Analytical Method for Differentiation of Chilled and Frozen-Thawed Chicken Meat
Abstract : Chilled and frozen chicken breast and thigh meat were stored at +4±1 oC and - 20±1 oC, respectively. Maillard reaction between ribose and meat proteins of the chicken samples was initiated. The changes in the ribose-induced Maillard reaction rate during chilled and frozen storage of chicken meat were evaluated on the bases of corrected absorbance values (A420*) and bovine melanoidin equivalent values (mg BME/g). Application of BME as a measure of ribose-induced Maillard reaction rate enables comparability of the data obtained by different spectrophotometers. It was found that the BME values of chicken meat frozen stored for more than 15 days were significantly (P<0.05) lower than BME values of chilled-stored samples. According to the suggested threshold limit values the chicken thigh and breast meat with BME values lower than 30 mg BME/g and 51 mg BME/g, respectively could be classified as frozen-thawed.
Identification of Fresh-Chilled and Frozen-Thawed Chicken Meat and Estimation of their Shelf Life Using an E-Nose Machine Coupled Fuzzy KNN
In this study, the capability of an electronic nose machine to identify chilled and frozen-thawed chicken meat was investigated. According to the importance of fresh chicken meat consumption in people’s daily diet, recognition of fresh chicken meat from frozen-thawed one is an essential issue. In the mentioned system, eight sensors (MOS type) were applied. The outputs of sensors were preprocessed, then features were extracted, and fuzzy K-nearest neighbors (F-KNN) algorithm was applied for classification. Chicken meats were classified in two classes (fresh and frozen-thawed). Also, each group of fresh and frozen-thawed chicken meat was classified in five classes according to their shelf life (elapsed day after slaughtering/thawing). The obtained results showed that the average amount of accuracy for fresh-chilled chicken meat classification and frozen-thawed one were 95.2 and 94.67%, respectively. Finally, the accuracy of fresh chicken meat with 95.83% demonstrated the high accuracy of it compare with frozen-thawed one. According to the results, high performance of F-KNN algorithm demonstrated that e-nose system can be applied as a rapid, accurate, and nondestructive method for online and automated identification of fresh and frozen-thawed chicken meat.
Laboratory Animal Models for Brucellosis Research
Brucellosis is a chronic infectious disease caused by Brucella spp., a Gram-negative facultative intracellular pathogen that affects humans and animals, leading to significant impact on public health and animal industry. Human brucellosis is considered the most prevalent bacterial zoonosis in the world and is characterized by fever, weight loss, depression, hepato/splenomegaly, osteoarticular, and genital infections. Relevant aspects of Brucella pathogenesis have been intensively investigated in culture cells and animal models. The mouse is the animal model more commonly used to study chronic infection caused by Brucella. This model is most frequently used to investigate specific pathogenic factors of Brucella spp., to characterize the host immune response, and to evaluate therapeutics and vaccines. Other animal species have been used as models for brucellosis including rats, guinea pigs, and monkeys. This paper discusses the murine and other laboratory animal models for human and animal brucellosis.