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High-level production of protein glutaminase from Chryseobacterium proteolyticum and its application in enhancing the functional properties of dried soybean meal protein powder
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作者 Kai Zhang Mengyue Duan +1 位作者 Linjun Yao Chong Zhang 《Food Bioscience》 2025年第10期1216-1229,共14页
This study improved protein glutaminase(PG)yield from Chryseobacterium proteolyticum using a response surface methodology-artificial neural network-genetic algorithm(RSM-ANN-GA)strategy.Optimization of nitrogen source... This study improved protein glutaminase(PG)yield from Chryseobacterium proteolyticum using a response surface methodology-artificial neural network-genetic algorithm(RSM-ANN-GA)strategy.Optimization of nitrogen sources increased PG activity by 63.370%to 7.590 U/mL,the highest reported under shake-flask conditions.PG was applied to deamidate deacetylated soybean meal protein(DSMP),and spray drying was optimized to achieve a 29.710%powder yield.PG treatment significantly enhanced DSMP solubility,dispersibility,antioxidant capacity,and in vitro digestibility.At a deamidation degree(DD)of 55%,digestibility matched commercial soybean protein powder(CSPP),with improved umami and reduced bitterness/astringency.Color analysis showed increased brightness and lower total color difference with rising DD,while proximate and amino acid composition remained largely unchanged,preserving essential nutrients.Electronic nose and tongue profiling confirmed improved aroma and flavor through beneficial volatile compounds.These findings demonstrate that PG deamidation alleviates spray drying-induced protein aggregation while enhancing the nutritional,functional,sensory,and visual qualities of plant protein powders,offering a scalable,cost-effective approach for food industry applications. 展开更多
关键词 Protein-glutaminase artificial neural network-genetic algorithm Soybean meal protein powder
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