In situ monitoring of grape seed protein hydrolysis by Raman spectroscopy
Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval part...
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Published in | Journal of food biochemistry Vol. 45; no. 4; pp. e13646 - n/a |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
01.04.2021
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Subjects | |
Online Access | Get full text |
ISSN | 0145-8884 1745-4514 1745-4514 |
DOI | 10.1111/jfbc.13646 |
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Abstract | Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si‐PLS) models of DH, IC50, and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC50 is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real‐time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy.
Practical applications
This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real‐time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry.
Real‐time monitoring of proteolysis of grape seed protein was done using model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. |
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AbstractList | Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC₅₀ of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si‐PLS) models of DH, IC₅₀, and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC₅₀ is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real‐time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. PRACTICAL APPLICATIONS: This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real‐time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry. Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si‐PLS) models of DH, IC50, and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC50 is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real‐time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. Practical applications This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real‐time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry. Real‐time monitoring of proteolysis of grape seed protein was done using model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si-PLS) models of DH, IC50 , and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC50 is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real-time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. PRACTICAL APPLICATIONS: This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real-time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry.Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si-PLS) models of DH, IC50 , and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC50 is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real-time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. PRACTICAL APPLICATIONS: This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real-time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry. Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC of the ACE inhibitory activity, and peptide content of the digestive products of grape seed protein were analyzed offline. The partial least squares (PLS), interval partial least squares (IPLS), and joint interval partial least squares (Si-PLS) models of DH, IC , and peptide content were established and the optimal pretreatment method was selected. In the optimal model, the corrected model r of the grape seed protein hydrolysis degree is 0.997, the Root Mean Square Error of Cross Validation (RMSECV) is 0.507%. The predicted model r value is 0.9932, the Root Mean Square Error of Prediction (RMSEP) is 1.15%. The corrected model r value of the IC is 0.9965, the RMSECV is 11.9%. The r value and RMSEP of predicted model are 0.9978 and 9.64%. The corrected model r value of the peptide content is 0.9955, the RMSECV is 12.7%, the predicted model r value is 0.9953, and the RMSEP is 15.4%. These results showed that in situ real-time monitoring of grape seed protein hydrolysis process can be achieved by Raman spectroscopy. PRACTICAL APPLICATIONS: This study uses Raman spectroscopy method to establish the quantification of proteolysis, IC50, and peptide content of the simulated digestive products during grape seed proteolysis. Analyze the model to monitor and evaluate the target parameters during the entire grape seed proteolysis process. In situ real-time monitoring of grape seed proteolysis is of great significance to the entire grape seed active peptide industry. |
Author | Ding, Qingzhi Gu, Xiangyue He, Ronghai Zhang, Ting Pan, Wenwen Ma, Haile Sun, Nianzhen Su, Xiaodong Rehman Sheikh, Arooj Luo, Lin |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33569796$$D View this record in MEDLINE/PubMed |
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Snippet | Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC50 of the ACE inhibitory... Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC of the ACE inhibitory... Raman spectroscopy was used to monitor the enzymatic hydrolysis process of grape seed protein. The degree of hydrolysis (DH), IC₅₀ of the ACE inhibitory... |
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SubjectTerms | active peptides enzymatic hydrolysis grape seed protein grape seeds hydrolysis industry inhibitory concentration 50 peptides prediction proteolysis Raman spectroscopy |
Title | In situ monitoring of grape seed protein hydrolysis by Raman spectroscopy |
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