Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-05-15 Cooperative journals: 《智慧农业（中英文）》
Abstract： In recent years, China's cold chain logistics industry has entered a stage of rapid development. At the same time, with the increase of greenhouse gas emissions, green and low-carbon transformation has become a new feature and direction of high-quality and healthy development of the cold chain industry to meet the future development needs of China's low-carbon economy. In view of this, in order to ensure the scientificity of China's low-carbon cold chain logistics evaluation system, in this paper, 30 indicators from the four levels of energy transformation, technological innovation, economic efficiency, and national policy based on different relevant levels were first preliminarily determined, and finally 14 indicators for building China's low-carbon cold chain logistics development evaluation system through consulting experts and the possibility of data acquisition were determined. Data from 2017 to 2021 were selected to conduct a quantitative evaluation of the development level of low-carbon cold chain logistics in China. Firstly, the entropy weight method was used to analyze the weight and obstacle degree of different indicators to explore the impact of different indicators on the development of low-carbon cold chain logistics; Secondly, a weighted decision-making matrix was constructed based on the weights of different indicators, and the technology for order preference by similarity to ideal solution (TOPSIS) evaluation model was used to evaluate the development of low-carbon cold chain logistics in China from 2017 to 2021, in order to determine the development and changes of low-carbon cold chain logistics in China. The research results showed that among the 14 different indicators of the established evaluation system for the development of low-carbon cold chain logistics in China, the growth rate of the use of green packaging materials, the number of low-carbon technical papers published, the proportion of scientific research personnel, the growth rate of cold chain logistics demand for fresh agricultural products, and the reduction rate of hydrochlorofluorocarbon refrigerants account for a relatively large proportion, ranking in the top five, respectively reaching 0.1243, 0.1074, 0.1066, 0.0982, and 0.0716, accounting for more than half of the overall proportion. It has a significant impact on the development of low-carbon cold chain logistics in China. From 2017 to 2021, the development level of China's low-carbon cold chain logistics was scored from 0.1498 to 0.2359, with a year-on-year increase of about 57.5%, indicating that China's low-carbon cold chain logistics development level was relatively fast in the past five years. Although China's low-carbon cold chain logistics development has shown an overall upward trend, it is still in the development stage.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-05-15 Cooperative journals: 《智慧农业（中英文）》
Abstract： The new generation of information technology has led to the rapid development of the intelligent level of the cold chain, and the precise control of the development level of the smart cold chain is the prerequisite foundation and guarantee to achieve the key breakthrough of the technical bottleneck and the strategic layout of the development direction. Based on this, an evaluation index system for China's intelligent cold chain development from the dimensions of supply capacity, storage capacity, transportation capacity, economic efficiency and informationization level was conducted. The entropy weight method combined with the technique for order preference by similarity to ideal solution (TOPSIS) was used to quantitatively evaluate the development of intelligent cold chain in 30 Chinese provinces and cities (excluding Tibet, Hong Kong, Macao and Taiwan) from 2017 to 2021. The quantitative evaluation of the level of intelligent cold chain development was conducted. The impact of the evaluation indicators on different provinces and cities was analysed by exploratory spatial data analyses (ESDA) and geographically weighted regression (GWR). The results showed that indicators such as economic development status, construction of supporting facilities and informationization level had greater weight and played a more important role in influencing the construction of intelligent cold chain. The overall level of intelligent cold chain development in China is divided into four levels, with most cities at the third and fourth levels. Beijing and the eastern coastal provinces and cities generally have a better level of intelligent cold chain development, while the southwest and northwest regions are developing slowly. In terms of overall development, the overall development of China's intelligent cold chain is relatively backward, with insufficient inter-regional synergy. The global spatial autocorrelation analysis shows that the variability in the development of China's intelligent cold chain logistics is gradually becoming greater. Through the local spatial autocorrelation analysis, it can be seen that there is a positive spatial correlation between the provinces and cities in East China, and negative spatiality in North China and South China. After geographically weighted regression analysis, it can be seen that the evaluation indicators have significant spatial and temporal heterogeneity in 2017, with the degree of influence changing with spatial location and time, and the spatial and temporal heterogeneity of the evaluation indicators is not significant in 2021. In order to improve the overall development level of China's intelligent cold chain, corresponding development countermeasures are proposed to strengthen the construction of supporting facilities and promote the transformation and upgrading of information technology. This study can provide a scientific basis for the global planning, strategic layout and overall promotion of China's intelligent cold chain.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-02-17 Cooperative journals: 《智慧农业（中英文）》
Abstract： As an emerging concept, metaverse has attracted extensive attention from industry, academia and scientific research field. The combination of agriculture and metaverse will greatly promote the development of agricultural informatization and agricultural intelligence, provide new impetus for the transformation and upgrading of agricultural intelligence. Firstly, to expound feasibility of the application research of metaverse in agriculture, the basic principle and key technologies of agriculture metaverse were briefly described, such as blockchain, non-fungible token, 5G/6G, artificial intelligence, Internet of Things, 3D reconstruction, cloud computing, edge computing, augmented reality, virtual reality, mixed reality, brain computer interface, digital twins and parallel system. Then, the main scenarios of three agricultural applications of metaverse in the fields of virtual farm, agricultural teaching system and agricultural product traceability system were discussed. Among them, virtual farm is one of the most important applications of agricultural metaverse. Agricultural metaverse can help the growth of crops and the raising of livestock and poultry in the field of agricultural production, provide a three-dimensional and visual virtual leisure agricultural experience, provide virtual characters in the field of agricultural product promotion. The agricultural metaverse teaching system can provide virtual agricultural teaching similar to natural scenes, save training time and improve training efficiency by means of fragmentation. Traceability of agricultural products can let consumers know the production information of agricultural products and feel more confident about enterprises and products. Finally, the challenges in the development of agricultural metaverse were summarized in the aspects of difficulties in establishing agricultural metaverse system, weak communication foundation of agricultural metaverse, immature agricultural metaverse hardware equipment and uncertain agricultural meta universe operation, and the future development directions of agricultural metaverse were prospected. In the future, researches on the application of metaverse, agricultural growth mechanism, and low power wireless communication technologies are suggested to be carried out. A rural broadband network covering households can be established. The industrialization application of agricultural meta universe can be promoted. This review can provide theoretical references and technical supports for the development of metaverse in the field of agriculture.
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