Integration of high-throughput phenotyping with anatomical traits of leaves to help understanding lettuce acclimation to a changing environment

Abstract

MAIN CONCLUSION: The combination of image-based phenotyping with in-depth anatomical analysis allows for a thorough investigation of plant physiological plasticity in acclimation, which is driven by environmental conditions and mediated by anatomical traits. Understanding the ability of plants to respond to fluctuations in environmental conditions is critical to addressing climate change and unlocking the agricultural potential of crops both indoor and in the field. Recent studies have revealed that the degree of eco-physiological acclimation depends on leaf anatomical traits, which show stress-induced alterations during organogenesis. Indeed, it is still a matter of debate whether plant anatomy is the bottleneck for optimal plant physiology or vice versa. Here, we cultivated 'Salanova' lettuces in a phenotyping chamber under two different vapor pressure deficits (VPDs; low, high) and watering levels (well-watered, low-watered); then, plants underwent short-term changes in VPD. We aimed to combine high-throughput phenotyping with leaf anatomical analysis to evaluate their capability in detecting the early stress signals in lettuces and to highlight the different degrees of plants' eco-physiological acclimation to the change in VPD, as influenced by anatomical traits. The results demonstrate that well-watered plants under low VPD developed a morpho-anatomical structure in terms of mesophyll organization, stomatal and vein density, which more efficiently guided the acclimation to sudden changes in environmental conditions and which was not detected by image-based phenotyping alone. Therefore, we emphasized the need to complement high-throughput phenotyping with anatomical trait analysis to unveil crop acclimation mechanisms and predict possible physiological behaviors after sudden environmental fluctuations due to climate changes.

Plant phenotyping relevance

画像ベースの高スループット表現型解析を解剖学的形質と統合し、環境変化によるストレス・順化シグナルの検出能力を評価することが研究目的の中心であるため、方法適用研究として含める。

Code and data availability

The paper's phenotyping and anatomical measurements are not deposited in any public repository; the authors state the data are available only upon reasonable request from the corresponding author. No author analysis code, images, or trained models are publicly linked. The supplementary file is a small DOCX without an明确

No evidence-backed public reproduction asset is currently recorded.