Diagnosing the pregnancy status of dairy cows: How useful is milk mid-infrared spectroscopy?

Abstract

Pregnancy diagnosis is an essential part of successful breeding programs on dairy farms. Milk composition alters with pregnancy, and this is well documented. Fourier-transform mid-infrared (MIR) spectroscopy is a rapid and cost-effective method for providing milk spectra that reflect the detailed composition of milk samples. Therefore, the aim of this study was to assess the ability of MIR spectroscopy to predict the pregnancy status of dairy cows. The MIR spectra and insemination records were available from 8,064 Holstein cows of 19 commercial dairy farms in Australia. Three strategies were studied to classify cows as open or pregnant using partial least squares discriminant analysis models with random cow-independent 10-fold cross-validation and external validation on a cow-independent test set. The first strategy considered 6,754 MIR spectra after insemination used as independent variables in the model. The results showed little ability to detect the pregnancy status as the area under the receiver operating characteristic curve was 0.63 and 0.65 for cross-validation and testing, respectively. The second strategy, involving 1,664 records, aimed to reduce noise in the MIR spectra used as predictors by subtracting a spectrum before insemination (i.e., open spectrum) from the spectrum after insemination. The accuracy was comparable with the first approach, showing no superiority of the method. Given the limited results for these models when using combined data from all stages after insemination, the third strategy explored separate models at 7 stages after insemination comprising 348 to 1,566 records each (i.e., progressively greater gestation) with single MIR spectra after insemination as predictors. The models developed using data recorded after 150 d of pregnancy showed promising prediction accuracy with the average value of area under the receiver operating characteristic curve of 0.78 and 0.76 obtained through cross-validation and testing, respectively. If this can be confirmed on a larger data set and extended to somewhat earlier stages after insemination, the model could be used as a complementary tool to detect fetal abortion.

Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems

“…Ho et al (2019) reported that milk spectra from early lactation cow together with other on-farm data (e.g., days in milk, days from calving to insemination, calving age, milk yield, genotypes, among others) could be used to classify cows that conceived at first insemination or did not conceive within the breading season with reasonable accuracy, based on the area under the curve (0.75), in herd-by-herd external validation. Delhez et al (2020) observed that milk spectra recorded after 150 days of pregnancy was promising to predict the pregnancy status in Holstein, with the area under the curve around 0.76 in cowindependent external validation. More efforts need to be made to investigate the reliability of milk spectra to predict fertility traits since the accuracies observed to date are not high and the number of studies is very low, although recent.…”

Predicting the likelihood of conception to first insemination of dairy cows using milk mid-infrared spectroscopy

“…On the one hand, the model uses this information to predict if a cow is pregnant (if the probability of 1 > the probability of 0) or open (if the probability of 1 < the probability of 0). On the other hand, the probability could be interpreted as how certain the model is in its prediction (Delhez et al, 2020). For example, if the predicted probabilities of cow A and cow B to be pregnant and open are 0.51 and 0.49 and 0.9 and 0.1, respectively, then the model will assign both cows a value of 1 (i.e., pregnant).…”

Genome-wide interaction analyses of milk production traits in dairy cattle

“…Otherwise cows with better fertility, which are more likely to be pregnant, would be penalized in their breeding value for milk production traits . As pregnancy affects milk yield and components, studies have been performed to investigate possibilities to predict pregnancy status based on milk infrared spectra Delhez et al, 2020). It has been suggested that after 150 d in pregnant predicting pregnancy status based on changes in milk yield and components might be used as a complementary tool to detect fetal abortion (Delhez et al, 2020).…”

“…It has been suggested that after 150 d in gestation pregnancy status can be predicted based on milk infrared spectra Delhez et al, 2020). Such information might be used as a complementary tool to detect fetal abortion (Delhez et al, 2020).…”

“…Pregnancy effects in late gestation are relevant for assessing the impact of shortening or omitting the dry-off period; shortening the dry off period will result in additional milk production that might compensate for decreased milk production in the next lactation (Kok et al, 2016). As pregnancy affects milk yield and composition, studies have been performed to investigate possibilities to predict pregnancy status based on milk infrared spectra Delhez et al, 2020). Pregnancy might also affect the genetic background of milk production traits.…”