Angky Wahyu Putranto, Anugerah Dany Priyanto, Dimas Firmanda Al Riza, Ferina Tiara Safitri, Nurul Istiqomah Khoirunnisa, Arrahmadiana Estuwilujeng, Candika Pambayun
{"title":"Optimization of pulsed electric field processing time and hydrolyzed bovine collagen concentration in pasteurized milk","authors":"Angky Wahyu Putranto, Anugerah Dany Priyanto, Dimas Firmanda Al Riza, Ferina Tiara Safitri, Nurul Istiqomah Khoirunnisa, Arrahmadiana Estuwilujeng, Candika Pambayun","doi":"10.21776/ub.afssaae.2022.005.01.3","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":325722,"journal":{"name":"Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21776/ub.afssaae.2022.005.01.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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.