• Physical Therapy Korea
• /
• v.3 no.1
• /
• pp.1-11
• /
• 1996

The purpose of this study was to analyse the subtalar joint movement characteristics in human stance phase. The data of subtalar joint movement patterns are collected by CTA(calcaneus to tibia angle) measurements. CTA is defined as a angle formed between the bisect of the posterior shank and bisect of the posterior heel, as determined by placement of the retroreflective markers. The angle measured in degrees. The participants are 74 healthy individuals (37 men and 37 women) who have no orthopedic and neurological impairment, aged from 19 to 29 years(mean 22.95). Prior to participation, each subjecct informed the procedures of experiment from researcher and assistant researcher. The equipments of this study are walking grid, marking tapes, goniometer, video camera, monitor and ink for foot print are used in the study. In order to determine the statistical significance of result, the paired t-test and Pearson correlation were applied at the 0.05 level of significance. The results were as follows : 1. The reliability of measured CTA value are showed a high correlation, ranged from .86 - .94. 2. The mean value of step width are 7.67cm in men and 6cm in women. So, significant difference between men and women in 0.05 level of significance. 3. There was significant difference between man and women's TOA(toe out angle)(p<0.05). 4. The CTA of female's is more higher than male's one, however not statistical difference between man and women(p>0.05). 5. The CTA is reduced according to increasing TOA(p<0.05).

• Journal of Animal Science and Technology
• /
• v.52 no.6
• /
• pp.467-473
• /
• 2010

A total of 4,323,781 records for informal 16 primary linear descriptive traits of dairy cows in Holstein breed from 1988 to 2007 in USA were analyzed to estimate adjustment factors for lactation number and stage. While all factors in the model were highly significant (P < 0.01), major influences on linear type traits were due to lactation number and stage. The frequencies of lactation number 1 through 6 were 58.6, 22.0, 11.8, 4.8, 2.1, and 0.8%, respectively. Further, the frequencies of lactation stage were 0.7, 76.9, 15.3, 4.9, and 2.1%, respectively, for springing, early, medium, late, and dry. To adjust 16 linear traits (stature, dairy form, strength, body depth, rump width, rump angle, legs rear view, leg set, foot angle, fore udder, rear udder height, rear udder width, udder support, udder depth, and front teat placement), additive and multiplicative adjustment factors of lactation number (lactations 2 to 4) and stage (springing, medium, late and dry) were estimated with the solutions in the generalized linear model, assigning lactation 1 and stage early as base class. Additive adjustment factors of lactation number ranged from -1.23 to 2.908, while multiplicative factors ranged from 0.853 to 2.207. Further, additive and multiplicative adjustment factors for lactation stage ranged from -0.668 to 0.785, and from 0.891 to 1.154. Application of adjustment factors to 20 randomly sampled sub-data sets produced the results that additive adjustment factors for both lactation number and stage reduced more mean square of lactation number and stage over 16 linear traits than any combination of adjustments, and leaded additive adjustment factors for both lactation number and stage as a choice of methods for adjustment of informal 16 primary linear type traits collected by classifiers of AI studs.

• Journal of agriculture & life science
• /
• v.51 no.6
• /
• pp.89-105
• /
• 2017

This study utilized 32,312 records of 17 linear type and 10 conformation traits(including final scores) of Hanwoo cows in the KAIA(Korea Animal Improvement Association) ('09~'10), with 60,556 animals in the pedigree file. Traits included stature, body length, strength, body depth, angularity, shank thickness, rump angle, rump length, pin bone width, thigh thickness, udder volume, teat length, teat placement, foot angle, hock angle, rear leg back view, body balance, breed characteristic, head development, forequarter quality, back line, rump, thigh development, udder development, leg line, and final score. Genetic and residual(co) variances were estimated using bi-trait pairwise analyses with EM-REML algorithm. Herd-year-classifier, year at classification, and calving stage were considered as fixed effects with classification months as a covariate. The heritability estimates ranged from 0.03(teat placement) to 0.42(body length). Rump length had the highest positive genetic correlation with pin bone width(0.96). Moreover, stature, body length, strength, and body depth had the highest positive genetic correlations with rump length, pin bone width, and thigh thickness(0.81-0.94). Stature, body length, strength, body depth, rump length, pin bone width, and thigh thickness traits also had high positive genetic correlations.

• Journal of agriculture & life science
• /
• v.50 no.1
• /
• pp.167-178
• /
• 2016

This study was conducted to estimate genetic parameters for milk production and linear type traits in Holstein dairy cattle in Korea. The data including milk yields, fat yields, protein yields, fat percent, protein percent, somatic score and 15 linear type traits for 10,218 first parity cows collected by Dairy Cattle Improvement Center, National Agricultural Cooperative, Korea, which were calving from January 2009 to April 2013. Genetic and error (co)variances between two traits selected form 19 traits were estimated using bi-trait pairwise analyses with WOMBAT package. The estimated heritabilities for milk yield(MY), fat yield(FY), protein yield(PY), fat percent(FP), protein percent(PP), somatic cell score(SCS), udder depth(UD), udder texture(UT), median suspensory(MS), fore udder attachment(FUA), front teat placement (FTP), rear attachment height(RAH), rear attachment width(RAW), rear teat placement(RTP), front teat length(FTL), foot angle(FA), heel depth(HD), bone quality(BQ), rear legs side view(RLSV), rear legs rear view(RLRV) and locomotion(LC) were 0.128, 0.144, 0.100, 0.273, 0.333, 0.090, 0.179, 0.066, 0.104, 0.109, 0.127, 0.099, 0.059, 0.069, 0.154, 0.014, 0.010, 0.052, 0.065, 0.175 and 0.031, respectively. Among the genetic correlations, UD, UT, FTP, RAW, FTL, FA and RLSV with MY were -0.334, 0.271, 0.445, 0.544, 0.076, -0.281 and -0.228, respectively, and MS, FTP, RTP, FTL, FA, BQ, RLSV, RLRV and LC with PP were -0.147, -0.182, -0.262, -0.136, 0.355, 0.311, 0.135, 0.233 and 0.143, respectively. Especially, MY had the highest positive genetic correlation with RAW (0.544), while SCS had the highest negative genetic correlation with LC (-0.603). FP had negative genetic correlation with most udder traits, whereas, FP had positive genetic correlation with leg and hoof traits (0.056 - 0.355).

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