2-D, 3-D and real-time near infrared (NIR) hyperspectral and fluorescence imaging of food and agricultural products 2D, 3D samt realtids nära infraröd (NIR) hyperspektral och flourescensbildupptagning av livsmedels- och jordbruksprodukter Development of rapid and real-time imaging methods for safety and quality measurements of food products. Near infrared (NIR) hyperspectral imaging integrates conventional digital imaging and NIR spectroscopy to attain information in two directions (both spatial and spectral) from an object or sample. This allows to tell not only how much of a compound might be present but also where it might be located within the sample. During this project NIR hyperspectral imaging will be used to detect faults in grains before it becomes visible to the human eye. Using pre-germinated barley during malting costs the South African brewing industry millions of Rands each year due to loss in quality. Being able to detect these pre-germinated grains early on will be of great advantage to the industry. Similary methods will be developed to detect spices that has been adulterated by adding cheaper ingredients such as milled bran to ground mixed spices. This will protect the consumer. Mathematical models will be developed that would allow the use of NIR hyperspectral imaging in industry. To be able to use this technique on-line, real-time methods will also be developed for these two applications. The mathematical models needed to be developed for this will allow fast measurement and calculation of results. These analysis are, however, only in two dimensions. To allow evaluations to be made three dimensionally, thin slices of grain samples, infected with a fungus, will be imaged and the images obtained put together mathematically to form a 3-D image. This would allow precise localisation of infection within a 3-D sample. This will allow information being obtained not possible with any other analytical method as well as the detection of precise localisation of infection within grain. To be able to execute these research projects effectively skills and expertise on imaging, chemometrics, food science and microbiology respectively available at SLU, Sweden and SU, South Africa are needed. All these expertise needed to be applied simultaneously to effectively interpret the results. At the same time knowledge will be transferred between the two countries to the benefit of both. Food safety and security is becoming increasingly important. This cutting-edge technique might not be suitable for immediate implementation in industry. However, it needs to be evaluated and methods developed as in future it will become an economical method for rapidly analysing food and agricultural products to ensure a safe, quality product for the consumer. NIR hyperspectral imaging mostly address food quality and safety aspects using 2-D imaging with laboratory set-ups. Four imaging projects will be executed. 2-D imaging will be evaluated for the detection of pre-germination in barley and the presence of adulterants in spices. A PAT system will be optimised and algorithms developed to allow real-time analysis. To detect precise localisation of fungal infection in food products, 3-D NIR hyperspectral images will be constructed by combining an array of tomographic NIR images. Exploratory principal component analysis, partial least squares (PLS) and PLS discriminant analysis will be used as chemometrics techniques. These projects will only be possible if it can be executed within this collaborative programme. The principal researcher in Sweden has expertise in imaging and chemometrics whereas the principal researcher in South Africa (SA) has expertise in the composition of food and agricultural products as well as microbiology. SA will provide all samples needed for the study. Imaging instrumentation is available in Sweden and all analytical facilities for reference methods are available in SA. Thus Sweden will gain skills on the applicaton of imaging techniques on food and agricultural samples while SA will obtain skills in the application of imaging and chemometrics. Data analysis and interpretation of images can only be effective with hisotological knowledge on the samples as well as applying correct chemometric techniques.