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Study on Wheat Grain Weight per Spike in the Area of Huaibei Region of Anhui Province

Yao Da-nian

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Abstract

Twenty-four wheat cultivars and lines were chosen to study the relationships between grain weight per spike and grain yield,yield components and other 18 agronomic traits through correlation and path coefficient analysis.The results showed that there were very significant differences in grain weight per spike,harvest index,yield and yield components among the tested varieties(or lines).Grain weight per spike showed extremely significant and positive correlation to grain number per spike,harvest index,single-stem biomass and grass weight;grain weight per spike also showed significant and positive correlation to yield,area of backward 3rd leaf;but grain weight per spike showed extremely significant and negative correlation to spike number and grain test weight.According to grain weight per spike,wheat varieties were classified into three broad types:Heavy-spike type with grain weight per spike more than or equal to 1.8 g;Mid-spike type with grain weight per spike between 1.4 g and 1.8 g;Light-spike type with grain weight per spike less than or equal to 1.4 g.In the purpose of enhancing grain weight per spike in Huaihei region,it was recommendable to increase the number of grains per spike along the increase of single-stem biomass and harvest index.

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What this paper is about

Twenty-four wheat cultivars and lines were chosen to study the relationships between grain weight per spike and grain yield,yield components and other 18 agronomic traits through correlation and path coefficient analysis.The results showed that there were very significant differences in grain weight per spike,harvest index,yield and yield components among the tested varieties(or lines).Grain weight per spike showed extremely significant and positive correlation to grain number per spike,harvest index,single-stem biomass and grass weight;grain weight per spike also showed significant and positive correlation to yield,area of backward 3rd leaf;but grain weight per spike showed extremely significant and negative correlation to spike number and grain test weight.According to grain weight per spike,wheat varieties were classified into three broad types:Heavy-spike type with grain weight per spike more than or equal to 1.8 g;Mid-spike type with grain weight per spike between 1.4 g and 1.8 g;Light-spike type with grain weight per spike less than or equal to 1.4 g.In the purpose of enhancing grain weight per spike in Huaihei region,it was recommendable to increase the number of grains per spike along the increase of single-stem biomass and harvest index.

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Available abstract

Twenty-four wheat cultivars and lines were chosen to study the relationships between grain weight per spike and grain yield,yield components and other 18 agronomic traits through correlation and path coefficient analysis.The results showed that there were very significant differences in grain weight per spike,harvest index,yield and yield components among the tested varieties(or lines).Grain weight per spike showed extremely significant and positive correlation to grain number per spike,harvest index,single-stem biomass and grass weight;grain weight per spike also showed significant and positive correlation to yield,area of backward 3rd leaf;but grain weight per spike showed extremely significant and negative correlation to spike number and grain test weight.According to grain weight per spike,wheat varieties were classified into three broad types:Heavy-spike type with grain weight per spike more than or equal to 1.8 g;Mid-spike type with grain weight per spike between 1.4 g and 1.8 g;Light-spike type with grain weight per spike less than or equal to 1.4 g.In the purpose of enhancing grain weight per spike in Huaihei region,it was recommendable to increase the number of grains per spike along the increase of single-stem biomass and harvest index.

Key concepts: Spike (software development), Path coefficient, Correlation coefficient, Agronomy, Grain yield, Yield (engineering), Cultivar, Path analysis (statistics)

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