| Makale Türü |
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| Dergi Adı | Frontiers in Genetics (Q1) | ||
| Dergi ISSN | 1664-8021 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 08-2022 |
| Kabul Tarihi | 12-04-2026 | Yayınlanma Tarihi | – |
| Cilt / Sayı / Sayfa | 13 / 897696 / 1–13 | DOI | 10.3389/fgene.2022.897696 |
| Makale Linki | http://dx.doi.org/10.3389/fgene.2022.897696 | ||
| Özet |
| Common bean is considered a recalcitrant crop for in vitro regeneration and needs a repeatable and efficient in vitro regeneration protocol for its improvement through biotechnological approaches. In this study, the establishment of efficient and reproducible in vitro regeneration followed by predicting and optimizing through machine learning (ML) models, such as artificial neural network algorithms, was performed. Mature embryos of common bean were pretreated with 5, 10, and 20 mg/L benzylaminopurine (BAP) for 20 days followed by isolation of plumular apice for in vitro regeneration and cultured on a post-treatment medium containing 0.25, 0.50, 1.0, and 1.50 mg/L BAP for 8 weeks. Plumular apice explants pretreated with 20 mg/L BAP exerted a negative impact and resulted in minimum shoot regeneration frequency and shoot count, but produced longer shoots. All output variables (shoot regeneration frequency, shoot counts, and shoot length) increased significantly with the enhancement of BAP concentration in the post-treatment medium. Interaction of the pretreatment × post-treatment medium revealed the need for a specific combination for inducing a high shoot regeneration frequency. Higher shoot count and shoot length were achieved from the interaction of 5 mg/L BAP × 1.00 mg/L BAP followed by 10 mg/L BAP × 1.50 mg/L BAP and 20 mg/L BAP × 1.50 mg/L BAP. The evaluation of data through ML models revealed that R 2 values ranged from 0.32 to 0.58 (regeneration), 0.01 to 0.22 (shoot counts), and 0.18 to 0.48 (shoot length). On the other hand, the mean squared error values ranged from 0.0596 to 0.0965 for shoot regeneration … |
| Anahtar Kelimeler |
| machine learning algorithms | artificial neural network | in vitro regeneration | plumular apices | coefficient of determination | mean squared error |
| Atıf Sayıları | |
| Google Scholar | 35 |
| Web of Science | 25 |
| Dergi Adı | Frontiers in Genetics |
| Yayıncı | Frontiers Media SA |
| Açık Erişim | Evet |
| E-ISSN | 1664-8021 |
| CiteScore | 6,2 |
| SJR | 0,863 |
| SNIP | 0,745 |