Juiciness is considered an important yet complex sensory attribute for animal and plant-based meats. The dynamic nature of sensory juiciness is influenced by individual ingredients, the overall food matrix, and interactions occurring during oral processing, making predicting or measuring juiciness instrumentally complex. This study aims to compare sensory juiciness assessments from a trained panel with physical measurements of liquid loss at varying compression rates and sample preparations. We hypothesise that sensory juiciness of burgers is related to the release of fluid during compression. This is tested by performing sensory texture analysis on six animal-based meat (ABM) and six plant-based meat analogue (PBMA) burgers. Sensory results obtained using a trained panel are compared to physical measurements of liquid loss upon compression at different compression rates and sample preparations. The PBMA samples all had significantly lower fluid release upon compression (compression loss) and lower sensory juiciness than ABM regardless of the composition of the food matrix. Samples varied in preparation methods based on the percentage of oil, water and methylcellulose (MC) and the cooking time of the samples. Additionally, MC was added either as a powder or as a premixed foam composed of water, oil and MC. Adding methylcellulose as a premixed rather than as a dry powder resulted in the highest juiciness scores for PBMA. The compression loss was measured at various compression speeds (0.1 mm/s and 10 mms) and with the crust of the sample on or with the crust removed. The strongest correlation between sensory juiciness and the compression loss was found at a strain limit of 50% and a compression rate of 10 mm/s, with the sample crust removed. This compression method is therefore recommended as a tool to help engineer the development of PBMA that seek to address the shortcomings in terms of perceived juiciness.
机构:
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Nebraska Food for Health Center, Department of Food Science and Technology, University of Nebraska-Lincoln, Lincoln, NEKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Shahzad K.
Alatalo J.M.
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Environmental Science Center, Qatar University, DohaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Alatalo J.M.
Zhu M.
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Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, BeijingKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Zhu M.
Cao L.
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Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, BeijingKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Cao L.
Hao Y.
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Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, BeijingKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
Hao Y.
DAI J.
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Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing
University of Chinese Academy of Sciences, BeijingKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing