Minwei Xu

North Dakota State University

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i-10 index

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Bingcan Chen

North Dakota State University

Jiajia Rao

North Dakota State University

Zhao Jin

North Dakota State University

Jae‐Bom Ohm

Edward T. Schafer Agricultural Research Center

Gabriel Swanson

University of Toronto

Zhongjiang Wang

Northeast Agricultural University

Muhammad Usman

Lanzhou University

Tianfu Cheng

Northeast Agricultural University

Zengwang Guo

Northeast Agricultural University

Qiong Chen

Central South University

Cooperative Institutions

North Dakota State University

Dakota State University

Jiangnan University

Northeast Agricultural University

Qilu University of Technology

Shandong Academy of Sciences

State Key Laboratory of Food Science and Technology

Chinese Academy of Sciences

Wells Fargo (United States)

Henan University of Technology

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Physicochemical and structural properties of proteins extracted from dehulled industrial hempseeds: Role of defatting process and precipitation pH

Food Hydrocolloids (2020)

Peiyi Shen Zili Gao Minwei Xu Jiajia Rao Bingcan Chen

Defatting

10.1016/j.foodhyd.2020.106065

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Citations (56)

Analytical advances in the determinations of dietary sphingolipids in milk, dairy products, and infant formula and impacts on human health

International Journal of Food Science & Technology (2024)

Emad Karrar Muhammad Usman Isam A. Mohamed Ahmed Charles S. Brennan Minwei Xu

Summary Sphingolipids (SL) are bioactive compounds in milk, dairy products, and infant formula. SL has been found to have different health benefits, such as anti‐inflammatory, antimicrobial, anticancer, and cholesterol‐lowering characteristics. SL requires careful extraction, separation, and identification due to their unique characteristics. This review discusses the importance of extracting, purifying, and analysing SL from milk and dairy products. OE (Organic extraction), SPE (solid‐phase extraction), and SFE (supercritical CO 2 ) techniques, as well as dispersive OE and SPE, are the most common methods. In addition, this review discussed various analytical techniques that can be used to determine and quantify SL classes, including TLC (thin‐layer chromatography), HPLC (high‐performance liquid chromatography), nuclear magnetic resonance spectroscopy, and mass spectrometry. These techniques are crucial for understanding the amounts of SL dairy products and infant formula. The paper also focuses on the different types of SL present in milk, dairy products, and infant formula and their concentrations. SL has the potential to be applied to the development of functional foods, and further research in this area is needed. This article sheds light on the extract, purification, and analysis of SL dairy products and infant formula, as well as their potential health benefits.

Sphingolipid

10.1111/ijfs.17492

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Potential nutritional and functional matters in yeast culture prepared by soybean meal fermentation

Journal of the Science of Food and Agriculture (2024)

Yazhuo Cao Minwei Xu Qiong Chen Dianhui Wu Jian Lu

Yeast culture (YC) is a product fermented on a specific medium, which is a type of postbiotic of anaerobic solid-state fermentation. Although YC has positive effects on the animal growth and health, it contains a variety of beneficial metabolites as dark matter, which have not been quantified. In the present study, liquid chromatography-tandem mass spectrometry is employed to identify the unknown metabolites. Following their identification, the important chemicals are quantified using HPLC-diode array detection methods.

10.1002/jsfa.13713

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HS-SPME-GC-MS/olfactometry combined with chemometrics to assess the impact of germination on flavor attributes of chickpea, lentil, and yellow pea flours

Food Chemistry (2018)

Minwei Xu Zhao Jin Lan Yang Jiajia Rao Bingcan Chen

10.1016/j.foodchem.2018.12.048

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Citations (149)

Sensory Profile of Pulse-Based High Moisture Meat Analogue: A Study on the Complex Effect of Germination and Extrusion Processing

Muhammad Usman Gabriel Swanson bingcan Chen Minwei Xu

In this research, yellow pea and lentil protein-rich flours from germinated/ungerminated pulse seeds were separately processed into high-moisture meat analogs (HMMAs) with twin screw extrusion cooking. Overall, 30 volatile compounds were identified by HS–SPME–GC–MS/O. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) exhibited that the extrusion markedly reduced common beany related flavors, such as hexanal, 1-hexanol, 2-nonenel, (E)-2-octen-1-ol, (E,E)-2,4-octadienal, and (E,E)-2,4-nonadienal in HMMAs. The synergistic effect of germination and extrusion process was observed to decrease some beany flavors such as 1-octen-3-ol and 2,4-decadienal and to lower the beany taste. Pea-based HMMAs are considered for poultry meat with lighter color and softer chewiness score, whereas lentil-based HMMAs can be considered for livestock meat with dark-brown color and harder chewiness score. Those findings offer novel insights into the regulation of beany flavors, odor notes, color, and taste to improve the sensory quality of HMMAs.

Meat packing industry

10.2139/ssrn.4404717

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Solid dispersion-based spray-drying improves solubility and mitigates beany flavour of pea protein isolate

Food Chemistry (2018)

Lan Yang Minwei Xu Jae‐Bom Ohm Bingcan Chen Jiajia Rao

Flavour

Pea protein

10.1016/j.foodchem.2018.11.074

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Citations (133)

Effect of xanthan gum (XG) and carrageenan (CG) ratio on casein (CA)-XG-CG ternary complex: Used to improve the stability of liquid diabetes formula food for special medical purposes

International Journal of Biological Macromolecules (2024)

Tianfu Cheng Yachao Tian Caihua Liu Yang Hong Zhongjiang Wang

Thermal Stability

10.1016/j.ijbiomac.2024.131770

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Citations (2)

Pulse seed germination improves antioxidative activity of phenolic compounds in stripped soybean oil-in-water emulsions

Food Chemistry (2018)

Minwei Xu Zhao Jin Allen Peckrul Bingcan Chen

Soybean oil

10.1016/j.foodchem.2018.01.049

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Citations (27)

Predicting Gypsum Tofu Quality from Soybean Seeds Using Hyperspectral Imaging and Machine Learning

Amanda Manoj Malik Billy G. Ram Dharanidharan Arumugam Zhao Jin Xin Sun

Assessing the quality of soybean seeds for tofu production traditionally requires the actual creation of tofu, a process that demands considerable time and effort. This study addresses this issue by employing machine learning to predict tofu quality from Hyperspectral Imaging (HSI) images of soybean seeds. Two hundred varieties of soybean seeds scanned with HSI have been classified into four categories based on their qualities of tofu products. Upon comparison, XGBoost was employed to pinpoint ten critical HSI wavelengths that show a potential correlation with the protein, carbohydrate, and oil contents in the soybean seeds. Subsequently, a Convolutional Neural Network model was formulated to forecast tofu quality, basing its predictions on HSI data of soybean varieties. Remarkably, the model successfully segregated the soybeans into four unique classes, demonstrating a predictive accuracy that varied between 96% and 99%. This research amalgamates cutting-edge technologies to revolutionize the conventional assessment of soybean seeds.

10.2139/ssrn.4503406

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The influence of pH and enzyme cross-linking on protein delivery properties of WPI-beet pectin complexes

Food Research International (2017)

Qiang Wang Yanrong Ren Yangping Ding Minwei Xu Bingcan Chen

Pectin

Whey protein isolate

10.1016/j.foodres.2017.11.076

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Citations (18)