Generation mean analysis in quality protein maize (Zea mays L.) for yield and quality attributes
Article Main
Abstract
Maize (Zea mays L.), the world’s most significant cereal crop, provides a pivotal roles for the supply of food for humans and forage for livestock. The present study aimed to perform a Generation mean analysis of two quality protein maize (QPM) (Zea mays L.) crosses [(CML149 x CML330) and (CML143 x CML193)] in order to determine the genetic effects along with the nature of gene action controlling morphological and biochemical traits underlying inheritance. All four components of scaling testing revealed significant differences with the parameter model, indicating the importance of the additive, dominance and epistatic modes of gene action for the inheritance of physiological, biochemical, grain yield and its attributing traits. Dominance variance showed more importance than additive variance and the presence of duplicate form of non-allelic gene interaction was prevalent for all the characters studied except days to 50% silking in CML149 × CML330 ([h] = 2.064, [l] = 1.536) and membrane stability index in CML143 × CML193 ([h] = 4.055, [l] = 17.362) which showed complementary gene action. Characters with duplicate genes, grain yield per plant in CML149 × CML330 ([h] = 1545.776, [l] = -2126.616) and plant height in CML149 × CML330 ([h] = 113.336, [l] = -104.376) showed strong dominance and dominance x dominance gene action. The significant role of dominance variance and duplicate epistasis was noted in the inheritance of the aforementioned characters. Selection could be rewarding for consecutive populations, followed by a bi-parental mating design to improve these traits.
Article Details
Article Details
Keywords
Additive and dominance effect, Generation mean analysis, Non-allelic interactions, Quality protein maize
References
Ayyanna, Bhat, J. S., Rakshith, P., & Kariyannanavar, P. (2023). Heterosis and combining ability analysis in newly developed inbred lines of maize (Zea mays L.). The Pharma Innovation Journal, 12(11), 1356-1362.
Abid, M., Ali, S., Qi, L.K. et al. Physiological and biochemical changes during drought and recovery periods at tillering and jointing stages in wheat (Triticum aestivum L.). Sci Rep 8, 4615 (2018). https://doi.org/10.1038/s41598-018-21441-7
Arsyad, F., & Basunanda, P. (2020). Identification of agronomic characters affecting cob weight of the families BTP1-X purple sweet corn (Zea mays L. Saccharata Sturt) using path analysis. IOP Conference Series: Earth and Environmental Science, 484, 012011. https://doi.org/10.1088/1755-1315/484/1/012011
Attri, H., Dey, T., Singh, B., & Kour, A. (2021). Genetic estimation of grain yield and its attributes in three wheat (Triticum aestivum L.) crosses using six parameter model. Journal of Genetics, 100(47). https://doi.org/10.1007/s12041-021-01298-y
Chiangmai, P.N., Yodmingkhwan, P., Nilprapruck, P., Aekatasanawan, C. & Kanjanamaneesathian, M. (2013). Generation means analysis of phytic acid and inorganic phosphorus contents in corn (Zea mays L). Maydica, 58, 243-253
Dinesh, H. B., Viswanatha, K. P., Lohithaswa, H., Pavan, R., & Singh, P. (2018). Genetic association estimates using third and fourth degree statistics in early segregating generations of cowpea. International Journal of Current Microbiology and Applied Sciences, 7(1), 894-899. https://doi.org/10.20546/IJCMAS.2018.701.105
Dorri, P., Khorasani, S.K. & Shahrokhi, M. (2014). Generation means analysis. A case study of variance components in KSC 500 generations of maize (Zea mays L.). International Research Journal of Applied and Basic Sciences, 8(2), 194-200.
Elmyhun, M., Abate, E., Abate, A., Teklewold, A., & Menkir, A. (2024). Genetic analysis of tolerance to combined drought and heat stress in tropical maize. PLOS ONE, 19(6), e0302272. https://doi.org/10.1371/journal.pone.0302272
Haq, M. I. U., Ajmal, S., Kamal, N., Khanum, S., Siddique, M. & Kiani, M. Z. (2013). Generation mean analysis for grain yield in maize. Generations 1(13), 11-38.
Hayman, B. I. (1958). The separation of epistasis from additive and dominance variation in Generation means. Heredity 12, 371–390. https://doi.or g/10.1007/BF01984430
Hamidi, S. M., Gogoi, R., Kumar, A., Singh, A., Yadav, R., & Dorjee, L. (2023). Tackling banded leaf and sheath blight disease of maize through activation of host defense. Frontiers in Agronomy, 5. https://doi.org/10.3389/fagro.2023.1229717
Li W, Pan K, Liu W, Xiao W, Ni S, Shi P, Chen X, Li T. (2024). Monitoring Maize Canopy Chlorophyll Content throughout the Growth Stages Based on UAV MS andRGB Feature Fusion. Agriculture. ; 14(8):1265. https://doi.org/10.3390/agriculture14081265
Mather, K. (1949). Biometrical Genetics: the Study of Continuous Variation. Metuen and Co.Limited, London.
Mather, K. & Jinks, J.L. (1971). Biometrical genetics, Chapman & Hall limited, London. https://doi.org/10.1007/978-1-4899-3404-8
Moharramnejad, S., Valizadeh, M. & Emaratpardaz, J. (2018). Generation mean analysis in maize (Zea mays L.) under drought stress. Fresenius Environmental Bulletin, 27(4), 2518-2522.
Nagarajan, D. et al. (2022). Inheritance studies through Generation mean analysis for quantitative traits in soybean (Glycine max (L.) Merrill.). Journal of Applied and Natural Science, 14 (SI), 111 - 118. https://doi.org/10.31018/jans.v14iSI.3576
Premachandra, G. S., Saneoka, H and Ogata, S. 1990. Cell membrane stability, an indicator of drought tolerance, as affected by applied nitrogen in soyabean. The J. Agricultural Sciences, Cambridge. 115: 63-66.
Pujar, M., Govindaraj, M., Gangaprasad, S., Kanatti, A., Gowda, T. H., Kumar, B. M. D., & Satish, K. M. (2022). Generation mean analysis reveals the predominant gene effects for grain iron and zinc contents in pearl millet. Frontiers in Plant Science, 12, 693680. https://doi.org/10.3389/fpls.2021.693680
Patil, K. H., Mahajan, R. C., & Nagargoje, V. T. (2020). Generation mean analysis in maize (Zea mays L.). Journal of Oilseeds Research, 37(Special issue). https://doi.org/10.56739/jor.v37iSpecialis sue.139527
Raj, G. S., Marker, S., Scaria, S., & Ansari, S. M. S. (2020). Quantitative studies on heterosis and inbreeding depression in quality protein maize for terminal heat tolerance. Journal of Pharmacognosy and Phytochemistry, 9(2), 784-788.
Rahangdale, P.Z., Kamdi, S.R., Patil, S.R., Deotale, R.D., Pandit, M.B., Upadhyay, D.Y. & Kankal, G.A. (2019). Generation mean analysis in maize (Zea mays L). Soils and crops, 29(1), p.126.
Rahimi Jahangirlou, M., Akbari, G.A., Alahdadi, I. et al. Phenotypic Traits, Grain Yield and Yield Components of Maize Cultivars Under Combinations of Management Practices in Semi-arid Conditions of Iran. Int. J. Plant Prod. 15, 459–471 (2021). https://doi.org/10.1007/s42106-021-00151-
Robinson, H. F., Comstock, R. E., & Harvey, P. H. (1949). Estimates of heritability and degree of dominance in corn. Agronomy Journal, 41, 253–259.
Sadasivam, S. & Manickam, A. (1996). Carbohydrates. In: Sada-sivam, S. & Manickam, A. (Eds). Methods in biochemistry.New Delhi, India, New Age International Pvt. Ltd, pp. 11-12.
Shahrokhi, M., Khorasani, S.K. & Ebrahimi, A. (2013). Study of genetic components in various maize (Zea mays L.) traits, using generation mean analysis method. International Journal of Agronomy and Plant Production 4(3), 405-412.
Sairam, R. K. 1994. Effect of moisture stress on physiological activities of two contrasting wheat genotypes. Indian J Experimental Biology. 32: 594-597.
Stubbs, C. J., Kunduru, B., Bokros, N., Verges, V., Porter, J., Cook, D. D., DeBolt, S., McMahan, C., Sekhon, R. S., & Robertson, D. J. (2023). Moving toward short stature maize: The effect of plant height on maize stalk lodging resistance. Field Crops Research, 300, 109008. https://doi.org/10.1016/j.fcr.2023.109008
Sharma, P., Singh, N., Kamboj, M. C. & Kumar, R. (2023). Understanding the genetics of important quality traits in maize (Zea mays L.) using diverse germplasm by Generation mean analysis. Agriculture Association of Textile Chemical and Critical Reviews, 11(4), 1-2. https://doi.org/10.58321/AATCCReview.2023.11.04.01
Sharma, P., Kamboj, M. C., Singh, N., Kumar, R. & Naveen, K. (2022). Generation mean analysis in maize (Zea mays L.) for yields and yield attributing traits. Indian Journal of Agricultural Sciences 92 (1), 110-117. https://doi.org/10.56093/ijas.v92i1.120854
Said, A. A. (2014). Generation mean analysis in wheat (Triticum aestivum L.) under drought stress conditions. Annals of Agricultural Science 59(2), 177–184. https://doi.org/10.1016/j.aoas.2014.11. 003
Shankar, M., Singh, R., Shahi, J. P., Devesh, P. & Singh, P. (2022). Generation Mean Analysis for Yield and Drought-Related Traits in Maize (Zea mays L.). Current Journal of Applied Science and Technology, 41(22), 30-45. https://doi.org/10.9734/cjast/2022/v41i2231758
Shen, C.-H. (2019). Quantification and analysis of proteins. In C.-H. Shen (Ed.), Diagnostic molecular biology (pp. 187-214). Academic Press. https://doi.org/10.1016/B978-0-12-802823-0.00008-0
Silva, P. C., Sánchez, A. C., Opazo, M. A., Mardones, L. A., & Acevedo, E. A. (2022). Grain yield, anthesis-silking interval, and phenotypic plasticity in response to changing environments: Evaluation in temperate maize hybrids. Field Crops Research, 285, 108583. https://doi.org/10.1016/j.fcr.2022.1 08583
Teja, K. V., Raju, K. K., Reddy, K. R., Sil, P., Rao, M. S., & Gupta, V. K. (2024). Genetic evaluation of heterosis and combining ability of quality protein maize (Zea mays L.) hybrids under terminal heat stress conditions. Agricultural Science Digest, 44(5), 806–815. https://doi.org/10.18805/ag.D-6027
Vidadala, R., Kumar, V., Rout, S., Sil, P., Teja, V., & Rahimi, M. (2024). Genetic analysis of Quality Protein Maize (QPM): A review. Cereal Research Communications. . https://doi.org/10.1007/s42976-024-00552-0
Wang, X., Li, Y., Han, W. et al. (2022). Evaluation of root lodging resistance during whole growth stage at the plant level in maize. Sci Rep 12, 10375 . https://doi.org/10.1038/s41598-022-14159-0
Yadav, S. K., Tiwari, Y. K., Singh, V., Patil, A. A., Shanker, A. K., Lakshmi, N. J., Vanaja, M., & Maheswari, M. (2018). Physiological and biochemical basis of extended and sudden heat stress tolerance in maize. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 88, 249–263. https://doi.org/10.1007/s40011-016-0
791-3
FAOStat. (2022). FAO Stat. FAO, Rome. http://www.fao.org/faostat
Zhai, L., Yang, W., Li, C. et al. (2024). Extraction of maize canopy temperature and variation factor analysis based on multi-source unmanned aerial vehicle remote sensing data. Earth Sci Inform . https://doi.org/10.1007/s12145-024-01363-x
Abid, M., Ali, S., Qi, L.K. et al. Physiological and biochemical changes during drought and recovery periods at tillering and jointing stages in wheat (Triticum aestivum L.). Sci Rep 8, 4615 (2018). https://doi.org/10.1038/s41598-018-21441-7
Arsyad, F., & Basunanda, P. (2020). Identification of agronomic characters affecting cob weight of the families BTP1-X purple sweet corn (Zea mays L. Saccharata Sturt) using path analysis. IOP Conference Series: Earth and Environmental Science, 484, 012011. https://doi.org/10.1088/1755-1315/484/1/012011
Attri, H., Dey, T., Singh, B., & Kour, A. (2021). Genetic estimation of grain yield and its attributes in three wheat (Triticum aestivum L.) crosses using six parameter model. Journal of Genetics, 100(47). https://doi.org/10.1007/s12041-021-01298-y
Chiangmai, P.N., Yodmingkhwan, P., Nilprapruck, P., Aekatasanawan, C. & Kanjanamaneesathian, M. (2013). Generation means analysis of phytic acid and inorganic phosphorus contents in corn (Zea mays L). Maydica, 58, 243-253
Dinesh, H. B., Viswanatha, K. P., Lohithaswa, H., Pavan, R., & Singh, P. (2018). Genetic association estimates using third and fourth degree statistics in early segregating generations of cowpea. International Journal of Current Microbiology and Applied Sciences, 7(1), 894-899. https://doi.org/10.20546/IJCMAS.2018.701.105
Dorri, P., Khorasani, S.K. & Shahrokhi, M. (2014). Generation means analysis. A case study of variance components in KSC 500 generations of maize (Zea mays L.). International Research Journal of Applied and Basic Sciences, 8(2), 194-200.
Elmyhun, M., Abate, E., Abate, A., Teklewold, A., & Menkir, A. (2024). Genetic analysis of tolerance to combined drought and heat stress in tropical maize. PLOS ONE, 19(6), e0302272. https://doi.org/10.1371/journal.pone.0302272
Haq, M. I. U., Ajmal, S., Kamal, N., Khanum, S., Siddique, M. & Kiani, M. Z. (2013). Generation mean analysis for grain yield in maize. Generations 1(13), 11-38.
Hayman, B. I. (1958). The separation of epistasis from additive and dominance variation in Generation means. Heredity 12, 371–390. https://doi.or g/10.1007/BF01984430
Hamidi, S. M., Gogoi, R., Kumar, A., Singh, A., Yadav, R., & Dorjee, L. (2023). Tackling banded leaf and sheath blight disease of maize through activation of host defense. Frontiers in Agronomy, 5. https://doi.org/10.3389/fagro.2023.1229717
Li W, Pan K, Liu W, Xiao W, Ni S, Shi P, Chen X, Li T. (2024). Monitoring Maize Canopy Chlorophyll Content throughout the Growth Stages Based on UAV MS andRGB Feature Fusion. Agriculture. ; 14(8):1265. https://doi.org/10.3390/agriculture14081265
Mather, K. (1949). Biometrical Genetics: the Study of Continuous Variation. Metuen and Co.Limited, London.
Mather, K. & Jinks, J.L. (1971). Biometrical genetics, Chapman & Hall limited, London. https://doi.org/10.1007/978-1-4899-3404-8
Moharramnejad, S., Valizadeh, M. & Emaratpardaz, J. (2018). Generation mean analysis in maize (Zea mays L.) under drought stress. Fresenius Environmental Bulletin, 27(4), 2518-2522.
Nagarajan, D. et al. (2022). Inheritance studies through Generation mean analysis for quantitative traits in soybean (Glycine max (L.) Merrill.). Journal of Applied and Natural Science, 14 (SI), 111 - 118. https://doi.org/10.31018/jans.v14iSI.3576
Premachandra, G. S., Saneoka, H and Ogata, S. 1990. Cell membrane stability, an indicator of drought tolerance, as affected by applied nitrogen in soyabean. The J. Agricultural Sciences, Cambridge. 115: 63-66.
Pujar, M., Govindaraj, M., Gangaprasad, S., Kanatti, A., Gowda, T. H., Kumar, B. M. D., & Satish, K. M. (2022). Generation mean analysis reveals the predominant gene effects for grain iron and zinc contents in pearl millet. Frontiers in Plant Science, 12, 693680. https://doi.org/10.3389/fpls.2021.693680
Patil, K. H., Mahajan, R. C., & Nagargoje, V. T. (2020). Generation mean analysis in maize (Zea mays L.). Journal of Oilseeds Research, 37(Special issue). https://doi.org/10.56739/jor.v37iSpecialis sue.139527
Raj, G. S., Marker, S., Scaria, S., & Ansari, S. M. S. (2020). Quantitative studies on heterosis and inbreeding depression in quality protein maize for terminal heat tolerance. Journal of Pharmacognosy and Phytochemistry, 9(2), 784-788.
Rahangdale, P.Z., Kamdi, S.R., Patil, S.R., Deotale, R.D., Pandit, M.B., Upadhyay, D.Y. & Kankal, G.A. (2019). Generation mean analysis in maize (Zea mays L). Soils and crops, 29(1), p.126.
Rahimi Jahangirlou, M., Akbari, G.A., Alahdadi, I. et al. Phenotypic Traits, Grain Yield and Yield Components of Maize Cultivars Under Combinations of Management Practices in Semi-arid Conditions of Iran. Int. J. Plant Prod. 15, 459–471 (2021). https://doi.org/10.1007/s42106-021-00151-
Robinson, H. F., Comstock, R. E., & Harvey, P. H. (1949). Estimates of heritability and degree of dominance in corn. Agronomy Journal, 41, 253–259.
Sadasivam, S. & Manickam, A. (1996). Carbohydrates. In: Sada-sivam, S. & Manickam, A. (Eds). Methods in biochemistry.New Delhi, India, New Age International Pvt. Ltd, pp. 11-12.
Shahrokhi, M., Khorasani, S.K. & Ebrahimi, A. (2013). Study of genetic components in various maize (Zea mays L.) traits, using generation mean analysis method. International Journal of Agronomy and Plant Production 4(3), 405-412.
Sairam, R. K. 1994. Effect of moisture stress on physiological activities of two contrasting wheat genotypes. Indian J Experimental Biology. 32: 594-597.
Stubbs, C. J., Kunduru, B., Bokros, N., Verges, V., Porter, J., Cook, D. D., DeBolt, S., McMahan, C., Sekhon, R. S., & Robertson, D. J. (2023). Moving toward short stature maize: The effect of plant height on maize stalk lodging resistance. Field Crops Research, 300, 109008. https://doi.org/10.1016/j.fcr.2023.109008
Sharma, P., Singh, N., Kamboj, M. C. & Kumar, R. (2023). Understanding the genetics of important quality traits in maize (Zea mays L.) using diverse germplasm by Generation mean analysis. Agriculture Association of Textile Chemical and Critical Reviews, 11(4), 1-2. https://doi.org/10.58321/AATCCReview.2023.11.04.01
Sharma, P., Kamboj, M. C., Singh, N., Kumar, R. & Naveen, K. (2022). Generation mean analysis in maize (Zea mays L.) for yields and yield attributing traits. Indian Journal of Agricultural Sciences 92 (1), 110-117. https://doi.org/10.56093/ijas.v92i1.120854
Said, A. A. (2014). Generation mean analysis in wheat (Triticum aestivum L.) under drought stress conditions. Annals of Agricultural Science 59(2), 177–184. https://doi.org/10.1016/j.aoas.2014.11. 003
Shankar, M., Singh, R., Shahi, J. P., Devesh, P. & Singh, P. (2022). Generation Mean Analysis for Yield and Drought-Related Traits in Maize (Zea mays L.). Current Journal of Applied Science and Technology, 41(22), 30-45. https://doi.org/10.9734/cjast/2022/v41i2231758
Shen, C.-H. (2019). Quantification and analysis of proteins. In C.-H. Shen (Ed.), Diagnostic molecular biology (pp. 187-214). Academic Press. https://doi.org/10.1016/B978-0-12-802823-0.00008-0
Silva, P. C., Sánchez, A. C., Opazo, M. A., Mardones, L. A., & Acevedo, E. A. (2022). Grain yield, anthesis-silking interval, and phenotypic plasticity in response to changing environments: Evaluation in temperate maize hybrids. Field Crops Research, 285, 108583. https://doi.org/10.1016/j.fcr.2022.1 08583
Teja, K. V., Raju, K. K., Reddy, K. R., Sil, P., Rao, M. S., & Gupta, V. K. (2024). Genetic evaluation of heterosis and combining ability of quality protein maize (Zea mays L.) hybrids under terminal heat stress conditions. Agricultural Science Digest, 44(5), 806–815. https://doi.org/10.18805/ag.D-6027
Vidadala, R., Kumar, V., Rout, S., Sil, P., Teja, V., & Rahimi, M. (2024). Genetic analysis of Quality Protein Maize (QPM): A review. Cereal Research Communications. . https://doi.org/10.1007/s42976-024-00552-0
Wang, X., Li, Y., Han, W. et al. (2022). Evaluation of root lodging resistance during whole growth stage at the plant level in maize. Sci Rep 12, 10375 . https://doi.org/10.1038/s41598-022-14159-0
Yadav, S. K., Tiwari, Y. K., Singh, V., Patil, A. A., Shanker, A. K., Lakshmi, N. J., Vanaja, M., & Maheswari, M. (2018). Physiological and biochemical basis of extended and sudden heat stress tolerance in maize. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 88, 249–263. https://doi.org/10.1007/s40011-016-0
791-3
FAOStat. (2022). FAO Stat. FAO, Rome. http://www.fao.org/faostat
Zhai, L., Yang, W., Li, C. et al. (2024). Extraction of maize canopy temperature and variation factor analysis based on multi-source unmanned aerial vehicle remote sensing data. Earth Sci Inform . https://doi.org/10.1007/s12145-024-01363-x
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)
How to Cite
Generation mean analysis in quality protein maize (Zea mays L.) for yield and quality attributes. (2024). Journal of Applied and Natural Science, 16(4), 1758-1770. https://doi.org/10.31018/jans.v16i4.5890
