Background Grain yield, ear and kernel attributes can assist to understand the performance of maize plant under different environmental conditions and can be used in the variety development process to address farmer's preferences. These parameters are however still laborious and expensive to measure. Results A low-cost ear digital imaging method was developed that provides estimates of ear and kernel attributes i.e., ear number and size, kernel number and size as well as kernel weight from photos of ears harvested from field trial plots. The image processing method uses a script that runs in a batch mode on ImageJ; an open source software. Kernel weight was estimated using the total kernel number derived from the number of kernels visible on the image and the average kernel size. Data showed a good agreement in terms of accuracy and precision between ground truth measurements and data generated through image processing. Broad-sense heritability of the estimated parameters was in the range or higher than that for measured grain weight. Limitation of the method for kernel weight estimation is discussed. Conclusion The method developed in this work provides an opportunity to significantly reduce the cost of selection in the breeding process, especially for resource constrained crop improvement programs and can be used to learn more about the genetic bases of grain yield determinants.

中文翻译：

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使用穗数字成像的玉米穗表型和籽粒重量估计的高通量方法。

背景 谷物产量、穗和籽粒属性有助于了解玉米植株在不同环境条件下的表现，并可用于品种开发过程以满足农民的偏好。然而，这些参数测量起来仍然费力且昂贵。结果 开发了一种低成本的穗数字成像方法，该方法可从田间试验地块收获的穗照片中估计穗和仁的属性，即穗数和大小、仁数和大小以及仁重。图像处理方法使用在 ImageJ 上以批处理模式运行的脚本；一个开源软件。使用从图像上可见的内核数和平均内核大小得出的总内核数来估计内核权重。数据显示，地面实况测量值与通过图像处理生成的数据在准确度和精度方面具有良好的一致性。估计参数的广义遗传力处于或高于实测粒重的范围内。讨论了核权重估计方法的局限性。结论 这项工作中开发的方法为显着降低育种过程中的选择成本提供了机会，特别是对于资源受限的作物改良计划，并可用于更多地了解粮食产量决定因素的遗传基础。讨论了核权重估计方法的局限性。结论 这项工作中开发的方法为显着降低育种过程中的选择成本提供了机会，特别是对于资源受限的作物改良计划，并可用于更多地了解粮食产量决定因素的遗传基础。讨论了核权重估计方法的局限性。结论 这项工作中开发的方法为显着降低育种过程中的选择成本提供了机会，特别是对于资源受限的作物改良计划，并可用于更多地了解粮食产量决定因素的遗传基础。