Follow
International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39 For more details click here
National Academy of Agricultural Sciences (NAAS) : NAAS Score: *5.38 (2020) [Effective from January 1, 2020]For more details click here

Login as a Reviewer

Indexed in



National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

See Guidelines to Authors
Current Issues

Original Research Articles

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2017.6(2): 25-295
DOI: http://dx.doi.org/10.20546/ijcmas.2017.602.034


Characterization of Reducing Sugars of Red Beet (Beta vulgaris L.) during Cold Storage through Statistical Modeling
Venkata Satish Kuchi1*, D. Ramesh2, S. Chakrabarty1 and R.S. Dhua1
1Department of Postharvest Technology of Horticultural Crops, Faculty of Horticulture,
Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal - 741252, India
2Department of Agricultural Statistics, Faculty of Agriculture, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal - 741252, India
*Corresponding author
Abstract:

Formation of reducing sugars during low temperature storage of red beet is detrimental for processing, consumption as vegetable and easily deteriorated when exposed to high temperatures. Most of the analytical methods are time consuming, cost effective and laborious. So, assessing internal red beet quality through statistical methods is alternative as mathematical modeling does not take error in to consideration. These equations contain few parameters and the storability of the product could be predicted before keeping it for storage based on the dependent parameters. An attempt was made by employing Multiple Linear Regression and paired T-test to predict the formation of reducing sugars on dependent variables like moisture content and total soluble solids.  Further, the results were confirmed by Shapiro-Wilk’s and Run tests. Regression analysis explained that reducing sugars were significantly influenced by selected variables; about 89.5 percent (R2 = 0.895). There was non-significant difference between actual (lab) and predicted (model) reducing sugars as per paired t-test.


Keywords: Moisture content, Multiple Linear Regression, Reducing sugars, Run test, Shapiro-Wilk’s test.
Download this article as Download

How to cite this article:

Venkata Satish Kuchi, D. Ramesh, S. Chakrabarty and Dhua, R.S. 2017. Characterization of Reducing Sugars of Red Beet (Beta vulgaris L.) during Cold Storage through Statistical Modeling.Int.J.Curr.Microbiol.App.Sci. 6(2): 25-295. doi: http://dx.doi.org/10.20546/ijcmas.2017.602.034