Randulová Z., Tremlová B., Řezáčová-Lukášková Z., Pospiech M., Straka I. (2011): Determination of soya protein in model meat products using image analysis. Czech J. Food Sci., 29: 318-321.The addition of plant proteins into meat products is nowadays a commonly used practice especially for the technological and economical reasons. Their properties have been known and used in meat products production for a long time. In the past, wheat protein or flour had been used most frequently, however, in these days they are being replaced by soya protein which has much more favourable properties in its use. Considering the possible misuse of raw materials of plant origin for the adulteration of meat products, the existence of highly sensitive and accurate procedures for their detection is needed including the determination of their content. Soya protein can be detected using various methods. In our work, an immunohistochemical method was used with image analysis for the quantification of soya protein. Model meat products with the addition of known amounts of soya protein in various forms were made for this experiment.

AbstractŘezáčová-Lukášková Z., Tremlová B., Pospiech M., Renčová E., Randulová Z. (2010): Immunohistochemical detection of wheat protein in model samples. Czech J. Food Sci., 28: 516-519.The study focused on the optimisation of immunohistochemical examination for gluten content detection in model samples (pork meat with wheat semi-smooth flour, pork meat with wheat protein edible vital). The best results were achieved with immunohistochemical method based on ABC (avidin-biotin complex) method utilising polyclonal antibodies diluted 1:1000. The results demonstrate that for pure wheat protein detection, the utilisation of immunohistochemical detection, which can detect as little as 0.1% of the added wheat protein, is more advantageous, while the commonly used ELISA method reliably proves this additive approximately from 0.4% upwards.

SummaryOptical microscopy offers the simplest way to obtain magnified images of biological tissues. The assessment of the muscle destructuration level can be performed by a method called Meat Destruction Indicator (MDI), which combines optical microscopy and image analysis. MDI can be used for evaluation of food quality and for considering mechanically separated meat (meat raw material with an MDI value above 58.1% contained muscle fibres sufficiently destructured). This paper is particularly focused on the metrological optimization of a quantitative image analysis method around the example of MDI measurement by microscopy, especially on the digital acquisition calibration focusing and analysis workflow. Ten different samples (45 sections) were examined with variable settings of microscope and camera to define the optimal configuration. The tests were performed with different observers to define rules and criteria for results validation. Based on the obtained results, we suggest choosing objective rules to set the light and colour of the camera and the microscope focus. To control the results of the automatic segmentation emerged also as a key step, and objective rules for observers to select or discard wrong segmented images should be defined. The adjusted MDI measurement by microscope can be used as a reliable method with good repeatability, thanks to this metrological assessment, which could and should be applied to all image analysis applications whatever the application.