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Remote Sens. 2018, 10(4), 562; https://doi.org/10.3390/rs10040562

Effects of Ambient Ozone on Soybean Biophysical Variables and Mineral Nutrient Accumulation

1
Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO 63108, USA
2
Center for Environmental Sciences, Saint Louis University, St. Louis, MO 63108, USA
*
Author to whom correspondence should be addressed.
Received: 17 January 2018 / Revised: 30 March 2018 / Accepted: 2 April 2018 / Published: 5 April 2018
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Abstract

The effects of increasing ambient ozone (O3) concentrations on food security has become a major concern as the demand for agricultural productivity is projected to increase significantly over the next several decades. In this contribution, the responses of common soybean genotypes (AK-HARROW, PI88788, DWIGHT, PANA, and WILLIAMS82) to ambient O3 are characterized using hyperspectral data and foliar biophysical, mineral nutrient concentrations and soybean yield. Specifically, leaf reflectance spectra measured at different growth stages and canopy layers were used to examine the spectral indices that were most strongly correlated with leaf physiological status. The effects of elevated O3 on six important nutrients (K, Ca, Mg, Fe, Mn and Cu) were evaluated by analyzing the variations in nutrient concentrations at two critical growth stages with increasing ambient O3 concentration using Partial Least Square Regression (PLSR). Lastly, the identified best spectral indices and the robust nutrient prediction models were extrapolated to the entire growth period to explore their ability to track the effects of ambient O3 concentrations on soybean physiology and nutrient uptake. The results showed that fluorescence yield (ΔF/Fm’) and photochemical quenching (qP) appear to be good indicators of soybean physiological responses to O3 stress that are echoed by the harvest index (HI). Newly identified normalized difference spectral index (NDSI) [R416, R2371] always had the highest correlation (R2 > 0.6) with ΔF/Fm’, qP and electron transport rate (ETR, μmol m−2 s−1) compared to the published indices. Additionally, there were significant and broad spectral regions in visible and near infrared region that were well-correlated with ΔF/Fm’ and selected NDSIs that were applicable to satellite observations. The results of nutrient modeling using PLSR explained 54–87% of the variance in nutrient concentrations, and the predicted mineral nutrient accumulation throughout the growing season reflected the responses of ozone tolerant and sensitive genotypes well. NDSI [R416, R2371] demonstrated great potential in regard to its sensitivity in tracking plant physiological responses to changing ambient O3 concentrations. The outcome of this research has potential implications for development of space-based observation of large-scale crop responses to O3 damage, as well as for biotechnological breeding efforts to improve ozone tolerance under future climate scenarios. View Full-Text
Keywords: hyperspectral data; ambient ozone; soybean; nutrient concentration; photochemical reflectance index (PRI); Partial Least Square Regression (PLSR) hyperspectral data; ambient ozone; soybean; nutrient concentration; photochemical reflectance index (PRI); Partial Least Square Regression (PLSR)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sagan, V.; Maimaitiyiming, M.; Fishman, J. Effects of Ambient Ozone on Soybean Biophysical Variables and Mineral Nutrient Accumulation. Remote Sens. 2018, 10, 562.

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