Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices. (29th June 2020)
- Record Type:
- Journal Article
- Title:
- Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices. (29th June 2020)
- Main Title:
- Comparison between Hyperspectral Imaging and Chemical Analysis of Polyphenol Oxidase Activity on Fresh-Cut Apple Slices
- Authors:
- Shrestha, Luna
Kulig, Boris
Moscetti, Roberto
Massantini, Riccardo
Pawelzik, Elke
Hensel, Oliver
Sturm, Barbara - Other Names:
- Ming Li-June Academic Editor.
- Abstract:
- Abstract : 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 3.7 e −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 asAbstract : 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 3.7 e −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. … (more)
- Is Part Of:
- Journal of spectroscopy. Volume 2020(2020)
- Journal:
- Journal of spectroscopy
- Issue:
- Volume 2020(2020)
- Issue Display:
- Volume 2020, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 2020
- Issue:
- 2020
- Issue Sort Value:
- 2020-2020-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-06-29
- Subjects:
- Spectrum analysis -- Periodicals
543.505 - Journal URLs:
- https://www.hindawi.com/journals/jspec/ ↗
- DOI:
- 10.1155/2020/7012525 ↗
- Languages:
- English
- ISSNs:
- 2314-4920
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14388.xml