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Identification of Eggplant Young Seedlings Infected by Root Knot Nematodes Using Near Infrared Spectroscopy

Wei Ma 1, 2 Xiu Wang 1, 2 Lijun Qi 3 Dongyan Zhang 4
1 Beijing Research Center of Intelligent Equipment for Agriculture
2 NERCITA - National Engineering Research Center for Information Technology in Agriculture [Beijing]
3 College of Engineering [Beijing]
4 School of Electronics and Information Engineering [Hefei]
Abstract : In this paper, eggplant young seedlings infected by root knot nematodes were identified using near infrared spectroscopy. The main research on MSC and SG pretreatment method and PCA principal component extraction method with the combination of effects on model for classification. Results show: The best classification process is to do the first MSC after SG smoothing pretreatment, after using PCA extracted as the main component of the SIMCA input variables for classification, and achieved a classification average accuracy higher than 90%. It is an effective method to classify the degree of infection of the root knot nematodes by using the visible and near infrared spectral characteristics of the eggplant leaves.
Keywords : Near-infrared spectroscopy Soil disease Disease identification Disease identification 
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https://hal.inria.fr/hal-02180004
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Submitted on : Friday, July 12, 2019 - 2:33:07 PM
Last modification on : Tuesday, December 1, 2020 - 3:34:03 PM

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Distributed under a Creative Commons Attribution 4.0 International License

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IFIP | IFIP-AICT | IFIP-AICT-509 | IFIP-CCTA | IFIP-TC5 | IFIP-TC | IFIP-WG5-14

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Wei Ma, Xiu Wang, Lijun Qi, Dongyan Zhang. Identification of Eggplant Young Seedlings Infected by Root Knot Nematodes Using Near Infrared Spectroscopy. 10th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2016, Dongying, China. pp.93-100, ⟨10.1007/978-3-030-06155-5_9⟩. ⟨hal-02180004⟩

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