Volume 16, Issue 92 (2019)                   FSCT 2019, 16(92): 165-175 | Back to browse issues page

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1- Sari University of Agricultural Sciences and Natural Resources , z.bagheri808@gmail.com
2- Sari University of Agricultural Sciences and Natural Resources
3- Noushirovani Industrial University of Babol
Abstract:   (1782 Views)
Cluster analysis (CA) is a multivariate tool used to organize a set of multivariate data (observations, objects) into groups called clusters. The cluster analysis method was carried out on characteristics of Ricotta cheese powder, with the effect of milk/whay ratio (formulation) and foam mat drying temperature. In this study, 4 types of formulations and 6 drying temperature were used to study the density, hygroscopic and color factors to find the formulation and optimal temperature that created the proper physical properties. The results of analysis of variance showed high temperature due to higher vapor velocity, decreased density and increased hygroscopicity (p<0.05). Also, with increasing temperature, the index "L" decreased and the indices "a" and "b" decreased. According to the results of cluster analysis, cluster 2 was selected as the best cluster for the least disparity between treatments and also due to the lowest Within-group variance. In this cluster, cheeses with a high percentage of whey in the formulation combination and low temperatures are found to foam mat drying. According to the results, the Lightness (L) of the powders of this cluster is higher, and at lower temperatures the density and hygroscopy are lower. Based on the results in general, the use of cluster analysis to select formulations for foam mat drying of ricotta cheese is a suitable method.
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Article Type: Original Research | Subject: Statistics, modeling and response levels in the food industry
Received: 2019/06/17 | Accepted: 2019/09/7 | Published: 2019/09/1

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