Short communication: Variance and autocorrelation of deviations in daily milk yield are related with clinical mastitis in dairy cows

Kok, A.; Tsousis, Georgios; Niozas, G; Kemp, B.; Kaske, Martin; Knegsel, A.T.M. van

doi:10.1016/j.animal.2021.100363

Cited by 8 publications

(9 citation statements)

References 7 publications

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“…The first explanation is that LnVar was favorably associated with some diseases (clinical mastitis, pneumonia; Table 7.9), but unfavorably with others (ketosis; Table 7.9), which levels out the economic effects. The significant association with clinical mastitis is in line with Kok et al (2021). The second explanation for the insignificant effect is that farmers likely did not register all (minor) health problems that required attention.…”

Section: Discussionmentioning

confidence: 66%

“…The authors mentioned missing records during mastitis treatment as a possible reason why they saw a negative instead of a positive relation of autocorrelation with clinical mastitis. Still, a positive relation between variance of daily milk yield deviations and clinical mastitis was observed, which suggests that for variance the presence of missing values is less important than for autocorrelation: apparently in the periods before or after the disease event deviations were sufficiently large to result in an increase in variance (Kok et al, 2021).…”

Section: Selection Of Longitudinal Traitmentioning

confidence: 96%

“…This thesis contains an extensive study on the use of these resilience indicators based on daily milk yield and step count in dairy cattle. Moreover, throughout the course of this study, many other studies have been conducted on resilience indicators based on longitudinal data in animals (Elgersma et al, 2018;van Dixhoorn et al, 2018;Berghof et al, 2019a;Putz et al, 2019;Adriaens et al, 2020;Cheng et al, 2020;van der Zande et al, 2020;Kok et al, 2021). Based on all these studies and this thesis, a road map can be designed that can be used by future researchers to develop resilience indicators that are suitable for implementation in practice, both for breeding and for management purposes.…”

Section: Application Of Indicators Of Resilience Based On 'Critical S...mentioning

confidence: 99%

“…Especially if missing values exist due to disease, the resilience indicators do not reflect response to that disease. Kok et al (2021) studied associations between resilience indicators based on milk yield deviations and clinical mastitis. The authors mentioned missing records during mastitis treatment as a possible reason why they saw a negative instead of a positive relation of autocorrelation with clinical mastitis.…”

Section: Selection Of Longitudinal Traitmentioning

confidence: 99%

“…This approach was performed by Van Dixhoorn et al (2018) for predicting resilience to the disturbance of calving in dairy cattle, and by Van der Zande et al (2020) for predicting resilience to a disease disturbance in pigs. An observational study can be performed as well, such as the one by Kok et al (2021), who investigated the association between resilience indicators and occurrence of mastitis cases.…”

Section: Validation Of Calculated Resilience Indicatorsmentioning

confidence: 99%

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Genetic improvement of resilience in dairy cattle using longitudinal data

Poppe¹

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Poppe, M. (2022). Genetic improvement of resilience in dairy cattle using longitudinal data. PhD thesis, Wageningen University, the Netherlands Resilience is the ability of cows to be minimally affected by, and to quickly recover from environmental disturbances, such as pathogens, extreme weather, or changes in feed quality. Resilience is important for welfare of cows and work pleasure of farmers, especially given an expected increase of disturbances in the future. This thesis focuses on developing indicators of resilience from longitudinal data, based on the expectation that longitudinal data records show response patterns to disturbances, informative about resilience. Resilience indicators based on response patterns can potentially assist in selecting the genetically most resilient animals for breeding, and in identifying resilience at herd level. The main focus of this thesis was on the resilience indicators 'variance' and 'autocorrelation' of daily deviations from expected values of milk yield and step count. Resilience is indicated by low variance (small deviations from baseline) and low lag-1 autocorrelation (weak dependency between subsequent deviations -quick recovery). Variance and autocorrelation of daily deviations from expected milk yield were heritable (0.21 and 0.09, respectively) and both were genetically similar within and between lactations. Variance seems informative about vulnerability and strength of response to disturbances, based on genetic correlations with milk loss upon reallife disturbances and with health, longevity and fertility. Autocorrelation had a favorable genetic correlation with recovery rate upon disturbances. Furthermore, variance was associated with lifetime gross margin, which confirms its economic importance. Levels of variance and autocorrelation differed considerably between herds, suggesting herd management plays a role in resilience. When based on step count instead of milk yield, variance and autocorrelation were heritable (0.14 and 0.04), and autocorrelation was favorably genetically correlated with health traits and fertility. However, variance had unfavorable genetic correlations with health. Additional traits based on step count were also heritable (especially mean step count; 0.45), but more research is needed into their relations with resilience. Genetic selection on a resilience index based on variance and autocorrelation of milk yield deviations, and potentially autocorrelation based on step count deviations, is expected to result in more resilient cows, that are less affected by disturbances and that recover more quickly. Contents

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Section: Discussionmentioning

confidence: 66%

Section: Selection Of Longitudinal Traitmentioning

confidence: 96%