Spectrochemical analysis; LIBS; LIF; White meat; Meat spoilage;INDUCED BREAKDOWN SPECTROSCOPY; TRANSFORM-INFRARED-SPECTROSCOPY; QUANTITATIVE DETECTION; MICROBIAL SPOILAGE; SENSORY ATTRIBUTES; COLD-STORAGE; DIAGNOSIS; BACTERIA; SPECTRA; CALCIUM

The overall objective of this paper is to evaluate the potential of laser spectrochemical analytical techniques as rapid, cost-effective, and accurate techniques to detect the onset of spoilage in fresh chicken breast fillets in three consecutive days directly following slaughter day. Samples were periodically examined via laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF). In the case of LIBS, the cyanide (CN) and carbon (C-2) molecular spectral emission bands in the LIBS spectra of meat have been taken as indicators of protein content in the chicken breast samples. The ratio of ionic to atomic spectral lines of both magnesium and iron is found to be proportional to the chicken meat tenderness which decreases with storage time. LIF has been also exploited as a simple and fast technique for white meat spoilage detection. There was a clear inverse proportionality between the intensity of the samples' fluorescence band and the storage period. The obtained spectrochemical results have been validated by measuring the total proteins in the investigated samples using a conventional meat analyzer. This work demonstrates the feasibility of adopting LIBS and LIF techniques in characterization of both fresh and spoiled chicken meat samples.

Mastitis; Bovine milk; LIBS; CN and C-2;BOVINE-MILK; DAIRY-COWS; SPECTROSCOPY; DIAGNOSIS

The present work focuses on the possibility of using the evolution of the spectral molecular bands of cyanide (CN) and carbon (C-2) in the laser-inducedbreakdown spectra of cow's milk for mastitis characterization. It has been found that the intensities of these molecular bands are directly proportional to the mastitis symptoms and consequently to the somatic cells count (SCC). The results obtained using laser-induced breakdown spectroscopy (LIBS) technique in the present measurements proved that it is a direct, straightforward, and easy method for discrimination between mastitis milk and normal milk. A linear relation between the CN and C-2 spectral line intensities and the corresponding average of the SCC has been obtained. Such linear relationship can be easily exploited in the identification and characterization of mastitic milk samples.

INDUCED BREAKDOWN SPECTROSCOPY; QUANTITATIVE-ANALYSIS; STEEL SAMPLES; CLASSIFICATION; PLASMA; RECOGNITION; TEMPERATURE; EXPLOSIVES; MODELS; SOILS

Laser induced breakdown spectroscopy with chemometric methods has been employed for sorting zamak alloy (zinc based alloy) samples. Plasma plumes were created on the sample surface using 50 mJ Nd:YAG laser pulses at its fundamental wavelength (lambda = 1064 nm). Six types of zinc alloy samples with different elemental compositions have been used to perform the LIBS measurements under optimized experimental conditions. On the obtained LIBS data three different chemometric classification models were applied, namely K Nearest Neighbor (KNN), Support Vector Machine (SVM) and Artificial Neural Networks (ANN). The effect of the input database choice and its normalization on the classification model efficiency has been investigated and found to play a crucial role. It was found that KNN, SVM and ANNs permit an appropriate classification of different zinc alloys using LIBS spectra and the best results were obtained from the largest input database. The effect of data normalization has been discussed for each model. The obtained results demonstrate the feasibility of using chemometric methods associated with the LIBS technique as an industrial tool for in situ zamak sorting.