The effect of drying methods on chlorophyll, polyphenol, flavonoids, phenolic compounds contents, color and sensory properties, and in vitro antioxidant and anti-diabetic activities of dried wild guava leaves

Abstract

Wild guava (Psidium guajava L.) commonly grows in tropical forests, and its leaves have long been used by Asian ethnic minorities as herbal tea and traditional medicine. This study aimed to evaluate the effects of different drying methods (sun drying, hot air drying, microwave drying, vacuum drying, and freeze drying) on the retention of bioactive compounds, antioxidant, and antidiabetic activities of wild guava leaves collected in Vietnam. The results showed that drying methods significantly affected the retention of bioactive compounds, biological activities, and color of guava leaves. The freeze-dried leaves had the highest levels of total phenolic content (173.25 ± 0.68 mg gallic acid equivalent g⁻¹ dw), total flavonoid content (24.46 ± 0.78 mg QE g⁻¹ dw), antioxidant capacity, and in vitro antidiabetic activity compared with others, while sun-dried leaves showed the lowest values of those parameters. The principal component analysis (PCA) showed a strong correlation among biological activities and contents of bioactive compounds, including antioxidant activity, in vitro antidiabetic activity, total phenolic content, and total flavonoid content (r² = 0.999, p < 0.0001). Specifically, the biological activities strongly and positively correlated epicatechin, rutin, chlorogenic acid, catechin, and gallic acid. Freeze-dried guava leaves had the highest positive scores, followed by hot air-dried, microwave-dried, vacuum-dried, and sun-dried samples. FD treatment sample also exhibited better color and sensory properties than others. Consequently, freeze drying is recommended as the most suitable drying method for preserving the bioactive compounds and sensory characteristics of dried wild guava leaves.

Keywords:

• Wild guava leaves
• drying methods
• phenolic compounds
• antioxidant
• in vitro antidiabetic

Authors’ contribution statement

Quang-Vinh Nguyen: Conceptualization, Methodology, Data analysis, writing – original draft, Investigation, Formal analysis, Validation, Visualization, Writing – review & editing. Bich-Huyen Bui Thi: Investigation, Formal analysis. Minh-Trung Nguyen: Investigation, Formal analysis. Manh-Dung Doan: Investigation, Formal analysis. Minh-Tam Le: Investigation, Formal analysis. Minh-Dinh Tran: Investigation, Formal analysis. Anh-Dzung Nguyen: Validation, Visualization, Writing – review & editing. Thi-Huyen Nguyen: Investigation, Formal analysis. Van-Cuong Tran, Thi-Dao Nguyen: Investigation, Formal analysis. Van-Chuyen Hoang: Validation, Visualization, Writing – review & editing.

Disclosure statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Additional information

Funding

This research was funded by the Ministry of Education and Training under grant number of B2021-TTN-03 and partially funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 106.99-2020.17. Minh Trung Nguyen was funded by Vingroup JSC and supported by the Master, PhD Scholarship programme of Vingroup Innovation Foundation (VINIF), Institute of Big Data, Code VINIF.2021.TS.157. This research was partly supported by Ho Chi Minh City University of Technology and Education (HCMUTE), Vietnam.