ArticlePlants (Basel, Switzerland)2023
Chemometric Analysis for the Prediction of Biochemical Compounds in Leaves Using UV-VIS-NIR-SWIR Hyperspectroscopy.
Article in Plants (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Harnessing Spectral Libraries From AVIRIS-NG Data for Precise PFT Classification: A Deep Learning Approach.Plant, cell & environment · 2026Article
- Hyperspectral imaging reveals early drought stress and associated molecular responses in lettuce for space agriculture.Plant phenomics (Washington, D.C.) · 2026Article
- Video-rate label-free molecular mapping in living plant tissue with a deployable optical encoder.PNAS nexus · 2026Article
- Optimizing chlorophyll content prediction in tea leaves via spectral transformations and deep learning.BMC plant biology · 2025Article
- Exploring Microelement Fertilization and Visible-Near-Infrared Spectroscopy for Enhanced Productivity inPlants (Basel, Switzerland) · 2024Article
- Fluorescence and Hyperspectral Sensors for Nondestructive Analysis and Prediction of Biophysical Compounds in the Green and Purple Leaves ofSensors (Basel, Switzerland) · 2024Article
- Indirect Estimation of Heavy Metal Contamination in Rice Soil Using Spectral Techniques.Plants (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Reflectance hyperspectroscopy is recognised for its potential to elucidate biochemical changes, thereby enhancing the understanding of plant biochemistry. This study used the UV-VIS-NIR-SWIR spectral range to identify the different biochemical constituents in Hibiscus and Geranium plants. Hyperspectral vegetation indices (HVIs), principal component analysis (PCA), and correlation matrices provided in-depth insights into spectral differences. Through the application of advanced algorithms-such as PLS, VIP,
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.