Dataset of visible-near infrared handheld and micro-spectrometers - comparison of the prediction accuracy of sugarcane properties.
Data Brief
; 31: 106013, 2020 Aug.
Article
en En
| MEDLINE
| ID: mdl-32715042
In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Data Brief
Año:
2020
Tipo del documento:
Article
País de afiliación:
Francia
Pais de publicación:
Países Bajos