RII Track-4: Penetrating the Inner Lives of Leaves to Breed Water-Wise Crops Using Math, 3D Imaging, and Experiments

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There is a need to grow more food with less land and fewer inputs to meet the demands of a growing population while simultaneously protecting the environment. Leveraging traits in the wild relatives of crop species could help breed sustainable crop varieties that produce more food with fewer resources. Leaf anatomy has a major effect on photosynthesis by determining rates of carbon gain and water loss. The aim of this project is to figure out if the leaf anatomy of wild relatives can improve the water-use efficiency of crops. To achieve this goal, the PI will integrate existing mathematical representations of carbon and water movement within leaves, parameterize models with 3D images of leaves from wild tomato species, and test model predictions using customized equipment for measuring photosynthesis. The mathematical tools and data collected on wild tomatoes will improve our nation's ability to grow food sustainably.Wild relatives of crop species are an underutilized reservoir of traits that could make agriculture more sustainable. The internal anatomy of leaves influences the rate of carbon gain and water loss during photosynthesis. It is not clear how crop water-use efficiency could be improved by harnessing natural variation in leaf anatomy among crop-wild relatives. This project aims to leverage recent advances in modeling, imaging, and measuring of leaf interiors in order to discover how and why crop-wild relatives of tomato (Solanum spp.) use water more wisely than their domesticated cousins. The goals of this project are to 1) model gas exchange (H2O and CO2 fluxes) in the leaf interior to understand how anatomy affects water-use efficiency; 2) image 3D leaf interiors using microCT to accurately quantify key traits identified by modeling; and 3) measure gas exchange parameters in wild tomatoes to validate modeling. With collaborators at the University of California, Davis, these objectives will be achieved by analyzing a spatially-explicit model of CO2 and water transport within the leaf, parameterizing the model using 3D images of wild tomato leaf interiors, and testing model predictions using a custom gas exchange system for artificial gas mixtures. This work will reveal both the opportunities and potential challenges of improving crop sustainability by introducing leaf anatomical variation from wild relatives.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.