Using mid-infrared spectroscopy to identify more fertile cows for insemination to sexed semen

Abstract

Context Broader applications of milk mid-infrared spectral data could add value to milk-recording data. One such application is to rank cows on the probability of conception to first service (MFERT) which could help prioritise cows for insemination with dairy sexed semen (SS). Aims This study compared the use of MFERT estimates against two other approaches, to (1) identify most and least fertile dairy cows and (2) prioritise cows predicted to be most fertile for first service insemination with SS. Methods Mid-infrared spectral data from first herd test after calving was used to generate 13 379 MFERT predictions for 76 cohorts. Reproduction records were used to calculate reproductive parameters, calf numbers and net benefit, i.e. calf values minus mating costs, for two breeding programs. Breeding program 1 used SS and conventional dairy semen, while Breeding program 2 used SS, conventional dairy and beef semen. Three semen-allocation approaches were compared, namely, allocation via MFERT, calving date (CDATE) or assignment via random number generator (RANDOM). Key results MFERT significantly outperformed (1) RANDOM in identifying cows most and least likely to calf after first insemination (P < 0.05), and (2) both CDATE and RANDOM in identifying cows most and least likely to calf overall (P < 0.05). This resulted in up to 1.5 and 4.5 more dairy heifer calves, in Breeding programs 1 and 2 respectively, and up to six fewer dairy-beef calves in Breeding program 2. Differences in net benefit among semen-allocation approaches were modest, although generally favoured MFERT. Few significant differences between MFERT and CDATE were found. However, significant net benefit differences among all three semen-allocation approaches were seen in Breeding program 2. Conclusions MFERT outperformed CDATE and RANDOM in identifying most and least fertile cows. Realised net benefits of semen allocation by MFERT over other approaches were modest. Given the impact of semen type and dairy-beef calf prices value proposition will vary. Implications Our study confirmed that MFERT can add value to milk recording data by identifying the most and least fertile cows. As MFERT value is sensitive to individual farm parameters, incorporation alongside other fertility parameters into a decision support tool is desirable.