Maize, an expanding grain crop in Bangladesh, faces high food and feed demand. However, domestic output is insufficient to meet demand, necessitating exports from other countries. Developing high-yielding cultivars is critical to meeting the national need for maize, and nutritional value should also be considered. This study aims to assess the protein content and yield of twenty maize lines by estimating the mean performance of twenty lines with fifteen quantitative characters and protein content, as well as measuring genetic variability factors, correlation coefficients, and path coefficients. The experiment was conducted at Bangladesh Agricultural University, Genetics and Plant Breeding Farm. The results of the analysis showed a significant difference at 0.1% level for most of the characters except cob length, cob diameter, and leaf number per plant in the analysis of variance. Finally, L3 (489.33 g), L10 (468.39 g), L13 (458.66 g), L9 (452 g), L4 (439 g) were evaluated as high yielding and L4 (12.51%), L18 (12.37%), L10 (12.57%), L7 (12.24%), L20 (12.23%), L3 (11.83%) were rich with protein content. In genetic variance analysis, plant height, cob weight, 1000 kernel weight, and protein content showed moderate GCV and PCV values, and cob weight per plant showed high GCV and PCV. Additive genetic advance deciding on plant height, cob weight, yield per plant, and protein content as high heritability along with GAM was observed for these traits. Correlation coefficient and path analysis showed that cob weight, diameter, and 1000 kernel weight positively contributed to yield per plant. Therefore, these parameters should be considered for further improvement of the lines.
References
[1]
Larkins, B.A., Lending, C.R. and Wallace, J.C. (1993) Modification of Maize-Seed-Protein Quality. The American Journal of Clinical Nutrition, 58, 264S-269S. https://doi.org/10.1093/ajcn/58.2.264S
[2]
Bangladesh Bureau of Statistics (2023) Statistical Yearbook of Bangladesh 2022. Bangladesh Bureau of Statistics.
[3]
(2024) BD Targets Ambitious 5.81m Tonne Maize Output after Record Yield. The Financial Express. https://thefinancialexpress.com.bd/economy/bd-targets-ambitious-581m-tonne-maize-output-after-record-yield
[4]
Food and Agriculture Organization of the United Nations (FAO) (2025) Country Brief: Bangladesh. Global Information and Early Warning System (GIEWS). https://www.fao.org/giews/countrybrief/country.jsp?code=BGD&form=MG0AV3
[5]
Maqbool, M.A., Beshir Issa, A. and Khokhar, E.S. (2021) Quality Protein Maize (QPM): Importance, Genetics, Timeline of Different Events, Breeding Strategies and Varietal Adoption. Plant Breeding, 140, 375-399. https://doi.org/10.1111/pbr.12923
[6]
Fufa, H., Akalu, G., Wondimu, A., Taffesse, S., Gebre, T., Schlosser, K., et al. (2003) Assessment of Protein Nutritional Quality and Effects of Traditional Processes: A Comparison between Ethiopian Quality Protein Maize and Five Ethiopian Adapted Normal Maize Cultivars. Food Nahrung, 47, 269-273. https://onlinelibrary.wiley.com/doi/abs/10.1002/food.200390063 https://doi.org/10.1002/food.200390063
[7]
Hossain, M., Khan, M.H. and Pramanik, M. (2015) Socio-Economic Impacts on Adoption of Quality Protein Maize (QPM) Using Organic Mulches in Riverine Chars of Bangladesh. European Academic Research, 3, 4240-4242. https://www.bas.org.bd/storage/app/uploads/public/62e/790/4fc/62e7904fc76c6763723223.pdf?form=MG0AV3
[8]
Billah, M.M., Hassan, L., Matin, M.Q.I., Talukder, M.Z.A. and Alam, M.K. (2021) Genetic Diversity for Yield and Yield Contributing Characters of Short Statured Maize Inbred Lines. American Journal of Plant Sciences, 12, 934-945. https://www.scirp.org/journal/paperinformation?paperid=110230 https://doi.org/10.4236/ajps.2021.126063
[9]
Posit Team (2023) RStudio: Integrated Development Environment for R. Posit Software. http://www.posit.co/
[10]
Popat, R. and Banakara, K. (2020) Doebioresearch, Analysis of Design of Experiments for Biological Research. R Package v0.1.0. https://CRAN.R-project.org/package=doebioresearch https://doi.org/10.32614/CRAN.package.doebioresearch
[11]
Popat, R., Patel, R. and Parmar, D. (2020) Variability: Genetic Variability Analysis for Plant Breeding Research. R Package v0.1.0. https://CRAN.R-project.org/package=variability https://doi.org/10.32614/CRAN.package.variability
[12]
Neuwirth, E. (2022) RColorBrewer: ColorBrewer Palettes. R Package v 1.1-3. https://CRAN.R-project.org/package=RColorBrewer
[13]
Peterson, B.G. and Carl, P. (2020) Performance Analytics: Econometric Tools for Performance and Risk Analysis. R package v2.0.4. https://CRAN.R-project.org/package=PerformanceAnalytics
[14]
Wei, T.Y. and Simko, V. (2021) R Package ‘Corrplot’: Visualization of a Correlation Matrix v0.92. https://github.com/taiyun/corrplot
[15]
Shtylla, B., Pikuli, K., Morava, K., Karapanci, N. and Zhidro, N. (2024) Determination of Proteins by the Kjeldahl Method in CEREALS of the markets in Korça City. Journal of Agriculture and Sustainable Rural Development, 2, 26-33. https://doi.org/10.62792/ut.jasrd.v2.i3-4.p2663
[16]
Dogar, M.W., Hussain, Z., Ashraf, M.I. and Naveed, M. (2023) Evaluation of Genetic Variability in Maize (Zea mays L.) Based on Yield and Its Attributed Traits. Asian Journal of Biotechnology and Genetic Engineering, 6, 200-210. https://journalajbge.com/index.php/AJBGE/article/view/115
[17]
Beulah, G., Marker, S. and Rajasekhar, D. (2018) Assessment of Quantitative Genetic Variability and Character Association in Maize (Zea mays L.). Journal of Pharmacognosy and Phytochemistry, 7, 2813-2816.
[18]
Magar, B.T., Acharya, S., Gyawali, B., Timilsena, K., Upadhayaya, J. and Shrestha, J. (2021) Genetic Variability and Trait Association in Maize (Zea mays L.) Varieties for Growth and Yield Traits. Heliyon, 7, e07939. https://www.sciencedirect.com/science/article/pii/S2405844021020429 https://doi.org/10.1016/j.heliyon.2021.e07939
[19]
Bartaula, S., Panthi, U., Timilsena, K., Sharma, S. and Shrestha, J. (2019) Variability, Heritability and Genetic Advance of Maize (Zea mays L.) Genotypes. Research in Agriculture, Livestock and Fisheries, 6, 163-169. https://doi.org/10.3329/ralf.v6i2.42962
[20]
Korsa, F., Dessalegn, O., Zeleke, H. and Petros, Y. (2024) Genetic Variability for the Yield and Yield-Related Traits in Some Maize (Zea mays L.) Inbred Lines in the Central Highland of Ethiopia. International Journal of Agronomy, 2024, Article ID: 9721304. https://onlinelibrary.wiley.com/doi/abs/10.1155/2024/9721304 https://doi.org/10.1155/2024/9721304
[21]
Kharel, R., Ghimire, S., Ojha, B. and Koirala, K. (2017) Estimation of Genetic Parameters, Correlation and Path Coefficient Analysis of Different Genotypes of Maize (Zea Mays L.). International Journal of Agriculture Innovations and Research, 6, 191-195.
[22]
Kebede, M.B. and Gebissa, D. (2020) Genetic Variability of Maize (Zea mays L.) Genotypes on Some Yield and Yield Components at Haramaya, Eastern Ethiopia. Turkish Journal of Agriculture—Food Science and Technology, 8, 1840-1845. https://www.agrifoodscience.com/index.php/TURJAF/article/view/3423 https://doi.org/10.24925/turjaf.v8i9.1840-1845.3423
[23]
Bello, O.B., Ige, S.A., Azeez, M.A., Afolabi, M.S., Abdulmaliq, S.Y. and Mahamood, J. (2012) Heritability and Genetic Advance for Grain Yield and Its Component Characters in Maize (Zea mays L.). International Journal of Plant Research, 2, 138-145. http://article.sapub.org/10.5923.j.plant.20120205.01.html https://doi.org/10.5923/j.plant.20120205.01
[24]
Mahesh, G., Lal, G., Thupakula, V.K., Subba Reddy, Y.V. and Nalla, S. (2022) Correlation and Path Coefficient Analysis for Grain Yield Components in Maize (Zea mays L.). International Journal of Plant & Soil Science, 34, 24-36.
[25]
Kumar, G.P., Sunil, N., Sekhar, J.C. and Chary, D.S. (2024) Character Association and Path Coefficient Analysis to Determine Interrelationships among Grain Yield and Its Components in Maize Genotypes (Zea mays L.). Journal of Scientific Research and Reports, 30, 275-283. https://journaljsrr.com/index.php/JSRR/article/view/1878 https://doi.org/10.9734/jsrr/2024/v30i31878
[26]
Tripathi, H., Yadav, R.K., Singh, L., Singh, H.C., Shweta Saini, P.K., Dwivedi, S. and Pandey, P. (2023) Correlation and Path Coefficient Analyses for Grain Yield and Its Contributing Traits in Quality Protein Maize (Zea mays L.). Biological Forum—An International Journal, 15, 47-54.
[27]
Dipak, A., Patel, R.P., Parmar, D.J. and Sondarava, P. (2022) Genotypic and Phenotypic Correlation Coefficient Study to Identify Best Yield and Yield Attributing Trait for Selection in Maize (Zea mays L.). International Journal of Current Microbiology and Applied Sciences, 11, 368-374. https://www.ijcmas.com/abstractview.php?ID=22769&vol=11-1-2022&SNo=44 https://doi.org/10.20546/ijcmas.2022.1101.044
[28]
Gazal, A., Ahmed, Z., Lone, A., Yousuf, N. and Gulzar, S. (2018) Studies on Maize Yield under Drought Using Correlation and Path Coefficient Analysis. International Journal of Current Microbiology and Applied Sciences, 7, 516-521. https://doi.org/10.20546/ijcmas.2018.701.062
[29]
Rathod, S.D., Shinde, G.C. and Shinde, S.D. (2021) Genetic Variability and Path Coefficient Analysis Studies in Forage Maize Genotypes (Zea mays L.). Journal of Pharmacognosy and Phytochemistry, 10, 2-8.
[30]
Singh, D., Kumar, A., Kumar, R., Singh, S.K., Kushwaha, N. and Mohanty, T.A. (2020) Correlation and Path Coefficient Analysis for Yield Contributing Traits in Quality Protein Maize (Zea mays L.). Current Journal of Applied Science and Technology, 39, 91-99. https://doi.org/10.9734/cjast/2020/v39i2530889
[31]
Aman, J., Bantte, K., Alamerew, S. and Sbhatu, D.B. (2020) Correlation and Path Coefficient Analysis of Yield and Yield Components of Quality Protein Maize (Zea mays L.) Hybrids at Jimma, Western Ethiopia. International Journal of Agronomy, 2020, Article ID: 9651537. https://onlinelibrary.wiley.com/doi/abs/10.1155/2020/9651537 https://doi.org/10.1155/2020/9651537
[32]
Badu-Apraku, B., Fakorede, M.A., Annor, B. and Talabi, A.O. (2018) Improvement in Grain Yield and Low-Nitrogen Tolerance in Maize Cultivars of Three Eras. Experimental Agriculture, 54, 805-823. https://doi.org/10.1017/S0014479717000394
