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Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices

Shrestha, L.; Kulig, B.; Moscetti, R.; Massantini, R.; Pawelzik, Elke; Hensel, O. and Sturm, B. (2020) Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices. Journal of Spectroscopy, n.n., pp. 1-10.

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Document available online at: https://www.hindawi.com/journals/jspec/2020/7012525/


The assessment of the quality of fresh-cut apple slices is important for processing, storage, market value, and consumption. Determination of polyphenol oxidase activity (PPO) in apples is critical for controlling the quality of the final product (i.e., dried apples and juices). Hyperspectral imaging (HSI) is a nondestructive, noncontact, and rapid food quality assessment technique. It has the potential to detect physical and chemical quality attributes of foods such as PPO of apple. The aim of this study was to investigate the suitability of HSI in the visible and near-infrared (VIS-NIR) range for indirect assessment of PPO activity of fresh-cut apple slices. Apple slices of two cultivars (cv. Golden Delicious and Elstar) were used to build a robust detection algorithm, which is independent of cultivars and applied treatments. Partial least squares (PLS) regression using the 7-fold cross-validation method and method comparison analysis (Bland–Altman plot, Passing–Bablok regression, and Deming regression) were performed. The 95% confidence interval (CI) bands for the Bland–Altman analysis between the methods were −4.19 and 13.11, and the mean difference was 3.7e−12. The Passing–Bablok regression had a slope of 0.8 and an intercept of 7.6. The slope of the Deming regression was 0.8 within the CI bands of 0.56 and 1.10. These results show acceptable performance and no significant deviation from linearity. Hence, the results demonstrated the feasibility of HSI as an indirect alternative to the standard chemical analysis of PPO enzyme activity.

EPrint Type:Journal paper
Keywords:BÖLN, BOELN, BÖL, BOEL, FKZ 17OE005, SusOrgPlus
Agrovoc keywords:
analytical methods
Subjects: Food systems > Food security, food quality and human health
Food systems > Processing, packaging and transportation
Research affiliation: European Union > CORE Organic > CORE Organic Cofund > SusOrgPlus
Germany > Federal Organic Farming Scheme - BOELN > Food > Processing
Germany > University of Göttingen
Germany > University of Kassel > Department of Agricultural Engineering and Agricultural Engineering in the Tropics and Subtropics
Horizon Europe or H2020 Grant Agreement Number:727495
Related Links:https://www.susorgplus.eu, https://orgprints.org/cgi/search/advanced?addtitle%2Ftitle=&keywords=17OE005&projects=BOEL&_order=bypublication&_action_search=Suchen
Deposited By: von Gersdorff, Gardis J.E.
ID Code:38730
Deposited On:08 Jan 2021 11:26
Last Modified:08 Jan 2021 11:34
Document Language:English
Refereed:Peer-reviewed and accepted

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