Prediction of drying kinetics and energy consumption values of purple carrots dried in a temperature-controlled microwave dryer by Decision Tree, Random Forest and Ada Boost approaches
Yazarlar (6)
Necmettin Erbakan Üniversitesi, Türkiye
Türkiye
Türkiye
Doç. Dr. Muhammed TAŞOVA
Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Türkiye
Türkiye
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Chemometrics and Intelligent Laboratory Systems |
| Dergi ISSN | 0169-7439 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q1 |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2025 |
| DOI Numarası | 10.1016/j.chemolab.2025.105352 |
| Makale Linki | https://www.sciencedirect.com/science/article/pii/S0169743925000371 |
| Özet |
| In the study, primarily purple carrot slices were reduced from 6.13±0.05 g moisture/g dry matter moisture value to 0.14±0.018 g moisture/g dry matter value. Among the models, the drying rates were best estimated by the Midilli-Küçük (R2: 0.9993) model. The lowest energy consumption was determined in the drying process at 70 ºC. Estimation of intermediate values is very useful because experimental studies can be length and expensive. Sometimes, even if cost is not a concern, long-term experimental studies and the high number of experiment repetitions increase the importance of estimation methods for researchers. The decision tree, random forest and ada boost methods, which are fast operating methods, were used as estimation methods in this study. MAPE and R2 success values are expressed for all three methods. The Decision tree method was found to be the most successful technique with the highest R2 value (0.96) and the lowest MAPE value (0.03). |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 9 |