秋刀鱼肉质感官评价与质构的相关性分析

Correlation between meat quality sensory evaluation and texture of Cololabis saira

  • 摘要: 【目的】分析秋刀鱼肉质感官评价与质构的相关性,为全面评价秋刀鱼不同部位的加工特性及开发秋刀鱼产品提供理论依据。【方法】以秋刀鱼背部和尾部肌肉为材料,对4℃解冻过程中的感官评定和质构分析(TPA)结果进行因子和主成分分析,以及相关性分析;再以TPA指标为自变量、感官评定指标为因变量进行逐步回归分析,建立感官预测模型。【结果】不同解冻时间的秋刀鱼背肌和尾肌的硬度、弹性、胶黏性、咀嚼性和回复性等质构特性差异显著(P<0.05,下同),色泽、气味、组织形态、弹性、硬度、黏聚性和胶黏性等感官评定指标也存在显著差异。通过因子和主成分分析,秋刀鱼背肌和尾肌的感官评定指标得出3个主成分,方差贡献率分别为80.995%和78.872%,TPA指标得出2个主成分,方差贡献率分别达99.259%和98.865%。综合感官评定指标和TPA测定结果的相关性分析,建立了色泽与胶黏性的预测模型Co=-8.966+53.936a和硬度与胶黏性的预测模型Ha=-10.490+59.475a,R均大于0.900,呈良好的线性相关,且两个分析预测模型均具有显著性。【结论】秋刀鱼肉质感官指标中的色泽和硬度受TPA指标中胶黏性显著影响;开发秋刀鱼产品时可将感官评定与质构分析两种方法相结合用于评价秋刀鱼产品品质。

     

    Abstract: ObjectiveThe present study was conducted to analyze correlation between sensory evaluation and texture of Cololabis saira in order to provide references for evaluating the specific processing features of different parts in C. saira and development of C. saira products. MethodTaking back and tail muscles of C. saira as materials, factor analysis, prin-cipal component analysis and correlation analysis were conducted based on results of sensory evaluation and texture profile analysis(TPA) during 4 ℃ thawing process. Then taking TPA indicators as independent variables, sensory evaluation in-dicators as dependent variables, stepwise regression analysis was conducted and sensory evaluation model was established.ResultAt different thawing times,texture characteristics of C. saira back and tail muscles including hardness,elastici-ty,tackiness,chewiness and resilience were significantly different(P<0.05, the same below),sensory evaluation indicators including color,smell,tissue form,elasticity,hardness,cohesiveness,tackiness were also significantly different. Through factor analysis and principal component analysis, three principal components of sensory evaluation indicators in back and tail muscles of C. saira were obtained, variance contribution ratios were 80.995%, 78.872%, respectively; two principal components of TPA indicators were obtained whose variance contribution ratios were 99.259%, 98.865%, respectively. Based on correlation analysis of sensory evaluation indicators and TPA indicators, forecasting model of color and tackiness was presented as follows: Co=-8.966+53.936a. Forecasting model of hardness and tackiness was presented as follows:Ha=-10.490+59.475a. R was more than 0.900. The forecasting models showed linear correlation, and both forecasting models reached significant level. ConclusionColour and hardness in sensory evaluation are significantly affected by tac-kiness in TPA. When developing C.sairaproducts, sensory evaluation and TPA can be combined to evaluate the product quality.

     

/

返回文章
返回