Application Of Predictive Modeling To Assess The Shelf Life Of Functional Enriched Sugarcane Juice

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dc.contributor.authorRajalakshmi, R.
dc.contributor.authorSujatha, G.
dc.contributor.authorPandian, A.Serma Saravana
dc.contributor.authorRita, N
dc.contributor.authorPerasiriyan, V.
dc.contributor.authorPandian, N.Karpoora Sundara
dc.contributor.authorTANUVAS
dc.date.accessioned2022-03-23T09:46:37Z
dc.date.available2022-03-23T09:46:37Z
dc.date.issued2022
dc.descriptionTNV_IJAS_14(1)_2022_11049-11051en_US
dc.description.abstractConsumers demand for fresh and safe food with favourable sensory and nutritional properties with an adequate shelf life. Currently, ready to drink functional enriched sugarcane juice with extended shelf life is not available in markets. Functional enriched sugarcane juice blended with amla and lemon juice was developed with extended shelf life processed without/minimal heat treatment by utilizing novel food processing technologies viz., Pulsed Electric Field (PEF), Ultraviolet C (UV-C) treatment and Ohmic Heating (OH). Response Surface Methodology (RSM) was used to determine the combinations of experiment. The optimum levels of sugarcane juice, amla juice and lemon juice extracts were found to be 91.998 mL, 4.720 mL, 3.282 mL respectively. The standardized juice was processed using different novel food processing technologies. Multiple linear regression analysis was conducted to model the relationship between the dependent variable towards predictor variables viz., pH, total soluble solids (TSS), vitamin C, antioxidant activity and total plate count (TPC). From the analysis of PEF treated juice, the predicted data showed that the variables pH, Vitamin C and TPC were found to be significantly associated at 1 per cent level (p0.05) difference with the age of the product. It was observed that the variables pH, VC AA and TPC were found to be significantly associated at 1 per cent level (p0.05) difference with the age of the product. Hence, the regression equation obtained can be selected to be the mathematical model for prediction of age of the juice based on independent variables.en_US
dc.identifier.urihttps://krishikosh.egranth.ac.in/handle/1/5810183740
dc.keywordsVeterinary Science, Food Business Management, Sugarcane juice, Response surface methodology, Novel food processing technologies, Predictive model, Shelf lifeen_US
dc.language.isoEnglishen_US
dc.pages11049-11051en_US
dc.relation.ispartofseries;1
dc.subjectVeterinary Scienceen_US
dc.subjectFood Managementen_US
dc.titleApplication Of Predictive Modeling To Assess The Shelf Life Of Functional Enriched Sugarcane Juiceen_US
dc.typeArticleen_US
dc.volume14en_US
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