AI Article Synopsis

  • Spike shape and characteristics are crucial for the productivity and classification of cultivated hexaploid wheat species.
  • A new method utilizing 2D image analysis for measuring these traits has been developed, providing more precision than traditional manual measurements.
  • The study confirmed strong correlations between image-based traits and manual measurements, demonstrating that digital phenotyping can effectively classify wheat types and identify significant variations among species.

Article Abstract

The spike shape and morphometric characteristics are among the key characteristics of cultivated cereals, being associated with their productivity. These traits are often used for the plant taxonomy and authenticity of hexaploid wheat species. Manual measurement of spike characteristics is tedious and not precise. Recently, the authors of this study developed a method for wheat spike morphometry utilizing 2D image analysis. Here, this method is applied to study variations in spike size and shape for 190 plants of seven hexaploid (2 = 6 = 42) species and one artificial amphidiploid of wheat. Five manually estimated spike traits and 26 traits obtained from digital image analysis were analyzed. Image-based traits describe the characteristics of the base, center and apex of the spike and common parameters (circularity, roundness, perimeter, etc.). Estimates of similar traits by manual measurement and image analysis were shown to be highly correlated, suggesting the practical importance of digital spike phenotyping. The utility of spike traits for classification into types (spelt, normal and compact) and species or amphidiploid is shown. It is also demonstrated that the estimates obtained made it possible to identify the spike characteristics differing significantly between species or between accessions within the same species. The present work suggests the usefulness of wheat spike shape analysis using an approach based on characteristics obtained by digital image analysis.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11478967PMC
http://dx.doi.org/10.3390/plants13192736DOI Listing

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