Optimising profitability and productivity of pasture-based dairy farms with automatic milking systems

There is a large variability in profitability and productivity between farms operating with automatic milking systems (AMS). The objectives of this study were to identify the physical factors associated with profitability and productivity of pasture-based AMS and quantify how changes in these factors would affect farm productivity. We utilised two different datasets collected between 2015 and 2019 with information from commercial pasture-based AMS farms. One contained annual physical and economic data from 14 AMS farms located in the main Australian dairy regions; the other contained monthly, detailed robot-system performance data from 23 AMS farms located across Australia, Ireland, New Zealand, and Chile. We used linear mixed models to identify the physical factors associated with different profitability (Model 1) and partial productivity measures (Model 2). Additionally, we conducted a Monte Carlo simulation to evaluate how changes in the physical factors would affect productivity. Our results from Model 1 showed that the two main factors associated with profitability in pasture-based AMS were milk harvested/robot (MH; kg milk/robot per day) and total labour on-farm (full-time equivalent). On average, Model 1 explained 69% of the variance in profitability. In turn, Model 2 showed that the main factors associated with MH were cows/robot, milk flow, milking frequency, milking time, and days in milk. Model 2 explained 90% of the variance in MH. The Monte Carlo simulation showed that if pasture-based AMS farms manage to increase the number of cows/robot from 54 (current average) to ∼ 70 (the average of the 25% highest performing farms), the probability of achieving high MH, and therefore profitability, would increase from 23% to 63%. This could make AMS more attractive for pasture-based systems and increase the rate of adoption of the technology.

Improving parlor efficiency in block calving pasture-based dairy systems through the application of a fixed milking time determined by daily milk yield and milking frequency

Adjusting end-of-milking criteria, in particular applying a maximum milking time determined by expected milk yield at an individual milking session, is one strategy to optimize parlor efficiency. However, this strategy can be difficult to apply practically on farm due to large differences in session milk yield, driven by milking interval, which affects milking routines and can be limited by in-parlor technology. The objective of this study was to test the hypothesis that a single fixed milking time (duration) could be applied at all milking sessions without compromising milk production or udder health for a range of milking intervals. To test the hypothesis, 4 experimental herds were established: (1) herd milked twice a day (TAD) using a 10- and 14-h interval, (2) herd milked TAD using an 8- and 16-h interval, (3) herd milked 3 times in 2 d using a 10-19-19-h interval, and (4) herd milked once a day (OAD). Herds consisted of 40 cows each, and were established for two 6-wk experimental periods, one in peak lactation and the other in mid-late lactation. Within each herd, half the cows had an end-of-milking criterion of 0.35 kg/min (Flow), and the other half had milking ended after a fixed period of time (FixedT) based on the average milking session yield, the daily milk yield divided by average number of milkings per day, irrespective of milking interval. We found no differences in daily milk yield between end-of-milking criteria due to residual milk from one milking likely increasing the proportion of milk in the udder cistern at the next milking session for the FixedT treatment. However, fat yield was compromised when the percentage of the herd with a truncated milking exceeded an estimated 33% at a milking session, which occurred in the TAD 8-16 herd due to the divergence from the average milking interval (in the case of TAD, 12-12 h). Applying a fixed milking time had no detrimental effects on udder health, except in the OAD herd in mid-late lactation, which had both a higher cell count and new intramammary infection rate. This warrants further investigation, although the majority of cultured bacteria were coagulase-negative staphylococci (CNS). Consequently, we conclude that, in general, with appropriate monitoring (e.g., weekly inspection) to ensure the proportion of the herd with truncated milkings does not exceed 33%, farmers in pasture-based dairy systems can use a fixed milking time to improve parlor efficiency.

Short communication: Increasing the teatcup removal settings of the last milking quarter did not reduce box time in a pasture-based automatic milking system

This research followed our previous experimental and simulation work on the effect of different teatcup removal settings based on the rolling average milk flowrate and on milking duration at the quarter and udder levels. The aims of this experiment were to (1) quantify the differences in quarter milking duration in a pasture-based automatic milking system and (2) test the effect of increasing the milk flowrate at which teatcups are removed on the last milking quarter on udder milking duration, box time, milk production rate, and somatic cell count (SCC). Milking duration is an important component of efficiency and profitability in conventional and automatic milking systems. Additionally, quarters within an udder have significantly different milk yields and milking durations. This study used data from April to May 2018 of a pasture-based automatic milking system to evaluate quarter milking duration differences between quarters of an udder. Subsequently, we experimentally evaluated the use of 2 percentage-based teatcup removal settings applied to the last milking quarter (i.e., the last quarter with a teatcup still attached) on milking duration, box time, milk production rate, and SCC. The teatcup removal settings were at 30 or 50% of the last quarter's rolling average milk flowrate, while the other quarters remained at the 30% level. The selection of the quarter that would receive the more aggressive teatcup removal setting was determined by identifying the last quarter with a teatcup attached in every milking. Sixty-nine cows were divided into 2 groups that each received 1 of the 2 treatments for a 1-wk period and then switched to the other treatment for a second week. For the months of April and May 2018, quarter milking duration was significantly different between the quarter with the longest and the second longest milking duration within an udder. The quarter with the longest milking duration was milked on average 49 s longer than the quarter with second longest milking duration. However, in 36% of the milkings, the quarter with the longest milking duration was different from that of the previous milking. In the experimental part of this study, we saw no differences in milking duration, box time, milk production rate, or SCC between the 30 and 50% teatcup removal setting applied to the last milking quarter. Further research on using a variation of this percentage-based setting to target the quarter with the average longest milking duration or using an absolute milk flowrate switch-point or a maximum milking duration setting on the last quarter for reducing cow milking duration and box time is warranted.

A randomized trial to study the effect of automatic cluster remover settings on milking performance, teat condition, and udder health

The objectives were to study the effect of 2 different automatic cluster remover settings on (1) milking characteristics, (2) milk component yields, (3) teat tissue condition, and (4) udder health. In a randomized controlled field trial, Holstein cows (n = 689) from 1 commercial dairy farm with a thrice-daily milking schedule were allocated to 2 treatment groups. Treatment consisted of a cluster remover take-off milk flow threshold of 1.2 (ACR1.2) or 0.8 kg/min (ACR0.8) for 57 d. Milking characteristics (milk yield; and milking unit-on time, MUOT) were obtained with electronic on-farm milk meters. Composite milk samples were collected and analyzed for fat, protein, lactose, and somatic cell count. Machine-milking-induced short- and long-term changes to the teat tissue condition were assessed visually. General linear mixed models demonstrated differences in MUOT, whereas no meaningful differences in milk yield were detected. Milk yield (least squares means, 95% confidence interval) was 11.3 (10.9-11.8) and 11.3 (10.8-11.8) kg in groups ACR1.2 and ACR0.8, respectively. The effect of treatment on MUOT was modified by parity. Milking unit-on time in first-, second-, and ≥third-lactation cows, respectively, was 260.7 (252.0-269.4), 257.8 (247.4-268.1), and 260.2 (252.6-267.9) s in group ACR1.2; and 273.7 (264.9-282.5), 279.1 (269.4-288.8), and 295.7 (287.9-303.6) s in group ACR0.8. We detected no meaningful differences in milk component yields or linear somatic cell score. Least squares means in groups ACR1.2 and ACR0.8, respectively, were milk fat yield, 0.42 (0.40-0.44) and 0.42 (0.40-0.44) kg; milk protein yield, 0.36 (0.35-0.37) and 0.37 (0.36-0.37) kg; milk lactose yield, 0.61 (0.60-0.63) and 0.63 (0.61-0.64) kg, and linear somatic cell score, 1.9 (1.8-2.0) and 1.9 (1.8-2.0). A generalized linear mixed model revealed an effect of treatment on machine-milking-induced short-term changes. The odds of short-term changes to the teat tissue were lower for cows in group ACR1.2 [odds ratio (95% confidence interval) = 0.78 (0.63-0.96)]. No meaningful differences were detected in machine-milking-induced long-term changes between treatment groups. Increasing cluster remover take-off milk flow threshold from 0.8 to 1.2 kg/min decreased individual milking duration and alleviated machine-milking-induced short-term changes to the teat tissue without adversely affecting milking performance or somatic cell count. Future studies are warranted to investigate the effect on milk production and udder health over a whole lactation period.