Ground-Sensor Soil Reflectance as Related to Soil Properties and Crop Response in a Cotton Field |
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| Authors: | Email author" target="_blank">S?StamatiadisEmail author C?Christofides C?Tsadilas V?Samaras J?S?Schepers D?Francis |
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| Institution: | (1) Soil Ecology and Biotechnology Laboratory, Gaia Environmental Research and Education Center, Goulandris Natural History Museum, 13 Levidou Street, 14562 Kifissia, Greece;(2) Institute of Soil Classification and Mapping, National Agricultural Research Foundation, 1 Theophrastou Street, 41335 Larissa, Greece;(3) USDA-ARS, University of Nebraska, 120 Keim Hall, Lincoln, NE 68583-0915, USA |
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| Abstract: | Bare soil reflectance from airborne imagery or laboratory spectrometers has been used to infer soil properties such as soil texture, organic matter, water content, salinity and crop residue cover. However, the relation of soil properties to reflectance data often varies with soil type and conditions and surface reflectance may not be representative of the conditions in the root zone. The objectives of this study were to assess the soil reflectance data obtained by ground-based sensors and to model soil properties in the root zone as a function of surface soil reflectance and plant response. Ground-based sensors were used to simultaneously monitor soil and canopy reflectance in the visible and near-infrared (VNIR) along six rows and in two growth stages in a 7 ha cotton field. The reflectance data were compared to soil properties, leaf nutrients and biomass measured at 33 sampling positions along the rows. Brightness values of the blue and green bands of soil reflectance were better correlated to soil water content, particulate organic matter and extractable potassium and phosphorus, while those in the red and NIR bands were correlated to soil carbonate content, total nitrogen, electrical conductivity and foliar nutrients. The correlation of red soil reflectance with canopy reflectance was significant and indicated an indirect inverse relationship between soil fertility and plant stress. The integration of surface soil reflectance and plant response variables in a multiple regression model did not substantially improve the prediction of soil properties in the root zone. However, crop nutrient status explained a significant portion of the spatial variability of soil properties related to nitrification processes when soil reflectance did not. The implication of these findings to agricultural management is discussed. |
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| Keywords: | canopy reflectance NDVI spatial variability crop nutrients biomass |
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