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Grapevine leaves have diverse shapes and sizes which are influenced by many factors including genetics, vine phytosanitary status, environment, leaf and vine age, and node position on the shoot. To determine the relationship between grapevine leaf shape or size and leaf canopy temperature, we examined five seedling populations grown in a vineyard in California, USA. The populations had one parent with compound leaves of the Vitis piasezkii type and a different second parent with non-compound leaves. In previous work, we had measured the shape and size of the leaves collected from these populations using 21 homologous landmarks. Here, we paired these morphological data with canopy temperature measurements made using a handheld infrared thermometer. After recording time of sampling and canopy temperature, we used a linear model between time of sampling and canopy temperature to estimate temperature residuals. Based on these residuals, we determined if the canopy temperature of each vine was cooler or warmer than expected, based on the time of sampling. We established a relationship between leaf size and canopy temperature: vines with larger leaves were cooler than expected. By contrast, leaf shape was not strongly correlated with variation in canopy temperature. Ultimately, these findings indicate that vines with larger leaves may contribute to the reduction of overall canopy temperature; however, further work is needed to determine whether this is due to variation in leaf size, differences in the openness of the canopy or other related traits. 

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.