ArticleFrontiers in plant science2017
Chlorophyll Fluorescence Imaging Uncovers Photosynthetic Fingerprint of Citrus Huanglongbing.
Article in Frontiers in plant science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Fertilization Strategies in Huanglongbing-InfectedPlants (Basel, Switzerland) · 2025Article
- Recent advances in plant stress analysis using chlorophyllPhotosynthetica · 2025Review
- Plant stress detection using multimodal imaging and machine learning: from leaf spectra to smartphone applications.Frontiers in plant science · 2025Article
- Exploration and genetic analyses of canopy leaf pigmentation changes in soybean (Glycine max L.): unveiling a novel phenotype.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Precision Detection of Salt Stress in Soybean Seedlings Based on Deep Learning and Chlorophyll Fluorescence Imaging.Plants (Basel, Switzerland) · 2024Article
- Hyperspectral indices data fusion-based machine learning enhanced by MRMR algorithm for estimating maize chlorophyll content.Frontiers in plant science · 2024Article
- Classification of tomato seedling chilling injury based on chlorophyll fluorescence imaging and DBO-BiLSTM.Frontiers in plant science · 2024Article
- Foliar Applications of Salicylic Acid on Boosting Salt Stress Tolerance in Sour Passion Fruit in Two Cropping Cycles.Plants (Basel, Switzerland) · 2023Article
- Impact of Web Blight on Photosynthetic Performance of an Elite Common Bean Line in the Western Amazon Region of Colombia.Plants (Basel, Switzerland) · 2022Article
- Chlorophyll Fluorescence Imaging as a Tool for Evaluating Disease Resistance of Common Bean Lines in the Western Amazon Region of Colombia.Plants (Basel, Switzerland) · 2022Article
- Handheld Multifunctional Fluorescence Imager for Non-invasive Plant Phenotyping.Frontiers in plant science · 2022Article
- End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses.Plant phenomics (Washington, D.C.) · 2022Article
- Review: Application of Artificial Intelligence in Phenomics.Sensors (Basel, Switzerland) · 2021Review
- Low-Cost Chlorophyll Fluorescence Imaging for Stress Detection.Sensors (Basel, Switzerland) · 2021Article
- Quantitative Analysis of UV-B Radiation Interception in 3D Plant Structures and Intraindividual Distribution of Phenolic Contents.International journal of molecular sciences · 2021Article
- 'Frontiers in microbiology · 2021Article
- Breeding for Climate Change Resilience: A Case Study of Loblolly Pine (Frontiers in plant science · 2021Review
- Potential Phenotyping Methodologies to Assess Inter- and Intravarietal Variability and to Select Grapevine Genotypes Tolerant to Abiotic Stress.Frontiers in plant science · 2021Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Huanglongbing (HLB) is one of the most destructive diseases of citrus, which has posed a serious threat to the global citrus production. This research was aimed to explore the use of chlorophyll fluorescence imaging combined with feature selection to characterize and detect the HLB disease. Chlorophyll fluorescence images of citrus leaf samples were measured by an in-house chlorophyll fluorescence imaging system. The commonly used chlorophyll fluorescence parameters provided the first screening of HLB disease. To further explore the photosynthetic fingerprint of HLB infected leaves, three feature selection methods combined with the supervised classifiers were employed to identify the unique fluorescence signature of HLB and perform the three-class classification (i.e., healthy, HLB infected, and nutrient deficient leaves). Unlike the commonly used fluorescence parameters, this novel data-driven approach by using the combination of the mean fluorescence parameters and image features gave the best classification performance with the accuracy of 97%, and presented a better interpretation for the spatial heterogeneity of photochemical and non-photochemical components in HLB infected citrus leaves. These results imply the potential of the proposed approach for the citrus HLB disease diagnosis, and also provide a valuable insight for the photosynthetic response to the HLB disease.
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