Reticulo-rumen temperature as a predictor of calving time in primiparous and parous Holstein females

Abstract

The objective of this research was to define and analyze drops in reticulo-rumen temperature (Trr) as an indicator of calving time in Holstein females. Data were collected from 111 primiparous and 150 parous Holstein females between November 2012 and March 2013. Between -15 and -5 d relative to anticipated calving date, each female received an orally administered temperature sensing reticulo-rumen bolus that collected temperatures hourly. Daily mean Trr was calculated from d -5 to 0 relative to using all Trr values (A-Trr) or only Trr values ≥37.7°C (W-Trr) not altered by water intake. To identify a Trr drop, 2 methodologies for computing the baseline temperature were used. Generalized linear models (GLM) were used to estimate the probability of calving within the next 12 or 24 h for primiparous, parous, and all females, based on the size of the Trr drop. For all GLM, a large drop in Trr corresponded with a large estimated probability of calving. The predictive power of the GLM was assessed using receiver-operating characteristic (ROC) curves. The ROC curve analyses showed that all models, regardless of methodology in calculation of the baseline or tested category (primiparous or parous), were able to predict calving; however, area under the ROC curve values, an indication of prediction quality, were greater for methods predicting calving within 24 h. Further comparisons between GLM for primiparous and parous, and using baseline 1 and 2, provide insight on the differences in predictive performance. Based on the GLM, Trr drops of 0.2, 0.3, and 0.4°C were identified as useful indicators of parturition and further analyzed using sensitivity, specificity, and diagnostic odds ratios. Based on sensitivity, specificity, and diagnostic odds ratios, the best indicator of calving was an average Trr drop ≥0.2°C, regardless of methodology used to compute the baseline or category of animal evaluated.

Using Circadian Rhythm Patterns of Continuous Core Body Temperature to Improve Fertility and Pregnancy Planning

“…Using CBT, Cagnacci et al, characterized the follicular phase by a 0.3 °C lower mesor, a 40% increase in the amplitude and a 90-minute advance in the daily nadir compared to the luteal phase [ 53 ]. Signal processing analysis of CCBT data has been demonstrated to be effective for detecting and predicting physiologic events of fertility, including ovulation, pregnancy, parturition, and spontaneous abortions [ 54 55 56 57 ].…”

Developing and evaluating threshold-based algorithms to detect drinking behavior in dairy cows using reticulorumen temperature

“…The ability to detect drinking events using a thresholding method and by incorporating this information rather that removing it, as in previous studies (Cooper-Prado et al, 2011;Costa et al, 2016), has the potential to expand temperature monitoring in cows (Cooper-Prado et al, 2011;Timsit et al, 2011;Costa et al, 2016;Kovács et al, 2017). Drinking behavior in dairy cattle is important for the physical and emotional state of the animals (Baxter, 1983) and for farm economics because it is highly related to milk production (Steiger Burgos et al, 2001;Kramer et al, 2009;Daros et al, 2019).…”

“…Previous studies have suggested that drinking events can be detected using a fixed threshold value of 37.7°C (Cooper-Prado et al, 2011;Costa et al, 2016). This was based on previous studies that used a small sample (n = 9 cows; Boehmer et al, 2009), or few water intake observations per cow (e.g., 3 data points per cow; Bewley et al, 2008b;Boehmer et al, 2009), or col- lected data under controlled experimental conditions (e.g., oral drench, water and feed restricted for up to 21 h; Bewley et al, 2008b;Boehmer et al, 2009).…”

“…In recent years, the development of precision livestock farming technology has facilitated not only the collection of real-time data but also the integration of this information within the overall monitoring of individual animals (Berckmans, 2014;Walton et al, 2018). Among these technologies is the collection of reticuloruminal temperature data through the use of reticular boluses that transmit data to a central computer using an active radiofrequency transmitter (Costa et al, 2016;Kovács et al, 2017;Lees et al, 2018). This allows farmers to continuously monitor cows' temperature, providing an alert when temperature goes out of a preset range; for example, during heat stress (Koltes et al, 2018).…”

“…Reticuloruminal temperature has been assessed as a potential prediction tool for estrus (Cooper-Prado et al, 2011), calving (Costa et al, 2016), dystocia (Kovács et al, 2017), and health status (Timsit et al, 2011) in cattle. In addition, reticuloruminal temperature can be affected by external variables such as water intake (Bewley et al, 2008b).…”