Jie  Shen^1,2

1 Haining Chang'an Town Guangyi Family Farm, Haining, 314408, Zhejiang, China
2 Zhejiang Agronomist College, Hangzhou, 310021, Zhejiang, China
Author    Correspondence author
Molecular Soil Biology, 2026, Vol. 17, No. 5   
Received: 20 Jul., 2026    Accepted: 24 Aug., 2026    Published: 08 Sep., 2026

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Vegetable production in the Zhejiang region is characterized by intensive cultivation systems and high fertilizer inputs, making soil nutrient management a critical factor for maintaining productivity and sustainability. This review aims to evaluate the effects of soil nutrient conditions on vegetable productivity using statistical analysis approaches and to establish a quantitative framework for understanding nutrient-crop relationships. The impacts of major soil fertility indicators, including nitrogen, phosphorus, potassium, organic matter, soil pH, and micronutrients, on vegetable growth, yield formation, and quality development are discussed. Statistical methods, including correlation analysis, regression models, multivariate analysis, principal component analysis, and machine-learning algorithms, are summarized for identifying key nutrient drivers and predicting vegetable productivity. A case study of greenhouse vegetable production in Zhejiang demonstrates the application of statistical models in evaluating nutrient contributions, determining optimal nutrient ranges, and improving fertilizer management strategies. Furthermore, integrating soil nutrient monitoring with geographic information systems, digital agriculture technologies, and predictive models provides new opportunities for precision fertilization and sustainable vegetable production. This review highlights the importance of data-driven soil fertility assessment and demonstrates that statistical analysis can effectively support nutrient optimization, improve fertilizer-use efficiency, and enhance long-term productivity of vegetable agroecosystems in the Zhejiang region.

Soil nutrients; Vegetable productivity; Statistical analysis; Precision fertilization; Zhejiang region