Photosynthesis Laboratory, Department of Horticulture, College of Aburaihan, University of Tehran, Tehran, Iran.
Photosynthesis Laboratory, Department of Horticulture, College of Aburaihan, University of Tehran, Tehran, Iran; Controlled Environment Agriculture Center, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.
Plant Physiol Biochem. 2023 Aug;201:107893. doi: 10.1016/j.plaphy.2023.107893. Epub 2023 Jul 13.
High light (HL) is a common environmental stress directly imposes photoinhibition on the photosynthesis apparatus. Breeding plants for tolerance against HL is therefore highly demanded. Chlorophyll fluorescence (ChlF) is a sensitive indicator of stress in plants and can be evaluated using OJIP transients. In this study, we compared the ChlF features of plants exposed to HL (1200 μmol m s) with that of control plants (300 μmol m s). To extract the most reliable ChlF features for discrimination between HL-stressed and non-stressed plants, we applied three artificial neural network (ANN)-based algorithms, namely, Boruta, Support Vector Machine (SVM), and Recursive Feature Elimination (RFE). Feature selection algorithms identified multiple features but only two features, namely the maximal quantum yield of PSII photochemistry (F/F) and quantum yield of energy dissipation (ɸ), remained consistent across all genotypes in control conditions, while exhibited variation in HL. Therefore, considered reliable features for HL stress screening. The selected features were then used for screening 14 tomato genotypes for HL. Genotypes were categorized into three groups, tolerant, semi-tolerant, and sensitive genotypes. Foliar hydrogen peroxide (HO) and malondialdehyde (MDA) contents were measured as independent proxies for benchmarking selected features. Tolerant genotypes were attributed with the lowest change in HO and MDA contents, while the sensitive genotypes displayed the highest magnitude of increase in HO and MDA by HL treatment compared to the control. Finally, a F/F higher than 0.77 and ɸ lower than 0.24 indicates a healthy electron transfer chain (ETC) when tomato plants are exposed to HL.
高光（HL）是一种常见的环境胁迫，直接对光合作用装置造成光抑制。因此，培育对 HL 具有耐受性的植物是非常有需求的。叶绿素荧光（ChlF）是植物胁迫的敏感指标，可以使用 OJIP 瞬变来评估。在这项研究中，我们比较了暴露在 HL（1200 μmol m s）下的植物和对照植物（300 μmol m s）的 ChlF 特征。为了提取最可靠的 ChlF 特征，用于区分 HL 胁迫和非胁迫植物，我们应用了三种基于人工神经网络（ANN）的算法，即 Boruta、支持向量机（SVM）和递归特征消除（RFE）。特征选择算法确定了多个特征，但只有两个特征，即 PSII 光化学的最大量子产量（F/F）和能量耗散的量子产量（ɸ），在对照条件下在所有基因型中保持一致，而在 HL 下表现出变化。因此，被认为是 HL 应激筛选的可靠特征。然后，使用所选特征筛选 14 个番茄基因型进行 HL 筛选。基因型分为三组，即耐受型、半耐受型和敏感型。测量叶片过氧化氢（HO）和丙二醛（MDA）含量作为基准所选特征的独立指标。与对照相比，耐受型基因型的 HO 和 MDA 含量变化最小，而敏感型基因型的 HO 和 MDA 含量增加幅度最大。最后，当番茄植物暴露在 HL 下时，F/F 高于 0.77 和 ɸ 低于 0.24 表明电子传递链（ETC）健康。
