Near-infrared hyperspectral imaging for predicting colour, pH and tenderness of fresh beef

The relationship between consumer perception of quality and the food industry's drive to satisfy consumer needs is complex and involves many different components. Science and innovation play a major role in equipping the industry to respond to consumer concerns and expectations. This paper examines the main elements of consumer perception of meat with focus on the red meat sector. Emphasis is placed on perception at point of sale particularly the intrinsic quality cues of colour, packaging and degree of visual fat. The state of the art developments in increasing consumers' perception at this point are discussed. Experienced quality cues such as tenderness and flavour are well known as being of immense importance to consumers at point of consumption. The latest technological developments to enhance the quality experienced by consumers are discussed. The use of pre-rigor restraining techniques offers the industry a method for changing its conventional procedures of processing beef for instance. Background cues of safety, nutrition, animal welfare and sustainability are also discussed. Finally opportunities and challenges facing the industry are outlined. It is concluded that the meat industry needs to invest in and embrace an innovation agenda in order to be sustainable. It must utilise emerging scientific knowledge and take a more proactive role in setting out a research agenda. Show more

Spectral imaging extends the capabilities of biological and clinical studies to simultaneously study multiple features such as organelles and proteins qualitatively and quantitatively. Spectral imaging combines two well-known scientific methodologies, namely spectroscopy and imaging, to provide a new advantageous tool. The need to measure the spectrum at each point of the image requires combining dispersive optics with the more common imaging equipment, and introduces constrains as well. The principles of spectral imaging and a few representative applications are described. Spectral imaging analysis is necessary because the complex data structure cannot be analyzed visually. A few of the algorithms are discussed with emphasis on the usage for different experimental modes (fluorescence and bright field). Finally, spectral imaging, like any method, should be evaluated in light of its advantages to specific applications, a selection of which is described. Spectral imaging is a relatively new technique and its full potential is yet to be exploited. Nevertheless, several applications have already shown its potential. (c) 2006 International Society for Analytical Cytology. Show more