Estimation of bodyweight from body measurements and determination of body measurements on Limousin cattle using digital image analysis

2016 ◽  
Vol 56 (12) ◽  
pp. 2060 ◽  
Author(s):  
Serkan Ozkaya ◽  
Wojciech Neja ◽  
Sylwia Krezel-Czopek ◽  
Adam Oler
Keyword(s):  
Image Analysis ◽  
Body Length ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Digital Camera ◽  
Body Measurements ◽  
Analysis Software ◽  
Body Area ◽  
Image Analysis Software

The objective of this study was to predict bodyweight and estimate body measurements of Limousin cattle using digital image analysis (DIA). Body measurements including body length, wither height, chest depth, and hip height of cattle were determined both manually (by measurements stick) and by using DIA. Body area was determined by using DIA. The images of Limousin cattle were taken while cattle were standing in a squeeze chute by a digital camera and analysed by image analysis software to obtain body measurements of each animal. While comparing the actual and predicted body measurements, the accuracy was determined as 98% for wither height, 97% for hip height, 94% for chest depth and 90.6% for body length. Regression analysis between body area and bodyweight yielded an equation with R2 of 61.5%. The regression equation, which included all body traits, resulted in an R2 value of 88.7%. The results indicated that DIA can be used for accurate prediction of body measurements and bodyweight of Limousin cattle.

Accuracy of body measurements using digital image analysis in female Holstein calves

2012 ◽  
Vol 52 (10) ◽  
pp. 917 ◽  
Author(s):  
Serkan Ozkaya
Keyword(s):  
Image Analysis ◽  
Body Length ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Digital Camera ◽  
Body Measurements ◽  
Analysis Software ◽  
High Prediction ◽  
Holstein Calves ◽  
The Difference

The objective of this study was to determine the accuracy of body measurements (BM) in Holstein female calves using digital image analysis. BM including body length, wither height, chest depth, hip height, and hip width of calves were recorded by stick and tape measurements at birth, weaning and 24 weeks of age. Then photos of calves were taken while calves were standing in a squeeze chute by a digital camera and were analysed by image analysis software to obtain BM of each calf from the image in centimetres. After comparing the actual and predicted BM, the accuracy was determined as 71, 97 and 99% for body length, 69, 87 and 99% for wither height, 43, 98 and 99% for chest depth, 74, 99 and 99% for hip height and 53, 99 and 98% for hip width at birth, weaning and 24 weeks of age, respectively. The difference between actual and predicted BM was significant at birth (P < 0.01). Although there were numerical differences between actual and predicted BM, the differences were not significant at weaning and 24 weeks of age (P > 0.01). According to these results, the BM estimation of Holstein female calves using digital image analysis produced high prediction accuracy at weaning and 24 weeks of age, but not at birth. The data presented in this study indicate that the digital image analysis provides very close agreement and reality for prediction of BM of Holstein female calves.

scholarly journals Anatomical Characteristics of Garcinia lucida (Vesque) and Scorodophloeus zenkeri (Harms) Wood and Debarking Response in the South Region Cameroon

2017 ◽  
Vol 6 (4) ◽  
pp. 132
Author(s):  
Marie Caroline Momo Solefack ◽  
Hans Beeckman ◽  
Lucie Felicite Temgoua ◽  
Ghislain Kenguem Kinjouo
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Analysis Software ◽  
Anatomical Changes ◽  
Image Analysis Software ◽  
Conductive Zone ◽  
Before And After

The aim of this work was to investigate the possible anatomical changes of Garcinia lucida and Scorodophloeus zenkeri after the removal of their bark. Debarking was done on individuals of each species at 1.30 m from the soil. The wound was rectangular in shape with 30 cm side. There was a follow-up every three months for nine months during which the survival and rate of regeneration of the bark were recorded. A block of cube was cut from the regenerated and intact wood of species for microtomy and microscopy activities. On the cross-section of each wood, vessel features like density and diameter were measured before and after wounding. Semi-automatic measurements were made using the SpectrumSee digital image analysis software. In the wood of the two species, it appeared that the density of the vessels before debarking was significantly comparable to the density after debarking, while the diameter of vessels in the regenerated wood was smaller. The cambial area increased slightly in the rainy season for all species. After nine months all the species started the restoration of their conductive zone. G. lucida heals its wound more rapidly than S. zenkeri.

scholarly journals Free digital image analysis software helps to resolve equivocal scores in HER2 immunohistochemistry

2015 ◽  
Vol 468 (2) ◽  
pp. 191-198 ◽  
Author(s):  
Henrik O. Helin ◽  
Vilppu J. Tuominen ◽  
Onni Ylinen ◽  
Heikki J. Helin ◽  
Jorma Isola
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Analysis Software ◽  
Image Analysis Software

Tumor Volume in Radical Prostatectomy Specimens Assessed by Digital Image Analysis Software Correlates With Other Prognostic Factors

2010 ◽  
Vol 183 (5) ◽  
pp. 1808-1815 ◽  
Author(s):  
Justin C. Sherwin ◽  
George Mirmilstein ◽  
John Pedersen ◽  
Nathan Lawrentschuk ◽  
Damien Bolton ◽  
...  
Keyword(s):  
Image Analysis ◽  
Prognostic Factors ◽  
Radical Prostatectomy ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Tumor Volume ◽  
Analysis Software ◽  
Image Analysis Software

scholarly journals The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle

2008 ◽  
Vol 51 (2) ◽  
pp. 120-128 ◽  
Author(s):  
S. Ozkaya ◽  
Y. Bozkurt
Keyword(s):  
Image Analysis ◽  
Body Weight ◽  
Beef Cattle ◽  
Body Length ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Regression Equation ◽  
Body Area ◽  
Prediction Ability ◽  
Brown Swiss

Abstract. The objective of this study was to predict body weight (BW) of pre-slaughtering beef cattle using digital image analysis. Data used in this study were collected from slaughterhouses in Isparta and nearby provinces from 140 animals. Selected body measurements such as body weight (BW), wither height (WH), body length (BL), chest depth (CD), hip width (HW), hip height (HH) and body area (BA) of different breeds of beef cattle were combined and compared by digital image analysis. The body area was included as a different parameter for prediction of BW instead of chest girth. However, regression equation that included only body area gave the lowest R2 value for Holstein (18.0%), but the R2 value was 43.2 and 51.7% for Brown Swiss and crossbred animals, respectively. The regression equation which included all body traits resulted in R2 values 35.3, 85.1, and 79.6% for Holstein, Brown Swiss and crossbred, respectively. The regression equation which included body area and body length showed that prediction ability of digital image analysis was high for prediction of BW in Brown Swiss and crossbred animals compared to Holsteins (R2 82.6, 76.5, and 29.5%, respectively). Results indicated that the prediction ability of digital image analysis was low for prediction of BW. Although possibility of using body area as a parameter in predicting BW is low it can be developed by further and better designed experiments.

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