ArticleFrontiers in plant science2017
Accurate Digitization of the Chlorophyll Distribution of Individual Rice Leaves Using Hyperspectral Imaging and an Integrated Image Analysis Pipeline.
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 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Manganese Phytoremediation Potential ofPlants (Basel, Switzerland) · 2025Article
- SMICGS: A novel snapshot multispectral imaging sensor for quantitative monitoring of crop growth.Plant phenomics (Washington, D.C.) · 2025Article
- From ADAS to Material-Informed Inspection: Review of Hyperspectral Imaging Applications on Mobile Ground Robots.Sensors (Basel, Switzerland) · 2025Review
- From spectrum to yield: advances in crop photosynthesis with hyperspectral imaging.Photosynthetica · 2025Review
- Hyperspectral and Fluorescence Imaging Approaches for Nondestructive Detection of Rice Chlorophyll.Plants (Basel, Switzerland) · 2024Article
- Optimal-Band Analysis for Chlorophyll Quantification in Rice Leaves Using a Custom Hyperspectral Imaging System.Plants (Basel, Switzerland) · 2024Article
- Simultaneous Quantification and Visualization of Photosynthetic Pigments inPlants (Basel, Switzerland) · 2023Article
- High throughput analysis of leaf chlorophyll content in sorghum using RGB, hyperspectral, and fluorescence imaging and sensor fusion.Plant methods · 2022Article
- Identification of plant leaf phosphorus content at different growth stages based on hyperspectral reflectance.BMC plant biology · 2021Article
- Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature.Plant phenomics (Washington, D.C.) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pigments absorb light, transform it into energy, and provide reaction sites for photosynthesis; thus, the quantification of pigment distribution is vital to plant research. Traditional methods for the quantification of pigments are time-consuming and not suitable for the high-throughput digitization of rice pigment distribution. In this study, using a hyperspectral imaging system, we developed an integrated image analysis pipeline for automatically processing enormous amounts of hyperspectral data. We also built models for accurately quantifying 4 pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoid) from rice leaves and determined the important bands (700-760
Indexed as
Identifiers
What OpenQuestion holds
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.