Laboratory evaluation of a proximal sensing technique for simultaneous measurement of soil clay and water content

Precision agriculture, largely the application of information and communications' technologies to in-field data gathering and management, may be regarded as 'best practice' far crop growth in the future because of its twin goals of maximising economic returns whilst concurrently minimising environmental impact. The practice of precision agriculture, whether it be to differentially apply fertiliser, seed, pesticide, irrigation or tillage requires detailed knowledge of the spatial and temporal variation of crop yield components, weeds, soil-borne pests and attributes of physical, chemical and biological soil fertility. However, a detailed description of fine or even coarse scale variation in soil properties has always been difficult and costly to perform. Sensing and scanning technologies are currently being developed to more efficiently and economically describe and obtain precise information on the extent and variability of soil attributes which affect crop growth and yield. Combining these technologies with vastly improved ground positioning systems allows detailed mapping of soil resource and crop yield variability which may therefore be an important input for site-specific decision making. Experiments were conducted to design an invasive sensor for real-time, simultaneous measurements of clay, organic matter and soil water content from reflectance of a suitable wavelength or combination of wavelengths in the near infra-red (NIR) portion of the electromagnetic spectrum. Soil materials were prepared with varying amounts of clay, soil water and organic matter according to a response-surface design, and the reflectance spectra measured at 2-nm intervals from 1300 nm to 2500 nm. Response-surface models were fitted to the reflectance data at specified wavelengths. Reflectance showed significant response to clay content and soil water but not to organic matter. A thorough selection procedure using non-linear modelling and root-mean-square-error of prediction was used to derive the four most suitable wavelengths (1600, 1800, 2000 and 2100 nm) for simultaneously measuring clay and soil water content. In a simulation experiment clay content was more accurately predicted than water content. (C) 1998 Elsevier Science B.V. All rights reserved.