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 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.

scholarly journals Recent Advances on Early Detection of Heat Strain in Dairy Cows Using Animal-Based Indicators: A Review

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 980
Author(s):  
Hang Shu ◽  
Wensheng Wang ◽  
Leifeng Guo ◽  
Jérôme Bindelle
Keyword(s):  
Heat Stress ◽  
Early Detection ◽  
Dairy Cows ◽  
Real Time ◽  
Dairy Farms ◽  
Time Measurement ◽  
Heat Strain ◽  
Detection Methods ◽  
Livestock Farming ◽  
Real Time Measurement

In pursuit of precision livestock farming, the real-time measurement for heat strain-related data has been more and more valued. Efforts have been made recently to use more sensitive physiological indicators with the hope to better inform decision-making in heat abatement in dairy farms. To get an insight into the early detection of heat strain in dairy cows, the present review focuses on the recent efforts developing early detection methods of heat strain in dairy cows based on body temperatures and respiratory dynamics. For every candidate animal-based indicator, state-of-the-art measurement methods and existing thresholds were summarized. Body surface temperature and respiration rate were concluded to be the best early indicators of heat strain due to their high feasibility of measurement and sensitivity to heat stress. Future studies should customize heat strain thresholds according to different internal and external factors that have an impact on the sensitivity to heat stress. Wearable devices are most promising to achieve real-time measurement in practical dairy farms. Combined with internet of things technologies, a comprehensive strategy based on both animal- and environment-based indicators is expected to increase the precision of early detection of heat strain in dairy cows.

scholarly journals URINE GLUCOSE DETECTION AS A DIABETES DISEASE IN WOMEN AND ELDERLY IN KEDUNGPANDAN VILLAGE, JABON, SIDOARJO

2021 ◽  
Vol 1 (1) ◽  
pp. 5-10
Author(s):  
Andreas Putro Ragil Santoso ◽  
Devyana Dyah Wulandari
Keyword(s):  
Early Detection ◽  
Community Service ◽  
Metabolic Disorders ◽  
The Elderly ◽  
Total Sample ◽  
Glucose Detection ◽  
Early Detection Of Disease ◽  
The Public

Diabetes is a disease of metabolic disorders caused by poor production of insulin by the pancreas or due to the use of body insulin which is not maximal, causing interference. The main diabetes that often occurs in the community is type 1 and type 2 diabetes because of the influence of body insulin. Examination for detection is intended so that the public can find out about the presence of glucose in the urine so that the community can immediately recover faster, considering that if there is a glucose level in the urine, there is an increase in the level of glucose in the blood. The method used in this community service is to collect residents at the center, which is then carried out by examining the urine sample using a urine dysptic. Based on the results of examinations carried out on 62 people consisting of mothers and the elderly, it showed that there were 10 positive people or 19% of the total sample. This shows that early detection is important because there are still people who do not know the importance of early detection of disease in themselves, especially in the Kedung Pandan area.

scholarly journals Effect of the first and second postpartum partial milking on blood serum calcium concentration in dairy cows

2014 ◽  
Vol 59 (No. 3) ◽  
pp. 128-133
Author(s):  
E.G. Salgado-Hernández ◽  
A. Aparicio-Cecilio ◽  
F.H. Velásquez-Forero ◽  
D.A. Castillo-Mata
Keyword(s):  
Blood Serum ◽  
Dairy Cows ◽  
Serum Calcium ◽  
Metabolic Disorders ◽  
Calcium Concentration ◽  
Atomic Absorption Spectrophotometry ◽  
Serum Calcium Concentration ◽  
Group 2 ◽  
Group 1

Parturient paresis and subclinical hypocalcemia are frequent metabolic disorders in dairy cows postpartum. The aim of this study was to determine the effect of postpartum partial milking in the first two milkings on blood serum calcium concentration in dairy cows. Twenty multiparous Holstein dairy cows were randomized into two groups. Cows of group 1 (n = 10) were partially milked at the first and second milking postpartum. Cows of group 2 (n = 10) were completely milked. Blood samples were collected from all animals 5–7 days before calving, within 30 min after calving, and 4, 8, 12, 16, 20, 24, 28, and 32 h after calving for determination of serum calcium (Ca), phosphorus (P), and magnesium (Mg) concentrations. Colostrum production was registered and sampled in the first and second milking. Concentration of Ca in colostrum was determined by atomic absorption spectrophotometry. Serum Ca and P concentrations decreased in both groups after parturition (P < 0.05) and remained low during 32 h postpartum with no difference observed between groups (P > 0.05). Serum concentrations of Mg were stable in all samples and no statistical difference was observed between groups (P > 0.05). Colostrum production was higher in completely milked cows only in the first postpartum milking (P < 0.05), but there was no difference between groups at the second milking. Total Ca secretion in colostrum was higher in the complete milking group at the first and second postpartum milking. Colostrum Ca secretion increased at the second milking with respect to the first one in both groups (P < 0.05). There was no correlation between serum Ca and colostrum Ca (P > 0.05). In this study, the partial milking of colostrum in the first and second milking postpartum did not prevent subclinical hypocalcemia in dairy cows.  

The effect of ammoniated and roasted barley on rumen pH, milk yield and milk composition of lactating dairy cows

2003 ◽  
Vol 2003 ◽  
pp. 107-107
Author(s):  
M. H. Fathi ◽  
A. Nikkhah
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Milk Fat ◽  
Dry Matter ◽  
Metabolic Disorders ◽  
Milk Composition ◽  
Barley Grain ◽  
Nutrient Requirements ◽  
Rumen Ph ◽  
Lactating Dairy Cows

Cereal grains can provide the major source of energy in diets in order to meet the nutrient requirements of high producing dairy cows. However the amount of starch that can be included in the diets of dairy cows is limited particularly if starch is rapidly fermented such as barley starch. Reduction of feed intake, rumen pH, milk fat test, microbial growth and other metabolic disorders are expected if ruminally degradable starch is fed in amount that cant be efficiently metabolized by rumen microbs. Various techniques for processing barley grain have been developed to decrease the degradability of dry matter in rumen without reducing its extent of digestion. McNiven (1995) showed roasting of barley is more effective treatment. The objective of this experiment was to study of effects the roasting and ammoniation of barley grain on rumen pH, feces pH, milk yield and milk composition in dairy cows.

scholarly journals Welfare Quality® for dairy cows: towards a sensor-based assessment

2020 ◽  
Vol 87 (S1) ◽  
pp. 28-33 ◽  
Author(s):  
Francisco Maroto Molina ◽  
Carlos C. Pérez Marín ◽  
Laura Molina Moreno ◽  
Estrella I. Agüera Buendía ◽  
Dolores C. Pérez Marín
Keyword(s):  
Dairy Cows ◽  
Dairy Farms ◽  
Assessment Method ◽  
Sensor Data ◽  
Objective Data ◽  
Livestock Farming ◽  
Precision Livestock Farming ◽  
Non Invasive ◽  
Social Concerns ◽  
Welfare Quality

AbstractThis Research Reflection addresses the possibilities for Welfare Quality® to evolve from an assessment method based on data gathered on punctual visits to the farm to an assessment method based on sensor data. This approach could provide continuous and objective data, while being less costly and time consuming. Precision Livestock Farming (PLF) technologies enabling the monitorisation of Welfare Quality® measures are reviewed and discussed. For those measures that cannot be assessed by current technologies, some options to be developed are proposed. Picturing future dairy farms, the need for multipurpose and non-invasive PLF technologies is stated, in order to avoid an excessive artificialisation of the production system. Social concerns regarding digitalisation are also discussed.

Principal component analysis for the early detection of mastitis and lameness in dairy cows

2013 ◽  
Vol 80 (3) ◽  
pp. 335-343 ◽  
Author(s):  
Bettina Miekley ◽  
Imke Traulsen ◽  
Joachim Krieter
Keyword(s):  
Principal Component Analysis ◽  
Early Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Error Rates ◽  
Sensor Data ◽  
Sequence Length ◽  
Feeding Patterns ◽  
Original Dataset ◽  
Block Sensitivity

This investigation analysed the applicability of principal component analysis (PCA), a latent variable method, for the early detection of mastitis and lameness. Data used were recorded on the Karkendamm dairy research farm between August 2008 and December 2010. For mastitis and lameness detection, data of 338 and 315 cows in their first 200 d in milk were analysed, respectively. Mastitis as well as lameness were specified according to veterinary treatments. Diseases were defined as disease blocks. The different definitions used (two for mastitis, three for lameness) varied solely in the sequence length of the blocks. Only the days before the treatment were included in the blocks. Milk electrical conductivity, milk yield and feeding patterns (feed intake, number of feeding visits and time at the trough) were used for recognition of mastitis. Pedometer activity and feeding patterns were utilised for lameness detection. To develop and verify the PCA model, the mastitis and the lameness datasets were divided into training and test datasets. PCA extracted uncorrelated principle components (PC) by linear transformations of the raw data so that the first few PCs captured most of the variations in the original dataset. For process monitoring and disease detection, these resulting PCs were applied to the Hotelling's T2 chart and to the residual control chart. The results show that block sensitivity of mastitis detection ranged from 77·4 to 83·3%, whilst specificity was around 76·7%. The error rates were around 98·9%. For lameness detection, the block sensitivity ranged from 73·8 to 87·8% while the obtained specificities were between 54·8 and 61·9%. The error rates varied from 87·8 to 89·2%. In conclusion, PCA seems to be not yet transferable into practical usage. Results could probably be improved if different traits and more informative sensor data are included in the analysis.

Insulin resistance: the link between metabolic disorders and cystic ovarian disease in high yielding dairy cows?

1999 ◽  
Vol 56 (3-4) ◽  
pp. 211-222 ◽  
Author(s):  
G. Opsomer ◽  
Th. Wensing ◽  
H. Laevens ◽  
M. Coryn ◽  
A. de Kruif
Keyword(s):  
Insulin Resistance ◽  
Dairy Cows ◽  
Metabolic Disorders ◽  
Ovarian Disease ◽  
Cystic Ovarian Disease
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