Soil coring at multiple field environments can directly quantify variation in deep root traits to select wheat genotypes for breeding.
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ABSTRACT:
SUBMITTER: Wasson AP
PROVIDER: S-EPMC4223987 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background and Aims:Root distribution has a major influence on soil exploration and nutrient and water acquisition by plants. Soil coring is a well-known way to estimate root distribution. However, identifying an optimal core-sampling strategy is important if one is to strike the right balance between the high cost of making field estimates of root length density (RLD) vs. the need for accurate estimates. Virtual assessment of competing soil-coring strategies, based on three-dimensional (3-D) models of root system architecture (RSA), is a highly effective way to find that balance. Methods:The trajectories of the axile roots of two maize cultivars having contrasting axile root angles were measured in the field using in situ 3-D digitization. Lateral roots were also measured by recording topological and geometrical parameters. Based on the measurement dataset obtained, contrasting 3-D RSA models of individual maize plants were constructed in which the different lateral rooting angles were represented. Using these RSA models the accuracies of various core-sampling strategies for estimating RLD were assessed in a series of virtual experiments. Key Results:Substantial biases occur if a one-core sampling strategy is used to estimate RLD. The biases largely remain for two-core sampling, although a weighting method can reduce these. However, given that identification of an optimal weighting method is difficult in practice, a new sampling strategy is proposed based on an area-weighting algorithm. In this way low deviations in RLD estimation can be achieved by sampling between rows and also by using larger-diameter (7.5 or 10 cm) cores. Conclusions:A 3-D root architecture model based on a detailed measurement dataset provides an ideal platform for assessing a range of soil-coring strategies. The improved two-core sampling strategy, based on an area-weighting algorithm, shows considerable promise as a cost-efficient way of obtaining good quality RLD estimates for maize.
| S-EPMC5906962 | biostudies-literature
Project description:Wheat crop in drought-prone regions of Bangladesh suffers from osmotic stress. The objective of this study was to investigate the response of wheat genotypes with respect to root morphology and root hair traits under polyethylene glycol (PEG)-induced osmotic stress. A total of 22 genotypes of wheat were grown hydroponically and two treatments-0% and 10% PEG-were imposed at 14 days after germination. Plant growth was reduced in terms of plant height, number of live leaves per tiller, shoot dry weight, number of root-bearing phytomers, and roots per tiller. Notably, PEG-induced osmotic stress increased root dry weight per tiller by increasing length of the main axis and lateral roots, as well as the diameter and density of both lateral roots and root hairs of the individual roots. A biplot was drawn after a principal component analysis, taking three less-affected (high-yielding genotypes) and three highly affected (low-yielding genotypes and landrace) genotypes under 10% PEG stress, compared to control. Principal component 1 separated PEG-treated wheat genotypes from control-treated genotypes, with a high and positive coefficient for the density of lateral roots and root hairs, length and diameter of the main axis, and first-order lateral roots and leaf injury scores, indicating that these traits are associated with osmotic stress tolerance. Principal component 2 separated high-yielding and tolerant wheat genotypes from low-yielding and susceptible genotypes, with a high coefficient for root dry weight, density of root hairs and second-order lateral roots, length of the main axis, and first-order lateral roots. An increase in root dry weight in PEG-stress-tolerant wheat genotypes was achieved through an increase in length and diameter of the main axis and lateral roots. The information derived from this research could be exploited for identifying osmotic stress-tolerant QTL and for developing abiotic-tolerant cultivars of wheat.
| S-EPMC8224394 | biostudies-literature
Project description:Plant-soil biological interactions are increasingly recognized as a key feature of agroecosystems, promoting both crop and soil health. However, the effectiveness of plant-soil synergies is likely modulated by both root system characteristics and soil management impacts on soil biological communities. To successfully manage for plant-soil interactions, we need to better understand how crops respond to changes in soil management, especially in terms of belowground investment. Specifically, crop genotypes that exhibit reduced plasticity in root growth and investment may not be able to take full advantage of changes in soil biological activity associated with soil health promoting practices. We hypothesized that genotypes with greater belowground investment respond more, in terms of plant growth and crop nitrogen (N) uptake, to compost and earthworm additions, agronomic factors commonly associated with soil health. We evaluated four spring wheat (Triticum aestivum) genotypes with distinct breeding and environmental histories, and one progenitor of wheat (Aegilops tauschii) under low soil fertility conditions in the greenhouse for differences in belowground root biomass and architecture. We then determined how these belowground traits influenced genotype response to additions of compost and earthworms. Measurements included plant growth, biomass, grain yield, root characteristics, plant N uptake, and soil N. Overall, in unamended soils, genotypes differed in above and belowground phenotypic traits. In general, Ae. tauschii had three times greater root: shoot (R:S) ratio, root length, and root biomass relative to wheat genotypes. We found that genotypes with higher R:S ratios responded more positively to compost additions compared to those with lower R:S ratios, particularly in terms of plant aboveground biomass, N uptake and soil N-cycling, and also exhibited greater plasticity in root morphology. Consequently, while higher R:S genotypes had relatively poorer yields in unamended soils, they outperformed lower R:S genotypes in total seed weight under compost treatments. Our findings suggest that genotypes with greater belowground investment may be better able to take advantage of soil health promoting practices, such as the use of organic amendments. These results highlight the need to consider soil management practices (and associated biological communities) in parallel with root phenotypic plasticity when evaluating wheat lines for improvements in plant-soil synergies.
| S-EPMC6057726 | biostudies-literature
Project description:Using a field to lab approach, mature deep-rooting traits in wheat were correlated to root phenotypes measured on young plants from controlled conditions. Mature deep-rooting root traits of 20 wheat genotypes at maturity were established via coring in three field trials across 2 years. Field traits were correlated to phenotypes expressed by the 20 genotypes after growth in four commonly used lab screens: (i) soil tubes for root emergence, elongation, length, and branching at four ages to 34 days after sowing (DAS); (ii) paper pouches 7 DAS and (iii) agar chambers for primary root (PR) number and angles at 8 DAS; and (iv) soil baskets for PR and nodal root (NR) number and angle at 42 DAS. Correlations between lab and field root traits (r2=0.45-0.73) were highly inconsistent, with many traits uncorrelated and no one lab phenotype correlating similarly across three field experiments. Phenotypes most positively associated with deep field roots were: longest PR and NR axiles from the soil tube screen at 20 DAS; and narrow PR angle and wide NR angle from soil baskets at 42 DAS. Paper and agar PR angles were positively and significantly correlated to each other, but only wide outer PRs in the paper screen correlated positively to shallower field root traits. NR phenotypes in soil baskets were not predicted by PR phenotypes in any screen, suggesting independent developmental controls and value in measuring both root types in lab screens. Strong temporal and edaphic effects on mature root traits, and a lack of understanding of root trait changes during plant development, are major challenges in creating controlled-environment root screens for mature root traits in the field.
| S-EPMC7410186 | biostudies-literature
Project description:Root system characteristics determine soil space exploration and resource acquisition, and these characteristics include competitive traits that increase individual fitness but reduce population performance. We hypothesize that crop breeding for increased yield is often a form of "group selection" that reduces such "selfish" traits to increase population yield. To study trends in root architecture resulting from plant breeding and test the hypothesis that increased yields result in part from group selection on root traits, we investigated root growth and branching behavior in a historical sequence of wheat (Triticum aestivum) cultivars that have been widely grown in northwestern China. Plants were grown in gel-filled chambers to examine growth angles, numbers, and lengths of seminal roots, and in soil-filled chambers under eight soil resource levels for fractal analysis of root system architecture. Yield in field was evaluated at standard and low planting densities. Newer cultivars produced higher yields than older ones only at the higher sowing density, showing that increased yield results from changes in competitive behavior. Seminal root number and growth angles were negatively correlated with yield, while primary seminal root length was positively correlated with yield. Roots of higher-yielding modern varieties were simpler and less branched, grew deeper but spread less laterally than modern varieties. The fractal dimension of root branching was negatively correlated with the yield of cultivars at all resource levels. Root:shoot ratio was negatively correlated with yield under high soil resource levels. The results are consistent with the hypothesis that the success of wheat breeding for higher yields over past 100 years in northwestern China has been in part due to unconscious group selection on root traits, resulting in smaller, less branched, and deeper roots, suggesting a direction for further increases in crop yield in the future.
| S-EPMC6439874 | biostudies-literature
Project description:To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes (SYN) were crossed to 20 spring bread wheat (BW) cultivars at the International Wheat and Maize Improvement Center. Modified single seed descent was used to develop 97 populations with 50 individuals per population using first back-cross, biparental, and three-way crosses. Individuals from each cross were selected for short stature, early heading, flowering and maturity, minimal lodging, and free threshing. Yield trials were conducted under irrigated, drought, and heat-stress conditions from 2011 to 2014 in Ciudad Obregon, Mexico. Genomic estimated breeding values (GEBVs) of parents and synthetic derived lines (SDLs) were estimated using a genomic best linear unbiased prediction (GBLUP) model with markers in each trial. In each environment, there were SDLs that had higher GEBVs than their recurrent BW parent for yield. The GEBVs of BW parents for yield ranged from -0.32 in heat to 1.40 in irrigated trials. The range of the SYN parent GEBVs for yield was from -2.69 in the irrigated to 0.26 in the heat trials and were mostly negative across environments. The contribution of the SYN parents to improved grain yield of the SDLs was highest under heat stress, with an average GEBV for the top 10% of the SDLs of 0.55 while the weighted average GEBV of their corresponding recurrent BW parents was 0.26. Using the pedigree-based model, the accuracy of genomic prediction for yield was 0.42, 0.43, and 0.49 in the drought, heat and irrigated trials, respectively, while for the marker-based model these values were 0.43, 0.44, and 0.55. The SYN parents introduced novel diversity into the wheat gene pool. Higher GEBVs of progenies were due to introgression and retention of some positive alleles from SYN parents.
| S-EPMC5033409 | biostudies-literature
Project description:Background:Plant breeding requires numerous generations to be cycled and evaluated before an improved cultivar is released. This lengthy process is required to introduce and test multiple traits of interest. However, a technology for rapid generation advance named 'speed breeding' was successfully deployed in bread wheat (Triticum aestivum L.) to achieve six generations per year while imposing phenotypic selection for foliar disease resistance and grain dormancy. Here, for the first time the deployment of this methodology is presented in durum wheat (Triticum durum Desf.) by integrating selection for key traits, including above and below ground traits on the same set of plants. This involved phenotyping for seminal root angle (RA), seminal root number (RN), tolerance to crown rot (CR), resistance to leaf rust (LR) and plant height (PH). In durum wheat, these traits are desirable in environments where yield is limited by in-season rainfall with the occurrence of CR and epidemics of LR. To evaluate this multi-trait screening approach, we applied selection to a large segregating F2 population (n?=?1000) derived from a bi-parental cross (Outrob4/Caparoi). A weighted selection index (SI) was developed and applied. The gain for each trait was determined by evaluating F3 progeny derived from 100 'selected' and 100 'unselected' F2 individuals. Results:Transgressive segregation was observed for all assayed traits in the Outrob4/Caparoi F2 population. Application of the SI successfully shifted the population mean for four traits, as determined by a significant mean difference between 'selected' and 'unselected' F3 families for CR tolerance, LR resistance, RA and RN. No significant shift for PH was observed. Conclusions:The novel multi-trait phenotyping method presents a useful tool for rapid selection of early filial generations or for the characterization of fixed lines out-of-season. Further, it offers efficient use of resources by assaying multiple traits on the same set of plants. Results suggest that when performed in parallel with speed breeding in early generations, selection will enrich recombinant inbred lines with desirable alleles and will reduce the length and number of years required to combine these traits in elite breeding populations and therefore cultivars.
| S-EPMC5950182 | biostudies-literature
Project description:Phenotyping, via remote and proximal sensing techniques, of the agronomic and physiological traits associated with yield potential and drought adaptation could contribute to improvements in breeding programs. In the present study, 384 genotypes of wheat (Triticum aestivum L.) were tested under fully irrigated (FI) and water stress (WS) conditions. The following traits were evaluated and assessed via spectral reflectance: Grain yield (GY), spikes per square meter (SM2), kernels per spike (KPS), thousand-kernel weight (TKW), chlorophyll content (SPAD), stem water soluble carbohydrate concentration and content (WSC and WSCC, respectively), carbon isotope discrimination (?13C), and leaf area index (LAI). The performances of spectral reflectance indices (SRIs), four regression algorithms (PCR, PLSR, ridge regression RR, and SVR), and three classification methods (PCA-LDA, PLS-DA, and kNN) were evaluated for the prediction of each trait. For the classification approaches, two classes were established for each trait: The lower 80% of the trait variability range (Class 1) and the remaining 20% (Class 2 or elite genotypes). Both the SRIs and regression methods performed better when data from FI and WS were combined. The traits that were best estimated by SRIs and regression methods were GY and ?13C. For most traits and conditions, the estimations provided by RR and SVR were the same, or better than, those provided by the SRIs. PLS-DA showed the best performance among the categorical methods and, unlike the SRI and regression models, most traits were relatively well-classified within a specific hydric condition (FI or WS), proving that classification approach is an effective tool to be explored in future studies related to genotype selection.
| S-EPMC5343032 | biostudies-other
Project description:Ensuring future food security for a growing population while climate change and urban sprawl put pressure on agricultural land will require sustainable intensification of current farming practices. For the crop breeder this means producing higher crop yields with less resources due to greater environmental stresses. While easy gains in crop yield have been made mostly "above ground," little progress has been made "below ground"; and yet it is these root system traits that can improve productivity and resistance to drought stress. Wheat pre-breeders use soil coring and core-break counts to phenotype root architecture traits, with data collected on rooting density for hundreds of genotypes in small increments of depth. The measured densities are both large datasets and highly variable even within the same genotype, hence, any rigorous, comprehensive statistical analysis of such complex field data would be technically challenging. Traditionally, most attributes of the field data are therefore discarded in favor of simple numerical summary descriptors which retain much of the high variability exhibited by the raw data. This poses practical challenges: although plant scientists have established that root traits do drive resource capture in crops, traits that are more randomly (rather than genetically) determined are difficult to breed for. In this paper we develop a hierarchical nonlinear mixed modeling approach that utilizes the complete field data for wheat genotypes to fit, under the Bayesian paradigm, an "idealized" relative intensity function for the root distribution over depth. Our approach was used to determine heritability: how much of the variation between field samples was purely random vs. being mechanistically driven by the plant genetics? Based on the genotypic intensity functions, the overall heritability estimate was 0.62 (95% Bayesian confidence interval was 0.52 to 0.71). Despite root count profiles that were statistically very noisy, our approach led to denoised profiles which exhibited rigorously discernible phenotypic traits. Profile-specific traits could be representative of a genotype, and thus, used as a quantitative tool to associate phenotypic traits with specific genotypes. This would allow breeders to select for whole root system distributions appropriate for sustainable intensification, and inform policy for mitigating crop yield risk and food insecurity.
| S-EPMC5332416 | biostudies-literature
Project description:Root traits influence the amount of water and nutrient absorption, and are important for maintaining crop yield under drought conditions. The objectives of this research were to characterize variability of root traits among spring wheat genotypes and determine whether root traits are related to shoot traits (plant height, tiller number per plant, shoot dry weight, and coleoptile length), regions of origin, and market classes. Plants were grown in 150-cm columns for 61 days in a greenhouse under optimal growth conditions. Rooting depth, root dry weight, root: shoot ratio, and shoot traits were determined for 297 genotypes of the germplasm, Cultivated Wheat Collection (CWC). The remaining root traits such as total root length and surface area were measured for a subset of 30 genotypes selected based on rooting depth. Significant genetic variability was observed for root traits among spring wheat genotypes in CWC germplasm or its subset. Genotypes Sonora and Currawa were ranked high, and genotype Vandal was ranked low for most root traits. A positive relationship (R2 ≥ 0.35) was found between root and shoot dry weights within the CWC germplasm and between total root surface area and tiller number; total root surface area and shoot dry weight; and total root length and coleoptile length within the subset. No correlations were found between plant height and most root traits within the CWC germplasm or its subset. Region of origin had significant impact on rooting depth in the CWC germplasm. Wheat genotypes collected from Australia, Mediterranean, and west Asia had greater rooting depth than those from south Asia, Latin America, Mexico, and Canada. Soft wheat had greater rooting depth than hard wheat in the CWC germplasm. The genetic variability identified in this research for root traits can be exploited to improve drought tolerance and/or resource capture in wheat.
| S-EPMC4063797 | biostudies-literature