Makale detayı · 2025
Ultrasound-Assisted Sustainable Processing of Garden Cress Juice: Enhancing Bioactive Compounds and Bioaccessibility through XGBoost Optimization
- Yıl
- 2025
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı ACS Omega
- Katalog eşleşmesi (ISSN) ACS Omega
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
High Resolution Image Download MS PowerPoint Slide This study aimed to improve the functional and nutritional properties of garden cress ( Lepidium sativum ) juice using ultrasound and optimize process parameters by modeling them with advanced machine learning algorithms. Using a Box–Behnken experimental design, the effects of sonication time (8–16 min) and amplitude (60–100%) on total chlorophyll, total phenolic content (TPC), and ferric reducing antioxidant power (FRAP) were investigated. Nonparametric, high-accuracy estimations were made using the XGBoost algorithm. Optimum conditions were determined to be 12 min and 80% amplitude. Under these conditions, TPC (78.44 mg GAE/mL), FRAP (59.80 mg TE/mL), and chlorophyll (7.15 g/100 mL) values were significantly higher than those in control and pasteurized samples ( p < 0.05). HPLC-DAD analysis showed that ultrasound treatment positively impacted the phenolic profile by increasing the release of quercetin, quercetin derivatives, caffeic acid, and chrysin. GC-MS data revealed that volatile aroma compounds (especially 1-hexanol, benzaldehyde, and cinnamaldehyde) were preserved mainly by ultrasound. In vitro digestion simulation showed that total postdigestion recovery rates in ultrasound-treated samples were 34.96% for TPC, 32.50% for chlorophyll, and 28.81% for FRAP, demonstrating a significant increase in bioaccessibility. PCA and hierarchical clustering analyses confirmed a significant biochemical separation of ultrasound-treated samples. The findings indicate that ultrasound technology is a superior method for preserving bioactive compounds, maintaining the aroma profile, and enhancing bioaccessibility compared to heat treatment. This enables data-driven process design. The developed model showed a strong predictive performance under optimal conditions. However, the study is limited by the relatively small data set used for model training.
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