Near-infrared techniques for fraud detection in dairy products: A review

The dairy products sector is an important part of the food industry, and their consumption is expected to grow in the next 10 years. Therefore, the authentication of these products in a faster and precise way is required for the sake of public health. This review proposes the use of near-infrared techniques for the detection of food fraud in dairy products as they are faster, nondestructive, environmentally friendly, do not require sample preparation, and allow multiconstituent analysis. First, we have described frequent forms of food fraud in dairy products and the application of traditional techniques for their detection, highlighting gaps and counterproductive characteristics for the actual global food chain, as longer sample preparation time and use of reagents. Then, the application of near-infrared spectroscopy and hyperspectral imaging for the detection of food fraud mainly in cheese, butter, and yogurt are described. As these techniques depend on model development, the coverage of different dairy products by the literature will promote the identification of food fraud in a faster and reliable way.     

Near-infrared hyperspectral imaging for grading and classification of pork

In this study, a hyperspectral imaging technique was developed to achieve fast, accurate, and objective determination of pork quality grades. Hyperspectral images were acquired in the near-infrared (NIR) range from 900 to 1700 nm for 75 pork cuts of longissimus dorsi muscle from three quality grades (PSE, RFN and DFD). Spectral information was extracted from each sample and six significant wavelengths that explain most of the variation among pork classes were identified from 2nd derivative spectra. There were obvious reflectance differences among the three quality grades mainly at wavelengths 960, 1074, 1124, 1147, 1207 and 1341 nm. Principal component analysis (PCA) was carried out using these particular wavelengths and the results indicated that pork classes could be precisely discriminated with overall accuracy of 96%. Algorithm was developed to produce classification maps of the tested samples based on score images resulting from PCA and the results were compared with the ordinary classification method. Investigation of the misclassified samples was performed and showed that hyperspectral based classification can aid in class determination by showing spatial location of classes within the samples.     

Outcome of percutaneous intervention in iliac artery stents

PURPOSE: To assess the safety and efficacy of secondary procedures in iliac artery stents. MATERIALS AND METHODS: Thirty-four patients (36 limbs) underwent one or more interventional procedures in iliac artery stents to treat restenosis (n = 30) or occlusion (n = 6). All patients were followed up by means of clinical and angiographic examination. Primary and secondary patency were assessed with angiography, duplex ultrasound, or both. Primary patency was determined after one interventional procedure, and secondary patency was determined at the end of the study (mean +/- standard deviation, 20.1 months +/- 17.5; range, 1-58 months). RESULTS: Immediate angiographic success was achieved in all cases. Four complications were observed. The primary and secondary cumulative patency rates were 77.5% +/- 7.6 and 94% +/- 4.1 at 6 months, 73% +/- 8.4 and 89.3% +/- 6 at 12 months, and 51.4% +/- 10.9 and 78.8% +/- 8.8 at 2 years. At the end of the study, 80% of the arteries were still nominally patent. CONCLUSION: Restenosis and chronic occlusion in iliac artery stents can be treated with percutaneous interventional procedures; however, stenosis can still recur.