High‐throughput Phenotyping and Genomic Selection: The Frontiers of Crop Breeding Converge^F

Abstract

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield.

Development of a field-based high-throughput mobile phenotyping platform

“…Field use of NIRS has potential for rapid, non-destructive evaluation of biomass accumulation, radiation use efficiency, drought and nutrient use efficiency screening, and assessment of yield performance under stress conditions (Araus and Cairns 2013;Cabrera Bosquet et al 2012). The advantages of NIRS include low cost, rapidity, high precision, and repeatability (Cabrera Bosquet et al 2012).…”

“…Most spectral and imaging technologies currently used for phenotyping utilize electromagnetic radiation within visible and infrared bands transmitted or reflected from the crop (Araus and Cairns 2013). Incoming electromagnetic radiation in the visible range, between 400-700 nm, is absorbed by crop leaves and wavelengths between 700-1100 nm, referred to as near infrared, and wavelengths up to 2500 nm, referred to as shortwave infrared, are strongly reflected (Cabrera Bosquet et al 2012;Furbank and Tester 2011). Spectral and imaging techniques feasible for phenotyping can be grouped into three categories: visible to near infrared spectroradiometry, infrared thermometry and thermal imaging, and conventional digital photography (Araus and Cairns 2013).…”

“…These techniques allow measurement of physical and chemical characteristics from plots such as canopy architecture, canopy temperature, water status, and nitrogen concentration (Montes, Melchinger, and Reif 2007a). Furthermore, measured spectral information, used to create vegetation indices (VIs) which are ratios or differences between spectral reflectance data of specific wavelengths, are related to different plant characteristics (Cabrera Bosquet et al 2012).…”

“…To improve complex traits through genomic selection, phenotypic data from thousands of plant varieties grown in replications under various environmental conditions is necessary, and measurements must be repeatedly taken throughout plant development in order to observe the interaction between the expression of plant traits and the environment (Cabrera Bosquet et al 2012;Montes, Melchinger, and Reif 2007b).…”

Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum

“…Plant breeders are able to use phenotypic data to link plant phenotype with genotype and environmental conditions early in growth to evaluate crop status and accelerate an understanding of breeding processes for large numbers of plants. Developments in automation, imaging and software solutions have enabled high-throughput phenotyping studies in controlled environments, such as greenhouses and laboratories, (Cobb et al 2013;Cabrera-Bosquet et al 2012), which utilize stationary measurement devices to either manually or automatically phenotype individual plants. Indoor phenotyping is effective for individual plants produced in a controlled environment, but field-based phenotyping provides an expanded realistic set of phenotypic data from crops grown in actual environmental conditions (Fuglie and Heisey 2007;White et al 2012).…”