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Title: High-throughput field phenotyping using hyperspectral reflectance and partial least squares regression (PLSR) reveals genetic modifications to photosynthetic capacity

Author
item MEACHAM-HENSOLD, KATHERINE - University Of Illinois
item MONTES, CHRISTOPHER - University Of Illinois
item WU, JIN - Brookhaven National Laboratory
item GUAN, KAIYU - University Of Illinois
item PEDERSON, TAYLOR - University Of Illinois
item MOORE, CAITLIN - University Of Illinois
item Ainsworth, Elizabeth - Lisa
item RAINES, CHRISTINE - University Of Essex
item BROWN, KENNY - University Of Essex
item Bernacchi, Carl

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2019
Publication Date: 9/15/2019
Citation: Meacham-Hensold, K., Montes, C.M., Wu, J., Guan, K., Pederson, T., Moore, C., Ainsworth, E.A., Raines, C., Brown, K., Bernacchi, C.J. 2019. High-throughput field phenotyping using hyperspectral reflectance and partial least squares regression (PLSR) reveals genetic modifications to photosynthetic capacity. Remote Sensing of Environment. 231:111176. https://doi.org/10.1016/j.rse.2019.04.029.
DOI: https://doi.org/10.1016/j.rse.2019.04.029

Interpretive Summary: Photosynthesis is process by which plants utilize energy from light to grow and, for the purpose of agriculture, produce food, fuel, feed, and fiber. Photosynthesis, however, is relatively inefficient which lowers the potential yield from crops. But this inefficiency also provides opportunity to improve yields through modifying the photosynthetic pathway to be more efficient. A key challenge to assessing improved photosynthetic pathway in plants involve measuring photosynthesis; traditional methods for determining photosynthetic rates are slow, laborious, and expensive. Newer technologies rely on 'high-throughput' methods for measuring photosynthesis in a much faster, inexpensive, and efficient manner. However, it isn't clear whether these techniques, which rely on light reflection from leaves at various different wavelengths, will provide insights into photosynthetic capacity for plants genetically modified to have high photosynthetic efficiency. The research in this paper uses a high-throughput method to measure photosynthesis in plants that have a range of photosynthetic capacities, which includes natural variation among different plant cultivars and a number of genetically modified plants to have higher and lower photosynthetic rates. The results show that the high-throughput techniques to assess photosynthesis works for plants have been genetically modified as well as those that are non-modified wild-type plants. The results show that high-throughput techniques that have been developed for plants occurring in nature can be used on genetically modified plants and, as a result, can rapidly improve breeding of crops toward higher yields.

Technical Abstract: hotosynthesis is a major target for improvement to increase staple food crop yields, yet measuring photosynthesis in field trials is slow and laborious. Here we used hyperspectral reflectance analysis to predict photosynthetic capacity in field trials of plants with transgenic modifications made to the photosynthetic pathway. With this high throughput approach, we were able to successfully predict Vcmax (maximum carboxylation rate of Rubisco) (R2 = 0.66) and Jmax (maximum electron transport rate) (R2 = 0.57) in transgenic plants with increased photosynthetic enzyme activity and reduced Rubisco, showing the potential for using hyperspectral reflectance as a high-throughput phenotyping tool to determine photosynthetic capacities in large field trials of plants with photosynthetic modifications.