2018
DOI: 10.1186/s13717-018-0138-4
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Determination of soil physicochemical attributes in farming sites through visible, near-infrared diffuse reflectance spectroscopy and PLSR modeling

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Cited by 40 publications
(9 citation statements)
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“…This study found a positive correlation between BD and silt, which is consistent with the study by Amanuel et al (2018) and contrary to the study by Assefa and Wossenu (2016). There was a negative correlation between the particle size distribution of sand and silt content, which is consistent with the study by Vibhute et al (2018). While soil-mediated effects on avifaunal habitat preference have been recognized (Meyer et al 2015), however, there are scanty studies documenting such effects on a particular species.…”
Section: Discussionsupporting
confidence: 87%
“…This study found a positive correlation between BD and silt, which is consistent with the study by Amanuel et al (2018) and contrary to the study by Assefa and Wossenu (2016). There was a negative correlation between the particle size distribution of sand and silt content, which is consistent with the study by Vibhute et al (2018). While soil-mediated effects on avifaunal habitat preference have been recognized (Meyer et al 2015), however, there are scanty studies documenting such effects on a particular species.…”
Section: Discussionsupporting
confidence: 87%
“…Spectral data analysis is performed with the use of multivariate statistical methods, the success of which is highly dependent on the selected calibration method [38]. PLSR is the most commonly-used linear method to describe the relationship between spectral data and soil properties due to its interpretability and low computation time [39,40]. Thus, it has been observed that the aforementioned relationship is not always linear, and that therefore PLSR could be considered insufficient for modelling soil properties [41].…”
Section: Multivariate Calibrationsmentioning
confidence: 99%
“…The initial model contained eight predictors (RMSEP= 0.80 and R 2 = 0.15), whereas the final model contained only four predictors (RMSEP= 0.79 and R 2 = 0.19). An accurate and stable model is indicated by a lower RMSE and a higher R 2 (Vibhute, Kale, Mehrotra, Dhumal, & Nagne, ). In PLS regression plots, variables located on the perimeter of the circle are strongly correlated.…”
Section: Methodsmentioning
confidence: 99%