The main objective of this work was to develop a method for rapid and non-destructive detection and grading of wooden breast (WB) syndrome in chicken breast fillets. Near-infrared (NIR) spectroscopy was chosen as detection method, and an industrial NIR scanner was applied and tested for large scale on-line detection of the syndrome. Two approaches were evaluated for discrimination of WB fillets: 1) Linear discriminant analysis based on NIR spectra only, and 2) a regression model for protein was made based on NIR spectra and the estimated concentrations of protein were used for discrimination. A sample set of 197 fillets was used for training and calibration. A test set was recorded under industrial conditions and contained spectra from 79 fillets. The classification methods obtained 99.5–100% correct classification of the calibration set and 100% correct classification of the test set. The NIR scanner was then installed in a commercial chicken processing plant and could detect incidence rates of WB in large batches of fillets. Examples of incidence are shown for three broiler flocks where a high number of fillets (9063, 6330 and 10483) were effectively measured. Prevalence of WB of 0.1%, 6.6% and 8.5% were estimated for these flocks based on the complete sample volumes. Such an on-line system can be used to alleviate the challenges WB represents to the poultry meat industry. It enables automatic quality sorting of chicken fillets to different product categories. Manual laborious grading can be avoided. Incidences of WB from different farms and flocks can be tracked and information can be used to understand and point out main causes for WB in the chicken production. This knowledge can be used to improve the production procedures and reduce today’s extensive occurrence of WB.

An online NIR interactance imaging instrument was tested for fat distribution analysis in raw and salted salmon fillets. Approximately 3000 spectra were collected for each fillet when passing under the instrument on a conveyor belt (approximately 1s exposure). The instrument was calibrated using five cylindrical plugs (15 mm diameter) from each fillet. The fat content was measured for each of these plugs using ¹H-NMR spectrometry and the spectra from each plug region were averaged and used for calibration and validation. It was found that online NIR interactance imaging is well-suited for distributional fat analysis in raw and salted intact salmon fillets. The local sampling and calibration strategy using 15 mm diameter plugs for reference analysis and spectral averaging was found to provide relevant information and robust models. The average prediction errors (root mean square error of cross-validation) for raw and salted fillets in combination were approximately 2% fat for local plug regions.

The muscle syndrome woody breast (WB) impairs quality of chicken fillets and is a challenge to the poultry meat industry. There is a need for online

Muscle food products play a vital role in human nutrition due to their sensory quality and high nutritional value. One well-known challenge of such products is the high perishability and limited shelf life unless suitable preservation or processing techniques are applied. Thermal processing is one of the well-established treatments that has been most commonly used in order to prepare food and ensure its safety. However, the application of inappropriate or severe thermal treatments may lead to undesirable changes in the sensory and nutritional quality of heat-processed products, and especially so for foods that are sensitive to thermal treatments, such as fish and meat and their products. In recent years, novel thermal treatments (e.g., ohmic heating, microwave) and non-thermal processing (e.g., high pressure, cold plasma) have emerged and proved to cause less damage to the quality of treated products than do conventional techniques. Several traditional assessment approaches have been extensively applied in order to evaluate and monitor changes in quality resulting from the use of thermal and non-thermal processing methods. Recent advances, nonetheless, have shown tremendous potential of various emerging analytical methods. Among these, spectroscopic techniques have received considerable attention due to many favorable features compared to conventional analysis methods. This review paper will provide an updated overview of both processing (thermal and non-thermal) and analytical techniques (traditional methods and spectroscopic ones). The opportunities and limitations will be discussed and possible directions for future research studies and applications will be suggested.

This article presents a method by which noncontact near-infrared (NIR) interactance imaging spectroscopy can be applied to determine the amount of edible meat in single live crabs ( Cancer pagurus) on a conveyor belt at high speed. The physiology and optical properties of the crabs are presented and discussed in order to explain the requirements for representative spectroscopic sampling. Two different sampling and calibration strategies are discussed. One strategy is based on the extraction of one average NIR spectrum from certain locations in each crab. The other strategy relies on first making a model based on average spectra from a certain location, and then using this model for pixel-wise prediction of the meat content within the crabs. A measure of the predicted distribution of meat is then used for calibration. Reference measurements of meat content were based on an objective quantitative metric of the meat content. The results show that NIR imaging enables on-line grading of the crabs with a correlation of 0.96 with the measured meat content. Due to seasonal variations in the crabs, a piece-wise regression strategy performs slightly better than a global model. Pixel-wise predictions of meat content provide informative images showing the distribution and amount of meat within each crab.