Sugar quality (Brix and Pol) is the key index to evaluate the value of sugarcane. Hence, a rapid, accurate, and time-efficient method is needed to determine the sugar quality. This study develops a two-point sugarcane quality model that uses a benchtop near infrared (NIR) spectrometer and a portable visible-near infrared (Vis-NIR) spectrometer to measure the sugarcane juice and stalk spectra, respectively. GT two experiments for developing a two-point sugarcane quality model. In the first, a model to calibrate the sugar quality as measured by a polarimeter and refractometer, and also by the benchtop NIR spectrometer. In the second, we developed a model to calibrate the sugar quality predicted from the calibration model developed in the first experiment, by measuring the sugarcane stalk absorption spectra using a portable Vis-NIR spectrometer. The results of the first experiment showed that the standard normal variate (SNV) spectral pretreatment was the most effective method for Brix calibration, with a coefficient of determination of prediction (r(p)(2)) of 0.99 and root mean square error of prediction (RMSEP) of 0.2. In the case of Pol, second derivatives were the best spectral pretreatment for effective calibration (r(2) = 0.99, RMSEP = 0.3). The results of the second experiment showed that the multiple linear regression model developed using the stalk spectra with the second derivative was the best model for Brix calibration (r(2) = 0.70, RMSEP = 1.4). The second derivative with the SNV pretreatment was best for Pol calibration (r(2) = 0.70, RMSEP = 1.4). Our study showed that a sugar quality regression model can be developed for a portable Vis-NIR spectrometer using the data from the sugar quality predicted by a benchtop NIR spectrometer.
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