Muhammad Aasim

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Muhammad Aasim (PhD)

Muhammad Aasim

Dean, Faculty of Agricultural Science and Technology, Sivas Science and Technology University, Sivas, Türkiye

Member Advisory Board, Journal of Environmental and Agricultural Sciences 

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Education

Research Interests

Muhammad Asim, Agricultural Biotechnology, Plant Tissue Culture, Phytoremediation, Aquatic Plants, Nanoparticle Applications, Artificial Intelligence Applications in Agriculture and Plant Sciences

Work Experience

Academic Honors and Awards

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Featured Publications

  • Katırcı, R., Muhammad Aasim, G. Deveci and Z. Mustafa. 2024. Comparing quantum machine learning and classical machine learning for in vitro regeneration of cowpea (Vigna unguiculata). Plant Cell, Tissue and Organ Culture. 159: 32. doi: 10.1007/s11240-024-02880-9
  • Sözmen EU, Karaköy T, Muhammad Aasim (2024). Optimizing benzylaminopurine (BAP) and
    naphthalene acetic acid (NAA) concentration for in vitro micropropagation of Goji Berry
    (Lycium barbarum L.) using various optimizing tools. Pak. J. Agri. Sci., Vol. 61(1),
    DOI:10.21162/PAKJAS/24.95
  • Aasim M, Akın F, Ali SA (2024). Synergizing LED Technology and Hydropriming for Intelligent Modeling and Mathematical Expressions to Optimize Chickpea Germination and Growth indices. Journal of Plant Growth Regulation, 43:2340-2359
  • Aasim M, Yıldırım B, Say A, Ali SAA, Aytaç S, Nadeem MA (2024). Artificial Intelligence Models for Validating and Predicting the Impact of Chemical Priming of Hydrogen Peroxide (H2O2) and Light Emitting Diodes on In vitro Grown Industrial Hemp (Cannabis sativa L.).
    Plant Molecular Biology, 114:33
  • Aasim M, Katırcı R, Acar AS, Ali SA (2024). Computing artificial neural network and genetic algorithm for the feature optimization of basal salts and cytokinin-auxin for in vitro organogenesis of royal purple (Cotinus coggygria Scop). Industrial Crops and
    Products, 199, 116718.
  • Mirza, K., Muhammad Aasim, Katırcı, R., KarataÅŸ, M., & Ali, S. A. (2022). Machine Learning and Artificial Neural Networks-Based Approach to Model and Optimize Ethyl Methanesulfonate and Sodium Azide Induced In Vitro Regeneration and Morphogenic Traits of Water Hyssops (Bacopa monnieri L.). Journal of Plant Growth Regulation, 1-15.
  • Aasim, M., Korkmaz, E., Culu, A., Kahveci, B., & Sonmezoglu, O. A. (2023). TiO2 nanoparticle synthesis, characterization and application to shoot regeneration of water hyssop (Bacopa monnieri L. Pennel) in vitro. Biotechnic & Histochemistry, 1-9.
  • Aasim, M., Ali, S. A., Aydin, S., Bakhsh, A., Sogukpinar, C., Karatas, M., … & Aydin, M. E. (2023). Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L. Environmental Science and Pollution Research, 1-12.
  • Baloch, F. S., Altaf, M. T., Bedir, M., Nadeem, M. A., Tatar, M., Karaköy, T., and Muhammad Aasim. (2023). iPBS-retrotransposons variations: DNA fingerprinting and the evaluation of genetic diversity and population structure in international cowpea germplasm. Genetic Resources and Crop Evolution, 1-11.
  • Aasim, M., Akin, F., Ali, S. A., Taskin, M. B., Colak, M. S., & Khawar, K. M. (2023). Artificial neural network modeling for deciphering the in vitro induced salt stress tolerance in chickpea (Cicer arietinum L). Physiology and Molecular Biology of Plants, 1-16.
  • Aasim, M., Ali, S. A., Altaf, M. T., Ali, A., Nadeem, M. A., & Baloch, F. S. (2023). Artificial
    neural network and decision tree facilitated prediction and validation of cytokinin-auxin
    induced in vitro organogenesis of sorghum (Sorghum bicolor L.). Plant Cell, Tissue and
    Organ Culture (PCTOC), 1-14.
  • Baloch FS, Altaf MT, Liaqat W, Bedir M, Nadeem MA, Cömertpay G, Çoban N, Habyarimana
    E, Barutçular C, Cerit I, Ludidi N, Karaköy T, Muhammad Aasim, … (2023) Recent advancements in the breeding of sorghum crop: current status and future strategies for marker-assisted breeding. Front.Genet. 14:1150616. doi: 10.3389/fgene.2023.1150616
  • Aasim M, Ayhan A, Katırcı R, Acar AS, Ali SA (2023). Computing artificial neural network and genetic algorithm for the feature optimization of basal salts and cytokinin-auxin for in vitro organogenesis of royal purple (Cotinus coggygria Scop). Industrial Crops and Products, 199, 116718.
  • Barut, M., Nadeem, M. A., AKGÃœR, Ö., Tansi, L. S., Muhammad Aasim, Altaf, M. T., & BALOCH, F. S. (2022). Medicinal and aromatic plants in the omics era: application of plant breeding and
    biotechnology for plant secondary metabolite production. Turkish Journal of Agriculture and
    Forestry, 46(2), 182-203.
  • Ali, H. H., Zaheer, M. S., Aasim, M., Nadeem, M. A., Ismail, Z., Raza, A., … & Mumtaz, M. Z. (2022). Assessıng Phytotoxıc Impact Of Melılotus Indıcus L. On The Germınatıon And Seedlıng Emergence Of Sorghum Bıcolor L. Under Varıous Salıne Condıtıons. Pak. J. Bot, 54(4), 1191-1198.
  • Aasim, M., Katırcı, R., Akgur, O., Yildirim, B., Mustafa, Z., Nadeem, M. A., … & Yılmaz, G. (2022). Machine learning (ML) algorithms and artificial neural network for optimizing in vitro germination and growth indices of industrial hemp (Cannabis sativa L.). Industrial Crops and Products, 181, 114801.
  • Kirtis, A., Aasim, M., & Katırcı, R. (2022). Application of artificial neural network and machine learning algorithms for modeling the in vitro regeneration of chickpea (Cicer arietinum L.). Plant Cell, Tissue and Organ Culture (PCTOC), 1-12.
  • Akgur, O., Muhammad Aasim. (2022). Deciphering the iPBS retrotransposons based genetic diversity of nanoparticles induced in Vitro seedlings of industrial hemp (Cannabis sativa L.). Molecular Biology Reports, 1-9.
  • Aasim, M., Katirci, R., Baloch, F. S., Mustafa, Z., Nadeem, M. A., Ali, S. A., … & Chung, Y. S. 2022. Innovation in the breeding of common bean through a combined approach of in vitro regeneration and machine learning algorithms. Frontiers in Genetics, 1592.
  • Aasim M, Umer EM, Karim A (2008). Yield and competition indices of intercropping Cotton
    (Gossypium hirsutum L.) using different planting pattern. Tarim Bilimleri Dergisi (Journal of
    Agricultural Sciences), 14(4), 326-333
  • Sahin-demirbag N, Kendir H, Muhammad Aasim. (2008). Yaygın mürdümük (Lathyrus sativus L.)’te adventif sürgün rejenerasyonu, Tarım Bilimleri Dergisi (Journal of Agricultural Sciences), 14(3), 297-302
  • Demirbag N, Kendir H, Khawar K, Muhammad Aasim. (2008). In vitro plant regeneration from Hungarian vetch (Vicia pannonica Crantz) using cotyledonary node explants. Biotechnology & Biotechnological Equipments, 22(4), 929-932
  • Sahin-Demirbag, N., Kendir, H., Khawar, K. M., and Muhammad Aasim, M. 2008. In vitro regeneration of Turkish endemic Trifolium pannonicum JACQ. Subsp. elongatum (WILLD). Biotechnology & Biotechnological Equipments, 22(4), 921-924
  • Kendir H, Sahin-Demirbag N, Khawar KM, and Muhammad Aasim. (2008). In vitro plant regeneration from Narbon Vetch (Vicia narbonensis L.) using cotyledonary node explants. African Journal of Biotechnology, 7(14), 2491-2494
  • Aasim M, Khawar KM, Özcan S (2008). In vitro micropropagation from shoot meristems of
    Turkish Cowpea (Vigna unguiculata L.). Bangladesh Journal of Botany, 37(2), 149-154
  • Aasim M, Khawar KM, Özcan S (2008). In vitro regeneration of Red Squill Urginea maritima
    (L.) BAKER. using Thidiazuron. Biotechnology & Biotechnological Equipments, 22(4), 925-
    928

Research Keywords

Muhammad Asif Sajjad, Agricultural Biotechnology, Plant Tissue Culture, Phytoremediation, Aquatic Plants, Nanoparticle Applications, Artificial Intelligence Applications in Agriculture and Plant Sciences

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