Analysis of Shoot Architecture Traits in Edamame Reveals Potential Strategies to Improve Harvest Efficiency

Dhakal, Kshitiz; Zhu, Qian; Zhang, Bo; Li, Mao; Li, Song

doi:10.3389/fpls.2021.614926

Cited by 9 publications

(5 citation statements)

References 68 publications

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“…Lara (2016) identified SNPs associated with SW, sucrose content, and protein content; Zhao et al (2019) reported SNPs associated to soybean seed shape; and Dhakal et al. (2021) identified SNPs associated with shoot architecture traits which can improve edamame harvestability. According to Grant et al.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of genetic diversity and association mapping for seed weight and size in vegetable soybean germplasm

et al. 2021

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Edamame is a vegetable‐typesoybean [Glycine max (L.) Merr.] with large seed size, typically twice that of commodity soybean. Understanding the genetic diversity among large‐seeded germplasm as well as the genetic variation for seed size in the germplasm pool is important for edamame breeding. The objectives of this study were to analyze the genetic diversity of 343 edamame soybean accessions and 36 breeding lines, and to identify quantitative trait loci (QTLs) associated with seed weight (SW), seed volume (VOL), seed length (SL), seed breadth (SB), and seed height (SH) through genome‐wide association studies. We observed two main genetic groups among the 343 accessions and found that the breeding lines were genetically dissimilar to germplasm accessions. Through single‐ and multi‐locus models, a total of two, two, seven, one, and four SNPs were reported to be associated with SW, VOL, SL, SB, and SH located across two, two, five, one, and four chromosomes, respectively. There were three SNPs associated with SL, SB, and/or SH that were not found to be within a previously reported SL, SB, or SH QTL. The SNP ss715587475, positioned at the 24.9‐Mb position on chromosome 4, was located within the gene Glyma04g21680 which was associated with SW in Arabidopsis and may be a candidate gene for SW in edamame soybean. There were four additional SNPs positioned within genes that encode proteins that may relate to plant growth and development in soybean. Identifying and pyramiding favorable alleles for seed size and weight will enhance edamame breeding efforts.

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Section: Introductionmentioning

confidence: 99%

Evaluation of genetic diversity and association mapping for seed weight and size in vegetable soybean germplasm

et al. 2021

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“…However, the application of skeletonisation as part of a morphological analysis pipeline using RGB images or images derived from visible-spectrum imagery is less common. Examples where this has been used include the phenotyping of roots [ 34 ], mapping of branching in edamame [ 35 ], the identification of legumes based on leaf venation [ 30 ], identification of the structure of maize tassels [ 36 ] and branches in roses for the purposes of training a robot to undertake pruning [ 37 ]. Our work is the first example of using skeletonisation from RGB images to map branching in dicotyledonous species.…”

Section: Discussionmentioning

confidence: 99%

Mapping and quantifying unique branching structures in lentil (Lens culinaris Medik.)

Dimech,

Kaur,

Breen

2024

Plant Methods

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Background Lentil (Lens culinaris Medik.) is a globally-significant agricultural crop used to feed millions of people. Lentils have been cultivated in the Australian states of Victoria and South Australia for several decades, but efforts are now being made to expand their cultivation into Western Australia and New South Wales. Plant architecture plays a pivotal role in adaptation, leading to improved and stable yields especially in new expansion regions. Image-based high-throughput phenomics technologies provide opportunities for an improved understanding of plant development, architecture, and trait genetics. This paper describes a novel method for mapping and quantifying individual branch structures on immature glasshouse-grown lentil plants grown using a LemnaTec Scanalyser 3D high-throughput phenomics platform, which collected side-view RGB images at regular intervals under controlled photographic conditions throughout the experiment. A queue and distance-based algorithm that analysed morphological skeletons generated from images of lentil plants was developed in Python. This code was incorporated into an image analysis pipeline using open-source software (PlantCV) to measure the number, angle, and length of individual branches on lentil plants. Results Branching structures could be accurately identified and quantified in immature plants, which is sufficient for calculating early vigour traits, however the accuracy declined as the plants matured. Absolute accuracy for branch counts was 77.9% for plants at 22 days after sowing (DAS), 57.9% at 29 DAS and 51.9% at 36 DAS. Allowing for an error of ± 1 branch, the associated accuracies for the same time periods were 97.6%, 90.8% and 79.2% respectively. Occlusion in more mature plants made the mapping of branches less accurate, but the information collected could still be useful for trait estimation. For branch length calculations, the amount of variance explained by linear mixed-effects models was 82% for geodesic length and 87% for Euclidean branch lengths. Within these models, both the mean geodesic and Euclidean distance measurements of branches were found to be significantly affected by genotype, DAS and their interaction. Two informative metrices were derived from the calculations of branch angle; ‘splay’ is a measure of how far a branch angle deviates from being fully upright whilst ‘angle-difference’ is the difference between the smallest and largest recorded branch angle on each plant. The amount of variance explained by linear mixed-effects models was 38% for splay and 50% for angle difference. These lower R2 values are likely due to the inherent difficulties in measuring these parameters, nevertheless both splay and angle difference were found to be significantly affected by cultivar, DAS and their interaction. When 276 diverse lentil genotypes with varying degrees of salt tolerance were grown in a glasshouse-based experiment where a portion were subjected to a salt treatment, the branching algorithm was able to distinguish between salt-treated and untreated lentil lines based on differences in branch counts. Likewise, the mean geodesic and Euclidean distance measurements of branches were both found to be significantly affected by cultivar, DAS and salt treatment. The amount of variance explained by the linear mixed-effects models was 57.8% for geodesic branch length and 46.5% for Euclidean branch length. Conclusion The methodology enabled the accurate quantification of the number, angle, and length of individual branches on glasshouse-grown lentil plants. This methodology could be applied to other dicotyledonous species.

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“…Vegetable soybean has been extensively used for more than 2000 years in East Asian countries [ 3 ]. In recent years, acceptance of vegetable soybean-based food products has been reported in North and South America, Europe, and Africa [ 4 ]. Vegetable soybean has become a popular food all over the world because of their taste and nutritional value.…”

Section: Introductionmentioning

confidence: 99%

Comparative transcriptome analysis of vegetable soybean grain discloses genes essential for grain quality

Wang,

Bu,

Zhang

et al. 2024

BMC Plant Biol

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Background Vegetable soybean is an important vegetable crop in world. Seed size and soluble sugar content are considered crucial indicators of quality in vegetable soybean, and there is a lack of clarity on the molecular basis of grain quality in vegetable soybean. Results In this context, we performed a comprehensive comparative transcriptome analysis of seeds between a high-sucrose content and large-grain variety (Zhenong 6, ZN6) and a low-sucrose content and small-grain variety (Williams 82, W82) at three developmental stages, i.e. stage R5 (Beginning Seed), stage R6 (Full Seed), and stage R7 (Beginning Maturity). The transcriptome analysis showed that 17,107 and 13,571 differentially expressed genes (DEGs) were identified in ZN6 at R6 (vs. R5) and R7 (vs. R6), respectively, whereas 16,203 and 16,032 were detected in W82. Gene expression pattern and DEGs functional enrichment proposed genotype-specific biological processes during seed development. The genes participating in soluble sugar biosynthesis such as FKGP were overexpressed in ZN6, whereas those responsible for lipid and protein metabolism such as ALDH3 were more enhanced in W82, exhibiting different dry material accumulation between two genotypes. Furthermore, hormone-associated transcriptional factors involved in seed size regulation such as BEH4 were overrepresented in ZN6, exhibiting different seed size regulation processes between two genotypes. Conclusions Herein, we not only discovered the differential expression of genes encoding metabolic enzymes involved in seed composition, but also identified a type of hormone-associated transcriptional factors overexpressed in ZN6, which may regulate seed size and soluble content. This study provides new insights into the underlying causes of differences in the soybean metabolites and appearance, and suggests that genetic data can be used to improve its appearance and textural quality.

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Analysis of Shoot Architecture Traits in Edamame Reveals Potential Strategies to Improve Harvest Efficiency

Cited by 9 publications

References 68 publications

Evaluation of genetic diversity and association mapping for seed weight and size in vegetable soybean germplasm

Evaluation of genetic diversity and association mapping for seed weight and size in vegetable soybean germplasm

Mapping and quantifying unique branching structures in lentil (Lens culinaris Medik.)

Comparative transcriptome analysis of vegetable soybean grain discloses genes essential for grain quality

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