scholarly journals An Improved Approach to Automated Measurement of Body Condition Score in Dairy Cows Using a Three-Dimensional Camera System

Animals ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 72
Author(s):  
Rodrigo I. Albornoz ◽  
Khageswor Giri ◽  
Murray C. Hannah ◽  
William J. Wales
Keyword(s):  
Dairy Cows ◽  
Body Condition ◽  
Body Condition Score ◽  
Three Dimensional ◽  
Data Sets ◽  
Camera System ◽  
Visual Method ◽  
Condition Score ◽  
Body Condition Scoring ◽  
Over Time

Body condition scoring is a valuable tool used to assess the changes in subcutaneous tissue reserves of dairy cows throughout the lactation resulting from changes to management or nutritional interventions. A subjective visual method is typically used to assign a body condition score (BCS) to a cow following a standardized scale, but this method is subject to operator bias and is labor intensive, limiting the number of animals that can be scored and frequency of measurement. An automated three-dimensional body condition scoring camera system is commercially available (DeLaval Body Condition Scoring, BCS DeLaval International AB, Tumba, Sweden), but the reliability of the BCS data for research applications is still unknown, as the system’s sensitivity to change in BCS over time within cows has yet to be investigated. The objective of this study was to evaluate the suitability of an automated body condition scoring system for dairy cows for research applications as an alternative to visual body condition scoring. Thirty-two multiparous Holstein-Friesian cows (9 ± 6.8 days in milk) were body condition scored visually by three trained staff weekly and automatically twice each day by the camera for at least 7 consecutive weeks. Measurements were performed in early lactation, when the greatest differences in BCS of a cow over the lactation are normally present, and changes in BCS occur rapidly compared with later stages, allowing for detectable changes in a short timeframe by each method. Two data sets were obtained from the automatic body condition scoring camera: (1) raw daily BCS camera values and (2) a refined data set obtained from the raw daily BCS camera data by fitting a robust smooth loess function to identify and remove outliers. Agreement, precision, and sensitivity properties of the three data sets (visual, raw, and refined camera BCS) were compared in terms of the weekly average for each cow. Sensitivity was estimated as the ratio of response to precision, providing an objective performance criterion for independent comparison of methods. The camera body condition scoring method, using raw or refined camera data, performed better on this criterion compared with the visual method. Sensitivities of the raw BCS camera method, the refined BCS camera method, and the visual BCS method for changes in weekly mean score were 3.6, 6.2, and 1.7, respectively. To detect a change in BCS of an animal, assuming a decline of about 0.2 BCS (1–8 scale) per month, as was observed on average in this experiment, it would take around 44 days with the visual method, 21 days with the raw camera method, or 12 days with the refined camera method. This represents an increased capacity of both camera methods to detect changes in BCS over time compared with the visual method, which improved further when raw camera data were refined as per our proposed method. We recommend the use of the proposed refinement of the camera’s daily BCS data for research applications.

scholarly journals Hormonal profile and body condition scoring in dairy cows during pre partum and post partum periods

2015 ◽  
Vol 84 (2) ◽  
pp. 141-151 ◽  
Author(s):  
Mária Vargová ◽  
Vladimír Petrovič ◽  
Jana Konvičná ◽  
Marián Kadaši ◽  
Peter Zaleha ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Body Condition ◽  
Negative Correlation ◽  
Body Condition Score ◽  
Post Partum ◽  
Mean Values ◽  
Hormonal Profile ◽  
Condition Score ◽  
Body Condition Scoring ◽  
The Mean

The aim of this study was to evaluate the dynamics of selected indicators of energy, hormonal profile, body condition score (BCS) and their relationships in dairy cows of the Slovak Pied Cattle from 3 weeks before parturition to 9 weeks after. Significant differences were found in the mean values of non-esterified fatty acids (NEFA) (P < 0.001) and β-hydroxybutyrate (BHB) (P < 0.05). According to BCS results, the dry cows were overweight (4.42 ± 0.75 points). After calving the cows lost weight significantly, as the BCS was 3.25 ± 0.30 points at 9 weeks post partum (P < 0.001). The highest concentration of leptin was recorded before calving (26.80 ± 11.47 ng/ml). The concentrations of insulin and ghrelin did not change significantly (an increase in insulin concentrations from 580.8 ± 66.30 IU/ml to 625.50 ± 174.90 IU/ml and a decrease in ghrelin concentrations from 29.25 ± 4.82 pg/ml to 26.57 ± 5.35 pg/ml were found comparing 3 weeks to 1 week before parturition, respectively). Relationships between the hormones showed positive correlation between insulin and leptin (r = 0.220, P < 0.05), BCS and leptin (r = 0.360, P < 0.001), BCS and insulin (r = 0.232, P < 0.05) and negative correlation between leptin and ghrelin (r = -0.235, P < 0.05), BCS and ghrelin (r = -0.257, P < 0.05). These data provide evidence that the variations in the concentrations of leptin, ghrelin, and insulin are related to variations in the BCS. Negative correlation between leptin and ghrelin contributes to the argument that leptin negatively regulates ghrelin.

Body condition score and reproductive performance in dairy cows in Greece

2007 ◽  
Vol 2007 ◽  
pp. 60-60
Author(s):  
G. Oikonomou ◽  
G. Arsenos ◽  
G.E. Valergakis ◽  
A. Tsiaras ◽  
G. Banos
Keyword(s):  
Dairy Cows ◽  
Body Condition ◽  
Reproductive Performance ◽  
Energy Content ◽  
Body Condition Score ◽  
Reliable Estimate ◽  
Condition Score ◽  
Body Condition Scoring ◽  
Body Energy ◽  
The Impact

Various studies in dairy cows have shown that their Body Condition Score (BCS) effectively reflects their nutritional status and energy content (Ferguson et al. 1994). Extremes in BCS and BCS losses have been identified as a risk factor for health problems and reduced reproductive efficiency (Markusfeld et al. 1997, Lopez-Gatius et al. 2003). Body condition scoring is easy and inexpensive to perform and gives a reliable estimate of body energy reserves. Hence, in practice, BCS can be used as a tool for ration formulation and management decisions concerning reproduction of dairy cows (Banos et al. 2004). The objective of this study was to determine and quantify the impact of BCS in the reproductive performance of primiparous Holstein cows.

Estimating body weight, body condition score, and type traits in dairy cows using three dimensional cameras and manual body measurements

2020 ◽  
Vol 236 ◽  
pp. 104054 ◽  
Author(s):  
B.M. Martins ◽  
A.L.C. Mendes ◽  
L.F. Silva ◽  
T.R. Moreira ◽  
J.H.C. Costa ◽  
...  
Keyword(s):  
Body Weight ◽  
Dairy Cows ◽  
Body Condition ◽  
Body Condition Score ◽  
Three Dimensional ◽  
Body Measurements ◽  
Condition Score ◽  
Type Traits

scholarly journals Dairy Cows' Body Condition Score. Effects on reproduction, health and milk production. Use in farm management

2017 ◽  
Vol 59 (4) ◽  
pp. 320
Author(s):  
G. OIKONOMOU (Γ. ΟΙΚΟΝΟΜΟΥ) ◽  
Z. BAZDAGIANNI (Ζ. ΜΠΑΣΔΑΓΙΑΝΝΗ) ◽  
G. E. VALERGAKIS (Γ. Ε. ΒΑΛΕΡΓΑΚΗΣ)
Keyword(s):  
Adverse Effects ◽  
Dairy Cows ◽  
Milk Production ◽  
Body Condition ◽  
Body Condition Score ◽  
Fatty Tissue ◽  
Special Equipment ◽  
Body Regions ◽  
Condition Score ◽  
Body Condition Scoring

Body Condition Scoring (BCS) is an assessment of dairy cows' subcutaneous fatty tissue that can provide useful information on their body energy reserves. It is a quick and easy to perform method that does not require special equipment and can be easily used at farm level. A body condition scoring method based on visual observation of specific body regions has been described. A 5 point scale (1 = emaciated, 5 = obese) is used. Low BCS and high BCS losses were found to have adverse effects on cows' reproductive performance. Low or high BCS and high BCS losses were also found to have adverse effects on cows' health, while they were also found to significantly affect milk production. Body condition score has medium-high heritability and significant genetic correlation with reproduction. Body condition score levels should be 3-3.25 at calving, not higher than 3.25 at drying off and at least 2.5 60-80 days post calving. Farmers and their consultants should try to achieve these goals through proper management. Body condition scoring can be performed at calving, 30 days post calving, at first artificial insemination, at mid-lactation and at drying off.

Automatic Measurement and Determination of Body Condition Score of Cows Based on 3D Images Using CNN

2018 ◽  
Vol 30 (2) ◽  
pp. 206-213 ◽  
Author(s):  
Masahiro Shigeta ◽  
◽  
Reiichirou Ike ◽  
Hiroshi Takemura ◽  
Hayato Ohwada
Keyword(s):  
Dairy Cows ◽  
Body Condition ◽  
Body Condition Score ◽  
Three Dimensional ◽  
Automatic Measurement ◽  
Two Dimensional ◽  
Long Period ◽  
Condition Score ◽  
Two Dimensional Images

According to the Ministry of Agriculture, Forestry, and Fisheries of Japan, the number of rearing houses has been decreasing in Japan in recent years due to lower business volumes. However, the number of rearing animals per house has been increasing, and in such situations, management of a herd of cows becomes very important. However, although systems such as a milking robot and an automatic feeding machine have been designed and implemented, an automatic measurement system to evaluate the body condition score (BCS), which is used for nutrition management of dairy cows, has not yet become popular. There have been many prior studies on this subject; however, none of them have succeeded in creating an inexpensive and highly accurate system that is capable of capturing images over a long period of time. The purpose of this study was to develop a system that continuously and automatically captures images of cows using a camera over a long period of time and to carry out a highly accurate determination of BCS. By attaching a three-dimensional camera to a sorting gate of a milking robot, we have developed a system that automatically captures images of cows as they pass through the gate. Data obtained from the captured images are automatically accumulated in a server. Thus, we successfully obtained a huge amount of data within two months. All parts of the image except the dairy cows were removed from the obtained three-dimensional data, and the three-dimensional data were then converted into two-dimensional images. Subsequently, the two-dimensional images were analyzed using a convolutional neural network, resulting in 89.1% of the answers being correct. When the acceptable error was ±0.25, the rate of correct answers is 94.6%, and the average absolute error, which is the average of the difference between the predicted BCS and the actual BCS for all test data, is 0.05. Although we used images that do not cover the entire body of the cow because of the position of the camera and the variation in captured parts (depending on images), we have successfully achieved a high accuracy. This promises that even higher accuracy can be achieved by automating the flow of data and carrying out the appropriate treatment of data to determine BCS.

scholarly journals The Capacity of Holstein-Friesian and Simmental Cows to Correct a Negative Energy Balance in Relation to Their Performance Parameters, Course of Lactation, and Selected Milk Components

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1674
Author(s):  
Ilona Strączek ◽  
Krzysztof Młynek ◽  
Agata Danielewicz
Keyword(s):  
Fatty Acid ◽  
Energy Balance ◽  
Dairy Cows ◽  
Body Condition ◽  
Body Condition Score ◽  
Negative Energy ◽  
Negative Energy Balance ◽  
Holstein Friesian ◽  
Condition Score ◽  
Peak Lactation

A significant factor in improving the performance of dairy cows is their physiological ability to correct a negative energy balance (NEB). This study, using Simmental (SIM) and Holstein-Friesian (HF) cows, aimed to assess changes in NEB (non-esterified fatty acid; body condition score; and C16:0, C18:0, and C18:1) and its effect on the metabolic efficiency of the liver (β-hydroxybutyrate and urea). The effects of NEB on daily yield, production at peak lactation and its duration, and changes in selected milk components were assessed during complete lactation. Up to peak lactation, the loss of the body condition score was similar in both breeds. Subsequently, SIM cows more efficiently restored their BCS. HF cows reached peak lactation faster and with a higher milk yield, but they were less able to correct NEB. During lactation, their non-esterified fatty acid, β-hydroxybutyrate, C16:0, C18:0, C18:1, and urea levels were persistently higher, which may indicate less efficient liver function during NEB. The dynamics of NEB were linked to levels of leptin, which has anorectic effects. Its content was usually higher in HF cows and during intensive lactogenesis. An effective response to NEB may be exploited to improve the production and nutritional properties of milk. In the long term, it may extend dairy cows’ productive life and increase lifetime yield.

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