There are currently many in-field methods for estimating soil properties (e.g., pH, texture, total C, total N) available in precision agriculture, but each have their own level of suitability and only a few can be used for direct determination of plant-available nutrients. As promising approaches for reliable in-field use, this review provides an overview of electromagnetic, conductivity-based, and electrochemical techniques for estimating plant-available soil nutrients and pH. Soil spectroscopy, conductivity, and ion-specific electrodes have received the most attention in proximal soil sensing as basic tools for precision agriculture during the last two decades. Spectral soil sensors provide indication of plant-available nutrients and pH, and electrochemical sensors provide highly accurate nitrate and pH measurements. This is currently the best way to accurately measure plant-available phosphorus and potassium, followed by spectral analysis. For economic and practicability reasons, the combination of multi-sensor in-field methods and soil data fusion has proven highly successful for assessing the status of plant-available nutrients in soil for precision agriculture. Simultaneous operation of sensors can cause problems for example because of mutual influences of different signals (electrical or mechanical). Data management systems provide relatively fast availability of information for evaluation of soil properties and their distribution in the field. For rapid and broad adoption of in-field soil analyses in farming practice, in addition to accuracy of fertilizer recommendations, certification as an official soil analysis method is indispensable. This would strongly increase acceptance of this innovative technology by farmers.

目前，精准农业中有许多用于估算土壤特性（例如 pH、质地、总碳、总氮）的现场方法，但​​每种方法都有各自的适用性，并且只有少数方法可用于直接测定植物的生长状况。 - 可用营养素。作为可靠的现场使用的有前途的方法，本综述概述了用于估计植物有效土壤养分和 pH 值的电磁、电导率和电化学技术。在过去的二十年里，土壤光谱学、电导率和离子特异性电极作为精准农业的基本工具，在近端土壤传感领域受到了最多的关注。光谱土壤传感器可指示植物可利用的养分和 pH 值，电化学传感器可提供高精度的硝酸盐和 pH 值测量。这是目前准确测量植物有效磷和钾的最佳方法，然后进行光谱分析。出于经济和实用性的原因，多传感器现场方法和土壤数据融合的结合已被证明在评估精准农业土壤中植物有效养分的状况方面非常成功。传感器的同时操作可能会导致问题，例如由于不同信号（电气或机械）的相互影响。数据管理系统为评估土壤特性及其在田间的分布提供了相对较快的信息可用性。为了在农业实践中快速广泛地采用田间土壤分析，除了肥料建议的准确性之外，作为官方土壤分析方法的认证也是必不可少的。这将极大地提高农民对这项创新技术的接受度。