Related Experiment Video
Updated: Aug 23, 2025

Author Spotlight: Unraveling Plant Responses to Abiotic Stresses Using the PlantScreen Robotic Platform
Published on: June 7, 2024
Dominant and Priming Role of Waterlogging in Tomato at e[CO2] by Multivariate Analysis
Rong Zhou1,2, Fangling Jiang1, Xiaqing Yu1
1College of Horticulture, Nanjing Agricultural University, Nanjing 210095, China.
Abstract:
The frequency of waterlogging episodes has increased due to unpredictable and intense rainfalls. However, less is known about waterlogging memory and its interaction with other climate change events, such as elevated CO2 concentration (e[CO2]). This study investigated the combined effects of e[CO2] and two rounds of waterlogging stress on the growth of cultivated tomato (Solanum lycopersicum) and wild tomato (S. pimpinellifolium). The aim is to elucidate the interaction between genotypes and environmental factors and thereby to improve crop resilience to climate change. We found that two rounds of treatments appeared to induce different acclimation strategies of the two tomato genotypes. S. pimpinellifolium responded more negatively to the first-time waterlogging than S. lycopersicum, as indicated by decreased photosynthesis and biomass loss. Nevertheless, the two genotypes respond similarly when waterlogging stress recurred, showing that they could maintain a higher leaf photosynthesis compared to single stress, especially for the wild genotype. This showed that waterlogging priming played a positive role in stress memory in both tomato genotypes. Multivariate analysis showed that waterlogging played a dominant role when combined with [CO2] for both the cultivated and wild tomato genotypes. This work will benefit agricultural production strategies by pinpointing the positive effects of e[CO2] and waterlogging memory.
More Related Videos
Related Concept Videos
Regulation of Transpiration by Stomata
Tonicity in Plants
Responses to Drought and Flooding
Regulation of Water Output
Adaptations that Reduce Water Loss
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...

