Genetic variability, character association and path analysis for anaerobic germination traits in rice (Oryza sativa L.)

Sudeepthi, K.; Srinivas, T.; Kumar, Bnvsr Ravi; Dpb, Jyothula; Umar, Sk. Nafeez

doi:10.22271/phyto.2020.v9.i1i.10489

Cited by 10 publications

(14 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The non-significant association with grain yield of total tillers per plant indicated the need for adoption of restricted selection on simultaneous basis to eliminate the undesirable indirect effects and make use of the high direct effects. Similar result were also reported by earlier workers Surek et al [37], Kumar et al [38], Khare et al [28], Nayak et al [39]; Nanda et al [36] and Sudeepthi et al [12].…”

Section: Path Coefficient Analysissupporting

confidence: 91%

“…Similar result were also reported earlier by Mohanty et al[7], Tuwar et al[8], Singh et al[9], Acharya et al[10], Priyanka et al[11] and Sudeepthi et al[12].Moderate PCV and GCV values were recorded for head rice recovery percentage(19.11 and 18.82), plant height (16.84 and 16.691), effective tillers per plant (15.98 and 8.46), total tillers per plant (14.71and 7.07), grain L:B ratio (13.64 and 13.29), spikelet fertility percentage (12.88 and 8.15), amylose content (12.75 and 11.96), kernel L:B ratio (12.14 and 11.55), grain length (11.28 and 11.21), kernel length (10.91 and 10.81) and grain breadth (10.29 and 9.98 % respectively).The results are in agreement with those of Akter et al[13], Mohanty et al[7], Dhanwani et al[14], Sharma and Koutu [15],. Singh et al[9], Nirmaladevi et al[16], Singh et al[17] and Sudeepthi et al[12]. Similar results were also reported by Aditya et al[18], Dhanwani et al[14], Nirmaladevi et al[16], Singh et al[17], Rashid et al[19] and Sudeepthi et al[12].…”

supporting

confidence: 91%

“…Singh et al[9], Nirmaladevi et al[16], Singh et al[17] and Sudeepthi et al[12]. Similar results were also reported by Aditya et al[18], Dhanwani et al[14], Nirmaladevi et al[16], Singh et al[17], Rashid et al[19] and Sudeepthi et al[12].…”

supporting

confidence: 69%

See 2 more Smart Citations

Genetic Dissection of Yield Determinants in Advance Breeding Lines (ABLs) of Rice (Oryza sativa L.) under Irrigated Condition of Chhattisgarh, India

Noatia

Sao

Tiwari

et al. 2021

IJPSS

View full text Add to dashboard Cite

The present study was undertaken to study the extent of genetic variability, character association and path analysis in 53 irrigated late duration breeding lines for 12 quantitative and 10 quality parameters. Analysis of variance revealed the presence of significant variation among the breeding lines for all the characters except for total tillers per plant, effective tillers per plant, spikelet fertility percentage and grain yield per plant. The highest magnitude of PCV and GCV were displayed by grain yield per plant followed by harvest index, filled spikelet per panicle and 1000 seed weight. The greater extent of heritability in broad sense were recorded for days to maturity, days to 50% flowering, 1000 seed weight, plant height, total spikelet per panicle, kernel length, kernel L:B ratio, grain length, head rice recovery percentage, amylose content, hulling and milling percentage. However, high heritability coupled with high genetic advance as percent of mean were displayed by plant height, number of spikelet per panicle, filled spikelet per panicle,1000 seed weight, kernel length, kernel L:B ratio, grain length, head rice recovery percentage and amylose content. Grain yield per plant exhibited positive significant correlation with harvest index, effective tillers per plant, 1000 seed weight, spikelet fertility %, days to maturity and days to 50% flowering. Path analysis revealed direct effect on grain yield were exerted by days to 50% flowering followed by harvest index, 1000 seed weight, total tillers per plant, number of spikelet per plant, effective tillers per plant and plant height indicating their importance in rice breeding programs.

show abstract

Section: Path Coefficient Analysissupporting

confidence: 91%

supporting

confidence: 91%

See 1 more Smart Citation

Genetic Dissection of Yield Determinants in Advance Breeding Lines (ABLs) of Rice (Oryza sativa L.) under Irrigated Condition of Chhattisgarh, India

Noatia

Sao

Tiwari

et al. 2021

IJPSS

View full text Add to dashboard Cite

show abstract

“…High PCV and GCV were seen in the traits viz., NPT, NFG, SPY, KB, L/B ratio, KLAC, ASV and WUR, while the traits, DFF, PH, TGW, KL, KBAC, LER, BER, AC and VER showed moderate PCV and GCV and low PCV and GCV was shown by PL. This was parallel to the findings of Sudeepthi, Srinivas [24] for NPT and TGW, Sujitha, Pillai [25] for DFF, PH, TGW and KL, Kumar, Kumar [26] for DFF, KBAC, LER, BER, VER, L/B, KLAC and WUR, Sadhana, Raju [27] for NFG, KL, KBAC and LER, Lakshmi, Shanmuganathan [28] for NFG, NPT, SPY, DFF and PH, Bhargavi, Suneetha [29] for AC and ASV and Bhargavi, Suneetha [29] for NFG, NPT, SPY, L/B, KL, KBAC, LER, BER and VER. Contrary findings by Sadhana, Raju [27] and Maurya, Dwivedi [30] for KB were found.…”

Section: Per Se Performance and Genetic Variability Studiessupporting

confidence: 88%

Diversity and Multi-variate Analysis of Basmati and Non-Basmati Rice Genotypes over Two Seasons using Organo-leptic Traits

Hemalatha¹,

Geetha²,

Saraswathi³

et al. 2023

IJPSS

View full text Add to dashboard Cite

Investigation on multi-variate analysis was done with Mahalanobis’ D2 statistic, Principal Component Analysis (PCA), genetic variability studies and Pearson’s correlation coefficient analysis among fifty-one rice genotypes over two consecutive seasons i.e., Kharif 2021 and Rabi 2021. It led to the clustering of the genotypes into ten clusters with maximum intra cluster distance found in cluster III and inter cluster distance between clusters III and X. PCA led to six principal components that had eigen values greater than one, explaining cumulative of 76.77% of the total variation. Based on the per se performance, D2 analysis and PCA, it was found that the genotypes, Improved white ponni, CO 52, VGD 1, BPT 5204, RNR 15048, Pusa Basmati 1121 and Pusa Basmati 1 were highly divergent due to the large genetic distance from the genotypes viz., TRY 3, TPS 5, Palawan, Azucena and Khao do ngoi for both grain yield and organoleptic traits indicating the possibilities for the potential use of these parents in future breeding programme aimed at improvement of grain yield and desirable organoleptic traits . Linear elongation ratio was positively correlated with amylose content, kernel length, L/B ratio and kernel length after elongation but negatively correlated with kernel breadth, kernel breadth after cooking, water uptake ratio and volume expansion ratio and hence indirect selection for longer grains and intermediate to high amylose content would improve LER inspite of the seasonal influence. These traits attribute to the selection of genotypes with desirable cooking quality that fetches premium price in the market in particular to that of non-basmati genotypes.

show abstract

“…Positive and significant associations were noticed for panicle length, number of panicles per plant, number of filled grains per panicle. The positive but non-significant association was observed with days to maturity, grain length, grain width, 1000 grain weight, kernel length, kernel breadth, grain iron content, grain zinc content and showed a negative non significant correlation with days to 50% [20] and Sudeepti et al [21] for grain yield per plant.…”

Section: Resultsmentioning

confidence: 99%

Studies on Correlation and Path Coefficient Analysis of Yield and Yield Attributing Characters in Rice Landraces (Oryza sativa L.)

Manasa

Reddy²,

Murthy³

et al. 2022

IJECC

View full text Add to dashboard Cite

In order to characterise the correlation and path analysis for yield and yield attributing traits for 66 genotypes including 4 checks in Augmented Block Design replicated thrice during Kharif, 2021, the present investigation was conducted at the Agricultural College, Aswaraopet, Bhadradri, Telangana. The most positive and significant correlation between important traits and grain yield per plant was found to be between the number of panicles per plant and the number of filled grains per panicle indicating yield can be improved through improvement of these traits. The features number of panicles per plant and number of filled grains per panicle had reported the strongest positive direct effect on grain yield per plant, and may be considered as excellent selection criteria for yield improvement, according to path coefficient analysis.

show abstract

Genetic variability, character association and path analysis for anaerobic germination traits in rice (Oryza sativa L.)

Cited by 10 publications

References 0 publications

Genetic Dissection of Yield Determinants in Advance Breeding Lines (ABLs) of Rice (Oryza sativa L.) under Irrigated Condition of Chhattisgarh, India

Genetic Dissection of Yield Determinants in Advance Breeding Lines (ABLs) of Rice (Oryza sativa L.) under Irrigated Condition of Chhattisgarh, India

Diversity and Multi-variate Analysis of Basmati and Non-Basmati Rice Genotypes over Two Seasons using Organo-leptic Traits

Studies on Correlation and Path Coefficient Analysis of Yield and Yield Attributing Characters in Rice Landraces (Oryza sativa L.)

Contact Info

Product

Resources

About