A Robotic milking cluster system with the manipulator for an automatic milking system was designed and built for farmer to work easily and comfortably during milking processing. The cluster system was composed of screws, cams and links for power transmission, DC motors, the Quick Basic one-chip microprocessor, the vision system for image processing, and tea-cups. Software, written in Visual C+ and Quick Basic, combined the function of image capture, image processing, milking cluster control, and control into one control. The unit was made to transfer from four fixed points to four teats with four teat-cups. Performance tests of the cluster unit, the fully integrated system, were conducted to attach and detach the teat-cup on the teat of a artificial cow. The transfer programming provided for a teat-cup milking loop during the system starts and comes back the original fixed point at the manipulator of it for milking. It transferred the teat-cup with a success rate of more than 70%. The average time it took ot perform the milking loop was about 20 seconds.
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.
Total three hundred and fourteen dairy cows were used in this study to analysis of correlation between milking levels and automatic milking system (AMS). Cows were divided into five groups according to their milking levels (over 50 kg/day, 49~40 kg/day, 39~30 kg/day, 29~20 kg/day, 19~10 kg/day). All groups were compared with daily milking number, rejected number by AMS, residence time at AMS, milking time, flow rate of milk. Daily milking number and milking time were higher in the group of over 50 kg and 49~40 kg than that of other groups (p<0.05). There are no correlation on rejected number by AMS, residence time at AMS and flow rate of milk between milking levels and AMS. In addition, we found that the milk yield affected to feed intake and rumination of dairy cows. In conclusion, present results indicated that installation of AMS on dairy farms with high milk producing cows might be affected positively.
Automatic milking systems (AMS) have been increasingly introduced to Korean dairy farms. However, in comparison with conventional milking systems (CMS), some negative changes in milk quality are being observed. The use of AMS leads to an increase in milking frequency, which in turn might result in higher physical stress on the milk, possibly causing changes in the milk fat globule (MFG) membrane. Therefore, the purpose of this study was to examine the effect of the different milking systems on the milk quality, with a focus on milk fat properties. At the same time, we studied the effect of feeding the dairy cows with protected fat. Raw milk samples were taken monthly from individual cows as well as from bulk tanks at four AMS and four CMS dairy farms. We measured quality-related parameters such as MFG size distribution, free fatty acid content and composition, and acid values. Although most results showed no significant differences with regard to the milking system, we found a relatively high positive correlation between MFG size and milk fat content. Moreover, larger MFG size was observed in the milk when cows had been fed protected fat. The significantly higher (P< 0.05) free fatty acid content of milk observed under this experimental condition could be attributed to higher milking frequency as a result of using AMS.
Vijayakumar, Mayakrishnan;Park, Ji Hoo;Ki, Kwang Seok;Lim, Dong Hyun;Kim, Sang Bum;Park, Seong Min;Jeong, Ha Yeon;Park, Beom Young;Kim, Tae Il
Asian-Australasian Journal of Animal Sciences
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제30권8호
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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.
Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas. Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit. Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values. Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.
To develop an automatic detecting system of body temperature of dairy cattle while milking, measurement of the temperature of mammary skin using three thermometers attached into the lining of teat cup was carried out for 23 dairy cattle, whereas measurement of the temperature of milk while milking was also performed for 263 animals. For the latter experiment, three thermometers were attached at 10cm(left and right) and 20 cm away from an individual milk collector on the milk transporting hose. Taking the rectal temperature was accompanied all the time for the experiments. The measurement of the temperature of mammary skin using teat cup was successful for 11 of 23 dairy cattle(47.8%) and the mean temperature was $33.5^{\circ}C$ with the mean difference of $5.2^{\circ}C$ from the mean rectal temperature. The measurement of the temperature of milk using the thermometers onto the milk transporting hose while milking was very successful , From 37.3 to $38.4^{\circ}C$ of rectal temperature, the temperature of milk was almost the same and from 38.5 to $39.5^{\circ}C$ of rectal temperature, the temperature of milk tended to be low with the difference of 0.1$^{\circ}C$. From 39.6 to $41^{\circ}C$ of rectal temperature, the temperature of milk tended to be low with the difference of $0.2-0.6^{\circ}C$. These results indicated that automatic detection of body temperature whether low or high can be possible if the temperature of milk is taken while milking and if it is connected to the integration system by on-line.
These studies were performed to find out the possibility of automatic detection of the diseased animal with fever by farmers themselves. Firstly, the body temperature of 331 dairy cows was investigated according to major disease symptoms manifested. Secondly, AD 590 thermometer was used to take the teat temperature of the milking cows to determine the possibility of automatic taking of body temperature while milking. The temperatures of scapha of ear and coccygeal artery part were also taken fur the non-milking dairy cows and Korean native cowl 1. The average body temperature of dairy cows associated with respiratory diseases puerperal disease, or mastitis was higher than normal temperature denoting respectively 39.8,39.6, and $39.3{\circ}C.2.$ The teat temperaure of the milking dairy cows with fever($39.5~39.6{\circ}C$) and the cows with mastitis was respectively 1.02 and 0.56${\circ}C$ higher than that of normal cows. 3. The average teat temperature taken by AD 590 was 33.91, 34.93, and 34.50${\circ}C$ in normal milking dairy cows, cows with fever(39.5~39.6${\circ}C$), and cows with mastitis, respectively. 4. The mean temperatures at scapha and coccygeal part of non-milking dairy cows and Korean native cows were 35.62 and 36.63${\circ}C$, respectively. It was concluded that AD 590 thermometer would be usable for the farmers to automatirally detect the body temperature of dairy cows while milking and subsquently to find the diseased cow with fever and that the scapha of ear and coccygeal artery part of the cattle could be the body parts of simply detecting body temperature of non-milking cattle.
한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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pp.779-790
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1993
A prototype of the feeding-milking robot was developed in the Hungarian Institute of Agricultural Engineering in 1988-89. Before starting with the operation tests the cleaning system had to be elaborated . The cleaning system has two parts. Those are the complete cleaning of the system, producing a practically sterile state, as well as flushing through the milking device between milking of two cows. Separate electronic sensor development was necessary for both system which can connect to the control system of the robot. To clean the system pneumatic air input was applied. As an effect of the local adjustment of the electronic control system optimal flow conditions can be formed what is more favourable comparing to the earlier solutions of cleaning due to the mechanical effect. In the flushing through overpressure air is applied. The air and the cleaning liquid input duration can be adjusted to the local conditions. The electronic control unit can be connected to the electric ircuits of robot.
To maintain a predominantly pasture-based system, the large herd milked by automatic milking rotary would be required to walk significant distances. Walking distances of greater than 1-km are associated with an increased incidence of undesirably long milking intervals and reduced milk yield. Complementary forages can be incorporated into pasture-based systems to lift total home grown feed in a given area, thus potentially 'concentrating' feed closer to the dairy. The aim of this modelling study was to investigate the total land area required and associated walking distance for large automatic milking system (AMS) herds when incorporating complementary forage rotations (CFR) into the system. Thirty-six 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 6 rates of replacement of each of these pastures by grazeable CFR (0%, 10%, 20%, 30%, 40%, 50%) were investigated. Results showed that AMS cows were required to walk greater than 1-km when the farm area was greater than 86 ha. Insufficient pasture could be produced within a 1 km distance (i.e. 86 ha land) with home-grown feed (HGF) providing 43%, 29%, and 22% of the metabolisable energy (ME) required by 400, 600, and 800 cows, respectively from pastures. Introduction of pasture (moderate): CFR in AMS at a ratio of 80:20 can feed a 400 cow AMS herd, and can supply 42% and 31% of the ME requirements for 600 and 800 cows, respectively with pasture (moderate): CFR at 50:50 levels. In contrast to moderate pasture, 400 cows can be managed on high pasture utilisation (provided 57% of the total ME requirements). However, similar to the scenarios conducted with moderate pasture, there was insufficient feed produced within 1-km distance of the dairy for 600 or 800 cows. An 800 cow herd required 140 and 130 ha on moderate and high pasture-based AMS system, respectively with the introduction of pasture: CFR at a ratio of 50:50. Given the impact of increasing land area past 86 ha on walking distance, cow numbers could be increased by purchasing feed from off the milking platform and/or using the land outside 1-km distance for conserved feed. However, this warrants further investigations into risk analyses of different management options including development of an innovative system to manage large herds in an AMS farming system.
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