Predicting pork loin intramuscular fat using computer vision system
- 1 September 2018
- journal article
- research article
- Published by Elsevier in Meat Science
- Vol. 143, 18-23
Abstract
No abstract availableKeywords
Funding Information
- Natural Science Foundation for Young Scientists of Jiangsu Province of China (BK20140715)
This publication has 38 references indexed in Scilit:
- Use of computer vision system (CVS) for detection of PSE pork meat obtained from m. semimembranosusLWT, 2016
- Simultaneous data pre-processing and SVM classification model selection based on a parallel genetic algorithm applied to spectroscopic data of olive oilsFood Chemistry, 2014
- Measurement of Soluble Solid Contents and pH of White Vinegars Using VIS/NIR Spectroscopy and Least Squares Support Vector MachineFood and Bioprocess Technology, 2013
- Lightness of the color measured by computer image analysis as a factor for assessing the quality of pork meatMeat Science, 2011
- Effect of visual marbling on sensory properties and quality traits of pork loinMeat Science, 2010
- Color grading of beef fat by using computer vision and support vector machineComputers and Electronics in Agriculture, 2010
- Classification of milk by means of an electronic nose and SVM neural networkSensors and Actuators B: Chemical, 2004
- Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of AgricultureJournal of Animal Science, 2002
- Marbling effects on quality characteristics of pork loin chops: consumer purchase intent, visual and sensory characteristicsMeat Science, 2001
- Support-vector networksMachine Learning, 1995