Abstract
Progress in high-throughput tools has enabled plant breeders to increase the rate of genetic gain through multidimensional assessment of previously intractable traits in a fast and nondestructive manner. This study investigates the potential use of spectral reflectance indices (SRIs; 15 vegetation-SRIs; 15 water-SRIs) as alternative selection tools for destructively measured traits in wheat breeding programs. The genetic variability, heritability (h2), genetic gain (GG), and expected genetic advances (GA) of these indices were compared with those of destructively measured traits in 43 F7-8 recombinant inbred lines (RILs) grown under limited water conditions. The performance of SRIs to estimate the destructively measured traits directly was also evaluated using the partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) models. Most vegetation-SRIs exhibited high genotypic variation, similar to the measured traits, and phenotypic correlations with these traits, compared with the water-SRIs. Most vegetation-SRIs presented comparable values for h2 (>60%) and GG (>20%) as intermediate traits, while about half of water-SRIs exhibited a high h2 (>60%), but low GG (<20%). Principle component analysis revealed that most vegetation-SRIs and seven of 15 water-SRIs were grouped together in a positive direction, had a moderate to strong relationship with measured traits, and could identify the drought-tolerant parent Sakha 93 and several RILs. The PLSR model based on all SRIs as a single index showed moderate to high R2 in calibration (0.53–0.75) and validation (0.46–0.72) datasets, with strong relationships between observed and predicted values of measured traits. The SMLR models identified four and three SRIs from vegetation-SRIs and water-SRIs, respectively, to explain 63–86% of the total variability in measured traits among genotypes. These results demonstrated that vegetation-SRIs can be used individually or combined with water-SRIs as alternative breeding tools to increase genetic gains and selection accuracy in spring wheat breeding.
Highlights
The combination of water shortage and global climate change will increase the occurrence of drought events in arid and semiarid regions, which will become a critical issue for the sustainability of field crop production in such regions
The main objectives of this study were: to (1) evaluate the potential use of different spectral reflectance indices (SRIs) as alternative indirect breeding tools for breeding purposes under limited water irrigation conditions based on their genetic variability, heritability, genetic gain, and expected genetic advances in advanced breeding wheat lines; (2) evaluate the performance of different partial least squares regression (PLSR) models based on all SRIs as a single index for the accurate estimation of measured traits; and (3) select the most influential SRIs that explain most variability in each destructively measured trait across genotypes via a stepwise multiple linear regression analysis
The only exception was for the red edge inflection point (REIP) and structure insensitive pigment index (SIPI) among the vegetation-SRIs and the normalized difference moisture index-1 (NDMI-2), normalized difference water index-1240 (NDWI1240), normalized difference water index-D (NDWI-D), shortwave infrared water index (SWWI), normalized difference spectral index for relative water content (NRWC), dry matter content index-D (DMCI-D), and ligno-cellulose absorption index (LCA) among the water-SRIs, for which the genotypic main effect was non-significant for theses indices (Table 2)
Summary
The combination of water shortage and global climate change will increase the occurrence of drought events in arid and semiarid regions, which will become a critical issue for the sustainability of field crop production in such regions. Improving agronomic practices and cultivation of drought-tolerant cultivars are the most feasible strategies to maintain the sustainability of crop production under limited water supply conditions. Hyperspectral spectroradiometers contain sensors that can detect small changes in biophysical and biochemical characteristics of the canopy by monitoring changes in canopy spectral signatures at the visible (VIS), near-infrared (NIR), and shortwave-infrared (SWIR) parts of the spectrum They represent an important phenotyping tool in breeding programs and are used to accelerate the development of genotypes for different environmental stress conditions by performing fast, in-depth phenotypic assessments of various phenological plant traits in multiple genotypes [7,8,9,10]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
