In this contribution, we examine the potential of using field spectroscopy to discriminate the responses of five soybean cultivars to background ozone concentration. Statistical analysis of hyperspectral data including one-way analysis of variance (ANOVA) and spectral instability analysis (ISI) were used to identify the most effective wavelengths in mapping and differentiating the five cultivars with different tolerance to ozone damage. Our results show several distinctive spectral regions that can be used for effective crop type mapping within species level, and quantifying the effects of ozone damage at leaf and canopy scales. This work demonstrates that hyperspectral remote sensors soon become available from government and private sector satellites offer a new set of high-resolution spectral data that will help to quantify impacts background ozone concentrations due to climate change on food security.
['Abduwasit Ghulam', 'Jack Fishman', 'Matthew Maimaitiyiming']
Spectral separability analysis of five soybean cultivars with different ozone tolerance using hyperspectral field spectroscopy