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Light Acquisition02:16

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Employing Spectral Features to Accelerate Sorghum Phenotyping Against Sap-Feeding Aphids.

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Spectral sensing effectively identifies sorghum resistance to sugarcane aphids (SCA). This method offers a faster, more accurate alternative to traditional phenotyping for monitoring crop pest resistance.

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Area of Science:

  • Plant Science
  • Agricultural Engineering
  • Remote Sensing

Background:

  • Traditional crop phenotyping for insect resistance is slow and variable.
  • Sugarcane aphid (SCA) significantly impacts sorghum growth, necessitating improved monitoring.
  • Spectral reflectance (VIS-NIR-SWIR) can assess plant stress and physiological status.

Purpose of the Study:

  • To evaluate spectral features for enhanced sorghum phenotyping against SCA.
  • To improve monitoring of sorghum resistance mechanisms to insect pests.
  • To explore spectral sensing as a tool for rapid aphid resistance assessment.

Main Methods:

  • Collected spectral reflectance data (400-2500 nm) from eight sorghum lines with varied SCA resistance.
  • Measured plant physiological and chlorophyll fluorescence parameters using LICOR and MultispeQ.
  • Utilized random forest and partial least square regression models for data analysis.

Main Results:

  • Random forest model achieved 87.4% accuracy in differentiating aphid-infested from control plants using VIS-NIR spectral features.
  • Significant differences in Greenness Index and Plant Senescence Reflectance Index were observed in susceptible lines.
  • Resistant lines showed higher stomatal conductance and chlorophyll fluorescence than susceptible lines when infested.

Conclusions:

  • VIS-NIR spectral features show promise for differentiating aphid-infested sorghum plants.
  • Spectral sensing offers a potential for effective monitoring and phenotyping of plant resistance to aphids.
  • This study provides a proof-of-concept for spectral sensing in pest resistance evaluation.