Prediction of Carcass Composition and Meat and Fat Quality Using Sensing Technologies: A Review

Consumer demand for high-quality healthy food is increasing; therefore, meat processors require the means toassess their products rapidly, accurately, and inexpensively. Traditional methods for quality assessments are time-consum-ing, expensive, and invasive and have potential to negatively impact t...

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Bibliographic Details
Published inMeat and muscle biology Vol. 5; no. 3
Main Authors Leighton, Patricia L. A., Segura, Jose, Lam, Stephanie, Marcoux, Marcel, Wei, Xinyi, Lopez-Campos, Oscar, Soladoye, Philip, Dugan, Mike E. R., Juarez, Manuel, Prieto, Nuria
Format Journal Article
LanguageEnglish
Published Iowa State University Digital Press 05.07.2022
Subjects
Bioelectrical impedance analysis
Computed tomography
Computer vision systems
Dual energy X-ray absorptiometry
Near infrared spectroscopy
Ultrasound
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Summary:Consumer demand for high-quality healthy food is increasing; therefore, meat processors require the means toassess their products rapidly, accurately, and inexpensively. Traditional methods for quality assessments are time-consum-ing, expensive, and invasive and have potential to negatively impact the environment. Consequently, emphasis has been puton finding nondestructive, fast, and accurate technologies for product composition and quality evaluation. Research in thisarea is advancing rapidly through recent developments in the areas of portability, accuracy, and machine learning.Therefore, the present review critically evaluates and summarizes developments of popular noninvasive technologies(i.e., from imaging to spectroscopic sensing technologies) for estimating beef, pork, and lamb composition and quality,which will hopefully assist in the implementation of these technologies for rapid evaluation/real-time grading of livestockproducts in the near future.
ISSN:2575-985X
2575-985X
DOI:10.22175/mmb.12951