PREPARATION AND EVALUATION OF MUSKMELON WINE: EFFECT OF DILUTION OF PULP, DAHP, PECTINESTERASE ENZYME AND CITRIC ACID ON PHYSICO-CHEMICAL AND SENSORY QUALITY CHARACTERISTICS


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Article type :

Original article

Author :

Vinod K. Joshi

Volume :

1

Issue :

2

Abstract :

An attempt has been made to study the effect of dilution, addition of diammonium hydrogen phosphate (DAHP), pectinesterase enzyme and citric acid on the fermentability, physico-chemical and sensory quality characteristics of muskmelon wine. Initial physico-chemical characteristics of the muskmelon pulp showed that it is an average source of sugars and a good source of phenols, which make it more suitable as fermentation media. Out of the two dilutions, fermentation of 1:1 dilution of muskmelon pulp gave good fermentability, physico-chemical and sensory characteristics except fermentation efficiency and amino acid content. Fermentability, physico-chemical and sensory characteristics of muskmelon wine was found to be affected significantly by the addition of DAHP in the must. The addition of pectinesterase enzyme significantly effected fermentability, physico-chemical and sensory characteristics of the muskmelon wine except pH, titratable acidity and amino acid content. Addition of citric acid in the must did not show any drastic impact on the quality of muskmelon wine. Clustering of the data showed that muskmelon wine prepared using 1:1 dilution of pulp with the addition of DAHP and pectinesterase enzyme fell in one cluster, whereas, the rest of the wines fell in the other cluster. Physico-chemical characteristics and variables of muskmelon wine were reduced to two principal components using Principal Component Analysis (PCA) that accounted for 89.02% and 98.03% variation respectively. It is concluded that 1:1 dilution of muskmelon pulp, with the addition of DAHP, pectinesterase enzyme and citric acid can be successfully used for the preparation of good quality muskmelon wine.

Keyword :

Muskmelon, dilution, DAHP, pectinesterase enzyme, citric acid, wine, cluster analysis, PCA
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