Abstract
Vibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results. This study aimed at optimizing one of the essential settings during the acquisition of FTIR spectra (viz. Scans number) using the standardized moment distance index (SMDI) as a metric that could trap the fine points of the curve and extract optimal spectral fingerprints of the sample. Furthermore, it can be used successfully to assess the spectra resemblance. The study revealed that beyond 50 scans the similarity of the acquisitions has been remarkably improved. Subsequently, the effect of the number of scans on the predictive ability of partial least squares regression models for the estimation of five selected soil properties (i.e., soil pH in water, soil organic carbon, total nitrogen, cation exchange capacity and Olsen phosphorus) was assessed, and the results showed a general tendency in improving the correlation coefficient (R2) as the number of scans increased from 10 to 80. In contrast, the cross-validation error RMSECV decreased with increasing scan number, reflecting an improvement of the predictive quality of the calibration models with an increasing number of scans.
Highlights
Vibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results
40 soil samples representing different Moroccan regions were used to assess the effect of the scan number on the accuracy of predictive models
We have shown that the scan number setting is an essential factor for improving the quality of FTIR spectra of soil samples
Summary
Vibrational spectroscopy such as Fourier-transform infrared (FTIR), has been used successfully for soil diagnosis owing to its low cost, minimal sample preparation, non-destructive nature, and reliable results. Recent developments promise to greatly simplify soil diagnosis, to make it faster, cheaper and more suitable for routine analysis. This effort of simplification continues and is mostly based on the advent of dry chemistry applied especially to spectroscopy. Methods based on the absorbance/reflectance of infrared emissions offer several advantages compared with conventional agrochemical ones, and soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. The advances in instrumentation, i.e. the development of fast, low cost, reproducible and portable instruments available for infrared techniques (medium and near infrared) have opened new opportunities for researchers
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