In this review, the principles and usage of NIRS are described, emphasizing the importance of portable NIRS as a rapid analysis system in the meat industry. The miniaturized and portable NIRS instruments offer a great potential for on-site monitoring quality control not only in the meat sector but also all other food and agro-industries. The mobility of these devices, enabling in situ, robust, on-site, and product-to-product on-line inspection and control, are their major advantages. The emergence of miniature and portable NIRS systems allows establishment of rapid protocols, which might increase rigorous quality control, implying that food quality can be routinely monitored along the entire logistic chain. For meat-value chain, the possibility to implement portable NIRS systems at any point along the logistic chain could dramatically reduce the number of serious scandals related to meat quality and safety. Conversely, results obtained with these instruments are unrealistic in some applications, stressing the need for more applications with diversity in sample presentation and measurement techniques. This will lead to improvements in their performance and help to establish more robust models. In the near future, these devices might stand as promising alternatives to large, expensive, and benchtop types in food analysis, inspection, and control.

As a source of vital nutrients for the normal functioning of the body, chicken meat plays an important role in promoting good health. This study examines the occurrence of total volatile basic nitrogen (TVB-N) as an index for evaluating freshness, using novel colorimetric sensor arrays (CSA) in combination with linear and nonlinear regression models. Herein, the TVB-N was determined by steam distillation, and the CSA was fabricated via the use of nine chemically responsive dyes. The corresponding dyes utilized, and the emitted volatile organic compounds (VOCs) were found to be correlated. Afterwards, the regression algorithms were applied, assessed, and compared, with the result that a nonlinear model based on competitive adaptive reweighted sampling coupled with support vector machines (CARS-SVM) achieved the best results. Accordingly, the CARS-SVM model provided improved coefficient values (Rc = 0.98 and Rp = 0.92) based on the figures of merit used, as well as root mean square errors (RMSEC = 3.12 and RMSEP = 6.75) and a ratio of performance deviation (RPD) of 2.25. Thus, this study demonstrated that the CSA paired with a nonlinear algorithm (CARS-SVM) could be employed for fast, noninvasive, and sensitive detection of TVB-N concentration in chicken meat as a major indicator of freshness in meat.

In this paper, we developed a mathematical model to describethe dynamics of Aflatoxins in plants, animals, and humans. Fourequilibrium points were found, and their stability analyses wereconducted using threshold quantities. If both are less than one, thestandardized toxic limit is not exceeded, while if both are greater thanone it is exceeded in both animals and humans. Standardized toxic limitis exceeded in a relevant host (animals or humans) when their respectivethreshold quantity is greater than one. Numerical simulations werecarried out to support the analytic results. The need to use experimentaldata in the model is also shown. This could ease satisfactoryharmonization of acceptable standards and facilitate international tradeof food and feeds.