Predicting Key Agronomic Soil Properties with UV-Vis Fluorescence Measurements Combined with Vis-NIR-SWIR Reflectance Spectroscopy: A Farm-Scale Study in a Mediterranean Viticultural Agroecosystem

Sensors (Basel). 2018 Apr 10;18(4):1157. doi: 10.3390/s18041157.

Abstract

For adequate crop and soil management, rapid and accurate techniques for monitoring soil properties are particularly important when a farmer starts up his activities and needs a diagnosis of his cultivated fields. This study aimed to evaluate the potential of fluorescence measured directly on 146 whole soil solid samples, for predicting key soil properties at the scale of a 6 ha Mediterranean wine estate with contrasting soils. UV-Vis fluorescence measurements were carried out in conjunction with reflectance measurements in the Vis-NIR-SWIR range. Combining PLSR predictions from Vis-NIR-SWIR reflectance spectra and from a set of fluorescence signals enabled us to improve the power of prediction of a number of key agronomic soil properties including SOC, Ntot, CaCO₃, iron, fine particle-sizes (clay, fine silt, fine sand), CEC, pH and exchangeable Ca2+ with cross-validation RPD ≥ 2 and ≥ 0.75, while exchangeable K⁺, Na⁺, Mg2+, coarse silt and coarse sand contents were fairly predicted (1.42 ≤ RPD < 2 and 0.54 ≤ < 0.75). Predictions of SOC, Ntot, CaCO₃, iron contents, and pH were still good (RPD ≥ 1.8, ≥ 0.68) when using a single fluorescence signal or index such as SFR_R or FERARI, highlighting the unexpected importance of red excitations and indices derived from plant studies. The predictive ability of single fluorescence indices or original signals was very significant for topsoil: this is very important for a farmer who wishes to update information on soil nutrient for the purpose of fertility diagnosis and particularly nitrogen fertilization. These results open encouraging perspectives for using miniaturized fluorescence devices enabling red excitation coupled with red or far-red fluorescence emissions directly in the field.

Keywords: Mediterranean vineyard soils; UV-Vis fluorescence; Vis-NIR-SWIR reflectance spectroscopy; fertility assessment; model averaging; multiple excitation fluorescence sensor; partial least squares regression; soil properties.

MeSH terms

  • Ecosystem
  • Farms
  • Nitrogen
  • Silicon Dioxide
  • Soil*
  • Spectroscopy, Near-Infrared

Substances

  • Soil
  • Silicon Dioxide
  • Nitrogen