Abstract
Advancements in techniques to rapidly and non-destructively detect the impact of tropospheric ozone (O3) on crops are required. This study demonstrates the capability of full-range (350–2500 nm) reflectance spectroscopy to characterize responses of asymptomatic sage leaves under an acute O3 exposure (200 ppb for 5 h). Using partial least squares regression, spectral models were developed for the estimation of several traits related to photosynthesis, the oxidative pressure induced by O3, and the antioxidant mechanisms adopted by plants to cope with the pollutant. Physiological traits were well predicted by spectroscopic models (average model goodness-of-fit for validation (R2): 0.65–0.90), whereas lower prediction performances were found for biochemical traits (R2: 0.42–0.71). Furthermore, even in the absence of visible symptoms, comparing the full-range spectral profiles, it was possible to distinguish with accuracy plants exposed to charcoal-filtered air from those exposed to O3. An O3 effect on sage spectra was detectable from 1 to 5 h from the beginning of the exposure, but ozonated plants quickly recovered after the fumigation. This O3-tolerance was confirmed by trends of vegetation indices and leaf traits derived from spectra, further highlighting the capability of reflectance spectroscopy to early detect the responses of crops to O3.
Highlights
Tropospheric ozone (O3 ), produced by a variety of precursors, such as nitrogen oxides (NOx )and volatile organic compounds (VOCs), under light conditions, is a major phytotoxic air pollutant, with deleterious effects on animal health [1,2,3]
The aims of this work were (i) to develop spectroscopic models for the estimation of a variety of traits related to photosynthesis, the oxidative pressure induced by O3, and the antioxidant mechanisms adopted by plants to cope with the pollutant, (ii) to evaluate the potential of spectral phenotyping to accurately detect and predict O3 stress, and (iii) to elucidate the variations of both vegetation indices and the abovementioned leaf traits predicted from spectra by partial least squares regression (PLSR)-models, under O3 exposure
The root meanmean square error error (RMSE) for validation data were from 1.4 to 3.6 fold higher than RMSEs for calibration data, while larger differences were for water use efficiency (WUEi) and water use efficiencies (WUEin) (6.2 and 16 fold)
Summary
Volatile organic compounds (VOCs), under light conditions, is a major phytotoxic air pollutant, with deleterious effects on animal health [1,2,3]. O3 is commonly debated as a major air pollutant with detrimental effects on plants, some studies have proposed exposure to an Plants 2019, 8, 346; doi:10.3390/plants8090346 www.mdpi.com/journal/plants. Plants 2019, 8, 346 adequate concentration of O3 for a short time, under controlled conditions, as a tool to improve plant nutritional quality since it usually increases plant antioxidants to cope with O3 -induced oxidative stress without severely affecting plant performance [7,8]. Advancements in phenotyping techniques able to early detect and monitor the effects of O3 on crops, in the absence of visible symptoms, may optimize crop management, potentially leading to reduced crop yield losses and increased crop quality
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
