Prediction of Sensory Attributes of Fresh Beef Using Advanced Spectral Analysis

Document Type : Original Article

Author

Abstract

One of the main roles of home economics tasks is to seek high quality food with desirable palatability and lowest costs. The development of an advanced method to guarantee the sensory and nutritional parameters becomes very crucial in modern food technology. Spectral imaging technology has more advantages over the other conventional methods in food quality evaluation due to rich information it provides. The main aim of the current study was to present a method for non-invasive determination of sensory quality attributes of beef based on spectral analyses of spectral images in the near infrared (NIR) region. Twenty seven of fresh beef samples were collected, spectral data were extracted and the sensory quality attributes were measured. The spectral signatures of beef samples and their corresponding sensory features were then analysed using partial least squares (PLS) regression yielding determination coefficients () of 0.97, 0.92, 0.49 and 0.93 for predicting juiciness, tenderness, flavour and overall acceptability, respectively. The results are very encouraging and implied that the proposed method has a great potential in non-ruinous determination of several sensory attributes simultaneously without tedious sensory panel evaluation. The study recommends applying this non-destructive technique in industrial scales to guarantee high quality of beef and meat products before being marketed to the consumers.

Keywords

Main Subjects

Suez Canal University Journal of Food Sciences
Volume 7, Issue 1
October 2020
Pages 35-42

Files

Share

How to cite

Statistics