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      Patterns of milking unit kick-off as a proxy for habituation to milking in primiparous cows

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          Graphical Abstract

          Summary: Habituation to the milking routine is a stressful process for primiparous cows, and animal reactions to new settings may represent a risk for both workers and cows. The objective of this study was to analyze the dynamics of milking unit kick-off (KO) behavior in primiparous (PRI) and multiparous (MUL) cows during the first 3 months of lactation. The odds of KO in PRI were higher than those of MUL during the entire monitoring period. The proportions of KO in PRI cows increased during the first week postpartum before decreasing after the first month of lactation, whereas KO in MUL remained stable during the whole monitoring period. Our results indicate that KO behavior in PRI cows persists over the course of the lactation, but the frequency of KO events declines after the first 30 days in milk.

          Highlights

          • Milking unit kick-off has the potential to affect worker and animal welfare, as well as cow performance.

          • Occurrence of KO in MUL cows was consistent throughout the monitoring period, but PRI cows experienced periods of greater KO between the second and the fourth week of lactation.

          • Compared with MUL, PRI cows had doubled odds of KO during the first 90 days in milk.

          Abstract

          The onset of lactation and the subsequent habituation to the milking routine is a stressful period, particularly for primiparous (PRI) cows. The objective of this study was to describe the dynamics of milking unit kick-off (KO) behavior in PRI cows during the first 3 mo of lactation, considering multiparous (MUL) cows as a reference for comparison. In addition, the potential associations between KO and milk yield and mastitis presentation were investigated. A total of 869 cows (PRI = 199; MUL = 670) on a dairy farm in northern CO were included in the analysis. Cows calving between August and November 2020 were enrolled from 3 DIM until 90 DIM. Participants were milked 3×/day in a 60-unit rotary parlor and data from each milking session were downloaded from parlor management software. Milking unit kick-off was used as a proxy for habituation to the milking procedure. Kick-off events were reported by the milking system and defined as an abrupt interruption in the milk flow during the milking process. Cow KO events were recorded for each milking session. Subsequently, occurrence of KO was analyzed by grouping the 3 consecutive milking sessions in each day and categorized as yes or no, indicating whether or not an individual kicked at least once in a given day. Data were analyzed by repeated measures ANOVA and logistic regression, including parity category, calving season, occurrence of dystocia, and their potential interactions in the models. Least squares means for daily proportions of KO were calculated considering the number of cows with KO events per day in the PRI and MUL categories. Subsequently, odds ratios for the occurrence of KO in PRI versus MUL were calculated at multiple periods of time. When KO was analyzed by DIM, proportions of KO were greater in PRI than in MUL during the whole monitoring period. In PRI, proportions of KO increased from 0.10/d to 0.20/d between 3 DIM and 15 DIM, to start decreasing around 30 DIM and remaining above MUL up to 90 DIM. On the contrary, in MUL cows, proportions of KO remained close to 0.05/d during the 90-d period. Overall, the odds of KO were greater for PRI versus MUL cows (odds ratio [95% confidence interval] = 2.07 [1.58–2.73]). No differences in milk yield were established among KO categories, while the percentage of cows affected with mastitis was greater in cows grouped in the quartile with more frequent KO events. We concluded that the relationship between days in milk and the proportion of PRI cows displaying KO was not linear, but rather KO increased during the first 2 wk postpartum before decreasing after the first month of lactation. First-parity cows had greater levels of KO than MUL cows, which is most likely associated with the process of habituation to milking during their first lactation.

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          Most cited references31

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          The cost of clinical mastitis in the first 30 days of lactation: An economic modeling tool.

          Clinical mastitis results in considerable economic losses for dairy producers and is most commonly diagnosed in early lactation. The objective of this research was to estimate the economic impact of clinical mastitis occurring during the first 30 days of lactation for a representative US dairy. A deterministic partial budget model was created to estimate direct and indirect costs per case of clinical mastitis occurring during the first 30 days of lactation. Model inputs were selected from the available literature, or when none were available, from herd data. The average case of clinical mastitis resulted in a total economic cost of $444, including $128 in direct costs and $316 in indirect costs. Direct costs included diagnostics ($10), therapeutics ($36), non-saleable milk ($25), veterinary service ($4), labor ($21), and death loss ($32). Indirect costs included future milk production loss ($125), premature culling and replacement loss ($182), and future reproductive loss ($9). Accurate decision making regarding mastitis control relies on understanding the economic impacts of clinical mastitis, especially the longer term indirect costs that represent 71% of the total cost per case of mastitis. Future milk production loss represents 28% of total cost, and future culling and replacement loss represents 41% of the total cost of a case of clinical mastitis. In contrast to older estimates, these values represent the current dairy economic climate, including milk price ($0.461/kg), feed price ($0.279/kg DM (dry matter)), and replacement costs ($2,094/head), along with the latest published estimates on the production and culling effects of clinical mastitis. This economic model is designed to be customized for specific dairy producers and their herd characteristics to better aid them in developing mastitis control strategies.
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            Relationships between human-animal interactions and productivity of commercial dairy cows.

            This study examined the relationships between a number of stockperson and cow variables at 66 commercial dairy farms. Variables such as the attitudes and behavior of stockpeople toward their cows and the behavioral response to humans and productivity of cows were studied over one lactation. There were consistent and significant correlations between some of these stockperson and cow variables. For example, a positive attitude by stockpeople toward the behavior of dairy cows was negatively correlated with the number of forceful, negative, tactile interactions used by stockpeople in handling cows (r = -0.27, df = 127, P 0.05). Support for the existence of a negative fear-productivity relationship was the finding that the use of negative interactions by stockpeople was significantly and negatively correlated with milk yield, protein, and fat at the farm (r = -0.36, -0.35 and -0.33, respectively, df = 64, P < 0.01) and was significantly and positively correlated with milk cortisol concentrations at the farm (r = 0.34, df= 64, P < 0.01). Furthermore, the percentage of cows approaching within 3 m of an experimenter in a standard test was positively correlated with conception rate to the first insemination (r = 0.38, df = 46, P < 0.01). The significant correlations found in the present study between stockperson attitudes and behavior and cow behavior and productivity, although not evidence of causal relationships, indicate the possibility of targeting these human characteristics to reduce fear responses of dairy cows to humans and improve the cows' productivity.
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              The effect of joint exposures: examining the presence of interaction.

              Clinical epidemiological studies investigate whether an exposure, or risk factor, is causally related to the development or progression of a disease or mortality. It might be of interest to study whether this relation is different in different types of patients. To address such research questions, the presence of interaction among risk factors can be examined. Causal interaction between two risk factors is considered most clinically relevant in epidemiology. Causal interaction occurs when two risk factors act together in causing disease and is explicitly defined as a deviation from additivity on a risk difference scale. Statistical interaction can be evaluated on both an additive (absolute risk) and multiplicative (relative risk) scale, depending on the model that is used. When using logistic regression models, which are multiplicative models, several measures of additive interaction are presented to evaluate whether the magnitude of an association differs across subgroups: the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), or the synergy index (S). For a transparent presentation of interaction effects the recent Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement advises reporting the separate effect of each exposure as well as the joint effect compared with the unexposed group as a joint reference category to permit evaluation of both additive and multiplicative interaction.
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                Author and article information

                Contributors
                Journal
                JDS Commun
                JDS Commun
                JDS Communications
                Elsevier
                2666-9102
                21 July 2023
                September 2023
                21 July 2023
                : 4
                : 5
                : 385-389
                Affiliations
                [a ]Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523
                [b ]Aurora Organic Farms, Platteville, CO 80651
                [c ]École Nationale de Vétérinaire de Toulouse, CIRAD, Toulouse 31300, France
                [d ]Department of Clinical Sciences, Colorado State University, Fort Collins, CO 80523
                Author notes
                [* ]Corresponding author pablo.pinedo@ 123456colostate.edu
                Article
                S2666-9102(23)00065-0
                10.3168/jdsc.2023-0384
                10505780
                37727250
                2d75058f-021e-4e2e-a744-d7acb46c8475
                © 2023.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 February 2023
                : 11 April 2023
                Categories
                Health, Behavior, and Well-being
                Short Communication
                Short Communication

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