Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy. (13th July 2019)
- Record Type:
- Journal Article
- Title:
- Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy. (13th July 2019)
- Main Title:
- Non‐destructive determination of strawberry fruit and juice quality parameters using ultraviolet, visible, and near‐infrared spectroscopy
- Authors:
- Włodarska, Katarzyna
Szulc, Julia
Khmelinskii, Igor
Sikorska, Ewa - Abstract:
- Abstract: BACKGROUND: The development of rapid methods for the determination of the soluble solids content (SSC) and total phenolic content (TPC) in fruit juices is of great interest. Soluble solids content is related to sensory attributes, whereas TPC is related to the antioxidant capacity of juices. The aim of this study was to develop and optimize the calibration models for the prediction of the SSC and TPC of strawberry juices from the spectra of fruit and juices. RESULTS: Near infrared (NIR) spectra were measured for strawberry fruit and ultraviolet (UV), visible (VIS), and NIR spectra were measured for juices. The partial least squares regression models were validated using the test sample set and their predictive ability was evaluated on the basis of determination coefficients (R 2 P ) and root mean square error of prediction (RMSEP). For SSC the models with high predictive ability were obtained using spectra of fruit (R 2 P = 0.929, RMSEP = 0.46%) or juices (R 2 P = 0.979, RMSEP = 0.25%) in the NIR range. The optimal models for TPC were obtained using NIR spectra of fruit (R 2 P = 0.834, RMSEP = 130.8 mg GA L −1 ) or UV–VIS–NIR spectra of juices (R 2 P = 0.844, RMSEP = 126.7 mg GA L −1 ). CONCLUSION: The results show the potential of spectroscopy for predicting quality parameters of strawberry juices from the juice spectra itself or non‐destructively from the fruit spectra. They may contribute to the development of fruit sorting systems to optimize their use in juiceAbstract: BACKGROUND: The development of rapid methods for the determination of the soluble solids content (SSC) and total phenolic content (TPC) in fruit juices is of great interest. Soluble solids content is related to sensory attributes, whereas TPC is related to the antioxidant capacity of juices. The aim of this study was to develop and optimize the calibration models for the prediction of the SSC and TPC of strawberry juices from the spectra of fruit and juices. RESULTS: Near infrared (NIR) spectra were measured for strawberry fruit and ultraviolet (UV), visible (VIS), and NIR spectra were measured for juices. The partial least squares regression models were validated using the test sample set and their predictive ability was evaluated on the basis of determination coefficients (R 2 P ) and root mean square error of prediction (RMSEP). For SSC the models with high predictive ability were obtained using spectra of fruit (R 2 P = 0.929, RMSEP = 0.46%) or juices (R 2 P = 0.979, RMSEP = 0.25%) in the NIR range. The optimal models for TPC were obtained using NIR spectra of fruit (R 2 P = 0.834, RMSEP = 130.8 mg GA L −1 ) or UV–VIS–NIR spectra of juices (R 2 P = 0.844, RMSEP = 126.7 mg GA L −1 ). CONCLUSION: The results show the potential of spectroscopy for predicting quality parameters of strawberry juices from the juice spectra itself or non‐destructively from the fruit spectra. They may contribute to the development of fruit sorting systems to optimize their use in juice production, as well as fast‐screening methods for quality control of juices. © 2019 Society of Chemical Industry … (more)
- Is Part Of:
- Journal of the science of food and agriculture. Volume 99:Number 13(2019)
- Journal:
- Journal of the science of food and agriculture
- Issue:
- Volume 99:Number 13(2019)
- Issue Display:
- Volume 99, Issue 13 (2019)
- Year:
- 2019
- Volume:
- 99
- Issue:
- 13
- Issue Sort Value:
- 2019-0099-0013-0000
- Page Start:
- 5953
- Page End:
- 5961
- Publication Date:
- 2019-07-13
- Subjects:
- soluble solids content -- total phenolic content -- UV, VIS, and NIR spectroscopy -- variable selection -- PLS regression
Food -- Periodicals
Agriculture -- Periodicals
664 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0010 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/jsfa.9870 ↗
- Languages:
- English
- ISSNs:
- 0022-5142
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5055.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11689.xml