巴氏奶中脉冲电场处理时间及水解牛胶原蛋白浓度的优化

Angky Wahyu Putranto, Anugerah Dany Priyanto, Dimas Firmanda Al Riza, Ferina Tiara Safitri, Nurul Istiqomah Khoirunnisa, Arrahmadiana Estuwilujeng, Candika Pambayun
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引用次数: 1

摘要

牛奶是一种极易变质的食物,因为它的营养成分有利于微生物的生长。不当的牛奶处理方法会导致牛奶营养减少和微生物污染。胶原蛋白饮料目前是一种日益增长的商业产品。因此,本研究旨在确定水解牛胶原浓度和脉冲电场(PEF)时间对富含水解牛胶原的牛奶的物理、微生物和感官品质的影响,并确定最佳处理方法。本实验设计采用响应面法(RSM)的中心复合设计(CCD)来探索胶原浓度与PEF处理时间之间的最佳响应关系。本实验提出了优化TPC和粘度的CCD实验,共获得13个实验设计。RSM-CCD给出的模型结果为二次模型。结果表明,以水解牛胶原蛋白浓度为2.837%、PEF处理时间为116.369 s为最佳设计,其理想值为0.809。三次重复的验证结果显示,平均TPC为3.38 log CFU/mL,粘度为4.56 mpa。在此条件下,两个响应的错误率值均小于5%,表明模型优化是可以接受的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of pulsed electric field processing time and hydrolyzed bovine collagen concentration in pasteurized milk
Milk is a highly perishable food due to its nutritional composition for microbial growth. Improper milk handling practices cause nutritional reduction and microbial contamination in milk. Collagen drinks are currently a growing commercial product. Therefore, this study aimed to determine the effect of hydrolyzed bovine collagen concentration and pulsed electric field (PEF) time on the physical, microbiological, and organoleptic qualities of milk enriched with hydrolyzed bovine collagen, as well as to determine the best treatment. Central composite design (CCD) for Response Surface Methodology (RSM) was used in this experimental design to explore optimal response based on the relationship between collagen concentration and PEF processing time. This CCD experiment was proposed to optimize TPC and viscosity and obtained a total of 13 experimental designs. The model results suggested by RSM-CCD are quadratic models. The result showed the optimization of the supplemented milk using a concentration of 2.837% hydrolyzed bovine collagen and PEF processing time of 116.369 seconds were the optimal designs with the desirability value of 0.809. Validation results using three repetitions produced an average TPC of 3.38 log CFU/mL and viscosity results of 4.56 mPas. Under these conditions, the error rate value of both responses is less than 5%, indicating that the model optimization can be accepted.
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