Abstract: To conveniently and nondestructively detect the soluble solids content (SSC) of kiwifruits, near infrared (NIR) spectra of ‘Huayou’, ‘Xuxiang’, and ‘Xixuan’ kiwifruits were obtained by using a portable system for SSC detection in kiwifruit based on a mini-spectrometer. The effective wavelengths were selected by different methods, and the effects of the selected characteristic wavelengths and the full spectra on the prediction precision of the models established by partial least square regression (PLSR) were compared. Slope/bias (S/B) algorithm was used to correct the model for ‘Huayou’ kiwifruits to predict the SSCs of ‘Xuxiang’ and ‘Xixuan’ kiwifruits. The results showed that the SPA algorithm could effectively extract the effective wavelengths. The root mean square error of predictions (RMSEPs) were 0.583, 0.678 and 0.646 °Brix for ‘Huayou’, ‘Xuxiang’, and ‘Xixuan’ kiwifruits, respectively. A total of 10 ‘Xuxiang’ and 50 ‘Xixuan’ samples were sufficient to improve the prediction performance of the corrected model with RMSEP of 0.966 and 0.875 °Brix, respectively. This study can offer useful information for developing a more accurate and portable miniature integrated detector for kiwifruit SSC.

Key words: kiwifruit, soluble solids content, near infrared spectroscopy, portable, slope/bias (S/B) algorithm