Prediction of lamb eating quality using hyperspectral imaging

Tong Qiao, Jinchang Ren, Jaime Zabalza, Stephen Marshall

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

191 Downloads (Pure)


Lamb eating quality is related to 3 factors, which are tenderness, juiciness and flavour. In addition to these factors, the surface colour of lamb could influence the purchase decision of consumers. Objective quality evaluation approaches, like near infrared spectroscopy (NIRS) and hyperspectral imaging (HSI), have been proved fast and non-destructive in assessing beef quality, compared with conventional methods. However, rare research has been done for lamb samples. Therefore, in this paper the feasibility of HSI for evaluating lamb quality is tested. A total of 80 lamb samples were imaged using a visible range HSI system and the spectral profiles were used for predicting lamb quality related traits. For some traits, noises were removed from HSI spectra by singular spectrum analysis (SSA) for better performance. Support vector machine (SVM) was employed to construct prediction equations. Considering SVM is sensitive to high dimensional data, principal component analysis (PCA) was applied to reduce the dimensionality first. The prediction results suggest that HSI is promising in predicting lamb eating quality
Original languageEnglish
Title of host publicationOCM (Optical Characterization of Materials) 2015
Subtitle of host publication2nd International Conference on Optical Characterization of Materials
EditorsJürgen Beyerer, Fernando Puente León, Thomas Längle
Place of PublicationKarlsruhe, Germany
Number of pages10
Publication statusPublished - 15 Mar 2015
EventOCM (Optical Characterization of Materials) 2015 - Karlsruhe, Germany
Duration: 18 Mar 201519 Mar 2015


ConferenceOCM (Optical Characterization of Materials) 2015
Abbreviated titleOCM 2015


  • hyperspectral imaging (HSI)
  • singular spectrum analysis (SSA)
  • principal component analysis (PCA)
  • lamb eating quality
  • tenderness
  • juiciness
  • flavour


Dive into the research topics of 'Prediction of lamb eating quality using hyperspectral imaging'. Together they form a unique fingerprint.

Cite this