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首页> 外文期刊>The Indian journal of genetics & plant breeding >Genetic improvement trend analysis for end-use quality characteristics among wheat cultivars of North-Western India
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Genetic improvement trend analysis for end-use quality characteristics among wheat cultivars of North-Western India

机译:印度西北部小麦品种最终品质特征的遗传改良趋势分析

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摘要

To test the perception among consumers in India for declining nutritional quality of wheat, the trends in end use quality characteristics of popular wheat cultivars of North Western Plain Zone were studied. Fourteen mega varieties released since 1900 were grown in randomized block design over two years. ANOVA revealed no significant differences for nitrogen percentage in grain as well as straw, however, significant differences among the genotypes within breeding period for kernel hardness, sedimentation value and thousand kernel weights was observed. Linear regression equation for thousand kernel weight indicated a poor gain of 0.036g per year. However, the cubical polynomial regression equation significantly improved the association between kernel weight and year of release (R-2 = 0.675). Similarly, cubical polynomial equation indicated continuous decline for sedimentation value with indication of some improvement in recent past. The present study therefore, clearly establishes no perceptible loss in nutritional quality. No trend was observed for flour recovery over the years. The study establishes that breeders did not deliberately modify any of the quality traits except grain plumpness and perceived changes are either not true or due to deterioration in production environment over years. GGE biplot analysis grouped HD 2967, HDCSW 16, HD 3086 along with C 591 and identified HDCSW 16 as the most ideal genotype for grain weight.
机译:为了检验印度消费者对小麦营养质量下降的看法,研究了西北平原地区流行小麦品种最终用途质量特征的趋势。自1900年以来发行的14个大型变种以随机区组设计种植了两年。方差分析显示谷物和稻草中的氮含量无显着差异,但是,在繁殖期内,各基因型之间的籽粒硬度,沉降值和千粒重均存在显着差异。千粒重的线性回归方程表明每年可增加0.036g。但是,三次多项式回归方程显着改善了籽粒重量与释放年份之间的关联(R-2 = 0.675)。同样,三次多项式方程表明沉降值连续下降,表明最近有所改善。因此,本研究显然没有确定营养品质的明显下降。多年来没有观察到面粉回收的趋势。该研究表明,育种人员没有刻意修改任何质量性状,除非谷物饱满感和感知的变化不是真实的,或者是由于多年来生产环境的恶化所致。 GGE双图分析将HD 2967,HDCSW 16,HD 3086和C 591分组在一起,并确定HDCSW 16是最理想的谷物重量基因型。

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