Dataset Information

Root Architecture and Functional Traits of Spring Wheat Under Contrasting Water Regimes.

ABSTRACT: Wheat roots are known to play an important role in the yield performance under water-limited (WL) conditions. Three consecutive year trials (2015, 2016, and 2017) were conducted in a glasshouse in 160 cm length tubes on a set of spring wheat (Triticum aestivum L.) genotypes under contrasting water regimes (1) to assess genotypic variability in root weight density (RWD) distribution in the soil profile, biomass partitioning, and total water used; and (2) to determine the oxygen and hydrogen isotopic signatures of plant and soil water in order to evaluate the contribution of shallow and deep soil water to plant water uptake and the evaporative enrichment of these isotopes in the leaf as a surrogate for plant transpiration. In the 2015 trial under well-watered (WW) conditions, the aerial biomass (AB) was not significantly different among 15 wheat genotypes, while the total root biomass and the RWD distribution in the soil profile were significantly different. In the 2016 and 2017 trials, a subset of five genotypes from the 2015 trial was grown under WW and WL regimes. The water deficit significantly reduced AB only in 2016. The water regimes did not significantly affect the root biomass and root biomass distribution in the soil depths for both the 2016 and 2017 trials. The study results highlighted that under a WL regime, the production of thinner roots with low biomass is more beneficial for increasing the water uptake than the production of large thick roots. The models applied to estimate the relative contribution of the plant's primary water sources (shallow or deep soil water) showed large interindividual variability in soil, and plant water isotopic composition resulted in large uncertainties in the model estimates. On the other side, the combined information of root architecture and the leaf stable isotope signatures could explain plant water status.

SUBMITTER: Brunel-Saldias N

PROVIDER: S-EPMC7686047 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Root Architecture and Functional Traits of Spring Wheat Under Contrasting Water Regimes.

Brunel-Saldias Nidia N Ferrio Juan Pedro JP Elazab Abdelhalim A Orellana Massiel M Del Pozo Alejandro A

Frontiers in plant science 20201111

Wheat roots are known to play an important role in the yield performance under water-limited (WL) conditions. Three consecutive year trials (2015, 2016, and 2017) were conducted in a glasshouse in 160 cm length tubes on a set of spring wheat (<i>Triticum aestivum</i> L.) genotypes under contrasting water regimes (1) to assess genotypic variability in root weight density (RWD) distribution in the soil profile, biomass partitioning, and total water used; and (2) to determine the oxygen and hydroge ...[more]

PMID: 33262777

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Project description:The incorporation of nondestructive and cost-effective tools in genetic drought studies in combination with reliable indirect screening criteria that exhibit high heritability and genetic correlations will be critical for addressing the water deficit challenges of the agricultural sector under arid conditions and ensuring the success of genotype development. In this study, the proximal spectral reflectance data were exploited to assess three destructive agronomic parameters [dry weight (DW) and water content (WC) of the aboveground biomass and grain yield (GY)] in 30 recombinant F7 and F8 inbred lines (RILs) growing under full (FL) and limited (LM) irrigation regimes. The utility of different groups of spectral reflectance indices (SRIs) as an indirect assessment tool was tested based on heritability and genetic correlations. The performance of the SRIs and different models of partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) in estimating the destructive parameters was considered. Generally, all groups of SRIs, as well as different models of PLSR and SMLR, generated better estimations for destructive parameters under LM and combined FL+LM than under FL. Even though most of the SRIs exhibited a low association with destructive parameters under FL, they exhibited moderate to high genetic correlations and also had high heritability. The SRIs based on near-infrared (NIR)/visible (VIS) and NIR/NIR, especially those developed in this study, spectral band intervals extracted within VIS, red edge, and NIR spectral range, or individual effective wavelengths relevant to green, red, red edge, and middle NIR spectral region, were found to be more effective in estimating the destructive parameters under all conditions. Five models of SMLR and PLSR for each condition explained most of the variation in the three destructive parameters among genotypes. These models explained 42% to 46%, 19% to 30%, and 39% to 46% of the variation in DW, WC, and GY among genotypes under FL, 69% to 72%, 59% to 61%, and 77% to 81% under LM, and 71% to 75%, 61% to 71%, and 74% to 78% under FL+LM, respectively. Overall, these results confirmed that application of hyperspectral reflectance sensing in breeding programs is not only important for evaluating a sufficient number of genotypes in an expeditious and cost-effective manner but also could be exploited to develop indirect breeding traits that aid in accelerating the development of genotypes for application under adverse environmental conditions.

Dataset Information

Root Architecture and Functional Traits of Spring Wheat Under Contrasting Water Regimes.

Publications

Root Architecture and Functional Traits of Spring Wheat Under Contrasting Water Regimes.

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