| Literature DB >> 33897019 |
Sonal Patil1,2, Sachin K Sonawane2, S S Arya1.
Abstract
The objective of the study was to screen amongst various gluten free flours to prepare Indian unleavened flatbread using principal component analysis (PCA) and hierarchical cluster analysis (HCA) as a mathematical tool. Gluten free flours studied in this work were, rice, sorghum, moong, amaranth, sama, ragi, water chestnut, buckwheat, soy, tamatind kernel, chickpea, black gram and unripe banana flour. The characteristics of sorghum: rice flatbread was analyzed such as dough making ability, subjective rollability, puffing and acceptability with respect to wheat. Interrelationship between the parameters analyzed and the different gluten free flours were investigated by using PCA and HCA. PCA revealed that the first two components represented 92.56% of the total variability in flatbread making characteristics. HCA classified samples into 6 clusters on the basis of measured flatbread making characteristics. From the results, moong, water chestnut and unripe banana flour in addition to mixture sorghum: rice (30:70) flour were chosen as ingredients for the preparation of Indian unleavened flatbread. © Association of Food Scientists & Technologists (India) 2020.Entities:
Keywords: Chemometrics; Flatbread; Gluten free; HCA; PCA
Year: 2020 PMID: 33897019 PMCID: PMC8021619 DOI: 10.1007/s13197-020-04694-x
Source DB: PubMed Journal: J Food Sci Technol ISSN: 0022-1155 Impact factor: 2.701