Nutrient Composition and Predicted Glycemic Index of Rice Varieties from Nigeria
Amaka M. Odenigbo
Department of Bioresource Engineering, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, H9X 3V9, Canada and Department of Human Nutrition and Dietetics, Michael Okpara University of Agriculture, Umudike, Nigeria
Nahemiah Danbaba
National Cereals Research Institute (NCRI), Badeggi, Nigeria
Michael Ngadi *
Department of Bioresource Engineering, McGill University, 21111 Lakeshore Road, Ste-Anne-de-Bellevue, Quebec, H9X 3V9, Canada.
*Author to whom correspondence should be addressed.
Abstract
Aims: This study aimed to evaluate the nutritional composition, rate of starch digestibility and predicted glycemic indices of selected nine commonly grown rice varieties in Nigeria.
Place and Duration of Study: Samples were collected from Nigeria, analyzed at McGill University, Canada between 2012 and 2013.
Methodology: The samples involved five improved varieties and four local varieties of milled, non-parboiled rice. Predicted glycemic index (pGI) was estimated by in vitro enzymatic starch digestion. Proximate nutrients and mineral compositions were determined by standardized methods.
Results: The proximate, mineral composition and starch digestibility varied among samples. The predicted glycemic indices (pGI) were within the range of 66.09 to 73.20 %. Jamila had the lowest pGI and starch hydrolysis rate (66.09 % and 0.05 min-1,respectively). FARO 52 exhibited significant lowest phosphorus, potassium and magnesium (P<0.05). Yardass had significantly highest values for protein (11.59 %) and fat (1.47 %).
Conclusion: The local rice varieties generally, portrayed lower rate of starch digestibility with higher nutritional value compared to improved rice varieties.
Keywords: Non-parboiled rice, nutritional composition, in vitro starch digestibility, glycemic index