Influences of Detection Position and Double Detection Regions on Determining Soluble Solids Content (SSC) for Apples Using On-line Visible/Near-Infrared (Vis/NIR) Spectroscopy

Abstract

With increasing living standards, more attention has been drawn to the eating quality of fruits. To meet the standards of market and consumers, on-line fruits grading in terms of the internal qualities, such as soluble solids content (SSC), is necessary in the industrial scale. Near-infrared (NIR) spectroscopy technology has advantages of being rapid, safe, non-destructive, and environmentally friendly; thus, it was widely applied in this area. Therefore, in the present work, an on-line near-infrared SSC detection system for apples based on bicone roller transportation was used to compare the influences of detection positions and double detection regions with the help of mono-branch optical fiber and binary-branch optical fiber on the performance of the prediction models. Better prediction models were obtained at the specific position than those at the random one. The system with the binary-branch optical fiber proved superior robustness, while that with the mono-branch optical fiber proved superior accuracy. The optimal model, when considering robustness and accuracy, had a root mean square error of calibration (RMSEC), determination coefficient of calibration (RC2), root mean square error of validation (RMSEP), and determination coefficient of validation (RP2) of 0.568%, 0.7319, 0.610%, and 0.6295, respectively. It was established by data simultaneously detected in two different regions utilizing the binary-branch optical fiber at the specific position. This work provided a possible solution on improving the model robustness in the practical application of on-line NIR detection for the SSC measurement of apples.