Search

Improving the interest linkage models between new farmers and small farmers is an important measure to realize the organic connection between small farmers and modern agricultural development. Based on the survey data of 572 new farmers in 16 provinces in China, this study uses the ordered probit model to empirically analyze the impact of entrepreneurial organization form on the interest linkage models between new farmers and small farmers. The results show that: (1) The choice of different entrepreneurial organization forms such as individual operation, cooperative operation, partner operation and company operation by new farmers will significantly affect the degree of interest linkage and then the linkage models. Partner operation and company operation have significantly improved the tightness of interest linkage between new farmers and small farmers. (2) The form of entrepreneurial organization significantly impacts the interest linkage between new farmers and small farmers. The higher the stability of entrepreneurial organization form, the closer the interest linkage and the more significant the impact on the interest linkage models. This effect remains significant after considering potential endogeneity issues and robustness tests. (3) In addition, further research also found significant regional differences and group differences in the impact of entrepreneurial organization form on the new farmers and small farmers' interest linkage models. The impact of the western region is more significant than that of the eastern and central regions, and government entrepreneurship support policies can significantly strengthen the interest linkage models. The research results of this paper have vital reference significance for exploring the path of agricultural modernization under the "big country with small farmers"., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Stockmanship is an important determinant for good animal welfare and health. The goal of the FarmMERGE project is to investigate the associations between farmer health and work environment, and the health, productivity and welfare of their livestock. We merged several livestock industry databases with a major total population-based health study in Norway (The Trøndelag Health Study 2017–2019 (HUNT4)). This paper describes the project's collection and merging of data, and the cohort of farmers and farms that were identified as a result of our registry merge. There were 56,042 participants of HUNT4 (Nord-Trøndelag County participants only, participation rate: 54.0%). We merged a list of HUNT4 participants whose self-reported main occupation was "farmer" (n = 2,407) with agricultural databases containing production and health data from sheep, swine, dairy and beef cattle from 2017–2020. The Central Coordinating Register for Legal Entities was used as an intermediary step to achieve a link between the farmer and farming enterprise data. We identified 816 farmers (89.5% male, mean age 51.3 years) who had roles in 771 farming enterprises with documented animal production. The cohort included 675 unique farmer-farm combinations in cattle production, 139 in sheep, and 125 in swine. We linked at least one HUNT4 participant to approximately 63% of the dairy farms, 53% of the beef cattle farms, 30% of the sheep farms, and 38% of the swine farms in Nord-Trøndelag County in the 2017–2019 period. Using existing databases may be an efficient way of collecting large amounts of data for research, and using total population-based human health surveys may decrease response bias. However, the quality of the resulting research data will depend on the quality of the databases used, and thorough knowledge of the databases is required. [ABSTRACT FROM AUTHOR]

Nitrous oxide (N2O) and ammonia (NH3) volatilization (AV) are the major pathways of nitrogen (N) loss in soil, and recently, N2O and NH3 mitigation has become urgently needed in agricultural systems worldwide. However, the influence of straw incorporation (SI) and biochar addition (BC) on N2O and NH3 emissions are still unclear. To fill this knowledge gap, a soil column experiment was conducted with two management strategies using straw ‐ straw incorporation (S1) and straw removal (S0) ‐ and four biochar application rates (0 (C0), 15 (C1), 30 (C2), and 45 t ha−1 (C3)) to evaluate the impacts of their interactions on N2O and NH3 emissions. The results showed that NO3−−N concentration and pH was the major contributors to affect the N2O and NH3 losses. Without biochar addition, N2O emissions was decreased by 59.6% (P<0.05) but AV was increased by 97.3% (P<0.05) under SI when compared to SR. Biochar was beneficial for N2O mitigation when straw was removed, but increased N2O emission by 39.4%−83.8% when straw was incorporated. Additionally, biochar stimulated AV by 27.9%−60.4% under S0 and 78.6%−170.3% under S1. Consequently, SI was found to significantly interact with BC in terms of affecting N2O (P<0.001) and NH3 (P<0.001) emissions; co-application of SI and BC promoted N2O emissions and offset the mitigation potential by SI or BC alone. The indirect N2O emissions caused by AV, however, might offset the reduction of direct N2O caused by SI or BC, thus leading to an increase in overall N2O emission. This paper recommended that SI combined BC at the amount of 8.2 t ha−1 for maintaining a lower overall N2O emission for future agriculture practices, but the long-term impacts of straw incorporation and biochar addition on the trade-off between N2O and NH3 emissions and reactive N losses should be further examined and assessed. [ABSTRACT FROM AUTHOR]

The feeding amount of bass farming is closely related to the number of bass. It is of great significance to master the number of bass to achieve accurate feeding and improve the economic benefits of the farm. In view of the interference caused by the problems of multiple targets and target occlusion in bass data for bass detection, this paper proposes a bass target detection model based on improved YOLOV5 in circulating water system. Firstly, acquiring by HD cameras, Mosaic-8, a data augmentation method, is utilized to expand datasets and improve the generalization ability of the model. And K-means clustering algorithm is applied to generate suitable coordinates of prior boxes to improve training efficiency. Secondly, Coordinate Attention mechanism (CA) is introduced into backbone feature extraction network and neck feature fusion network to enhance attention to targets of interest. Finally, Soft-NMS algorithm replaces Non-Maximum Suppression algorithm (NMS) to re-screen prediction boxes and keep targets with higher overlap, which effectively solves the problems of missed detection and false detection. The experiments show that the proposed model can reach 98.09% in detection accuracy and detection speed reaches 13.4ms. The proposed model can help bass farmers under the circulating water system to accurately grasp the number of bass, which has important application value to realize accurate feeding and water conservation. [ABSTRACT FROM AUTHOR]

The benefits of internal communication not only can be associated with higher performance, but also with increased awareness of the values within an organization, setting and achieving objectives, getting involved in beneficial activities, encouraging employees' personal development and, last but not least, educating and motivating employees to take responsibility. A responsible working environment facilitates effective internal communication, which is in line with the principles of the Bata Management System. The aim of this paper is to evaluate whether setting top-down internal communication is in line with the sustainable principles of Tomas Bata in organizations in the Czech Republic. The article assesses workplace communication and relationships, including social sustainability and social responsibility, focusing on their added value for corporate practice in all areas of business. The study is based on quantitative research in organizations across sectors and qualitative research in agricultural organizations (questionnaire survey n1 = 183; focus group n3 = 5), using the tools of descriptive statistics, logistic regression and cluster analysis. The results have shown that combining methods of top-down communication is crucial for communicating information efficiently, stimulating employees and achieving the organization´s objectives and that Tomas Bata´s philosophy concerning communication setting can be implemented even more easily in the current digital age than it was in the past if organizations are interested. The research contributes to a better understanding of how the Bata Management System can be applied within each organization, how effective communication settings will help prevent conflicts that workers are engaged in, increase their stabilization, and facilitate the application of Bata's sustainable legacy in the international space. Research makes a significant contribution to advancing knowledge of effective communication from the perspective of Bata for the sustainability of agricultural organizations where the principles have not yet been explored. This is evidenced by the zero overlap with previously published articles despite the rapid progress of research and technology., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Urbancová et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Under the new development pattern, both "digital" and "low-carbon" development have entered the fast track, and digital transformation has become an important path to promote green development and enhance total factor productivity in agriculture. Based on the data of agricultural companies, this paper empirically verifies the impact of voluntary environmental regulations on total factor productivity. The empirical results show that voluntary environmental regulation has a significant positive impact on total factor productivity of agribusiness. In the mechanistic analysis, it is found that voluntary environmental regulations accelerate the digital transformation process of firms, which in turn increases their total factor productivity. In addition, the level of government environmental concern contributes to the increase of voluntary environmental regulations on firms' total factor productivity. The findings have practical implications for the sustainable development of agribusiness, providing empirical evidence for policy formulation and adjustment, and helping the agricultural economy to achieve high-quality development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Chen, Zhang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Recently, China has exerted great efforts to develop agro-industrial agglomerations and optimize the agricultural industry's regional distribution to increase farmers' income. This study posits that agro-industrial agglomeration should be "dual body," provides a theoretical framework for agro-industrial agglomeration's effects on farmer income, and uses a spatial panel model to prove its influence on farmers' income and the spatial spillover effect. The results show that agro-industrial agglomeration in a specific region significantly impacts farmers' income and also has a spillover effect on income in adjacent regions. Further research shows that, contrary to traditional agglomeration theory, agricultural industry agglomeration has little impact on farmers' agricultural production but primarily promotes the establishment and development of agricultural organizations, thus improving farmers' income. Finally, the paper discusses the positive and negative effects of agro-industrial agglomeration on the Global Sustainable Development Goals(SDGs), and proposes some useful suggestions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yi Ding. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Planning for cost-effective conservation requires reliable estimates of land costs, spatially-differentiated at high resolution. Nolte (2020) provides a county-by-county, parcel-level estimation approach that dramatically improves estimates of fair market value for undeveloped land across the contiguous Unites States. Much undeveloped land of conservation interest is under threat of conversion to agricultural use or is already agricultural. This paper demonstrates the value of accounting for additional variables that affect agricultural productivity and demand for undeveloped land, as well as the benefit of modeling at scales corresponding to regional agricultural markets. We find that countywide median home value, climatic variables, and several parcel-level soil type variables contribute substantially to predictive power. Enlarging the set of predictors and the geographical scale of modeling improves accuracy by approximately 15 percent and, relative to a more restricted modeling benchmark adapted from Nolte (2020), extends coverage into 376 counties occupying 1.35 million km2. To assess the practical benefits of our modeling approach, we simulate the protection of 30 percent of US lands via government purchasing, modeled after the Biden administration's "30x30" initiative. Using our proposed modeling strategy, the purchasing agency saves approximately $15 million per year, or 4 percent of the USDA's annual land easement budget., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Gold et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Soy is the main product of Brazilian agriculture and the fourth most cultivated bean globally. Since soy cultivation tends to increase and due to this large market, the guarantee of product quality is an indispensable factor for enterprises to stay competitive. Industries perform vigor tests to acquire information and evaluate the quality of soy planting. The tetrazolium test, for example, provides information about moisture damage, bedbugs, or mechanical damage. However, the verification of the damage reason and its severity are done by an analyst, one by one. Since this is massive and exhausting work, it is susceptible to mistakes. Proposals involving different supervised learning approaches, including active learning strategies, have already been used, and have brought significant results. Therefore, this paper analyzes the performance of non-supervised techniques for classifying soybeans. An extensive experimental evaluation was performed, considering (9) different clustering algorithms (partitional, hierarchical, and density-based) applied to 5 image datasets of soybean seeds submitted to the tetrazolium test, including different damages and/or their levels. To describe those images, we considered 18 extractors of traditional features. We also considered four metrics (accuracy, FOWLKES, DAVIES, and CALINSKI) and two-dimensionality reduction techniques (principal component analysis and t-distributed stochastic neighbor embedding) for validation. Results show that this paper presents essential contributions since it makes it possible to identify descriptors and clustering algorithms that shall be used as preprocessing in other learning processes, accelerating and improving the classification process of key agricultural problems., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 de Oliveira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Abiotic stressors impair crop yields and growth potential. Despite recent developments, no comprehensive literature review on crop abiotic stress assessment employing deep learning exists. Unlike conventional approaches, deep learning-based computer vision techniques can be employed in farming to offer a non-evasive and practical alternative., Methods: We conducted a systematic review using the revised Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to assemble the articles on the specified topic. We confined our scope to deep learning-related journal articles that focused on classifying crop abiotic stresses. To understand the current state, we evaluated articles published in the preceding ten years, beginning in 2012 and ending on December 18, 2022., Results: After the screening, risk of bias, and certainty assessment using the PRISMA checklist, our systematic search yielded 14 publications. We presented the selected papers through in-depth discussion and analysis, highlighting current trends., Conclusion: Even though research on the domain is scarce, we encountered 11 abiotic stressors across 7 crops. Pre-trained networks dominate the field, yet many architectures remain unexplored. We found several research gaps that future efforts may fill., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Orka et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Based on the current state of China's agricultural industry, this article proposes an integrated framework for the agricultural innovation ecosystem in developing countries. Furthermore, a dynamic simulation model is constructed to analyze the game process and factors influencing the agricultural innovation ecosystem. The results indicate that industry-university-research collaboration serves as the main source of innovation within the agricultural innovation ecosystem, playing a central role in its development. The willingness to participate, cost of participation, and establishment of default fees by governments, agro-related enterprises, universities, and research institutions have significant implications for the evolution of collaborative innovation within agricultural innovation ecosystems. In order to promote the evolution of the system, agriculture-related enterprises, universities, and research institutions should establish more effective reward and punishment mechanisms, as well as cost control mechanisms. Governments should set reasonable regulatory costs and incentive intervals to actively foster a collaborative innovation atmosphere. The innovation points of this paper are as follows: extending the theory of innovation ecosystems to agriculture, particularly in developing countries characterized by imbalanced and insufficient development. A game model is also constructed to represent the collaborative innovation evolution among government, agriculture-related enterprises, universities, and research institutions, with the government as the endogenous variable. Through numerical simulation, the dynamic evolution process of collaborative innovation within the agricultural innovation ecosystem is revealed. This research enriches and expands upon innovation ecosystem theory, providing guidance for the of innovation ecology in agriculture through mathematical models in developing countries. This, in turn, promotes the convergence of symbiotic, shared, and-creation development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Hou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Farmers' entrepreneurship is an important engine to comprehensively help promote rural revitalization. Based on data from the China Household Finance Survey (CHFS2019), this paper empirically examines the effect of digital literacy on farmers' entrepreneurial behavior using the Probit model and instrumental variable method; and examines the mediating role of health status in this effect using the mediation effect model, combined with the Sobel and Bootstrap tests. The results of the study showed that (1) digital literacy positively influenced farmers' entrepreneurial behavior at the 1% significant level, and this positive influence showed some differences across gender and age; (2) health status played a mediating effect in the positive influence of digital literacy on farmers' entrepreneurial behavior. Accordingly, policy recommendations are made to foster farmers' digital literacy, encourage farmers' entrepreneurship, and ensure farmers' "digital health" services., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Bai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Plant protection drones are fast and efficient application machines that are characterised by high application efficiency and no damage to crops. They are particularly suitable for small areas of farmland and mountainous terrain in regions such as Asia and are currently the dominant insecticide application technology in China. The presence of wind is a prerequisite for the spread and dissemination of airborne diseases and it can directly influence the distance and height of ascent of pathogenic spores. This paper investigates the effect of downwash airflow generated by the flight altitude of a plant protection drone on the horizontal distribution, vertical distribution and ground distribution of powdery mildew spores in wheat. Monitoring the changing dynamics of airborne powdery mildew conidia using spore traps. The test results show that: the number of powdery mildew pathogenic spores is related to various factors such as weather, relative humidity and wind speed; the release of spores is greatly influenced by airflow disturbances but has little effect at the early stages of sporulation; the disease is caused by the accumulation process of pathogenic spores and in the control of powdery mildew in wheat, preventive spraying should be carried out within 2–3 days of the germination of pathogenic spores. The study lays the foundation for further in-depth research on the spread of powdery mildew spores and improved pest control, and provides a basis for scientific and rational spraying and control by agricultural drones. [ABSTRACT FROM AUTHOR]

In Tunisia, agriculture is the main source of livelihood for more than 75% of small and subsistence farmers with minimal use of technology. The use of information and communication technology (ICT),such as mobile applications, represents a pertinent opportunity for these smallholders to access agricultural innovation and market information and improve their farming technologies and farm management. Thus, ICT can act as a replacement to foster access to innovation for this category of farmers. Unfortunately, the underuse of mobile applications has contributed to low and slow adoption of agricultural innovation and consequently the benefits of this technology have not been attained. The purpose of this study is to identify the factors affecting the adoption of Short Message Service (SMS) through a contextual ICT model for livestock, olive crop, and beekeeping. Data were collected from 200 small-scale beekeepers, 225 olive growers, and 140 livestock breeders selected in Jendouba, Kairouan, and Zaghouan in Tunisia. The objective of this paper is to examine the factors that influence mobile applications using the partial least squares structural equation modelling technique, for livestock, olive crop, and beekeeping agricultural activities. The results showed that the final ICT-induced structural models were highly predictive of the use of SMS and its increased adoption. Factors affecting the use of SMS differed according to the farming system. The major perceived factor affecting the use of SMS was 'observability' for livestock farmers, 'compatibility' for olive growers, and 'information quality' for beekeepers. Understanding these factors by taking into account the specificity of the agricultural activity leads to a better understanding of the adoption of ICT tools by smallholder farmers in Tunisia. [ABSTRACT FROM AUTHOR]

The integration of rural industries will inevitably lead to new business forms and new models, which put forward new requirements for traditional agricultural finance. The development of digital inclusive finance will provide new momentum for the integration of rural industries. Based on the provincial panel data from 2011 to 2020, the evaluation index system is constructed from three dimensions: industrial integration method, integration subject and integration format, and the development index of rural industrial integration is calculated. This paper establishes double fixed effect model and intermediary effect model to test the effect and path of digital inclusive finance on the integration of rural industries, and further explores the regulatory role and spatial difference of financial support. The results show that: (1) The integration of rural industries shows a growing trend, the eastern region develops more rapidly, while the central and western regions develop more slowly; (2) The digital inclusive finance can promote the integration of rural industries, digitization degree is remarkable, but coverage breadth and using depth are not significant, increasing the rate of per capita electricity consumption and urbanization can promote the integration of rural industries, consumption has limited pulling effect on the integration of rural industries, the per capita investment in fixed assets has no significant effects on the integration of rural industries; (3) The financial availability and the agricultural digitization play a complete intermediary effect; (4) Financial support has a negative moderating effect on the relationship between the two; (5) The eastern and central regions have a significant promoting effect, while the western region has a negative effect. [ABSTRACT FROM AUTHOR]

China's agricultural economy is developing rapidly, but the unbalanced regional development is still a key issue that needs to be discussed today. By studying the total factor productivity of green agriculture and its factors, this paper analyzes the regional differences in time and space changes between the eastern, central and western parts of China. In this paper, the total factor productivity of green agriculture is calculated and decomposed by Metafrontier Malmquist-Luenberger index based on directional distance function. The results are as follows: First, the total factor productivity level of green agriculture in China is increasing year by year, but the overall level is still at a low level and has greater volatility; Second, although the total factor productivity of green agriculture shows an upward trend, the three regions show a downward trend in turn, which has great differences; Third, there are obvious differences in technological efficiency, optimal production potential and technological gap between the eastern, central and western regions, and there are great differences in productivity among regions and provinces. Based on the results, this paper puts forward policy recommendations, according to the regional heterogeneity, from a number of angles to rely on the joint efforts of many parties to improve the level of total factor productivity of green agriculture. [ABSTRACT FROM AUTHOR]

H-index is the most commonly applied tool to evaluate scientific productivity. In this study, the use of the H-index to evaluate scientific production in swine veterinary medicine was explored. A database of 137 pig infectious agents was constructed, including its taxonomic division, zoonotic potential, status as emerging pathogen and whether it was OIE-listed. The H-index and the total number of citations were calculated for those pathogens, the location of the affiliation of the first author of each paper included in the H-index core was registered and, for the ten pathogens with the highest H-index, evolution over time was measured. H-index values were compared to the M quotient, A-index, G-index, HG-index and the G/H ratio. H-indices were found to be severely affected by search accuracy and the database was hand curated. Swine pathogen H-indexes were highly dispersed ranging from 0 to 106 and were generally higher for pathogens causing endemic diseases in large pig producing countries. Indeed, the three top pathogens were Escherichia coli, Porcine reproductive and respiratory syndrome virus and Porcine circovirus type 2 with H-indices 106, 95 and 85, respectively. H-indices of viruses and bacteria were significantly higher (P<0.001) than other pathogen types. Also, non-zoonotic pathogens had higher H-indices than zoonotic pathogens (p<0.009) while no differences could be found for being listed by the OIE. For emerging diseases, only non-emerging viruses had higher H-index (p = 0.02). The study of H-indexes over time revealed three general patterns and that they had increased mainly after the 1980’s. As expected, there were strong geographic patterns in terms of authorship and North America (38%) and Europe (46%) coped the majority of the papers. Finally, in order to quantify the contribution of a subject to a specific field, a new index “Deciphering Citations Organized by Subject” (Dcos) is proposed. [ABSTRACT FROM AUTHOR]

Drought is a complex natural hazard that occurs when a region experiences a prolonged period of dry conditions, leading to water scarcity and negative impacts on the environment. This study analyzed the recurrence of drought and wet spells in Baluchistan province, Pakistan. Reconnaissance Drought Index (RDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Vegetation Condition Index (VCI) were used to analyze droughts in Baluchistan during 1986–2021. Statistical analysis i.e. run theory, linear regression, and correlation coefficient were used to quantify the trend and relationship between meteorological (RDI, SPEI) and agricultural (VCI) droughts. The meteorological drought indices (1, 3, 6, and 12-month RDI and SPEI) identified severe to extreme drought spells during 1986, 1988, 1998, 2000–2002, 2004, 2006, 2010, 2018–2019, and 2021 in most meteorological stations (met-stations). The Lasbella met-station experienced the most frequent extreme to severe droughts according to both the 12-month RDI (8.82%) and SPEI (15.38%) indices. The Dalbandin met-station (8.34%) follows closely behind for RDI, while Khuzdar (5.88%) comes in second for the 12-month SPEI. VCI data showed that Baluchistan experienced severe to extreme drought in 2000, 2001, 2006, and 2010. The most severe drought occurred in 2000 and 2001, affecting 69% of the study region. A positive correlation was indicated between meteorological (RDI, SPEI) and agricultural drought index (VCI). The multivariate indices can provide valuable knowledge about drought episodes and preparedness to mitigate drought impacts. [ABSTRACT FROM AUTHOR]

The key trend for future agricultural growth is efficient, green and sustainable high-quality development, and it is crucial to sort out the factors influencing high-quality agricultural development., Objectives: The purpose of this study is to dissect whether environmental regulation has a catalytic effect on quality rural development, through which paths it is driven and whether there is a threshold effect to be further clarified., Method: In this study, the panel data of 34 provinces in China from 2012 to 2018 are used, and 17 variables are used to construct an evaluation index system, covering four dimensions: agricultural endowment, agricultural output level, agricultural green degree and social sustainability. The high-quality development of agriculture is measured by entropy method. And further, using a baseline regression model and a mediating effects model, we empirically investigated the impact of environmental regulation on high-quality agricultural development and its mechanism of action, and empirically assessed the nonlinear effects of environmental regulation using a threshold regression model., Results: Environmental control, as noted in the study, considerably assists in the establishment of high-quality agriculture; at the same time, large-scale land management plays a role in mitigating the influence of both. There is a single income threshold impact on rural households between high-quality agricultural growth and environmental regulation, and once that threshold is reached, the influence of high-quality agricultural growth grows. Contribution: According to the research findings, recommendations are made for the design of scientific environmental regulation policies, the establishment of a sound service system for large-scale rural land management, and the establishment of a stable mechanism for rural residents to sustain their income, in order to strengthen the effect of environmental regulation and realize high-quality agricultural growth in China. The marginal contribution of this paper is to enrich the study of the relationship between environmental regulation and high-quality agricultural development, which has theoretical and practical implications for promoting sustainable agricultural development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Leng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Trajectory tracking is one of the key technologies for tractor automatic navigation. Its main purpose is to adjust the steering mechanism of the tractor to follow the planned trajectory. Thus, in this paper a trajectory tracking control system is designed for an agricultural tractor with the electric power steering mechanism. A DC brush motor is added on the steering column of the tractor and the hardware circuits for the steering controller are designed to control the front wheel angel. The three degrees of freedom model of the tractor is established, and a trajectory tracking control system is proposed including a fuzzy sliding mode controller and a steering angle tracking controller designed according to the internal mode control and minimized sensitivity theory. The effectiveness of the designed trajectory tracking control system is demonstrated by simulation analyses in reference to the planed trajectory., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Bao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The power harnessed by cattle traction was undeniably a valuable asset to Neolithic communities. However, data are still lacking on the timing, purposes, and intensity of exploitation of draught animals. This paper sheds new light on a region of Europe-Neolithic Ireland-for which our knowledge is particularly restricted as evidence from both Ireland and Britain in this period has been so far patchy and inconclusive. Using a suite of methods and refined criteria for traction identification, we present new and robust data on a large faunal assemblage from Kilshane, Co. Dublin that strongly support cattle traction in the middle 4th millennium BC in Ireland. Bone pathology data combined with osteometric analysis highlight specialised husbandry practices, producing large males, possibly oxen, for the purpose of cattle traction. This new technology has important implications for early agriculture in the region since it provides a key support for more extensive land management practices as well as for megalithic construction, which increased considerably in scale during this period. We argue that access to draught animals and the exploitation of associated resources were at the heart of wider changes that took place in Neolithic Ireland in the second half of the 4th millennium BC., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Pigière, Smyth. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Traffic congestion in freeway network is a prevalent transportation problem and leads to a strong degradation of freeway network facilities. This paper proposes a new coordinated optimization approach for freeway network, aiming to relieve the traffic congestion in freeway network equipped with the coordinated traffic controllers. The challenge is how to solve the problem between the traffic control goals of each path and those of the network. In this paper, the bi-level programming theory is used to address this problem. More exactly, in the path level, the optimal control model is designed to relieve congestion in each path of the test network. Furthermore, in the network level, the optimal model considers the traffic equilibrium and cost optimization. The efficiency of the proposed approach is tested on a well-known traffic network calibrated by the field test data of freeway network. The results show that the proposed approach has positive effects in balancing traffic load and improving the service level of freeway networks. [ABSTRACT FROM AUTHOR]

Land use change (LUC) is a main cause of global environmental change, and is an important activity to be studied. Our research aims to examine the current state of evidence on the link between LUC and human health in the Amazon region. We conducted a scoping review of literature in two research databases, resulting in 14 papers for analysis. Our analysis demonstrated a lack of clear definitions for LUC, a wide variety of negative health effects from LUC, the lack of qualitative articles, a lack of studies exploring the potential positive health effects of LUC, and the predominance of studies coming from the Brazilian Amazon. Our study validated the prevailing idea that LUC can lead to negative health consequences, if not managed properly. [ABSTRACT FROM AUTHOR]

The electric tractor has the advantages of zero-emission, high efficiency, and low noise, which is the direction of future development and transformation of agricultural power machinery. Aim at the problem that the simulation methods commonly used in the development of electric tractor drive system are poorly generalized and cannot meet the simulation needs of complex multi-domain physical systems. This paper proposes a modeling method for an electric tractor drive system, takes the YTO-500 tractor as the research object, designs and calculates the overall scheme and parameters of its drive system, divides the drive system into modules, establishes the energy system, motor system and mechanical parts model based on Modelica, and integrates the simulation model of electric tractor drive system on this basis. The traction performance and transportation working conditions were simulated and tested. With compared and analyzed, in the traction characteristics, the simulation and test results of maximum speed, maximum traction force, and maximum traction power of each gear are consistent; within 400s transportation simulation conditions, the speed range of electric tractor is 13~28km·h-1, which is consistent with the speed range of electric tractor transportation gear. The results show that the simulation and the test results are consistent, which verifies the credibility of the simulation and the correctness of the model built, providing a basis for future research and development of agricultural machinery., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Mao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Most European hunter-gatherers slowly assimilated into farming communities during the Neolithic period. In the north these groups persisted far longer. In this paper, we present evidence from what may be one of the most recent non-agricultural sites in the region, where a marine hunter-gatherer lifestyle may have continued until as late as the 15th-16th centuries AD. The isotope composition of incremental dental analysis suggests a significant, long-term dependence on seals. This indicates that vestiges of this means of subsistence might have been present in Europe for much longer than previously thought., Competing Interests: The authors have declared that no competing interests exist, (Copyright: © 2022 Lahtinen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The present contribution focuses on investigating the interaction of people and environment in small-scale farming societies. Our study is centred on the particular way settlement location constraints economic strategy when technology is limited, and social division of work is not fully developed. Our intention is to investigate prehistoric socioeconomic organisation when farming began in the Old World along the Levant shores of Iberian Peninsula, the Neolithic phenomenon. We approach this subject extracting relevant information from a big set of ethnographic and ethnoarchaeological cases using Machine Learning methods. This paper explores the use of Bayesian networks as explanatory models of the independent variables-the environment- and dependent variables-social decisions-, and also as predictive models. The study highlights how subsistence strategies are modified by ecological and topographical variables of the settlement location and their relationship with social organisation. It also establishes the role of Bayesian networks as a suitable supervised Machine Learning methodology for investigating socio-ecological systems, introducing their use to build useful data-driven models to address relevant archaeological and anthropological questions., Competing Interests: The authors have declared that no competing interests exist.

Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting the possibility of an accurate diagnosis. This paper proposes an innovative method for identifying and classifying infected brinjal leaves using Deep Convolutional Neural Networks (DCNN) and Radial Basis Feed Forward Neural Networks (RBFNN). We collected 1100 images of brinjal leaf disease that were caused by five different species (Pseudomonas solanacearum, Cercospora solani, Alternaria melongenea, Pythium aphanidermatum, and Tobacco Mosaic Virus) and 400 images of healthy leaves from India's agricultural form. First, the original plant leaf is preprocessed by a Gaussian filter to reduce the noise and improve the quality of the image through image enhancement. A segmentation method based on expectation and maximization (EM) is then utilized to segment the leaf's-diseased regions. Next, the discrete Shearlet transform is used to extract the main features of the images such as texture, color, and structure, which are then merged to produce vectors. Lastly, DCNN and RBFNN are used to classify brinjal leaves based on their disease types. The DCNN achieved a mean accuracy of 93.30% (with fusion) and 76.70% (without fusion) compared to the RBFNN (82%—without fusion, 87%—with fusion) in classifying leaf diseases. [ABSTRACT FROM AUTHOR]

This paper aims to examine the key determinants and efficiency of China's agricultural exports with its 114 importing countries by applying the Stochastic Frontier Analysis (SFA) on an augmented gravity model for the period of 2000-2019. The Poisson Pseudo Maximum Likelihood (PPML) and the fixed effect models were also estimated simultaneously to confirm the robustness of our findings. The results reveal that China's economic size (GDP) and its importing countries, the Belt and Road Initiative (BRI), common border, and the Chinese language positively determine China's agricultural export flows. The results, on the other hand, also reveal that China's agricultural export is adversely influenced by the income (per capita GDP) of China and its trade partners, currency depreciation, distance, and landlocked. On an average account, China has untapped the potential of 51% in its agriculture export with the countries used in this study. We provide policy suggestions as part of our study., Competing Interests: The authors have declared that no competing interests exist.

Annual monitoring of the spatial distribution of cultivated land is important for maintaining the ecological environment, achieving a status quo of land resource management, and guaranteeing agricultural production. With the gradual development of remote sensing technology, it has become a common practice to obtain cultivated land boundary information on a large scale with the help of satellite Earth observation images. Traditional land use classification methods are affected by multiple types of land cover, which leads to a decrease in the accuracy of cultivated land mapping. In contrast, although the current advanced methods (such as deep learning) can obtain more accurate cultivated land mapping results than traditional methods, such methods often require the use of a massive amount of training samples, large computing power, and highly complex model tuning processes, increasing the cost of mapping and requiring the involvement of more professionals. This has hindered the promotion of related methods in mapping institutions. This paper proposes a method based on time series vector features (MTVF), which uses vector thinking to establish the features. The advantage of this method is that the introduction of vector features enlarges the differences between the different land cover types, which overcomes the loss of mapping accuracy caused by the influences of the spectra of different ground objects and ensures the calculation efficiency. Moreover, the MTVF uses a traditional method (random forest) as the classification core, which makes the MTVF less demanding than advanced methods in terms of the number of training samples. Sentinel-2 satellite images were used to carry out cultivated land mapping for 2020 in northern Henan Province, China. The results show that the MTVF has the potential to accurately identify cultivated land. Furthermore, the overall accuracy, producer accuracy, and user accuracy of the overall study area and four sub-study areas were all greater than 90%. In addition, the cultivated land mapping accuracy of the MTVF is significantly better than that of the maximum likelihood, support vector machine, and artificial neural network methods., Competing Interests: The authors have declared that no competing interests exist.

Background: In the wake of the severe impact of COVID-19 on the food security of the vulnerable groups in rural areas, the issue of how to achieve the Sustainable Development Goals 2 aims to "Zero Hunger" (SDG 2) and ensure the food safety of farmers has drawn unprecedented attention. Nutritional intake is generally used as an important indicator to reflect family food security. Under the background that Chinese farmers have gradually changed from the traditional diversified production mode to the specialized production of crops, the main purpose of this article is to explore what are the impact of crop specialization on farmers' nutritional intake? Could the specialization of crop production be taken as an important measure to ensure the food safety of farmers and achieve the SDG 2?, Methods: Based on the micro-survey data from 866 farmer households in China, this paper using Seemingly Unrelated Regressions model, Group Regression model and Mediating Effect model to analyze the average and heterogeneous effects of crop specialization on the nutritional intake of farmers, as well as the mediating effect of income. In addition, robustness test and endogenous treatment were performed by using alternative explanatory variables and IV-2SLS method was used to estimate the results., Results: After correcting for endogenous bias, crop specialization had a significant negative impact on energy intake and fat intake of farmers at the statistical level of 5% and 1% respectively, especially for farmers in mountainous areas. Household income played a mediating effect on the effect of crop specialization on farmers' energy and fat intake, and the proportion of the masking effect was 8.43% and 8.96% respectively. In addition, household financial capital and social capital have a significant positive impact on farmers' nutritional intake., Conclusions: Crop specialization cannot guarantee the food safety of farmers in terms of nutritional intake. However, when the development trend of crop specialization is irreversible, more attention should be paid to improving the level of various livelihood capital of farmers, especially those in mountainous areas, and to continuously increasing their income to ease and ultimately eliminate the negative impact of crop specialization on farmers' nutritional intake, which finally make everyone realize the SDG 2., Competing Interests: The authors have declared that no ompeting interests exist.

Fruit-picking robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology, people are demanding higher picking efficiency from fruit-picking robots. And a good fruit-picking path determines the efficiency of fruit-picking. Currently, most picking path planning is a point-to-point approach, which means that the path needs to be re-planned after each completed path planning. If the picking path planning method of the fruit-picking robot is changed from a point-to-point approach to a continuous picking method, it will significantly improve its picking efficiency. The optimal sequential ant colony optimization algorithm(OSACO) is proposed for the path planning problem of continuous fruit-picking. The algorithm adopts a new pheromone update method. It introduces a reward and punishment mechanism and a pheromone volatility factor adaptive adjustment mechanism to ensure the global search capability of the algorithm, while solving the premature and local convergence problems in the solution process. And the multi-variable bit adaptive genetic algorithm is used to optimize its initial parameters so that the parameter selection does not depend on empirical and the combination of parameters can be intelligently adjusted according to different scales, thus bringing out the best performance of the ant colony algorithm. The results show that OSACO algorithms have better global search capability, higher quality of convergence to the optimal solution, shorter generated path lengths, and greater robustness than other variants of the ant colony algorithm. [ABSTRACT FROM AUTHOR]

Effective prevention and control of agricultural non-point source pollution is a major challenge faced by the Chinese local government in the context of rural revitalization, and clarifying the game relationship between stakeholders in agricultural non-point source pollution control actions will help achieve multiple co-governance better. Accordingly, this paper discusses the interactive decision-making relationships between local government and livestock and poultry breeding enterprise (LPBE) under the participation of Environmental non-government organizations (ENGOs) and public, by constructing an evolutionary game model, as well as analyzing evolutionary cooperative stability strategies and realizing the simulation of evolution processes in different scenarios by MATLAB. The results show that government subsidy has an incentive effect on LPBE to adopt the purifying strategy, yet reduces the enthusiasm of local government for supervision. Improving the participation degree and right space of ENGOs is conducive to the realization of multiple co-governance models. Furthermore, the impact of public participation on multiple co-governance of agricultural non-point source pollution is related to the local government's investigation rate and the public reporting fairness; strengthening the local government's supervision capacity and improving the public reporting fairness can achieve better collaborative governance effects. [ABSTRACT FROM AUTHOR]

Seed moisture content (SMC) is an important attribute to seed quality. Maintaining seed dryness throughout supply chain (The Dry Chain) prevents seed germination and quality losses. Ambient relative humidity (RH) and temperature affect seed moisture and thereof seed moisture isotherm. Present study was conducted to compare the moisture adsorption isotherms of wheat, maize, cotton and quinoa seeds packed in hermetic Super Bag and traditional packaging materials including paper, polypropylene (PP), jute and cloth bags. Seeds were incubated at 60, 70, 80 and 90% static RH. Nearly straight line moisture isotherms for all crop seeds were obtained in Super Bag. Seed moisture contents increased in traditional packaging materials with increasing RH. At higher level of RH, moisture contents increased slightly (1–2%) in Super Bag, whereas this increase was much higher in traditional packaging materials (≈9% higher than original SMC at 90% RH). In second study, seeds were dried to 8 and 14% initial seed moisture contents using zeolite drying beads and were stored in hermetic and conventional packaging materials for a period of 18 months. For all crop seeds, germination was severely affected in all packaging materials both at 8 and 14% initial SMC except storage in Super Bag at 8% SMC. Wheat seed stored in Super Bag at 8% SMC almost maintained initial germination while germination of cotton, maize and quinoa seeds declined 7%, 14% and 30% respectively in Super Bag at 8% SMC. Seed storage in Super Bag can help to prevent the significant increase in seed moisture at higher RH as is evident from moisture isotherm study, thus helps to preserve quality of maize, wheat, cotton and quinoa seeds by maintaining The Dry Chain throughout the storage period. [ABSTRACT FROM AUTHOR]

A diversity of arthropods (myrmecophiles) thrives within ant nests, many of them unmolested though some, such as the specialized Eucharitidae parasitoids, may cause direct damage to their hosts. Ants are known to discriminate between nestmates and non-nestmates, but whether they recognize the strength of a threat and their capacity to adjust their behavior accordingly have not been fully explored. We aimed to determine whether Ectatomma tuberculatum ants exhibited specific behavioral responses to potential or actual intruders posing different threats to the host colony and to contribute to an understanding of complex ant-eucharitid interactions. Behavioral responses differed significantly according to intruder type. Ants evicted intruders that represented a threat to the colony’s health (dead ants) or were not suitable as prey items (filter paper, eucharitid parasitoid wasps, non myrmecophilous adult weevils), but killed potential prey (weevil larvae, termites). The timing of detection was in accordance with the nature and size of the intruder: corpses (a potential source of contamination) were detected faster than any other intruder and transported to the refuse piles within 15 min. The structure and complexity of behavioral sequences differed among those intruders that were discarded. Workers not only recognized and discriminated between several distinct intruders but also adjusted their behavior to the type of intruder encountered. Our results confirm the previously documented recognition capabilities of E. tuberculatum workers and reveal a very fine-tuned intruder discrimination response. Colony-level prophylactic and hygienic behavioral responses through effective removal of inedible intruders appears to be the most general and flexible form of defense in ants against a diverse array of intruders. However, this generalized response to both potentially lethal and harmless intruders might have driven the evolution of ant-eucharitid interactions, opening a window for parasitoid attack and allowing adult parasitoid wasps to quickly leave the natal nest unharmed. [ABSTRACT FROM AUTHOR]

Contract farming is a growing practice in agricultural economy. A well-designed crop-planting and buyout contract, offered by an enterprise, to a fraction of contract farmers brings benefit to farmers as well as to the enterprise itself. However, in the process of contract fulfillment, farmers possess private information about the degree of effort on fulfilling the contract of themselves. Thus, the more informed farmers may not work hard in the process of planting crops. This opportunistic behavior of farmers caused by asymmetric information has seriously affected the sustainability of contract farming. An enterprise with reciprocity preference tends to make a contract both improves farmers' welfare and brings enough profit to sustain its own operations, while a farmer with reciprocity will work hard in return for the enterprise's reward. In this paper, we develop a non-profit index principal-agent model between enterprises and farmers, assuming both have reciprocity preference, to investigate how to design an incentive mechanism in contract farming. We begin our analysis by establishing a non-profit index evaluation system to evaluate farmers' effort degree in contract fulfillment. Then we solve principal-agent problem with the assumption that farmers' expected certainty income premium (ECIP) is constant. We find that in the perfect Bayesian equilibrium, farmers with higher degree of reciprocity preference require less ECIP, and will improve efforts to complete contract tasks, even actively sacrifice their own interests to repay extra rewards from enterprises. Furthermore, we explore our model to the scenario in which farmers' ECIP is a function of enterprise payment difference (EPD). We find that the higher the degree of reciprocity preference of farmers, the greater the probability of enterprises to increase income. Numerical simulations are conducted to verify the validity of the conclusions. Our study shows that the reciprocity preference behavior of enterprises and farmers improves the fulfillment rate of contract farming, which contributes to the realization of the incentive mechanism of contract farming., Competing Interests: The authors have declared that no competing interests exist.

In order to explore the sustainable growth of Chinese agriculture, this paper assesses how the heterogeneous SPS measures affect China's growth margins and quality upgrading in the agricultural sector. We estimate improved gravity-model that exploit the cross-country differences in SPS measures over the period from 2000 to 2014. Our findings show that the heterogeneous SPS measures restrict the intensive margin and extensive margin, but significantly promote the product quality-even with no significant effect on price index. Conditional on quality upgrading, the heterogeneous SPS measures decrease the extent of quality upgrading. On one hand, because of cross-country differences in SPS standards, standards from developed countries have less effective trade effect on China's agri-products export quality upgrading; On the other hand, because of cross-firm differences in the ability to deal with SPS standards, the laggards in China have the higher probability to switch to lower entrance barrier countries. Therefore, it is possible for China to trap in the low-quality agricultural growth in the long term., Competing Interests: The authors declare no conflict of interest.

A review with meta-analysis of outflow and nitrate loss reduction in controlled drainage (CD) vs conventional, free drainage (FD) was carried out in the study. Since the results of experimental field studies usually cover short periods of data collection, hence in this paper, meta-analyses were based on model studies that usually cover a longer time range. The databases Web of Science and Scopus were searched for eligible English articles, published until December 2020, that describe the quantity and quality of drainage water. The meta-analysis of outflow and nitrate loss reduction in CD vs FD using the mean difference (MD) with a confidence interval (CI) of 95%. The influence of each study was measured through heterogeneity, sensitivity analyses and publication bias using STATISTICA (version 13.3) for all analyses. Of the 107 works identified, 18 were finally included in the analysis based on established criteria required for an appropriate meta-analysis. In general the results indicate a reduction in average drainage outflow of 30.5% (MD = -71.26 mm; 95% CI, -103.49 --39.04; p = 0.000) in arable land with CD in comparison to FD practice. In the case of nitrate load the reduction was 33.61% and in the drainage water there was lower content in CD practice by an average of 8.36 kg NO3 ha-1year-1 (95% CI, -9.93 --6.79; p = 0.000). Subgroup analysis of two meta-analyses indicates that the results concerning these associations may vary with the calculated weight for each article, in which the number of years of study had the most significant impact., Competing Interests: The authors have declared that no competing interests exist.