Spectral Estimation of In Vivo Wheat Chlorophyll a/b Ratio under Contrasting Water Availabilities

Gabriel Mulero, Harel Bacher, Uri Kleiner, Zvi Peleg, Ittai Herrmann*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


To meet the ever-growing global population necessities, integrating climate-change-rele-vant plant traits into breeding programs is required. Developing new tools for fast and accurate estimation of chlorophyll parameters, chlorophyll a (Chl-a) content, chlorophyll b (Chl-b) content, and their ratio (Chl-a/b), can promote breeding programs of wheat with enhanced climate adapta-bility. Spectral reflectance of leaves is affected by changes in pigment concentration and can be used to estimate chlorophyll parameters. The current study identified and validated the top known spectral indices and developed new vegetation indices (VIs) for Chl-a and Chl-b content estimation and used them to non-destructively estimate Chl-a/b values and compare them to hyperspectral estima-tions. Three wild emmer introgression lines, with contrasting drought stress responsiveness dynam-ics, were selected. Well-watered and water-limited irrigation regimes were applied. The wheat leaves were spectrally measured with a handheld spectrometer to acquire their reflectance in the 330 to 790 nm range. Regression models based on calculated VIs as well as all hyperspectral curves were calibrated and validated against chlorophyll extracted values. The developed normalized difference spectral indices (NDSIs) resulted in high accuracy of Chl-a (NDSI415,614) and Chl-b (NDSI406,525) estimation, allowing for indirect non-destructive estimation of Chl-a/b with root mean square error (RMSE) values that could fit 6 to 10 times in the range of the measured values. They also performed similarly to the hyperspectral models. Altogether, we present here a new tool for a non-destructive estimation of Chl-a/b, which can serve as a basis for future breeding efforts of cli-mate-resilient wheat as well as other crops.

Original languageAmerican English
Article number2585
Pages (from-to)2585
Number of pages1
JournalRemote Sensing
Issue number11
StatePublished - 1 Jun 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • drought
  • high throughput phenotyping
  • hyperspectral
  • pigment
  • wild emmer


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