Study on the optimal algorithm prediction of corn leaf component information based on hyperspectral imaging-Reference-Cited by-同舟云学术

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Study on the optimal algorithm prediction of corn leaf component information based on hyperspectral imaging

Published:2016-09 Issue: Volume:78 Page:66-71
ISSN:1350-4495
Container-title:Infrared Physics & Technology
language:en
Short-container-title:Infrared Physics & Technology

Author:

Wu Qiong,Wang Jihua,Wang Cheng,Xu Tongyu

Funder

Natural Science Foundation of China

Special Fund for Agro-Scientific Research in the Public Interest of China

Liaoning Province Science and Technology Plan Projects

Education Department of Liaoning Province

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference22 articles.

1. A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies;Roggo;J. Pharm. Biomed. Anal.,2007

2. Cluster analysis of citrus genotypes using near-infrared spectroscopy;Liao;Intell. Automat. Soft Comput.,2013

3. Near-infrared Spectroscopy in Food Science and Technology;Ozaki,2007

4. Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties;Chang;Soil Sci. Soc. Am. J.,2000

5. Introduction to Spectral Analysis;Stoica,1997

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1. Genetic Algorithm Captured the Informative Bands for Partial Least Squares Regression Better on Retrieving Leaf Nitrogen from Hyperspectral Reflectance;Remote Sensing;2022-10-18

2. Chlorophyll content estimation based on cascade spectral optimizations of interval and wavelength characteristics;Computers and Electronics in Agriculture;2021-10

3. Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data;Photosynthesis Research;2021-09-07

4. PREDICTIVE MODELS OF CHLOROPHYLL CONTENT IN SUGARCANE SEEDLINGS USING SPECTRAL IMAGES;Engenharia Agrícola;2021-08

5. Non-destructive estimation of winter wheat leaf moisture content using near-ground hyperspectral imaging technology;Acta Agriculturae Scandinavica, Section B — Soil & Plant Science;2020-02-18

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