Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation (Part 2/2)

Long-term field monitoring of leaf pigment content is informative for
understanding plant responses to environments distinct from regulated
chambers but is impractical by conventional destructive measurements. We
developed PlantServation, a method incorporating robust image-acquisition
hardware and deep learning-based software that extracts leaf color by
detecting plant individuals automatically. As a case study, we applied
PlantServation to examine environmental and genotypic effects on the
pigment anthocyanin content estimated from leaf color. We analyzed
>4 million images of small individuals of four Arabidopsis species
in the field, where the plant shape, color, and background vary over
months. Past radiation, coldness, and precipitation significantly affected
the anthocyanin content. The synthetic allopolyploid A. kamchatica
recapitulated the fluctuations of natural polyploids by integrating
diploid responses. The data support a long-standing hypothesis stating
that allopolyploids can inherit and combine the traits of progenitors.
PlantServation facilitates the study of plant responses to complex
environments termed “in natura”.

对叶片色素含量开展长期野外监测，有助于理解植物在与受控培养箱（regulated chambers）环境截然不同的自然条件下的响应，但传统破坏性测量方法难以实现此类监测工作。我们开发了PlantServation方法，该方法集成了稳定可靠的图像采集硬件与基于深度学习的软件，可通过自动识别植株个体来精准提取叶片颜色信息。作为案例研究，我们运用PlantServation方法探究了环境与基因型对通过叶片颜色估算得到的色素——花青素（anthocyanin）含量的影响。我们对野外环境下4种拟南芥（Arabidopsis）的小型植株的超过400万张图像进行了分析，这些图像中的植株形态、颜色以及背景均随月份发生显著变化。过往的辐射、低温与降水条件均对花青素含量产生了显著影响。人工合成异源多倍体（allopolyploid）A. kamchatica通过整合二倍体的响应特征，重现了自然异源多倍体的含量波动规律。本研究数据验证了一个长期存在的假说：异源多倍体能够继承并结合其亲本的性状。PlantServation方法为研究植物在被称为"in natura"的复杂野外环境中的响应提供了有力支撑。