Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties - Sun, Xudong; Deng, Di; Liu, Jiacheng; Feng, Shaoran (Frontiers in Nutrition, 2022)
The variation of fruit among batch except target component influences the performance of portable near infrared spectroscopy (NIRS) instrument and then determines the success or failure for practical application in fruit industry. Model development and updating methods were investigated for determining soluble solid contents (SSC) and titrable acidity (TA) of Newhall navel orange. The pretreatment and variable selection methods were explored for building partial least square regression (PLSR) models. For SSC, the combination of second derivative (2D) and variable sorting for normalization (VSN) and spectral range of 672-912 nm by window search were recommended in root mean square error of prediction (RMSEP). But for TA, the lowest RMSEP of was obtained in full spectral range and with 2D pretreatment. The RMSEP values for SSC and TA in predicting an independent set were decreased by 21.5 % and 9.6 % using the upgrade method of dynamic orthogonal projection (DOP) compared with the control group. The results suggested model development and upgrade with DOP could improve the robustness of the portable NIRS instrument in predicting SSC and TA of citrus fruit.