Peptides are functional active fragments of proteins which can provide nutrients needed for human growth and development,and they also have unique physiological activity characteristics relative to proteins.Bioactive ...Peptides are functional active fragments of proteins which can provide nutrients needed for human growth and development,and they also have unique physiological activity characteristics relative to proteins.Bioactive peptides contain a great deal of development potential.More specifically,food-derived bioactive peptides have the advantages of a wide variety of sources,unique structures,high efficiency and safety,so they have broad development prospects.This review provides an overview of the current advances regarding the preparation,functional characteristics,and structure–activity relationships of food-derived bioactive peptides.Moreover,the prospects for the future development and application of food-derived bioactive peptides are discussed.This review may provide a better understanding of foodderived bioactive peptides,and some constructive inspirations for further research and applications in the food industry.展开更多
The fiber mouthfeel of fish muscle is a highly sought-after goal for surimi gel products.The primary aim of research and development has been to quickly and accurately evaluate fiber degree for fish muscle.Therefore,b...The fiber mouthfeel of fish muscle is a highly sought-after goal for surimi gel products.The primary aim of research and development has been to quickly and accurately evaluate fiber degree for fish muscle.Therefore,based on the ResNet model,edge feature attentional mechanism was introduced to obtain the edge feature attention net (EFANet) to evaluate fiber degree for fish muscle.The EFANet was trained and tested on a dataset,which was made by collecting microscopic pictures of fish samples with different degrees of breakage.Compared with the three classic convolutional neural network (CNN) models,the EFANet emphasizes the learning of fiber texture information for fish muscle,reduces the effect of image color change,and significantly improves the detection accuracy.The average accuracy and specificity of the EFANet-50 on the testing dataset were 96.22% and 97.92%,respectively,which proved that it can effectively predict the fiber degree of fish muscle.展开更多
Antifreeze protein(AFP)can inhibit the growth of ice crystals to protect organisms from freezing damage,and demonstrates broad application prospects in food industry.Antifreeze peptides(AFPP)are specifi c peptides wit...Antifreeze protein(AFP)can inhibit the growth of ice crystals to protect organisms from freezing damage,and demonstrates broad application prospects in food industry.Antifreeze peptides(AFPP)are specifi c peptides with functional domains showing antifreeze activity in AFP.Bioinformatics-based molecular simulation technology can more accurately explain the properties and mechanisms of biological macromolecules.Therefore,the binding stability of antifreeze peptides and antifreeze proteins(AFP(P))to ice and the molecular-scale growth kinetics of ice were analyzed by molecular simulation,which can make up for the limitations of experimental technology.This review concludes the molecular simulation-based research in the inhibition’s study of AFP(P)on ice growth,including sequence prediction,structure construction,molecular docking and molecular dynamics(MD)studies of AFP(P)on ice applications in growth inhibition.Finally,the review prospects the future direction of designing new antifreeze biomimetic materials through molecular simulation and machine learning.The information presented in this paper will help enrich our understanding of AFPP.展开更多
基金supported by the National Natural Science Foundation of China(U1905202,31972017,and 31771922)the National Key R&D Program of China(2018YFD0901006)+2 种基金the Fujian Major Project of Provincial Science&Technology Hall,China(2020NZ010008)the Open Project of the Key Laboratory of Refrigeration and Conditioning Aquatic Products Processing,Ministry of Agriculture and Rural Affairs,China(KLRCAPP2021-03)the Quanzhou Science&Technology Project,China(2019C085R)。
文摘Peptides are functional active fragments of proteins which can provide nutrients needed for human growth and development,and they also have unique physiological activity characteristics relative to proteins.Bioactive peptides contain a great deal of development potential.More specifically,food-derived bioactive peptides have the advantages of a wide variety of sources,unique structures,high efficiency and safety,so they have broad development prospects.This review provides an overview of the current advances regarding the preparation,functional characteristics,and structure–activity relationships of food-derived bioactive peptides.Moreover,the prospects for the future development and application of food-derived bioactive peptides are discussed.This review may provide a better understanding of foodderived bioactive peptides,and some constructive inspirations for further research and applications in the food industry.
基金financially supported by the National“Thirteenth Five-Year”Plan for Science&Technology(2019YFD0902000)the Major Science and Technology Planed Program Projects in Xiamen City(3502Z20201032)+3 种基金the Fund of Fujian Provincial Key Laboratory of Refrigeration and Conditioning Aquatic Products Processing(FPKLRCAPP2021-02)the Jiangsu Agricultural Science and Technology Innovation Fund(CX(21)2040)the National First-class Discipline Program of Food Science and Technology(JUFSTR20180102)the Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province.
文摘The fiber mouthfeel of fish muscle is a highly sought-after goal for surimi gel products.The primary aim of research and development has been to quickly and accurately evaluate fiber degree for fish muscle.Therefore,based on the ResNet model,edge feature attentional mechanism was introduced to obtain the edge feature attention net (EFANet) to evaluate fiber degree for fish muscle.The EFANet was trained and tested on a dataset,which was made by collecting microscopic pictures of fish samples with different degrees of breakage.Compared with the three classic convolutional neural network (CNN) models,the EFANet emphasizes the learning of fiber texture information for fish muscle,reduces the effect of image color change,and significantly improves the detection accuracy.The average accuracy and specificity of the EFANet-50 on the testing dataset were 96.22% and 97.92%,respectively,which proved that it can effectively predict the fiber degree of fish muscle.
基金This work was supported by Natural Science Foundation of China(U1905202)Fujian Major Project of Provincial Science&Technology Hall of China(2020NZ010008)Xiamen Ocean and Fishery Development Special Fund Project(21CZP006HJ04).
文摘Antifreeze protein(AFP)can inhibit the growth of ice crystals to protect organisms from freezing damage,and demonstrates broad application prospects in food industry.Antifreeze peptides(AFPP)are specifi c peptides with functional domains showing antifreeze activity in AFP.Bioinformatics-based molecular simulation technology can more accurately explain the properties and mechanisms of biological macromolecules.Therefore,the binding stability of antifreeze peptides and antifreeze proteins(AFP(P))to ice and the molecular-scale growth kinetics of ice were analyzed by molecular simulation,which can make up for the limitations of experimental technology.This review concludes the molecular simulation-based research in the inhibition’s study of AFP(P)on ice growth,including sequence prediction,structure construction,molecular docking and molecular dynamics(MD)studies of AFP(P)on ice applications in growth inhibition.Finally,the review prospects the future direction of designing new antifreeze biomimetic materials through molecular simulation and machine learning.The information presented in this paper will help enrich our understanding of AFPP.
