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    Effect of Dietary Cannabis sativa L. Residue Supplementation on Meat Quality and Flavor-Enhancing Free Amino Acids in Broiler Chickens
    (2025-03-01)
    Sopian, Yusup
    ;
    Sahatsanon, Katatikarn
    ;
    Satsook, Apinya
    ;
    Arjin, Chaiwat
    ;
    Sringarm, Korawan
    This study investigated the effects of dietary Cannabis sativa residues (CR) on broiler growth and meat characteristics. A total of 256 one-day-old male Ross-308 broilers were randomly assigned to four treatments: a basal diet (control) and diets containing 0.5%, 1%, and 2% CR. CR supplementation had no effect on growth performance, survival rate, or European production index but reduced average daily feed intake (p < 0.01). No significant differences were found in meat pH, color, drip loss, thawing loss, cooking loss, or shear force (p > 0.05). However, the ΔE values (0.5% CR: 3.97, 1.0% CR: 3.71, 2.0% CR: 4.95) indicated perceptible color differences compared to the control. CR significantly reduced C12:0, C20:1n9, and C22:1n9 fatty acids (p < 0.05) while increasing free amino acids, including aspartic acid, serine, proline, methionine, and phenylalanine (p < 0.05). It also increased moisture content and decreased fat content, especially at 2% CR (p < 0.05). In conclusion, CR supplementation improves the flavor and nutritional value of broiler meat and is a potential alternative to conventional feed additives.
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    Rapid evaluation of fat content in curry soup containing coconut milk by using near infrared spectroscopy
    (2018-02-01)
    Cheevitsopon, Ekkapong
    ;
    Sirisomboon, Panmanas
    The feasibility of a near infrared spectroscopy to evaluate the fat content in instant curry soup containing coconut milk including green curry, red curry, massaman curry and panang curry was investigated. The soup samples were collected from a processing line and as the finished product. There were also fat content-adjusted samples where the curry was made from the same recipe as in the processing line but increasing by 30, 60 and 90% coconut milk and reducing by 30, 60 and 90% coconut milk from normal. A Fourier transform near infrared spectrometer was used to collect scans. A partial least squares regression model for fat content was established using near infrared spectral data in conjunction with reference data, which was validated using a leave-one-out cross-validation and test set validation. The test set validation, using a set of unknown samples, showed better prediction performance. The best model developed using vector normalization spectral pre-treatment on 9404–7498 and 6102–5446 cm<sup>−1</sup> provided coefficient of determination, root mean square error of prediction, bias and ratio of performance to interquartile values of 0.90, 0.9%, −0.1% and 1.2, respectively, for the validation samples. However, the model developed using samples without fat content adjusted samples gave a slightly lower coefficient of determination (0.89), but provided a lower root mean square error of prediction (0.5%) and acceptable ratio of standard error of validation to the standard deviation (3.2). In addition, the vibration bands of CH<inf>2</inf> which was in the long chain fatty acid moiety highly influenced the prediction of fat content in the curry soup. The near infrared spectroscopy protocol developed for the determination of fat could be applied in the instant curry soup production line.
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