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The nondestructive detection of the quality attributes and maturity of kiwifruits by using hyperspectral imaging technique and chemometric algorithms were investigated. Two models of the partial least square regression and principal components regression were built up based on full variables. The multiple linear regression (MLR) was designed to develop the simplified detection models based on feature variables chosen by the successive projection algorithm and competitive adaptive reweighted sampling (CARS). Results showed that the optimal CARS‐MLR model was designed to determine the quality attributes with RPD above 2.2. Particularly, about SSC (R2P = 0.896, RMSEP = 0.628%, RPD = 3.121), about firmness (R2P = 0.871, RMSEP = 1.065 kg/cm2, RPD = 2.809). The partial least square discriminant analysis and simplified k nearest neighbor models were designed to discriminate the kiwifruits maturity stages with a classification accuracy of 93.3% and 98.3%. This research demonstrates that the hyperspectral imaging technology coupled with chemometric algorithms is promising for the quality assessment and maturity discrimination of kiwifruits. Practical applications: The quality and maturity of kiwifruits have a direct relationship with the indicators of the SSC, firmness and color. Traditional methods for predicting the quality and maturity of kiwifruits are destructive, time‐consuming, and unusually affected by subjective factors. Hyperspectral imaging technique has the advantages of nondestructive, rapid, non‐pollution, and so on. The results demonstrated that the hyperspectral imaging technique coupled with chemometric algorithms can predict the quality and maturity of kiwifruits, which provides a theoretical basis to develop a real‐time detection system to predict the quality and maturity of fruits. [ABSTRACT FROM AUTHOR]

BACKGROUND: The application of exogenous plant growth regulator, for example forchlorfenuron (CPPU), on kiwifruits has become an important factor that influences kiwifruit economic efficiency and the health development of the kiwifruit industry. Owing to the slight difference in calyx shape between the kiwifruits treated with CPPU (CPPU‐treated kiwifruits) and the kiwifruits without CPPU treatment (CPPU‐untreated kiwifruits), this study aims to provide a cheap, quick, convenient, and non‐destructive method for identifying CPPU‐treated kiwifruits based on the images of kiwifruits captured at visible lights. RESULTS: The identification method includes three steps. Firstly, the kiwifruit was extracted from the background by using Otsu algorithm, hole filling operation and 'bwareaopen' function. Secondly, the calyx was extracted by using corrosion, image enhancement, hole filling and closing operations. Finally, the length/width ratio of the minimum enclosing rectangle of calyx region was calculated. The kiwifruit was regarded as a CPPU‐treated kiwifruit if the length/width ratio of the rectangle was higher than 1.6. Otherwise, the kiwifruit was regarded as a CPPU‐untreated one. The method had the total identification accuracy rate of 90.0% when the kiwifruit images were captured either by utilizing a smartphone at normal lighting condition or by using an image acquisition system. CONCLUSION: The programs run on computer and smartphone were developed, and they could realize kiwifruit identification in 0.6 s and 2 s, respectively. The study makes identifying CPPU‐treated kiwifruits in online processing be realizable, and offers a convenient method for kiwifruit consumers. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Abstract: BACKGROUND: Fungal development in agricultural products may cause mycotoxin contamination, which is a significant threat to food safety. Patulin (PAT) and PAT‐producer contamination has been established as a worldwide problem. The present study aimed to investigate the mycoflora and PAT‐producers present in kiwifruits and environmental samples collected from orchards and processing plants in Shaanxi Province, China. RESULTS: Variations in mycoflora were observed in different samples, with penicillia and aspergilli as the predominant genera. Approximately 42.86% of dropped fruits were contaminated with PAT‐producers, which harbored the 6‐methylsalicylic acid synthase and the isoepoxydon dehydrogenase genes that are involved in PAT biosynthesis. The growth of Penicillium expansum, Penicillium griseofulvum and Penicillium paneum in kiwi puree agar (KPA) medium and kiwi juice well fitted the modified Gompertz and Baranyi and Roberts models (R2 ≥ 0.95). A significant positive correlation between colony diameter and PAT content in KPA medium of P. expansum and P. griseofulvum was observed (P < 0.05). CONCLUSIONS: The present study analyzed the mycofloral composition and the potential risk for PAT and PAT‐producer contamination in kiwifruit, which may be utilized in the establishment of proper management practices in the kiwifruit industry. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]