• Asian-Australasian Journal of Animal Sciences
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• v.27 no.4
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• pp.587-591
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• 2014

Automatic milking systems (AMS) rely upon voluntary cow traffic (the voluntary movement of cattle around a farm) for milk harvesting and feed consumption. Previous research on conventional milking systems has shown differences between dairy cow breeds for intake and milk production, however, the ability to manipulate voluntary cow traffic and milking frequency on AMS farms through breed selection is unknown. This study investigated the effect of breed (Holstein Friesian versus Illawarra) on voluntary cow traffic as determined by gate passes at the Camden AMS research farm dairy facility. Daily data on days in milk, milk yield, gate passes and milking frequency for 158 Holstein Friesian cows and 24 Illawarra cows were collated by month for the 2007 and 2008 years. Illawarra cows had 9% more gate passes/day than Holstein cows over the duration of the study; however, the milking frequency and milk yield of both breeds were similar. Gate passes were greatest for both breeds in early lactation and in the winter (June to August) and summer (December to February) seasons. These findings highlight an opportunity to translate increased voluntary cow movement associated with breed selection into increased milking frequencies, milk production and overall pasture-based AMS performance.

• Journal of Animal Environmental Science
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• v.3 no.2
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• pp.87-95
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• 1997

This study was peformed to compare work routine time and performance of milking systems by measuring motion and time in milking procedure. Data were collected from thirteen dairy farms among which milking was done by bucket in two farms, by pipelines in three, by tandem parlors in four including one remodeled side-opening, by herringborn parlors in three and by a parallel milking parlor. Recording time and motion for milking parlor. Recording time and motion for milking procedure was performed by stopwatch and notebook computer. Work routine elements were recorded and calculated into cows milked per-man-hour(CMPH). The results are as follows : Average milking time per cow(MTPC) in bucket and pipeline milking systems usually installed in cow stall were 442.7 and 395.8 seconds, respectively. And average CMPH of bucket and pipeline milking system were 144.5, 303.3, 272.5 and 380.3 seconds, respectively. And CMPH of tandem, herringbone, parallel and modified side-opening systems were 24.9, 11.9, 13.2 and 9.5 heads, respectively. CMPH was the highest in the tandem milking system and the lowest in the bucket milking facilities. CMPH, when milked in a parlor resulted in high value compared with bucket or pipeline milking systems installed in cow stable. They showed considerably low CMPH compared with the results of other countries. The reason why so low CMPH could be derived from type and mechanization of facilities and equipment, operator's ability, number of operator, idle time and milking procedure.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.169-172
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• 2001

This research was carried out to investigate the quantity of Holstein milking cow manure excreted and their characteristics. The average body weight of the Holstein milking cow during experiment was 550.0kg, and fried intake(DM basis), water consumption, milk yield was 16.7, 85.4, 24.4k7/day/head, repectively. The average manure production of Holstein milking cow was 63.5kg/day/head(feces 42.3, urine 10.2kg). The average moisture content of feces and urine was 83.9%, 96.9%, respectively. Wastewater pollutant concentration of $BOD_5$(Biochemical Oxygen demand). $COD_{Mn}$ (Chemical Oxygen demand), SS(Suspended Solids), T-N(Total Nitrogen) and T-P(Total Phosphorus), excreted from Holstein milking cow was 16,560, 40,329, 78,500, 2,854, 577mg/ l in feces and 4,580, 7,575, 370, 4,164, 7mg/ l in urine, repectively.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1093-1098
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• 2017

Objective: The aim of the current study was to describe the relationship between milk yield and lactation number, stage, length and milking frequency in Korean Holstein dairy cows using an automatic milking system (AMS). Methods: The original data set consisted of observations from April to October 2016 of 780 Holstein cows, with a total of 10,751 milkings. Each time a cow was milked by an AMS during the 24 h, the AMS management system recorded identification numbers of the AMS unit, the cow being milking, date and time of the milking, and milk yield (kg) as measured by the milk meters installed on each AMS unit, date and time of the lactation, lactation stage, milking frequency (NoM). Lactation stage is defined as the number of days milking per cows per lactation. Milk yield was calculated per udder quarter in the AMS and was added to 1 record per cow and trait for each milking. Milking frequency was measured the number of milkings per cow per 24 hour. Results: From the study results, a significant relationship was found between the milk yield and lactation number (p<0.001), with the maximum milk yield occurring in the third lactation cows. We recorded the highest milk yield, in a greater lactation length period of early stage (55 to 90 days) at a $4{\times}$ milking frequency/d, and the lowest milk yield was observed in the later stage (>201 days) of cows. Also, milking frequency had a significant influence on milk yield (p<0.001) in Korean Holstein cows using AMS. Conclusion: Detailed knowledge of these factors such as lactation number, stage, length, and milking frequency associated with increasing milk yield using AMS will help guide future recommendations to producers for maximizing milk yield in Korean Dairy industries.

• 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.

• Journal of Animal Environmental Science
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• v.8 no.3
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• pp.159-164
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• 2002

The distance between teats of each head on twenty heads of holstein was measured in Nation Livestock Research Institute of Rural Development Administration to find design variables on the teat-cup attachment system of the auto-milking system before milking. The distance between teats was tested by the steps for milk producing in the morning and evening. The results from this study is summarized as follow. 1 The maximum and minimum length between front teats were 297mm and 112mm respectively, the maximum and minimum length between rear teats were 231mm and 36mm and the maximum and minimum length between left front and left rear were 220 and 84mm. And the maximum length of right front and right rear were 205mm and 90mm. A relative position of the each teats was asymmetric. 2. The size of teats, the length between front teats, and the length between rear teats by lactating period were very much changed for its milking. 3. The design variables on the teat-cup attachment system was found by the length between each teats tested. Since the position of teat-cup is changed by milking environment for a cow to milk, the design variables should be considered to be asymmetric area between four teat of COW.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.3
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• pp.422-430
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• 2014

Pasture-based automatic milking systems (AMS) require cow traffic to enable cows to be milked. The interval between milkings can be manipulated by strategically allocating pasture. The current experiment investigated the effect of replacing an allocation of grazed pasture with grazed soybean (Glycine max) with the hypothesis that incorporating soybean would increase voluntary cow traffic and milk production. One hundred and eighty mixed age, primiparous and multiparous Holstein-Friesian/Illawarra cows were randomly assigned to two treatment groups (n = 90/group) with a $2{\times}2$ Latin square design. Each group was either offered treatments of kikuyu grass (Pennisetum clandestinum Hoach ex Chiov.) pasture (pasture) or soybean from 0900 h to 1500 h during the experimental period which consisted of 2 periods of 3 days following 5 days of training and adaptation in each period with groups crossing over treatments after the first period. The number of cows trafficking to each treatment was similar together with milk yield (mean ${\approx}18$ L/cow/d) in this experiment. For the cows that arrived at soybean or pasture there were significant differences in their behaviour and consequently the number of cows exiting each treatment paddock. There was greater cow traffic (more cows and sooner) exiting pasture allocations. Cows that arrived at soybean stayed on the allocation for 25% more time and ate more forage (8.5 kg/cow/d/allocation) relative to pasture (4.7 kg/cow/d/allocation). Pasture cows predominantly replaced eating time with rumination. These findings suggest that replacing pasture with alternative grazeable forages provides no additional incentive to increase voluntary cow traffic to an allocation of feed in AMS. This work highlights the opportunity to increase forage intakes in AMS through the incorporation of alternative forages.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.238-247
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• 2014

The milking robot system is very important to detect correctly the teats position in the moving condition of cow. Also, the robot manipulator must control tracking the teat cup to the detected teat position. The presented milking robot is designed using the one point laser sensor for teat position detection. The teats of cow are detected by the laser scanning unit and the manipulator has the function of 3 axes moving control unit. The presented teat detection method and the electrical driving manipulator have the advantages of a simple, low cost and very quiet. The designed manipulator is realized by the totally electrical motor and servo poison control algorithm with velocity PID compensation. The presented robot is realized using the teat detection unit, 4 teat cups, 3 axes robot arm, 6 servo motors and automatic milking control line. The designed robot is experimented in the cow farm and is satisfied with the designed performance specification for milking robot manipulator.

• Journal of Animal Science and Technology
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• v.49 no.1
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• pp.137-146
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• 2007

This study was conducted to determine fertilizer nutrient and pollutant production of Holstein dairy cattle by estimating manure characteristics. The moisture content of feces was 83.9% and 95.1% for urine. The pH of feces and urine were in the ranges of 7.0～7.4 and 7.5～7.8, respectively. The average BOD5, COD, SS, T-N, T-P concentrations of the dairy feces were 18,294, 52,765, 102,889, 2,575, and 457mg/ℓ, respectively. Dairy urine showed lower levels of BOD5(5,455mg/ℓ), COD(8,089mg/ℓ), SS(593mg/ℓ), T-N(3,401mg/l), and T-P(13mg/ℓ) than feces. The total daily produced pollutant amounts of a dairy cow were 924.1g(Milking cow), 538.8g(Dry cow), 284.4g(Heifer) of BOD5, 2,336.5g (Milking cow), 1,651.8g(Dry cow), 734.1g(Heifer) of COD and 4,210.1g(Milking cow), 2,417.1g(Dry cow), 1,629.1g(Heifer) of SS and 194.8g(Milking cow), 96.4g(Dry cow), 58.3g(Heifer) of T-N and 24.0g(Milking cow), 10.2g(Dry cow), 6.1g(Heifer) of T-P. The calculated amount of pollutants produced by a 450kg dairy cow for one year were 181.3kg of BOD5, 492.5kg of COD, 899.9kg of SS, 36.0kg of T-N and 4.1kg of T-P. The total yearly estimated pollutant production from all head(497,261) of dairy cattle in Korea is 90,149 tons of BOD5, 244,890 tons of COD, 447,491 tons of SS, 17,898 tons of T-N and 2,008 tons of T-P. The fertilizer nutrient concentrations of dairy feces was 0.26% N, 0.1% P2O5 and 0.14% K2O. Urine was found to contain 0.34% N, 0.003% of P2O5 and 0.31% K2O. The total daily fertilizer nutrients produced by dairy cattle were 197.4g (Milking cow), 97.4g(Dry cow), and 57.9g(Heifer) of Nitrogen, 54.2g(Milking cow), 22.2g(Dry cow), and 14.2g(Heifer) of P2O5 and 110.8g(Milking cow), 80.4g (Dry cow), and 39.5g(Heifer) of K2O. The total yearly estimated fertilizer nutrient produced by a 450kg dairy animal is 36.2kg of N, 8.8kg of P2O5, 24.6kg of K2O. The estimated yearly fertilizer nutrient production from all dairy cattle in Korea is 18,000 tons of N, 4,397 tons of P2O5, 12,206 tons of K2O. Dairy manure contains useful trace minerals for crops, such as CaO and MgO, which are contained in similar levels to commercial compost being sold in the domestic market. Concentrations of harmful trace minerals, such as As, Cd, Hg, Pb, Cr, Cu, Ni, Zn, met the Korea compost standard regulations, with some of these minerals being in undetected amounts.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.7
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• pp.1044-1052
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• 2015

The aim of this modelling study was to investigate the effect of large herd size (and land areas) on walking distances and milking interval (MI), and their impact on milk yield and economic penalties when 50% of the total diets were provided from home grown feed either as pasture or grazeable complementary forage rotation (CFR) in an automatic milking system (AMS). Twelve scenarios consisting of 3 AMS herds (400, 600, 800 cows), 2 levels of pasture utilisation (current AMS utilisation of 15.0 t dry matter [DM]/ha, termed as 'moderate'; optimum pasture utilisation of 19.7 t DM/ha, termed as 'high') and 2 rates of incorporation of grazeable complementary forage system (CFS: 0, 30%; CFS = 65% farm is CFR and 35% of farm is pasture) were investigated. Walking distances, energy loss due to walking, MI, reduction in milk yield and income loss were calculated for each treatment based on information available in the literature. With moderate pasture utilisation and 0% CFR, increasing the herd size from 400 to 800 cows resulted in an increase in total walking distances between the parlour and the paddock from 3.5 to 6.3 km. Consequently, MI increased from 15.2 to 16.4 h with increased herd size from 400 to 800 cows. High pasture utilisation (allowing for an increased stocking density) reduced the total walking distances up to 1 km, thus reduced the MI by up to 0.5 h compared to the moderate pasture, 800 cow herd combination. The high pasture utilisation combined with 30% of the farm in CFR in the farm reduced the total walking distances by up to 1.7 km and MI by up to 0.8 h compared to the moderate pasture and 800 cow herd combination. For moderate pasture utilisation, increasing the herd size from 400 to 800 cows resulted in more dramatic milk yield penalty as yield increasing from c.f. 2.6 and 5.1 kg/cow/d respectively, which incurred a loss of up to $AU 1.9/cow/d. Milk yield losses of 0.61 kg and 0.25 kg for every km increase in total walking distance (voluntary return trip from parlour to paddock) and every one hour increase in MI, respectively. The high pasture utilisation combined with 30% of the farm in CFR in the farm increased milk yield by up to 1.5 kg/cow/d, thereby reducing loss by up to $0.5/cow/d (c.f. the moderate pasture and 800 cow herd scenario). Thus, it was concluded that the successful integration of grazeable CFS with pasture has the potential to improve financial performance compared to the pasture only, large herd, AMS.