GENETIC DIVERSITY ANALYSIS IN RICE (Oryza sativa L.)

Chakma, S. P.; Huq, H.; Mahmud, Firoz; Husna, Asmaul

doi:10.3329/bjpbg.v25i1.17010

Cited by 14 publications

(13 citation statements)

References 4 publications

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“…The traits viz., number of filled grains per panicle, days to 50% flowering, and grain yield per plot, ear bearing tillers per m 2 contributed more than ninety per cent towards total divergence. The results were in conformity with [11,12,13]. Hence, these characters should be given importance during hybridization and selection in the segregating population under water stress condition.…”

Section: Resultssupporting

confidence: 88%

Genetic Diversity Analysis for Yield Parameters in Rice (Oryza sativa. L) Genotypes

Soundharya

Rathod

Shahana

et al. 2020

CJAST

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The present investigation was conducted during Kharif, 2019 at Regional Sugarcane and Rice Research Station, Rudrur, Nizamabad. Twenty rice genotypes were studied to assess genetic diversity analysis for days to fifty percent flowering, plant height (cm), ear bearing tillers per m2, panicle length (cm), number of filled grains per panicle, test weight (g) and plot yield (kg/ha). Based on the analysis, the genotypes were grouped into four clusters. The maximum number of genotypes (14 genotypes) was grouped in cluster I. Cluster II and III consists of three and two genotypes respectively. Remaining cluster was represented by a single genotype. Maximum inter cluster distance was observed between I and II (27.46) followed by between cluster I and IV (23.19) and between cluster II and IV (20.43) indicating wider genetic diversity between genotypes. Hence these lines may be utilized in a further breeding programme for the exploitation of hybrid vigour. Among the seven traits studied, the number of filled grains per panicle contributed maximum divergence (42.68%) followed by days to 50% flowering (32.04%), grain yield per plot (12.01%) and ear bearing tillers per m2 (8.12%). Hence these altogether contribute more than ninety per cent towards total divergence. Therefore, these characters may be given importance during hybridization programme.

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Section: Resultssupporting

confidence: 88%

Genetic Diversity Analysis for Yield Parameters in Rice (Oryza sativa. L) Genotypes

Soundharya

Rathod

Shahana

et al. 2020

CJAST

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“…A survey of recent literatures pertaining to our study revealed the formation of five clusters in the investigations by Siddique et al, (2013), (Kumar et al, 2014) involving 40 and 134 genotypes for 14 and 16 traits. Chakma et al, (2012), Ranjith et al, (2018), Singh et al, (2018) and Tiruneh et al, (2019) obtained six clusters with around same number of genotypes viz., 39, 30, 30 and 36 for 12, 12, 14 and 15 traits respectively. In a study with 51 genotypes, Palaniraja and Anbuselvam (2010) reported as many as 15 clusters for just seven traits.…”

Section: Genetic Diversity For Agro-morphological Traitsmentioning

confidence: 96%

“…Their genetic distances were 36.45 and 22.36 respectively. In six clusters Chakma et al, (2012) reported the highest genetic distance of 15.84 between clusters II and III. So also, Baradhan and Thangavel (2011) obtained a genetic distance of 13.2 between II and VI.…”

Section: Intra and Inter Cluster Distancesmentioning

confidence: 99%

Genetic Divergence Studies in Subspecies of Oryza sativa L.

Sangeetha¹,

Saraswathi²,

Amudha³

et al. 2019

Int.J.Curr.Microbiol.App.Sci

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An experiment was carried out to study the divergence among twenty four rice genotypes (14 indica and 10 japonica lines) for 15 agro-morphological traits using D 2 statistics and at molecular level using 114SSR markers. The cluster analysis using Mahalonobis' D 2 statistics classified the genotypes into five clusters. The cluster IV was the largest with seven indica and three tropical japonica types. The second largest cluster (V) accommodated four tropical japonica and two indica genotypes. The intra cluster distance ranged from 1.077 to 8.299 and it showed a gradual increase from cluster I to cluster V. Cluster III with four genotypes showed the highest inter cluster distance with cluster I (14.312), followed by cluster II (12.032) and cluster IV (11.734). Cluster II with AC 38479 and IR 64 showed the highest mean values for five traits viz., panicle length, number of primary branches panicle -1 , number of secondary branches panicle -1 , filled grains panicle -1 and single plant yield and the lowest mean values for hundred grain weight, kernel length, kernel breadth and kernel thickness which are desirable. The kernel traits viz., kernel L/B ratio (35.14%), 100 grain weight (25.73%), kernel thickness (14.13%) and kernel breadth (12.31%) alone contributed for 87.31% of the total genetic divergence. In molecular diversity analysis, 69 SSR markers were detected to be polymorphic out of 114 markers. In total, 216 alleles were detected and the number of alleles amplified ranged between two to seven. The average number of alleles obtained was 3.13. The Polymorphism Information Content (PIC) which reflects the allelic diversity varied from 0.08 (RM2) to 0.81(RM3317) and its average was 0.5. The dendrogram based on the UPGMA classified the 24 genotypes into four major distinguishable clusters with two sub clusters for cluster I. The Jaccard's dissimilarity index was lowest (0.34) between CB 16144 and CB 15138; highest (0.89) between CB 16174 and Pato as well as between CB 16174 and AC 38476. It is concluded that in both methods, some distinct genotypes in each group were accommodated in the same cluster without separation. Also, no distinct clusters were formed for each of the two sub groups indica and tropical japonica separately but the genotypes of both the groups were spread over all clusters indicating sufficient genetic diversity within the groups which can be utilized in selecting parents for hybridization program.

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“…In hybridization programs, parental lines must be selected from the clusters that are at highest genetic divergence because divergent parents are expected to produce wide variability and transgressive segregations with high heterotic effects [28,29]. Chakma et al [30] pointed out the role of the magnitude of genetic distance, the contribution of different characters towards the total divergence, and the magnitude of cluster mean for different characters performance in the selection of the parents for the hybridization program. Nisar et al [31] suggested selecting the lines belonging to diverse clusters and showing high mean performance in desirable directions for different traits can be used as parents in the breeding program.…”

Section: Mahalanobis Distancementioning

confidence: 99%

Multivariate Analysis of Phenotypic Diversity of Rice (Oryza sativa L.) Landraces from Lamjung and Tanahun Districts, Nepal

Dhakal

Pokhrel

Sharma

2020

International Journal of Agronomy

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The magnitude and nature of genetic divergence play a vital role in the selection of the desirable landraces for its utilization in the breeding program. A study was carried out with 30 rice landraces at the Institute of Agriculture and Animal Science, Lamjung Campus, during June–November 2018 to determine relation among individuals, estimate the relative contribution of various traits of rice using principal component analysis, and identify the potential parents for hybridization using Mahalanobis distance (D2). The principal component analysis revealed that five among the thirteen principal components were significant (eigenvalue >1) and contributed to 29.96%, 20.26%, 13.56%, 11.68%, and 9.22% of the total variance, respectively. PC1 included the traits that were related mostly to the yield, yield attributing, and grain characteristics. Landraces from Anadi group, Jetho Budo, Jarneli, and Rato Masino performed well in PC1 while landraces such as Mansara, Pakhe Sali, and Aanga performed well in PC2. The landraces were grouped into six clusters where 12 landraces were grouped into cluster I. Cluster analysis showed maximum and minimum intracluster distance in cluster VI (D2 = 35.77) and cluster I (D2 = 18.59), respectively. The maximum intercluster distance was obtained between clusters V and VI (D2 = 40.18) followed by clusters III and VI (D2 = 36.17) and clusters IV and VI (D2 = 35.74). Cluster III showed the highest mean value for grain width, flag leaf breadth, yield, and minimum mean value for plant height while mean values of total grain per panicle, filled grain percentage, and thousand-grain weight were maximum in cluster IV. Mean values of effective tiller and kernel width were found maximum in clusters V and VI, respectively. Landraces from clusters V and VI or clusters III and VI or clusters IV and VI can be used in the hybridization program to develop the superior hybrids by exploiting heterosis in segregating generation.

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GENETIC DIVERSITY ANALYSIS IN RICE (Oryza sativa L.)

Cited by 14 publications

References 4 publications

Genetic Diversity Analysis for Yield Parameters in Rice (Oryza sativa. L) Genotypes

Genetic Diversity Analysis for Yield Parameters in Rice (Oryza sativa. L) Genotypes

Genetic Divergence Studies in Subspecies of Oryza sativa L.

Multivariate Analysis of Phenotypic Diversity of Rice (Oryza sativa L.) Landraces from Lamjung and Tanahun Districts, Nepal

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