| dc.creator |
BOZKURT, YALÇIN |
|
| dc.creator |
AKTAN, Sedat |
|
| dc.creator |
Ozkaya, Serkan |
|
| dc.date |
2008-04-30T21:00:00Z |
|
| dc.date.accessioned |
2020-10-06T09:49:04Z |
|
| dc.date.available |
2020-10-06T09:49:04Z |
|
| dc.identifier |
44a56a66-856c-4424-9a47-9d58199cb4ff |
|
| dc.identifier |
10.3923/ajava.2008.129.137 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/44a56a66-856c-4424-9a47-9d58199cb4ff/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/58762 |
|
| dc.description |
This study was aimed at predicting carcass weight and some carcass characteristics of slaughtered beef cattle by using digital image analysis system. A total of 55 digital images and carcass measurements were taken, such as Hot Carcass Weight (HCW), Carcass Area (CA), Carcass Length (CL), Carcass Depth (CD) and 29 digital images of Longissimus Muscle Area (LMA) from slaughtered beef cattle. Carcass area was calculated from hot carcass images by digital camera for prediction of carcass weight and CA was found to be the best predictor compared to CL and CD. Linear, quadratic and cubic effects of predictors were also examined and R-2 values of CA were 85.9, 86.0 and 91.3%, respectively. Correlation coefficient between HCW and CA gave the highest value of 0.93 among other measurements and found to be statistically significant. At the same time, there were no significant differences between mean values of LMA obtained by digital images and calculated by acetate planimeter. Correlation coefficient was also high (r = 0.93) and significant for these values, R-2 value for LMA obtained by digital images was 85.6%. The results showed that the prediction ability of digital image analysis system was very promising to predict HCW. It was also concluded that HCW and LMA can be predicted by digital image analysis system with confidence and flexibility. However, there is a need for further studies under better controlled experimental conditions in order to develop better techniques to use for prediction, taking into account of different breeds of cattle and their size as well. |
|
| dc.language |
eng |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Digital image analysis to predict carcass weight and some carcass characteristics of beef cattle |
|
| dc.type |
info:eu-repo/semantics/article |
|