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Sensitivity of leaflet growth rate to drought predicts yield in common bean (Phaseolus vulgaris)
Functional Plant Biology ( IF 2.6 ) Pub Date : 2020-06-19 , DOI: 10.1071/fp19332
Amber N Hageman 1 , Milan O Urban 2 , Elizabeth Van Volkenburgh 3
Affiliation  

Although drought limits yield by decreasing photosynthesis and therefore biomass accumulation, biomass is not the strongest predictor of yield under drought in common beans (Phaseolus vulgaris L.). Instead, resource partitioning from pod walls into seeds is a stronger correlate. Our aim was to determine whether growth rates of developing leaflets and pods, as independent indicators of sink strength, predict resource partitioning into seeds. Using 20 field-grown genotypes, we paired biomass, yield, and resource partitioning data with leaflet and pod growth rates under well-watered and droughted conditions. We hypothesised that genotypes with faster growing leaflets and pods under drought would fill seeds better. However, we found that leaflet and pod growth rates did not predict partitioning to seeds; rather, sensitivity of leaflet growth rate to drought was a good predictor of yield reduction. Further, plants with rapidly growing leaves under well-watered conditions were most vulnerable to decreases in leaflet growth rate under drought. This suggests that lines that inherited a conservative growth strategy were better able to maintain yield by allocating resources to seeds. Our findings indicate that inherent sensitivity of leaflet growth rate to drought may be used as a predictor of partitioning and yield in common beans.

中文翻译:

叶片生长速率对干旱的敏感性预测普通豆(Phaseolus vulgaris)的产量

尽管干旱通过减少光合作用和生物量积累来限制产量,但生物量并不是普通豆类(Phaseolus vulgaris L.)干旱条件下产量的最强预测因子。相反,从豆荚壁到种子的资源划分具有更强的相关性。我们的目的是确定发育中的小叶和豆荚的生长速度,作为库强度的独立指标,是否可以预测资源分配到种子中。使用 20 种田间种植的基因型,我们将生物量、产量和资源分配数据与水分充足和干旱条件下的小叶和豆荚生长率配对。我们假设在干旱条件下具有更快生长的小叶和豆荚的基因型会更好地填充种子。然而,我们发现小叶和豆荚的生长率并不能预测种子的分配;相当,叶片生长速率对干旱的敏感性是减产的良好预测指标。此外,在水分充足的条件下叶片快速生长的植物最容易受到干旱条件下叶片生长速度下降的影响。这表明继承了保守生长策略的品系能够通过将资源分配给种子来更好地保持产量。我们的研究结果表明,小叶生长速率对干旱的固有敏感性可用作普通豆类分配和产量的预测因子。
更新日期:2020-06-19
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