Agricultural Production Technologies Research Articles

Solar Dryers: Technical Insights and Bibliometric Trends in Energy Technologies

This review article provides a comprehensive analysis of the technical advancements and research trends in solar drying technologies for agricultural products. The study encompasses various innovations in energy storage systems, including phase change materials (PCMs) and the use of computational fluid dynamics (CFD) for optimizing the drying process. Through a bibliometric analysis of 126 scientific papers published between 1984 and 2024, five major research clusters were identified: energy generation, heat transfer, thermal storage, simulation modeling, and the integration of hybrid systems. The results demonstrate a marked increase in scientific output over the past decade, emphasizing a growing interest in the sustainable use of solar energy for drying applications. Key findings highlight that while PCM-based storage solutions significantly enhance the thermal stability of dryers, the high implementation costs and technical complexities limit their adoption, especially in small-scale operations. Similarly, CFD models have proven effective in optimizing air and temperature distribution within dryers; however, their performance is hindered by real-world fluctuations in solar radiation and humidity levels. To address these limitations, future research should focus on the development of cost-effective PCM materials and the improvement of CFD models for dynamic environmental conditions. The review concludes by emphasizing the importance of interdisciplinary collaboration in the design and application of these technologies, recommending the inclusion of real-world case studies to better illustrate the practical implications and economic benefits of solar drying technologies for agricultural production.

Unlocking Potential: The Role of Zinc Fortification Combating Hidden Hunger and Enhancing Nutritional Security

Micronutrient shortage is rapidly becoming apparent have drawn more attention in the cultivation of crops. The main causes of this deficit are the introduction of high-yielding varieties, an intensified cropping strategy, and advanced irrigation systems etc. A further aspect contributing to this issue is the increased use of high analysis chemical fertilizers instead of organic plant nutrition (composts, farmyard manure, etc.). Most countries have acute shortages of micronutrients due to the significant depletion of soil reserves caused by current agricultural production technologies. In order to increase both the quantity and quality of crops, micronutrients are crucial. Through the integration of agronomic, breeding and transgenic techniques, researchers seek to strengthen the zinc concentration in field crops, so improving their nutritional value and mitigating the risk of zinc deficiency in human diets. The availability and absorption of micronutrients in crops are improved by agronomic techniques such as foliar spraying, and soil fertilizer treatment including organic amendments. Meanwhile, biofortification of vegetable and fruit crops has also been achieved by transgenic and breeding strategies. In other hand, Rhizobacteria-based biofortification, Chelated Zn biofortification, nutri-priming are also important techniques in Zinc fortification programs to ensure food security and nutritional quality, bio-fortification of micronutrients in crops is vital. In addition, bio-fortification improved quality and crop output, reducing hidden hunger and demonstrating that it was a viable and economical approach. The present review addresses several aspects of zinc insufficiency in human populations, including public health and socioeconomic issues, bio-fortification and ferti-fortification studies, and future efforts to mitigate zinc deficiency in soil and the population at large.

A Review of the Application of Hyperspectral Imaging Technology in Agricultural Crop Economics

China is a large agricultural country, and the crop economy holds an important place in the national economy. The identification of crop diseases and pests, as well as the non-destructive classification of crops, has always been a challenge in agricultural development, hindering the rapid growth of the agricultural economy. Hyperspectral imaging technology combines imaging and spectral techniques, using hyperspectral cameras to acquire raw image data of crops. After correcting and preprocessing the raw image data to obtain the required spectral features, it becomes possible to achieve the rapid non-destructive detection of crop diseases and pests, as well as the non-destructive classification and identification of agricultural products. This paper first provides an overview of the current applications of hyperspectral imaging technology in crops both domestically and internationally. It then summarizes the methods of hyperspectral data acquisition and application scenarios. Subsequently, it organizes the processing of hyperspectral data for crop disease and pest detection and classification, deriving relevant preprocessing and analysis methods for hyperspectral data. Finally, it conducts a detailed analysis of classic cases using hyperspectral imaging technology for detecting crop diseases and pests and non-destructive classification, while also analyzing and summarizing the future development trends of hyperspectral imaging technology in agricultural production. The non-destructive rapid detection and classification technology of hyperspectral imaging can effectively select qualified crops and classify crops of different qualities, ensuring the quality of agricultural products. In conclusion, hyperspectral imaging technology can effectively serve the agricultural economy, making agricultural production more intelligent and holding significant importance for the development of agriculture in China.

Effect of farmland scale on agricultural green production technology adoption: Evidence from rice farmers in Jiangsu Province, China

Agricultural green production technology (AGPT) is crucial for mitigating farmland pollution and degradation, as well as promoting green agricultural development. Using data from 774 rice farmers in the 2021 China Land Economy Survey (CLES), the study analyzes the impact mechanisms and mediating pathways of farmland scale on AGPT adoption at both the farmer and plot levels. The study also reveals the differences in impact based on the heterogeneity of plot concentrations and technological attributes. The results show that: (1) Farmland scale positively impacts AGPT adoption, both at the farmer and plot level. (2) Farmland scale positively impacts AGPT adoption at two levels by affecting commercialization rate, time preference, and machinery investment. (3) The positive impact of farmland scale are heterogenous at two levels. When rice is scatteringly planted, plot scale has a more significant impact on AGPT adoption than operation scale; however, when rice is concentratedly planted, the situation is the opposite. Additionally, when faced with "capital-increasing, labor-saving, and risks-increasing" technology, operation scale has a more significant impact on AGPT adoption than plot scale; however, when faced with "capital-stabilizing, labor-increasing, and risks-controlling" technologies, the situation is the opposite. These findings help to provide policy implications for promoting AGPT adoption and sustainable farmland use.

Application of 5G network technology in agricultural production and information management

Establishing a management information system that adapts to the continuous development of agricultural production management today, adopting advanced 5G technology and means, and comprehensively managing the entire agricultural production is an inevitable trend in the development of agricultural production management. In order to improve the effect of agricultural production informatization management, this paper combines 5G (fifth-generation) network technology to construct agricultural production and informatization management models. In view of the massive dynamic agricultural production management data, this paper studies the efficient multi-copy management strategy, which can consider the two aspects of load balancing and energy efficiency at the same time, so as to achieve efficient data access and energy efficiency. Moreover, this paper introduces a time series-based file access heat calculation model. In terms of determining the number of copies of files, this paper proposes a copy factor allocation algorithm centered on the ranking of file access popularity, and gives a characteristic function. Through cluster analysis, it can be seen that the agricultural production informatization management model based on 5G technology proposed in this paper can effectively improve the efficiency of agricultural information management.

Impact of the degree of agricultural green production technology adoption on income: evidence from Sichuan citrus growers

Enhancing farmers’ adoption of agricultural green production technology (AGPT) is crucial for the green transformation of the agricultural sector. Obtaining additional income is the primary motivation for farmers to adopt AGPTs. Therefore, clarifying the relationship between AGPTs’ adoption degree and income will facilitate the possibility of farmers’ adoption of AGPTs. Based on research data obtained from 805 citrus farmers in Sichuan Province, this study examines the impact of the degree of AGPT adoption on farmers’ income and its mechanisms using the inverse probability weighted regression adjustment (IPWRA) model. These findings indicate: (1) The greater the degree of adoption of AGPTs by farmers, the more pronounced the impact on income increase. Using 1, 2, and 3 AGTs can increase farmers’ income from citrus sales by 7.1, 10.5, and 19.8 percentage points, respectively. (2) The adoption of AGPTs leads to increased income through higher yields and sales prices, which offset the incurred costs. (3) Market channels and farmers’ operating scales can affect the revenue effect of AGPT adoption. (4) Factors (i.e., education level, physical health status, and cultivation area) can affect farmers’ adoption of AGPTs. This study presents policy recommendations based on the above conclusions, aiming to guide the government in promoting AGPTs and advancing agricultural green transformation.

Application and Development of Agricultural Mechanization and Automation in Modern Agriculture

Agricultural mechanization and automation is an important way to realize agricultural modernization and improve agricultural production efficiency. This paper expounds the application status and development path of agricultural mechanization automation. Firstly, the popularization of the mechanization automation technology in agricultural production, the application of major crop production and the application of the technology, facility agriculture and precision agriculture. Secondly, the development path of agricultural mechanization and automation is discussed, including technological innovation and research and development investment, talent training and team building, promotion and demonstration and experience exchange and so on. The article points out that agricultural mechanization and automation is the only way for the future agricultural development, which needs the joint efforts of the government, enterprises and farmers to promote.

Exploration of the application of artificial intelligence in modern agricultural production Take orchard management as an example

In the context of increasing global agricultural challenges, the application of artificial intelligence technology in the agricultural field is increasingly a trend, especially in the production of agricultural products, intelligent identification technology has shown the potential to significantly improve production efficiency and optimize yield and quality. By the mid-21st century, demand for food production is expected to reach 50 percent, and there will be enormous pressure to achieve this goal with traditional agricultural technologies, which could be achieved through the application of artificial intelligence. The application of artificial intelligence technology in modern agricultural production will be analyzed in detail in this paper, the guidance of future research fields will be proposed, and the existing challenges and technical problems will be identified and discussed in order to promote the deepening and wide application of intelligent agriculture. This paper specifically discusses examples of applications in orchard management, pest detection, and automated harvesting and summarizes the effectiveness and obstacles of these techniques.

Improvement of methods of rational use in conditions of land degradation in the Almaty region, Karasai district

The study was aimed at identifying the potential of modern methods of rational land use in the Karasai district of the Almaty region of Kazakhstan, taking into account their intensive degradation. The research methodology was represented by the methods of statistical observation, comparison, analytical-structural grouping and forecasting. The priority goals of modernisation of agriculture of the Republic in the technological aspect have been analysed. It was established that innovative approaches to land use have the potential to increase the level of efficiency of the agrarian sector, improve the state of local and regional landscape. The concept of improving the state of degraded lands, including a system of management measures and practical activities, has been developed. It was proved that it should be based on the synergy of economic efficiency and environmental safety, with the mandatory introduction of modern innovative technological approaches. The effectiveness of methods of rational use of degraded lands as an effective tool for the transformation of the agrarian sector has been determined. It was proposed to intensify the development of organic agricultural production, which is positioned as the gentlest for degraded landscapes. It was proved that the implementation of sustainable management of landscape complexes in the innovative context implies the use of information monitoring technology, which anticipates the diagnosis, genesis and forecasting of the state of the studied ecosystems. Such measures will make it possible to develop programmes for the restoration of ecological functions of natural landscapes, which is an integral part of sustainable development programmes. Actualised the situation in the context of ecologisation of land use in Kazakhstan, predicted further destruction of ecosystems of agrarian landscapes in case of use of aggressive methods of soil cultivation. The necessity of introduction of improved methods of rational land use is substantiated, and the specificity of the introduction of organic and biological technologies of agricultural production is outlined, with an indication of tangential risks and challenges in the economic realities of Kazakhstan. The study substantiated that the application of integrated management and ecosystem approach have a synergistic potential to ensure the rational use of land in the Almaty region, the Karasai district in the conditions of their degradation

Influencing Drivers of Agricultural Production Technology of Rice in Burundi

Influencing Drivers of Agricultural Production Technology of Rice in Burundi

An analysis of the effect of agriculture subsidies on technical efficiency: Evidence from rapeseed production in China

This study was conducted to examine the effects of agricultural subsidies on the technical efficiency of agricultural production technology and on factor input. It utilized a random frontier production function, instrumental variable method, and threshold regression model. The data used for this analysis consisted of 609 field yield measurements from the National Rapeseed Industry Technology System in 2020. The findings indicate that agricultural subsidies have a substantial impacts and it increases the technical efficiency of production process. Specifically, these subsidies encourage the use of land resources while inhibiting the use of chemical fertilizers. However, this does not have a significant effect on the utilization of labor and capital resources. Furthermore, the impact of agricultural subsidies on production technology efficiency varies depending on the scale of the farming operation. The subsidies significantly enhance the production technology efficiency of farmers with a business scale of less than 0.67 ha, but do not significantly improve the production technology efficiency of farmers with a business scale exceeding 0.67 ha. To optimize the effectiveness of agricultural subsidy policy, three methods and recommendations are proposed: increasing the overall amount of subsidies, expanding and diversifying the types of subsidies, and refining the process of disbursing subsidies.

DIRECTIONS FOR IMPROVING THE ADMINISTRATIVE AND LEGAL MECHANISM FOR ENSURING FOOD SECURITY IN UKRAINE

The author emphasises that Ukrainian legislation does not contain a comprehensive legal regulation of public administration in the area of ensuring food security of Ukraine. That is why there is an urgent need to reform, first of all, the regulatory support of this function of public administration. The main directions of such reform should be: 1) adoption of a specialised law which would lay down a new legal basis for public administration in the area of food security of Ukraine; 2) improvement of the mechanism of strategic planning of the relevant area of state policy; 3) introduction of European principles and standards of public administration in this area; 4) improvement of interaction between civil society institutions and public administration in the course of public administration in the area of food security of Ukraine. In conclusion, it is emphasised that the new law on food security of Ukraine should clearly define the system of goals and objectives of public administration in the field of food security of Ukraine, delimit the powers and competence of public administration entities within this functional area of their activities, and determine the mechanism for guaranteeing physical and economic access to food and essential goods for everyone. In addition, the Food Security Strategy for the period up to 2030 should be adopted, which should: include the principles of food security generally recognised in the EU; regulate Ukraine’s participation in ensuring global food security; involve digital technologies in agricultural production; and expand cooperation with civil society institutions in the implementation of state policy in this area.

Effect of Partial Substitution of Chemical Fertilizers with Organic Fertilizers on N2O and NO Emissions from a Peach Orchard

Organic fertilizer substitution has been promoted as a weight loss, efficient, and diversified fertilizer substitution technology in agricultural production. However, there is a lack of comprehensive assessment of the impact of organic fertilizers on N2O and NO emissions from orchards. In this study, N2O and NO emissions from peach orchards were observed annually using static dark box-gas chromatography to compare the effects of chemical fertilizer application alone and partial replacement of chemical fertilizer treatment on NO emissions from peach orchards. The results showed that the partial replacement of chemical fertilizers with organic fertilizers reduced the total N2O and NO emissions from peach orchards by 15.0 % and 9.4 %, respectively. The N2O and NO emission factors were reduced by 21.3 % and 21.1 %. The mineral N content of the soil in the organic fertilizer treatment was lower than that in the chemical fertilizer treatment alone. The organic fertilizer treatment increased the contribution of AOA to nitrification and decreased the contribution of AOB, thus reducing N2O and NO from nitrification. In addition, the results of the dual isotope mixing model[δ18O(N2O/H2O) vs. δ15NSP] indicated that the bacterial denitrification/nitrifying bacterial denitrification (bD/nD) process served as the primary pathway for N2O emissions in peach orchards. Partial substitution with organic fertilizers enhanced soil denitrification, resulting in larger reductions in the amounts of N2O and NO. Therefore, partial substitution of organic fertilizer is a viable measure to mitigate nitrogen oxide emissions from orchards and to achieve green and low-carbon development in agriculture.

Effect of digital multimedia on the adoption of agricultural green production technology among farmers in Liaoning Province, China

Agricultural green production technology (AGPT) is essential for the sustainable development of agriculture, yet adoption rates among farmers are often low due to limited access to education and information. Based on the extended technology acceptance model, this study takes Liaoning, a major agricultural province in China, as a representative region to explore how digital multimedia influences the adoption of AGPT by farmers. The findings show that the perceived ease of use of these technologies significantly enhances farmers' intentions to adopt, while perceived risks detract from these intentions. Although digital multimedia effectively promotes AGPT by improving its perceived ease of use and usefulness, its role in mitigating perceived risks is minimal. Based on these results, we recommend that the government improve the quality of information on digital platforms by involving experts in the field and offer specific digital marketing training to potential users to increase the adoption of sustainable agricultural technologies.

A novel transformer-based neural network under model interpretability for improving wheat yield estimation using remotely sensed multi-variables

Timely and accurate yield prediction before wheat harvest is of great significance for food policy formulation and national economic development. Deep learning method gains importance on crop yield estimation and growth monitoring with the rapid development of deep learning models combined with remotely sensed data. However, the problems of nonlinear parameter optimization and long-term dependence in time series data have restricted the improvement of yield estimation accuracy. Transformer model completely abandons the traditional deep learning architecture and is gradually applied to time series tasks due to the advantage in modeling long-term dependence. This study introduced a novel transformer-based deep learning framework to estimate winter wheat yield in the Guanzhong Plain utilizing remotely sensed multi-variables, namely leaf area index (LAI), fraction of photosynthetically active radiation (FPAR) and vegetation temperature condition index (VTCI). The proposed model, called SSA-LSTM-transformer (SLTF), was developed for dealing with above problems under the automatic optimization capability of the sparrow search algorithm (SSA) and the long-term memory advantage of the long short-term memory (LSTM) structure. The findings demonstrated that the SLTF model achieved better estimation accuracy at the county level (R2 = 0.72, RMSE = 488.68 kg/ha) compared with the single transformer model (R2 = 0.61, RMSE = 573.99 kg/ha). The analysis on SLTF model’s performance at sampling sites over different disasters suggested that the model can effectively learn the effects of diseases, lodge and pests on crop yield estimation, which had good generalization ability at all sampling sites (R2 = 0.45, RMSE = 738.63 kg/ha). The Shapley Additive exPlanations (SHAP) approach was employed to evaluate the relative importance of remotely sensed multi-variables to yield and to understand how each input variable influences the estimated yield for global interpretability and local interpretability of the SLTF model. It was found that FPAR played the largest roles in yield estimation with the highest importance value, and FPAR and LAI from late April to late May and VTCI from late March to mid-April were regarded as important features for the estimated yield with high importance value. In conclusion, our findings indicated the potential of SLTF model for winter wheat yield estimation, which contributes to promoting further application of remotely sensed technology for agricultural production.

Survey and Research on the Long-term Mechanism for Increasing Farmers' Income in Anhui Province Empowered by Digital Rural Construction

This article studies the impact of digital village construction on farmers' income increase, and takes Anhui Province as an example for in-depth analysis. The article firstly outlines the background and significance of digital village construction, then discusses in detail the application of digital technology in agricultural production, management, service and rural governance, and analyzes how these applications can promote farmers' income. Then, the article further discusses the impact of regional differences on the role of farmers' income, pointing out that different regions should formulate targeted development strategies according to their own characteristics. Finally, the article summarizes the important achievements and findings of digital village construction in Anhui Province, and puts forward the proposal of constructing an assessment and evaluation index system for digital village construction, with a view to promoting the sustainable development of digital village construction and helping the cause of rural revitalization to flourish.

The future of sustainable farming: An evolutionary game framework for the promotion of agricultural green production technologies

In the context of global climate change and increasing population, transitioning to resource-efficient, environmentally friendly agricultural technologies is essential for sustainability. In this context, the present study is anchored in the theories of information asymmetry and bounded rationality. It constructs a tripartite evolutionary game model under market mechanisms and government guidance, facing the challenges of promoting green agricultural technologies among multiple actors. This model explores the strategic choices and dynamic evolution of these actors under economic incentives and risk perception. The objective of the research is to reveal the dynamic evolutionary trends of stakeholder behavior under different policy intervention conditions and how governments can propel the promotion of green agricultural production technologies through policy instruments. To encompass the impact of historical decisions on the evolutionary process of green technology dissemination, this study employs a Delay Differential Equations (DDE) algorithm that considers historical time lags in its numerical simulations. Through stability analysis and DDE numerical simulations, the research identifies factors influencing the promotion of green agricultural production technologies. The findings indicate that under market mechanisms, there is a risk of “market failure” in the dissemination model of green agricultural technologies. Government participation can provide external incentive support, effectively enhancing the stability and efficiency of the evolutionary game system for promoting green technologies. Simulation results further suggest that government intervention can significantly improve the stability and efficiency of technology promotion. Economies of scale, initial willingness, risk perception, and subsidy intensity are decisive factors in technology adoption. Consequently, policymakers are advised to formulate precise and multifaceted subsidy strategies based on the varying needs of different actors, to stimulate engagement, reduce risk, and encourage widespread adoption of green technologies. This study lays a theoretical groundwork for smallholders and family farms to overcome technology adoption barriers, crucial for sustainable agricultural development. It provides a framework for understanding and addressing these challenges, guiding policymakers in crafting effective green agriculture policies to improve farming efficiency and sustainability.

ТЕНДЕНЦИИ И ПЕРСПЕКТИВЫ РАЗВИТИЯ ЦИФРОВОЙ ТРАНСФОРМАЦИИ В УПРАВЛЕНИИ ДЕЯТЕЛЬНОСТЬЮ ПРЕДПРИЯТИЙ АГРОПРОМЫШЛЕННОГО КОМПЛЕКСА РОССИИ

The scientific article presents an assessment of the current state and potential of digital transformation of enterprises of the agro-industrial complex of Russia. The relevance of the research is related to the general trend of digitalization and the spread of digital technologies that improve production, management and business processes in organizations of various spheres and sectors of the Russian and global economy. The object of the study is the enterprises of the agro-industrial complex of Russia. The subject is the technology of digital transformation of Russian agricultural enterprises. A review of digital technologies in management and agricultural production has been conducted. The measures aimed at ensuring the economic sustainability of Russian agricultural enterprises in the process of solving the tasks of digital transformation are proposed.

Farmland transfer contract performance and green production technology adoption among farmers: evidence from a survey of four provinces in China.

The popularization and use of green production technology is the key to promoting the sustainable development of agriculture. Exploring the path of promoting farmers' adoption of green production technology has important theoretical and practical significance for promoting the green transformation of agriculture and realizing the high-quality development of agriculture. This study examined the impact of contract performance on the adoption of green production technology in the farmland transfer market based on the characteristics of green production technology. An empirical test was conducted using survey data from Heilongjiang, Henan, Zhejiang, and Sichuan Provinces, which differ in agricultural resource endowment and economic development. The results demonstrated that farmland area was positively associated with the number of green production technologies adopted by farmers and use of straw returning, subsoiling, and soil testing for formula fertilization technology. Moreover, improving the performance rates of farmland transfer contracts strengthened the promotional effect of operation scale on green production technology adoption. Using either contract execution or dispute resolution rates to measure contract performance promoted the adoption of green production technology, particularly for large-scale farmers. Therefore, in the publicity and promotion of agricultural green production technology, the government should not only formulate differentiated promotion strategies and support policies based on resource endowment, but also focus on the construction of rural legal systems, which are helpful for building and maintaining a good farmland market order and performance environment, and create conditions for the durability and stability of technology adoption.

Development of Learning Modules for Entrepreneurship Courses to Train The Independence of Agricultural Product Technology Study Program Students

This research aims to produce a learning module for entrepreneurship courses to train student independence. The module was prepared in the form of a printed module. This module was created as an educational tool for entrepreneurship classes in the Faculty of Agriculture's Agricultural Product Technology Study Program, PGRI Banyuwangi University. The technique employed in developing this module is the ADDIE development model, this model is used because the development stages are simpler and the time used is not too long. The study's findings are in the form of an entrepreneurship learning module to determine the feasibility of using this module, trials have been carried out including individual trials and group trials. The individual trial involved 3 students, while the group involved 9 students. In this study, it was found that the confirmation from material experts was 92.5% and the media expert validation was 87.5% so that it could be categorized as very good. It is also carried out limited and group trials with the aim of seeing the feasibility of the products developed. The restricted trial's outcomes were as follows an average of 89.58%, meaning that the average can be categorized as excellent and the results of the group trial obtained an average of 90.26% so that the developed module is categorized as feasible and can train student independence.