Analyses of the correlation between hyperspectral reflectance and pigment content including chlorophyll-a, chlorophyll-b and carotenoid of leaves in different sites of rice were reported in this paper. The hyperspectral reflectance of late rice during the whole growing season was measured using a Spectroradiometer with spectral range of 350-1050 nm and resolution of 3 nm. The chlorophyll-a, chlorophyll-b and carotenoid contents in rice leaves in rice fields to which different levels of nitrogen were applied were measured. The chlorophyll-a content of upper leaves was well correlated with the spectral variables. However, the correlation between both chlorophyll-b and caroteniod and the spectral variables was far from that of chlorophyll-a. The potential of hyperspectral reflectance measurement for estimating chlorophyll-a of upper leaves was evaluated using univariate correlation and multivariate regression analysis methods with different types of predictors. This study showed that the most suitable estimated model of chlorophyll-a of upper leaves was obtained by using some hyperspectral variables such as SD(r), SD(b) and their integration.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1631/jzus.2003.0727 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Robust estimation of skin physiological parameters from hyperspectral images using Bayesian neural networks.
J Biomed Opt
January 2025
University of Ljubljana, Faculty of Mathematics and Physics, Ljubljana, Slovenia.
Significance: Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte Carlo and inverse adding-doubling (IAD).
Aim: We aim to develop a Bayesian neural network model for robust prediction of physiological parameters from hyperspectral images.
Approach: We propose a two-component system for extracting physiological parameters from hyperspectral images.
Using hyperspectral reflectance to detect changes in photosynthetic activity in leaves as a function of decreasing soil water content.
Photosynthetica
January 2025
Chengde Bijiashan Ecological Agriculture Technology Development Co., Ltd., 067000 Chengde, Hebei, China.
Application of hyperspectral reflectance technology to track changes in photosynthetic activity in () remains underexplored. This study aimed to investigate the relationship between hyperspectral reflectance and photosynthetic activity in the leaves of in response to a decrease in soil water content. Results demonstrated that the reflectance in both the visible light and near-infrared bands increased in conjunction with reduced soil water content.
View Article and Find Full Text PDFIntegrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants.
Chem Biodivers
January 2025
Department of Horticultural Science, Faculty of Agriculture, Jahrom University, Jahrom, Iran.
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) integrated with intelligent techniques to overcome these problems was investigated in this research. For this purpose, three classification methods-support vector machine, random forest (RF), and extreme gradient boosting-were studied for the classification of plants in three classes of medicinal, edible, and ornamental for the organs of leaf, stem, flower, and root.
View Article and Find Full Text PDFA hyperspectral stealth material design method based on the composition and mixing spectral feature of desert soil.
Sci Rep
January 2025
School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
In this study, we used desert soil from Gansu, China, as a sample to propose a method for designing hyperspectral stealth coatings against desert soil backgrounds within the spectral range of 400-2500 nm, and the corresponding coating was prepared. Firstly, the correlation between the composition and typical spectral detected characteristics of the desert soil was systematically analyzed. It was found that the color and the spectrum of the desert soil in the range of 400-1000 nm were influenced by different types of iron oxides.
View Article and Find Full Text PDFSearch of Reflectance Indices for Estimating Photosynthetic Activity of Wheat Plants Under Drought Stress.
Plants (Basel)
December 2024
Department of Biophysics, National Research Lobachevsky, State University of Nizhny Novgorod, 23 Gagarin Avenue, 603022 Nizhny Novgorod, Russia.
Global climate change and the associated increasing impact of droughts on crops challenges researchers to rapidly assess plant health on a large scale. Photosynthetic activity is one of the key physiological parameters related to future crop yield. The present study focuses on the search for reflectance parameters for rapid screening of wheat genotypes with respect to photosynthetic activity under drought conditions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!