Quality Of Agricultural Products Research Articles

Research on the Maturity Detection Method of Korla Pears Based on Hyperspectral Technology

In this study, hyperspectral imaging technology with a wavelength range of 450 to 1000 nanometers was used to collect spectral data from 160 Korla pear samples at various maturity stages (immature, semimature, mature, and overripe). To ensure high-quality data, multiple preprocessing techniques such as multiplicative scatter correction (MSC), standard normal variate (SNV), and normalization were employed. Based on these preprocessed data, a custom convolutional neural network model (CNN-S) was constructed and trained to achieve precise classification and identification of the maturity stages of Korla pears. Additionally, a BP neural network model was used to determine the characteristic wavelengths for maturity assessment based on the sugar content feature wavelengths. The results demonstrated that the BP model, based on sugar content feature wavelengths, effectively discriminated the maturity stages of the pears. Specifically, the comprehensive recognition rates for the training, testing, and validation sets were 98.5%, 93.5%, and 90.5%, respectively. Furthermore, the combination of hyperspectral imaging technology and the custom CNN-S model significantly enhanced the detection performance of pear maturity. Compared to traditional CNN models, the CNN-S model improved the accuracy of the test set by nearly 10%. Moreover, the CNN-S model outperformed existing techniques based on partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) in capturing hyperspectral data features, showing superior generalization capability and detection efficiency. The superior performance of this method in practical applications further supports its potential in smart agriculture technology, providing a more efficient and accurate solution for agricultural product quality detection. Additionally, it plays a crucial role in the development of smart agricultural technology.

Utilizing deep learning via computer vision for agricultural production quality control: jackfruit growth stage identification

Jackfruit (Artocarpus heterophyllus), a tropical fruit renowned for its diverse culinary uses, necessitates identifying the optimal growth stage to ensure superior flavor and texture. This research investigates employing deep learning techniques, particularly convolutional neural networks (CNNs), for accurately detecting jackfruit growth stages. Despite the challenge posed by the nuanced visual differences among fruits at various maturity stages, a meticulously curated dataset of labeled jackfruit images was developed in collaboration with experts, utilizing the BBCH scale. This dataset facilitated training and evaluation. A modified version of the Places 365 GoogLeNet CNN model was proposed for classifying four distinct growth stages of jackfruit, compared with a state-of-the-art CNN model. The trained models demonstrated varying levels of accuracy in classification. Furthermore, the proposed CNN model was trained and tested using original and augmented images, achieving an impressive overall validation accuracy of 90%. These results underscore the efficacy of deep learning in automating the detection of growth stages, offering promising implications for quality control and decision-making in jackfruit production and distribution.

Sosialisasi Konsep Pertanian Berkelanjutan Di Kampung Napua Distrik Napua Kabupaten Jayawijaya

Traditional agriculture implemented in Napua Village, Napua, Jayawijaya indirectly has a negative impact on the environment and the sustainability of food production. Socialization and assistance regarding the concept of sustainable agriculture is important to increase farmers' awareness in implementing more environmentally friendly and sustainable agricultural practices. This service activity aims to provide farmers with an understanding of the concept of sustainable agriculture. The implementation method is socialization in the form of delivering material about sustainable agriculture and assistance to farmer groups in practicing the concept of sustainable agriculture. The results of this socialization activity are the emergence of farmer awareness about the factors causing the decline in the quality and quantity of agricultural products in Napua Village and increased knowledge about the concept of sustainable agriculture as a solution to the problems.

Market Participation and Farmers’ Adoption of Green Control Techniques: Evidence from China

As a standard clean production technology, the wide use of green control techniques (GCT) helps improve the quality of agricultural products and protect the environment. However, the level of application of GCT by Chinese farmers is not high. The market, as the ultimate place to realize the value of grain and the returns of grain farmers, plays an essential part in promoting GCT. Based on survey data from grain farmers in Sichuan Province, China, this study used a conditional mixed process (CMP) model to examine the effect of farmers’ market participation on their GCT adoption behavior and a mediated effects model to test the impact mechanism. The study further explored the effect of farmers’ market participation capability on their GCT adoption behavior. The results showed that (1) farmers’ market participation could significantly increase the likelihood of adopting GCT. (2) Market participation could influence farmers’ adoption behavior through agricultural income, market information, and green cognition. (3) Further research found that farmers were more likely to adopt GCT if their market participation capability was strong. These findings highlight the fact that developing countries have increased their efforts to encourage farmers to participate in markets and to enhance their market participation capability, thereby facilitating the adoption of GCT by farmers.

Farmers' Biosecurity Awareness in Small-Scale Alpine Dairy Farms and the Crucial Role of Veterinarians.

Biosecurity measures are essential to improve animal health and welfare, tackle antimicrobial resistance (AMR), minimize the burden of infectious diseases, and enhance the safety, security, and quality of sustainable agricultural products. However, the implementation of these measures in small mountain farms can be influenced by several factors, which probably differ from the main variables that affect intensive farming systems. This study investigated the awareness among farmers regarding the implementation of biosecurity measures at the local level in small dairy farms located in the Autonomous Province of Bolzano/Bozen (Italy). In order to determine to what extent these measures are in line with the recommendations, a questionnaire was conceptualized and sent by post to a representative group of local farmers. The initiative was voluntary and anonymous. A total of 50 farmers responded to the questionnaire, resulting in a response rate of 27.5%. This study confirms that most of the farmers are familiar with biosecurity, and 38% of them know its comprehensive definition. The results indicate that 77% of respondents are willing to implement preventive measures to reduce the use of antimicrobials, and 76% of them acknowledge that they would follow the recommendations provided by veterinarians. In agreement with other studies, the role of the veterinarian as a person of trust among farmers is confirmed. Main strengths and areas of improvement have been identified. Additional data and effective tools are needed to better investigate drivers toward biosecurity and to implement impactful and practical measures for mountain farming.

КОНТРОЛЬ ЧРЕЗВЫЧАЙНОГО ЗАГРЯЗНЕНИЯ ВОЗДУХА ТРАНСПОРТОМ САНКТ-ПЕТЕРБУРГА ПО КРИТЕРИЯМ НАНОСИМОГО УЩЕРБА

In the aspect of the triple planetary crisis, expressed by climate warming, reduction in biological diversity of species and habitat pollution, the problem of emergency control of the dangerous impact of vehicle exhaust gases on the living conditions of citizens in Saint-Petersburg is being studied. Control is carried out according to the criteria of expected «uncompensated costs» using original models and calculation algorithms adapted to the real conditions of the transport being used and the financial and demographic social environment. Calculation estimates of critical, in particular, extreme accumulation in the air of soot particles, oxides of sulfur, nitrogen, carbon and hydrocarbons are provided. Assessments are expressed in physical and monetary indicators, monitored by the negative effects of health problems, deterioration in the quality of agricultural products, «damage» to infrastructure elements, and climate warming.

Enhancing irrigation water quality efficiently with potassium feldspar-derived adsorbent: Heavy metal detoxification and nutrient augmentation

The pollution of Pb2+ and Cd2+ in both irrigation water and soil, coupled with the scarcity of vital mineral nutrition, poses a significant hazard to the security and quality of agricultural products. An economical potassium feldspar-derived adsorbent (PFDA) was synthesized using potassium feldspar as the main raw material through ball milling-thermal activation technology to solve this problem. The synthesis process is cost-effective and the resulting adsorbent demonstrates high efficiency in removing Pb2+ and Cd2+ from water. The removal process is endothermic, spontaneous, and stochastic, and follows the quasi-second-order kinetics, intraparticle diffusion, and Langmuir model. The adsorption and elimination of Pb2+ and Cd2+ is largely dependent on monolayer chemical sorption. The maximum removal capacity of PFDA for Pb2+ and Cd2+ at room temperature is 417 and 56.3 mg·g−1, respectively, which is superior to most mineral-based adsorbents. The desorption of Pb2+/Cd2+ on PFDA is highly challenging at pH≥3, whereas PFDA and Pb2+/Cd2+ are recyclable at pH≤0.5. When Pb2+ and Cd2+ coexisted, Pb2+ was preferentially removed by PFDA. In the case of single adsorption, Pb2+ was mainly adsorbed onto PFDA as Pb2SiO4, PbSiO3·xH2O, Pb3SiO5, PbAl2O4, PbAl2SiO6, PbAl2Si2O8, Pb2SO5, and PbSO4, whereas Cd2+ was primarily adsorbed as CdSiO3, Cd2SiO4, and Cd3Al2Si3O12. After the complex adsorption, the main products were PbSiO3·xH2O, PbAl2Si2O8, Pb2SiO4, Pb4Al2Si2O11, Pb5SiO7, PbSO4, CdSiO3, and Cd3Al2Si3O12. The forms of mineral nutrients in single and complex adsorption were different. The main mechanisms by which PFDA removed Pb2+ and Cd2+ were chemical precipitation, complexation, electrostatic attraction, and ion exchange. In irrigation water, the elimination efficiencies of Pb2+ and Cd2+ by PFDA within 10 min were 96.0 % and 70.3 %, respectively, and the concentrations of K+, Si4+, Ca2+, and Mg2+ increased by 14.0 %, 12.4 %, 55.7 %, and 878 %, respectively, within 60 min. PFDA holds great potential to replace costly methods for treating heavy metal pollution and nutrient deficiency in irrigation water, offering a sustainable, cost-effective solution and paving a new way for the comprehensive utilization of potassium feldspar.

Empirical Research on Factors Influencing Chinese Farmers’ Adoption of Green Production Technologies

During a critical period of structural reform in China’s agricultural supply chain, accelerating the promotion and application of green production technologies emerges as a pivotal strategy to ensure the quality and safety of agricultural products while advancing agricultural modernization. This study empirically examines the factors influencing farmers’ adoption of green production technologies using an ordered logistic model based on survey data collected from 533 respondents in Shandong Province. The survey targeted regions where major economic crops such as corn and soybeans are cultivated, employing simple random sampling to ensure the data’s representativeness and reliability. The findings underscore several critical factors influencing farmers’ willingness to adopt green production technologies, including the presence of quality inspections, evaluations of restrictions on prohibited pesticide use, sales performance of green products, availability of government subsidies, and traceability of agricultural products. To foster greater adoption of green production technologies and propel the transformation of China’s agriculture, it is recommended to advocate and guide green agricultural practices, enhance green agricultural subsidy policies, and strengthen agricultural product market management systems. These measures are essential for ensuring sustainable agricultural development in China.

Enhanced data preprocessing with novel window function in Raman spectroscopy: Leveraging feature selection and machine learning for raspberry origin identification

In this study, a simple and accurate approach is proposed for enhancing the origin identification of raspberry samples using a combination of innovative Raman spectral preprocessing techniques, feature selection, and machine learning algorithms. Window function was creatively introduced and combined with baseline removal technique to preprocess the Raman spectral data, reducing the dimensionality of the raw data and ensuring the quality of the processed data. An optimization process was conducted to determine the optimal parameter for the window function, resulting in a binning window width of 5 that yielded the highest accuracy. After applying three feature selection techniques, it was found that the information gain model had the best performance in extracting discriminative spectral features. Finally, ten different machine learning algorithms were employed to construct predictive models, and the optimal models were selected. Linear Support Vector Classifier (LinearSVC), Multi-Layer Perceptron Classifier (MLPClassifier), and Linear Discriminant Analysis (LDA) achieve accuracy, precision, recall, and F1 values above 0.96, while the Random Vector Functional Link Network Classifier (RVFLClassifier) surpasses 0.93 for these performance metrics. These results demonstrate the effectiveness of the proposed approach in identifying the origin of raspberry samples with high accuracy and robustness, providing a valuable tool for agricultural product authentication and quality control.

Plant leaf disease recognition based on improved SinGAN and improved ResNet34.

The identification of plant leaf diseases is crucial in precision agriculture, playing a pivotal role in advancing the modernization of agriculture. Timely detection and diagnosis of leaf diseases for preventive measures significantly contribute to enhancing both the quantity and quality of agricultural products, thereby fostering the in-depth development of precision agriculture. However, despite the rapid development of research on plant leaf disease identification, it still faces challenges such as insufficient agricultural datasets and the problem of deep learning-based disease identification models having numerous training parameters and insufficient accuracy. This paper proposes a plant leaf disease identification method based on improved SinGAN and improved ResNet34 to address the aforementioned issues. Firstly, an improved SinGAN called Reconstruction-Based Single Image Generation Network (ReSinGN) is proposed for image enhancement. This network accelerates model training speed by using an autoencoder to replace the GAN in the SinGAN and incorporates a Convolutional Block Attention Module (CBAM) into the autoencoder to more accurately capture important features and structural information in the images. Random pixel Shuffling are introduced in ReSinGN to enable the model to learn richer data representations, further enhancing the quality of generated images. Secondly, an improved ResNet34 is proposed for plant leaf disease identification. This involves adding CBAM modules to the ResNet34 to alleviate the limitations of parameter sharing, replacing the ReLU activation function with LeakyReLU activation function to address the problem of neuron death, and utilizing transfer learning-based training methods to accelerate network training speed. This paper takes tomato leaf diseases as the experimental subject, and the experimental results demonstrate that: (1) ReSinGN generates high-quality images at least 44.6 times faster in training speed compared to SinGAN. (2) The Tenengrad score of images generated by the ReSinGN model is 67.3, which is improved by 30.2 compared to the SinGAN, resulting in clearer images. (3) ReSinGN model with random pixel Shuffling outperforms SinGAN in both image clarity and distortion, achieving the optimal balance between image clarity and distortion. (4) The improved ResNet34 achieved an average recognition accuracy, recognition precision, recognition accuracy (redundant as it's similar to precision), recall, and F1 score of 98.57, 96.57, 98.68, 97.7, and 98.17%, respectively, for tomato leaf disease identification. Compared to the original ResNet34, this represents enhancements of 3.65, 4.66, 0.88, 4.1, and 2.47%, respectively.

SPATIAL EVOLUTION OF ORGANIC FARMLAND IN POLAND

The main aim of the study was to determine changes in the concentration degree of organic farmland at the regional level in Poland. Spatial aspects were considered using absolute shares determining the interregional distribution of the analysed features and the location quotient (LQ) measuring the degree of regional specialization against the national background. The study utilized secondary source material from the Inspection of Commercial Quality of Agricultural and Food Products and Statistics Poland. It was found that the area of organic farmland undergoes continuous evolution, both at the national and regional levels. Considering the size of organic farmland, it was noted that there was a systematic increase from 2004 to 2013, followed by a decrease until 2018. Similar trends, although with varying intensities, were observed at the regional level. The leaders in terms of organic farmland area in both 2014 and 2021 were Zachodniopomorskie and Warmińsko-Mazurskie voivodeships. In analyses concerning the area of farmland allocated for selected organic crops, these voivodeships dominated in all types except for orchard and berry crops, which were most prevalent in Mazowieckie, Lubelskie, and Podkarpackie voivodeships. Based on the calculation using the location quotient, it was found that the highest spatial concentration of organic farmland was in the Lubuskie, Podlaskie, Warmińsko-Mazurskie, and Zachodniopomorskie voivodeships, and no significant changes occurred in this regard from 2014 to 2020.

The effects of agricultural output market access interventions on agricultural, socio‐economic, food security, and nutrition outcomes in low‐ and middle‐income countries: A systematic review

AbstractBackgroundAn estimated two billion people do not have sufficient access to nutritious food, and nearly half are dependent on small‐scale and subsistence farming. Projections show that the global population is not on track to reach the Sustainable Development Goals. With this in mind, development actors are increasingly seeking to better integrate rural farmers into agricultural markets. This synthesis of the literature can help to inform policy decisions to improve outcomes for smallholder farmers in low‐ and middle‐income countries, and to enable the realization of the Sustainable Development Goals. This work is the most comprehensive and up‐to‐date review synthesizing evidence from 262 interventions.ObjectivesThe purpose of this systematic review is to appraise and synthesize evidence of the effects of five types of interventions facilitating farmers' access to output markets in low‐ and middle‐income countries. We examine how these effects vary across contexts and subgroups. We also identify evidence on program costs and evidence gaps in the literature.Search MethodsThe search of included studies was based on nine major databases/search engines and 25 institutional websites, using a set of English search terms. We also conducted forward and backward citation tracking of literature, published a public call for papers, and contacted key experts.Selection CriteriaWe included studies on the effects of five types of output market access interventions, focusing on participants residing in low‐ and middle‐income countries: (1) Farm‐to‐market transport infrastructure interventions; (2) Access to output market information interventions; (3) New marketplaces or alternative marketing opportunities interventions; (4) Contract farming interventions; (5) Improved storage infrastructure and technologies interventions. We included published and unpublished studies from 2000 onwards, with experimental and quasi‐experimental study designs focusing on relevant outcomes.Data Collection and AnalysisWe screened 52,366 studies, identifying a total of 439 papers representing 289 unique studies on the effects of 262 interventions in 53 countries. Data extraction and risk of bias assessments were completed by two independent reviewers.Main ResultsAll five types of output market access interventions resulted in small‐to‐moderate positive effects on almost all measures of market participation, agricultural production, and welfare outcomes. These improvements occurred through a reduction in transaction costs, adoption of improved practices, greater farm investment, access to higher prices for farmers, greater volume sold, and increased farm income. Effects vary by intervention type. However, the body of evidence is comprised of a large share of included studies with a high risk of bias. Few studies have information on the cost of interventions, and there are gaps in the available evidence.Authors' ConclusionsOutput market access interventions are effective in reducing transaction costs and addressing market failures, thereby leading to higher income levels. Evidence of effects on food security and nutrition is sparse and has not provided conclusive findings. We also found that multi‐component interventions are not necessarily more effective than single component interventions. The specific needs and dynamics of each context should inform the choice of the intervention and approach. Investments in additional research with low risk of selection bias and confounding effects will improve the evidence base, especially for outcomes that constitute gaps in the literature. For example, the effects on quality of agricultural products and group participation are under‐researched, and we did not find any included studies focusing on North Africa or the Middle East. Collecting and reporting information on interventions' cost‐effectiveness will help decision‐makers to prioritize limited resources.

Investigation of pesticide residues based on integrated multi-strategy: Occurrence, fate and dietary risk assessment

To gain a comprehensive overview of the risk of pesticide intake exposure posed by vegetables from farms, a joint multi-strategy of pesticide monitoring was conducted on vegetable and edible mushroom samples from planting bases. The strategy integrated traditional methods and non-targeted screening by proposing modified rapid standard pre-treatment methods combined with GC, HPLC-MS and HPLC-HRMS for screening and quantification of known pesticides and unknowns. The results showed that 40 pesticides were detected at different levels in 308 samples by targeted monitoring and 27 pesticides were confirmed by non-targeted screening, of which 8 samples were detected at levels exceeding the defined maximum residue limits. The risk of acute and chronic dietary exposure for the detected pesticides in eleven groups of vegetables was acceptable. Comparative analysis of targeted and multi-strategies revealed that farm-based cultivation can improve the quality and safety of non-certified products, and pesticides with low ADIs confirmed via the multi-joint risk monitoring strategy will significantly increase the risk of cumulative chronic dietary exposure. These results will help to improve the quality and safety of agricultural products at the source and the monitoring and management of pesticides in planting bases.

Food independence and technological sovereignty of Russia in the vegetable growing sector

Relevance. The state of Russia's agro-industrial complex determines the country's national security, as it provides the population with quality agricultural products and raw materials, which affects state sovereignty. According to a number of analysts, in commercial vegetable growing, about 80 % of sown areas are annually sown with imported varieties and hybrids, and this is a vulnerability in ensuring the industry's independence and the country's competitiveness. Strengthening technological sovereignty in the field of vegetable production is one of the priorities of the state agrarian policy, as well as the main focus of scientific organisations and private companies.Results. Federal State Budgetary Scientific Institution Federal Scientific Vegetable Center (FSBSI FSVC) is a major scientific center of the industry, which can compete with foreign companies with its breeding achievements. The article shows the leading position in the breeding of vegetable and melon crops FSBSI FSVC, which actively conducts research on private genetics, biotechnology, contributing to the acceleration of the breeding process; varieties and hybrids are created that combine consistently high productivity, early maturity, resistance to biotic and abiotic stressors, high quality products with an optimal content of biologically active substances to obtain potential raw materials and products of functional action; development of resource-saving, environmentally safe, high-precision technologies for cultivation of vegetable and melon crops, taking into account species and varietal characteristics, as well as scientific bases and practical recommendations for production of original seeds taking into account zonal specifics.However, there are problems hindering the introduction of breeding achievements: the increased cost of registration of breeding achievements in the State Register of Selection Achievements of the Russian Federation of the Russian Federation, bureaucratic difficulties in their approbation, which arose for breeders after the adoption of the new law "On Seed Production". In order to solve the problems of seed production, the Ministries in charge of vegetable production have launched a sub-programme "Development of breeding and seed production of vegetable crops", which aims to increase the production of domestic competitive seeds and brings together the state, science and business.

Selective and efficient immobilization of cadmium in soil by layered double hydroxides intercalated with the mercaptosuccinic acid

Cadmium (Cd) contamination in cropland poses a significant threat to the quality of agricultural products, but even though in-situ remediation has been extensively applied, non-selective immobilization remains an issue. In order to develop a material that specifically immobilizes Cd in soil, a layered double hydroxide, intercalated with mercaptosuccinic acid (MSA-CFA), was synthesized through co-precipitation. In this case, the MSA-CFA's maximum adsorption capacity was increased from the 513.8 mg·g−1 for unintercalated hydrotalcite CFA to 692.6 mg·g−1. Besides, MSA-CFA efficiently removed 99.25 % of Cd from soil water-extract solution and immobilized up to 70.03 % of bio-available Cd. However, interestingly, its immobilization effects on beneficial metal elements Fe, Mn and Zn were milder, being equivalent to 2/7, 5/7 and 1/2 that of lime, respectively. Moreover, XRD and XPS techniques revealed isomorphous substitution with calcium and sulfhydryl complexation during the Cd adsorption by MSA-CFA. Compared with CFA, the increased adsorption capacity of MSA-CFA for Cd was due to intercalated MSA acting as a new adsorption site, while the enhanced selectivity was contributed by sulfhydryl's affinity for Cd. Altogether, MSA-CFA showed great promise as a competitive and highly efficient candidate amendment in Cd-contaminated soil remediation.

Analysis in Terms of Environmental Awareness of Farmers’ Decisions and Attitudes: Reducing Pesticide Use and Risks

Pesticide residues are a significant problem affecting the quality and safety of agricultural products in Turkey. This study aims to investigate farmers’ risk perception regarding pesticide residues, including the primary factors that influence their behavior from the farmers’ perspective. In addition, the main characteristics of pesticide residues encountered in the production of agricultural products against the current policy background is investigated to provide decision support to the Turkish government for improving the safe production of agricultural products. This paper uses a binary logistic model to analyze farmers’ perceptions of pesticide residues using a cross-sectional dataset of 323 vegetable growers in Bursa, Turkey. Farmer characteristics and pesticide application behavior were more effective in reducing residual risk perceptions than farm characteristics. The effects of membership in a cooperative, average amount of pesticide used, location where the pesticide was purchased, application timing, and adherence to last spraying and harvest timing on the perception of residues were the largest. Farmers receive helpful but limited information from pesticide distributors. However, the primary source of information is not the advisors, which is why these grievances exist. The study results show that policymakers should support cooperatives, expand pesticide training, and make public extension services more effective and that pesticide dealers should conduct more frequent inspections.

Exploration of the Application of Agricultural Intelligent Robots in the Qinghai-Tibet Plateau

In order to improve agricultural efficiency, reduce labor intensity, and improve the quality and yield of agricultural products on the Tibetan Plateau, this paper takes the application of traditional agricultural robots as an example and proposes the application of agricultural robots to agriculture on the Qinghai-Tibet Plateau based on the special breeding environment of the Qinghai-Tibet Plateau combined with the current situation of traditional agriculture. Through the application practice of robots in traditional agriculture, the possibility of the application of agricultural robots in the Qinghai-Tibet Plateau is pointed out, the working methods and advantages of robots in the Qinghai-Tibet Plateau are expounded, and the application of intelligent agricultural robots in the agriculture of the Qinghai-Tibet Plateau is discussed and analyzed. The results show that with the progress of science and technology, intelligent robots have gradually played an important role in various fields, and intelligent robots have broad application prospects in plateau agriculture. The application of agricultural robots in the Qinghai-Tibet Plateau should be aimed at the Qinghai-Tibet Plateau to make some adaptive research and development, intelligent upgrading and demonstration project promotion in order to promote the Qinghai-Tibet Plateau agricultural automation.

Analysis of Distribution and Marketing Efficiency of Pineapples from a Sharia Economic Perspective

The agricultural sector plays an important role in long-term economic development and rural economic recovery in Indonesia. The development of agricultural-based businesses and sustainable agricultural systems is needed to improve the quality of human resources and agricultural products. Horticultural commodities, such as fruit, have high economic potential and can be a source of income for farmers. However, there are several obstacles in the agricultural sector, such as competition with other horticultural products, low quality and quantity of local supplies, and a lack of transparent market information. In addition, distribution in Islam has principles that can be applied in the context of the distribution of wealth and economic resources in Islam, such as justice, equality, public benefits, prohibition of exploitation, and social solidarity. This research aims to analyze pineapple marketing distribution and pineapple marketing efficiency from a sharia economic perspective. The research method used is field research using primary and secondary data. The research results show that there are two marketing distribution channels that are used, namely marketing distribution channel I and marketing distribution channel II. Marketing distribution channel I involves farmers selling directly to the city without intermediaries, while marketing distribution channel II involves collectors buying from farmers and selling to the city. Keywords: Distribution, Efficiency, Marketing

Study of the Impact of New Rural Cooperatives on the Implementation of the Rural Revitalisation Strategy

This study aims to explore the impact of new rural cooperatives on the implementation of China's rural revitalisation strategy, focusing on the roles and challenges of new cooperatives in promoting agricultural modernisation, facilitating the optimisation of socio-economic structures, and achieving an ecological civilisation. Through literature review, case study analysis and field research, this study comprehensively assesses the importance and impact of new rural cooperatives in rural revitalisation. The study finds that new rural cooperatives have significantly improved agricultural productivity and product quality and contributed to agricultural modernisation by pooling farmers' efforts and introducing modern agricultural technologies and management models. These cooperatives have also contributed to the optimisation of rural socio-economic structures by providing employment opportunities, skills training and increasing farmers' incomes. In addition, co-operatives have demonstrated a positive role in promoting rural ecological environment protection and sustainable development, such as promoting green agriculture, conserving resources and protecting the ecological environment. At the same time, this study also points out the challenges faced by new rural co-operatives in the process of development, including management and operational efficiency, market adaptability, balance between environmental protection and sustainable development, fund raising and resource allocation. In response to these challenges, the study proposes a series of countermeasures, such as strengthening the internal management of cooperatives, broadening market channels, promoting environmentally friendly agricultural practices, enhancing the effective use of funds and resources, and strengthening policy support and guidance. Overall, new rural cooperatives play an important role in promoting rural revitalisation strategies, and their successful experiences and challenges are of great reference value in guiding the implementation of rural revitalisation strategies. Through an in-depth study of new rural cooperatives, this paper provides practical insights and suggestions for policymakers, cooperative managers and rural development researchers.

Fresh Agricultural Products Cold Chain Logistics Development Status and Countermeasures Research

With the improvement of the living standard of consumers in China, people are more and more concerned about the demand and quality of fresh agricultural products, and the market scale of cold chain logistics of fresh agricultural products is growing explosively. However, China's cold chain logistics still exists such as insufficient cold chain logistics infrastructure, low level of information technology, high cost, low degree of standardization of fresh agricultural products production and other problems, resulting in China's fresh agricultural products cold chain logistics is facing serious challenges. This paper analyzes the development status quo of cold chain logistics and puts forward some solutions to provide some references for subsequent research.