Abstract
The aim of the current study was to evaluate the relation of automatically determined body condition score (BCS) and inline biomarkers such as β-hydroxybutyrate (BHB), milk yield (MY), lactate dehydrogenase (LDH), and progesterone (mP4) with the pregnancy success of cows. The cows (n = 281) had 2.1 ± 0.1. lactations on average, were 151.6 ± 0.06 days postpartum, and were once tested with “Easy scan” ultrasound (IMV imaging, Scotland) at 30–35 d post-insemination. According to their reproductive status, cows were grouped into two groups: non-pregnant (n = 194 or 69.0% of cows) and pregnant (n = 87 or 31.0% of cows). Data concerning their BCS, mP4, MY, BHB, and LDH were collected each day from the day of insemination for 7 days. The BCS was collected with body condition score camera (DeLaval Inc., Tumba, Sweden); mP4, MY, BHB, and LDH were collected with the fully automated real-time analyzer Herd Navigator™ (Lattec I/S, Hillerød, Denmark) in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). Of all the biomarkers, three differences between groups were significant. The body condition score (BCS) of the pregnant cows was higher (+0.49 score), the milk yield (MY) was lower (−4.36 kg), and milk progesterone in pregnant cows was (+6.11 ng/mL) higher compared to the group of non-pregnant cows (p < 0.001). The pregnancy status of the cows was associated with their BCS assessment (p < 0.001). We estimated that cows with BCS > 3.2 were 22 times more likely to have reproductive success than cows with BCS ≤ 3.2.
Highlights
The novel digital equipment, such as multiple sensors, a data infrastructure, and data analytics, can be used to monitor animals or their environment [1]
Blood biomarkers are valuable indicators of animal health but not generally applicable commercially. They could provide a lot of information, especially because subclinical stages of diseases can be detected by biomarkers while the cow may appear completely healthy, showing no external signs of sickness
The body condition score (BCS) of the pregnant cows was higher (+0.49 score) and the milk yield (MY) was lower (−4.36 kg), and mP4 in pregnant cows was (+6.11 ng/mL) higher compared to the group of non-pregnant cows (p < 0.001)
Summary
The novel digital equipment, such as multiple sensors, a data infrastructure, and data analytics, can be used to monitor animals or their environment [1]. Blood biomarkers are valuable indicators of animal health but not generally applicable commercially. They could provide a lot of information, especially because subclinical stages of diseases can be detected by biomarkers while the cow may appear completely healthy, showing no external signs of sickness. Elevated levels of BHB in blood have been associated with reduction in milk yield, impaired reproductive performance, and increased occurrence of metabolic disorders; early detection of higher BHB levels is crucial [5]. For the detection of subclinical mastitis, a good indicator is measurement of inline lactate dehydrogenase (LDH) activity in milk, for it is both simple and cost effective with high sensitivity and specificity [6]. Larsen et al [7] reported that the milk enzyme LDH performed with acute phase proteins and somatic cell count as inflammatory indicators of mastitis
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