Thermography as a Tool to Assess Inter-Cultivar Variability in Garlic Performance along Variations of Soil Water Availability.

REMOTE SENSING(2020)

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摘要
Climate change entails increasingly frequent, longer, and more severe droughts, especially in some regions, such as the Mediterranean region. Under these water scarcity conditions, agricultural yields of important crops, such as garlic, are threatened. Finding better adapted cultivars to low water availability environments could help mitigate the negative agricultural and economic impacts of climate change. For this purpose, plant phenotyping protocols based on remote-sensing technologies, such as thermal imaging, can be particularly valuable since they facilitate screening and selection of germplasm in a cost-effective manner, covering a wide range of temporal and spatial scales. In this study, the use of a thermal index known as the crop water stress index (CWSI) was tested as a predictor of bulb biomass and for the assessment of inter-cultivar variability of five garlic cultivars in response to a gradient of soil volumetric water contents (VWCs). Three experimental assays, one in the 2018 season and two in 2019, covering a wide range of water availability levels were carried out. Different linear models were developed, with CWSI and VWCs as continuous predictors of bulb biomass, and the factor cultivar as a categorical predictor. The results support the existence of inter-cultivar variation in terms of sensitivity to water availability. The most productive cultivars under favorable conditions were also the most sensitive to water availability. In contrast, the cultivars with lower bulb production potential displayed lower sensitivity to water availability and higher stability across experimental assays. The results also support that CWSI, which was sensitive to inter-cultivar variability, is a good predictor of garlic bulb biomass. Therefore, CWSI can be a valuable tool for garlic phenotyping and cultivar screening.
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关键词
thermography,garlic,CWSI,water availability,cultivar,modeling,R,biomass,climate change,plant phenotyping
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