6.5 Dairy cow condition scoring

1981 ◽  
Vol 4 ◽  
pp. 349-353 ◽  
Author(s):  
P. M. Mulvany
Keyword(s):  
Milk Yield ◽  
Body Condition ◽  
Dairy Cow ◽  
Individual Performance ◽  
Animal Performance ◽  
Basic Part ◽  
Health Measures ◽  
Final Item ◽  
Body Condition Scoring ◽  
The Individual

Records on animal performance form a basic part of management. Without records it is not possible to measure the effect of changes in management nor assess the individual performance of an animal. Condition scoring provides a means of recording body condition and may assist in monitoring changes in body reserves. However, it is of limited use if other, more significant, records are not kept. It provides an enhancement to a recording scheme in which reproduction, production health and feeding/grazing records are kept. These records should be simple. Some data are required on calvings and inseminations, milk yield and/or rate of growth, preventative and curative health measures and on the probable feed available to an animal and how this feed is utilized. Body condition scoring will provide some data for this final item.

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.

scholarly journals Software-Automatized Individual Lactation Model Fitting, Peak and Persistence and Bayesian Criteria Comparison for Milk Yield Genetic Studies in Murciano-Granadina Goats

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1505 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Francisco Javier Navas González ◽  
Vincenzo Landi ◽  
José Manuel León Jurado ◽  
Juan Vicente Delgado Bermejo ◽  
...  
Keyword(s):  
Milk Yield ◽  
Linear Models ◽  
Model Fitting ◽  
Goat Milk ◽  
Individual Performance ◽  
Individual Variability ◽  
Curve Shape ◽  
Lactation Curve ◽  
Future Challenges ◽  
The Individual

SPSS model syntax was defined and used to evaluate the individual performance of 49 linear and non-linear models to fit the lactation curve of 159 Murciano-Granadina goats selected for genotyping analyses. Lactation curve shape, peak and persistence were evaluated for each model using 3107 milk yield controls with an average of 3.78 ± 2.05 lactations per goat. Best fit (Adjusted R2) values (0.47) were reached by the five-parameter logarithmic model of Ali and Schaeffer. Three main possibilities were detected: non-fitting (did not converge), standard (Adjusted R2 over 75%) and atypical curves (Adjusted R2 below 75%). All the goats fitted for 38 models. The ability to fit different possible functional forms for each goat, which progressively increased with the number of parameters comprised in each model, translated into a higher sensitivity to explaining curve shape individual variability. However, for models for which all goats fitted, only moderate increases in explanatory and predictive potential (AIC, AICc or BIC) were found. The Ali and Schaeffer model reported the best fitting results to study the genetic variability behind goat milk yield and perhaps enhance the evaluation of curve parameters as trustable future selection criteria to face the future challenges offered by the goat dairy industry.

Equine obesity and the role of the veterinary nurse

UK-Vet Equine ◽  
2021 ◽  
Vol 5 (6) ◽  
pp. 265-268
Author(s):  
Clarissa Seeley ◽  
Stella Chapman
Keyword(s):  
Body Condition ◽  
The Body ◽  
Body Condition Scoring ◽  
Client Education ◽  
Inherent Problem ◽  
Equine Obesity ◽  
The Individual ◽  
The Uk

Equine obesity is defined as a medical disease in which excess body fat has accumulated to such an extent that it has an adverse effect on the general health of the horse. Obesity is a cause for concern, with one-third of the equine population in the UK being regarded as obese, although owner recognition of obesity in horses is an inherent problem, with many underestimating the body condition or weight of their horse. This is further complicated by the fact that with larger framed horses, or horses that are already overweight, assessing body condition is more difficult. There are a number of ways to assess body condition and the most practical means of regular assessment is body condition scoring, although this is regarded as subjective. As with many diseases and disorders, the cause of obesity is multifactorial. However, the most common reason for a horse to become obese is overfeeding, coupled with a lack of exercise. Obesity can be addressed with client education and veterinary nurses can provide advice on weight management programmes. However, these need to be tailored to the individual horse and owners need to recognise that they are entering into a long-term commitment.

scholarly journals Impact of Heat Stress on Selected Parameters of Robotic Milking

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3114
Author(s):  
Roman Gálik ◽  
Gabriel Lüttmerding ◽  
Štefan Boďo ◽  
Ivana Knížková ◽  
Petr Kunc
Keyword(s):  
Heat Stress ◽  
Dairy Cows ◽  
Milk Yield ◽  
Dairy Cow ◽  
Performance Parameters ◽  
New Knowledge ◽  
Humidity Index ◽  
Robotic Milking ◽  
The Individual ◽  
Two Parameters

The values of the temperature-humidity index and its influence on the performance parameters of dairy cows were monitored on four farms located in the southern part of the central Slovakia during a period of three years. The observed parameters included: the milk yield per cow per day, average milk speed and maximum milk speed. The thermal-humidity index was calculated based on a formula. The individual periods were divided according to the achieved THI. The results of dairy cows with a milk yield of 29 kg to 31 kg show that there is not a decrease in the milk yield per milking if the THI value is lower than 68. It was also found that there was a decrease in the milk yield per dairy cow in the robotic milking parlor for a THI value greater than 72. The influence of a THI value higher than 68 in these dairy cows results in a higher average milk speed, as well as a higher maximum milk speed. These two parameters are not yet in the main area of research interest. This study enriches the area with new knowledge, according to which dairy cows can show thermal stress by increasing the milk speed as well as the maximum milk speed.

scholarly journals A Dairy Cow Body Condition Scoring System and Its Relationship to Selected Production Characteristics

1982 ◽  
Vol 65 (3) ◽  
pp. 495-501 ◽  
Author(s):  
E.E. Wildman ◽  
G.M. Jones ◽  
P.E. Wagner ◽  
R.L. Boman ◽  
H.F. Troutt ◽  
...  
Keyword(s):  
Body Condition ◽  
Dairy Cow ◽  
Scoring System ◽  
Body Condition Scoring ◽  
Production Characteristics

scholarly journals Monitoring body condition score of reintroduced banteng (Bos javanicus D’Alton, 1923) into Salakphra Wildlife Sanctuary, Thailand

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9041 ◽  
Author(s):  
Praeploy Kongsurakan ◽  
Rattanawat Chaiyarat ◽  
Seree Nakbun ◽  
Nikorn Thongthip ◽  
Panat Anuracpreeda
Keyword(s):  
Body Condition ◽  
Body Condition Score ◽  
Natural Habitat ◽  
Individual Performance ◽  
Camera Traps ◽  
The Body ◽  
Wildlife Sanctuary ◽  
Bos Javanicus ◽  
Condition Score ◽  
The Individual

Background Banteng (Bos javanicus d’Alton 1823) are an endangered species, highly sensitive to habitat structure and quality. In many areas, banteng were extinct and needed to be reintroduced to restore their population. Thus, understanding the responses of body condition of reintroduced banteng to their habitat was important for ensuring the sustainability of a reintroduction program. The aim of the present study was to evaluate the body condition of banteng after reintroduction into the Salakphra Wildlife Sanctuary in Thailand based on photographs from camera-traps carried out between July 2016 and November 2018. Methods Seven banteng were bred at the Khao Nampu Nature and Wildlife Education Center and systematically reintroduced into the Salakphra Wildlife Sanctuary in December 2015 (four) and July 2016 (three). The seven reintroduced adults and two newborns (from the 2015 group) were captured via camera traps in 2018. The body condition scoring (BCS) obtained from these photographs was used to identify the individual performance of all seven adults after their reintroduction. Results The BCS scores in reintroduced adult banteng, both males and females, (between 5 and 7 years old) increased significantly over time after reintroduction into a natural habitat (p < 0.05), although the BCS scores in females were not significantly different between the second and third years (p > 0.05). Conclusions The results from the present study suggest that camera traps are a practical tool to assess the BCS of reintroduced banteng, and can be used to monitor their condition post-release. These techniques may be appropriate for translocation programs elsewhere.

Comparison of two methods of assessing dairy cow body condition score

2009 ◽  
Vol 77 (1) ◽  
pp. 95-98 ◽  
Author(s):  
Jeffrey M Bewley ◽  
Robert E Boyce ◽  
David J Roberts ◽  
Michael P Coffey ◽  
Michael M Schutz
Keyword(s):  
Body Condition ◽  
Dairy Cow ◽  
Body Condition Score ◽  
Scoring Systems ◽  
Regression Equations ◽  
Two Systems ◽  
Condition Score ◽  
Body Condition Scoring ◽  
The Uk ◽  
Body Condition Scores

Two body condition scoring systems were compared for assessing body condition of cows at the Scottish Agricultural College's Crichton Royal Farm. The weekly body condition scores (BCS) were collected for a period of 12 weeks (5 September–21 November). Scores were obtained using the primary systems utilized within the UK and USA. The USBCS were obtained by the same evaluator each week, while the UKBCS were obtained by two different evaluators alternating between weeks. Paired scores (n=2088) between the two systems within week were moderately correlated (r=0·75, P<0·0001). Regression equations to convert scores between the two systems were created using the GLM procedure of SAS (SAS Institute Inc., Cary NC, USA). The simple GLM models to convert from UK to US scores and US to UK scores were USBCS=1·182+0·816 * UKBCS (R2=0·56) and UKBCS=0·131+0·681 (R2=0·56), respectively. These equations may be used to interpret scores within the literature obtained using these two BCS systems, although they must be used with caution.

Body Condition Scoring bei Hunden

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

Export Citation Format

Share Document