Udder Ultrasonography of Dairy Cows: Investigating the Relationship between Echotexture, Blood Flow, Somatic Cell Count and Milk Yield during Dry Period and Lactation

Abstract

Udder health of dairy cows is related to their productivity and welfare. The period from dry-off to calving and early lactation is crucial. Ultrasonography is a useful and practical tool for the examination of the mammary parenchyma and blood flow. This observational study investigated the relationship between udder echotexture features, blood flow volume (BFVol) in the milk vein, milk somatic cell count (SCC) and daily milk yield (DMY) from late lactation, throughout the dry period and consecutive early lactation. Seventeen repeated measurements were performed on twenty-one Holstein cows. The udder parenchyma was examined with B-mode ultrasonography. Udder echotexture was studied using 15 features: Numerical Pixel Value (NPV), Pixel Standard Deviation (PSD), Skewness, Excess, Contrast, Homogeneity, Correlation, Entropy, Run Percentage, Long-Run Emphasis, Grey Value Distribution, Runlength Distribution, Gradient Mean Value, Gradient Variance and Percentage of Non-zero Gradients. Blood flow in the milk vein was examined with spectral Doppler. Linear mixed-effects models were employed to investigate relationships between BFVol, udder echotexture features, SCC and DMY throughout the study period. Our models showed that a 1 kg increase in DMY was associated with a significant increase of 0.25 L/min in the expected BFVol and that a 1,000,000-cells/mL increase in SCC was associated with a significant BFVol decrease of 0.49 L/min, keeping all other variables constant. Multivariable models showed significant associations between DMY and NPV, between PSD and Long-Run Emphasis, and between SCC and NPV, PSD, Gradient Mean Value, Homogeneity, Gradient Variance and Entropy. In conclusion, udder echotexture and BFVol in the milk vein are related to SCC and milk yield. Ultrasonography can be used for the comprehensive assessment of udder health in support of precision dairy farming.

The avian and human influenza A virus receptors sialic acid (SA)-α2,3 and SA-α2,6 are widely expressed in the bovine mammary gland

“…Interestingly, neither the human-, chicken-, nor the duck receptors were expressed in the ducts of the mammary gland, making an ascending mammary gland infection more challenging. It is not clear to which degree the HPAIV infected cows develop viremia, however, even a very low degree of viremia may be adequate for the virus to enter the mammary gland and establish infection because the blood flow in the lactation period is ~400 liter per hour 26 . Suggestions by the USDA that only some udder quarters may be involved in infection does, however, argue against a viremic source 27 .…”

Health of the dairy herd and indicators of milk quality

“…Період від запуску до отелення та рання лактація мають вирішальне значення. Themistokleous et al (2023) вивчали зв'язок між особливостями ехотекстури вимені, об'ємом кровотоку у молочній вені, кількістю соматичних клітин і добовим надоєм молока протягом пізньої лактації, сухостійного періоду та ранньої лактації. Автори дійшли висновку, що ультразвукову діагностику можна використовувати для комплексної оцінки здоров'я вимені.…”

Investigation of Bovine Disease and Events through Machine Learning Models

“…Researchers have explored a range of machine learning techniques to develop innovative methods for mastitis detection in bovine. In recent studies, ultrasound imaging has been used to assess udder health and identify early signs of mastitis (Themistokleous et al, 2023). Additionally, researchers have integrated data from milk composition analysis, such as somatic cell count and milk conductivity, into machine learning algorithms for mastitis prediction (Matera et al, 2022).…”