Screening microchip sites to predict body temperature in young calves.

Thermal microchip sensors can automate body temperature measurements. The best site of implantation is still unknown, and the accuracy and precision of body temperature predictions based on microchip data need to be investigated. The aim of this study was to investigate the best site for microchip implant for monitoring body temperature in dairy calves. Seventeen calves were used (32.2 ± 5.2 kg of body weight) and the microchips were implanted four days after birth. The microchips were implanted at navel, ear and tail base (subcutaneous), neck (cleidocephalicus) and internal face of leg (gracilis) (intramuscular). Rectal temperature (RT, °C), obtained with a clinical thermometer, was considered as core temperature. Air temperature (AT), relative humidity (RH) and the temperature and humidity index (THI) were evaluated at the same time of rectal and microchip temperature measurements over 56 days. The range of AT, RH and THI was 7.6-34.4 °C, 17.5-99.0% and 50.6 to 91.5. The average for rectum, ear, neck, tail, leg, and navel were 38.7; 36.9; 38.0; 37.0, 37.8 and 37.0 °C. The intramuscular implantations had closest values to RT. The correlations between RT and ear, neck, tail, leg, and navel temperatures were 0.56, 0.60, 0.60, 0.53 e 0.48. The RT prediction based on microchip data had precision (rc) ranged between 0.49 and 0.60 and accuracy (Cb) between 0.79 and 0.88. The inclusion of AT, RH and THI as predictive variables in models decrease the mean absolute error (23%) and increase the precision (21.3%) and accuracy (10.2%). The Concordance Correlation Coefficient and root-mean-square error for equations using tail or neck microchips were 0.68 and 0.67, and 0.29 and 0.28 °C, respectively. The tail base is a promising site for microchip implantation to predict rectal temperature. The inclusion of air temperature as a predictive variable in the models is recommended.

Relationship between feed efficiency indexes and performance, body measurements, digestibility, energy partitioning, and nitrogen partitioning in pre-weaning dairy heifers.

The objectives of this study were: 1) to classify animals into groups of high and low feed efficiency using two feed efficiency indexes (Residual feed intake (RFI) and residual feed intake and body weight gain (RIG)), and 2) to evaluate if pre-weaning heifer calves divergent for feed efficiency indexes exhibit differences in performance, body measurements, digestibility, energy partitioning, and nitrogen partitioning. A total of 32 Gyr heifer calves were enrolled in a 63-d trial and classified into two feed efficiency (FE) groups based on RFI and RIG (mean ± 0.5 SD). The groups were classified as high efficiency (HE) RFI (HE RFI, n = 9; HE RIG, n = 10), and low efficiency (LE) RFI (LE RFI, n = 10; LE RIG, n = 11). The remaining animals were classified as intermediate (n = 13 (RFI) and n = 11 (RIG)). HE and LE calves had RFI values of-0.052 and 0.049 kg/d (P < 0.05), respectively. The HE RFI group consumed 8.9% less solid diet than the LE RFI group. HE RFI animals exhibited an increased digestibility of crude protein and ether extract and tended to have greater total dry and organic matter digestibility. LE RFI animals had greater gross energy and nitrogen intake, though greater fecal losses resulted in a tendency to reduce energy and nitrogen use efficiency. HE and LE calves had RIG values of 0.080 and -0.077kg/d (P ≤ 0.01), respectively. HE RIG animals exhibited greater average daily gain (9.4%), body weight (BW), and heart girth, though HE RIG group exhibited narrower hip width. HE RIG animals tended to have greater ether extract digestibility but greater methane losses (% of gross energy). HE RFI in pre-weaning heifers seems to be related to differences in digestibility. Divergent animals for RIG during the assessed phase appear to differ in body measurements, which may be related to differences in the composition of the gain.