Journal
MICROCHEMICAL JOURNAL
Volume 145, Issue -, Pages 1094-1101Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.microc.2018.12.027
Keywords
Near infrared spectroscopy; Soil; Moisture; Organic matter; Partial least squares regression; External parameter orthogonalization
Categories
Funding
- Instituto Nacional de Ciencia e Tecnologia de Bioanalitica (INCTBio)
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq, Brazil) [465389/2014-7, 303994/2017-7]
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES, Brazil) [001]
- Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP, Brazil) [2014/508673]
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Near-infrared spectroscopy (NIR) is one of the most promising alternative technique for soil analysis in routine laboratories, which can provide faster and cheaper determinations of some soil parameters, including soil organic matter (SOM) content. However, NIR spectroscopy is quite sensitive to external environmental conditions, such as soil moisture, drastically reducing the accuracy of the methodology. In this study we used the external parameter orthogonalization (EPO) to minimize the moisture effect on soil spectra, making possible to apply the model developed with dry samples in moist ones. It was used 163 soil samples collected from several regions of Brazil, of these 103 dry samples were used to build the calibration model and the remaining 60 samples were moisturized at five different levels (5-35% w/w) to build the EPO model and to validate the methodology. The results obtained by EPO model (1.85 g/dm(3), 0.86 and 2.02 for RMSEP, R(val)2(,) and RPDval, respectively) showed that the method was able to remove the effect of moisture in the NIR spectra, with accuracy values statistically equivalent for dry and moist soil samples.
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