Walnut dreg protein hydrolysates(WDPHs)exhibit a variety of biological activities,however,the cyclooxygenase-2(COX-2)inhibitory peptide of WDPHs remain unclear.The aim of this study was to rapidly screen for such pept...Walnut dreg protein hydrolysates(WDPHs)exhibit a variety of biological activities,however,the cyclooxygenase-2(COX-2)inhibitory peptide of WDPHs remain unclear.The aim of this study was to rapidly screen for such peptides in WDPHs through a combination of in silico and in vitro analysis.In total,1262 peptide sequences were observed by nano liquid chromatography/tandem mass spectrometry(nano LC-MS/MS)and 4 novel COX-2 inhibitory peptides(AGFP,FPGA,LFPD,and VGFP)were identified.Enzyme kinetic data indicated that AGFP,FPGA,and LFPD displayed mixed-type COX-2 inhibition,whereas VGFP was a non-competitive inhibitor.This is mainly because the peptides form hydrogen bonds and hydrophobic interactions with residues in the COX-2 active site.These results demonstrate that computer analysis combined with in vitro evaluation allows for rapid screening of COX-2 inhibitory peptides in walnut protein dregs.展开更多
The demand for plant protein is increasing significantly due to the shortage of protein resources.Walnut protein,the main by-product of preparing walnut oil,has limited application in the food industry due to its poor...The demand for plant protein is increasing significantly due to the shortage of protein resources.Walnut protein,the main by-product of preparing walnut oil,has limited application in the food industry due to its poor solubility.It was found that the soy protein isolate(SPI)concentration had significant effects on the gel properties of the walnut protein isolate(WNPI)-κ-Carrageenan(KC)composite system treated with 15 mmol/L NaCl.The results showed that the gel strength of the composite system increased first and then decreased with the increased concentration of SPI from 0 to 2.5%.The best rheological properties,texture properties,water holding capacity((92.03±1.05)%),swelling ratio((2.04±0.19)%),freeze-thaw stability and thermal stability(85.53°C)of the composite gel were found at an SPI concentration of 1%.In the meantime,the secondary structure of protein had the least α-helix content of 10.17% and the highest β-sheet content of 39.64%,the fluorescence intensity and free sulfhydryl content reached the highest value.1% SPI could also act as a filler for WNPI to enhance the intermolecular forces such as hydrophobic interaction between the two substances,thus forming a stable gel network structure.This study can provide technical support for improving the gel properties of walnut protein and producing new plant protein gel products.展开更多
Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential sol...Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential solutions for walnuts nutrients detection by obtaining both spectral and textural information.However,the redundancy and large computation of spectral data prevent the widespread application of hyperspectral technology for high throughput evaluation.For walnut kernel protein inversion from hyperspectral image,this study proposed a novel feature selection method,which is named as improved whale optimized algorithm(IWOA).In the IWOA,a comprehensive feature selection criterion was applied in the iterative process,which fully considered the relevance of spectra information with target variables,representative ability of the selected wavebands to entire spectra,and redundancy of the selected wavebands.Especially in the relevance with target variables,the amplitude and shape characteristics of the spectra were both taken into consideration.Eight wavelengths around 996,1225,1232,1377,1552,1600,1691 and 1700 nm were then selected as the sensitive wavelengths to walnut protein.These wavelengths showed good correlation with certain chemical compounds related to protein contents mechanistically.Then three protein prediction models were established.After analysis and comparison,the model based on the selected wavelengths got better results with the one based on the full spectrum.Compared to the models based on solely spectral information,the model that combine spectral and textural information outperformed and got the best prediction results.The R2 in the calibration group was 0.9047,and the root mean square errors(RMSE)was 11.1382 g/kg.In the validation group,the R2 was 0.8537,and the RMSE was 18.9288 g/kg.The results demonstrated that the combination of the selected wavelengths through the IWOA with the textural characteristics could effectively estimate walnut protein contents.And the proposed method can be extended to the detection and inversion of other nutritional variables of nuts.展开更多
Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential sol...Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential solutions for walnuts nutrients detection by obtaining both spectral and textural information.However,the redundancy and large computation of spectral data prevent the widespread application of hyperspectral technology for high throughput evaluation.For walnut kernel protein inversion from hyperspectral image,this study proposed a novel feature selection method,which is named as improved whale optimized algorithm(IWOA).In the IWOA,a comprehensive feature selection criterion was applied in the iterative process,which fully considered the relevance of spectra information with target variables,representative ability of the selected wavebands to entire spectra,and redundancy of the selected wavebands.Especially in the relevance with target variables,the amplitude and shape characteristics of the spectra were both taken into consideration.Eight wavelengths around 996,1225,1232,1377,1552,1600,1691 and 1700 nm were then selected as the sensitive wavelengths to walnut protein.These wavelengths showed good correlation with certain chemical compounds related to protein contents mechanistically.Then three protein prediction models were established.After analysis and comparison,the model based on the selected wavelengths got better results with the one based on the full spectrum.Compared to the models based on solely spectral information,the model that combine spectral and textural information outperformed and got the best prediction results.The R^(2)in the calibration group was 0.9047,and the root mean square errors(RMSE)was 11.1382 g/kg.In the validation group,the R^(2)was 0.8537,and the RMSE was 18.9288 g/kg.The results demonstrated that the combination of the selected wavelengths through the IWOA with the textural characteristics could effectively estimate walnut protein contents.And the proposed method can be extended to the detection and inversion of other nutritional variables of nuts.展开更多
基金supported by the Major Project of Science and Technology Department of Yunnan Province (202002AA100005 and 202102AE090027-2)the Project of Yunnan Province Food and Drug Homologous Resources Functional Food Innovation Team (A3032023057)+2 种基金the YEFICRC project of Yunnan provincial key programs (2019ZG009)Yunnan Province Ten Thousand Plan Industrial Technology Talents project (YNWR-CYJS-2020-010)the Yunnan Provincial Department of Science and Technology Agricultural Joint Special Project (202101BD070001-120)。
文摘Walnut dreg protein hydrolysates(WDPHs)exhibit a variety of biological activities,however,the cyclooxygenase-2(COX-2)inhibitory peptide of WDPHs remain unclear.The aim of this study was to rapidly screen for such peptides in WDPHs through a combination of in silico and in vitro analysis.In total,1262 peptide sequences were observed by nano liquid chromatography/tandem mass spectrometry(nano LC-MS/MS)and 4 novel COX-2 inhibitory peptides(AGFP,FPGA,LFPD,and VGFP)were identified.Enzyme kinetic data indicated that AGFP,FPGA,and LFPD displayed mixed-type COX-2 inhibition,whereas VGFP was a non-competitive inhibitor.This is mainly because the peptides form hydrogen bonds and hydrophobic interactions with residues in the COX-2 active site.These results demonstrate that computer analysis combined with in vitro evaluation allows for rapid screening of COX-2 inhibitory peptides in walnut protein dregs.
基金funded by the Research and Application of Key Technology of Xinjiang Walnut Oil Refining Deep Processing(2022A02004-4)the National Key R&D Program of China(2018YFD0400302)+2 种基金the Special Fund for Anhui Agriculture Research System(AHCYJSTX-NCPJG)-15the Cooperative Projects of Hefei University of Technology-Wuhan Xudong Food Co.,Ltd.(W2020JSKF0457,W2021JSKF0356)the 7^(th) Young Elite Scientist Sponsorship Program by CAST(2021QNRC001).
文摘The demand for plant protein is increasing significantly due to the shortage of protein resources.Walnut protein,the main by-product of preparing walnut oil,has limited application in the food industry due to its poor solubility.It was found that the soy protein isolate(SPI)concentration had significant effects on the gel properties of the walnut protein isolate(WNPI)-κ-Carrageenan(KC)composite system treated with 15 mmol/L NaCl.The results showed that the gel strength of the composite system increased first and then decreased with the increased concentration of SPI from 0 to 2.5%.The best rheological properties,texture properties,water holding capacity((92.03±1.05)%),swelling ratio((2.04±0.19)%),freeze-thaw stability and thermal stability(85.53°C)of the composite gel were found at an SPI concentration of 1%.In the meantime,the secondary structure of protein had the least α-helix content of 10.17% and the highest β-sheet content of 39.64%,the fluorescence intensity and free sulfhydryl content reached the highest value.1% SPI could also act as a filler for WNPI to enhance the intermolecular forces such as hydrophobic interaction between the two substances,thus forming a stable gel network structure.This study can provide technical support for improving the gel properties of walnut protein and producing new plant protein gel products.
基金This paper was supported by the Science and Technology Innovation Key Cultivation Project of Xinjiang Academy of Agricultural Sciences(xjkcpy-004).
文摘Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential solutions for walnuts nutrients detection by obtaining both spectral and textural information.However,the redundancy and large computation of spectral data prevent the widespread application of hyperspectral technology for high throughput evaluation.For walnut kernel protein inversion from hyperspectral image,this study proposed a novel feature selection method,which is named as improved whale optimized algorithm(IWOA).In the IWOA,a comprehensive feature selection criterion was applied in the iterative process,which fully considered the relevance of spectra information with target variables,representative ability of the selected wavebands to entire spectra,and redundancy of the selected wavebands.Especially in the relevance with target variables,the amplitude and shape characteristics of the spectra were both taken into consideration.Eight wavelengths around 996,1225,1232,1377,1552,1600,1691 and 1700 nm were then selected as the sensitive wavelengths to walnut protein.These wavelengths showed good correlation with certain chemical compounds related to protein contents mechanistically.Then three protein prediction models were established.After analysis and comparison,the model based on the selected wavelengths got better results with the one based on the full spectrum.Compared to the models based on solely spectral information,the model that combine spectral and textural information outperformed and got the best prediction results.The R2 in the calibration group was 0.9047,and the root mean square errors(RMSE)was 11.1382 g/kg.In the validation group,the R2 was 0.8537,and the RMSE was 18.9288 g/kg.The results demonstrated that the combination of the selected wavelengths through the IWOA with the textural characteristics could effectively estimate walnut protein contents.And the proposed method can be extended to the detection and inversion of other nutritional variables of nuts.
基金supported by the Science and Technology Innovation Key Cultivation Project of Xinjiang Academy of Agricultural Sciences(Grant No.xjkcpy-004).
文摘Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses.Hyperspectral image technology provides potential solutions for walnuts nutrients detection by obtaining both spectral and textural information.However,the redundancy and large computation of spectral data prevent the widespread application of hyperspectral technology for high throughput evaluation.For walnut kernel protein inversion from hyperspectral image,this study proposed a novel feature selection method,which is named as improved whale optimized algorithm(IWOA).In the IWOA,a comprehensive feature selection criterion was applied in the iterative process,which fully considered the relevance of spectra information with target variables,representative ability of the selected wavebands to entire spectra,and redundancy of the selected wavebands.Especially in the relevance with target variables,the amplitude and shape characteristics of the spectra were both taken into consideration.Eight wavelengths around 996,1225,1232,1377,1552,1600,1691 and 1700 nm were then selected as the sensitive wavelengths to walnut protein.These wavelengths showed good correlation with certain chemical compounds related to protein contents mechanistically.Then three protein prediction models were established.After analysis and comparison,the model based on the selected wavelengths got better results with the one based on the full spectrum.Compared to the models based on solely spectral information,the model that combine spectral and textural information outperformed and got the best prediction results.The R^(2)in the calibration group was 0.9047,and the root mean square errors(RMSE)was 11.1382 g/kg.In the validation group,the R^(2)was 0.8537,and the RMSE was 18.9288 g/kg.The results demonstrated that the combination of the selected wavelengths through the IWOA with the textural characteristics could effectively estimate walnut protein contents.And the proposed method can be extended to the detection and inversion of other nutritional variables of nuts.
