Ripeness Prediction of Postharvest Kiwifruit Using a MOS E-Nose Combined with Chemometrics

Abstract

Postharvest kiwifruit continues to ripen for a period until it reaches the optimal “eating ripe” stage. Without damaging the fruit, it is very difficult to identify the ripeness of postharvest kiwifruit by conventional means. In this study, an electronic nose (E-nose) with 10 metal oxide semiconductor (MOS) gas sensors was used to predict the ripeness of postharvest kiwifruit. Three different feature extraction methods (the max/min values, the difference values and the 70th s values) were employed to discriminate kiwifruit at different ripening times by linear discriminant analysis (LDA), and results showed that the 70th s values method had the best performance in discriminating kiwifruit at different ripening stages, obtaining a 100% original accuracy rate and a 99.4% cross-validation accuracy rate. Partial least squares regression (PLSR), support vector machine (SVM) and random forest (RF) were employed to build prediction models for overall ripeness, soluble solids content (SSC) and firmness. The regression results showed that the RF algorithm had the best performance in predicting the ripeness indexes of postharvest kiwifruit compared with PLSR and SVM, which illustrated that the E-nose data had high correlations with overall ripeness (training: R2 = 0.9928; testing: R2 = 0.9928), SSC (training: R2 = 0.9749; testing: R2 = 0.9143) and firmness (training: R2 = 0.9814; testing: R2 = 0.9290). This study demonstrated that E-nose could be a comprehensive approach to predict the ripeness of postharvest kiwifruit through aroma volatiles.

A Comparative Study of PLSR and SVM-R with Various Preprocessing Techniques for the Quantitative Determination of Soluble Solids Content of Hardy Kiwi Fruit by a Portable Vis/NIR Spectrometer

“…Green, black, and oolong teas were identified using SVM as an application of chemometrics [ 23 ]. Du et al [ 24 ] investigated the eating ripe stage and SSC of Actinidia chinensis . cv.…”

Tracing internal quality and aroma of a red-fleshed kiwifruit during ripening by means of GC-MS and E-nose

“…Du et al used a MOS E-nose system to predict the ripeness of kiwifruit, and results showed overall ripeness, SSC, and rmness were well predicted by E-nose combined with chemometrics. 17 The above studies have illustrated the potential of E-nose technique in detecting the quality of fruit, but few articles have been published in evaluating the avor quality of fruit by E-nose technology. As mentioned above, the aroma of fruit is a result of complex volatile compounds, and it may have tight relationships with internal quality.…”

E-nose Prototype to Monitoring the Growth and Maturation of Peaches in the Orchard

“…Table VII shows that the proposed prototype obtained a reduced error rate (98.08% accuracy), compared to other closer studies with e-noses to measure the maturation of peaches found in the literature. The main ones are: 93% of Brezmes et al [35], 97.56% of Benedetti et al [34] and 85% of Guohua et al [36]; a considerable standard error of 8.77 reported by Zhang et al [33]; R 2 = 0.9928 of Du et al [45], and 97.47% of Yang et al [46].…”