scholarly journals Combination of Sensor Data and Health Monitoring for Early Detection of Subclinical Ketosis in Dairy Cows

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1484 ◽  
Author(s):  
Valentin Sturm ◽  
Dmitry Efrosinin ◽  
Manfred Öhlschuster ◽  
Erika Gusterer ◽  
Marc Drillich ◽  
...  
Keyword(s):  
Early Detection ◽  
Dairy Cows ◽  
Health Monitoring ◽  
Sensor Data ◽  
Farm Animals ◽  
Economic Losses ◽  
Early Lactation ◽  
Subclinical Ketosis ◽  
Different Types ◽  
Secondary Diseases

Subclinical ketosis is a metabolic disease in early lactation. It contributes to economic losses because of reduced milk yield and may promote the development of secondary diseases. Thus, an early detection seems desirable as it enables the farmer to initiate countermeasures. To support early detection, we examine different types of data recordings and use them to build a flexible algorithm that predicts the occurence of subclinical ketosis. This approach shows promising results and can be seen as a step toward automatic health monitoring in farm animals.

6.2. Early detection of metabolic disorders in dairy cows by using sensor data

2015 ◽  
pp. 239-248
Author(s):  
R.M. de Mol ◽  
J. van Dijk ◽  
M.H. Troost ◽  
A. Sterk ◽  
R. Jorritsma ◽  
...  
Keyword(s):  
Early Detection ◽  
Dairy Cows ◽  
Metabolic Disorders ◽  
Sensor Data

scholarly journals The Effect of Subclinical Ketosis in Early Lactation on Reproductive Performance of Postpartum Dairy Cows

2007 ◽  
Vol 90 (6) ◽  
pp. 2788-2796 ◽  
Author(s):  
R.B. Walsh ◽  
J.S. Walton ◽  
D.F. Kelton ◽  
S.J. LeBlanc ◽  
K.E. Leslie ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Reproductive Performance ◽  
Early Lactation ◽  
Subclinical Ketosis

scholarly journals Use of a glycogenic precursor during the prepartum period and its effects upon metabolic indicators and reproductive parameters in dairy cows

2020 ◽  
Vol 11 (2) ◽  
pp. 408-420
Author(s):  
Carlos Leyva Orasma ◽  
Jesús Jaime Benitez-Rivas ◽  
Juan Luis Morales Cruz ◽  
Cesar Alberto Meza-Herrera ◽  
Oscar Ángel-García ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Transition Period ◽  
Body Condition Score ◽  
Treated Group ◽  
Control Group ◽  
Blood Levels ◽  
Early Lactation ◽  
Homogeneous Groups ◽  
Subclinical Ketosis ◽  
Retained Placenta

The aim was to evaluate if 1-2 propanodiol plus calcium propionate (glycogenic precursor) supplementation during the transition period in high yielding dairy cows reduces metabolic and reproductive dysfunctions during early lactation. Cows (n=202) where divided into two homogeneous groups regarding number of lactations and body condition score. 1) Treated Group (GG; n=112) received 60g/cow/day  15d of a glycogenic precursor during the transition period. 2) Control Group (GC; n = 90) received no treatment. Postpartum levels of BHB (GG= 0.9±0.2 mmol/L vs GC =1.3±0.2 mmol/L; P < 0.05), and NEFA (GG= 0.6 ± 0.1 mEq/L vs GC = 0.8 ± 0.1 mEq/L; P < 0.05) were higher for GC. Likewise, GC-cows had a higher percentage of retained placenta (23% vs. 13%; P ≤ 0.06) subclinical ketosis (GG = 10%, GC = 56%; P < 0.05), and mastitis (GG = 8%, GC = 16%; P < 0.05). Metritis, dystocia, abortions, clinical ketosis, hypocalcemia and ruminal acidosis showed no differences. Administration of a glycogenic precursor during the transition period demonstrated a positive effect upon BHB and NEFA blood levels during early lactation. Also, levels of subclinical ketosis and retained placenta were reduced.

Sensor placement determination in system health monitoring process based on dual information risk and uncertainty criteria

2017 ◽  
Vol 232 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Farzin Salehpour-Oskouei ◽  
Mohammad Pourgol-Mohammad
Keyword(s):  
Steam Turbine ◽  
Health Monitoring ◽  
Sensor Placement ◽  
Information Value ◽  
Sensor Data ◽  
Economic Losses ◽  
System Failure ◽  
Monitoring Process ◽  
Sensor Information

Validity of sensor data is a challenge in system monitoring due to stochastic nature of failure occurrence. The quantity and location of sensors affect the system health information, while sensor malfunction causes misleading results about the system condition. Occurred economic losses are irrecoverable expenses in respect to the monitoring system as well as the system failure. In this study, a dual index approach is proposed for the determination of sensor placement scenarios based on two criteria: (1) uncertainty of sensor information and (2) risk of sensor failure. With about variation of environmental factors conditions (e.g. temperature) and their failure threshold characterization, system failure model is developed and analyzed by a proposed efficient Monte Carlo simulation. Statistical variance of sensor information about estimating of system state as the quantitative uncertainty measure of choice in this research is estimated according to the information value that each possible sensor placement scenario provides through sensor information. In the next phase, risk index is determined based on sensor malfunction and corresponding quantifiable losses through both failure costs and maintenance expenditure. All feasible combinations of sensor failures are considered in the risk model. Finally, a combinatorial criterion is determined through information entropy calculation, which considers both indexes proposed above simultaneously. Sensor placement scenarios are comparatively prioritized based on this criterion. Accordingly, the technical directions are provided for suitability of the criteria for prioritizing sensor arrangement in various systems with different reliability-based characteristics. As a case study, determination of sensor placement is demonstrated on a typical steam turbine. According to the low variation of both information uncertainty and risk indexes, it is concluded that the combinatorial index is the proper criterion for sensor placement determination in health monitoring process of the steam turbine.

scholarly journals Metabolic evaluation of dairy cows submitted to three different strategies to decrease the effects of negative energy balance in early postpartum

2011 ◽  
Vol 31 (suppl 1) ◽  
pp. 11-17 ◽  
Author(s):  
Alejandra M.B García ◽  
Felipe C Cardoso ◽  
Rómulo Campos ◽  
Diego X Thedy ◽  
Félix H.D González
Keyword(s):  
Energy Balance ◽  
Fatty Liver ◽  
Dairy Cows ◽  
Milk Yield ◽  
Ketone Bodies ◽  
Negative Energy ◽  
Negative Energy Balance ◽  
Early Lactation ◽  
Blood Samples ◽  
Subclinical Ketosis

In early lactation dairy cattle suffer metabolic alterations caused by negative energy balance, which predisposes to fatty liver and ketosis. The aim of this study was to evaluate the metabolic condition of high yielding dairy cows subjected to three treatments for preventing severe lipomobilization and ketosis in early lactation. Fifty four multiparous Holstein cows yielding >30 L/day were divided into four groups: control (CN= no treatment), glucose precursor (PG= propylene-glycol), hepatic protector (Mp= Mercepton®), and energy supplement with salts of linolenic and linoleic faty acids (Mg-E= Megalac-E®). Treatments were administrated randomly at moment of calving until 8 weeks postpartum. Blood samples were collected on days 1, 7, 14, 21, 28, 35, 42 and 49 postpartum. Body condition score (BCS) was evaluated at the same periods and milk yield was recorded at 2nd, 4th, 5th, 6th, 7th, and 8th weeks of lactation. Concentrations of non-esterified fatty acids (NEFA), albumin, AST, ß-hydroxybutyrate (BHBA), cholesterol, glucose, total protein, urea and triglycerides were analyzed in blood samples. Cut-off points for subclinical ketosis were defined when BHBA >1.4 mmol/L and NEFA >0.7 mmol/L. General occurrence of subclinical ketosis was 24% during the period. An ascendant curve of cholesterol and glucose was observed from the 1st to the 8th week of lactation, while any tendency was observed with BHBA and NEFA, although differences among treatments were detected (p<0.05). BCS decreased from a mean of 3.85 at 1st week to 2.53 at 8th week of lactation (p=0.001). Milk yield was higher in the Mg-E group compared with the other treatment groups (p<0.05) Compared with the CN group, the treatments with Mp and PG did not show significant differences in blood biochemistry and milk yield. Cows receiving PG and Mg-E showed higher values of BHBA and NEFA (P<0.05), indicating accentuated lipomobilization. Supplementation with Mg-E also resulted in significant higher concentrations of cholesterol, BHBA, urea, AST and lower values of glycemia. This performance may be explained by the highest milk yield observed with this treatment. Treatments with PG and Mp did not improve milk yield, compared with control cows, but did not show metabolic evidence of ketosis, fat mobilization or fatty liver. These results suggest that treatment with Mg-E improves milk production but induces a higher negative energy balance leading to moderated lipomobilization and ketone bodies production, increasing the risk of fatty liver.

The effect of foot lesions on locomotion score and spine posture measured using computerised motion analysis in early lactation Holstein dairy cows

2007 ◽  
Vol 2007 ◽  
pp. 100-100
Author(s):  
N. Blackie ◽  
E.C.L Bleach ◽  
J.R Amory ◽  
C.R Nicholls ◽  
J.R Scaife
Keyword(s):  
Early Detection ◽  
Dairy Cows ◽  
Motion Analysis ◽  
Dairy Cow ◽  
Scoring Systems ◽  
Early Lactation ◽  
Foot Lesions ◽  
Locomotion Score ◽  
Holstein Dairy Cows

Locomotion scoring is an important tool to detect dairy cow lameness. A number of locomotion scoring systems use the posture of the back to identify lame cows (score 3). For example Sprecher et al (1997) suggested the presence of an arched back standing and walking indicates lameness. Flower and Weary (2006) developed this system to score cows while walking where a score 3 cow has a more severely arched back than a score 2 cow. However to date no work has been published characterising the degree of arching of the spine observed in lame animals and its relationship with foot lesions. This is important in the early detection of lameness and could be incorporated into locomotion scoring systems to improve the objectivity. The aim of this study was to assess the effect of foot lesions on spine posture of Holstein dairy cows in early lactation by motion analysis.

019 The use of prepartal standing behavior as a parameter for early detection of subclinical ketosis in postpartal dairy cows

2017 ◽  
Vol 95 (suppl_2) ◽  
pp. 9-9
Author(s):  
S. Rodriguez-Jimenez ◽  
K. J. Haerr ◽  
J. J. Loor ◽  
J. S. Osorio ◽  
F. C. Cardoso
Keyword(s):  
Early Detection ◽  
Dairy Cows ◽  
Subclinical Ketosis
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