Abstract

Simple SummaryIn dairy cows, the transition to lactation period is metabolically challenging. Elevated blood ketone bodies, known as hyperketonemia or ketosis, is a postpartum metabolic disorder that is associated with negative energy balance, greater comorbidity risk, and decreased milk production. Research to understand the etiology of hyperketonemia has highlighted risk factors and unfavorable outcomes; however, analysis of real-world data is valuable for determining the outcomes across a region. Dairy herd improvement data from herds with diverse size and production were analyzed to determine potential risk factors for and production outcomes of hyperketonemia in the Midwest region (US). Cows predicted to have hyperketonemia had greater previous lactation dry period length, somatic cell count, and dystocia, which may represent risk factors for ketosis. Cows with predicted hyperketonemia had lower milk yield and milk protein but greater milk fat and somatic cell count in the current lactation. Culling rate within 60d of calving, days open, and artificial inseminations were all greater in cows predicted to have hyperketonemia. Prevalence of hyperketonemia decreased linearly in herds with greater rolling herd average milk yield. This work demonstrates the impact of hyperketonemia on production variables which underscores the importance on continued work to reduce hyperketonemia prevalence.Prediction of hyperketonemia (HYK), a postpartum metabolic disorder in dairy cows, through use of cow and milk data has allowed for high-throughput detection and monitoring during monthly milk sampling. The objective of this study was to determine associations between predicted HYK (pHYK) and production parameters in a dataset generated from routine milk analysis samples. Data from 240,714 lactations across 335 farms were analyzed with multiple linear regression models to determine HYK status. Data on HYK or disease treatment was not solicited. Consistent with past research, pHYK cows had greater previous lactation dry period length, somatic cell count, and dystocia. Cows identified as pHYK had lower milk yield and protein percent but greater milk fat, specifically greater mixed and preformed fatty acids (FA), and greater somatic cell count (SCC). Differential somatic cell count was greater in second and fourth parity pHYK cows. Culling (60d), days open, and number of artificial inseminations were greater in pHYK cows. Hyperketonemia prevalence decreased linearly in herds with greater rolling herd average milk yield. This research confirms previously identified risk factors and negative outcomes associated with pHYK and highlights novel associations with differential SCC, mixed FA, and preformed FA across farm sizes and production levels.

Highlights

  • Use of data to predict and to diagnose dairy cattle health events has become of great interest as the availability of data sources on-farm increases

  • Milk Fourier-transform infrared spectroscopy (FTIR) based testing for ß-hydroxybutyrate (BHB) concentration during routine milk testing is a commonly employed method for predicting ketosis; predicted milk BHB concentrations have lower correlations with blood BHB compared to more comprehensive models developed to predict HYK based on both milk and cow variables using approaches ranging from multiple linear regression to more advanced artificial neural networks [4,8,9,10,11,12,13]

  • The analysis presented here is the first large scale analysis of data from the previously published multiple linear regression models that utilize both cow data and milk analysis to predict blood BHB with greater than 83% accuracy in Holstein cows [4]

Read more

Summary

Introduction

Use of data to predict and to diagnose dairy cattle health events has become of great interest as the availability of data sources on-farm increases. Cow- and farm-level data, and more comprehensive analysis of routinely analyzed milk samples have generated datasets that can be used to monitor and predict productivity, animal health, and inform management decisions as previously reviewed [1,2,3]. Given the known negative impacts of HYK on farm economics and animal health, there has been strong interest in high-throughput data-based methods of predicting herd- or cow-level HYK. Milk Fourier-transform infrared spectroscopy (FTIR) based testing for ß-hydroxybutyrate (BHB) concentration during routine milk testing is a commonly employed method for predicting ketosis; predicted milk BHB concentrations have lower correlations with blood BHB compared to more comprehensive models developed to predict HYK based on both milk and cow variables using approaches ranging from multiple linear regression to more advanced artificial neural networks [4,8,9,10,11,12,13]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call