3D characterization of walnut morphological traits using X-ray computed tomography

Abstract

Background: Walnuts are grown worldwide in temperate areas and producers are facing an increasing demand. In a climate change context, the industry also needs cultivars that provide fruits of quality. This quality includes satisfactory filling ratio, thicker shell, ease of cracking, smooth shell and round-shaped walnut, and larger nut size. These desirable traits have been analysed so far using calipers or micrometers, but it takes a lot of time and requires the destruction of the sample. A challenge to take up is to develop an accurate, fast and non-destructive method for quality-related and morphometric trait measurements of walnuts, that are used to characterize new cultivars or collections in any germplasm management process.

Results: In this study, we develop a method to measure different morphological traits on several walnuts simultaneously such as morphometric traits (nut length, nut face and profile diameters), traits that previously required opening the nut (shell thickness, kernel volume and filling kernel/nut ratio) and traits that previously were difficult to quantify (shell rugosity, nut sphericity, nut surface area and nut shape). These measurements were obtained from reconstructed 3D images acquired by X-ray computed tomography (CT). A workflow was created including several steps: noise elimination, walnut individualization, properties extraction and quantification of the different parts of the fruit. This method was applied to characterize 50 walnuts of a part of the INRAE walnut germplasm collection made of 161 unique accessions, obtained from the 2018 harvest. Our results indicate that 50 walnuts are sufficient to phenotype the fruit quality of one accession using X-ray CT and to find correlations between the morphometric traits. Our imaging workflow is suitable for any walnut size or shape and provides new and more accurate measurements.

Conclusions: The fast and accurate measurement of quantitative traits is of utmost importance to conduct quantitative genetic analyses or cultivar characterization. Our imaging workflow is well adapted for accurate phenotypic characterization of a various range of traits and could be easily applied to other important nut crops.

Keywords: 3D characterization; Germplasm collection; Image analysis; Morphological traits; Walnut; X-ray computed tomography.

Fig. 1

X-ray CT workflow of walnut measurements. a Preparation of walnut samples using floral foam (12 walnuts/batch in average), b Acquisition of X-ray CT images with right images of 2D slices, c 3D reconstruction, d Preprocessing with right image showing noise and artifacts that have to be removed, e Individualization of each walnut of the batch and f XY, YZ, ZX segmentation and labelling of a walnut leading to segmentation of each different part, with the shell in red, the kernel in green and the empty space in blue

Fig. 2

Separation and individualization of walnuts

Fig. 3

Greyscale histogram analysis. a Example of a 2D slice, b the corresponding histogram and c a bar that visualizes an approximate percentage of pixels in each cluster

Fig. 4

Pearson correlation matrix for walnut morphological traits

Fig. 5

Principal Component Analysis using the 161 walnut accessions and the 14 traits quantified using the X-ray CT method. a PCA correlation circle of the 14 variables (dimensions 1 and 2), b Scree plot of the percentage of variances explained by the first ten dimensions, c PCA scatterplot of the 161 accessions (dimensions 1 and 2), d Correlation plot of the 14 variables (dimensions 1 and 2). For a and c plots, color gradient indicates the quality of the representation of each variable given by the squared cosines cos²