ArticlePlants (Basel, Switzerland)2022
Rapid Quantification Method for Yield, Calorimetric Energy and Chlorophyll
Article in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 22 citations in OpenAlex.
- Progressive Water Deficit Impairs Soybean Growth, Alters Metabolic Profiles, and Decreases Photosynthetic Efficiency.Plants (Basel, Switzerland) · 2025Article
- Evaluating the Effect of Thermal Treatment on Phenolic Compounds in Functional Flours Using Vis-NIR-SWIR Spectroscopy: A Machine Learning Approach.Foods (Basel, Switzerland) · 2025Article
- Comparative Insights into Photosynthetic, Biochemical, and Ultrastructural Mechanisms in Hibiscus and Pelargonium Plants.Plants (Basel, Switzerland) · 2024Article
- Hyperspectral Indices Developed from Fractional-Order Derivative Spectra Improved Estimation of Leaf Chlorophyll Fluorescence Parameters.Plants (Basel, Switzerland) · 2024Article
- Non-Invasive Assessment, Classification, and Prediction of Biophysical Parameters Using Reflectance Hyperspectroscopy.Plants (Basel, Switzerland) · 2023Article
- Article
- A Novel Method for Estimating Chlorophyll and Carotenoid Concentrations in Leaves: A Two Hyperspectral Sensor Approach.Sensors (Basel, Switzerland) · 2023Article
- Enhancing Pigment Phenotyping and Classification in Lettuce through the Integration of Reflectance Spectroscopy and AI Algorithms.Plants (Basel, Switzerland) · 2023Article
- Hyperspectral remote sensing for tobacco quality estimation, yield prediction, and stress detection: A review of applications and methods.Frontiers in plant science · 2023Review
- Classification and Prediction by Pigment Content in Lettuce (Plants (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
High-throughput and large-scale data are part of a new era of plant remote sensing science. Quantification of the yield, energetic content, and chlorophyll a fluorescence (ChlF) remains laborious and is of great interest to physiologists and photobiologists. We propose a new method that is efficient and applicable for estimating photosynthetic performance and photosystem status using remote sensing hyperspectroscopy with visible, near-infrared and shortwave spectroscopy (Vis-NIR-SWIR) based on rapid multivariate partial least squares regression (PLSR) as a tool to estimate biomass production, calorimetric energy content and chlorophyll a fluorescence parameters. The results showed the presence of typical inflections associated with chemical and structural components present in plants, enabling us to obtain PLSR models with R2P and RPDP values greater than >0.82 and 3.33, respectively. The most important wavelengths were well distributed into 400 (violet), 440 (blue), 550 (green), 670 (red), 700−750 (red edge), 1330 (NIR), 1450 (SWIR), 1940 (SWIR) and 2200 (SWIR) nm operating ranges of the spectrum. Thus, we report a methodology to simultaneously determine fifteen attributes (i.e., yield (biomass), ΔH°area, ΔH°mass, Fv/Fm, Fv’/Fm’, ETR, NPQ, qP, qN, ΦPSII, P, D, SFI, PI(abs), D.F.) with high accuracy and precision and with excellent predictive capacity for most of them. These results are promising for plant physiology studies and will provide a better understanding of photosystem dynamics in tobacco plants when a large number of samples must be evaluated within a short period and with remote acquisition data.
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Registered trials
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