अमूर्त

Research on prediction for ripeness of apples by means of NIRspectroscopy

Qiongyan Wu, Ming Sun

Prediction for ripeness of apple had an important significance to determine the optimumharvest time and the accurate classification of apple. Soluble solids content (SSC) and firmness, as important internal physical and chemical indicators of apple, were important parameters of the evaluation of the ripeness degree of apple. Since Near infrared spectral analysis technologywas a fast and non-destructivemethod to determine the internal quality of apple, different pretreatment methods and modeling methods were studied in this paper, and the best combined method was chosen as the modelingmethod of SSC and firmness. The result showed partial least squares (PLS) was the best modeling methods both to SSC and firmness. The modeling correlation coefficient, calibration standard deviation, the prediction correlation coefficient and predicted standard deviation of SSC were: 0.9093, 0.6145, 0.9622 and 0.4104, respectively. The modeling correlation coefficient, calibration standard deviation, the prediction correlation coefficient and predicted standard deviation of firmness were: 0.8463, 0.3825, 0.8268 and 0.2919, respectively. The ripeness degree could be evaluated by SSC and firmness which was detected by NIR spectral analysis. At last, the evaluation software for the ripeness of apple which was based on matlab GUI was designed.