Genetic Diversity Studies on Selected Rice (Oryza Sativa L.) Genotypes Based on Amylose Content and Gelatinization Temperature

Musyoki, Mawia A; Kioko, Wambua F; Mathew, Ngugi P

doi:10.4172/2329-8863.1000193

Cited by 5 publications

(6 citation statements)

References 19 publications

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“…The peak of the endotherm was reported as the GT. Samples were classified as low-GT (below 67 °C), as intermediate-GT (68–73 °C), and as high-GT (GT ≥ 74 °C) [Cuevas et al 2010 ; Musyoki et al 2015 ].…”

Section: Methodsmentioning

confidence: 99%

Multivariate-based classification of predicting cooking quality ideotypes in rice (Oryza sativa L.) indica germplasm

Cuevas

Domingo

Sreenivasulu

2018

Rice

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BackgroundFor predicting texture suited for South and South East Asia, most of the breeding programs tend to focus on developing rice varieties with intermediate to high amylose content in indica subspecies. However, varieties within the high amylose content class may still be distinguishable by consumers, who are able to distinguish texture that cannot be differentiated by proxy cooking quality indicators.ResultsThis study explored a suite of assays to capture viscosity, rheometric, and mechanical texture parameters for characterising cooked rice texture in a set of 211 rice accessions from a diversity panel and employed multivariate approaches to classify rice varieties into distinct cooking quality classes. Results suggest that when the amylose content range is narrowed to the intermediate to high classes, parameters determined by rheometry and RVA become diagnostic. Modeled parameters distinguishing cooking quality ideotypes within the same range of amylose classes differ in textural parameters scored by a descriptive sensory panel.ConclusionsOur results reinforced the notion that it is important to define cooking quality classes in indica subtypes based on multidimensional parameters, by going beyond amylose predictions. These predictive cooking models will be handy in capturing cooking and eating quality properties that address consumer preferences in future breeding programs. Policy implications of such findings may lead to changes in criteria used in assessing grain quality in the intermediate to high amylose classes.Electronic supplementary materialThe online version of this article (10.1186/s12284-018-0245-y) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Multivariate-based classification of predicting cooking quality ideotypes in rice (Oryza sativa L.) indica germplasm

Cuevas

Domingo

Sreenivasulu

2018

Rice

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“…This value was higher compared to 0.358 reported by Chen et al [30] and lower than an average of 0.5513 reported in Kenyan and Tanzanian genotypes [16] and 0.68 in Asian rice accessions [31]. Evaluation of gene diversity based on the attributes of the genotypes, showed that improved genotypes had higher gene diversity value of 0.3729 compared 0.3167 of the landrace genotypes.…”

Section: Discussionmentioning

confidence: 40%

“…They are popularly known in the determination of the genetic diversity, generating gene map for tagging traits of interest, germplasm conservation and crop improvement [13]. Microsatellites also known as simple sequence repeats (SSR) markers have been applied in various studies to study rice genetic diversity [14][15][16], marker assisted selection [17,18] and in mapping of the QTLs [19,20]. In Kenyan and Tanzanian rice genotypes SSRs have been used to study diversity studies gelatinization temperature and amylose content [15].…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity Studies on Selected Rice (Oryza sativa L.) Genotypes based on Gel Consistency and Alkali Digestion

LR¹,

MA²

2016

J Rice Res

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Knowledge of rice genetic diversity is necessary to ascertain the germplasm conservation and the development of improved rice genotypes with good quality traits through various breeding programs. The aim of this study was to determine the genetic diversity based on gel consistency and alkali digestion among selected Kenyan and Tanzanian genotypes using SSR markers. PowerMarker version 3.25, GenAlEx version 6.41 and DARwin 6.0.12 statistical software were used to carry out data analysis. The number of alleles per locus ranged from 2 to 4 with an average of 2.75 across the 8 markers used. Polymorphic information content (PIC) ranged from 0.5224 (RM577) to 0.1411 (RM85) with an average of 0.3673 observed across all the markers. Gene diversity ranged from 0.5764 (RM577) to 0.1528 (RM85) with an average of 0.4181 with one rare allele was detected at RM577 loci. Pairwise genetic dissimilarity matrix ranged from ranged from 0.9333 to 0.1818 with the least genetic distance being observed between IR 54 and BS 370 while the highest, 0.9333 being between Saro 5 and IR 2793. The unweighted neighbour joining tree clustered the rice genotypes into three major clusters and subsequent sub clusters hence effectively differentiating the Kenyan and Tanzanian genotypes based on gel consistency and alkali digestion. This clustering was complemented with the findings in the principal coordinate analysis. These results show that determination of genetic diversity using SSR markers cam be successfully achieved. In this study RM577 was the best and most informative SSR marker given it showed the highest PIC, gene diversity and allele per locus. In addition, it's the only marker that showed a rare allele at 400 bp.

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“…(2010). Samples were classified on the basis of GT observations as follows: low, <67 °C; intermediate, 68–73 °C; and high, ≥74 °C (Cuevas et al., 2010; Musyoki et al., 2015).…”

Section: Methodsmentioning

confidence: 99%

“…Gelatinization temperature was measured through differential scanning calorimetry using the similar protocol described earlier by Cuevas et al (2010). Samples were classified on the basis of GT observations as follows: low, <67˚C; intermediate, 68-73˚C; and high, ≥74˚C (Cuevas et al, 2010;Musyoki et al, 2015).…”

Section: Grain Quality Testingmentioning

confidence: 99%

Genomics‐assisted breeding for successful development of multiple‐stress‐tolerant, climate‐smart rice for southern and southeastern Asia

et al. 2021

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Rice (Oryza sativa L.) in rainfed marginal environments is prone to multiple abiotic and biotic stresses, which can occur in combination in a single cropping season and adversely affect rice growth and yield. The present study was undertaken to develop high‐yielding, climate‐resilient rice that can provide tolerance to multiple biotic and abiotic stresses. An assembled first‐crossing scheme was employed to transfer 15 quantitative trait loci (QTL) and genes—qDTY1.1, qDTY2.1, qDTY3.1, qDTY12.1 (drought), Sub1 (submergence), Gm4 (gall midge), Pi9, Pita2 (blast), Bph3, Bph17 (brown plant hoppers), Xa4, xa5, xa13, Xa21, and Xa23 (bacterial leaf blight)—from eight different parents using genomics‐assisted breeding. A funnel mating design was employed to assemble all the targeted QTL and genes into a high‐yielding breeding line IR 91648‐B‐1‐B‐3‐1. Gene‐based linked markers were used in each generation from intercrossing to the F6 generation for tracking the presence of desirable alleles of targeted QTL and genes. Single‐plant selections were performed from F2 onwards to select desirable recombinants possessing alleles of interest with suitable phenotypes. Phenotyping of 95 homozygous F6 lines carrying six to 10 QTL and genes was performed for nonstress, reproductive‐stage (RS) drought, blast, bacterial leaf blight (BLB), gall midge (GM), and for grain quality parameters such as chalkiness, amylose content (AC), gelatinization temperature (GT), and head rice recovery (HRR). Finally, 56 F7 homozygous lines were found promising for multiple‐location evaluation for grain yield (GY) and other traits. These multiple‐stress‐tolerant lines with the desired grain quality profiling can be targeted for varietal release in southern and southeastern Asia through national release systems.

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Genetic Diversity Studies on Selected Rice (Oryza Sativa L.) Genotypes Based on Amylose Content and Gelatinization Temperature

Cited by 5 publications

References 19 publications

Multivariate-based classification of predicting cooking quality ideotypes in rice (Oryza sativa L.) indica germplasm

Multivariate-based classification of predicting cooking quality ideotypes in rice (Oryza sativa L.) indica germplasm

Genetic Diversity Studies on Selected Rice (Oryza sativa L.) Genotypes based on Gel Consistency and Alkali Digestion

Genomics‐assisted breeding for successful development of multiple‐stress‐tolerant, climate‐smart rice for southern and southeastern Asia

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