Prediction of mineral contents in sugarcane cultivated under saline conditions based on stalk scanning by Vis/NIR spectral reflectance

Abstract

Mineral contents in the sugarcane juice are important qualitative variables to be used in the development of new products and to establish physicochemical criteria for food processing. The objective of this study was to estimate the mineral contents (K+, Na+, and Mg2+) in sugarcane stalk samples by visible/near infrared (Vis/NIR) spectral reflectance measurements and multivariate data analysis. Four sugarcane varieties were cultivated under different saline conditions in a greenhouse. The spectral reflectance of stalk surface was measured with a portable spectrometer. The juice mineral compositions were determined by a reference laboratory method. Partial least squares regression (PLSR) was used for calibrating the estimation models. The most abundant mineral in the sugarcane juice was K+ (310.01–561.48 mg 100 ml−1) as compared to Na+ (4.63–122.96 mg 100 ml−1) and Mg2+ (6.93–18.78 mg 100 ml−1). During the calibration process, the proposed models presented low root mean square errors (RMSE) for calibration (62.46, 25.70, 2.36, and 0.05 mg 100 ml−1), and for cross-validation (90.08, 30.86, 3.79, and 0.06 mg 100 ml−1) for K+, Na+, Mg2+, and Na+/K+ ratio, respectively. Results were also satisfactory for the external validation with low root mean square error (27.30, 10.69, 0.57, and 0.03 mg 100 ml−1), and mean bias error (−4.45, 6.57, 0.07, 0.01 mg 100 ml−1), as well as high coefficients of determination (0.78, 0.89, 0.93, and 0.74), for K+, Na+, Mg2+, and Na+/K+ ratio, respectively. Spectrometry combined to the PLSR technique resulted in an efficient, quick, and non-destructive method for evaluating sugarcane mineral contents.