Getting the most out of advanced farm management technologies: roles of technology suppliers and dairy industry organisations in supporting precision dairy farmers

The use of advanced management technologies is increasing in pasture-based dairy systems, an evolution that has been termed precision dairying. This change has been driven, at least in part, by a continual increase in the scale of dairy farming and an associated drive for efficiencies, and technological advances in the area of sensors and automated devices for animal and resource management. In this paper, a survey of New Zealand precision dairy farmers is presented, highlighting lessons from farmers for technology developers and industry. Respondents indicated that they invested in technologies such as electronic identification, milk meters, automated cup removers, and automated drafting for labour saving and to make herd management easier. Most were positive about their investments, with perceived benefits from saved time during milking, decreased farm workforce requirement, and increased farm profitability. Farmers also felt there was unused functionality in their herd management systems and that they could benefit from increased support and training to get more from their technology. Technology suppliers need to refocus on after-sales service and tailor their support programs to stages of learning development, while creating a value proposition for farmers to pay for such services. Dairy industry organisations need to take the lead in building awareness of the opportunities such technologies offer, while facilitating access to independent information about technology capability and investment.

Evaluating rates of technology adoption and milking practices on New Zealand dairy farms

This study assessed technology use and evaluated rates of technology adoption and milking practices on New Zealand dairy farms. Industry surveys were conducted in 2008 and 2013, when farmers were asked a series of questions relating to their physical farm details, their role in the business, their attitudes towards technology, the technologies they had on-farm and their levels of satisfaction. In total, 532 and 500 respondents were questioned in the two surveys, respectively, with a similar representation of rotary and herringbone dairies. Questions relating to attitudes towards new technologies were subjected to a cluster analysis using the 2013 dataset. Farmers were classified into two categories, ‘fast’ and ‘slow’ adopters. Fast adopters are more likely to have a rotary, with a larger farm and more cows. The most common technology in herringbone dairies is automatic vat washing and in rotary dairies automatic cluster removers (ACR). Rotary dairies equipped with ACR, automatic drafting and automatic teat spraying achieve greater labour utilisation (cows/labour unit). Around half of farmers with herringbone dairies sometimes or always wait for slow-milking cows to milk out and 85% of farmers do not know the their ACR settings, highlighting significant potential to improve milking efficiency. Overall, technology is associated with greater labour utilisation. However, the benefits of each technology should be scrutinised to ensure appropriate investment decisions are made by farmers.

Principles for maximising operator efficiency and return on investment in rotary dairies

This study quantified the effect of rotary size, platform speed, cluster attachment time, milk yield and end-of-milking criteria on cow throughput, operator efficiency and return on investment. A model was developed to predict the mean and standard deviation of cow milking duration for a given milk yield using milking data collected from commercial dairy farms in New Zealand. After accounting for the effect of end-of-milking criteria, this estimate was used to calculate the expected cow throughput and operator efficiency for a given platform speed, rotary size and cluster attachment time. The economic return of investing in rotaries of 44–80 bails, relative to a 40-bail rotary, was evaluated using a 25-year internal rate of return. The economic return of installing automatic cluster removers (ACR) was also examined. Estimated cow throughput increased with increasing platform speed and ACR threshold for a 50-bail rotary (a common rotary size) and the largest single gain in cow throughput came from changing the ACR threshold from 0.2 to 0.4 kg/min. Further increases had less impact, especially at lower platform speeds. However, for larger rotaries, maximum operator efficiency could be achieved using a variety of platform speeds and end-of-milking criteria. A larger rotary was required to achieve maximum potential operator efficiency, for a given cluster attachment time, as milk yield was increased. Increasing the minimum cluster attachment time decreased maximum potential operator efficiency. Consequently, operator ability and anticipated milk yield are key parameters when selecting the number of bails in a new-build rotary. Seventy- and 80-bail rotaries were generally not more operator efficient than 60-bail rotaries. Economically, the 50-bail rotary allowed the greatest labour saving per dollar invested for a typical farm conversion in Canterbury, New Zealand, although the ultimate choice of rotary size depends on the individual farm situation. The internal rate of return for installing ACR decreased with increasing rotary size, but was always positive. Farmers should carefully evaluate their options before investing in a new rotary.

Relationships between residual feed intake, average daily gain, and feeding behavior in growing dairy heifers

Residual feed intake (RFI) is a measure of an individual's efficiency in utilizing feed for maintenance and production during growth or lactation, and is defined as the difference between the actual and predicted feed intake of that individual. The objective of this study was to relate RFI to feeding behavior and to identify behavioral differences between animals with divergent RFI. The intakes and body weight (BW) of 1,049 growing dairy heifers (aged 5-9 mo; 195 ± 25.8 kg of BW) in 5 cohorts were measured for 42 to 49 d to ascertain individual RFI. Animals were housed in an outdoor feeding facility comprising 28 pens, each with 8 animals and 1 feeder per pen, and were fed a dried, cubed alfalfa diet. This forage diet was chosen because most dairy cows in New Zealand are grazed on ryegrass-dominant pastures, without grain or concentrates. An electronic feed monitoring system measured the intake and feeding behavior of individuals. Feeding behavior was summarized as daily intake, daily feeding duration, meal frequency, feeding rate, meal size, meal duration, and temporal feeding patterns. The RFI was moderately to strongly correlated with intake in all cohorts (r=0.54-0.74), indicating that efficient animals ate less than inefficient animals, but relationships with feeding behavior traits (meal frequency, feeding duration, and feeding rate) were weak (r=0.14-0.26), indicating that feeding behavior cannot reliably predict RFI in growing dairy heifers. Comparison of the extremes of RFI (10% most and 10% least efficient) demonstrated similar BW and average daily gain for both groups, but efficient animals ate less; had fewer, longer meals; shorter daily feeding duration; and ate more slowly than the least-efficient animals. These groups also differed in their feeding patterns over 24h, with the most efficient animals eating less and having fewer meals during daylight (0600 to 2100 h), especially during the afternoon (1200 to 1800 h), but ate for a longer time during the night (0000-0600 h) than the least-efficient animals. In summary, correlations between RFI and feeding behavior were weak. Small differences in feeding behavior were observed between the most- and least-efficient animals but adverse behavioral effects associated with such selection in growing dairy heifers are unlikely.

Large rotary dairies achieve high cow throughput but are not more labour efficient than medium-sized rotaries

It was hypothesised that large rotary dairies (>60 clusters) are not more operator efficient than medium-sized rotaries (40–60 clusters). This was tested by collecting and analysing milking data, during peak and late lactation, from block calving herds milked in rotary dairies fitted with electronic milk meters. Data were collected from a total of 61 unique farms around New Zealand, with rotary dairies ranging in size from 28 to 80 clusters, for two 5-day periods during spring (September–November 2010; 47 farms; average milk yield 23.1 kg/day) and autumn (February–April 2011; 60 farms; average milk yield 16.4 kg/day). A telephone survey was conducted to collect basic farm details: size, land area, the number of herds managed (including hospital herds), number of operators in the dairy and total labour input. A site visit was conducted to collect data such as the number of bails/stalls over the entrance and exit of the platform. The herd management software on each farm was programmed to record similar fields for each of the six machine manufacturers represented. Variables recorded included cow, date, identification time, bail number, milk yield, milking duration, and average milk flow rate. Calculations were performed to determine the number of cows milked and milk harvested per hour as well as the operator efficiency values for these measures and an estimate of cluster utilisation. Mixed models were used to determine the relationship between the dependent variables, cows milked per hour, milk harvested per hour, cows milked per operator per hour, milk harvested per operator per hour, and cluster utilisation, and the independent variables collected. Cows milked and milk harvested per hour increased linearly with rotary size, during both spring and autumn and there was a quadratic relationship between operator efficiency measures and rotary size, which peaked at ~60 clusters. Cluster utilisation, the amount of time clusters were harvesting milk out of the plant running time, was estimated at 46 ± 6%. Larger rotary dairies on average achieved greater throughput; however, they were not more operator efficient than medium-sized rotaries. Thus, large rotary dairies are best suited to farms where the additional throughput is required.

Increasing platform speed and the percentage of cows completing a second rotation improves throughput in rotary dairies

This study sought to improve milking efficiency in rotary dairies by modelling the effect of increasing platform speed on the percentage of cows requiring multiple rotations to complete milking, i.e. ‘go-around’ cows, and cow throughput. Milking data, including 376 429 milking event records from 44 530 cows, were collected from 62 commercial farms with rotary dairies in New Zealand. Average rotation time, a function of platform speed and rotary size, was 10.0 ± 1.5 min, mean milking duration 383 ± 129 s, and mean milk yield 11.9 ± 3.8 kg per milking session. Milking duration data were normalised using a log10 transformation. An estimate of the percentage of ‘go-around’ cows and potential throughput over a range of platform speeds were made using the NORMDIST function of Microsoft Excel 2010. Results indicate that throughput continues to increase with increasing platform speed, despite a greater number of ‘go-around’ cows. If a potential shadow effect (whereby a ‘go-around’ cow may cause the following bail to be unoccupied) is considered, the optimum percentage of ‘go-around’ cows was ~20%. Accordingly, a change of operating practices in many rotary dairies is justified as the current target of 10% ‘go-around’ cows may limit throughput. In order to achieve greater cow throughput, platform speed should rather be set based on the capability of the operator attaching clusters. The difference between the current average rotation time and milking duration indicates that many dairies can increase platform speed and thus throughput. Furthermore, many work routines can be accelerated so faster platform speeds can be achieved without increasing labour requirements. The increased throughput potential of larger dairies is only realised when operated at fast platform speeds.

Comparing somatic cell counts, production and milking durations of dairy cows when milked at two automatic cup-removal flow-rate thresholds

The present study evaluated the effect of two automatic cup remover (ACR) flow-rate threshold settings (0.2 and 0.4 kg/min) on somatic cell count (SCC), clinical mastitis (CM), milk production and milking duration for cows milked twice daily. In a crossover design, 161 cows were assigned to one of two groups and milked with an ACR set at either 0.2 kg/min (Group 1, n = 81) or 0.4 kg/min (Group 2, n = 80) for a 3-week period from peak lactation. Following a 1-week transition period at a milk-flow threshold setting of 0.3 kg/min for both groups, there was a further 3-week treatment period where Group 1 was milked with an ACR set at 0.4 kg/min and Group 2 set at 0.2 kg/min. The milk-flow threshold setting did not affect SCC (P > 0.05). Clinical mastitis was detected in 3% of cows, and was not more prevalent when cows were milked to a flow rate of 0.4 kg/min. Post-milking strip yields were larger when thresholds were set at 0.4 kg/min than those with 0.2 kg/min (P < 0.05). Average fat yield was not affected by treatment (P > 0.05), but average daily milk, MS and protein yields were lower (P < 0.05) for the 0.4 kg/min setting, equating to a 1% difference in production. Milking duration was reduced by 11% (P < 0.001) when cups were removed at flow rates of 0.4 kg/min, compared with 0.2 kg/min. Increasing the milk flow-rate threshold for cluster removal can reduce milking time without affecting milk quality, but may result in a minor reduction in MS production.

Effect of setting a maximum milking time, from peak lactation, on production, milking time and udder health

AIM

To examine the effect of setting a maximum milking time, from peak lactation until drying-off, on production, duration of milking, and udder health of dairy cows.

METHODS

Forty cows were assigned in twin-pairs to be either milked until cups were removed at a milk flow-rate threshold of 0.35 kg/minute (Control), or until cups were removed at a milk flow-rate threshold of 0.35 kg/minute, or maximum time, whichever came first (MaxT). The maximum time was set by determining the milking time of the 70th percentile cow when ranked from fastest to slowest, irrespective of yield. The milking routine was typical of that practised on dairy farms in New Zealand, and involved no pre-milking preparation. The study began at peak lactation (68 (SD 7) days in milk; DIM) and continued for 26 weeks. Duration of milking and milk yield were measured for each milking. Composition of milk was determined from weekly herd tests, and milk quality from fortnightly somatic cell counts (SCC). Completeness of milking and teat condition were assessed during the study. The bacterial status of quarter milk samples was determined at the beginning and end of the study, and all treated cases of clinical mastitis recorded. ANOVA was used to examine the effect of treatment group on variables of interest.

RESULTS

Total milk, fat and protein yields during the study period did not differ between treatments. On average, 30.3% of the morning and 27.6% of the afternoon milkings of MaxT cows reached the maximum time at which cups were removed, and were therefore shortened. While the average milking time of the slowest-milking cow was longer for the Control compared with MaxT group in Weeks 1-18, the average milking time did not differ between treatments. There was no difference in overall SCC, and the incidence of clinical mastitis, or the percentage of infected quarters at drying-off, was similar for the MaxT and Control cows.

CONCLUSION

The results show that setting a maximum milking time can reduce the milking time of slower-milking cows in a herd without compromising overall herd production and udder health.

CLINICAL RELEVANCE

Although the numbers of cows in the study were small there was no evidence of a major increase in SCC, or subclinical or clinical mastitis when a maximum milking time was set for slower-milking cows.

The effect of prepubertal immunization against gonadotropin-releasing hormone on the development of sexual and social behavior of bulls

To determine the effect of prepubertal immunization against GnRH on the development of sexual and social behavior of Friesian bulls, 90 calves were randomly assigned to five treatments: 1) I2, immunized against GnRH at 2 and boosted at 2.5, 4, and 7.5 mo of age, n = 2 x 10; 2) I4, immunized against GnRH at 4 and boosted at 4.5 and 7.5 mo of age, n = 2 x 10; 3) I7.5, immunized against GnRH at 7.5 and boosted at 8 mo of age n = 2 x 10; 4) S, steers castrated at 2 mo of age, n = 10; and 5) B, intact bulls, n = 2 x 10. Blood samples were collected initially every 2, then every 3 wk. Plasma was analyzed for anti-GnRH titers and plasma testosterone concentration. Sexual and agonistic behavior, male-male mounting, and damage to paddocks was assessed throughout the experiment. All immunized calves developed antibodies against GnRH (32.3 +/- 2.0% bound at a 1:10 plasma:PBS-BSA dilution, 14 d after first boost). Plasma testosterone concentrations were < 1 ng/mL for all immunized animals until 11 mo of age, when they increased to levels found in intact bulls at 14 mo of age. At slaughter, testes and seminal vesicle weights were 38.3 and 31.6% lighter, respectively, for all immunized treatments compared to B. There were no significant differences between I2, I4, and I7.5 in any of the sexual or agonistic behavior tests. Bulls scored higher than steers in all sexual behavior tests. Immunized bulls scored lower than bulls in sexual behavior tests from 10 to 17 mo of age. The proportion of immunized animals that serviced an estrous cow was lower than the proportion of intact bulls at 10, 12.5, 14, and 17 mo of age. Immunized animals scored lower than bulls in bull challenge tests at 8.5, 11.5, 13, 14.5, and 17 mo of age. Paddock damage by animals on the three immunization treatments was lower than that by bulls from 7 to 14.5 mo of age, as were leg were scores (an indicator of male-male mounting behavior) from 9 to 14 mo of age. There was no difference in sexual behavior between immunized bulls (I2, I4, and I7.5) and bulls while held in lairage pens for 16 h before slaughter, but all treatment groups scored higher than steers. There was a similar trend for agonistic behavior, although I4 bulls were no different from steers. Prepubertal immunization against GnRH at 2, 4, and 7.5 mo of age impaired testes function and affected the development of social and sexual behavior of young bulls.