EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 344 (2025) EPJ Web Conf., 344 (2025) 01030 References
Open Access
Issue
EPJ Web Conf.
Volume 344, 2025
AI-Integrated Physics, Technology, and Engineering Conference (AIPTEC 2025)
Article Number 01030
Number of page(s) 9
Section AI-Integrated Physics, Technology, and Engineering
DOI https://doi.org/10.1051/epjconf/202534401030
Published online 22 December 2025
  1. A. Amzeri, S. Suhartono, S. Fatimah, G. Pawana, K. P. W. Sukma, Combining ability analysis in maize diallel hybrid populations under optimum and drought stress conditions. SABRAO J Breed Genet. 56, 476–492 (2024). https://doi.org/10.54910/sabrao2024.56.2.3 [Google Scholar]
  2. S. Fatimah, A. Amzeri, M. Syafii, Y. Purwaningsih, Screening of red rice (Oryza sativa L.) landraces for drought tolerance at early stages using PEG 6000. Agrivita. 45, 199–208 (2023). https://doi.org/10.17503/agrivita.v45i2.3723 [Google Scholar]
  3. H. Kustanto, F. Hendrayana, A study on the specific combining ability in several inbred lines of maize. PLANTA TROPIKA. 11, 141–149 (2023). https://doi.org/10.18196/pt.v11i2.14026 [Google Scholar]
  4. A. Amzeri, K. Badami, S. B. Santoso, K. P. Sukma, Morphological and molecular characterization of maize lines tolerance to drought stress. Biodiversitas. 23, 5844–5853 (2022). https://doi.org/10.13057/biodiv/d231138 [Google Scholar]
  5. G. B. Adu, B. Badu-Apraku, R. Akromah, Strategies for selecting early maturing maize inbred lines for hybrid production under low soil nitrogen and Striga infestation. Agronomy. 11, (2021). https://doi.org/10.3390/agronomy [Google Scholar]
  6. T. Mahmood et al., Genetic potential and inheritance pattern of phenological growth and drought tolerance in cotton (Gossypium hirsutum L.). Front Plant Sci. 12, (2021). https://doi.org/10.3389/fpls.2021.705392 [Google Scholar]
  7. L. Muntean, A. Ona, I. Berindean, I. Racz, S. Muntean, Maize breeding: From domestication to genomic tools. Agronomy. 12, (2022). https://doi.org/10.3390/agronomy12102365 [Google Scholar]
  8. G. M. Di Pasquale et al., Morphological and genetic characterization of maize landraces adapted to marginal hills in North-West Italy. Plants. 13, (2024). https://doi.org/10.3390/plants13071030 [Google Scholar]
  9. R. Khatun, M. I. Uddin, M. M. Uddin, M. T. H. Howlader, M. S. Haque, Analysis of qualitative and quantitative morphological traits related to yield in country bean (Lablab purpureus L. sweet) genotypes. Heliyon. 8, (2022). https://doi.org/10.1016/j.heliyon.2022.e11631 [Google Scholar]
  10. B. K. Kirchoff, S. J. Richter, D. L. Remington, Characters as groups: A new approach to morphological characters in phylogenetic analysis. Taxon. 56, 479–492 (2007). https://doi.org/10.1002/tax.562018 [Google Scholar]
  11. Y. Limbongan, R. Sjahril, A. M. Pata’dungan, T. Y. Parari, Genetic performance, heritability, and correlation of traits in new plant type of rice lines for highland ecosystem. Reproduction and Breeding. 4, 203–211 (2024). https://doi.org/10.1016/j.repbre.2024.08.002 [Google Scholar]
  12. A. Amzeri, K. Badami, P. Gita, M. A. Syah, B. Setiadi Daryono, Phenotypic and genetic diversity of watermelon (Citrullus lanatus) in East Java, Indonesia. Biodiversitas. 22, (2021). https://doi.org/10.13057/biodiv/d221161 [Google Scholar]
  13. A. P. Marwan, A. Munandar, A. Anwar, A. Syarif, P. K. Dewi Hayati, Variability, heritability, and performance of 28 West Sumatran upland rice cultivars, Indonesia. Biodiversitas. 23, 1058–1064 (2022). https://doi.org/10.13057/biodiv/d230249 [Google Scholar]
  14. T. Chen et al., Characterization and comprehensive evaluation of phenotypic characters in wild Camellia oleifera germplasm for conservation and breeding. Front Plant Sci. 14, (2023). https://doi.org/10.3389/fpls.2023.1052890 [Google Scholar]
  15. S. Natesan et al., Identification of drought-tolerant maize inbred lines through morphophysiological traits. Madras Agricultural Journal. 111, 130 (2024). https://doi.org/10.29321/MAJ.10.0MMA27 [Google Scholar]
  16. L. Gaier, E. M. Poetsch, W. Graiss, A. Klingler, M. Herndl, B. Krautzer, The effect of drought on agronomic and plant physiological characteristics of cocksfoot (Dactylis glomerata L.) cultivars. Agriculture. 14, (2024). https://doi.org/10.3390/agriculture14071116 [Google Scholar]
  17. R. Fischer, R. Maurer, Drought resistance in spring wheat cultivars. I. Grain yield response. Aust. J. Agric. Res. 29, 897–912 (1978) [Google Scholar]
  18. S. Sheoran, Recent advances for drought stress tolerance in maize (Zea mays L.). Front Plant Sci. 13, (2022). https://doi.org/10.3389/fpls.2022.872566 [Google Scholar]
  19. V. S. Weber, A. E. Melchinger, C. Magorokosho, D. Makumbi, M. Bänziger, G. N. Atlin, Efficiency of managed-stress screening of elite maize hybrids under drought and low nitrogen for yield under rainfed conditions in Southern Africa. Crop Sci. 52, 1011–1020 (2012). https://doi.org/10.2135/cropsci2011.09.0486 [Google Scholar]
  20. A. R. Hallauer, M. C. Carena, J. B. M. Filho, Quantitative Genetics in Maize Breeding. Springer, London (2010) [Google Scholar]
  21. R. E. Walpole, Introduction of Statistic. 3rd ed., MacMillan Publishing Company, New York (1982) [Google Scholar]
  22. J. P. A. da Silva, J. M. S. Viana, Efficiency of genomic selection for developing superior pure lines. Agronomy. 15, 2247 (2025). https://doi.org/10.3390/agronomy15102247 [Google Scholar]
  23. M. A. Malek, M. Y. Rafii, M. Shahida Sharmin Afroz, U. K. Nath, M. M. A. Mondal, Morphological characterization and assessment of genetic variability, character association, and divergence in soybean mutants. Scientific World Journal. (2014). https://doi.org/10.1155/2014/968796 [Google Scholar]
  24. S. B. Priyanto, R. Effendi, B. Zainuddin, Genetic variability, heritability, and path analysis for agronomic characters in hybrid maize. Jurnal Kultivasi. 22, 26–35 (2023). http://dx.doi.org/10.24198/kultivasi.v22i1.38807 [Google Scholar]
  25. P. Schmidt, Estimating heritability in plant breeding programs. (2019), 1–76 (2019) [Google Scholar]
  26. J. Ren, X. Ji, C. Wang, J. Hu, G. Nervo, J. Li, Variation and genetic parameters of leaf morphological traits of eight families from Populus simonii × P. nigra. Forests. 11, (2020). https://doi.org/10.3390/f11121319 [Google Scholar]
  27. C. Liu et al., Revisiting heritability accounting for shared environmental effects and maternal inheritance. Hum Genet. 134, 169–179 (2015). https://doi.org/10.1007/s00439-014-1505-6 [Google Scholar]
  28. H. Maulana, Y. Maxiselly, Y. Yuwariah, D. Ruswandi, Heritability and selection using GGE biplots and the sustainability index (SI) of maize mutants under different cropping systems in upland. Sustainability. 15, (2023). https://doi.org/10.3390/su15086824 [Google Scholar]
  29. R. Islam, Md. S. Hossain, S. Aktar, D. C. Sharma, S. Islam, Md. O. Kayess, Genetic and multivariate analysis of some local and advanced selected Aman rice genotypes under Bangladesh condition. Discover Plants. 2, (2025). https://doi.org/10.1007/s44372- 025-00352-8 [Google Scholar]
  30. W. A. Abdelrady et al., Evaluating physiological and yield indices of Egyptian barley cultivars under drought stress conditions. Agronomy. 14, (2024). https://doi.org/10.3390/agronomy14112711 [Google Scholar]
  31. A. Wasae, Evaluation of drought stress tolerance based on selection indices in haricot bean varieties exposed to stress at different growth stages. International Journal of Agronomy. (2021). https://doi.org/10.1155/2021/6617874 [Google Scholar]
  32. A. Amzeri, S. B. Santoso, F. Adiputra, S. Khoiri, K. Badami, A. S. Umam, Combining ability and heterotic effects of maize (Zea mays) lines for drought tolerance using the line × tester method. Biodiversitas. 26, 748–760 (2025). https://doi.org/10.13057/biodiv/d260223 [Google Scholar]
  33. J. L. Neyhart, A. J. Lorenz, K. P. Smith, Multi-trait improvement by predicting genetic correlations in breeding crosses. G3 (Genes, Genomes, Genetics). 9, 3153–3165 (2019). https://doi.org/10.1534/g3.119.400406 [Google Scholar]
  34. [34]A. Kovincic et al., Efficiency of biological typing methods in maize hybrid genetic purity estimation. Genes. 14, (2023). https://doi.org/10.3390/genes14061195 [Google Scholar]
  35. A. Basak, S. Man, K. Dasgupta, Conventional methods of plant breeding: Principles and techniques. Genetic Horizons: Advancement in Plant Breeding. 1–38 (2025). https://doi.org/10.58532/nbennurghch1 [Google Scholar]
  36. M. Farid et al., Evaluation of high yielding hybrid lines of Unhas corn based on a systematic approach and genetic analysis. Asian J Plant Sci. 23, 81–87 (2024). https://doi.org/10.3923/ajps.2024.81.87 [Google Scholar]
  37. M. F. Scott et al., Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding. Heredity. 125, (2020). https://doi.org/10.1038/s41437-020-0336-6 [Google Scholar]
  38. J. M. M. Kuhn, M. Jakobsson, T. Günther, Estimating genetic kin relationships in prehistoric populations. PLoS One. 13, (2018). https://doi.org/10.1371/journal.pone.0195491 [Google Scholar]
  39. M. S. Abd El-Aty et al., Generation mean analysis, heterosis, and genetic diversity in five Egyptian faba beans and their hybrids. Sustainability. 15, (2023). https://doi.org/10.3390/su151612313 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.