Big data driven outlier detection for soybean straw near infrared spectroscopy-Reference-Cited by-同舟云学术

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Big data driven outlier detection for soybean straw near infrared spectroscopy

Published:2018-05 Issue: Volume:26 Page:178-189
ISSN:1877-7503
Container-title:Journal of Computational Science
language:en
Short-container-title:Journal of Computational Science

Author:

Wang Yan,Liu Qingfen,Hou Han-dan,Rho Seungmin,Gupta Brij,Mu Ying-xin,Shen Wei-zheng

Funder

National Key Research and Development Program of China

The National Natural Science Foundation of Heilongjiang Province

The “Young Talents” Project of Northeast Agricultural University

Publisher

Elsevier BV

Subject

Modelling and Simulation,General Computer Science,Theoretical Computer Science

Reference33 articles.

1. Current status of biomass energy development in China;Wu;Trans. Chin. Soc. Agric. Mach.,2009

2. Predicting Jatropha curcas seed-oil content, oil composition and protein content using near-infrared spectroscopy—a quick and non-destructive method;Vaknina;Ind. Crops Prod.,2011

3. Rapid characterization of woody biomass digestibility and chemical composition using near-infrared spectroscopy;Hou;J. Integr. Plant Biol.,2011

4. Nondestructive measurement of internal quality of Nanfeng mandarin fruit by charge coupled device near infrared spectroscopy;Liu;Comput. Electron. Agric.,2010

5. Feasibility of near infrared spectroscopy for analyzing com kernel damage and viability of soybean and com kernels;Agelet;J. Cereal Sci.,2012

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4. Discriminating geographical origins and determining active substances of water caltrop shells through near-infrared spectroscopy and chemometrics;Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy;2023-12

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