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Starting in 2006, China launched a project to carry out Basic Farmland Construction in 116 representative counties. The objective of this project was to enhance agricultural productivity. China invested 30 billion yuan in this project from 2006 to 2013. Using a difference‐in‐differences approach, this study estimates that Basic Farmland Construction increased per capita agricultural output by 6.3%, crop sown area by 5%, and agricultural mechanization by 7.3%. The total benefits of the project far exceeded the total investments. By incorporating with rainfall shocks, this study finds that the project could mitigate most of the damage from droughts and floods. [ABSTRACT FROM AUTHOR]

This paper establishes a high-fidelity and efficient Computational Fluid Dynamics (CFD) numerical method (AL-LDS-nnew) for wind turbine wake by combining the actuator line (AL), the localized dynamic Smagorinsky (LDS) sub-grid scale (SGS), and the new generation nnew vortex identification method under the framework of large eddy simulation. The model advantages are encouraging: 1) In terms of turbine modeling, the AL model is adopted to replace the traditional threedimensional solid model, which avoids solving the boundary layer on the blade surface and improves computational efficiency; 2) In terms of wake simulation, the LDS SGS model is used to model turbulence, reducing vortex dissipation and further improving the refinement of turbine wake; 3) In terms of vortex identification, the new generation nnew vortex identification method avoids the difficult threshold selection in previous vortex identification and captures more refined vortex structures. The accuracy of the model is validated against published data of a NREL 5 MW wind turbine, and then extended to simulate the wake interference of tandem twin-rotor turbines by changing the pitch angle of the upstream wind turbine (WT1). The influence mechanisms between array wake interference and energy conversion efficiency under the pitch strategy are explored, demonstrating the AL-LDS-finew coupling method is computationally accurate and efficient for simulating the complex wake interference. From analyses, the pitch strategy can effectively suppress the wake effect of the upstream turbine (WT1) and increase the power output of the downstream turbine (WT2), thus improving the overall output power of the array farm. Compared with the non-pitch condition (0 pitch angle), a pitch angle of (2°) maximizes the global energy conversion efficiency of the twin-rotor array: power augmentation by 0.29%, and thrust reduction by 5%. This optimal state reduces the fatigue load of the turbine and is more conducive to long-term operation. The findings, whilst preliminary, encourage the use of turbine pitch strategies in the wind farm planning and operation. [ABSTRACT FROM AUTHOR]

Fertilizer application has been one of the most important facilities to advance agricultural mechanization. Particularly, manual fertilization cannot fully meet the large-scale production in recent years. In this article, a chain reversal trenching and application device was presented for the organic fertilizer in orchards, in order to enhance the trenching depth and uniform fertilization. A reverse-chain trenching mechanism was employed with a fixed trenching blade that moved in the opposite direction of the chain. The soil cutting and simultaneous backfilling were allowed within the trench, as the device progressed. A trenching depth of up to 600mm was achieved in the chain trenching mechanisms. The separate backfilling was reduced to leave no visible trenches on the surface after completion. This design was also a streamlined operation. The mathematical analysis of the trenching blade was conducted to establish a mathematical model using Cartesian coordinate transformations. The relationship equation was derived for the cutting angle. Optimal angle parameters were also provided. According to the trenching depth analysis, the hydraulic adjustment cylinders were selected for the trenching device. A scrapertype fertilizer application mechanism was adopted to develop the discrete element simulation models for both upright and sideways fertilizer application modes. The fertilizer distribution patterns were analyzed under the two modes. While both modes were similarly distributed fertilizer, and the forward-facing mode was more suitable for the operations with the larger fertilizer widths, while the sideward-facing mode was with the smaller fertilizer widths. In the two fertilizer application modes, the sideways application mode had better uniformity, especially at the lower forward speeds. Therefore, the application mode of sideward-facing fertilizer was selected to ensure that all organic fertilizer accurately fell into the trench. A single-factor experiment was carried out to explore the effects of scraper height, angle, and spacing on the normal contact force and coefficient of variation. All three parameters shared a significant impact on the coefficient of variation. In a coefficient of variation of less than 15%, the optimal height, angle, and spacing of the scraper were selected to minimize the normal contact force, resulting in values of 20 mm, 90°, and 180 mm, respectively. According to these optimal parameters of the scraper, the simulation was conducted to yield a coefficient of variation of 6.02% and a normal contact force of 9.03 N, both of which were lower than those before optimization. Subsequently, a physical prototype was fabricated and field-tested. An average coefficient of variation of 8.34% was obtained for fertilizer distribution, indicating better uniformity. Furthermore, the maximum and minimum fertilizer application tests showed that the quantities ranged from 0.8 to 6 kg/m, thus meeting the fertilization requirements of different plots. The trenching performance tests show that the average trenching depths of two operations were 616.0 and 624.4 mm, respectively, with stability coefficients of 93.57% and 92.58%, respectively, both exceeding 90%. The average trenching widths were 305.4 and 295.4 mm, respectively, with consistency coefficients of 96.16% and 95.04%, respectively, both exceeding 95%. Therefore, the device exhibited excellent performance in the fertilizer distribution and trenching operations, fully meeting the agronomic requirements. The findings can provide a new tool for the deep application of organic fertilizers in orchards, indicating the promising potential prospects. Innovative design and efficiency can also offer valuable insights into the agricultural fields. [ABSTRACT FROM AUTHOR]

Wake effect is a significant factor contributing to power loss in wind farms. Studies have shown that wake steering control can mitigate this power loss. Currently, wind farm wake control strategies primarily utilize fixed yaw control due to limitations in the accuracy and efficiency of dynamic wake models. However, fixed yaw control fails to fully exploit the power improvement potential of wake steering control. Therefore, in this study, we first propose a dynamic wake model for wind farms based on the physics-guided neural network (PGNN) approach. This model can predict the dynamic wake flow field within wind farms in real time using instantaneous inflow wind speed and turbine operational states. Then, by employing the PGNN dynamic wake model as the predictive model, a wind farm dynamic wake control strategy based on the model predictive control method is proposed. To quantify the advantages of the proposed control strategy, both fixed yaw control and dynamic yaw control are tested on a wind farm with a 3 × 2 layout. Results from large eddy simulations demonstrate that the proposed dynamic wake control strategy increases the power output of the wind farm by 11.51% compared to a 6.56% increase achieved with fixed yaw control. [ABSTRACT FROM AUTHOR]

Agriculture plays a crucial role in the economy of Burkina Faso and other sub-Saharan African countries. It provides food for the population and is the primary source of employment in rural areas. The government of Burkina Faso has implemented a 2018–2027 Agro-Sylvo-Pastoral production sector policy to improve agricultural productivity and reduce poverty. This study uses a dynamic computable general equilibrium model linked to a microsimulation model, which evaluates the impact of subsidizing investment in agricultural capital on production, income, and poverty under three different fiscal financing scenarios. The results indicate that the agricultural mechanization subsidy program effectively reduces poverty, but the extent of the reduction varies depending on the financing method used. Financing the subsidy by reducing nonproductive public expenditure further reduces poverty, especially in rural areas. However, it is essential to supplement the subsidy policy with an agricultural extension service program for the program to have long-lasting effects. [ABSTRACT FROM AUTHOR]

Maintaining agricultural machinery is crucial for efficient mechanized farming. Specifically, diagnosing faults in rolling bearings, which are essential rotating components, is of significant importance. Domain-adaptive technology often addresses the challenge of limited labeled data from a single source domain. However, information transfer can sometimes fall short in providing adequate relevant details for supporting target diagnosis tasks, leading to poor recognition performance. This paper introduces a novel fault diagnosis model based on a multi-source locally adaptive graph convolution network to diagnose rolling bearing faults in agricultural machinery. The model initially employs an overlapping sampling method to enhance sample data. Recognizing that two-dimensional time–frequency signals possess richer spatial characteristics in neural networks, wavelet transform is used to convert time series samples into time–frequency graph samples before feeding them into the feature network. This approach constructs a sample data pair from both source and target domains. Furthermore, a feature extraction network is developed by integrating the strengths of deep residual networks and graph convolutional networks, enabling the model to better learn invariant features across domains. The locally adaptive method aids the model in more effectively aligning features from the source and target domains. The model incorporates a Softmax layer as the bearing state classifier, which is set up after the graph convolutional network layer, and outputs bearing state recognition results upon reaching a set number of iterations. The proposed method's effectiveness was validated using a bearing dataset from Jiangnan University. For three different groups of bearing fault diagnosis tasks under varying working conditions, the proposed method achieved recognition accuracies above 99%, with an improvement of 0.30%-4.33% compared to single-source domain diagnosis models. Comparative results indicate that the proposed method can effectively identify bearing states even without target domain labels, showcasing its practical engineering application value. [ABSTRACT FROM AUTHOR]

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Determining how the economy and society interact with the environment of water quality is essential to determining the financial impact of green development. Based on China's provincial panel data from 2010 to 2021, this research considers non-agricultural sources of water pollution (NASWP) as a negative factor of production, investigates its influence on the urban-rural divide, and explains the mechanism of action. The empirical results show that there is a significant correlation between NASWP and the urban-rural gap, with a "U-shaped" relationship between the two. Water pollution first reduces and then increases the urban-rural income gap, and the results are robust after considering endogeneity. Mechanistic research demonstrates that NASWP cause a loss in food output, which in combination with changes in food prices and food subsidy programs impacts the incomes of rural dwellers, thereby having an influence on the urban-rural income gap. Using the threshold effect model, it is discovered that under the combined influence of agricultural mechanization and food subsidy policy, the relationship between NASWP and urban-rural income divide exhibits an U-shape in areas with high agricultural mechanization and an "inverted U" shape in areas with low agricultural mechanization. [ABSTRACT FROM AUTHOR]

Traditional small‐holder agricultural landscapes in southern China are being consolidated to increase mechanisation levels in agriculture, but it is unclear how this influences rice arthropod communities in these landscapes.Here, based on a six‐year study in 20 rice fields, we evaluated the impact of land consolidation on arthropod communities, crop damage, and rice yield. We also analysed how effects of land consolidation were moderated by the proportion of large semi‐natural habitat patches and insecticide use.We found that, compared to consolidated fields, rice fields in traditional farmlands had a higher abundance and family richness of natural enemies, but a similar abundance of rice pests. Land consolidation did not significantly interact with the proportion of large semi‐natural habitat patches or insecticide application, in terms of affecting arthropods. The proportion of semi‐natural habitat reduced the negative effect of insecticide application on key rice pests, but no equivalent interaction occurred for natural enemies.Synthesis and applications: Land consolidation can have negative impacts on the abundance and richness of natural enemies, but not pests in small‐holder rice systems, and these impacts are independent from insecticide application and proportion of semi‐natural habitat in the landscape. We recommend the implementation of agri‐environmental measures or re‐establishing field margin vegetation during the consolidation process to mitigate these potential negative effects, although trade‐off between enhancing crop yields and preserving rice arthropod biodiversity should be considered. We encourage future research to focus on the detailed assessment of the function of linear habitats for a better understanding of the impact of land consolidation. [ABSTRACT FROM AUTHOR]

With the increasing penetration of wind power into the grid, its intermittent and fluctuating characteristics pose a challenge to the frequency stability of grids. Energy storage systems (ESSs) are beginning to be used to assist wind farms (WFs) in providing frequency support due to their reliability and fast response performance. However, the current schemes mostly focused on the sole operation of either WT or ESSs for frequency support, lacking in economy and reliability. To address these issues, this work proposes a sliding mode consensus control (SMCC) method for ESSs to assist the frequency response of WTs. First, a coordination strategy for the WTs and ESS is proposed to reinforce the frequency support capability of a WT–ESS by determining the optimal capacity of ESSs. Meanwhile, a novel SMCC is proposed to achieve proportional power sharing among ESSs and increase the total power output of the entire WFs during wind energy shortages. Moreover, an event triggered communication mechanism is utilized to reduce the information exchanges among ESSs. Subsequently, a Lyapunov stability analysis is conducted to prove the stability and finite time consensus of the proposed method. Simulation case studies are conducted in IEEE 39-bus system to validate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Active yaw control (AYC) can effectively improve offshore wind farm power generation performance. This work aims to study the sensitivity of full wind conditions and different yaw offset threshold settings to active yaw control for wake redirection, power generation efficiency, and annual energy production at a large-scale wind farm in Hangzhou Bay in Zhejiang Province, China. The results demonstrated that the optimization of AYC largely depends on the wind direction, which determines the wake strength of the wind farm. In the medium-speed environment, AYC is not sensitive to the wind speed variation and a similar yaw angle can be implemented on the wind turbines in these conditions. Moreover, the performance of AYC under different yaw offset threshold settings is approximately the same at low and high wind speeds and the optimal yaw offset threshold is about ±25° for all turbines. Compared with the aligned condition, AYC can achieve a contribution rate of more than 15% for a total power increase at medium wind speed and eventually gains an annual energy production of 0.32%, which will promote the efficient development and utilization of offshore wind power. [ABSTRACT FROM AUTHOR]

The wake effect will cause wind farm power loss. Wake redirection is a wind farm control strategy to reduce wake losses and increase total power output. In the previous research, analytical wake models with steady-wind-condition assumptions were always employed to optimize the yaw angle of wind turbines, in which wind direction change and yaw process were not considered. Therefore, this study proposes a dynamic yaw control methodology for wind farms to balance the energy gain and the number of yaw actions. It was found that when the dead band is 10°, the past time is 15 min, and the wind direction bins step is 8°, the number of yaws of the front row unit is only 97.2% of that under the conventional control, and the total power generation is increased by 3.41%. [ABSTRACT FROM AUTHOR]

Climate change has exacerbated the contradiction between water scarcity and sustainable agricultural development. Assessing the crop water use efficiency and its influencing factors could provide a decision-making reference to realize Sustainable Development Goal 2. By analyzing the temporal and spatial evolution characteristics of the crop water footprint, the blue water footprint, green water footprint, and grey water footprint were introduced into the super efficiency slack-based measure model to evaluate the crop water use efficiency in basins. The influence of the driving factors was examined by using the geographic detector model. The situation in the provinces along the Yellow River Basin from 2005 to 2020 was used as a verification case. The results indicated that (1) during the study period, crop water use in the basin was mainly based on the blue water footprint, accounting for approximately 55% of the total water footprint, the grey water footprint, accounting for approximately 30% of the total water footprint, and the green water footprint, accounting for the lowest proportion, at approximately 15%. (2) The crop water use efficiency exhibited a spatial distribution pattern of high values in the east and low values in the west, with obvious upstream provinces disposable income of rural residents (0.71) > population urbanization rate (0.65) > degree of agricultural mechanization (0.63) > agricultural disaster rate (0.61). Furthermore, the interaction effects between the driving factors were greater than the effects of the single factors. The study provides an important reference for understanding the changes, driving mechanisms, and impacts of crop water use efficiency in basin areas. It promotes green agricultural transformation and development to address climate change and alleviate the pressure on water resources. [ABSTRACT FROM AUTHOR]

Plant density, the number of plants per unit area, is an important factor in maize production. Plant density exhibits high variability and depends on a number of factors, i.e., the length of the growing period of the hybrid, the morphological characteristics of the plant, the amount and distribution of precipitation during the growing season, the reserve of winter moisture in the soil, the level of soil fertility, the time of sowing, agronomic management practices, and biomass and yield. The objective of this paper was to determine the agronomic optimal plant density for maize in calcareous soil in the semiarid conditions of the South Pannonian Basin. Field experiments were conducted at the experimental field—IFVCNS (two locations: Rimski Šančevi and Srbobran) to evaluate four plant densities (55,000; 65,000; 75,000; and 85,000 plants ha−1). The experimental sites "Rimski Šančevi" and "Srbobran" are located in the typical chernozem zone of the southern part of the Pannonian Basin. On average for all hybrids, the grain yield followed a second-degree polynomial model in response to the increasing planting density, with the highest value at plant density (PD2: 65,000 plants ha−1). To achieve maximum yield, the optimal planting density for corn hybrids of the FAO 200 group should be 57,600 plants ha−1, for the FAO 300 group 64,300 plants ha−1, for the FAO 400 group 68,700 plants ha−1, for the FAO 500 group 66,800 plants ha−1, and for the FAO 600 group 63,500 plants ha−1. "Which–Won–Where" biplot showed that the hybrid H24 from FAO 600 group was the highest yielding in all of the environments. Hybrid H17 from the same FAO group was the most stable across all of the environments. Selected hybrids may further be studied for planting density and nutritional requirements for getting maximum yield. By introducing new maize hybrids with higher genetic yield potential and better agronomic management practices, modern mechanization and agricultural techniques allowed to increase planting densities. [ABSTRACT FROM AUTHOR]

We present a new approach to establish an empirical overview of farmers' risk preferences and the characteristics associated with these preferences. We rely on an Individual Participant Data Meta-analysis whereby we identify studies eliciting risk preferences through self-assessments and Holt and Laury lotteries, and construct and analyse a unique dataset of 5,157 farmers from 19 studies in 13 European countries. Our results reveal significant heterogeneity in risk preferences across elicitation methods, within and across studies, risk domains and farm and farmer characteristics. European farmers are on average risk-averse when risk preferences are elicited by lotteries, and on average risk-neutral when elicited by self-assessments. Beyond differences in the average risk aversion, there are distributional differences pointing to a limited convergence between elicitation methods and a larger explanatory power of farm and farmer characteristics to determine risk preferences elicited with self-assessments compared to lotteries. [ABSTRACT FROM AUTHOR]

Despite having 22% of the world's population, China only has 7% of arable land, making it difficult for the country to be self-sufficient in food production and increasing food security. Therefore, it is imperative to investigate the factors that can enhance food production in China, considering the country's significant population size juxtaposed with limited arable land. In light of this, the present study examines the impact of farm mechanization, financial development, and renewable energy on China's food production. Using the Quantile Autoregressive Distributed Lag technique, which explores the nonlinear relationship between variables exhibiting heterogeneity across different quantiles of the dependent variable, we analyze the short and long-run effects of these factors on food production. The findings reveal significant long-term impacts of farm mechanization, renewable energy, and financial development on food production, while the short-run results exhibit some variation. Based on these results, the research suggests various strategies to promote the utilization of renewable energy, farm machinery and improve farmer access to financing, thereby fostering enhanced food production in China. [ABSTRACT FROM AUTHOR]

Using data from a survey of farm households in the Indian state of Uttar Pradesh and employing a sequential logit model, this paper has investigated the impact of farmers' participation in the Direct Benefit Transfer (DBT) subsidy scheme for micro-irrigation on crop performance. The findings show that over 91% of the farmers were aware of the scheme, 61% of them registered as potential beneficiaries and two-thirds of them actually benefitted from it. Registration is the critical transition stage for participation in the DBT scheme. Our findings show that conditional upon the ownership of tube-wells and water pumping devices, several personal and household-level factors such as age, education, access to information and membership of village-level organizations distinguish the beneficiaries of DBT from the non-beneficiaries. There appears no selection bias in the scheme as neither the farm size nor the social status of potential beneficiaries appeared significant in the sequential selection process. Further, the findings show that controlling for the farm and farmer characteristics, the DBT scheme has a positive and statistically significant impact on crop yield as well as net returns, but more on the latter implying its role in reduction in the cost of production. These findings imply the need to expand DBT scheme for its greater impact on farm income and inclusiveness. [ABSTRACT FROM AUTHOR]

Bangladesh is increasing agricultural mechanization to reduce labor-intensive drudgery and to address labor shortages in farming. Agricultural equipment, such as power tillers and threshers, are used to achieve this goal and require regular replacement of the spare parts that experience significant wear in use. Spare parts are currently imported at twice the cost of domestic ones. This paper supports the development of domestic manufacturing by analyzing the manufacturing processes for two fast-moving spare agricultural parts, tiller blades and threshing teeth, and providing a method to develop more efficient processes. The manufacturing processes, which focused on the design of forging and bending dies, reflect the constraints of the manufacturing equipment and stock materials available in Bangladesh. The die designs and manufacturing processes were verified by FEA simulations and by experimental testing. The experiments and simulations suggest that the spare parts should be made at elevated temperatures and high rates of forming. Recommended die designs and processing conditions and forces required to achieve the final part and that can be implemented in manufacturing facilities in Bangladesh are presented. [ABSTRACT FROM AUTHOR]

This study aimed to determine the performance of agriculture sector in Nepal which would help in formulating better policies for its improvement. The study estimated the growth and instability for the period 2001-02 to 2020-21, dividing it into two periods, period-I (2001-02 to 2010-11) and period-II (2011-12 to 2020-21). The growth and instability analysis indicated that the growth of production of almost all crops were increased during period-II. Oilseeds showed the highest increase in production with growth rate of 6.26%, whereas millet and coffee showed decreasing rate of production in period-II. The area under wheat and millet decreased drastically in period-II. Although instability in area increased in period-II for almost all the crops, tea experienced highest increase. Instability in coffee production decreased from 41.85% in period-I to 15.92% in period-II, highest among selected crops. The instabilities in production were due to natural calamities, lesser and untimely availability of inputs, less priority in the research sector for minor crops and so on. Livestock subsector has been performing well as compared to the crop sector. Prioritization by the government and wide climatic conditions are the major strengths of the sector whereas unavailability of inputs in time and lack of investment frameworks are the weaknesses. Farm mechanization, topography and agri-tourism are some opportunities and climate change, fragmentation of arable land, brain-drain are the threats to this sector in Nepal. The major focus of the government should be on utilizing the rural labor force on agriculture sector through different schemes such as effective crop and livestock insurance, timely supply of demanded inputs and proper extension services. [ABSTRACT FROM AUTHOR]

This study reviewed the advancements of Agriculture 4.0 in mechanized sugarcane harvesting, analyzing the efficiency of the mechanized harvesting system and evaluating the impact of the harvesting, loading, and transportation process costs. The mechanized sugarcane harvesting system in the 2020/21 harvest reached 91.6% or approximately 588 Mg in Brazil. As this activity demands a high amount of capital - assets, labor, inputs - the cost of the harvesting, loading, and transporting process represents 40% of the sugarcane production cost. The continuous delivery of raw material to the industrial processing unit is essential to ensure stability and maximum yield for obtaining sugar and ethanol, especially in an environment with geographical dispersion of harvesting fronts and agronomic factors linked to crop management. Therefore, tools that enable real-time equipment tracking benefit process management. Digital agriculture, defined as the application of technologies that seek to add intelligence and process automation, allows for improved agricultural management of farms, making it possible to reach new productivity levels in the field. The data generated through digital agriculture allows for the creation of models to construct scenarios that improve decision-making, both in terms of operational strategies - distribution of resources by harvesting front - and long-term strategies - the adoption of new technologies in the process. [ABSTRACT FROM AUTHOR]

This paper describes an innovative method to provide a micro-electric tractor which has been developed as part of an initiative that aims to provide socially inclusive and affordable green energy solutions to smallholders in sub-Saharan Africa. It utilizes a 15.0-kW solar array and battery system to power micro-electric tractors for an agricultural practice called deep bed farming in Malawi. Deep bed farming increases smallholder crop yield by about two and half times, which increases revenue by up to 12 times. The extra revenue can then be used to perpetually purchase domestic energy from the solar array, creating a self-sustaining model for decentralized energy access. However, the requirement for land preparation is onerous, and mechanization is needed to help overcome barriers to entry. This paper describes the technical requirements of a solar base station and micro-tractor for use with the deep bed farming technique. The paper covers the 5.9 kWp modular solar design and a 10.0-kWh rated micro-tractor. Testing was undertaken at an isolated grid in Loughborough as a precursor for large-scale testing in Malawi. [ABSTRACT FROM AUTHOR]

For large-scale constructed wind farms, reducing wake loss and improving the overall output power are the main objectives for their optimal operation. Therefore, a wind farm power maximization method based on a multi-strategy improved sparrow search algorithm (MS-ISSA) is proposed in this paper. Integrating the wake propagation mechanism of wind turbines and the characteristics of the classic Jensen wake model, the Jensen-Gaussian wake model and wake superposition model were constructed to accurately calculate the wind farm wake distribution. The constructed Jensen-Gaussian wake model and wake superposition model can accurately describe the non-uniform distribution characteristics of wake velocity. The Sin chaotic model, Cauchy distribution, and hyperparameter adaptive adjustment strategy were used to improve the sparrow search algorithm (SSA), and the optimization ability, convergence speed, and stability of the SSA were improved. Accordingly, considering the maximum output power of the wind farm as the optimization target and axial induction factor as the optimization variable, a coordinated optimization model for wind turbines based on MS-ISSA was proposed to realize the coordinated optimal operation of wind turbines with reduced wake loss. Considering the Danish Horns Rev wind farm as the research object, the results of optimization using particle swarm optimization algorithm, whale optimization algorithm, basic sparrow search algorithm, and MS-ISSA were calculated and analyzed. The calculation results revealed that under different incoming wind conditions, the MS-ISSA exhibited better optimization results than the other optimization algorithms. [ABSTRACT FROM AUTHOR]

Summary: Background: Routine tasks performed by equids have been taken over by motorised transportation and agricultural mechanisation services, and both are rapidly expanding in developing nations. For instance, in developing nations, the length of all‐season roads annually has increased by 0.2% and the number of vehicles by 15% to 17%. Consequently, rural agriculture no longer regularly recruits equines. Objectives: Strategies need to be developed to safeguard the use values of equids to guarantee their crucial role in the daily lives of rural people. Study design: The report has compiled the findings of field‐based exploratory qualitative study. Methods: This study involved in‐depth interviews of 10 knowledgeable informants and analysed FAOSTAT historical dataset to assess the population status of equids. Results: To encourage people to use equids for companionship and recreational purposes, the hobbies of equine farming need to be promoted in both urban and rural areas. Equestrian riding and racing can be beneficial for festivals and sociocultural events, like weddings, funerals and competitions. It is illogical to disregard the transportation, ploughing and crop harvesting roles of equids. It is worthwhile to include donkeys and mules in the well‐established sports of horseracing and riding. Bovines can produce high‐quality carcasses when equids are used as work animals. Equine manure is rich in nutrients compared with ruminant manure. Equid meat is occasionally consumed and exported. Equid hides can be used to produce leather goods and parchments. It is essential to investigate the medicinal value of equine products. By clipping hair from horses' tails and manes, handicraft people can make whiskers and cords of musical instruments. Equids are highly sought‐after in landscape management and scientific studies. In rangelands, horses can assist in monitoring grazing and browsing livestock. In open urban public spaces and rural areas, equines can graze on communal grazing lands as stray animals and a population of feral animals may eventually emerge. Main limitations: This is an exploratory qualitative study and it needs to be supported by extensive studies involving formal surveys. Conclusion: To ensure the continued existence of equids, it is worthwhile to explore the derived use values, enhance the existing ones and alleviate their major production constraints. [ABSTRACT FROM AUTHOR]

It is one of the most important tasks for the work of Agriculture, Rural areas and Farmers' in the new era to consolidate and develop the achievements of rural poverty alleviation and effectively link them with the revitalization of rural industries, and agricultural science and technology plays a key role in the revitalization of rural industries. There are many problems in the ethnic minority areas of Sichuan province, such as the insufficient investment in agricultural science and technology innovation, the weak foundation of modern agriculture, the in- sufficient supply of agricultural science and technology talents, the imperfect mechanism of agricultural science and technology innovation, the relatively low scientific and cultural timber of farmers, and the insufficient endogenous motivation, it is suggested that the construction of the Double system' of agricultural science and technology innovation and achievement transformation system, building a platform for demonstration and transformation of high-level scientific and technological achievements, improving the level of scientific and technological supply, perfecting the organizational system of agricultural production and management, perfecting the service system of agricultural informationization and mechanization, establishing the quality safety and standardization system of agricultural products, strengthening the training system of agricultural science and technology talents should be started from six aspects, the achievement of consolidating and expanding poverty alleviation in ethnic minority areas in Sichuan province has been effectively linked with the revitalization of rural areas. [ABSTRACT FROM AUTHOR]

This paper is an attempt to assess the impact of climate on wheat yield in the Indo-Gangetic Plain (IGP) region of India by using panel data analysis. Five IGP states namely Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal have been considered to frame a panel. The study used the data of climatic and non-climatic variables from 1990 to 2022 to achieve the objective of the study. The Im-Pesaran-Shin unit-root test was applied to check the stationarity of data. The results of the panel least square dummy variable model indicated that all the climatic variables had non significant influence. Among non-climatic variables that help increase wheat yield, fertilizer consumption and mechanization in agriculture were found to have a significant positive impact on wheat yield in the IGP region of India. [ABSTRACT FROM AUTHOR]

The advancement of agricultural mechanization necessitates precise and standardized classification based on technical characteristics to enhance green, efficient, and high-quality development. The current lack of scientific and standardized definitions and classifications for various types of agricultural machinery has become a bottleneck, complicating the machine selection and affecting the compatibility of the machinery with optimized field operations. To address this complexity, we propose a comprehensive classification method that integrates principal component analysis (PCA), cluster analysis, and the qualitative analysis of the functional components for defining and scientifically classifying harvesters. The key functional and technical properties of harvesters were analyzed, and eight primary parameters (machine weight, cutting width, feed rate, rated power, overall machine length, width, height, and working efficiency) were selected, supplemented by nine key functional components (walking mechanism, cutting device, threshing device, separating device, cleaning device, grain collecting device, grain unloading device, cabin, and track size). In the first step, principal component analysis was performed to reduce the dimensionality of the parameters, yielding three principal components with contribution rates of 41.610%, 28.579%, and 15.134%, respectively. One primary parameter from each component was selected for further analysis. In the second stage, Q-type cluster analysis classified the harvesters based on the squared Euclidean distance between the operational parameters, resulting in three classes of harvesters. Finally, functional component analysis provided detailed insights, further refining the classification into four major categories: mini, small, medium, and large harvesters. The results of this work provide a scientific basis for the definition and classification of the harvester products available on the market. This method offers a robust framework for the rational selection and planning of agricultural machinery, promoting sustainable mechanization with a focus on technical parameters and functional attributes. [ABSTRACT FROM AUTHOR]

Since the early 2000s, aquaculture in Nigeria has grown exponentially. African catfish aquaculture was a major contributor to this expansion. However, a fall in output started in 2015, mostly due to challenging economic conditions which affected farmer's profitability. This challenge has been exacerbated by the COVID‐19 pandemic. Notwithstanding, some catfish farms remained profitable. This study investigates the profitability strategies that aid farmers' resilience in times of both economic distress and COVID‐type shock. Data from 609 randomly sampled farms across the country were verified and included in the study covering 1118 operations for the pre‐COVID and COVID periods. Budgetary analysis was done, and stepwise regression was used to identify factors that most contribute to profitability. These factors were ranked by average profit per kilogram and grouped. The profitability during the periods was influenced by factors within the subcategories of scale of operation, experience, targeted markets, ownership, and pond type. Engagement in other agricultural ventures favored profitability during the COVID period. Profitable and non‐profitable groups were further characterized based on their technical and financial indicators. Explored strategies for profitability, including the operation scale, marketing tactics, cost‐cutting, and innovative production techniques all proved successful during economic distress and the pandemic. [ABSTRACT FROM AUTHOR]

To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general framework that can combine other optimization algorithms. The proposed methodology is tested on the modified WSCC 9-bus system and the New England 39-bus system. The results verify the feasibility of the method. [ABSTRACT FROM AUTHOR]

The Haors in Bangladesh are saucer-shaped, low-lying land depressions that form deep basins; they remain submerged for approximately half of the year, typically from June onwards. This fragile ecosystem spans over 2.0 million hectares in the northeastern region of the country, accounting for roughly 14% of the total areas, where approximately 19.4 million people reside. Factors including floods, flash floods, and low winter temperatures constrain agricultural productivity in the haor areas. It is a great challenge to change the haor areas from less productive to more productive land. This is a comprehensive analysis of the biophysical and socioeconomic characteristics of haors which also highlights the constraints and opportunities in agricultural production. It explores strategies for significantly increasing crop, livestock, and fish production within the haor ecosystem, in alignment with government policies. Some of the proposed agricultural development strategies for the haor areas include the development of short-duration, cold-tolerant crop varieties, such as Boro rice, utilizing relatively flood-free elevated lands and homesteads for vegetable production and promoting agricultural mechanization, livestock rearing, fisheries, and agribusiness development. The recommendations presented in this paper focus on enhancing crop yields, increasing cropping intensity, and boosting livestock and fish production; ultimately, they contribute to food security, poverty reduction, and improved livelihoods for the inhabitants of the haor areas. [ABSTRACT FROM AUTHOR]

Agricultural development in developing countries generally faces increasingly severe financing constraints, and China's practice provides a model for other countries. This article investigates the impact of the policy to alleviate rural financing constraints on agricultural carbon emissions in developing countries by using a quasi-natural experiment, the "Incremental Incentives for Agricultural Loans from County Financial Institutions," implemented in China, with data from 2005 to 2018, and with a DID approach. It is found that under the influence of this policy, the alleviation of agricultural financing constraints will significantly generate an increase in the intensity of agricultural carbon emissions, which is triggered by the fact that the alleviation of financing constraints increases the production factors invested per unit area in the agricultural production process, while the increase in the mechanization and scale of agriculture will assist to reduce the contribution of the alleviation of financing constraints to carbon emissions. The impact of financing constraint alleviation on agricultural carbon emissions may differ among places with different economic and social development and agricultural bases. Additionally, the alleviation of rural financing constraints can promote agricultural development and increase farmers' income, enabling other developing countries to adjust their policy orientation when adopting such policies, thus promoting agricultural development while controlling agricultural carbon emissions and contributing to the global emission reduction cause. [ABSTRACT FROM AUTHOR]

In the fresh tomato market, it is crucial to sort and sell tomatoes based on their quality. This is important to enhance the competitiveness and profitability of the market. However, the manual sorting process is subjective and inefficient. To address this issue, we have developed an automatic tomato sorting system that uses the Raspberry PI 4B as the control platform for the robot arm. This system has been integrated with a human–computer interaction interface sorting system. Our experimental results indicate that this sorting method has an accuracy rate of 99.1% and an efficiency of 1350 tomatoes per hour. This development is in line with modern agricultural mechanization and intelligence needs. [ABSTRACT FROM AUTHOR]

Agricultural mechanization is recognized as an important technology to increase agricultural productivity, face labor shortages, and reduce post-harvest loss. However, variations among farms' characteristics and agricultural production systems suggest adopting a targeted strategy in mechanization programs for farmers. This research aimed to answer the following questions in the particular case of Haiti: are there different types of smallholder farmers in terms of mechanization use and socio-economic characteristics? What types of mechanization are used by farmers, and what drives their use among different types of farmers? What are the different types of farms in terms of mechanization use? We used typology construction methodology (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) for a sample of 637 farmers and have identified four different clusters of farmers according to the characteristics of the farms they managed: "Little rain-fed farms" (cluster 1), "Little lowlands farms" (cluster 2), "Medium-sized farms in irrigated plains" (cluster 3), and "Large fragmented mountain farms". Farms in cluster 3 were those who used more agricultural mechanization, and the results of multinomial logistic regression (MNLR) model revealed that the significant drivers of this use were location, access to credit and low food security status. Mechanization use of farms in clusters 1 and 4 was distinctively driven by saving behavior and off-farm income, respectively. In the pooled sample, the drivers of mechanization were: regions or location, age of the farmers, irrigation, livestock, access to credit, off-farm income and food security status. This study contributes to the literature by testing new drivers of agricultural mechanization such as food security status, and off-farm income. The findings can be used to design appropriate mechanization strategies to increase productivity and face labor price/scarcity challenges. They suggest that mechanization policies should focus on agricultural equipment that are adapted to the specificities of the production systems of each farm type, and strengthen access to credit. Otherwise, mechanization will be predominantly used only in irrigated lowlands. [ABSTRACT FROM AUTHOR]

Agricultural mechanization plays a pivotal role in transforming the farming sector across the globe. The number of patents granted in the field of agricultural mechanization hold significance as they encourage innovation, protect intellectual property and drive technological advancements. The present study examined patents data collected from XLPAT database, wherein 500,000 records out of which 479,010 patent grants/applications were considered. Trajectory of patents during COVID pandemic showed there was an apparent downturn in both the quantity of patent applications submitted and the number of patents officially granted. Developed countries have exhibited varying trends in agricultural mechanization and patent activities. China, the United States and India stand as examples. China has rapidly adopted mechanization in its agriculture, contributing to higher yields and efficiency. The United States has a long history of mechanized farming, and its advancements in this field have greatly impacted global agriculture. The standardization of reaping and threshing offer better agricultural equipments by agricultural startups. Expansion of patents in farm mechanization has led to increased productivity, resource efficiency, equity for small and marginal holders, affordability, eco-consciousness and food security. [ABSTRACT FROM AUTHOR]

The primary source of soil compaction is weight bearing down on the soil, which occurs frequently on agricultural land due to foot movement, livestock tramples, or the heavy weight of farm equipment. The primary cause of significant soil compaction is the driving of heavy machinery over moist soils. In this paper, the negative side of soil compaction and its influence on soil physical and chemical characteristics at the Awash Melkassa farm field located in Ethiopia were investigated. Compaction of soil test was taken at three different depths which are 10 cm, 20 cm, and 30 cm with the help of a hydraulically operated cone penetrometer integrated into the tractor. The three depths were expanded into 15 sample locations (designated as point A to point O) to collect 35 data points on soil compaction using a hydraulic-powered Spot-on digital soil cone penetrometer across a 0.6-hectare farmland area. A correlation analysis was conducted on the 15 sample points (A to O) to assess soil compaction in the field. In addition, soil samples were collected from specific farm locations at depths ranging from 0 to 10 cm, 10–20 cm, and 20–30 cm for subsequent physical and chemical tests in the laboratory. During the harvesting season, sample location A exhibited the highest soil compaction values, reaching 6,159 kPa, while the lowest values were observed at sample point F, measuring 327 kPa. For the seeding season, the sample point B showed the highest soil compaction values at 6,052 kPa, while the lowest values were recorded at sample point K, measuring 563 kPa. Moreover, the data indicates a consistent increase in soil compaction with depth during both experimental seasons. The laboratory test for soil texture revealed that the soil composition was classified as a clay loam, consisting of 36.7% sand, 30.3% clay, and 33% silt. The moisture content ranged from a high of 16.04% to a low of 13.97%. In addition, it was observed that total organic carbon, organic matter, and total nitrogen levels tend to rise with increased soil compaction, and conversely, decrease as soil compaction decreases. This study's insights are invaluable for agricultural mechanization. Given the substantial weight of farm machinery, comprehending soil properties and their correlation with compaction rates is imperative for optimizing farming practices. [ABSTRACT FROM AUTHOR]

To enhance the precision and efficiency of the tractor-failure-rate and equipment-quality inspection, the present study introduces a wireless rapid detection method for assessing tractor quality. For this study, which was based on the symmetrical structural characteristics of tractors, we designed a magnetic suction accelerometer. The test system was composed of a wireless router, a magnetic suction accelerometer sensor, a data-acquisition terminal, and other components. This test system aimed to test the equipment quality of the tractor at idle speed before leaving the factory. The experiment found that the vibration characteristics of the tractor had a symmetrical pattern on the left and right sides of the front and rear axle at idle. When the idle speed of the tractor was 800 r/min and 1000 r/min, the predominant vibration direction of both sides of the front axle of the tractor was the Y direction, while the predominant vibration direction of the rear axle was the Z direction. The experimental results showed that the proposed wireless rapid detection method of tractor quality and the designed acceleration sensor had good testing accuracy. The present study could provide a novel rapid detection method for the failure detection of power machinery in the agricultural field and for inspection before leaving the factory. The implementation of the method could improve the detection efficiency, and reduce the detection cost and the incidence of failure during actual use. [ABSTRACT FROM AUTHOR]

In order to explore the international competitiveness of China's agricultural product supply chain, this paper combines machine learning algorithms to optimize the data processing process of agricultural product supply chain, and proposes a data processing method for agricultural product supply chain based on the intra‐column rules and inter‐column rules. According to the problems of my country's agricultural product supply chain, this paper establishes a new agricultural product supply chain management model based on the various modules of the supply chain link, and constructs a corresponding intelligent analysis model. Moreover, this paper combines machine learning algorithms to study the improvement path of the international competitiveness of China's agricultural product supply chain, and builds an intelligent model to improve the international competitiveness of China's agricultural products. Finally, after constructing the model, this paper obtains the path to improve the international competitiveness of China's agricultural products through the simulation operation model, which also verifies the effectiveness of the intelligent algorithm of this paper from the side. [ABSTRACT FROM AUTHOR]

Wind prediction is a multi-step, high-dimensional time series problem. Prediction by Data-driven machine-learning methods performs better than physical and statistical methods. Thus, many data sources can enhance the accuracy of power projections. This study suggests combining static data from various sources with anticipated and observed wind turbine meteorology data. In order to achieve this, the Res-CNN network combines global information from various sources to facilitate input variables to achieve accuracy. The forecasting model uses an encoder-decoder with LSTM as a basic unit, Add & Norm for input variable improvement and a self-attention mechanism for global time information integration. Additionally, the distributed mechanism of time performs multi-step prediction. The study investigates power generation in Kutch, Gujarat, utilizing data from the Central Electricity Authority and weather data from regional weather centres. Compared to a traditional AI forecasting method like Seq2Seq+attention, this method makes better predictions. [ABSTRACT FROM AUTHOR]

With the rapid advancement of agricultural mechanization, intelligent header technology has emerged as a pivotal element in optimizing the efficiency and quality of grain combine harvesters. This paper offers a comprehensive analysis of the current state of intelligent header technology, with a particular emphasis on the structure, working principles, contour-following mechanisms, and height control technologies. By integrating cutting-edge sensor technologies, advanced control algorithms, and optimized mechanical designs, intelligent headers can achieve precise control over height and posture, thereby significantly reducing crop losses and enhancing both harvesting efficiency and quality. Despite substantial progress, challenges remain in areas such as response speed, real-time performance, height measurement accuracy, and control algorithm effectiveness. Future research will likely concentrate on improving control system performance, refining component and system designs, and incorporating emerging technologies to better accommodate diverse crops and complex terrains. This paper also provides a critical evaluation of current limitations in intelligent header research and projects future trends, offering valuable theoretical and practical insights for optimizing header structures, minimizing losses, and enhancing intelligent functionalities. The ultimate aim is to drive continuous innovation and advancement in header technology for grain combine harvesters. [ABSTRACT FROM AUTHOR]

In modern agriculture, with the development and widespread use of agricultural mechanization, mechanical compaction of soils has become a growing problem, resulting in soil degradation in the field. Based on the Boussinesq solution, the soil stress formula for the circular load area is derived, and MATLAB is used to simulate the stress-strain relationship of the soil at different depths. The results show that under the same load conditions, as the soil depth increases, the soil stress gradually decreases, with the most significant stress change occurring at 0.2 m depth. Soil compression experiments conducted using a consolidation instrument revealed that the soil void ratio dropped rapidly under loading of 50-200 kPa, and the decline slowed after 400 kPa. When the soil void ratio decreases to 0.2-0.4, the soil stress changes tend to stabilize. Comparison between the theoretical formula and the compression experimental data indicates that the soil stress gradually decreases as the thickness of the soil layer increases and the pressure load increases, verifying the linear relationship predicted by the theoretical formula. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the impact of technology adoption on farmers' subjective well-being, as measured by happiness and life satisfaction. A theoretical framework is constructed to link farmers' subjective well-being to technology adoption, with a particular emphasis on mechanization services in agricultural production. By fitting a nationally representative panel dataset – China Family Panel Studies – into an endogenous switching regression model that addresses potential selection bias, we find that technology adoption leads to a 0.194 standard deviation increase in happiness and a 0.065 standard deviation increase in life satisfaction. Further analysis reveals that the effect is more pronounced for individuals engaged in off-farm employment and varies across farm sizes. To underpin the causal effect, we test three plausible mechanisms – absolute income, relative income, and leisure – which are well-documented in the literature for their correlations with happiness and life satisfaction. Our empirical analysis indicates that the adoption of agricultural mechanization services indeed increases the absolute income of farmers and allows them to allocate more time to leisure activities. [ABSTRACT FROM AUTHOR]

This article explores collective memories about lost farms in New York City's watershed. It argues that farms taken by eminent domain for two water supply reservoirs came to symbolize lost rural and agricultural lifeways in the twentieth century. In the 1950s and 1960s, New York City condemned over two hundred farms in Delaware County, New York, flooding two valleys for reservoirs, contributing to a pattern of farm closure, and dramatically changing social and economic life. Nonetheless, farms declined in this region more slowly than across the state and nation, suggesting that it was not the loss of farms but the specific way these agricultural valleys were flooded that became important for collective memories about this local history. Using transcripts from eminent domain proceedings and local newspapers, this article explores the making and mobilization of collective memories that blamed New York City for the loss of the county's "best" farms. Reading historical documents as cultural texts, this article brings together the insights of science and technology studies and memory studies to show how residents in the watershed localized a more general politics of rural-urban division by linking anxieties about changes in the region to New York City's water supply development history. [ABSTRACT FROM AUTHOR]

Wind farm control can play a key role in reducing the negative impact of wakes on wind turbine power production. The helix approach is a recent innovation in the field of wind farm control, which employs individual blade pitch control to induce a helical velocity profile in a wind turbine wake. This forced meandering of the wake has turned out to be very effective for the recovery of the wake, increasing the power output of downstream turbines by a significant amount. This paper presents a wind tunnel study with two scaled wind turbine models of which the upstream turbine is operated with the helix approach. We used tomographic particle image velocimetry to study the dynamic behavior of the wake under the influence of the helix excitation. The measured flow fields confirm the wake recovery capabilities of the helix approach compared with normal operation. Additional emphasis is put on the effect of the helix approach on the breakdown of blade tip vortices, a process that plays an important role in re‐energizing the wake. Measurements indicate that the breakdown of tip vortices and the resulting destabilization of the wake are enhanced significantly with the helix approach. Finally, turbine measurements show that the helix approach was able to increase the combined power for this particular two‐turbine setup by as much as 15%. [ABSTRACT FROM AUTHOR]

The act of land transfer in rural areas is an important decision-making mechanism for farmers, to enhance resource allocation efficiency and promote capital mobility, and this act is of strategic importance in promoting the level of agricultural scale and mechanization, land system change, and, thus, the sustainable development of livelihoods and production in China. This study aims to explore farmers' decision-making mechanisms in the process of land transfer in rural areas, by constructing a theoretical framework. Structural equation modeling was used, based on data from a survey of rural families in the Liaoning Province area of Northeastern China. The main findings are as follows: (1) The seven types of exogenous latent variables, including environmental vulnerability, policy, and five main livelihood assets (natural capital, physical capital, financial capital, human capital, and social capital), are intermediary in farmers' land transfer behavior, which then positively affect farmers' livelihood outcomes. (2) Among the exogenous latent variables affecting farmers' land transfer, human assets have the most significant positive effect, followed by social assets and physical assets, family labor force share, frequency of work information exchange, and number of production tools, greatly affect the corresponding variable. (3) Natural assets play the most important role and have a negative effect on farmers' land transfer decision; contracted area of land per family is the greatest impacted measurable variable of this. The results of the study suggest that the government should strengthen skills training for farmers, improve the land transfer policy system, and provide appropriate subsidies in a regionally targeted manner. Thus, it can promote the transformation of Chinese-style agricultural modernization and achieve rural revitalization. [ABSTRACT FROM AUTHOR]

Climate change significantly impacts the livelihoods of farmer households. Particularly vulnerable areas, both economically and environmentally, face significant threats from climate change. This study developed a framework to assess household-level vulnerability to climate change by integrating the Exposure-Sensitivity-Resilience Analysis (ESRA) and Sustainable Livelihoods Analysis (SLA) frameworks. Using Gui-Zhou Province as the study area, the study examined whether livelihood vulnerability differs among various types of farmer households in economically and environmentally vulnerable areas and identified the main factors contributing to vulnerability. Results indicate significant differences in livelihood vulnerability among the three household types, with pure agricultural households (PAH) being the most vulnerable due to high exposure, sensitivity, and low adaptive capacity. Further analysis revealed minor differences in sensitivity but significant differences in adaptive capacity among the three farmer categories. In terms of sensitivity, all three farmer household categories exhibit high sensitivity to water, housing, and agricultural production. Regarding adaptive capacity, significant differences in human and financial capital exist among the three household types, with off-farm households (OFH) possessing the highest adaptive capacity due to their substantial human and financial capital. Further research identified high exposure and low adaptive capacity as the primary causes of livelihood vulnerability, noting no significant difference in the main contributing factors among the three types of farmer households. Common factors contributing to the livelihood vulnerability of farmer households include agricultural cooperatives, labor capacity, temperature changes, drought frequency changes, precipitation changes, agricultural insurance, and losses in agricultural production. Overall, the proposed livelihood vulnerability framework offers guidance for analyzing the vulnerability of farmer households in areas with both economic and environmental vulnerabilities under climate change. Concurrently, tailored measures to reduce farmer households' livelihood vulnerability should be developed for different household types, considering the local climatic, geographic, and socioeconomic conditions. [ABSTRACT FROM AUTHOR]

Among the many studies on the history of Polish countryside and agriculture after 1945, there are no studies analyzing in a broader scope the issue of the relationship between agricultural production and the natural environment, despite the close connection between this sector of the economy and natural resources. The negative impact of agricultural intensification based on chemicalization and mechanization of agriculture on the condition of the natural environment is also omitted (or treated marginally). This text is an attempt to fill this gap. Its subject is the problem of the impact of agriculture on the natural environment in Poland in the years 1944–2004, i.e. in the period from the end of the war to Poland's accession to the European Union. The basic research questions concern the directions of agricultural policy in the above period and selected methods of agricultural intensification and their impact on the environment, with particular emphasis on artificial fertilization and chemical plant protection, agricultural mechanization and agricultural land improvement. Due to the lack of space, the description of the above problems is a synthetic sketch concerning selected issues that await in-depth research. However, existing research shows that the degree of environmental threat depends on the level of fertilization and use of plant protection products, the degree of mechanization and dissemination of monocultures, and the level of drainage. Therefore, in Poland it occurred with varying intensity, greater in large-scale farming areas and less in the case of small and extensive family farms. [ABSTRACT FROM AUTHOR]

Effective scheduling of multiple agricultural machines in emergencies can reduce crop losses to a great extent. In this paper, cooperative scheduling based on deep reinforcement learning for multi-agricultural machines with deadlines is designed to minimize makespan. With the asymmetric transfer paths among farmlands, the problem of agricultural machinery scheduling under emergencies is modeled as an asymmetric multiple traveling salesman problem with time windows (AMTSPTW). With the popular encoder-decoder structure, heterogeneous feature fusion attention is designed in the encoder to integrate time windows and asymmetric transfer paths for more comprehensive and better feature extraction. Meanwhile, a path segmentation mask mechanism in the decoder is proposed to divide solutions efficiently by adding virtual depots to assign work to each agricultural machinery. Experimental results show that our proposal outperforms existing modified baselines for the studied problem. Especially, the measurements of computation ratio and makespan are improved by 26.7% and 21.9% on average, respectively. The computation time of our proposed strategy has a significant improvement over these comparisons. Meanwhile, our strategy has a better generalization for larger problems. [ABSTRACT FROM AUTHOR]

The effectiveness of farming relies heavily on the condition of machinery and equipment, as well as maintaining the ideal soil conditions for the desired yields. Soil cultivation tools endure substantial stress and wear, emphasizing the need to study their durability surrounding soil contact. Our research focuses on enhancing the lifespan of worn-out ploughshares through various heat treatment methods and hot metal spraying. By remelting the surface of ploughshares using a flame or laser, we aim to identify the most effective treatment for agricultural production. The improved surface treatment of the furrows in field tillers can significantly cut costs and enhance tillage efficiency. Our preliminary findings suggest that the metal spraying and remelting of nickel alloy hold promise for achieving these goals. [ABSTRACT FROM AUTHOR]

Mainstream economics argues that value chains provide farmers better prices and incomes, thus aiding development. However, this study contradicts this consensus, revealing that the value chain generates the status of petty commodity producers for farmers. Furthermore, it demonstrates that the value chain keeps downstream actors, such as merchants, processors, wholesalers, and retailers, in a powerful position against farmers. The study delves into these phenomena by considering the historical relationship between the market, the commodification of agriculture, the state, the interconnection of markets, the value chain, and neoliberalism. This research focuses on the political economy of groundnut input–output markets in Turkey through value chain analysis. Based on thorough primary field research, the paper demonstrates that the functioning of the value chain strengthens the position of downstream actors against farmers. Additionally, it shows that the value chain creates interlinking between farmers and merchants and makes small farmers the most disadvantaged actor. Moreover, the study highlights that groundnut production costs have risen at a higher rate than incomes under neoliberal policies. Finally, the article demonstrates that mechanization in groundnut farming, while increasing productivity by meeting the chain demands, fails to significantly improve farmers' incomes and profits due to the impact of neoliberal policies on other input costs. [ABSTRACT FROM AUTHOR]

Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machinery is mostly limited to the research on task goal planning and cooperative path optimization of a single operation. To address the mentioned shortcomings, this study addresses the problem of multi-machine cooperative operation of fertilizer applicators in fields with different fertility and fertilizer cooperative distribution of fertilizer trucks. The research uses the task allocation method of a multi-machine cooperative operation of applying fertilizer-transporting fertilizer. First, the problems of fertilizer applicator operation and fertilizer truck fertilizer distribution are defined, and the operating time and the distribution distance are used as optimization objectives to construct functions to establish task allocation mathematical models. Second, a Chaos–Cauchy Fireworks Algorithm (CCFWA), which includes a discretized decoding method, a population initialization with a chaotic map, and a Cauchy mutation operation, is developed. Finally, the proposed algorithm is verified by tests in an actual scenario of fertilizer being applied in the test area of Jimo District, Qingdao City, Shandong Province. The results show that compared to the Fireworks Algorithm, Genetic Algorithm, and Particle Swarm Optimization, the proposed CCFWA can address the problem of falling into a local optimum while guaranteeing the convergence speed. Also, the variance of the CCFWA is reduced by more than 48% compared with the other three algorithms. The proposed method can realize multi-machine cooperative operation and precise distribution of seeds and fertilizers for multiple seeding-fertilizer applicators and fertilizer trucks. [ABSTRACT FROM AUTHOR]