John Racheal, Bollinedi Haritha, Jeyaseelan Christine, Padhi Siddhant Ranjan, Sajwan Neha, Nath Dhrubjyoti, Singh Rakesh, Ahlawat Sudhir Pal, Bhardwaj Rakesh, Rana Jai Chand
Amity Institute of Applied Sciences, Amity University, Noida, India.
ICAR-IARI, Pusa, New Delhi, India.
Heliyon. 2023 Jun 26;9(7):e17524. doi: 10.1016/j.heliyon.2023.e17524. eCollection 2023 Jul.
The Indian subcontinent is the primary center of origin of rice where huge diversity is found in the Indian rice gene pool, including landraces. North Eastern States of India are home to thousands of rice landraces which are highly diverse and good sources of nutritional traits, but most of them remain nutritionally uncharacterized. Hence, nutritional profiling of 395 Assam landraces was done for total starch, amylose content (AC), total dietary fiber (TDF), total protein content (TPC), oil, phenol, and total phytic acid (TPA) using official AOAC and standard methods, where the mean content for the estimated traits were found to be 75.2 g/100g, 22.2 g/100g, 4.67 g/100g, 9.8 g/100g, 5.26%, 0.40 GAE g/100g, and 0.34 g/100g for respectively. The glycaemic index (GI) was estimated in 24 selected accessions, out of which 17 accessions were found to have low GI (<55). Among different traits, significant correlations were found that can facilitate the direct and indirect selection such as estimated glycemic index (EGI) and amylose content (-0.803). Multivariate analyses, including principal component analysis (PCA) and hierarchical clustering analysis (HCA), revealed the similarities/differences in the nutritional attributes. Four principal components (PC) i.e., PC1, PC2, PC3, and PC4 were identified through principal component analysis (PCA) which, contributed 81.6% of the variance, where maximum loadings were from protein, oil, starch, and phytic acid. Sixteen clusters were identified through hierarchical clustering analysis (HCA) from which the trait-specific and biochemically most distant accessions could be identified for use in cultivar development in breeding programs.
印度次大陆是水稻的主要起源中心，在印度水稻基因库（包括地方品种）中发现了丰富的多样性。印度东北部各邦拥有数千种高度多样的水稻地方品种，是营养特性的良好来源，但其中大多数在营养方面尚未得到表征。因此，采用美国官方分析化学家协会（AOAC）的官方方法和标准方法，对395份阿萨姆邦地方品种的总淀粉、直链淀粉含量（AC）、总膳食纤维（TDF）、总蛋白质含量（TPC）、油脂、酚类和总植酸（TPA）进行了营养成分分析，发现所估计性状的平均含量分别为75.2克/100克、22.2克/100克、4.67克/100克、9.8克/100克、5.26%、0.40没食子酸当量克/100克和0.34克/100克。对24个选定的种质进行了血糖生成指数（GI）评估，其中17个种质的血糖生成指数较低（<55）。在不同性状之间，发现了显著的相关性，这有助于直接和间接选择，如估计血糖生成指数（EGI）和直链淀粉含量（-0.803）。包括主成分分析（PCA）和层次聚类分析（HCA）在内的多变量分析揭示了营养属性的异同。通过主成分分析（PCA）确定了四个主成分，即PC1、PC2、PC3和PC4，它们贡献了81.6%的方差，其中最大载荷来自蛋白质、油脂、淀粉和植酸。通过层次聚类分析（HCA）确定了16个聚类，从中可以识别出性状特异且生化差异最大的种质，用于育种计划中的品种培育。
