E3S Web Conf.
Volume 189, 20202020 International Conference on Agricultural Science and Technology and Food Engineering (ASTFE 2020)
|Number of page(s)||5|
|Section||Food Biochemistry and Food Processing|
|Published online||15 September 2020|
Variability in Nutritional Composition, Kernel Morphology and Cooking Quality of Selected Rice in Xingan Meng from Northeast China
Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, 100081 Beijing China
2 Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, 100081 Beijing China
* Corresponding author: email@example.com
Paddy rice cultivation expanded in Northeast China, and Xingan Meng of Inner Mongolia is an emerging area of rice production area. The goals of this study: i) to investigate varietal differences in levels of nutritional quality, kernel morphology and cooking quality and ii) to identify clusters of rice samples from Xingan Meng, northeast part of China. Research was conducted in Xingan Meng, China during the 2019 rice-growing season. The nutritional quality (energy, protein, carbohydrate, lipid, amylose, ash, Ca, Na, Fe, Zn, Mn), cooking quality (alkali spreading value, gel consistency) and kernel morphology (length, width, length width ratio, chalky rice percentage, chalky rice degree) were analysed. Significant difference were found across all traits. The largest variation was found for Mn, followed by Ca, Fe and Zn content. Four principal components were found that accounted for 95.14% of overall variability. Cluster analysis sorted the rice sample into four clusters based on nutritional quality, kernel morphology, and cooking quality. The findings of this study can support to demonstrate the quality of rice from Xingan Meng, northeast part of China.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.