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Development of a statistical crop model to explain the relationship between seed yield and phenotypic diversity within the Brassica napus genepool

机译:建立统计作物模型以解释甘蓝型油菜种质资源内种子产量与表型多样性之间的关系

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摘要

Plants are extremely versatile organisms that respond to the environment in which they find themselves, but a large part of their development is under genetic regulation. The links between developmental parameters and yield are poorly understood in oilseed rape; understanding this relationship will help growers to predict their yields more accurately and breeders to focus on traits that may lead to yield improvements. To determine the relationship between seed yield and other agronomic traits, we investigated the natural variation that already exists with regards to resource allocation in 37 lines of the crop species Brassica napus. Over 130 different traits were assessed; they included seed yield parameters, seed composition, leaf mineral analysis, rates of pod and leaf senescence and plant architecture traits. A stepwise regression analysis was used to model statistically the measured traits with seed yield per plant. Above-ground biomass and protein content together accounted for 94.36% of the recorded variation. The primary raceme area, which was highly correlated with yield parameters (0.65), provides an early indicator of potential yield. The pod and leaf photosynthetic and senescence parameters measured had only a limited influence on seed yield and were not correlated with each other, indicating that reproductive development is notudnecessarily driving the senescence process within field-grown B. napus. Assessing the diversity that exists within the B. napus gene pool has highlighted architectural, seed and mineral composition traits that should be targeted in breeding programmes through the development of linked markers to improve crop yields.
机译:植物是一种极其通用的生物,可以对自身所处的环境做出反应,但是其大部分发育都处于遗传调控之下。油菜对发育参数和产量之间的联系了解甚少。理解这种关系将有助于种植者更准确地预测其产量,并帮助育种者专注于可能导致产量提高的性状。为了确定种子产量与其他农艺性状之间的关系,我们调查了37种作物甘蓝型油菜的资源分配方面已经存在的自然变异。评估了130多种不同的特征;它们包括种子产量参数,种子组成,叶片矿物质分析,豆荚和叶片衰老率以及植物结构性状。使用逐步回归分析对每株植物的种子产量与所测性状进行统计建模。地上生物量和蛋白质含量合计占已记录变异的94.36%。与产量参数(0.65)高度相关的初级总消旋面积,是潜在产量的早期指标。荚果和叶片的光合和衰老参数对种子产量的影响有限,并且彼此之间没有相关性,这表明在田间生长的油菜中,生殖发育没有不必要地驱动衰老过程。评估油菜双歧杆菌基因库内存在的多样性,突出了建筑,种子和矿物组成的性状,应通过开发相关标记来提高作物产量,将其作为育种计划的目标。

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