Analysis of complementarity of different spectral analytics to sense soil properties

迄今为止，土壤取样和分析的费用是根据当地需要调整具体地点农业投入管理的最大限制。不同的新方法已被考虑以最小失真近端土壤传感取代费力和昂贵的湿化学分析技术。其中最有利的基于光谱的技术是可见光、近红外和中红外光谱、激光诱导分解光谱（LIBS）以及机器视觉。单独地，这些方法中的每一种都在试图预测特定的物理和化学土壤特性时提供了积极的结果。本研究的目的是探索这些方法的互补性，以优化仪器和分析，用于固体土壤样品的流线分析。Logiag是一家年轻的创新公司，为加拿大东部的种植者提供服务，并开发了使用LIBS快速土壤分析的方法。这项研究的结果将有助于加强他们的新颖和有前途的土壤测试方法，并协助大规模实施精准农业。

To date, cost of soil sampling and analysis constitute the greatest limitation for adjusting site-specificmanagement of agricultural inputs according to local needs. Different new methods have been considered toreplace laborious and expensive wet chemistry analytical techniques with minimum distortion proximal soilsensing. Among most favorable spectra-based techniques are visible, near-infrared, and mid-infraredspectroscopy, laser-induced break down spectroscopy (LIBS), as well as machine vision. Individually, each ofthese methods has provided positive results when attempting to predict specific physical and chemical soilproperties. The goal of this research is to explore complementarity of these methods in order to optimizeinstrumentation and analytics to be used for streamline analysis of solid soil samples. Logiag is a young andinnovative company that provides both services to growers in Eastern Canada and develops methodology forrapid soil analysis using LIBS. The results of this study will help enhance their novel and promising approachto soil testing and assist in implementation of precision agriculture on a large scale.