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Yang G, Zhang J, Ma X, Ma R, Shen J, Liu M, Yu D, Feng F, Huang C, Ma X, La Y, Guo X, Yan P, Liang C. Polymorphisms of CCSER1 Gene and Their Correlation with Milk Quality Traits in Gannan Yak ( Bos grunniens). Foods 2023; 12:4318. [PMID: 38231770 DOI: 10.3390/foods12234318] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 01/19/2024] Open
Abstract
Coiled-coil serine-rich protein 1 (CCSER 1) gene is a regulatory protein gene. This gene has been reported to be associated with various economic traits in large mammals in recent years. The aim of this study was to investigate the association between CCSER1 gene single nucleotide polymorphisms (SNPs) and Gannan yaks and to identify potential molecular marker loci for breeding milk quality in Gannan yaks. We genotyped 172 Gannan yaks using Illumina Yak cGPS 7K liquid microarrays and analyzed the correlation between the three SNPs loci of the CCSER1 gene and the milk qualities of Gannan yaks, including milk fat, protein and casein. It was found that mutations at the g.183,843A>G, g.222,717C>G and g.388,723G>T loci all affected the fat, protein, casein and lactose traits of Gannan yak milk to varying extents, and that the milk quality of individuals with mutant phenotypes was significantly improved. Among them, the milk fat content of AG heterozygous genotype population at g.183,843A>G locus was significantly higher than that of AA and GG genotype populations (p < 0.05); the casein and protein content of mutant GG and CG genotype populations at g.222,717C>G locus was significantly higher than that of wild-type CC genotype population (p < 0.05); and the g.388,723G>T locus of the casein and protein contents of the mutant TT genotype population were significantly higher (p < 0.05) than those of the wild-type GG genotype population. These results provide potential molecular marker sites for Gannan yak breeding.
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Affiliation(s)
- Guowu Yang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
- College of Life Sciences and Engineering, Northwest Minzu University, Lanzhou 730106, China
| | - Juanxiang Zhang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoyong Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Rong Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Jinwei Shen
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Modian Liu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Daoning Yu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
- College of Life Sciences and Engineering, Northwest Minzu University, Lanzhou 730106, China
| | - Fen Feng
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Chun Huang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xiaoming Ma
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Yongfu La
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Xian Guo
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Ping Yan
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
| | - Chunnian Liang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou 730050, China
- Key Laboratory of Yak Breeding Engineering of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China
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Zhu H, Si X, Wang Y, Zhu P, Pang X, Wang X, Fauconnier ML, Ju N, Zhang S, Lv J. Fatty acid, triglyceride, and kinetic properties of milk fat fractions made by the combination of dry fractionation and short-path molecular distillation. J Dairy Sci 2023; 106:6655-6670. [PMID: 37210356 DOI: 10.3168/jds.2022-22970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 04/14/2023] [Indexed: 05/22/2023]
Abstract
In this study, we aimed to detect the physicochemical properties of distilled products (residue and distillate) obtained from anhydrous milk fat (AMF) and its dry fractionation products (liquid and solid fractions at 25°C [25 L and 25 S]). The results showed that the saturated fatty acids and low- and medium molecular-weight triglycerides were easily accumulated in the distillate, and the percentage of unsaturated fatty acid and high molecular-weight triglycerides in the residue were higher, and these components in 25 S and 25 L were influenced more significantly than those in the AMF. In addition, the distillate had larger melting ranges in comparison with the distilled substrate, while the melting ranges of residue was smaller. The triglycerides were presented as the mixture crystal forms (α, β', and β crystal) in 25 S, AMF, and their distilling products, and it was transformed gradually to a single form as the increasing of distilling temperature. Moreover, the accumulated pattern of triglycerides was double chain length in 25 S, AMF, and their distilling products. These results provide a new approach to obtain the milk fat fractions with different properties, and the findings of this study enrich the theoretical basis of milk fat separation in practical production.
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Affiliation(s)
- Huiquan Zhu
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China; Laboratory of Chemistry of Natural Molecules, Gembloux Agro-bio Tech, University of Liege, Gembloux 5030, Belgium
| | - Xin Si
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China; School of Food & Wine, Ningxia University, Yinchuan, Ningxia 750000, China
| | - Yunna Wang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Panpan Zhu
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China; School of Food & Wine, Ningxia University, Yinchuan, Ningxia 750000, China
| | - Xiaoyang Pang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Xiaodan Wang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Marie-Laure Fauconnier
- Laboratory of Chemistry of Natural Molecules, Gembloux Agro-bio Tech, University of Liege, Gembloux 5030, Belgium
| | - Ning Ju
- School of Food & Wine, Ningxia University, Yinchuan, Ningxia 750000, China.
| | - Shuwen Zhang
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
| | - Jiaping Lv
- Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China
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Sibono L, Grosso M, Tronci S, Errico M, Addis M, Vacca M, Manis C, Caboni P. Investigation of Seasonal Variation in Fatty Acid and Mineral Concentrations of Pecorino Romano PDO Cheese: Imputation of Missing Values for Enhanced Classification and Metabolic Profile Reconstruction. Metabolites 2023; 13:877. [PMID: 37512584 PMCID: PMC10386313 DOI: 10.3390/metabo13070877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/19/2023] [Accepted: 07/21/2023] [Indexed: 07/30/2023] Open
Abstract
Seasonal variation in fatty acids and minerals concentrations was investigated through the analysis of Pecorino Romano cheese samples collected in January, April, and June. A fraction of samples contained missing values in their fatty acid profiles. Probabilistic principal component analysis, coupled with Linear Discriminant Analysis, was employed to classify cheese samples on a production season basis while accounting for missing data and quantifying the missing fatty acid concentrations for the samples in which they were absent. The levels of rumenic acid, vaccenic acid, and omega-3 compounds were positively correlated with the spring season, while the length of the saturated fatty acids increased throughout the production seasons. Concerning the classification performances, the optimal number of principal components (i.e., 5) achieved an accuracy in cross-validation equal to 98%. Then, when the model was tasked with imputing the lacking fatty acid concentration values, the optimal number of principal components resulted in an R2 value in cross-validation of 99.53%.
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Affiliation(s)
- Leonardo Sibono
- Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy
| | - Massimiliano Grosso
- Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy
| | - Stefania Tronci
- Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Via Marengo 2, 09123 Cagliari, Italy
| | - Massimiliano Errico
- Department of Green Technology, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark
| | - Margherita Addis
- Agris Sardegna, Servizio Ricerca Prodotti di Origine Animale, Agris Sardegna, Loc., Bonassai, 07040 Sassari, Italy
| | - Monica Vacca
- Servizio Ricerca Studi Ambientali, Difesa delle Colture e Qualità delle Produzioni, Viale Trieste, 09123 Cagliari, Italy
| | - Cristina Manis
- Dipartimento di Scienze della vita e Ambiente, Cittadella Universitaria di Monserrato Blocco A, 09012 Monserrato, Italy
| | - Pierluigi Caboni
- Dipartimento di Scienze della vita e Ambiente, Cittadella Universitaria di Monserrato Blocco A, 09012 Monserrato, Italy
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“Omic” Approaches to Bacteria and Antibiotic Resistance Identification. Int J Mol Sci 2022; 23:ijms23179601. [PMID: 36077000 PMCID: PMC9455953 DOI: 10.3390/ijms23179601] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/19/2022] [Accepted: 08/21/2022] [Indexed: 11/28/2022] Open
Abstract
The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.
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Cui Y, Ge L, Lu W, Wang S, Li Y, Wang H, Huang M, Xie H, Liao J, Tao Y, Luo P, Ding YY, Shen Q. Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:7786-7795. [PMID: 35696488 DOI: 10.1021/acs.jafc.2c01447] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The price of mammalian milk from different animal species varies greatly due to differences in their yield and nutritional value. Therefore, the authenticity of dairy products has become a hotspot issue in the market due to the replacement or partial admixture of high-cost milk with its low-cost analog. Herein, four common commercial varieties of milk, including goat milk, buffalo milk, Holstein cow milk, and Jersey cow milk, were successfully profiled and differentiated from each other by rapid evaporative ionization mass spectrometry (REIMS) combined with chemometric analysis. This method was developed as a real-time lipid fingerprinting technique. Moreover, the established chemometric algorithms based on multivariate statistical methods mainly involved principal component analysis, orthogonal partial least squares-discriminant analysis, and linear discriminant analysis as the screening and verifying tools to provide insights into the distinctive molecules constituting the four varieties of milk. The ions with m/z 229.1800, 243.1976, 257.2112, 285.2443, 299.2596, 313.2746, 341.3057, 355.2863, 383.3174, 411.3488, 439.3822, 551.5051, 577.5200, 628.5547, 656.5884, 661.5455, 682.6015, and 684.6146 were selected as potential classified markers. The results of the present work suggest that the proposed method could serve as a reference for recognizing dairy fraudulence related to animal species and expand the application field of REIMS technology.
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Affiliation(s)
- Yiwei Cui
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Lijun Ge
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Weibo Lu
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Shitong Wang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Yunyan Li
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Haifeng Wang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Min Huang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Hujun Xie
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Jie Liao
- Zhejiang Huacai Testing Technology Co., Ltd., Shaoxing, Zhejiang 311800, China
| | - Ye Tao
- Hangzhou Linping District Maternal & Child Health Care Hospital, Hangzhou, Zhejiang 311113, China
| | - Pei Luo
- State Key Laboratories for Quality Research in Chinese Medicines, Faculty of Pharmacy, Macau University of Science and Technology, Macau 999078, China
| | - Yin-Yi Ding
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Qing Shen
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
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Sun X, Shi J, Li R, Chen X, Zhang S, Xu YJ, Liu Y. SWATH-MS2&1: Development and Validation of a Pseudotargeted Lipidomics Method for the Analysis of Glycerol Esters in Milk. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:3331-3343. [PMID: 35230101 DOI: 10.1021/acs.jafc.1c06446] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Glycerol ester (GE) is a kind of important lipid in milk, which varies greatly depending on many factors. In this study, a novel pseudotargeted lipidomics strategy, named SWATH-MS2&1, was developed for the detection of GEs in milk and the Folch method was selected for the sample preparation. The developed method exhibited a competitive alternative to the acknowledged pseudotargeted strategy, including wider coverage (12 more GEs detected), higher repeatability (12 more GEs, whose coefficient of variation < 0.3), better linearity (5 more GEs, whose R2 > 0.8), and similar sensitivity (only 2 GEs less than P-MRM after dilution). SWATH-MS2&1 was applied in the investigation of GEs from different milk samples. The orthogonal partial least-squares difference analysis of 219 GEs identified from SWATH-MS2&1 showed satisfying differentiation of different milk samples, and 76 GEs were screened out as potential markers. Our findings demonstrated that SWATH-MS2&1 could offer an accurate method to measure a wide spectrum of GEs in milk.
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Affiliation(s)
- Xian Sun
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Jiachen Shi
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Ruizhi Li
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Xiaoying Chen
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Shuang Zhang
- The Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi 214122, Jiangsu, People's Republic of China
| | - Yong-Jiang Xu
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
| | - Yuanfa Liu
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, National Engineering Reacher Center for Functional Food, National Engineering Laboratory for Cereal Fermentation Technology, Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province, Jiangnan University, No. 1800, Lihu Road, Wuxi 214122, Jiangsu, People's Republic of China
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