title: A novel tensile test method to assess texture and gaping in salmon fillets.
abstract: A new tensile strength method was developed to quantify the force required to tear a standardized block of Atlantic salmon muscle with the aim of identifying those samples more prone to factory downgrading as a result of softness and fillet gaping. The new method effectively overcomes problems of sample attachment encountered with previous tensile strength tests. The repeatability and sensitivity and predictability of the new technique were evaluated against other common instrumental texture measurement methods. The relationship between sensory assessments of firmness and parameters from the instrumental texture methods was also determined. Data from the new method were shown to have the strongest correlations with gaping severity (r =-0.514, P < 0.001) and the highest level of repeatability of data when analyzing cold-smoked samples. The Warner Bratzler shear method gave the most repeatable data from fresh samples and had the highest correlations between fresh and smoked product from the same fish (r = 0.811, P < 0.001). A hierarchical cluster analysis placed the tensile test in the top cluster, alongside the Warner Bratzler method, demonstrating that it also yields adequate data with respect to these tests. None of the tested sensory analysis attributes showed significant relationships to mechanical tests except fillet firmness, with correlations (r) of 0.42 for cylinder probe maximum force (P = 0.005) and 0.31 for tensile work (P = 0.04). It was concluded that the tensile test method developed provides an important addition to the available tools for mechanical analysis of salmon quality, particularly with respect to the prediction of gaping during factory processing, which is a serious commercial problem.
  
  
  CONCLUSIONS
  A novel, reliable method of measuring flesh tensile strength in salmon, provides data of relevance to gaping.
authors.affiliation: Fish Muscle Research Group, Scottish Oceans Inst., School of Biology, Univ. of St Andrews, Fife, Scotland KY16 8LB, UK.
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Ashton
authors.forename: Ian
authors.initials: I
authors.lastname: Michie
authors.forename: Ian A
authors.initials: IA
authors.lastname: Johnston
mesh_terms: D000818:Animals; D055598:Chemical Phenomena; D016000:Cluster Analysis; D003296:Cooking; D005519:Food Preservation / Q000379:methods; D005524:Food Technology; D005525:Food-Processing Industry / Q000379:methods*; D006244:Hardness; D006801:Humans; D007091:Image Processing, Computer-Assisted; D011786:Quality Control; D015203:Reproducibility of Results; D020317:Salmo salar; D017747:Seafood / Q000032:analysis*; D012677:Sensation; D033081:Shear Strength; D018709:Statistics, Nonparametric; D013718:Tensile Strength