Paper
6 January 1995 Estimation of lean and fat composition of pork ham using image processing measurements
Jiancheng Jia, Allan P. Schinckel, John C. Forrest
Author Affiliations +
Proceedings Volume 2345, Optics in Agriculture, Forestry, and Biological Processing; (1995) https://doi.org/10.1117/12.198887
Event: Photonics for Industrial Applications, 1994, Boston, MA, United States
Abstract
This paper presents a method of estimating the lean and fat composition in pork ham from cross-sectional area measurements using image processing technology. The relationship between the quantity of ham lean and fat mass with the ham lean and fat areas was studied. The prediction equations for pork ham composition based on the ham cross-sectional area measurements were developed. The results show that ham lean weight was related to the ham lean area (r equals .75, P < .0001) while ham fat weight was related tot the ham fat area (r equals .79, P equals .0001). Ham lean weight was highly related to the product of ham total weight times percentage ham lean area (r equals .96, P < .0001). Ham fat weight was highly related to the product of ham total weight times percentage ham fat area (r equals .88, P < .0001). The best combination of independent variables for estimating ham lean weight was trimmed wholesale ham weight and percentage ham fat area with a coefficient of determination of 92%. The best combination of independent variables for estimating ham fat weight was trimmed wholesale ham weight and percentage ham fat area with a coefficient of determination of 78%. Prediction equations with either two or three independent variables did not significantly increase the accuracy of prediction. The results of this study indicate that the weight of ham lean and fat could be predicted from ham cross-sectional area measurements using image analysis in combination with wholesale ham weight.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiancheng Jia, Allan P. Schinckel, and John C. Forrest "Estimation of lean and fat composition of pork ham using image processing measurements", Proc. SPIE 2345, Optics in Agriculture, Forestry, and Biological Processing, (6 January 1995); https://doi.org/10.1117/12.198887
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Cited by 4 scholarly publications.
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KEYWORDS
Image processing

Image analysis

Inspection

Cameras

RGB color model

Visualization

Bone

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