ArticlePlant methods2021
Quantitative visualization of photosynthetic pigments in tea leaves based on Raman spectroscopy and calibration model transfer.
Article in Plant methods, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 71 citations in OpenAlex.
- Regenerable Membrane Sensors for Ultrasensitive Nanoplastic Quantification Enabled by A Data-driven Raman Spectral Processing Algorithm.Environmental science & technology · 2025Article
- A machine-learning-powered spectral-dominant multimodal soft wearable system for long-term and early-stage diagnosis of plant stresses.Science advances · 2025Article
- Raman Spectroscopy in the Characterization of Food Carotenoids: Challenges and Prospects.Foods (Basel, Switzerland) · 2025Review
- In-vivo Raman microspectroscopy reveals differential nitrate concentration in different developmental zones in Arabidopsis roots.Plant methods · 2024Article
- Contemporary applications of vibrational spectroscopy in plant stresses and phenotyping.Frontiers in plant science · 2024Review
- Research Review on Quality Detection of Fresh Tea Leaves Based on Spectral Technology.Foods (Basel, Switzerland) · 2023Review
- Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy.Plants (Basel, Switzerland) · 2023Article
- Raman spectroscopy in crop quality assessment: focusing on sensing secondary metabolites: a review.Horticulture research · 2023Article
- Isolation of Lead Resistant Bacteria from Spent Mushroom Compost and Their Impact on Growth and Biochemical Parameters of Safflower.Current microbiology · 2023Article
- A Model Transfer Method among Spectrometers Based on Improved Deep Autoencoder for Concentration Determination of Heavy Metal Ions by UV-Vis Spectra.Sensors (Basel, Switzerland) · 2023Article
- Exogenous Application of Glycine Betaine on Sweet Cherry Tree (Plants (Basel, Switzerland) · 2022Article
- Classification and Prediction by Pigment Content in Lettuce (Plants (Basel, Switzerland) · 2022Article
- Quantification of Salicylates and Flavonoids in Poplar Bark and Leaves Based on IR, NIR, and Raman Spectra.Molecules (Basel, Switzerland) · 2022Article
- Raman Spectroscopy Applications in Grapevine: Metabolic Analysis of Plants Infected by Two Different Viruses.Frontiers in plant science · 2022Article
- Raman Spectroscopy Detects Changes in Carotenoids on the Surface of Watermelon Fruits During Maturation.Frontiers in plant science · 2022Article
- A Spatial-Temporal Analysis of Cellular Biopolymers on Leaf Blight-Infected Tea Plants Using Confocal Raman Microspectroscopy.Frontiers in plant science · 2022Article
- Insight into Details of the Photosynthetic Light Reactions and Selected Metabolic Changes in Tomato Seedlings Growing under Various Light Spectra.International journal of molecular sciences · 2021Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPhotosynthetic pigments participating in the absorption, transformation and transfer of light energy play a very important role in plant growth. While, the spatial distribution of foliar pigments is an important indicator of environmental stress, such as pests, diseases and heavy metal stress.
resultsIn this paper, in situ quantitative visualization of chlorophyll and carotenoid was realized by combining the Raman spectroscopy with calibration model transfer, and a laboratory Raman spectral model was successfully extended to a portable field spectral measurement. Firstly, a nondestructive and fast model for determination of chlorophyll and carotenoid in tea leaf was established based on confocal micro-Raman spectrometer in the laboratory. Then the spectral model was extended to a real-time foliar map scanning spectra of a field portable Raman spectrometer through calibration model transfer, and the spectral variation between the confocal micro-Raman spectrometer in the laboratory and the portable Raman spectrometer were effectively corrected by the direct standardization (DS) algorithm. The portable map scanning Raman spectra of the tea leaves after the model transfer were got into the established quantitative determination model to predict the concentration of photosynthetic pigments at each pixel of the tea leaves. The predicted photosynthetic pigments concentration of each pixel was imaged to illustrate the distribution map of foliar pigments. Statistical analysis showed that the predicted pigment contents were highly correlated with the real contents.
conclusionsIt can be concluded that the Raman spectroscopy was applicable for in situ, non-destructive and rapid quantitative detecting and imaging of photosynthetic pigment concentration in tea leaves, and the spectral detection model established based on the laboratory Raman spectrometer can be applied to a portable field spectrometer for quantitatively imaging of the foliar pigments.
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