Abstract
To investigate the feasibility of using near-infrared (NIR) spectral technology to detect the soluble solids content (SSC) of Malus micromalus Makino, rapid and non-destructive prediction models of SSC were studied using least-square support vector regression (LS-SVR), partial least squares regression (PLSR), and the error back propagation artificial neural network (BP-ANN). First, 110 samples of NIR diffuse reflectance spectra in the wavelength range of 400.41-1083.89 nm were obtained, and then were divided into the calibration set and prediction set by sample set partitioning based on the joint x-y distance (SPXY) algorithm. Second, we compared the prediction performance of the PLSR model after preprocessing by nine spectral preprocessing methods, and applied data dimension reduction methods (random frog, the successive projections algorithm (SPA), and principal component analysis) for variable selection. Finally, the effect of applying full spectrum and characteristic spectrum modeling on SSC prediction accuracy was compared and analyzed. The comparison studies confirmed that the optimal fusion model of SPA-LS-SVR had the best performance (R C = 0.9629, R P = 0.9029, RMSEC = 0.199, RMSEP = 0.271). The experimental results could provide a reference for future development of the internal component analysis system for Malus micromalus Makino based on NIR spectroscopy and its classification system using SSC as the classification standard.
Highlights
Malus micromalus Makino, Rosaceae apple, a rare fruit found only in China, is an important contributor to food production and nutrition [1]
The solids content (SSC) prediction models using different pretreatment methods based on partial least squares regression (PLSR) were established
This illustrated that the model utilizing the standard normal variable transformation (SNV) algorithm for pretreatment had better stability and cross validation effect than the other models, and it was selected for further analysis
Summary
Malus micromalus Makino, Rosaceae apple, a rare fruit found only in China, is an important contributor to food production and nutrition [1]. It is a good raw material for fruit processing and is rich in soluble solids content (SSC), acids, and calcium. It has been processed into brandy, beverages, pastries, and other products. Due to its high nutritional and economic value, it has been widely promoted by the local government as a special agricultural product of Fugu Valley to be shipped to all parts of the country and across the world
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have