Morphometry of the Wheat Spike by Analyzing 2D Images

Genaev, Mikhail A.; Komyshev, Evgenii G.; Smirnov, Alexander; Kruchinina, Yuliya; Гончаров, Н. П.; Afonnikov, D. A.

doi:10.20944/preprints201906.0105.v1

Cited by 13 publications

(11 citation statements)

References 22 publications

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“…The spike shape has been confirmed by calculation of Flaksberger's formula for spike density, D = 10(A -1)/B, where (A -1) is the number of spikelets per spike excluding the apical spikelet, and B is the length of the spike rachis in cm [30]. Calculated values for D displayed a high correlation with visual assessment of spike shape (see [31]).…”

Section: Plant Materials and Growth Conditionsmentioning

confidence: 84%

Genetic variability of spelt factor gene in Triticum and Aegilops species

et al. 2020

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Background Threshability, rachis fragility and spike shape are critical traits for the domestication and evolution of wheat, determining the crop yield and efficiency of the harvest. Spelt factor gene Q controls a wide range of domestication-related traits in polyploid wheats, including those mentioned above. The main goal of the present study was to characterise the Q gene for uninvestigated accessions of wheats, including four endemics, and Aegilops accessions, and to analyze the species evolution based on differences in Q gene sequences. Results We have studied the spike morphology for 15 accessions of wheat species, including four endemics, namely Triticum macha, T. tibetanum, T. aestivum ssp. petropavlovskyi and T. spelta ssp. yunnanense, and 24 Aegilops accessions, which are donors of B and D genomes for polyploid wheat. The Q-5A, q-5D and q-5S genes were investigated, and a novel allele of the Q-5A gene was found in accessions of T. tibetanum (KU510 and KU515). This allele was similar to the Q allele of T. aestivum cv. Chinese Spring but had an insertion 161 bp in length within exon 5. This insertion led to a frameshift and premature stop codon formation. Thus, the T. tibetanum have spelt spikes, which is probably determined by the gene Tg, rather than Q. We determined the variability within the q-5D genes among hexaploid wheat and their D genome donor Aegilops tauschii. Moreover, we studied the accessions C21–5129, KU-2074, and K-1100 of Ae. tauschii ssp. strangulata, which could be involved in the origin of hexaploid wheats. Conclusions The variability and phylogenetic relationships of the Q gene sequences studied allowed us to clarify the relationships between species of the genus Triticum and to predict the donor of the D genome among the Ae. tauschii accessions. Ae. tauschii ssp. strangulata accessions C21–5129, KU-2074 and K-1100 are the most interesting among the analysed accessions, since their partial sequence of q-5D is identical to the q-5D of T. aestivum cv. Chinese Spring. This result indicates that the donor is Ae. tauschii ssp. strangulata but not Ae. tauschii ssp. tauschii. Our analysis allowed us to clarify the phylogenetic relationships in the genus Triticum.

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Section: Plant Materials and Growth Conditionsmentioning

confidence: 84%

Genetic variability of spelt factor gene in Triticum and Aegilops species

et al. 2020

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“…Evaluation of spikes quantitative characteristics. WERecognizer (Genaev et al, 2019) was used to estimate spikes quantitative characteristics based on image analysis. This program describes a wheat spike by geometric model of two quadrangles based on image analysis (Fig.…”

Section: Methodsmentioning

confidence: 99%

Automatic morphology phenotyping of tetra- and hexaploid wheat spike using computer vision methods

et al. 2021

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Intraspecific classification of cultivated plants is necessary for the conservation of biological diversity, study of their origin and their phylogeny. The modern cultivated wheat species originated from three wild diploid ancestors as a result of several rounds of genome doubling and are represented by di-, tetra- and hexaploid species. The identification of wheat ploidy level is one of the main stages of their taxonomy. Such classification is possible based on visual analysis of the wheat spike traits. The aim of this study is to investigate the morphological characteristics of spikes for hexa- and tetraploid wheat species based on the method of high-performance phenotyping. Phenotyping of the quantitative characteristics of the spike of 17 wheat species (595 plants, 3348 images), including eight tetraploids (Triticum aethiopicum, T. dicoccoides, T. dicoccum, T. durum, T. militinae, T. polonicum, T. timopheevii, and T. turgidum) and nine hexaploids (T. compactum, T. aestivum, i:ANK-23 (near-isogenic line of T. aestivum cv. Novosibirskaya 67), T. antiquorum, T. spelta (including cv. Rother Sommer Kolben), T. petropavlovskyi, T. yunnanense, T. macha, T. sphaerococcum, and T. vavilovii), was performed. Wheat spike morphology was described on the basis of nine quantitative traits including shape, size and awns area of the spike. The traits were obtained as a result of image analysis using the WERecognizer program. A cluster analysis of plants according to the characteristics of the spike shape and comparison of their distributions in tetraploid and hexaploid species showed a higher variability of traits in hexaploid species compared to tetraploid ones. At the same time, the species themselves form two clusters in the visual characteristics of the spike. One type is predominantly hexaploid species (with the exception of one tetraploid, T. dicoccoides). The other group includes tetraploid ones (with the exception of three hexaploid ones, T. compactum, T. antiquorum, T. sphaerococcum, and i:ANK-23). Thus, it has been shown that the morphological characteristics of spikes for hexaploid and tetraploid wheat species, obtained on the basis of computer analysis of images, include differences, which are further used to develop methods for plant classifications by ploidy level and their species in an automatic mode.

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“…Likewise, Makanza et al [ 118 ] designed a simple low-cost RGB imaging method to quantitatively measure seed size, number, and weight of intact maize cobs in the field. Most recently, Genaev et al [ 113 ] described a simple RGB imaging setup which can precisely quantify morphological features such as spike shape and awnedness of the wheat spike. This work suggests that the deployment of HTP methods can help curators digitally characterize a wide range of traits related to the inflorescence and fruit, and once incorporated into genebank databases, readily provide this quantitative data for subsequent genetic analysis and breeding purposes by end-users.…”

Section: Phenomic Characterization and Evaluation Of Genebank Accementioning

confidence: 99%

Genebank Phenomics: A Strategic Approach to Enhance Value and Utilization of Crop Germplasm

Nguyen

Norton

2020

Plants

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Genetically diverse plant germplasm stored in ex-situ genebanks are excellent resources for breeding new high yielding and sustainable crop varieties to ensure future food security. Novel alleles have been discovered through routine genebank activities such as seed regeneration and characterization, with subsequent utilization providing significant genetic gains and improvements for the selection of favorable traits, including yield, biotic, and abiotic resistance. Although some genebanks have implemented cost-effective genotyping technologies through advances in DNA technology, the adoption of modern phenotyping is lagging. The introduction of advanced phenotyping technologies in recent decades has provided genebank scientists with time and cost-effective screening tools to obtain valuable phenotypic data for more traits on large germplasm collections during routine activities. The utilization of these phenotyping tools, coupled with high-throughput genotyping, will accelerate the use of genetic resources and fast-track the development of more resilient food crops for the future. In this review, we highlight current digital phenotyping methods that can capture traits during annual seed regeneration to enrich genebank phenotypic datasets. Next, we describe strategies for the collection and use of phenotypic data of specific traits for downstream research using high-throughput phenotyping technology. Finally, we examine the challenges and future perspectives of genebank phenomics.

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Morphometry of the Wheat Spike by Analyzing 2D Images

Cited by 13 publications

References 22 publications

Genetic variability of spelt factor gene in Triticum and Aegilops species

Genetic variability of spelt factor gene in Triticum and Aegilops species

Automatic morphology phenotyping of tetra- and hexaploid wheat spike using computer vision methods

Genebank Phenomics: A Strategic Approach to Enhance Value and Utilization of Crop Germplasm

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