High-quality Agricultural Products Research Articles

Development and Effects of Organic Farms in Poland, Taking into Account Their Location in Areas Facing Natural or Other Specific Constraints

Organic farms should, by definition, place particular emphasis on the protection of agricultural soils, landscape care and activities aimed at producing high-quality agricultural products. However, when joining this production system, the farms face many challenges in order to make these contributions to society at the expected level. The main aim of the study is to determine the scale of disproportions in production effects achieved by farms between organic and conventional production systems, taking into account the quality of natural management conditions. An equally important goal is to determine the factors in Polish agriculture that determine whether to conduct this production system. The paper aims to indicate the direction of development of organic farming in the EU, including Poland, based on the Eurostat data for 2012–2020. It was noted that the current development of the organic farming sector in EU member states has been at different rates. In Poland, its development strength largely depends on the presence of ANCs. Nearly ¾ of organic utilized agriculture area (UAA) is located in communes with a large share of them. Organic farms achieve lower production effects in comparison to conventional farms, and their disproportions also depend on the quality of natural farming conditions. In Poland, the personal competences of farmers are also an important determinant in joining organic farming.

Infrared radiation drying application in agriculture

World agricultural products, in general, are very diverse, and Vietnam is no exception. In the current trend, high quality agricultural products are increasingly receiving attention and modern methods are applied to improve their quality. Among many methods for improve quality, the infrared radiation drying method is evaluated to minimize drying time, reduce deterioration of agricultural product quality and limit environmental impact. Therefore, this article focuses on applying infrared radiation drying method to agricultural products composed of seafood. The article describes and compares the technical conditions when drying plants and animals using the infrared radiation drying method in combination with other drying methods.

What Determinants Will Enhance or Constrain the Spatiality of Agricultural Products with Geographical Indications in Northeast China? An Interpretable Learning Approach

Geographical indication (GI) offers a unique protection scheme to preserve high-quality agricultural products and support rural sustainability at the territorial level. However, not all the areas with traditional agricultural products are acknowledged with a GI. Quantifying the contribution of each factor to geographical indication agricultural products (GIAPs) can facilitate the formulation of effective policies to improve rural livelihoods. In this study, the random forest (RF) model was applied to investigate the contribution of multi-perspective factors, including nature, society, agriculture and market, on the distribution of GIAPs, and examined the driving causes using interpretable approaches. The empirical findings demonstrate that the RF model is able to accurately capture most of the important factors characterizing GIAPs and to make out-of-sample predictions of the study units which obtain GIs. This study revealed that natural conditions and market demand were contributing aspects to the disparity of GIAPs in Northeast China. The order of determinants was the category of online GIAPs (CatOn) > the number of online GIAPs (NumOn) > the area of black soil (BlaSoil) > the distance to offline stores selling GIAPs (DisOff). Of these, GIAPs was lower than ybase in parts of districts of Jilin and Heilongjiang Provinces when the area of black soil (BlaSoil) gradually increased. When the category and number of online GIAPs (CatOn and NumOn) were less than 20 and 5, respectively, GIAPs were enhanced, especially for 40% of the districts in Liaoning Province. Deepening understanding of GIAPs helps to better target and tailor sustainable development policies.

ВПЛИВ ПЕРЕДПОСІВНОЇ ОБРОБКИ НАСІННЯ МЕТАБОЛІЧНО АКТИВНИМИ РЕЧОВИНАМИ НА КІЛЬКІСНІ ТА ЯКІСНІ ПОКАЗНИКИ ВРОЖАЮ КОРЕНЕПЛОДІВ МОРКВИ СОРТУ НАНТСЬКА

The development of agriculture necessitates the adoption of new and effective methods to increase yields and enhance product quality. Obtaining high-quality agricultural products is becoming increasingly challenging due to climate variations, soil depletion, and decreasing arable land. These factors underscore the need to explore additional technologies that can enhance the cultivation of crops to meet the demand for quality produce. Pre-sowing seed treatment with metabolically active substances represents one such promising technology.
 The objective of our study was to investigate the impact of metabolically active substances and their combinations on the processes of yield formation and the quality of carrots from the Nantska seed variety. The following substances were used for pre-sowing treatment of carrot seeds: vitamin E, ubiquinone-10, paraoxybenzoic acid (POBA), methionine, and magnesium sulfate (MgSO4).
 Our findings revealed a positive influence of metabolically active compounds on various parameters, including root length, thickness, average root mass, and sugar content in the carrots. The combination of substances, specifically vitamin E + POBA + methionine + MgSO4, exhibited the most significant effect on root length throughout the growth period, surpassing control measurements by 5.23 % to 14.5 1%, depending on the stage of the study. All tested compounds, except for the vitamin E solution, had a favorable impact on the average root mass. Pre-sowing seed treatment with ubiquinone-10 resulted in the highest monosaccharide content in carrot roots after one month of storage, surpassing control measurements by 13.2 %. Although the monosaccharide and disaccharide content in carrot roots decreased during storage in all studied conditions, it remained higher compared to the control measurements, indicating enhanced nutritional value.
 In summary, pre-sowing seed treatment of carrots with metabolically active compounds and their combinations demonstrates the potential to improve both quantitative harvest indicators and sugar content in carrot roots, reflecting increased nutritional value. Incorporating pre-sowing treatment with metabolically active compounds into cultivation practices can be valuable in the production of vegetable crops.

The Effects of FC and CSR on Bilateral Quality Efforts of Agricultural Products Supply Chain

The aim of this study was to analyze the effect of fairness concern (FC) and corporate social responsibility (CSR) on the quality improvement of the agricultural product supply chain (APSC) composed of an agricultural product processor (processor) and an agricultural product supermarket (supermarket) so as to ensure the stable supply of high-quality agricultural products. This paper considered both FC and CSR, established four Stackelberg game models, and obtained the effects of FC and CSR on bilateral quality efforts in APSC through comparative analysis and numerical analysis. We prove that the supermarket’s FC can take the role of “profit distribution mechanism”, but it is not conducive to improving all bilateral quality efforts, the utility of the whole supply chain system, and consumer surplus. Additionally, APSC members sharing CSR can not only both improve the quality of agricultural products and promote the expansion of market demand, but they also can improve both the profit of all members and the supply chain. The CSR shared by both members has a greater impact on bilateral quality efforts than the supermarket’s FC, and thus the positive effect of CSR can overcome the negative effect of the supermarket’s FC.

The Design and Simulation of Autonomous Agricultural Vehicle for Orchards

In recent years, agricultural producers have faced challenges due to the uncertainty of labor force access, growing demand for safe, accessible, and high-quality agricultural products, high competition with international producers, and the need to reduce their carbon footprint. To continue their competitive and profitable production, producers must invest in technology and increase efficiency. Autonomous agricultural vehicles are crucial for autonomous processes in orchards, increasing productivity, collecting data for decision-making, reducing operating costs, and carbon footprint. This study focuses on the design and simulation of an autonomous vehicle for orchards. The autonomous vehicle can map the orchards using data from odometry and light detection and ranging (LIDAR) sensors by utilizing Simultaneous Localization and Mapping (SLAM) algorithm, accurately determine its position using the Adaptive Monte Carlo Localization method, and avoid obstacles using the dynamic window approach algorithm. The autonomous vehicle is an original design for netted orchards where GPS cannot work properly and is fully autonomous, requiring no external GPS data. It is expected to provide higher efficiency by reducing environmental pollution, operating expenses, and labor force in practice. The success of the mapping and localization application depends on the update frequency of the position and the number of particles used for localization. A path-planning application was developed to reach the desired position from the autonomous agricultural vehicle's current position on the map. The Dijkstra Algorithm was used for path planning, with the Dynamic Window Approach allowing the robot to escape obstacle. The simulation studies achieved the lowest position error when the vehicle's position was updated at intervals of 2 cm, and a minimum of 500 and a maximum of 2000 particles were used. While the vehicle was moving on a straight obstacle row in the simulation environment, an average localization error of 2.1 cm was obtained. This error is convenient as it enables seamless navigation between tree rows without any collision.

Review on Pesticide Abiotic Stress over Crop Health and Intervention by Various Biostimulants.

Plants are essential for life on earth, and agricultural crops are a primary food source for humans. For the One Health future, crop health is crucial for safe, high-quality agricultural products and the development of future green commodities. However, the overuse of pesticides in modern agriculture raises concerns about their adverse effects on crop resistance and product quality. Recently, biostimulants, including microecological bacteria agents and nanoparticles, have garnered worldwide interest for their ability to sustain plant health and enhance crop resistance. This review analyzed the effects and mechanisms of pesticide stress on crop health. It also investigated the regulation of biostimulants on crop health and the multiomics mechanism, combining research on nanoselenium activating various crop health aspects conducted by the authors' research group. The paper helps readers understand the impact of pesticides on crop health and the positive influence of various biostimulants, especially nanomaterials and small molecules, on crop health.

Comparative Analysis of Fruit Disease Identification Methods: A Comprehensive Study

The need for accurate and efficient technologies for recognising and controlling fruit diseases has increased due to the rising global demand for high-quality agricultural products. This study focuses on the advantages, disadvantages, and potential practical applications of a range of methods for identifying fecundities. Thanks to developments like improved imaging, machine learning, and data analysis tools, old methods of disease diagnosis have altered as technology has developed. The study compares older methods like visual observation, manual symptom correlation, spectroscopy, and chemical procedures with more contemporary methods like computer vision, autonomous learning algorithms, and sensor-based technologies. Precision, efficiency, cost, scalability, and ease of use are used to describe each method's effectiveness. The article reviews the research examples and practical applications of fruit endocrine disease detection in different cultivars and areas to provide a thorough comparison. This comparison focuses on the variations in disease prevalence and the ways that alternative treatments can be customised to certain situations.It is for this reason that this study offers useful information on how the methods for detecting fruit rot have evolved through time. It emphasises the significance of utilising technological advances to enhance the accuracy, effectiveness, and long-term sustainability of the management of agricultural diseases. Based on the unique requirements of their various agricultural systems, this analysis can assist researchers, practitioners, and policymakers in selecting the most effective methods for identifying fruit diseases.

How to promote the adoption of intelligent spray technology in farmers’ cooperatives? ——Based on the perspective of evolutionary game

In order to accelerate the development of smart agriculture and realize the green transformation of agriculture, the coupling of prospect theory and evolutionary game theory is introduced. Construct a two-party evolutionary game model for the adoption of intelligent spray technology in farmers' cooperatives, analyze the evolution of farmers' cooperatives and government strategy selection and its influencing factors according to the replication dynamic equation, and conduct numerical simulation experiments through Matlab software. The results show that the adoption of intelligent spray technology by farmers' cooperatives and the government's choice of subsidies are the two optimal stable states of the evolutionary system. The government's subsidy policy can effectively stimulate farmers' cooperatives to adopt intelligent spray technology, but when the government subsidy coefficient is greater than or equal to 70%, the decision-making evolution of the government and farmers' cooperatives is unstable. The increase in farmers' awareness of pesticide hazards, the scale of operation of farmers' cooperatives, the price of high-quality agricultural products, and the sensitivity of farmers' cooperatives to profits and losses contribute to the promotion of intelligent spray technology, and the damage probability of intelligent spray technology has a restraining effect.

Ensemble learning-based applied research on heavy metals prediction in a soil-rice system

Accurate prediction of heavy metal accumulation in soil ecosystems is crucial for maintaining healthy soil environments and ensuring high-quality agricultural products, as well as a challenging scientific task. In this study, we constructed a dataset containing 490 sets of multidimensional environmental covariate data and proposed prediction models for heavy metal concentrations (HMC) in a soil–rice system, EL-HMC (including RF-HMC and GBM-HMC), based on Random Forest (RF) and Gradient Boosting Machine (GBM) ensemble learning (EL) techniques. To reasonably evaluate the effectiveness of each model, Multiple linear and Bayesian regressions were selected as benchmark models (BM), and mean absolute error (MAE), root mean square error (RMSE), and determination coefficient R2 were selected as evaluation indicators. In addition, sensitivity and spatial autocorrelation (SAC) analyses were used to examine the robustness of the model. The results showed that the R2 values of RF-HMC and GBM-HMC for modeling available cadmium (Cd) concentrations in soil were 0.654 and 0.690, respectively, with an average increase of 48.0 % compared to the BMs. The R2 values of RF-HMC and GBM-HMC for predicting Cd, lead (Pb), chromium (Cr), and mercury (Hg) concentrations in rice ranged from 0.618 to 0.824 and 0.645 to 0.850, respectively, with an average increase of 58.2 % compared with the BMs. The corresponding MAEs and RMSEs of RF-HMC and GBM-HMC had low error levels. Sensitivity analysis of the input features and the SAC of the prediction bias showed that the EL-HMC models have excellent robustness. Therefore, the EL technology-based prediction models for HMCs proposed herein are practical and feasible, demonstrating better accuracy and stability than the traditional model. This study verifies the application potential of EL technology in pollution ecology and provides a new perspective and solution for sustainable management and precise prevention of heavy metal pollution in farmland soil at the regional scale.

Analysis on Trade Competition and Complementarity of High-Quality Agricultural Products in Countries along the Belt and Road Initiative

The Belt and Road Initiative was proposed by China in 2013 as a response to sluggish global economic growth. With most countries along the Belt and Road being developing countries, it is crucial to strengthen trade cooperation in agricultural products. However, the current literature lacks an analysis of the competitiveness and complementarity of agricultural products in these countries. This study aims to fill this gap by showing that the Belt and Road Initiative has reduced agricultural export competitiveness and increased agricultural trade complementarity. Several factors influence the similarity and complementarity of agricultural exports in participating countries along the Belt and Road, including geographical distance, level of economic development, free trade agreements, degree of country openness, exchange rates, cultural differences, share of agricultural value added, and level of infrastructure. The detailed analysis shows that the Belt and Road Initiative has significantly improved the quality of the agricultural exports of participating countries. The results of this paper provide a theoretical basis for the high-quality development of agricultural products in participating countries along the Belt and Road.

UNDERSTANDING FARMERS’ BAHAVIOUR REGARDING PESTICIDE USE IN VOJVODINA REGION

Requirements to provide high and stable yields and highquality agricultural products at reasonable prices are hard to meet without any use of pesticides. However, in addition to significant positive effect their application often has adverse effects on human health and environment. This study aims to uncover crop farmers’ behaviour regarding pesticide use in Serbia’s region of Vojvodina. The research was conducted based on farmers’ self-assessment regarding the application of pesticides. The results show that farmers have a serious and responsible approach concerning certain aspects of pesticide use. They generally follow recommendations, particularly concerning the preharvest interval, as well as the washing and maintenance of equipment. However, they often neglect other aspects, especially those related to their own safety protection. The study concludes that the mechanisms of appropriate sharing of information and farmers’ education should be addressed by decision-makers and that the advisory service should play a strong role in this process.

Evaluation of Agricultural Green Development Based on Gini Coefficient and Hesitation Fuzzy Multi-Attribute Decision-Making: The Case of China

In order to systematically solve the problem of formulating agricultural green development strategies based on the four dimensions of policy green, industry green, science and technology green, and awareness green, this paper uses the method of combining the Gini coefficient with hesitation fuzzy multi-attribute decision-making to carry out research. The research shows that: (1) The three most critical factors affecting the green development of agriculture are “consumers’ awareness of purchasing green agricultural products”, “investment in the construction of rural ecological civilization” and “the number of farmers’ scientific and technological training”, and the corresponding index weights are 0.12, 0.1 and 0.1, respectively. (2) There are differences in policy, industry, science and technology, and consciousness in the green development of agriculture. The green development of policy shows an obvious upward trend. The industrial green development shows a relatively gentle upward trend. The green development of science and technology showed rapid growth from 2011 to 2017, and the growth slowed down in the following two years and showed a downward trend in 2020. The awareness of green development shows a relatively stable upward trend. (3) The green development of agriculture is jointly driven by the relevant interests of the supply side, the demand side, and the regulator, and the demand side’s requirements for high-quality agricultural products become a stronger driving force for the green development of agriculture. The change in the consciousness and thinking of agricultural product producers on the supply side has become the basis for the green development of agriculture, and the implementation of government policies has become an important guarantee for the green development of agriculture. The innovation of this paper is to build an evaluation index system including government, consumers, farmers’ awareness of multiple subjects, government policies at all levels, industrial production status, and agricultural production technology. At the same time, we build an evaluation model that can comprehensively analyze quantitative and qualitative indicators. In view of the need for a holistic analysis of the agricultural system in the study of agricultural green development, future studies will include air pollution emissions and agricultural transport services in the evaluation model to improve the scientific and universal model.

The Evolving Status of Agricultural Products in the Global Value Chain since China and Kyrgyzstan Established Diplomatic Relations

Central Asia borders China and was the first stop of China’s opening to the west. Studying the evolving status of agricultural products in the global value chain since China and Kyrgyzstan established diplomatic relations in 1992 can facilitate China’s “Belt and Road” initiative and strengthen agricultural cooperation. Based on FAOSTAT and UN Comtrade data, this paper classifies agricultural products into three categories: primary agricultural products, rough-processed agricultural products, and deep-processed industrial products. An indicator system was constructed for measuring the status of agricultural products in the global value chain. Using the results of the NET trade index, this paper analyzed the evolving status of Chinese and Kyrgyzstani agricultural products in the global value from 1995 to 2020. The results showed that the status of Chinese and Kyrgyzstani primary agricultural products has continued to decline, with Kyrgyzstan slightly better than China. The status of Chinese rough-processed agricultural products was slowly declining, while Kyrgyzstan’s status dropped sharply by 2020. China has a solid foundation in deep-processed agricultural products, while Kyrgyzstan’s status was relatively low. Suggestions for future cooperation between China and Kyrgyzstan are discussed, such as strengthening agricultural technology exchanges and cooperation, expanding trade in high-quality agricultural products, etc.

Regional-scale assessment of soil functions and resilience indicators: Accounting for change of support to estimate primary soil properties and their uncertainty

Researchers and stakeholders are increasingly interested in evaluating soil functions and their relationships with soil physical resilience to prevent and mitigate natural and anthropogenic threats. This study aims to assess the effect of changing spatial support on estimating primary soil properties that are then used to map compound indicators of soil functions. The specific objectives are to determine the epistemic uncertainty associated with the estimates and assess the impact of accounting for the change-of-support when scaling up from the point- to the block-resolution.The study area is the southern Italian region of Campania, which is renowned for its high-quality agricultural and dairy products but is increasingly subject to soil disturbance and degradation. Seven primary soil properties (sand and clay contents, oven-dry soil bulk density, calcium carbonate, rock fragment, soil organic matter, and pH) were estimated over 75-m × 75-m blocks by jointly analyzing more than 3,000 point-based soil measurements with gridded terrain attributes by using multi-collocated block cokriging. Two compound soil indicators were then assessed from the maps of these soil properties: 1) the soil organic carbon stock (SOCS) in the entire region of Campania, and 2) the recharge transit time in the Sele alluvial plain where information about the mean annual depth to groundwater is available.The change-of-support proved to affect the total variance and the assessment of the extremes in the probability distributions of the primary soil variables. Our results emphasize that negative consequences occur when the change-of-support problem, upscaling in particular, is overlooked as happens when analyzing environmental data, especially for planning purposes and in the case of environmental risk assessment.

Factors Influencing the Chance of Inheriting the Family Farming Career among Heirs in the Upper Northern Region of Thailand in the Crisis of Farming Labor Decline

The aging society of farmers and lack of motivation to pursue a farming career among farmers’ young heirs could induce a severe labor shortage crisis in the farming sector in Thailand in the near future, especially in the upper northern region, which has been officially declared as the base of the organic agricultural production of the country. The main problem is the decision of farmers’ heirs to inherit or not inherit the farming career of their families. The relevant factors and their effects on the decision must be investigated and analyzed. A set of descriptive statistical tools were used to analyze the significance of each factor. A prediction model based on logistic regression was applied to analyze how sensitive of each factor is to the decision to inherit the family farming career. The discovered results could help the federal organization to plan and establish an appropriate strategy in order to cope with the crisis. Here, there are 519 surveyed samples referring to farmers’ heirs from five provinces in the upper northern region, which are Chiang Mai, Chiang Rai, Nan, Lamphun, and Mae Hong Son. The data were collected using a questionnaire. The following 10 relevant factors were found to have direct impacts on the decision to inherit the farming career: gender, increased age, marital status, increased yearly income, the chance to obtain advice from the Federal Department of Agricultural Extension, attitudes towards the farming career, an increase in the land size for farming per family, increase in the land size for farming in the rural area, the variety of agricultural products produced by the family, and an increased set of farming equipment and tools possessed by the family. However, an increase in the number of new family members could lead to unwillingness to inherit the farming career. All these factors in both the willing and unwilling groups had a statistical significance at the level of 0.05. Since the sample size of the willing group was considerably larger than the sample size of the unwilling group, a technique of minority oversampling was adopted to alleviate the problem of the imbalanced datasets. The classification accuracy obtained was 77.56. In addition to the federal planning and strategies applied to ease the crisis, the factors discovered in this study can be used as a stimulus for persuading and stimulating the young generation to inherit the farming career or become a skillful as well as knowledgeable professional farmer capable of producing high-quality agricultural products for the upper northern region of Thailand.

КОНФІГУРАЦІЯ ЦІННОСТЕЙ РЕСУРСНОГО ПОТЕНЦІАЛУ РОЗВИТКУ СІЛЬСЬКИХ ТЕРИТОРІЙ

The article is devoted to revealing the values of the resource potential of rural areas and the formation of configurations for their effective economic use. Rural areas are traditionally the basis and source of resource potential formation. Traditionally, rural areas not only provide industrial areas with food and raw materials, but are also a source of human resources and initial capital accumulation. In recent years, the role and value of the resource potential of rural areas has been steadily growing. The article highlights three levels of configuration of values of the resource potential of rural areas: ecological values, socio-cultural values, community values. For the development of the resource potential of rural areas, ecological values are one of the most important resources. Environmental protection has become the basis of the policy of implementing an ecological (green) economy, and the values of the resource potential of rural areas are recognized as the most important public goods. The list of socio-cultural factors includes special, high-quality agricultural products, local cuisine, folk music, minority languages, anthropogenic environment, arts and crafts, etc. Thanks to these factors, the available resource potential of these territories is growing. The values of the community are also often considered as the values of the resource potential of rural areas. Social networks, family relationships, mutual trust and understanding are important to all human communities, regardless of where they live. In fact, community values are closely related to human resources, and their absence in certain areas can seriously limit the possibilities of rural areas. The given values of the resource potential of rural areas are quite different. They can bring various advantages and opportunities for the development of rural areas. For the perspective of harmonious development of rural areas, it is necessary to take into account, use and consolidate as many different values of the resource potential of rural areas as possible.

ИСТОЧНИКИ ДОЛГОСРОЧНЫХ ИНВЕСТИЦИЙ В АПК В УСЛОВИЯХ НЕСТАБИЛЬНОСТИ

The most important system-forming sector of the economy is the agro-industrial complex, which ensures the food security of the state, and also combines production, processing, delivery of agricultural products to end consumers, and influences the sustainability of the functioning of all its participants. The socio-economic stability and food security of the state depend on the level of development of the country’s agro-industrial complex. Today the state strives to bring the domestic agro-industrial complex to a higher level, to make it highly efficient, technologically advanced and competitive. The main task is to increase the reliability of supplying the country with high-quality agricultural products. The main basis for the development of agriculture is investment. Investment policy in the Russian agro-industrial sector is a priority. For many years, scientists have highlighted the importance of contributions to the agricultural sector, since it is long-term investments that contribute to the development of agricultural production based on modern technologies. The article examines the main sources of financing for agricultural sectors, the importance of investments for agriculture, and reveals the main directions of state policy in terms of ensuring the investment attractiveness of the agricultural industry.

Multispectral Crop Yield Prediction Using 3D-Convolutional Neural Networks and Attention Convolutional LSTM Approaches

In recent years, national economies are highly affected by crop yield predictions. By early prediction, the market price can be predicted, importing, and exporting plan can be provided, social, and economic effects of waste products can be minimized, and a program can be presented for humanitarian food aid. In addition, agricultural fields are constantly growing to generate products required. The use of machine learning (ML) methods in this sector can lead to the efficient production and high-quality agricultural products. Traditional predictive machine models were unable to find nonlinear relationships between data. Recently, there has been a revolution in prediction systems via the advancement of ML, which can be used to achieve highly accurate decision-making networks. Thus far, many strategies have been used to evaluate agricultural products, such as DeepYield, CNN-LSTM, and ConvLSTM. However, preferable prediction accuracy is required. In this study, two architectures have been proposed. The first model includes 2D-CNN, skip connections, and LSTM-Attentions. The second model comprises 3D-CNN, skip connections, and ConvLSTM Attention. The Input data given from MODIS products such as Land-Cover, Surface-Temperature, and MODIS-Land-surface from 2003 to 2018 on the county level over 1800 counties, where soybean is mainly cultivated in the USA. The proposed methods have been compared with the most recent models. Then, the results showed that the second proposed method notably outperformed the other techniques. In case of MAE, the second proposed method, DeepYield, ConvLSTM, 3DCNN, and CNN-LSTM obtained 4.3, 6.003, 6.05, 6.3, and 7.002, respectively.

PRODUCTIVITY OF MELILOT (MELILOTUS OFFICINALIS (L.)) IN THE CONDITIONS OF RICE CROP ROTATION UNDER THE KYZYLORDA REGION

In the unfavorable environmental conditions of the Kyzylorda region, associated primarily with water scarcity, salinization and soil degradation, measures are needed for the cultivation of agricultural land and reproduction of soil fertility, associated with phyto-reclamation, the complex use of organic and mineral fertilizers, cultivation and introduction of salt-resistant crops, in particular legumes of perennial grasses, which, undoubtedly, it will become the basis for optimal functioning of agroecosystems, stable development of crop production diversification in order to obtain high-quality agricultural products. Melilotus, being an excellent pasture legume plant for restoring vegetation cover of saline soils, will make it possible to obtain high yields of off-season pasture production in territories that are currently unproductive.The article presents the results of studies to determine the effect of organomineral fertilizers on the yield and productivity elements of the clover. It was found that of the various studied norms of organomineral fertilizers, applying phosphorus fertilizers at a dose of P60 is the most effective, providing a stable and reliable increase in crop productivity by 53.5%. And the introduction of organomineral fertilizer "manure 15 t / ha + P60", where the highest yield of hay was 87.7 c / ha, the authors consider it ineffective, since the yield difference between them (2.2 c / ha) is insignificant, which is lower than the value of LSD05 = 4.7 c / ha. Variants of phosphorus fertilizers and a combination of manure of 15 t/ha with P60 had a significant impact on the quality and nutritional value of the melilot feed, where the protein content in the 1st year of the melilot life increased to 280.2 and 302.4 kg/ha, and in the 2nd year of life to 591.9 and 608.4 kg/ha.