Photosynthesis acclimates quickly to the fluctuating environment in order to optimize the absorption of sunlight energy, specifically the photosynthetic photon fluence rate (PPFR), to fuel plant growth. The conversion efficiency of intercepted PPFR to photochemical energy (ɛe) and to biomass (ɛc) are critical parameters to describe plant productivity over time. However, they mask the link of instantaneous photochemical energy uptake under specific conditions, that is, the operating efficiency of photosystem II (Fq′/Fm′), and biomass accumulation. Therefore, the identification of energy- and thus resource-efficient genotypes under changing environmental conditions is impeded. We long-term monitored Fq′/Fm′ at the canopy level for 21 soybean (Glycine max (L.) Merr.) and maize (Zea mays) genotypes under greenhouse and field conditions using automated chlorophyll fluorescence and spectral scans. Fq′/Fm′ derived under incident sunlight during the entire growing season was modeled based on genotypic interactions with different environmental variables. This allowed us to cumulate the photochemical energy uptake and thus estimate ɛe noninvasively. ɛe ranged from 48% to 62%, depending on the genotype, and up to 9% of photochemical energy was transduced into biomass in the most efficient C4 maize genotype. Most strikingly, ɛe correlated with shoot biomass in seven independent experiments under varying conditions with up to r = 0.68. Thus, we estimated biomass production by integrating photosynthetic response to environmental stresses over the growing season and identified energy-efficient genotypes. This has great potential to improve crop growth models and to estimate the productivity of breeding lines or whole ecosystems at any time point using autonomous measuring systems.

中文翻译：

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预测田间季节作物基因型的光合效率和生物量增益


光合作用快速适应波动的环境，以优化阳光能量的吸收，特别是光合光子注量率 (PPFR)，为植物生长提供燃料。截获的 PPFR 向光化学能 (ɛe) 和生物量 (ɛc) 的转化效率是描述植物随时间变化生产力的关键参数。然而，它们掩盖了特定条件下瞬时光化学能量吸收的联系，即光系统II的运行效率（Fq'/Fm'）与生物量积累的联系。因此，在不断变化的环境条件下鉴定能源效率和资源效率高的基因型受到阻碍。我们使用自动叶绿素荧光和光谱扫描在温室和田间条件下长期监测 21 种大豆 (Glycine max (L.) Merr.) 和玉米 (Zea mays) 基因型的冠层水平 Fq'/Fm'。根据基因型与不同环境变量的相互作用，在整个生长季节在入射阳光下导出的 Fq'/Fm' 被建模。这使我们能够累积光化学能量吸收，从而无创地估计 ɛe。 εe 范围为 48% 至 62%，具体取决于基因型，在最高效的 C4 玉米基因型中，高达 9% 的光化学能转化为生物质。最引人注目的是，在不同条件下的七个独立实验中，ɛe 与芽生物量相关，最高 r = 0.68。因此，我们通过整合光合作用对生长季节环境胁迫的反应来估计生物量产量，并确定节能基因型。这对于改进作物生长模型以及使用自主测量系统在任何时间点估计育种系或整个生态系统的生产力具有巨大的潜力。