|CAMARILLO-CASTILLO, FATIMA - International Maize & Wheat Improvement Center (CIMMYT)|
|MONDAL, SUCHISMITA - International Maize & Wheat Improvement Center (CIMMYT)|
|REYNOLDS, MATTHEW - International Maize & Wheat Improvement Center (CIMMYT)|
|Tilley, Michael - Mike|
|HAYS, DIRK - Texas A&M University|
Submitted to: Plant Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/26/2021
Publication Date: 6/7/2021
Publication URL: https://handle.nal.usda.gov/10113/7407634
Citation: Camarillo-Castillo, F., Huggins, T.D., Mondal, S., Reynolds, M.P., Tilley, M., Hays, D. 2021. High-resolution spectral information enables phenotyping of leaf epicuticular wax in wheat. Plant Methods. https://doi.org/10.1186/s13007-021-00759-w.
Interpretive Summary: Wheat is a major staple crop with more than 543 million acres cultivated worldwide. To meet the demand for wheat by 2050, production will need to increase by 60 to 100%, however, globally wheat production is estimated to decrease by 6% for every degree centigrade rise in temperature. Heat and drought annually reduce the grain yield of wheat as well as the yield of other grain crops by about 3-6 %. Epicuticular wax is the outermost layer of leaves which helps to protect the plant against excess solar radiation, minimize water loss from transpiration, and reduce leaf temperature. Currently, the amount of epicuticular wax on the leaves is measured by laboratory methods that chemically digest the leaves to determine the amount of wax. We explored a non-destructive method using wavelengths in the light spectrum to measure the amount of epicuticular wax. The light spectrum is made up of both visible and non-visible wavelengths which have been used to evaluate various plant processes like photosynthetic activity, stress-related senescence, and excess radiation dissipation. The objective of this study was to develop a new, non-destructive method for determining the amount of epicuticular wax covering the leaf surface using a multispectral camera mounted on an unmanned aerial vehicle (UAV) and a handheld spectrophotometer to measure how the light was reflected off leaves. Our results showed this new, non-destructive method is much faster and more accurate than the older chemical laboratory methods. This method can be used by wheat breeders to develop varieties that are resilient to the extreme heat and drought conditions found around the world and in the USA, especially in Texas, Oklahoma, Kansas, and Nebraska.
Technical Abstract: Wheat (Triticum aestivum L.) is a major staple crop with more than 220 million hectares cultivated globally. To maintain the current annual production (600 million tons), development of heat and drought resilient varieties is crucial to meeting the expected increased demand. Even though morphological and physiological plant traits have been the basis for improving grain yield, models for additional improvement have identified high temperature and drought resilience as key factors. Through strategic crossing, the genetically determined physiological traits such as canopy temperature, associated with these key factors can lead to additive genetic effects through selection but others such as epicuticular wax (EW) remain unexplored. Epicuticular wax covers the outer leaf and stem epidermis and sits atop the cutin matrix. It helps plants maintain integrity against UV radiation, biotic and abiotic environmental factors, minimizes transpirational water loss, and reduces leaf temperature. Improved tolerance to heat and drought stress in wheat is associated with a dense layer of EW. However, EW phenotyping currently involves chemical laboratory methods that are time consuming, destructive, and labor-intensive thus limiting its integration into wheat breeding pipelines. Developing an efficient screening method for EW will allow this secondary trait to be more easily selected for as part of wheat breeding programs. To explore the potential of using spectral wavelengths to measure EW we planted two spring wheat cultivar panels, one included 114 landraces and the second 216 landraces, and a third panel included synthetic derived wheat lines (SDLs). The panels were planted in an alpha-lattice design with two replications under non-irrigated conditions. Spectral data for the spring wheat panels and the SDLs were collected with a handheld FieldSpec 4 Hi-Res spectrophotometer that captured reflected light in 2151 continuous bands at a resolution of 3 nanometers. Also, an Aisa KESTREL-10 hyperspectral camera mounted to a Cessna 355 II aircraft was used to capture aerial hyperspectral images of the SDLs. Partial least square modeling identified several spectral regions statistically associated with EW. This generated narrow spectral indices identified as epicuticular wax indices (EWI), of which EWI-13 and EWI-1 predicted 65% and 44% of the variation in EW, respectively, for single-leaf reflectance. The generated normalized difference indices EWI-4 and EWI-9 improved the phenotyping efficiency of EW for field canopy reflectance. EWI-4 and EWI-9 were 70% more efficient for the indirect selection of EW compared to the chemical method. The epicuticular wax regression model (EWM)-7 accurately predicted 71% of the variation for EW load (mg.dm-2) using leaf reflectance. Several spectral linear models and vegetation indices were developed for predicting EW load based on the sensor utilized. EWI-1 and EWI-13 and model EWM-7 are ideal for indirect selection using leaf reflectance, and indices EWI-4 and EWI-9 are ideal for canopy reflectance. Recent advances in hyperspectral cameras and UAV devices have made it possible to successfully incorporate this technology into plant research, thus we recommend using EWI-4 and EWI-9 in wheat breeding programs to select for genotypes with dense EW.