s network. Firstly, a dataset of corn crop rows during different growth stages, including the seedling stage and mid-growth stage, is constructed in this paper; secondly, an improved YOLOv8s network, in which the backbone network is replaced by the swin transformer (ST), is proposed in this paper for detecting corn crop row segments; after that, an improved supergreen method is introduced in this paper, and the segmentation of crop rows and background within the detection frame is achieved utilizing the enhanced method; finally, the corn crop row lines are identified using the proposed local–global detection method, which detects the local crop rows first, and then detects the global crop rows. The corn crop row segment detection experiments show that the mean average precision (MAP) of the ST-YOLOv8s network during different growth stages increases by 7.34%, 11.92%, and 4.03% on average compared to the MAP of YOLOv5s, YOLOv7, and YOLOv8s networks, respectively, indicating that the ST-YOLOv8s network has a better crop row segment detection effect compared to the comparison networks. Corn crop row line detection experiments show that the accuracy of the local–global detection method proposed in this paper is improved by 17.38%, 10.47%, and 5.99%, respectively, compared with the accuracy of the comparison method; the average angle error is reduced by 3.78°, 1.61°, and 0.7°, respectively, compared with the average angle error of the comparison method; and the average fitting time is reduced by 5.30 ms, 18 ms, and 33.77 ms, respectively, compared with the average fitting time of the comparison method, indicating that the local–global detection method has a better crop row line detection effect compared to the comparison method. In summary, the corn crop row recognition algorithm proposed in this paper can well accomplish the task of corn crop row recognition during different growth stages and contribute to the development of crop row detection technology. [ABSTRACT FROM AUTHOR]

Agriculture has been the backbone of African economies, and agricultural development has the potential to drive overall economic growth. Considering the importance of agriculture in Africa, foreign aid donors have supported the sector to help push economic growth and reduce poverty. Studies indicate governance quality of a recipient country is an important factor for agricultural aid. Building upon this, the paper explores how bilateral donors provided agricultural aid to two African countries that have different institutional quality, Ghana and Uganda. The analysis of agricultural aid in those two countries was carried out with bilateral aidprofile data from 2011 to 2022. Despite the similar economic importance of agriculture in Ghana and Uganda, donors to Ghana invested the largest amount in agriculture among aid sectors, followed by health. On the other hand, donors to Uganda supported mainly health-relevant sectors with agriculture being ranked only fifth. Donors in both countries implemented agricultural aid mostly as project types. Yet, donors disbursed their aid funds through different aid channels. Donors to Ghana disbursed 48% of agricultural aid funds through the public sector institutions channel (or the state channel). By contrast, donors to Uganda disbursed only 24% of agricultural aid funds through the state channel, essentially bypassing Ugandan public agencies. They instead provided 76% of agricultural aid through the non-state channels such as non-governmental organizations, multilateral organizations, and private entities. Similar donor preferences of the aid disbursement channels were observed with total aid across all aid sectors. Overall, the donor aid profiles suggested donors provided Ghana with more flexible agricultural aid, while in Uganda they controlled agricultural aid more tightly. There could exist multiple underlying reasons for this, but the different level of institutional quality is highly likely one of the possible reasons. For foreign aid, governance quality is an important issue equally to both donors and recipients. [ABSTRACT FROM AUTHOR]

Technology is vital to American education. Each year schools spend millions of dollars on various technologies intended for use in classrooms, but research shows over a third of this equipment goes unused. This study explores how West Virginia agricultural educators make decisions about adopting and integrating internet-based technology into their classrooms. Results showed educators were most likely to use learning management systems and search engines, and least likely to use websites, apps, games, and the online curriculum platform iCEV. Educators integrated technology into their classrooms primarily by using it to provide and review lesson content with classes. Less common uses included introducing, activating, and assessing learning. [ABSTRACT FROM AUTHOR]

It is worthwhile to calculate the execution cost of a manipulator for selecting a planning algorithm to generate trajectories, especially for an agricultural robot. Although there are various off-the-shelf trajectory planning methods, such as pursuing the shortest stroke or the smallest time cost, they often do not consider factors synthetically. This paper uses the state-of-the-art Python version of the Robotics Toolbox for manipulator trajectory planning instead of the traditional D–H method. We propose a cost function with mass, iteration, and residual to assess the effort of a manipulator. We realized three inverse kinematics methods (NR, GN, and LM with variants) and verified our cost function's feasibility and effectiveness. Furthermore, we compared it with state-of-the-art methods such as Double A* and MoveIt. Results show that our method is valid and stable. Moreover, we applied LM (Chan λ = 0.1) in mobile operation on our agricultural robot platform. [ABSTRACT FROM AUTHOR]

Output uncertainty is a major concern for industries prone to exogenous, persistent and large fluctuations in output, such as agriculture, wind and solar power generation, while technology adoption aimed at mitigating output uncertainty can improve social welfare. This paper constructs a competitive market model with random output fluctuations to examine the scale of technology adoption at the long-term equilibrium and its comparison with the social optimum. We show that the First Welfare Theorem no longer holds in general, and depending on the characteristics of the demand function, the scale of technology adoption in the competitive market may be greater or less than the socially optimal scale. • We consider technology adoption aimed at mitigating output uncertainty in the competitive market. • We show that the First Welfare Theorem no longer holds in general. • We show that the scale of technology adoption in the competitive market may be too high or too low. [ABSTRACT FROM AUTHOR]

This study delves into the economic and trade relations between Turkey, the UAE, and Saudi Arabia over the past five years, highlighting the evolution driven by strategic interests and regional stability. The research analyzes secondary data, examining official trade and investment reports, government statements, international organization data, and academic articles. It also considers diplomatic developments such as highlevel visits and agreements. The period from 2020 to 2024 witnessed significant growth and diversification in trade among these nations. Turkey's exports to the UAE and Saudi Arabia increased markedly, driven by sectors like agricultural technologies, food security, clean energy, and construction. Key moments include the establishment of a $10 billion investment fund following UAE President Sheikh Mohammed bin Zayed Al Nahyan's visit to Turkey in 2021 and the signing of the Comprehensive Economic Partnership Agreement (CEPA) in 2023, aiming to elevate bilateral trade to $40 billion over five years. Simultaneously, Turkey's economic relations with Saudi Arabia experienced fluctuations but generally depicted a positive trend. High-level visits by President Recep Tayyip Erdoğan and Saudi Crown Prince Mohammed bin Salman revitalized economic ties, resulting in cooperation agreements across various sectors, including health, energy, and the defense industry. The economic relations between Turkey, the UAE, and Saudi Arabia reflect a dynamic interplay of strategic interests, mutual investments, and shared goals. The strengthened economic partnerships have contributed to regional stability and are expected to develop further, driven by strategic collaborations in energy, technology, and infrastructure. These developments underscore the importance of economic diplomacy and mutual investments in shaping future cooperation prospects and regional power dynamics. [ABSTRACT FROM AUTHOR]

Antimicrobial use (AMU) data are essential to monitor the effect of AMU reduction strategies in animal health. The use of technology and herd recording software to record AMU will be vital to scale the collation of these data in the future. The aim of this study was to determine the barriers and facilitators to Irish dairy farmers recording their AMU using a herd recording software and sharing AMU data. Thirty-three Irish dairy farmers involved in a study on AMU monitoring were asked to record their AMU using a herd recording software over a 12-mo period. At the end of the 12-mo period, 10 of these farmers were selected to take part in semi-structured interviews exploring their opinions on recording AMU, the use of herd recording software, and sharing AMU data. Interviews were transcribed and qualitatively analyzed using inductive thematic analysis. Several barriers and facilitators to farmers recording their AMU using a herd recording software and sharing AMU data were identified. Barriers included the age and generation of the farmer, farm infrastructure, a lack of training and education, a lack of knowledge around the benefits of digital data, a lack of incentive to digitize records, and a fear of repercussions. Facilitators identified by the farmers included the benefits of having instantly available data for making herd management decisions, reduced paperwork, increased organization for inspections, and a potential positive effect on the image of the dairy industry. To increase the uptake of new technology to record AMU at farm-level, farmers will need support in terms of education and training around the software available to them and reassurance around the perceived risks of repercussions with sharing data in a digital format. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to develop and test the impact of a social media-based intervention for improving the business skills and income of young smallholder farmers. Design/methodology/approach: First, the researchers used an exploratory approach to develop a social media-based intervention for acquiring business skills and improving income. Second, the researchers tested the effectiveness of the developed programme on a sample of 506 young smallholder farmers. Finally, the intervention and data collection took place over five years (2017–2021). Findings: The result showed steady improvements in business skills and income from 2017 to 2021 for the treatment group, unlike the control group. Also, improvements in business skills led to a reduction in expenses and an increase in profit from 2017 to 2021. A further evaluation of the result showed that an addition of 5.1 mean scores in business skills led to the addition of $91 income between 2017 and 2018; for 2018–2019, 2.6 improvements in business skills increased income by $123. For 2019–2020, a 2.7 improvement increased income by $209, whilst for 2020–2021, a 1.6 improvement increased income by $320. Originality/value: The results of this study could help explore ways of using social media to change behaviour aimed at improving income amongst young smallholder farmers. [ABSTRACT FROM AUTHOR]