With the gradual improvement of residents’ income level, the market demand for fresh food freshness is growing day by day, and the pursuit of quality is constantly improving. Due to the unique tropical Marine climate, Hainan has a large number of fresh food, such as mango, dragon fruit, lychee and golden passion fruit, which are popular in domestic and foreign markets. When winter comes, fresh food in Hainan has entered major cities in the mainland. However, compared with other coastal provinces, Hainan still has shortcomings in local economic development, especially in optimizing the fresh food supply chain. It faces challenges such as shortage of funds and weak technical strength, which makes it difficult to meet consumers’ demand for high-quality fresh food. At present, Hainan Free Trade Port is in the golden period of development. In the face of challenges and problems as well as huge market demand, it should seize the opportunity, rely on local characteristics, optimize the fresh food supply chain system, give play to its own advantages to avoid disadvantages, and build a management system with local characteristics.

This paper thoroughly explores the path of teaching reform for the course “Food Nutrition and Hygiene” based on the “Teaching, Research, Competition, and Innovation” model. In the context of rapid technological development and evolving social demands, the traditional educational model no longer fully meets the learning needs in the field of food nutrition and hygiene. Therefore, a comprehensive education strategy, “Teaching, Research, Competition, and Innovation,” is proposed to enhance students’ learning experiences and capabilities through innovative teaching methods, participation in research activities, competitions, and innovation and entrepreneurship training. The paper elaborates on the implementation of each component and its impact on students’ theoretical learning and practical skills, emphasizing the importance of this model in promoting students’ overall quality improvement and laying the foundation for future career development.

Land use, as a key form of human-environment interaction, has sharply and continuously transformed the global land surface. Farmland abandonment (FA) is an extreme manifestation of land use marginalization, exerting both positive and negative impacts on the ecological environment and human well-being. To map the extent of FA in Zhejiang Province and clarify its spatial pattern, driving mechanisms, and ecological-socioeconomic implications, this study employed the Google Earth Engine (GEE) and Geographic Information System (GIS) platforms, integrating multi-source land use/land cover data and Landsat time-series images. We used the random forest (RF) algorithm for land use classification, the land use trajectory method for FA identification, landscape pattern analysis (Fragstats 4) to quantify landscape characteristics, and spatial autocorrelation analysis (Moran’s I and LISA indices) to explore spatial aggregation patterns. The results showed that farmland accounted for 16.32% of the total land use area in Zhejiang Province, equivalent to 1.89 × 10⁴ km². The total area of FA was 1.72 × 10⁸ m², with a farmland abandonment rate of 1.65%. The area of active farmland (AF) was approximately 1.95 × 10⁹ m², with a continuous cultivation rate of 18.69%. The landscape fragmentation, aggregation, and diversity of FA, AF, and fallow land (FL) differed significantly: FA exhibited the most severe fragmentation, while AF had the highest aggregation degree. Spatial autocorrelation analysis revealed that FA and AF both showed dominant high aggregation and low dispersion characteristics; the global Moran’s I index of FA was 0.93 (Z-score = 439.45, p < 0.01), indicating a strong positive spatial autocorrelation. Local spatial autocorrelation (LISA) analysis showed that high-high (HH) and low-low (LL) clusters were the main types, accounting for 38.97% and 37.95% of FA patches (passing p < 0.01 significance test), respectively. Comparative analysis with existing studies confirmed the scientific validity of our results (overall classification accuracy > 95%). Finally, we discussed the ecological and socio-economic driving mechanisms of FA, analyzed its potential threats to food security, proposed targeted policy implications, and identified research limitations and future research directions. Our findings provide a scientific basis for rational land use management, farmland protection, and food security assurance in Zhejiang Province.