Laser-backscattering imaging for characterizing pork loin tenderness. Effect of pre-treatment with enzyme and cooking
| Autor: | Grau Meló, Raúl, Verdú, Samuel, Pérez Jiménez, Alberto José, Barat Baviera, José Manuel, Talens Oliag, Pau |
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| Rok vydání: | 2021 |
| Předmět: |
chemistry.chemical_classification
Pre treatment TECNOLOGIA DE ALIMENTOS food and beverages Non-destructive analysis Loin Biospeckle Imaging analysis Laser backscattering ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES Tenderness Papain chemistry.chemical_compound Enzyme chemistry Meat softness medicine Diffuse reflectance Cooked meat Food science medicine.symptom Food Science |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| ISSN: | 0260-8774 |
| DOI: | 10.1016/j.jfoodeng.2021.110508 |
| Popis: | [EN] The aim of this work was to characterizes, by the non-destructive technique based on the laser-backscattering imaging analysis, the effect of pre-treatment with papain enzyme (1% w/w), the enzyme action time (0, 3, 6 and 24 h at 4 degrees C) and cooking (80 degrees C for 3 min) on pork loin tenderness. Texture and image analyses were run for the untreated and treated samples, and for the uncooked and cooked samples. Images of the laser pattern generated on the meat surface were decomposed into red, green and blue channels. Two descriptors types (direct and relative) were developed for each one by segmentation. The obtained results revealed the increased tenderness in the samples that underwent enzyme treatment with maximum values at 6 h (29.3 +/- 3.2 N). Cooking increased enzyme action with much lower values (39.2 +/- 3 N) than for the samples without treatment (75.6 +/- 2.9 N). For uncooked meat, changes in texture were related mainly to the relative descriptor of the blue and green channels, and those from the red channel for cooked meat, which allowed prediction models to be obtained (R-2 CV = 0.9; RMSE CV = 1.9). The authors thank the "Ministerio Espanol de Ciencia e Innovacion" for the financial support provided through Project RTI2018-098842-B-I00. |
| Databáze: | OpenAIRE |
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