Modification of Soluble Solids Content sorting line based on light source transmitting and receiving integrated probe

Traditional quality sorting methods have been unable to meet people's increasing demands for fruit flavour and quality. Producers must therefore develop their traditional quality sorting methods to achieve sugar content sorting and ensure favourable flavour and quality. To address this, the near-infrared reflection spectra of navel oranges were collected separately through two different detection methods. The spectral energy of their ring transmission and diffuse reflection had to be stronger than that of the multi-point transmission and diffuse reflections. The positions of their peaks and troughs had to be approximately the same. The near-infrared diffuse reflectance spectra were preprocessed using baseline correction, multivariate scattering correction, first and second derivatives to reduce the influence of stray light and noise. A Partial Least Squares (PLS) model for the sugar content information that was collected through the two different reflection detection methods was established for their comparison and analysis. The experimental results show that the baseline correction preprocessing method produced the best results between the two methods. Its predicted correlation coefficient of sugar under ring transmission and diffuse reflection detection was 0.81 and its root mean square error was 0.46° Brix. The estimated correlation coefficient of the sugar content model using the multi-point transmission and diffuse reflection detection method was 0.76 and its root mean square error was 0.53° Brix. This research shows that it is feasible to use PLS modeling and near-infrared diffuse reflectance spectrum to upgrade the sugar content sorting methodology used on production lines.