Background Improving abiotic stress tolerance in wheat requires large scale screening of yield components such as seed weight, seed number and single seed weight, all of which is very laborious, and a detailed analysis of seed morphology is time-consuming and visually often impossible. Computed tomography offers the opportunity for much faster and more accurate assessment of yield components. Results An X-ray computed tomographic analysis was carried out on 203 very diverse wheat accessions which have been exposed to either drought or combined drought and heat stress. Results demonstrated that our computed tomography pipeline was capable of evaluating grain set with an accuracy of 95-99%. Most accessions exposed to combined drought and heat stress developed smaller, shrivelled seeds with an increased seed surface. As expected, seed weight and seed number per ear as well as single seed size were significantly reduced under combined drought and heat compared to drought alone. Seed weight along the ear was significantly reduced at the top and bottom of the wheat spike. Conclusions We were able to establish a pipeline with a higher throughput with scanning times of 7 min per ear and accuracy than previous pipelines predicting a set of agronomical important seed traits and to visualize even more complex traits such as seed deformations. The pipeline presented here could be scaled up to use for high throughput, high resolution phenotyping of tens of thousands of heads, greatly accelerating breeding efforts to improve abiotic stress tolerance.

中文翻译：

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使用计算机断层扫描对小麦的干旱和热胁迫耐受性进行筛查。

背景 提高小麦对非生物胁迫的耐受性需要大规模筛选种子重量、种子数和单粒重量等产量成分，所有这些都非常费力，而且对种子形态的详细分析既耗时又在视觉上通常是不可能的。计算机断层扫描提供了更快、更准确地评估产量成分的机会。结果 对 203 个非常多样化的小麦种质进行了 X 射线计算机断层扫描分析，这些种质已经暴露于干旱或干旱和热胁迫。结果表明，我们的计算机断层扫描管道能够以 95-99% 的准确度评估颗粒集。大多数暴露于干旱和热胁迫的种质会长出更小、干瘪的种子，种子表面增加。正如预期的那样，与单独干旱相比，干旱和高温联合下的种子重量和每穗种子数以及单个种子大小显着降低。在小麦穗的顶部和底部，沿穗的种子重量显着降低。结论 我们能够建立一个具有更高吞吐量的管道，扫描时间为每穗 7 分钟，准确性比以前的管道预测一组重要的农艺种子性状和可视化更复杂的性状，如种子变形。这里介绍的管道可以扩大规模以用于数万头的高通量、高分辨率表型分析，从而大大加快育种工作以提高非生物胁迫耐受性。在小麦穗的顶部和底部，沿穗的种子重量显着降低。结论 我们能够建立一个具有更高吞吐量的管道，扫描时间为每穗 7 分钟，准确性比以前的管道预测一组重要的农艺种子性状和可视化更复杂的性状，如种子变形。这里介绍的管道可以扩大规模以用于数万头的高通量、高分辨率表型分析，从而大大加快育种工作以提高非生物胁迫耐受性。在小麦穗的顶部和底部，沿穗的种子重量显着降低。结论 我们能够建立一个具有更高吞吐量的管道，扫描时间为每穗 7 分钟，准确性比以前的管道预测一组重要的农艺种子性状和可视化更复杂的性状，如种子变形。这里介绍的管道可以扩大规模以用于数万头的高通量、高分辨率表型分析，从而大大加快育种工作以提高非生物胁迫耐受性。结论 我们能够建立一个具有更高吞吐量的管道，扫描时间为每穗 7 分钟，准确性比以前的管道预测一组重要的农艺种子性状和可视化更复杂的性状，如种子变形。这里介绍的管道可以扩大规模以用于数万头的高通量、高分辨率表型分析，从而大大加快育种工作以提高非生物胁迫耐受性。结论 我们能够建立一个具有更高吞吐量的管道，扫描时间为每穗 7 分钟，准确性比以前的管道预测一组重要的农艺种子性状和可视化更复杂的性状，如种子变形。这里介绍的管道可以扩大规模以用于数万头的高通量、高分辨率表型分析，从而大大加快育种工作以提高非生物胁迫耐受性。