RGB imaging-based evaluation of waterlogging tolerance in cultivated and wild chrysanthemums
Waterlogging is a major stress that impacts the chrysanthemum industry. Large-scale germplasm screening for identifying waterlogging-tolerant resources in a quick and accurate manner is essential for developing new cultivars with improved waterlogging tolerance. To overcome this phenotyping bottleneck, consumer-grade digital cameras have been used to acquire the red-green-blue (RGB) images of 180 chrysanthemum cultivars and their wild relatives under waterlogging stress and well-watered conditions. A total of 103 image-based digital traits (i-traits), including 10 morphological i-traits and 93 texture i-traits, were extracted and systematically analyzed. Most of these i-traits presented high coefficients of variation (<i>CVs</i>) and broad-sense heritability (<i>H</i> <sup><i>2</i></sup> ), with an average <i>CV</i> of 34.04 % and an average <i>H</i> <sup><i>2</i></sup> of 0.93. We identified several novel texture i-traits associated with the hue (H) component, which strongly correlated with the traditional waterlogging tolerance index, the membership function value of waterlogging (MFVW) (<i>R</i> = 0.63-0.77). We further employed the random forest (RF) and gradient boosting tree (GBT) machine learning algorithms to predict aboveground biomass and MFVW on the basis of different i-trait datasets. The RF model achieved superior predictive performance, with a coefficient of determination (<i>R</i> <sup><i>2</i></sup> ) of up to 0.88 for shoot weight and 0.86 for MFVW. Moreover, a subset of the top 13 most important i-traits could accurately predict MFVW (<i>R</i> <sup><i>2</i></sup> > 0.80) via the cross-validation method. A total of 10 highly tolerant resources were selected by traditional and RGB-based evaluation, and 50 % belonged to <i>Artemisia</i>. Our findings confirmed that RGB-based technology provides a promising novel approach for quantifying waterlogging response that contributes to future breeding programs and genetic dissection for waterlogging tolerance.
Authors
- Limin Zhao (ORCID: https://orcid.org/0000-0002-5900-3236)
- Junwei Zeng (ORCID: https://orcid.org/0000-0001-6227-4849)
- Weimin Fang (ORCID: https://orcid.org/0000-0002-1804-9326)
- Siyue Wang (ORCID: https://orcid.org/0000-0002-0186-7955)
- Jiangshuo Su (ORCID: https://orcid.org/0009-0001-6350-1801)
- Fadi Chen (ORCID: https://orcid.org/0000-0001-9134-2353)
- Sumei Chen (ORCID: https://orcid.org/0000-0003-3973-0505)
- Haibin Wang (ORCID: https://orcid.org/0000-0002-9865-324X)
- Fei Zhang (ORCID: https://orcid.org/0009-0002-9879-5165)
- Yang Yang (ORCID: https://orcid.org/0009-0004-6746-3672)
Institutions
- Nanjing Agricultural University (CN)
- Zhongshan Hospital (CN)
- State Forestry and Grassland Administration (CN)
- Ministry of Agriculture and Rural Affairs (CN)
Publication Details
- Journal
- Plant Phenomics
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1016/j.plaphe.2025.100019
- Citations
- 1
- Primary Topic
- Plant responses to water stress
- Type
- article
- Field-Weighted Citation Impact
- 1.75