Modeling Early Indicators of Grapevine Physiology Using Hyperspectral Imaging and Partial Least Squares Regression (PLSR)

Matthew Maimaitiyiming, Maitiniyazi Maimaitijiang, Paheding Sidike, Vasit Sagan, Zoe Migicovsky, Daniel H. Chitwood, Peter Cousins, Nick Dokoozlian, Allison J. Miller, Misha Kwasniewski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this contribution, we use field-based hyperspectral imaging (HSI) and partial least squares regression (PLSR) to estimate early indicators of grapevine physiological indicators, and analyze identified significant spectral regions for fast and accurate plant health monitoring. HSI and physiological measurements were carried out at two commercial vineyards in California, USA. The PLSR models were developed between reflectance spectra extracted from hyperspectral images and four vine physiological parameters, including stomatal conductance (Gs) photosynthetic CO2 rate (A), intercellular CO2 concentration (Ci) and transpiration rate (E). The results demonstrate PLSR models to predict physiological parameters (\mathrm{R}^{2}\geq 0.6), and the best model was found for \mathrm{G}-{\mathrm{s}}\ (\mathrm{R}^{2}=0.7). The identified significant spectral regions overlap with most commonly used remote sensing stress indicator, suggesting that HSI coupled with PLSR has great potential for upscaling and broader agricultural applications.

Original languageEnglish (US)
Title of host publication2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1117-1120
Number of pages4
ISBN (Electronic)9781728163741
DOIs
StatePublished - Sep 26 2020
Event2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States
Duration: Sep 26 2020Oct 2 2020

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Country/TerritoryUnited States
CityVirtual, Waikoloa
Period9/26/2010/2/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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