Effects of Economic Factors on Adoption of Robotics and Consequences of Automation for Productivity Growth of Dairy Farms. Factor Markets Working Paper No. 32, December 2012

In the long term, productivity and especially productivity growth are necessary conditions for the survival of a farm. This paper focuses on the technology choice of a dairy farm, i.e. the choice between a conventional and an automatic milking system. Its aim is to reveal the extent to which economic rationality explains investing in new technology. The adoption of robotics is further linked to farm productivity to show how capital-intensive technology has affected the overall productivity of milk production. The empirical analysis applies a probit model and an extended Cobb-Douglas-type production function to a Finnish farm-level dataset for the years 2000–10. The results show that very few economic factors on a dairy farm or in its economic environment can be identified to affect the switch to automatic milking. Existing machinery capital and investment allowances are among the significant factors. The results also indicate that the probability of investing in robotics responds elastically to a change in investment aids: an increase of 1% in aid would generate an increase of 2% in the probability of investing. Despite the presence of non-economic incentives, the switch to robotic milking is proven to promote productivity development on dairy farms. No productivity growth is observed on farms that keep conventional milking systems, whereas farms with robotic milking have a growth rate of 8.1% per year. The mean rate for farms that switch to robotic milking is 7.0% per year. The results show great progress in productivity growth, with the average of the sector at around 2% per year during the past two decades. In conclusion, investments in new technology as well as investment aids to boost investments are needed in low-productivity areas where investments in new technology still have great potential to increase productivity, and thus profitability and competitiveness, in the long run.

Use of Extended Characteristics of Locomotion and Feeding Behavior for Automated Identification of Lame Dairy Cows.

This study was carried out to detect differences in locomotion and feeding behavior in lame (group L; n = 41; gait score ≥ 2.5) and non-lame (group C; n = 12; gait score ≤ 2) multiparous Holstein cows in a cross-sectional study design. A model for automatic lameness detection was created, using data from accelerometers attached to the hind limbs and noseband sensors attached to the head. Each cow's gait was videotaped and scored on a 5-point scale before and after a period of 3 consecutive days of behavioral data recording. The mean value of 3 independent experienced observers was taken as a definite gait score and considered to be the gold standard. For statistical analysis, data from the noseband sensor and one of two accelerometers per cow (randomly selected) of 2 out of 3 randomly selected days was used. For comparison between group L and group C, the T-test, the Aspin-Welch Test and the Wilcoxon Test were used. The sensitivity and specificity for lameness detection was determined with logistic regression and ROC-analysis. Group L compared to group C had significantly lower eating and ruminating time, fewer eating chews, ruminating chews and ruminating boluses, longer lying time and lying bout duration, lower standing time, fewer standing and walking bouts, fewer, slower and shorter strides and a lower walking speed. The model considering the number of standing bouts and walking speed was the best predictor of cows being lame with a sensitivity of 90.2% and specificity of 91.7%. Sensitivity and specificity of the lameness detection model were considered to be very high, even without the use of halter data. It was concluded that under the conditions of the study farm, accelerometer data were suitable for accurately distinguishing between lame and non-lame dairy cows, even in cases of slight lameness with a gait score of 2.5.

Short communication: Role of Streptococcus pluranimalium in Mediterranean buffaloes (Bubalus bubalis) with different udder health statuses

The aims of the current study were to describe presence and clinical role over time of Streptococcus pluranimalium isolated in milk samples of Mediterranean buffalo (MB). Two hundred composite milk samples originating from 40 primiparous MB were collected at 10, 30, 60, 90, and 150d in milk (DIM) and from 20 pluriparous MB at 77 to 120 DIM. Milk samples were used for analysis of somatic cell counts, bacteriological cultures, and identification (matrix-assisted laser desorption/ionization time-of-flight mass spectrometry). Nine of 200 (4.5%) samples of primiparous MB and 3 of 20 (15%) samples of pluriparous MB were positive for Strep. pluranimalium. The prevalence of the bacterium in primipari was 0% (0/40) at 10, 30, and 150 DIM, whereas it was 5 (2/40) and 17.5% (7/40) at 60 and 90 DIM, respectively. Eight primipari were positive only once, whereas 1 was positive at 2 different samplings. Mono-infection was not detected in any of the age categories or udder health status. Infections were transient in primipari. Clinical mastitis was observed in primipari once at 90 DIM, subclinical mastitis detected twice in the same animals at 60 and 90 DIM, and intramammary infections were diagnosed 1 and 5 times at 60 and 90 DIM in primipari, respectively, whereas 3 infections were diagnosed in pluripari. The clinical reflections demonstrate for the first time the presence of Strep. pluranimalium in MB and its association with different udder health status. Nevertheless, it cannot be excluded that the bacterium may simply follow a pattern of commensal or opportunistic behavior, taking advantage of a preexisting bacterial udder infection.

The influence of the rearing period on intramammary infections in Swiss dairy heifers: A cross-sectional study

Healthy replacement heifers are one of the foundations of a healthy dairy herd. Farm management andrearing systems in Switzerland provide a wide variety of factors that could potentially be associated withintramammary infections (IMI) in early lactating dairy heifers. In this study, IMI with minor mastitispathogens such as coagulase-negative staphylococci (CNS), contagious pathogens, and environmentalmajor pathogens were identified. Fifty-four dairy farms were enrolled in the study. A questionnaire wasused to collect herd level data on housing, management and welfare of young stock during farm isitsand interviews with the farmers. Cow-level data such as breed, age at first calving, udder condition andswelling, and calving ease were also recorded. Data was also collected about young stock that spent aperiod of at least 3 months on an external rearing farm or on a seasonal alpine farm. At the quarterlevel, teat conditions such as teat lesions, teat dysfunction, presence of a papilloma and teat lengthwere recorded. Within 24 h after parturition, samples of colostral milk from 1564 quarters (391 heifers)were collected aseptically for bacterial culture. Positive bacteriological culture results were found in 49%of quarter samples. Potential risk factors for IMI were identified at the quarter, animal and herd levelusing multivariable and multilevel logistic regression analysis. At the herd level tie-stalls, and at cow-level the breed category “Brown cattle” were risk factors for IMI caused by contagious major pathogenssuch as Staphylococcus aureus (S. aureus). At the quarter-level, teat swelling and teat lesions were highlyassociated with IMI caused by environmental major pathogens. At the herd level heifer rearing at externalfarms was associated with less IMI caused by major environmental pathogens. Keeping pregnant heifersin a separate group was negatively associated with IMI caused by CNS. The odds of IMI with coagulase-negative staphylococci increased if weaning age was less than 4 months and if concentrates were fed tocalves younger than 2 weeks. This study identified herd, cow- and quarter-level risk factors that may beimportant for IMI prevention in the future.

Upper White Oak Bayou, Buffalo Bay and tributaries flood damage protection : environmental impact statement.

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