The success of plant breeding depends on the availability of genetic variation, knowledge about desired traits, and efficient selection strategies that make it possible to exploit existing genetic resource. This study was carried out at Africa Rice Center, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria, and 239 double haploid lines from Republic of Korea were established along with one of the rice mega varieties (FARO 44) as check. The experiment was conducted using Alpha lattice design with four blocks each planted with 60 entries in two replications. Analysis of variance revealed highly significant differences (P ≤ 0.001) among the genotypes indicating existence of variation among the genotypes. Correlation coefficient of the yield and its association traits revealed significantly positive correlation of grain yield with number of tillers, plant height, days to 50% flowering, panicle length, effective tillers, leaf area, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant, hence, selection for these traits can improve yield. Path coefficient analysis revealed that days to 50% flowering, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant exhibited positive direct effect on grain yield. Among all traits examined, panicle weight had the highest significant positive correlation and high positive direct effect. Stepwise regression showed that characters such as panicle weight, grain yield per plant, flag leaf, days to 50% flowering, effective tillers and 1000 grain weight contributed more to the total grain yield. Therefore, selections for the aforementioned characters will assist breeders in making good improvement in rice grain yield.
Published in | American Journal of Agriculture and Forestry (Volume 9, Issue 3) |
DOI | 10.11648/j.ajaf.20210903.13 |
Page(s) | 114-121 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Oryza, Yield Components, Double Haploid, Genotypes, Path Coefficient and Correlation
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APA Style
Salim Hassan Kafi, Efisue Andrew Abiodun, Olasanmi Bunmi, Kang Kyung-Ho. (2021). Correlation Coefficient and Path Analyses of Yield and Yield Related Traits of Korean Double Haploid Rice for Germplasm Improvement in Nigeria. American Journal of Agriculture and Forestry, 9(3), 114-121. https://doi.org/10.11648/j.ajaf.20210903.13
ACS Style
Salim Hassan Kafi; Efisue Andrew Abiodun; Olasanmi Bunmi; Kang Kyung-Ho. Correlation Coefficient and Path Analyses of Yield and Yield Related Traits of Korean Double Haploid Rice for Germplasm Improvement in Nigeria. Am. J. Agric. For. 2021, 9(3), 114-121. doi: 10.11648/j.ajaf.20210903.13
AMA Style
Salim Hassan Kafi, Efisue Andrew Abiodun, Olasanmi Bunmi, Kang Kyung-Ho. Correlation Coefficient and Path Analyses of Yield and Yield Related Traits of Korean Double Haploid Rice for Germplasm Improvement in Nigeria. Am J Agric For. 2021;9(3):114-121. doi: 10.11648/j.ajaf.20210903.13
@article{10.11648/j.ajaf.20210903.13, author = {Salim Hassan Kafi and Efisue Andrew Abiodun and Olasanmi Bunmi and Kang Kyung-Ho}, title = {Correlation Coefficient and Path Analyses of Yield and Yield Related Traits of Korean Double Haploid Rice for Germplasm Improvement in Nigeria}, journal = {American Journal of Agriculture and Forestry}, volume = {9}, number = {3}, pages = {114-121}, doi = {10.11648/j.ajaf.20210903.13}, url = {https://doi.org/10.11648/j.ajaf.20210903.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajaf.20210903.13}, abstract = {The success of plant breeding depends on the availability of genetic variation, knowledge about desired traits, and efficient selection strategies that make it possible to exploit existing genetic resource. This study was carried out at Africa Rice Center, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria, and 239 double haploid lines from Republic of Korea were established along with one of the rice mega varieties (FARO 44) as check. The experiment was conducted using Alpha lattice design with four blocks each planted with 60 entries in two replications. Analysis of variance revealed highly significant differences (P ≤ 0.001) among the genotypes indicating existence of variation among the genotypes. Correlation coefficient of the yield and its association traits revealed significantly positive correlation of grain yield with number of tillers, plant height, days to 50% flowering, panicle length, effective tillers, leaf area, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant, hence, selection for these traits can improve yield. Path coefficient analysis revealed that days to 50% flowering, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant exhibited positive direct effect on grain yield. Among all traits examined, panicle weight had the highest significant positive correlation and high positive direct effect. Stepwise regression showed that characters such as panicle weight, grain yield per plant, flag leaf, days to 50% flowering, effective tillers and 1000 grain weight contributed more to the total grain yield. Therefore, selections for the aforementioned characters will assist breeders in making good improvement in rice grain yield.}, year = {2021} }
TY - JOUR T1 - Correlation Coefficient and Path Analyses of Yield and Yield Related Traits of Korean Double Haploid Rice for Germplasm Improvement in Nigeria AU - Salim Hassan Kafi AU - Efisue Andrew Abiodun AU - Olasanmi Bunmi AU - Kang Kyung-Ho Y1 - 2021/05/20 PY - 2021 N1 - https://doi.org/10.11648/j.ajaf.20210903.13 DO - 10.11648/j.ajaf.20210903.13 T2 - American Journal of Agriculture and Forestry JF - American Journal of Agriculture and Forestry JO - American Journal of Agriculture and Forestry SP - 114 EP - 121 PB - Science Publishing Group SN - 2330-8591 UR - https://doi.org/10.11648/j.ajaf.20210903.13 AB - The success of plant breeding depends on the availability of genetic variation, knowledge about desired traits, and efficient selection strategies that make it possible to exploit existing genetic resource. This study was carried out at Africa Rice Center, International Institute of Tropical Agriculture (IITA) Ibadan, Nigeria, and 239 double haploid lines from Republic of Korea were established along with one of the rice mega varieties (FARO 44) as check. The experiment was conducted using Alpha lattice design with four blocks each planted with 60 entries in two replications. Analysis of variance revealed highly significant differences (P ≤ 0.001) among the genotypes indicating existence of variation among the genotypes. Correlation coefficient of the yield and its association traits revealed significantly positive correlation of grain yield with number of tillers, plant height, days to 50% flowering, panicle length, effective tillers, leaf area, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant, hence, selection for these traits can improve yield. Path coefficient analysis revealed that days to 50% flowering, leaf area index, fertility, biomass, panicle weight, number of grains per panicle and grain yield per plant exhibited positive direct effect on grain yield. Among all traits examined, panicle weight had the highest significant positive correlation and high positive direct effect. Stepwise regression showed that characters such as panicle weight, grain yield per plant, flag leaf, days to 50% flowering, effective tillers and 1000 grain weight contributed more to the total grain yield. Therefore, selections for the aforementioned characters will assist breeders in making good improvement in rice grain yield. VL - 9 IS - 3 ER -