Phenotypic variability in bread wheat root systems at the early vegetative stage

AbstractHypergravity—an evolutionarily novel environment has been exploited to comprehend the response of living organisms including plants in the context of extra-terrestrial applications. Recently, researchers have shown that hypergravity induces desired phenotypic variability in seedlings. In the present study, we tested the utility of hypergravity as a novel tool in inducing reliable phenotype/s for potential terrestrial crop improvement applications. To investigate, bread wheat seeds (UAS-375 genotype) were subjected to hypergravity treatment (10×g for 12, and 24 h), and evaluated for seedling vigor and plant growth parameters in both laboratory and greenhouse conditions. It was also attempted to elucidate the associated biochemical and hormonal changes at different stages of vegetative growth. Resultant data revealed that hypergravity treatment (10×g for 12 h) significantly enhanced root length, root volume, and root biomass in response to hypergravity. The robust seedling growth phenotype may be attributed to increased alpha-amylase and TDH enzyme activities observed in seeds treated with hypergravity. Elevated total chlorophyll content and Rubisco (55 kDa) protein expression across different stages of vegetative growth in response to hypergravity may impart physiological benefits to wheat growth. Further, hypergravity elicited robust endogenous phytohormones dynamics in root signifying altered phenotype/s. Collectively, this study for the first time describes the utility of hypergravity as a novel tool in inducing reliable root phenotype that could be potentially exploited for improving wheat varieties for better water usage management.

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Wheat shovelomics I: A field phenotyping approach for characterising the structure and function of root systems in tillering species

10.1101/280875 ◽

2018 ◽

Cited By ~ 13

Author(s):

Larry M. York ◽

Shaunagh Slack ◽

Malcolm J Bennett ◽

M John Foulkes

Keyword(s):

Genetic Control ◽

Principal Component ◽

Root Systems ◽

Wheat Root ◽

Root Number ◽

Main Shoot ◽

Growth Angle ◽

Nodal Root ◽

Field Phenotyping ◽

And Function

AbstractWheat represents a major crop, yet the current rate of yield improvement is insufficient to meet its projected global food demand. Breeding root systems more efficient for water and nitrogen capture represents a promising avenue for accelerating yield gains. Root crown phenotyping, or shovelomics, relies on excavation of the upper portions of root systems in the field and measuring root properties such as numbers, angles, densities and lengths. We report a new shovelomics method that images the whole wheat root crown, then partitions it into the main shoot and tillers for more intensive phenotyping. Root crowns were phenotyped using the new method from the Rialto × Savannah population consisting of both parents and 94 doubled-haploid lines. For the whole root crown, the main shoot, and tillers, root phenes including nodal root number, growth angle, length, and diameter were measured. Substantial variation and heritability were observed for all phenes. Principal component analysis revealed latent constructs that imply pleiotropic genetic control of several related root phenes. Correlational analysis revealed that nodal root number and growth angle correlate among the whole crown, main shoot, and tillers, indicating shared genetic control among those organs. We conclude that this phenomics approach will be useful for breeding ideotype root systems in tillering species.

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An automatic segmentation method for scanned images of wheat root systems with dark discolourations

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-009-0055-x ◽

2009 ◽

Vol 19 (4) ◽

pp. 679-689 ◽

Cited By ~ 3

Author(s):

Jarosław Gocławski ◽

Joanna Sekulska-Nalewajko ◽

Ewa Gajewska ◽

Marzena Wielanek

Keyword(s):

Plant Root ◽

Automatic Segmentation ◽

Root Systems ◽

Wheat Root ◽

Health State ◽

Segmentation Method ◽

Wheat Roots ◽

Fuzzy C Means Clustering ◽

Scanned Images ◽

Plant Root System

An automatic segmentation method for scanned images of wheat root systems with dark discolourationsThe analysis of plant root system images plays an important role in the diagnosis of plant health state, the detection of possible diseases and growth distortions. This paper describes an initial stage of automatic analysis—the segmentation method for scanned images of Ni-treated wheat roots from hydroponic culture. The main roots of a wheat fibrous system are placed separately in the scanner view area on a high chroma background (blue or red). The first stage of the method includes the transformation of a scanned RGB image into the HCI (Hue-Chroma-Intensity) colour space and then local thresholding of the chroma component to extract a binary root image. Possible chromatic discolourations, different from background colour, are added to the roots from blue or red chroma subcomponent images after thresholding. At the second stage, dark discolourations are extracted by local fuzzy c-means clustering of an HCI intensity image within the binary root mask. Fuzzy clustering is applied in local windows around the series of sample points on roots medial axes (skeleton). The performance of the proposed method is compared with hand-labelled segmentation for a series of several root systems.

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Genotypic variation in durum wheat root systems at different stages of development in a Mediterranean environment

Euphytica ◽

10.1007/bf00025303 ◽

1993 ◽

Vol 66 (3) ◽

pp. 197-206 ◽

Cited By ~ 13

Author(s):

Rosella Motzo ◽

Giovanna Attene ◽

Mauro Deidda

Keyword(s):

Durum Wheat ◽

Genotypic Variation ◽

Root Systems ◽

Wheat Root ◽

Mediterranean Environment ◽

Stages Of Development

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Multi-locus genome-wide association studies reveal novel genomic regions associated with vegetative stage salt tolerance in bread wheat (Triticum aestivum L.)

Genomics ◽

10.1016/j.ygeno.2020.08.006 ◽

2020 ◽

Vol 112 (6) ◽

pp. 4608-4621

Author(s):

Shiksha Chaurasia ◽

Amit Kumar Singh ◽

L.S. Songachan ◽

Axma Dutt Sharma ◽

Rakesh Bhardwaj ◽

...

Keyword(s):

Triticum Aestivum ◽

Salt Tolerance ◽

Bread Wheat ◽

Association Studies ◽

Triticum Aestivum L ◽

Genome Wide Association ◽

Vegetative Stage ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Genomic Regions

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GENOTYPIC AND PHENOTYPIC VARIABILITY, HERITABILITY AND PHENOTYPIC CORRELATION FOR YIELD AND YIELD COMPONENTS IN BREAD WHEAT VARIETIES

Acta Agronomica Hungarica ◽

10.1556/aagr.49.2001.3.4 ◽

2001 ◽

Vol 49 (3) ◽

pp. 237-242 ◽

Cited By ~ 2

Author(s):

K. Z. Korkut ◽

I. BAŞER ◽

O. Bilgin

Keyword(s):

Grain Yield ◽

Plant Height ◽

Bread Wheat ◽

Yield Components ◽

Phenotypic Variability ◽

Kernel Weight ◽

Phenotypic Correlation ◽

Genotypic Variability ◽

Wheat Varieties ◽

Yield And Yield Components

This research was conducted to determine the effect of genetic and phenotypic variability on the yield and yield components of some bread wheat varieties over a period of four years (1995–1998). Experiments were established according to a completely randomised block design with three replicates in the Experimental Field of Tekirda đ Agricultural Faculty, Thrace University. In the present research, genotypic and phenotypic variability, heritability and phenotypic correlation coefficients were estimated for plant height, spike length, number of spikelets per spike, number of spikes per square metre, thousand kernel weight, test weight and grain yield per hectare. The results of data analyses showed that the highest genotypic variability was obtained for per hectare yield, whereas the highest phenotypic variability values were found for plant height, thousand kernel weight and grain yield. For plant height, thousand grain yield and test weight, the broad sense heritability coefficient was found to be the highest, while it was low for spike length, number of spikelets per spike and number of Key words: bread wheat, genotypic variability, phenotypic variability, heritability coefficient, phenotypic correlation, grain yield

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Soil, senescence and exudate utilisation: Characterisation of the Paragon var. spring bread wheat root microbiome

10.1101/2021.02.09.430461 ◽

2021 ◽

Author(s):

Sam Prudence ◽

Jake Newitt ◽

Sarah F. Worsley ◽

Michael C. Macey ◽

J. Colin Murrell ◽

...

Keyword(s):

Bread Wheat ◽

Community Composition ◽

Root Exudates ◽

Wheat Root ◽

Disease Suppression ◽

Soil Conditions ◽

Its2 Region ◽

Rrna Gene ◽

Spring Bread Wheat ◽

Living Plant

AbstractConventional methods of agricultural pest control and crop fertilisation are contributing to a crisis of biodiversity loss, biogeochemical cycle dysregulation, and ecosystem collapse. Thus, we must find ecologically responsible means to control disease and promote crop yields. The root-associated microbiome may contribute to this goal as microbes can aid plants with disease suppression, abiotic stress relief, and nutrient bioavailability. We applied 16S rRNA gene & fungal 18S rRNA gene (ITS2 region) amplicon sequencing to profile the diversity of the bacterial, archaeal & fungal communities associated with the roots of UK elite spring bread wheat variety Triticum aestivum var. Paragon in different soils and developmental stages. This revealed that community composition shifted significantly for all three groups across compartments. This shift was most pronounced for bacteria and fungi, while we observed weaker selection on the ammonia oxidising archaea-dominated archaeal community. Across multiple soil types we found that soil inoculum was a significant driver of endosphere community composition, however several bacterial families were identified as core enriched taxa in all soil conditions. The most abundant of these were Streptomycetaceae and Burkholderiaceae. Moreover, as the plants senesce, both families were reduced in abundance, indicating that input from the living plant was required to maintain their abundance in the endosphere. To understand which microbes are using wheat root exudates in the rhizosphere, root exudates were labelled in a 13CO2 DNA stable isotope probing experiment. This shows that bacterial taxa within the Burkholderiaceae family among other core enriched taxa, such as Pseudomonadaceae, were able to use root exudates but Streptomycetaceae were not. Overall, this work provides a better understanding of the wheat microbiome, including the endosphere community. Understanding crop microbiome formation will contribute to ecologically responsible methods for yield improvement and biocontrol in the future.

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