Quality Assessment of Beef Using Computer Vision Technology

Abstract

Imaging technique or computer vision technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of computer vision technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 hours post-mortem. Traits evaluated were color value (L*,a*,b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, Thiobarbituric acid reactive substance (TBARS), Peroxide value (POV), Free fatty acid (FFA), Total coliform count (TCC), Total viable count (TVC) and Total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination was done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XV.I. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r = 0.65) and moisture (r = 0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in Lightness (R²c = 0.73, R²p = 0.69) in beef. Results of this work show that computer vision technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

Combined effect of irradiation and butylated hydroxyanisole on shelf life and quality of beef at ambient temperature

“…Color was measured at 24 h post-slaughter using Konica Minolta Chroma Meter (CR 410, Konica Minolta Sensing, Inc., Osaka, Japan), a Miniscan Spectro colorimeter programmed with the CIE Lab, (International Commission on Illumination) L*, a*, and b* system, where L* represents lightness, a* redness and b* yellowness (CIELAB, 2014). The analysis was carried out on the medial surface (bone side) of the meat at 24 h post-mortem (Rahman et al, 2020).…”

“…Drip loss was measured following the procedure of Rahman et al (2020). For DL measurement approximately 30 g sample was hung with a wire and kept in an air tight plastic container for 24 h. After 24 h the sample was weighed and calculated the difference.…”

“…The conversion of muscle to meat is the key point of muscle pH. After slaughter the animals at early post-mortem stage muscle pH remains around 7.0-7.2 and converted to meat pH 5.5-5.9 (Rahman et al 2020). The result shown that raw pH values slightly decreased in all treatment groups but increased significantly (p<0.01) in all groups with the increasing storage time and found higher value at 7 th day (7.56) resulting increase of free fatty acids due to rancidity.…”

Determining Relationships between Marbling Scores and Carcass Yield Traits of German Beef Bull Carcasses Using Video-Image Analysis at the 12th and 10th Rib Position of Longissimus Thoracis and EUROP Classification

“…Rather, it is a matter of integrating important parameters, such as marbling and rib fat, into the classification in order to supplement EUROP traits and enrich the information about qualitative aspects of carcasses used in processing and marketing strategies. Classifying the different quality levels may lead to an adapted distribution of carcasses according to the different requirements of the various markets, processors or consumers in the process line [31]. Considering the fact that other studies already emphasize the high accuracy of VIA in predicting carcass traits [20][21][22], the implementation of VIA in European classification systems is highly recommendable, if not essential.…”

Prediction of beef quality traits through mini NIR spectrophotometer and multivariate analyses

“…is technologically and economically important not only for food-processing industry but also for consumers as an important attribute during purchasing meat (Akhter et al, 2009;Baset et al, 2003;Bithi et al, 2020;Disha et al, 2020;Habiba et el., 2021;Rahman et al, 2014). In Bangladesh, meat quality evaluation still depends on traditional analytical technology which involves chemical, biological and microbiological determinations but those are tedious, time-consuming, sample destructive and environmentally unfriendly (Rahman et al, 2020;Rana et al, 2014;Haque et al, 2017;Modak et al, 2009). The lack of fast, reliable and non-destructive methods for determining meat characteristics in the carcass and meat cuts has been one of the main obstacles for the development of quality control in the meat industry.…”