• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.65-76
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• 2003

The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.171-176
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• 2002

Physical parameters of milk cow were measured to design and build RMS(Robotic Milking System) with a tape-measurer and body parameter measurer. The parameters are very important variables to design an RMS. For the working zone space of an RMS manipulator and the movement blunting of milk cow, an interval frame was installed on the stall bottom, and then cow's behavioral reactions were tested. The results from this study is summarized as follow. 1. On the general physical condition measurement, the maximum, minimum and average body length of cow which is related to the space that the manipulator could work into the RMS were 175cm, 144cm, and 163cm respectively. It appeared that the average distance between bottom and chest was 60cm. 2. The average length between fore teats, fore and hind teats and hind teats were 178mm, 150mm and 95mm respectively. It appeared that the average length between bottom and teat attachments was 544mm, and the average length between fore teats and tail-end was 331mm. 3. Although a cow kept a some extent length between hind legs for milking, it looked a stable pose. However, the cow kept a some extent distance between front legs for milking, it looked a unstable pose. Based on results of this test, an interval frame of stall bottom should be installed around the position which was located at its hind legs.

• Asian-Australasian Journal of Animal Sciences
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• v.8 no.1
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• pp.67-73
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• 1995

This study showed that models of energy utilization(EU) developed for grazing cattle in oil palm plantations is valid as the simulated results shows an agreement with actual data of calves and cows body weight changes collected from Brahman x Kedah-Kelantan herd on Pengeli Timor Plantation. Simulation runs on EU models demonstrated that the growth pattern of male and female calves and the weight changes of cows are similar and showed slight variation from the actual data but with no significant difference (p > 0.05). Parameter values such as metabolizability (q), dry matter digestibility(DMD) of herbage and voluntary intake of grazing cattle (VIG) and faecal output/body weight ratio (F) of the animals which were collected from the field are essential in bearing the pattern of body weight changes of the calves and cows in relation to increase in time, physiological status and quality of herbage grazed by these animals in the production system. The EU models is suitable for determining the metabolizable energy requirements and to predict the production of grazing cattle according to quality of the feed on offer.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.868-872
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• 2005

Individual management of the animal is the first step towards reaching the goal of precision livestock farming that aids animal welfare. Accurate recognition of each individual animal is important for precise management. Electronic identification of cattle, usually referred to as RFID (Radio Frequency Identification), has many advantages for farm management. In practice, however, RFID implementations can cause several problems. Reading speed and distance must be optimized for specific applications. Image processing is more effective than RFID for the development of precision farming system in livestock. Therefore, the aim of this paper is to attempt the identification of cattle by using image processing. The majority of the research on the identification of cattle by using image processing has been for the black-and-white patterns of the Holstein. But, native Japanese and Korean cattle do not have a consistent pattern on the body, so that identification by pattern is impossible. This research aims to identify to Japanese black cattle, which does not have a black-white pattern on the body, by using image processing and a neural network algorithm. 12 Japanese black cattle were tested. Values of input parameter were calculated by using the face image values of 12 cows. The face was identified by the associate neural memory algorithm, and the algorithm was verified by the transformed face image, for example, of brightness, distortion, noise and angle. As a result, there was difference due to a transformation ratio of the brightness, distortion, noise, and angle. The algorithm could identify 100% in the range from -30 to +30 degrees of brightness, -20 to +40 degrees of distortion, 0 to 60% of noise and -20 to +30 degree of angle transformed images.

• Journal of Veterinary Clinics
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• v.10 no.1
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• pp.65-94
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• 1993

This study examined metabolic profiles of 1349 Holstein cows from 91 commercial herds. Thirteen parameters which are consisted of twelve blood components and body condition score were examined and their mean values. standard deviations and standard limits, which are 80% confidential limits, in each lactational stage were reported. The variations of each parameter affected by season, individual milk yield, adjusted corrected milk yield of herd. and lactation number were also reported. A model of metabolic profile test applicable to this country where the average number of cows in a herd is small as to be fifteen is designed. Metabolic profiles as reflected in each parameter were discussed in relation to adequacy of dietary intake for production, milk production, reproductive performance, and diseases, and the possible measure to improve productivity of dairy cows were proposed. Much of the variation in parameters was due to differences between herds, and less to differences between seasons, differences between individual milk yield, and differences between lactational stages. As the average herd size in this country is small, it is believed that all the cows in a herd must be sampled, and the individual result of each parameter was compared with the standard limit for each lactational stage, and the percentage of cows which are outside the standard limits in a herd was calculated to use as a criteria for evaluation of the herd. Data outside the 99% confidential limits were to be deleted at first, but when the trends of the data outside the 99% confidential limits are same as the trends of the data within 99% confidential limits, the deleted data must be reviewed again, otherwise some important informations would be missed. The mean concentration of blood urea nitrogen in this study was much higher than that was reported in England, U.S.A. and Japan, and it was similar to the upper limits reported in England, U.S.A. and Japan. So it was thought that the concentration of blood urea nitrogen is improper as a criteria for protein intake. The increase of serum total protein cocentration beyond standard limits was due to increase of serum globulin concentration in most of the cows. The correlation coefficient between serum and protein and serum globulin concentration was 0.83. Serum globulin concentration was negatively related to adjusted corrected milk of herd. Serum albumin, calcium and magnessium concentrations were negatively related to adjusted corrected milk of herd, which indicate that high-producing individual or high-producing herd have not taken sufficient protein/amino acids, calcium and magnessium. Packed cell volume was negatively related to adjusted corrected milk of the herd, and the trend was same In each lactational stage. The correlation coefficient between serum and packed cell volume was 0.16 and the correlation was very weak. Blood glucose concentration was lowest in early lactational stage, which indicates negative energy balance in early lactational stage. Blood glucose concentration was negatively related to adjusted corrected milk of herd from peak to late lactational stage, which indicates negative energy balance during the period in high-producing individuals or high-producing herds. Correlation coefficient between serum aspartate aminotransferase activity and serum ${\gamma}$-glutamyltransferase activity was 0.41, and this indicates that serum ${\gamma}$-glutamyltransferase should be included as a parameter of metabolic profile test to evaluate liver function. Body condition score of dairy cows in this country was lower than that of Japan in every lactational stages, and the magnitude of increase in body condition score during middle and late lactational stages was small. Metabolic profile can not be evaluated with solely nutritional intake. When an individual or large percentage of cows in a herd have adnormal values In parameters of metabolic profile test, veterinary clinician and nutritionist should cooperate so as to diagnose diseases and to calculate the e of no운ents simultaneously.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.345-352
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• 2009

This study utilized 332,625 records of linear type scores consisting for 15 primary traits, 22,175 final score and 84,612 pedigree information of 22,175 Holstein cows from 1993 to 2007 in Korea to estimate genetic parameters for 16 type traits. Genetic and error (co)variances between two traits selected from 16 traits were estimated using bi-trait pairwise analyses with DFREML package. The estimated heritabilities for stature (ST), strength (STR), body depth (BD), dairy form (DF), rump angle (RA), thurl width (TW), rear legs side view (RLSV), foot angle (FA), fore udder attachment (FUA), rear udder height (RUH), rear udder width (RUW), udder cleft (UC), udder depth (UD), front teat placement (FTP), front teat length (FTL) and final score (FS) were 0.31, 0.21, 0.25, 0.10, 0.29, 0.19, 0.09, 0.06, 0.12, 0.13, 0.12, 0.08, 0.26, 0.20, 0.28 and 0.15, respectively. ST had the highest positive genetic correlation with BD (0.90), while RLSV had the highest negative genetic correlation with FA (-0.56). RA had negative genetic correlation with most udder traits (-0.17~-0.02). Especially, RUW had the higher positive genetic correlation with STR (0.60), BD (0.62), and TW (0.49), however, UD had the higher negative genetic correlation with STR (-0.40) and BD (-0.40). FTL had negative genetic correlation with FUA, RUH, RUW, UC and UD. FS had positive genetic correlation with UC, UD and FTP (0.12, 0.18 and 0.20). However, additional research is needed on the use of these parameters in the genetic evaluation because estimated genetic and error variance-covariance matrices were not positive definite.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.689-694
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• 2003

Weight records of Hanwoo cows from birth to 36 months of age collected in Daekwanryeong branch, National Livestock Research Institute(NLRI) were fitted to Gompertz, von Bertalanffy and Logistic functions. For the growth curve parameters fitted on individual records using Gompertz model, the mean estimates of mature weight(A), growth ratio(b) and growth rate(k) were 383.42 ${\pm}$ 97.29kg, 2.374 ${\pm}$ 0.340 and 0.0037 ${\pm}$ 0.0012, respectively, and mean estimates of body weight, age and daily gain rate at inflection were 141.05 ${\pm}$ 35.79kg, 255.63 ${\pm}$ 109.09 day and 0.500 ${\pm}$ 0.123kg, respectively. For von BertalanfTy model, the mean estimates of A, b and k were 410.47 ${\pm}$ 117.98kg, 0.575${\pm}$0.057 and 0.003 ${\pm}$ 0.001, and mean estimates of body weight, age and daily gain at inflection were 121.62 ${\pm}$ 34.94kg, 211.02 ${\pm}$ 105.53 and 0.504 ${\pm}$ O.l24kg. For Logistic model, the mean estimates of A, b and k were 347.64 ${\pm}$ 97.29kg, 6.73 ${\pm}$ 0.34 and 0.006 ${\pm}$ 0.0018, and mean estimates of body weight, age and daily gain at inflection were 173.82 ${\pm}$ 37.25kg, 324.47 ${\pm}$ 126.85 and 0.508 ${\pm}$ 0.131kg. Coefficients of variation for the A, b and k parameter estimates were 25.3%, 14.3% and 32.4%, respectively, for Gompertz model, 28.70/0, 9.9% and 33.3% for von Bertalanffy model, and 27.9°/0, 5.0% and 30.0% for Logistic model.