Dataset of visible-near infrared handheld and micro-spectrometers-comparison of the prediction accuracy of sugarcane properties [Data paper] Zgouz, A. Heran, D. /Barthès, Bernard Bastianelli, D. Bonnal, L. Baeten, V. Lurol, S. Bonin, M. Roger, J. M. Bendoula, R. Chaix, G. Micro-spectrometers Handheld devices Visible-near infrared spectroscopy chemometrics sugarcane 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 log(10) (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 ac cess dataset could also be used to test new chemometric methods, for training, etc. 2020 text https://www.documentation.ird.fr/hor/fdi:010079738 fdi:010079738 Zgouz A., Heran D., Barthès Bernard, Bastianelli D., Bonnal L., Baeten V., Lurol S., Bonin M., Roger J. M., Bendoula R., Chaix G.. Dataset of visible-near infrared handheld and micro-spectrometers-comparison of the prediction accuracy of sugarcane properties [Data paper]. 2020, 31, 106013 [6 ] EN