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

  • Wei Ma
  • Xiu WangEmail author
  • Lijun Qi
  • Dongyan Zhang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

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 

Notes

Acknowledgements

This work was supported by the National Key Research and Development of China during the 13th Five-Year Plan Period(No. 2017YFD0201607-2) and our research center Innovation team project (JNKST201619). Sincere thanks to Dr. Liu Ting for helping me complete the complex work of inoculating the eggplant with nematodes.

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Intelligent Equipment for AgricultureBeijing Research CenterBeijingChina
  2. 2.Intelligent Equipment for AgricultureNational Engineering Research CenterBeijingChina
  3. 3.College of EngineeringChina Agricultural UniversityBeijingChina
  4. 4.School of Electronics and Information EngineeringAnhui UniversityHefeiChina

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