scholarly journals Validation of an Accelerometer Sensor-Based Collar for Monitoring Grazing and Rumination Behaviours in Grazing Dairy Cows

Animals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2724
Author(s):  
Muhammad Wasim Iqbal ◽  
Ina Draganova ◽  
Patrick C. H. Morel ◽  
Stephen T. Morris
Keyword(s):  
Dairy Cows ◽  
Real Time ◽  
Correlation Coefficient ◽  
Visual Observation ◽  
Accelerometer Sensor ◽  
Daily Observation ◽  
Observation Session ◽  
Time Basis ◽  
Grazing Dairy Cows ◽  
Observation Period

This study evaluated the accuracy of a sensor-based device (AfiCollar) to automatically monitor and record grazing and rumination behaviours of grazing dairy cows on a real-time basis. Multiparous spring-calved dairy cows (n = 48) wearing the AfiCollar were selected for the visual observation of their grazing and rumination behaviours. The total observation period was 36 days, divided into four recording periods performed at different times of the year, using 12 cows in each period. Each recording period consisted of nine daily observation sessions (three days a week for three consecutive weeks). A continuous behaviour monitoring protocol was followed to visually observe four cows at a time for each daily observation session, from 9:00 a.m. to 5:00 p.m. Overall, 144 observations were collected and the data were presented as behaviour activity per daily observation session. The behaviours visually observed were also recorded through an automated AfiCollar device on a real-time basis over the observation period. Automatic recordings and visual observations were compared with each other using Pearson’s correlation coefficient (r), Concordance correlation coefficient (CCC), and linear regression. Compared to visual observation (VO), AfiCollar (AC) showed slightly higher (10%) grazing time and lower (4%) rumination time. AC results and VO results had strong associations with each other for grazing time (r = 0.91, CCC = 0.71) and rumination time (r = 0.89, CCC = 0.80). Regression analysis showed a significant linear relationship between AC and VO for grazing time (R2 = 0.83, p < 0.05) and rumination time (R2 = 0.78, p < 0.05). The relative prediction error (RPE) values for grazing time and rumination time were 0.17 and 0.40, respectively. Overall, the results indicated that AfiCollar is a reliable device to accurately monitor and record grazing and rumination behaviours of grazing dairy cows, although, some minor improvements can be made in algorithm calibrations to further improve its accuracy.

scholarly journals Identification of Genomic Regions Associated with Concentrations of Milk Fat, Protein, Urea and Efficiency of Crude Protein Utilization in Grazing Dairy Cows

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 456
Author(s):  
Hewa Bahithige Pavithra Chathurangi Ariyarathne ◽  
Martin Correa-Luna ◽  
Hugh Thomas Blair ◽  
Dorian John Garrick ◽  
Nicolas Lopez-Villalobos
Keyword(s):  
Gene Ontology ◽  
New Zealand ◽  
Dairy Cows ◽  
Candidate Genes ◽  
Milk Fat ◽  
Crude Protein ◽  
Single Locus ◽  
Protein Utilization ◽  
Grazing Dairy Cows ◽  
Genomic Regions

The objective of this study was to identify genomic regions associated with milk fat percentage (FP), crude protein percentage (CPP), urea concentration (MU) and efficiency of crude protein utilization (ECPU: ratio between crude protein yield in milk and dietary crude protein intake) using grazing, mixed-breed, dairy cows in New Zealand. Phenotypes from 634 Holstein Friesian, Jersey or crossbred cows were obtained from two herds at Massey University. A subset of 490 of these cows was genotyped using Bovine Illumina 50K SNP-chips. Two genome-wise association approaches were used, a single-locus model fitted to data from 490 cows and a single-step Bayes C model fitted to data from all 634 cows. The single-locus analysis was performed with the Efficient Mixed-Model Association eXpedited model as implemented in the SVS package. Single nucleotide polymorphisms (SNPs) with genome-wide association p-values ≤ 1.11 × 10−6 were considered as putative quantitative trait loci (QTL). The Bayes C analysis was performed with the JWAS package and 1-Mb genomic windows containing SNPs that explained > 0.37% of the genetic variance were considered as putative QTL. Candidate genes within 100 kb from the identified SNPs in single-locus GWAS or the 1-Mb windows were identified using gene ontology, as implemented in the Ensembl Genome Browser. The genes detected in association with FP (MGST1, DGAT1, CEBPD, SLC52A2, GPAT4, and ACOX3) and CPP (DGAT1, CSN1S1, GOSR2, HERC6, and IGF1R) were identified as candidates. Gene ontology revealed six novel candidate genes (GMDS, E2F7, SIAH1, SLC24A4, LGMN, and ASS1) significantly associated with MU whose functions were in protein catabolism, urea cycle, ion transportation and N excretion. One novel candidate gene was identified in association with ECPU (MAP3K1) that is involved in post-transcriptional modification of proteins. The findings should be validated using a larger population of New Zealand grazing dairy cows.

scholarly journals Real-time behavioral recognition in dairy cows based on geomagnetism and acceleration information

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fuyang Tian ◽  
Jun Wang ◽  
Benhai Xiong ◽  
Linshu Jiang ◽  
Zhanhua Song ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Real Time

Supplementation of grazing dairy cows with a brewers grains/treated straw mixture

1990 ◽  
Vol 1990 ◽  
pp. 46-46 ◽  
Author(s):  
J.D. Leaver ◽  
R.C. Campling
Keyword(s):  
Dairy Cows ◽  
Crude Protein ◽  
Dry Matter ◽  
Barley Straw ◽  
Severe Drought ◽  
Grass Silage ◽  
Metabolisable Energy ◽  
Grazing Dairy Cows ◽  
Similar Cost ◽  
Friesian Cows

Supplementary feeding of grazing dairy cows is often uneconomic, and whilst supplementation with silage (buffer feeding) can be worthwhile, this often leads to a depletion of winter forage stores. In this study, a mixture of brewers grains and treated straw was used as a supplement. Offered as a 1:1 mixture in the dry matter (DM), it is a purchased substitute for grass silage, having a similar cost, and similar metabolisable energy (ME) and crude protein (CP) contents. The high seasonality adjustments to milk price in mid-late season make supplementation potentially worthwhile.Experiments were carried out from April to September in 1988 and 1989, which had moderate and very low rainfall respectively. Each year 20 British Friesian cows which calved December to March (1988 experiment) and February-April (1989) were allocated at random to either treatment B or C. In B, the cows were offered a 1:1 mixture (DM basis) of brewers grains and NaOH treated chopped barley straw for 60 minutes after morning milking. In C, the cows received no supplement. Both groups were fed 1.0 kg/day of concentrates in the milking parlour. Due to the severe drought in 1989, concentrate feeding was increased to 5.0 kg/day for all cows during the last 4 weeks of the experiment. Also, urea-treated whole crop wheat was fed at a level of 2.5 kg DM/day during the last 7 days.

scholarly journals Supplementation with Partially Hydrogenated Oil in Grazing Dairy Cows in Early Lactation

2002 ◽  
Vol 85 (3) ◽  
pp. 580-594 ◽  
Author(s):  
G.F. Schroeder ◽  
G.A. Gagliostro ◽  
D. Becu-Villalobos ◽  
I. Lacau-Mengido
Keyword(s):  
Dairy Cows ◽  
Early Lactation ◽  
Hydrogenated Oil ◽  
Grazing Dairy Cows ◽  
Partially Hydrogenated Oil

Supplementation with Ca salts of soybean oil interacts with concentrate level in grazing dairy cows: intake, ingestive behavior, and ruminal parameters

2016 ◽  
Vol 48 (8) ◽  
pp. 1593-1598 ◽  
Author(s):  
Fernanda Lopes Macedo ◽  
Fernanda Batistel ◽  
Jonas de Souza ◽  
Lucas Jado Chagas ◽  
Flávio Augusto Portela Santos
Keyword(s):  
Soybean Oil ◽  
Dairy Cows ◽  
Ingestive Behavior ◽  
Grazing Dairy Cows ◽  
Concentrate Level

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.

Corn By-products to Feed Grazing Dairy Cows during Summer

2013 ◽  
Author(s):  
M. R. Gallardo ◽  
S. E. Valtorta ◽  
J. Maiztegui
Keyword(s):  
Dairy Cows ◽  
Grazing Dairy Cows ◽  
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