Literature DB >> 27372584

Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part II. Mastitis.

M L Stangaferro1, R Wijma1, L S Caixeta1, M A Al-Abri1, J O Giordano2.   

Abstract

The objectives of this study were to evaluate (1) the performance of an automated health-monitoring system (AHMS) to identify cows with mastitis based on an alert system (health index score, HIS) that combines rumination time and physical activity; (2) the number of days between the first HIS alert and clinical diagnosis (CD) of mastitis by farm personnel; and (3) the daily rumination time, physical activity, and HIS patterns around CD. Holstein cows (n=1,121; 451 nulliparous and 670 multiparous) were fitted with a neck-mounted electronic rumination and activity monitoring tag (HR Tags, SCR Dairy, Netanya, Israel.) from at least -21 to 80 d in milk (DIM). Raw data collected in 2-h periods were summarized per 24 h as daily rumination and activity. An HIS (0 to 100 arbitrary units) was calculated daily for individual cows with an algorithm that used rumination and activity. A positive HIS outcome was defined as an HIS of <86 units during at least 1 d from -5 to 2 d after CD. Blood concentrations of nonesterified fatty acids, β-hydroxybutyrate, total calcium, and haptoglobin were also determined in a subgroup of cows (n=459) at -11±3, -4±3, 0, 3±1, 7±1, 14±1, and 28±1 DIM. The sensitivity of the HIS was 58% [95% confidence interval (CI): 49, 67] for all cases of clinical mastitis (n=123), and 55% (95% CI: 46, 64; n=114) and 89% (95% CI: 68, 100; n=9) for cases of mastitis alone or concurrent with other health disorders, respectively. Among clinical cases, sensitivity was 80.7% (95% CI: 67, 97) for cases caused by Escherichia coli (n=31) and ranged from 45 to 48% for cases caused by gram-positive bacteria (n=39; Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Streptococcus spp., Staphylococcus spp., and Trueperella pyogenes), Staphylococcus aureus (n=11), or cases with no bacterial growth (n=25). Days between the first HIS <86 and CD were -0.6 (95% CI: -1.1, -0.2) for all cases of mastitis. Cows diagnosed with mastitis had alterations of their rumination, activity, HIS patterns, and reduced milk production around CD depending on the type of mastitis case. Cows with mastitis also had some alterations of their calcium and haptoglobin concentrations around calving. The AHMS used in this study was effective for identifying cows with clinical cases of mastitis caused by E. coli and cows with another disease occurring during an event of mastitis, but it was less effective in identifying cows with mastitis not caused by E. coli.
Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  activity; dairy cow; mastitis; rumination

Mesh:

Substances:

Year:  2016        PMID: 27372584     DOI: 10.3168/jds.2016-10908

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  9 in total

Review 1.  Diagnosis of bovine mastitis: from laboratory to farm.

Authors:  Aqeela Ashraf; Muhammad Imran
Journal:  Trop Anim Health Prod       Date:  2018-06-08       Impact factor: 1.559

2.  The Early Prediction of Common Disorders in Dairy Cows Monitored by Automatic Systems with Machine Learning Algorithms.

Authors:  Xiaojing Zhou; Chuang Xu; Hao Wang; Wei Xu; Zixuan Zhao; Mengxing Chen; Bin Jia; Baoyin Huang
Journal:  Animals (Basel)       Date:  2022-05-12       Impact factor: 3.231

3.  Using Sensor Data to Detect Lameness and Mastitis Treatment Events in Dairy Cows: A Comparison of Classification Models.

Authors:  Christian Post; Christian Rietz; Wolfgang Büscher; Ute Müller
Journal:  Sensors (Basel)       Date:  2020-07-10       Impact factor: 3.576

4.  Sensor based time budgets in commercial Dutch dairy herds vary over lactation cycles and within 24 hours.

Authors:  P R Hut; S E M Kuiper; M Nielen; J H J L Hulsen; E N Stassen; M M Hostens
Journal:  PLoS One       Date:  2022-02-25       Impact factor: 3.240

5.  Assessment of feeding, ruminating and locomotion behaviors in dairy cows around calving - a retrospective clinical study to early detect spontaneous disease appearance.

Authors:  Mahmoud Fadul; Luigi D'Andrea; Maher Alsaaod; Giuliano Borriello; Antonio Di Lori; Dimitri Stucki; Paolo Ciaramella; Adrian Steiner; Jacopo Guccione
Journal:  PLoS One       Date:  2022-03-04       Impact factor: 3.240

6.  High Precision Classification of Resting and Eating Behaviors of Cattle by Using a Collar-Fitted Triaxial Accelerometer Sensor.

Authors:  Kim Margarette Corpuz Nogoy; Sun-Il Chon; Ji-Hwan Park; Saraswathi Sivamani; Dong-Hoon Lee; Seong Ho Choi
Journal:  Sensors (Basel)       Date:  2022-08-09       Impact factor: 3.847

7.  Sensitivity and Specificity for the Detection of Clinical Mastitis by Automatic Milking Systems in Bavarian Dairy Herds.

Authors:  Mathias Bausewein; Rolf Mansfeld; Marcus G Doherr; Jan Harms; Ulrike S Sorge
Journal:  Animals (Basel)       Date:  2022-08-19       Impact factor: 3.231

8.  Assessment of the Relationship between Postpartum Health and Mid-Lactation Performance, Behavior, and Feed Efficiency in Holstein Dairy Cows.

Authors:  Malia J Martin; Kent A Weigel; Heather M White
Journal:  Animals (Basel)       Date:  2021-05-13       Impact factor: 2.752

Review 9.  Alterations in sick dairy cows' daily behavioural patterns.

Authors:  I Dittrich; M Gertz; J Krieter
Journal:  Heliyon       Date:  2019-11-22
  9 in total

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