Characterizing 3D inflorescence architecture in grapevine using X-ray imaging and advanced morphometrics: implications for understanding cluster density

Li, Mao; Klein, Laura L.; Duncan, Keith E; Ni, Jinfu; Chitwood, Daniel H.; Londo, Jason P.; Miller, Allison J.; Topp, Christopher N.

doi:10.1093/jxb/erz394

Cited by 29 publications

(32 citation statements)

References 81 publications

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“…Although the processing and analysis of 3D images for complex biological structures remains nontrivial, automated computational tools providing precise analysis for 3D imaging are becoming increasingly powerful, permitting segmentation, reconstruction, registration, visualization, feature extraction, and modeling. For example, 3D wheat grains have been segmented and measured from images of the wheat panicle (Hughes et al , 2017), and 3D branching topology has been characterized comprehensively in grapevine inflorescences (Li et al , 2017, 2019). Furthermore, software such as C himera (Pettersen et al , 2004) has been used widely for the visualization and analysis of molecular structures, density maps, 3D microscopy, and associated data (Goddard et al , 2017), and topological data analysis tools such as the medial axis (Blum, 1967) have been used extensively for analyzing shape structure and for forming shape descriptors.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive 3D phenotyping reveals continuous morphological variation across genetically diverse sorghum inflorescences

Shao

Dan

et al. 2020

New Phytologist

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Inflorescence architecture in plants is often complex and challenging to quantify, particularly for inflorescences of cereal grasses. Methods for capturing inflorescence architecture and for analyzing the resulting data are limited to a few easily captured parameters that may miss the rich underlying diversity.Here, we apply X-ray computed tomography combined with detailed morphometrics, offering new imaging and computational tools to analyze three-dimensional inflorescence architecture. To show the power of this approach, we focus on the panicles of Sorghum bicolor, which vary extensively in numbers, lengths, and angles of primary branches, as well as the three-dimensional shape, size, and distribution of the seed.We imaged and comprehensively evaluated the panicle morphology of 55 sorghum accessions that represent the five botanical races in the most common classification system of the species, defined by genetic data. We used our data to determine the reliability of the morphological characters for assigning specimens to race and found that seed features were particularly informative.However, the extensive overlap between botanical races in multivariate trait space indicates that the phenotypic range of each group extends well beyond its overall genetic background, indicating unexpectedly weak correlation between morphology, genetic identity, and domestication history.

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Section: Introductionmentioning

confidence: 99%

Comprehensive 3D phenotyping reveals continuous morphological variation across genetically diverse sorghum inflorescences

Shao

Dan

et al. 2020

New Phytologist

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“…This method was also used in nuts and few works are reported, such as the detection of pinhole insect damage in almonds [ 46 ], the segmentation and classification in hazelnuts [ 47 ] and the behaviour study of fourth-instar weevil in pecan nuts [ 48 ]. In grapevine, a recent study aimed to characterize inflorescence architecture using X-rays [ 49 ]. The authors found correlations between 24 morphological traits among 392 samples of 10 wild Vitis species.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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“…Bunch architecture is controlled by environmental and genetic factors (Döring et al 2015 ; Tello and Ibáñez 2017 ). It is a complex trait composed of berry and stalk characteristics (Li et al 2019 ; Richter et al 2019 ; Rist et al 2018 ). Some of these sub-traits are under genetic control as reported for berry size, berry volume and berry weight (Ban et al 2016 ; Houel et al 2015 ; Mejia et al 2007 ; Tello et al 2015 ), berry number (Dry et al 2010 ; Fanizza et al 2005 ) and other rachis sub-traits (Correa et al 2014 ; Marguerit et al 2009 ; Tello et al 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Differential expression of transcription factor- and further growth-related genes correlates with contrasting cluster architecture in Vitis vinifera ‘Pinot Noir’ and Vitis spp. genotypes

et al. 2020

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Grapevine (Vitis vinifera L.) is an economically important crop that needs to comply with high quality standards for fruit, juice and wine production. Intense plant protection is required to avoid fungal damage. Grapevine cultivars with loose cluster architecture enable reducing protective treatments due to their enhanced resilience against fungal infections, such as Botrytis cinerea-induced gray mold. A recent study identified transcription factor gene VvGRF4 as determinant of pedicel length, an important component of cluster architecture, in samples of two loose and two compact quasi-isogenic ‘Pinot Noir’ clones. Here, we extended the analysis to 12 differently clustered ‘Pinot Noir’ clones from five diverse clonal selection programs. Differential gene expression of these clones was studied in three different locations over three seasons. Two phenotypically opposite clones were grown at all three locations and served for standardization. Data were correlated with the phenotypic variation of cluster architecture sub-traits. A set of 14 genes with consistent expression differences between loosely and compactly clustered clones—independent from season and location—was newly identified. These genes have annotations related to cellular growth, cell division and auxin metabolism and include two more transcription factor genes, PRE6 and SEP1-like. The differential expression of VvGRF4 in relation to loose clusters was exclusively found in ‘Pinot Noir’ clones. Gene expression studies were further broadened to phenotypically contrasting F1 individuals of an interspecific cross and OIV reference varieties of loose cluster architecture. This investigation confirmed PRE6 and six growth-related genes to show differential expression related to cluster architecture over genetically divergent backgrounds.

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Characterizing 3D inflorescence architecture in grapevine using X-ray imaging and advanced morphometrics: implications for understanding cluster density

Abstract: Grapevine 3D inflorescence architecture was comprehensively characterized among 10 wild Vitis species to reveal new phenotypic and evolutionary relationships.

Cited by 29 publications

References 81 publications

Comprehensive 3D phenotyping reveals continuous morphological variation across genetically diverse sorghum inflorescences

Comprehensive 3D phenotyping reveals continuous morphological variation across genetically diverse sorghum inflorescences

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

Differential expression of transcription factor- and further growth-related genes correlates with contrasting cluster architecture in Vitis vinifera ‘Pinot Noir’ and Vitis spp. genotypes

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