Literature DB >> 34207867

Improving the Functionality of Proso Millet Protein and Its Potential as a Functional Food Ingredient by Applying Nitrogen Fertiliser.

Honglu Wang1, Dongmei Li1, Chenxi Wan1, Yan Luo1, Qinghua Yang1, Xiaoli Gao1, Baili Feng1,2.   

Abstract

Nitrogen is required for n>an class="Species">proso millet growth and has a critical influence on yield and quality. However, the effect of nitrogen fertilisation on proso millet protein properties remains unclear. This study aimed to investigate how nitrogen fertiliser treatment (180 kg/hm2) affects the structural and functional properties of proso millet protein. In comparison with the control group (N0), nitrogen fertiliser treatment loosened the dense structure of the protein and presented a larger particle size. Nitrogen treatment did not change the main subunit composition, and β-sheet and α-helix were the main secondary structures of proso millet protein based on Fourier transform infrared spectroscopy. In addition, nitrogen fertiliser treatment improved the content of hydrophobic amino acids and β-sheet proportion from proso millet protein, and high water/oil absorption capacity and thermal stability was observed, but the solubility, emulsion stability and foaming properties from proso millet protein decreased. Proso millet proteins exhibited high amino acid content and good functional properties, including solubility, foaming capacity and emulsifying properties, especially the w139 variety. Results show that proso millet protein has great potential for food applications. The above results provide useful information for the food industry to determine emerging gluten-free protein resources.

Entities:  

Keywords:  emulsion; foam; proso millet; protein; solubility

Year:  2021        PMID: 34207867     DOI: 10.3390/foods10061332

Source DB:  PubMed          Journal:  Foods        ISSN: 2304-8158


  2 in total

1.  Integrated Starches and Physicochemical Characterization of Sorghum Cultivars for an Efficient and Sustainable Intercropping Model.

Authors:  Maw Ni Soe Htet; Honglu Wang; Lixin Tian; Vivek Yadav; Hamz Ali Samoon; Baili Feng
Journal:  Plants (Basel)       Date:  2022-06-15

2.  Modeling of nitrogen solubility in normal alkanes using machine learning methods compared with cubic and PC-SAFT equations of state.

Authors:  Seyed Ali Madani; Mohammad-Reza Mohammadi; Saeid Atashrouz; Ali Abedi; Abdolhossein Hemmati-Sarapardeh; Ahmad Mohaddespour
Journal:  Sci Rep       Date:  2021-12-22       Impact factor: 4.379

  2 in total

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