Rapid And Simultaneous Prediction Of Soil Quality Attributes Using Near Infrared Technology

The main purpose of this present study is to apply the near infrared (NIR) technology as a rapid and robust method in predicting soil quality parameters in form of potassium (K), Magnesium (Mg) and calcium (Ca) simultaneously. Diffuse reflectance spectra data were acquired for a total of 40 bulk soil samples (60 g per each bulk) in near infrared (NIR) wavelength range from 1000 to 2500 nm. On the other hand, actual reference K, Mg and Ca were measured using standard laboratory procedures. Prediction models, used to predict those three quality parameters were established using principal component regression (PCR) and partial least square regression (PLSR) method. Moreover, prediction accuracy and robustness were evaluated based on correlation coefficient (r) and residual predictive deviation (RPD) index respectively. The result showed that K, Mg and Ca of soil samples can be predicted simultaneously using NIR technology with maximum r coefficient and RPD index were 0.97 and 5.14 for K, 0.98 and 8.34 for Mg, 0.98 and 8.90 for Ca respectively, which categorized as excellent model performance. Thus, it may conclude that NIR technology can be used and applied as rapid and simultaneous method to predict quality parameters of soil samples satisfactory. Keywords— NIRS, soil, prediction, nutrients, quality, fast, method. ——————————  ——————————

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