Abstract

Background: Wheat is one of the most important staple source in the world for human consumption, animal feed and industrial raw materials. To deal with the global and increasing population demand, enhancing crop yield by increasing the fnal weight of individual grain is considered as a feasible solution. Morphometric analysis of wheat grain plays an important role in tracking and understanding developmental processes by assessing potential impacts on grains properties, size and shape that are major determinants of final grain weight. X ray micro computed tomo-graphy (μCT) is a very powerful non invasive imaging tool that is able to acquire 3D images of an individual grain, enabling to assess the morphology of wheat grain and of its diferent compartments. Our objective is to quantify changes of morphology during growth stages of wheat grain from 3D μCT images.

Methods: 3D μCT images of wheat grains were acquired at various development stages ranging from 60 to 310 degree days after anthesis. We developed robust methods for the identifcation of outer and inner tissues within the grains, and the extraction of morphometric features using 3D μCT images. We also developed a specifc workfow for the quantifcation of the shape of the grain crease.

Results: The diferent compartments of the grain could be semi automatically segmented. Variations of volumes of the compartments adequately describe the diferent stages of grain developments. The evolution of voids within wheat grain refects lysis of outer tissues and growth of inner tissues. The crease shape could be quantifed for each grain and averaged for each stage of development, helping us understand the genesis of the grain shape.

Conclusion: This work shows that μCT acquisitions and image processing methodologies are powerful tools to extract morphometric parameters of developing wheat grain. The results of quantitative analysis revealed remarkable features of wheat grain growth. Further work will focus on building a computational model of wheat grain growth based on real 3D imaging data.

Keywords: X ray micro computed tomography, μCT, Image analysis, Wheat, Triticum aestivum (L.), Grain development

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