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Author: search.filters.author.Khanthong, Thitirat

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    Sustainable Active Packaging: Essential Oil-Enhanced Rice Starch Film for Preserving Fried Foods
    (2025-12-01)
    Chysirichote, Teerin
    ;
    Khanthong, Thitirat
    ;
    Khampanin, Nonthiya
    This study develops a biodegradable, edible packaging film made from acetylated rice starch and enhanced with essential oils (EOs) to improve food preservation. Three EOs, including ginger, holy basil, and lemongrass, were selected for their well-documented antimicrobial and antioxidant activities as well as their relevance to regional culinary applications. The combination of EO-based antimicrobial properties with modified starch extended the shelf life of a typical fried food. The effects of acetylation at degrees of substitution (DS) of 1.0, 1.8, and 3.0 on the film’s physical, mechanical, and barrier properties were investigated. The film with DS 1.8 exhibited optimal properties, including low water solubility (15.3 %), low water vapor permeability (10 × 10⁻¹¹ g·m⁻¹·s⁻¹·Pa⁻¹), and high flexibility and tensile strength. The optimized acetylated rice starch film (ARSF) with the selected EOs was then evaluated for antimicrobial and antioxidant activities. Among the tested oils, lemongrass EO showed the strongest antibacterial and antifungal activities, supporting its emphasis as the most promising candidate for improving product shelf life. Predictive modeling demonstrated that the application of the optimized EO-enhanced ARSF (EO-ARSF) significantly prolonged the shelf life of pork crackling stored at 30 °C, increasing it from 37.8 days with ARSF alone to 57.7 days with EO-ARSF. These results emphasize the attractiveness of EO-ARSF, particularly lemongrass-enriched films, as a sustainable, industrially applicable packaging material for fried foods, combining functional preservation properties with eco-friendly design.
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    Detection of Hardening in Mangosteens Using near-Infrared Hyperspectral Imaging
    (2024-04-01)
    Workhwa, Saranya
    ;
    Khanthong, Thitirat
    ;
    Manmak, Napatsorn
    ;
    Thompson, Anthony Keith
    ;
    Teerachaichayut, Sontisuk
    Mangosteens can develop a postharvest physiological disorder, called “hardening”, which affects their marketability and is not detectable using visual inspection. The hardening disorder of mangosteens was determined by firmness value using the texture analyzer. Near-infrared hyperspectral imaging (NIR-HSI) in the region of 935–1720 nm was tested as a possible rapid and non-destructive method to detect this disorder. The spectra from a region of interest of mangosteens were acquired and used for analysis. Calibration models for firmness of a similarly sized group and a mixed-size group were established using partial least squares regression (PLSR) and support vector machine regression (SVMR). Chemometric algorithms were investigated in order to determine the optimal conditions for establishing the models for firmness. The optimum model was obtained when the fruit were graded into similarly sized groups. Using partial least squares regression (PLSR), the correlation coefficient of prediction (R<inf>p</inf>) was 0.87 and the root mean square error of prediction (RMSEP) was 6.25 N. The predictive images for firmness of the fruit were created by interpreting predicted firmness visualized as colors in every pixel. From the data, it was concluded that NIR-HSI can potentially be used to visualize hardening of individual mangosteens based on their predictive images.