#Soil Health Card

综述气候变化对土壤健康的影响，并评估可持续管理、新兴技术与政策支持。

基于扎根理论访谈八位农户，探究社交网络与互动如何影响土壤健康管理行为的持续。

综述37篇文献，论证南部非洲本土知识可支撑再生农业与可持续作物生产。

综述集约化蔬菜生产中的土壤健康限制，并评估物理、化学、生物管理措施及推广路径。

评估发酵有机肥配施化肥对稻麦轮作产量、土壤肥力与经济收益的综合影响。

提出土壤表型组框架，用近端传感量化管理导致的土壤时空变异。

A novel framework for integrating diverse environmental effects of agricultural soil for sustainable remediation。Agricultural Systems

Imbalanced fertilizer use is a major problem in Indian agriculture: excess nitrogen raises costs and pollutes water, while deficiencies of phosphorus, potassium and micronutrients limit yields. Effective fertilizer management requires knowing the nutrient status of each field, which conventional laboratory soil testing provides only slowly and at low spatial density. This paper reviews AI-based soil analysis and fertilizer management for precision agriculture. It examines soil sensing with in-field electrochemical NPK, pH and electrical-conductivity probes and with visible–near-infrared spectroscopy; machine learning models that classify soil fertility and predict nutrient levels from sensor and spectral data; digital soil mapping, which combines field samples with remote sensing and terrain covariates to map soil properties across landscapes; crop nitrogen status estimation; and recommendation engines that convert soil and crop information into site-specific fertilizer doses and variable-rate application. India's Soil Health Card programme is discussed as a data source and delivery channel. A five-layer architecture comprising soil sensing, data integration, AI analysis, fertilizer recommendation and farmer advisory layers is proposed, together with research gaps, objectives, a comparison of soil analysis methods and challenges such as sensor accuracy, sparse samples, model transferability, cost and farmer adoption. The review concludes that AI can make fertilizer use more efficient, profitable and environmentally sustainable.