Defining temperature groupings around mating of sows for farrowing rate using cluster analysis

Abstract

<p>Application The methodology of defining temperature groupings can be applied to other traits to better quantify ambient temperature effects on pig reproduction traits. </p><p> Introduction Seasons are defined by grouping calendar months according to specific climate characteristics. However, this definition of season does not account for variation within a calendar based season and between the same seasons in different years. Therefore, a more flexible approach is required to define seasons. The aim of this study was to define meaningful biological temperature based groupings relevant to mating dates of sows using cluster analysis. </p><p> Material and Methods Information about the farrowing rate (FR: 0=fail, 1=pregnancy) resulting from 55767 first-insemination records of 17484 sows, collected from 2012 to 2017, from a single farm in southern New South Wales, Australia were available. Maximum ambient temperature of the day (Tmax) for the piggery were obtained from the nearby Rutherglen weather station (~16km).The climate is characteriszed by very hot summers, cool winters and low humidity. Sows were housed in naturally ventilated sheds and had drip cooling provided during their lactation period when shed temperature exceeded 30°C. A generalized linear model with a logit link was used to identify the most informative days for FR at first insemination regarding Tmax in the time period 35 days prior to and 35 days post mating date. Additionally, the model for FR also included parityat mating, line (Large White, Landrace and Duroc, PrimegroTM Genetics, Corowa NSW) and year of mating. The most informative days based on significance (P<0.05) for FR were retained in the final analysis. Then, Tmax of the most informative days of every mating date was extracted for further cluster analysis. The Tmax pattern around mating was assigned according to their dissimilarity into five temperature classes using the Partitioning Around the Medoid (PAM) method in the R package cluster (Maechler et al.,2018; R Core Team,2018). PAM cluster approach has been described by Kaufman and Rousseeuw (1990). </p><p> Results The days 34, 29 and 18 d before mating,as well as 3, 26, 27 and 29 d after mating, were only significant (P<0.05) and therefore most informative for FR. Average lactation lengthwas 27 d. Therefore, all significant days prior to mating fell into the time period a sow generally wasin the farrowing house. Five clusters for temperature pattern were identified for Tmax information of informative days around the mating date. These five clusters represented trait specific temperature groupings (T-group, Table 1).</p>