Regression Analysis for Dairy Cattle Body Condition Scoring Based on Dorsal Images

2018 ◽  
pp. 557-566
Author(s):  
Heng Pan ◽  
Jinrong He ◽  
Yu Ling ◽  
Guoliang He
Keyword(s):  
Regression Analysis ◽  
Dairy Cattle ◽  
Body Condition ◽  
Body Condition Scoring

scholarly journals Comparison of a classical with a highly formularized body condition scoring system for dairy cattle

animal ◽  
2014 ◽  
Vol 8 (12) ◽  
pp. 1971-1977 ◽  
Author(s):  
A. Isensee ◽  
F. Leiber ◽  
A. Bieber ◽  
A. Spengler ◽  
S. Ivemeyer ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Body Condition ◽  
Scoring System ◽  
Body Condition Scoring

scholarly journals The Potential of Post-Mortem Carcass Assessments in Reflecting the Welfare of Beef and Dairy Cattle

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 959
Author(s):  
Melody Knock ◽  
Grace A. Carroll
Keyword(s):  
Regression Analysis ◽  
Dairy Cattle ◽  
Body Condition ◽  
Skin Lesions ◽  
Meat Inspection ◽  
Carcass Weight ◽  
Post Mortem ◽  
Lesion Score ◽  
Inspection Data ◽  
General Indicator

There is increasing interest in utilizing meat inspection data to help inform farmers of the health and welfare of their herds. The aim of this study was to determine whether ante-mortem measures of welfare in beef and dairy cattle (N = 305) were associated with post-mortem measures at a United Kingdom (UK) abattoir. Multiple regression analysis was used to determine the ability of ante-mortem measures of lameness, cleanliness, skin lesions, hair loss and body condition in predicting hot carcass weight and the frequency of carcass bruising. For beef cattle, lameness score (p = 0.04), cleanliness score (p = 0.02) and age (p < 0.001), were predictors of carcass bruise score while lameness score (p = 0.03), body condition (p = 0.01) and sex (p < 0.001) were predictors of hot carcass weight. For dairy cattle, sex (p < 0.001) and slaughter day (p < 0.001) were predictors of carcass bruise score while skin lesion score (p = 0.01), body condition (p < 0.001), age (p < 0.001), slaughter day (p < 0.001) and number of moves (p = 0.01) were predictors of hot carcass weight. These results suggest that recording carcass weight and carcass bruising at meat inspection may have potential as a general indicator of health and welfare status in cattle. However, animal characteristics and variables, such as slaughter day and abattoir staffing, should be taken into account when interpreting the results.

scholarly journals Validation of a Commercial Automated Body Condition Scoring System on a Commercial Dairy Farm

Animals ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. 287 ◽  
Author(s):  
Israel L. Mullins ◽  
Carissa M. Truman ◽  
Magnus R. Campler ◽  
Jeffrey M. Bewley ◽  
Joao H. C. Costa
Keyword(s):  
Dairy Cattle ◽  
Body Condition ◽  
Management Practice ◽  
Interobserver Reliability ◽  
Subcutaneous Fat ◽  
The Body ◽  
Automated System ◽  
Multiple Time ◽  
Camera System ◽  
Body Condition Scoring

Body condition scoring (BCS) is the management practice of assessing body reserves of individual animals by visual or tactile estimation of subcutaneous fat and muscle. Both high and low BCS can negatively impact milk production, disease, and reproduction. Visual or tactile estimation of subcutaneous fat reserves in dairy cattle relies on their body shape or thickness of fat layers and muscle on key areas of the body. Although manual BCS has proven beneficial, consistent qualitative scoring can be difficult to implement. The desirable BCS range for dairy cows varies within lactation and should be monitored at multiple time points throughout lactation for the most impact, a practice that can be hard to implement. However, a commercial automatic BCS camera is currently available for dairy cattle (DeLaval Body Condition Scoring, BCS DeLaval International AB, Tumba, Sweden). The objective of this study was to validate the implementation of an automated BCS system in a commercial setting and compare agreement of the automated body condition scores with conventional manual scoring. The study was conducted on a commercial farm in Indiana, USA, in April 2017. Three trained staff members scored 343 cows manually using a 1 to 5 BCS scale, with 0.25 increments. Pearson’s correlations (0.85, scorer 1 vs. 2; 0.87, scorer 2 vs. 3; and 0.86, scorer 1 vs. 3) and Cohen’s Kappa coefficients (0.62, scorer 1 vs. 2; 0.66, scorer 2 vs. 3; and 0.66, scorer 1 vs. 3) were calculated to assess interobserver reliability, with the correlations being 0.85, 0.87, and 0.86. The automated camera BCS scores were compared with the averaged manual scores. The mean BCS were 3.39 ± 0.32 and 3.27 ± 0.27 (mean ± SD) for manual and automatic camera scores, respectively. We found that the automated body condition scoring technology was strongly correlated with the manual scores, with a correlation of 0.78. The automated BCS camera system accuracy was equivalent to manual scoring, with a mean error of −0.1 BCS and within the acceptable manual error threshold of 0.25 BCS between BCS (3.00 to 3.75) but was less accurate for cows with high (>3.75) or low (<3.00) BCS scores compared to manual scorers. A Bland–Altman plot was constructed which demonstrated a bias in the high and low automated BCS scoring. The initial findings show that the BCS camera system provides accurate BCS between 3.00 to 3.75 but tends to be inaccurate at determining the magnitude of low and high BCS scores. However, the results are promising, as an automated system may encourage more producers to adopt BCS into their practices to detect early signs of BCS change for individual cattle. Future algorithm and software development is likely to increase the accuracy in automated BCS scoring.

scholarly journals Assessing the potential value for an automated dairy cattle body condition scoring system through stochastic simulation

2010 ◽  
Vol 70 (1) ◽  
pp. 126-150 ◽  
Author(s):  
J.M. Bewley ◽  
Boehlje ◽  
A.W. Gray ◽  
H. Hogeveen ◽  
S.J. Kenyon ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Stochastic Simulation ◽  
Body Condition ◽  
Scoring System ◽  
Potential Value ◽  
Body Condition Scoring

scholarly journals Frequency and Precision of Body Condition Scoring in Dairy Cattle

1994 ◽  
Vol 77 (6) ◽  
pp. 1543-1547 ◽  
Author(s):  
P.J. Hady ◽  
J.J. Domecq ◽  
J.B. Kaneene
Keyword(s):  
Dairy Cattle ◽  
Body Condition ◽  
Body Condition Scoring

Body Condition Scoring bei Hunden

2017 ◽  
Vol 27.2 (02) ◽  
pp. 10-11 ◽  
Author(s):  
Stefan Störk
Keyword(s):  
Body Condition ◽  
Body Condition Scoring

scholarly journals Relation of Automated Body Condition Scoring System and Inline Biomarkers (Milk Yield, β-Hydroxybutyrate, Lactate Dehydrogenase and Progesterone in Milk) with Cow’s Pregnancy Success

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1414
Author(s):  
Ramūnas Antanaitis ◽  
Vida Juozaitienė ◽  
Dovilė Malašauskienė ◽  
Mindaugas Televičius ◽  
Mingaudas Urbutis ◽  
...  
Keyword(s):  
Lactate Dehydrogenase ◽  
Reproductive Success ◽  
Milk Yield ◽  
Body Condition ◽  
Body Condition Score ◽  
The Body ◽  
Time Analyzer ◽  
Condition Score ◽  
Pregnancy Status ◽  
Body Condition Scoring

The aim of the current study was to evaluate the relation of automatically determined body condition score (BCS) and inline biomarkers such as β-hydroxybutyrate (BHB), milk yield (MY), lactate dehydrogenase (LDH), and progesterone (mP4) with the pregnancy success of cows. The cows (n = 281) had 2.1 ± 0.1. lactations on average, were 151.6 ± 0.06 days postpartum, and were once tested with “Easy scan” ultrasound (IMV imaging, Scotland) at 30–35 d post-insemination. According to their reproductive status, cows were grouped into two groups: non-pregnant (n = 194 or 69.0% of cows) and pregnant (n = 87 or 31.0% of cows). Data concerning their BCS, mP4, MY, BHB, and LDH were collected each day from the day of insemination for 7 days. The BCS was collected with body condition score camera (DeLaval Inc., Tumba, Sweden); mP4, MY, BHB, and LDH were collected with the fully automated real-time analyzer Herd Navigator™ (Lattec I/S, Hillerød, Denmark) in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). Of all the biomarkers, three differences between groups were significant. The body condition score (BCS) of the pregnant cows was higher (+0.49 score), the milk yield (MY) was lower (−4.36 kg), and milk progesterone in pregnant cows was (+6.11 ng/mL) higher compared to the group of non-pregnant cows (p < 0.001). The pregnancy status of the cows was associated with their BCS assessment (p < 0.001). We estimated that cows with BCS > 3.2 were 22 times more likely to have reproductive success than cows with BCS ≤ 3.2.

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