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首页> 外文期刊>Australian Journal of Crop Science >Correlations and path coefficient analysis for energy biomass production components in elephant grass (Pennisetum purpureum Schum)
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Correlations and path coefficient analysis for energy biomass production components in elephant grass (Pennisetum purpureum Schum)

机译:象草(Pennisetum purpureum Schum)中能量生物量生产成分的相关性和路径系数分析

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摘要

Elephant-grass (Pennisetum purpureum Schum) is known to have a great potential for biomass production, but studies on genotyperesponses to different sites and growing seasons are still scarce and necessary. This study aimed to estimate correlation and pathcoefficient analysis for biomass production trait in elephant grass under semi-annual cutting cycles. The experiment was conductedfrom 2012 to 2015 in a randomized block design with two replications. Seventy-three elephant grass cultivars (genotypes) wereassessed during six cutting cycles. Cuts were manually performed when grasses reached a height of 1.5 m (semi-annually). Thefollowing variables were analyzed HGT, SD, NT, LW, %DM and DMP. Data were subjected to individual and joint variance analysis, inaddition to analysis of genotypic, environmental, and phenotypic correlation and path analysis decomposition. Both genotypes andcuts had significant effects on all the variables. HGT, SD, and LW were significant, positive, and genotypically correlated with DMP.In terms of direct effects on DMP, NT (1.44) stood out with the highest effect and total correlation, thus showing a majorcontribution to DMP increases. Regarding indirect effects, %DM had a positive influence on DMP via NT and LW. The selection ofplants with a high %DM included genotypes with lower SD, HGT, and LW and higher NT. The environmental component had agreater influence on the relationships involving both NT and SD.
机译:众所周知,象草(Pennisetum purpureum Schum)具有巨大的生物量生产潜力,但是对不同地点和生长季节的基因型反应的研究仍然很少,而且是必要的。本研究旨在估计大象草在半年采伐周期下生物量生产性状的相关性和路径系数分析。该实验于2012年至2015年以随机分组设计进行,重复两次。在六个切割周期中评估了73个象草品种(基因型)。当草达到1.5 m高度(每半年)时,人工进行割草。分析了以下变量HGT,SD,NT,LW,%DM和DMP。数据进行了个体和联合方差分析,此外还进行了基因型,环境和表型相关性分析以及路径分析分解。基因型和切割对所有变量均具有显着影响。 HGT,SD和LW与DMP显着,正相关并在基因型上相关。就DMP的直接作用而言,NT(1.44)表现出最高的作用和总的相关性,从而显示出对DMP增加的主要贡献。关于间接影响,%DM通过NT和LW对DMP产生积极影响。 %DM高的植物的选择包括具有较低SD,HGT和LW和较高NT的基因型。环境因素对涉及NT和SD的关系有更大的影响。

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