In-plant, non-invasive spectral imaging for the prediction of lamb meat quality attributes

Muscle foods such as meat are a perishable, nutritious, relatively expensive food commodity, a great source of human nutrition and are a large part of the New Zealand economy, as well as overseas. Currently, New Zealand’s meat producing companies measure meat quality attributes by using a different technology for every trait, with no overarching way to combine them. There is a desire by the meat industry to find a single way to measure and compare meat quality parameters in a single process or technology. The development of an on-line, real time, non-destructive quality control system could help define multiple meat traits in a way that can guarantee the product in terms of composition, safety and consistency. These guarantees not only help the producer to ask a higher premium for their product but also give assurances to the consumer that they are getting exactly what they are expecting and paying for. This thesis focussed on determining whether the spectral imaging technologies of near infrared and hyperspectral imaging, and techniques were suitable for use in an in-plant situation for the measurement of lamb meat quality attributes.