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Access type: UnknownAuthor: search.filters.author.Mansamut, Chaiyut

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    Modelling the Effect of Types and Concentrations of Sugar on Hardness and Overall Acceptability of Freeze-Dried “Sáp” Coconut Meat: An Artificial Intelligent Approach
    (2025-01-01)
    Loan, Le Thi Kim
    ;
    Chi, Huynh Thi Kim
    ;
    Mansamut, Chaiyut
    ;
    Van Tai, Ngo
    Coconut is one of the common plants in Southeast Asia countries, which could further develop into various products. This study is aimed to study the effect of soaking conditions (types and concentrations of sugar) on the hardness and acceptance score of freeze-dried meat of “Sáp” coconut variety in Vietnam. Artificial neural network (ANN) model was used for predicting and modelling. A total of 540 datasets with two input variables and two output responses were divided into 70% of the training dataset, 15% of the validation dataset, and 15% of the testing dataset. ANN model was successfully forecasted the impact of soaking conditions on physical hardness and eating quality of product. The high agreement between actual and ANN’s predicted values was found with high coefficient determination (R<sup>2</sup> > 0.9). Moreover, the correlation between the hardness and acceptability of product also provided. This information could be supported for further study to optimize the process of producing high-quality and sensory freeze-dried coconut meat.
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    Enhancing antioxidant extraction efficiency from red dragon fruit peel by green approach using novel optimization technique
    (2025-01-01)
    Loan, Le Thi Kim
    ;
    Thao, Le Thi Nhu
    ;
    Vinh, Bui The
    ;
    Mansamut, Chaiyut
    ;
    Tai, Ngo Van
    This study is the first application of a combined sonication and enzyme extraction technique as green technology to recover biological compounds from the peel of red-fleshed dragon fruit, utilizing Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). The peel of dragon fruit had sonication pretreatment for 10–30 min (X<inf>1</inf>), followed by hydrolysis using 0.1 % Pectinex Ultra SP-L enzyme at temperatures ranging from 30 to 60 °C (X<inf>2</inf>) for a duration of 60–120 min (X<inf>3</inf>). The Box-Behnken design was employed to structure the experiment. The levels of polyphenol, betacyanin, and antioxidant activity in the extract were utilized to assess the efficacy of the extraction method. The research demonstrated a substantial enhancement in efficiency by the application of ultrasound pretreatment during the enzymatic hydrolysis of dragon fruit peel. The study identified the ideal parameters for the extraction process using the ANN-GA approach, which include an ultrasonic duration of 27.5 min, an enzyme incubation temperature of 47.1 °C, and an enzyme incubation duration of 135.1 min. Under these conditions, the extract exhibited a total phenolic content of 165.34 mg GAE/g peel weight, betacyanin content of 131.87 mg/100 g peel weight, and an antioxidant activity of 0.92 mg TE/100 g by using DPPH radical scavenging activity assay. The research demonstrated that dual treatment enhances the extraction process of chemicals from by-products, particularly dragon fruit peel. The study established a foundation for future research on the utilization and integration of effective extraction technologies to enhance the quality of extracts for use in the food sector.