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.

Genome-Wide Association Study Reveals Candidate Genes Involved in Fruit Trait Variation in Persian Walnut (Juglans regia L.)

“…On nuts collected in 2018, all traits were measured using an X-ray CT method on a subsample of 50 nuts randomly selected from the 100 nuts original sample collected. X-ray CT scans and analyses were performed as described by Bernard et al (2020a) . Nut shape and texture traits (nut shape VA3D, nut Feret shape VA3D, nut sphericity, and shell rugosity) were measured using the X-ray CT method on nuts collected in 2018.…”

“…Careful consideration of the phenotyping method is of great importance since the heritability of a given trait may depend on the accuracy of the data ( Furbank and Tester, 2011 ; Burghardt et al, 2017 ). Phenotyping techniques are evolving along with genotyping technologies, and X-ray computed tomography (CT) is one of the imaging techniques applied in food sciences to evaluate internal quality ( Kotwaliwale et al, 2014 ), used notably for studying nut species such as almond, hazelnut, pecan ( Harrison et al, 1993 ; Kim and Schatzki, 2001 ; Khosa and Pasero, 2014 ), and recently walnut ( Bernard et al, 2020a ).…”

A Computationally Efficient Reconstruction Algorithm for Circular Cone-Beam Computed Tomography Using Shallow Neural Networks

“…To assess the performance of the different reconstruction approaches in a segmentation task, we focus here on the segmentation of the shell and kernel of walnuts, based on our experimental CT data. The review [ 59 ] provides an overview of segmentation problems in walnut imaging, and their relevance. For segmenting the 3D volume after the reconstruction, we used a deterministic segmentation algorithm that combines thresholding, the watershed algorithm and prior knowledge of the scanned objects.…”

Introducing Three-Dimensional Scanning for Phenotyping of Olive Fruits Based on an Extensive Germplasm Survey

“…Being non-destructive, 3D scanning enables tracking of the architecture and development of plants through time [ 32 ]. Bernard et al [ 33 ] presented an X-ray computed tomography method for the 3D characterization of walnut morphological traits. Recently, Rist et al [ 34 ] established a fast and high-precision phenotyping pipeline for automated analysis of 3D point clouds and extraction of parameters related to grape bunch architecture.…”