scholarly journals 165 Evaluation of Milk Urea Nitrogen Measurement Precision and Accuracy

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 134-134
Author(s):  
Kristan F Reed ◽  
Emma Wood ◽  
David M Barbano ◽  
Matilde Portnoy
Keyword(s):  
Milk Fat ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Nitrogen Efficiency ◽  
Urea Nitrogen ◽  
Milk Urea ◽  
Precision And Accuracy ◽  
Milk Urea Nitrogen

Abstract High levels of urea in blood, milk and urine have been linked to poor nitrogen efficiency, increased feed costs, poor reproductive performance and increased environmental impacts of dairy farming. Milk urea nitrogen (MUN) is a commonly used metric to manage herd nitrogen efficiency, with current recommendations for MUN to be between 8–14 mg/dL to maintain milk production and reduce nitrogen losses. However, a previous work suggests commercial analysis of MUN with mid-infrared spectroscopy (MIR) may not be precise enough to determine if a milk sample is within the recommended range. Thus, the objective of this study was to evaluate the precision and accuracy of milk testing lab MUN measurements. Four sets of bulk tank samples were sent to 3 commercial labs and one research lab for analysis by MIR. Samples were sent to commercial labs in duplicate and MUN was also assessed through an enzymatic assay. The Euclidean distance (ED) was calculated as a combined metric of precision and accuracy. The ED was not different between labs and ranged from 0.81–1.27. Repeatability (sr) and reproducibility (sR) were estimated for commercial labs and ranged from (0.297–0.469) and (0.555–0.791) respectively. Differences between individual sample MIR and enzymatic MUN were regressed on the centered enzymatic MUN in a linear mixed model that included a random effect of lab and fixed effects for milk protein and milk fat. Regression results indicate MIR analysis over-predicts MUN at low MUN concentrations and under predicts MUN at high MUN concentrations. Results suggest MIR analysis of MUN is more accurate around milk MUN, protein, and fat concentrations of ~13 mg/dl, 3.4% protein, and 4.2% fat. Further, the combined residual error and random effect of lab suggest the standard error of an MUN MIR measurement is ±1.8.

scholarly journals Goats Given Transdermal Flunixin Meglumine Displayed Less Pain Behavior After Castration

2020 ◽  
Author(s):  
Amanda Lee ◽  
Meggan Graves ◽  
Andrea Lear ◽  
Sherry Cox ◽  
Marc Caldwell ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Body Position ◽  
Random Effect ◽  
Pain Behavior ◽  
Bout Duration ◽  
Flunixin Meglumine ◽  
Meat Goats ◽  
Transdermal Application

AbstractPain management should be utilized with castration to reduce physiological and behavioral changes. Transdermal application of drugs require less animal management and fewer labor risks, which can occur with oral administration or injections. The objective was to determine the effects of transdermal flunixin meglumine on meat goats’ behavior post-castration. Male goats (N = 18; mean body weight ± standard deviation: 26.4 ± 1.6 kg) were housed individually in pens and randomly assigned to 1 of 3 treatments: (1) castrated, dosed with transdermal flunixin meglumine; (2) castrated, dosed with transdermal placebo; and (3) sham castrated, dosed with transdermal flunixin meglumine. Body position, rumination, and head- pressing were observed for 1 h ± 10 minutes twice daily on days −1, 0, 1, 2, and 5 around castration. Each goat was observed once every 5-minutes (scan samples) and reported as percentage of observations. Accelerometers were used to measure standing, lying, and laterality (total time, bouts, and bout duration). A linear mixed model was conducted using GLIMMIX. Fixed effects of treatment, day relative to castration, and treatment*day relative to castration and random effect of date and goat nested within treatment were included. Treatment 1 goats (32.7 ± 2.8%) and treatment 2 goats (32.5 ± 2.8%) ruminated less than treatment 3 goats (47.4 ± 2.8%, P = 0.0012). Head pressing was greater on day of castration in treatment 2 goats (P < 0.001). Standing bout duration was greatest in treatment 2 goats on day 1 post-castration (P < 0.001). Lying bout duration was greatest in treatment 2 goats on day 1 post-castration compared to treatment 1 and treatment 3 goats(P < 0.001). Transdermal flunixin meglumine improved goats’ fluidity of movement post-castration and decreased head pressing, indicating a mitigation of pain behavior.

Misspecification of the random effect structure: Implications for the linear mixed model

2020 ◽  
Author(s):  
Brandon LeBeau
Keyword(s):  
Fixed Effects ◽  
Serial Correlation ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Type I Error ◽  
Random Effect ◽  
Correlated Data ◽  
Unbiased Estimation ◽  
Type I ◽  
Nested Data

<p>The linear mixed model is a commonly used model for longitudinal or nested data due to its ability to account for the dependency of nested data. Researchers typically rely on the random effects to adequately account for the dependency due to correlated data, however serial correlation can also be used. If the random effect structure is misspecified (perhaps due to convergence problems), can the addition of serial correlation overcome this misspecification and allow for unbiased estimation and accurate inferences? This study explored this question with a simulation. Simulation results show that the fixed effects are unbiased, however inflation of the empirical type I error rate occurs when a random effect is missing from the model. Implications for applied researchers are discussed.</p>

scholarly journals Exercise-induced hypoalgesia in women with varying levels of menstrual pain

2018 ◽  
Vol 18 (2) ◽  
pp. 303-310 ◽  
Author(s):  
Mervyn Travers ◽  
Penny Moss ◽  
William Gibson ◽  
Dana Hince ◽  
Sheree Yorke ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Activity Levels ◽  
Menstrual Pain ◽  
Isometric Handgrip ◽  
Pressure Pain Thresholds ◽  
Significant Difference ◽  
Exercise Induced

Abstract Background and aims: Exercise-induced hypoalgesia (EIH) is a well-established phenomenon in pain-free individuals that describes a decrease in pain sensitivity after an acute bout of exercise. The EIH response has been demonstrated to be sub-optimal in the presence of persisting pain. Menstrual pain is a common recurrent painful problem with many women experiencing high levels of pain each cycle. However, the EIH response has not been examined in a cohort of women with high levels of menstrual pain. This research aimed to examine whether EIH manifests differently in women with varying levels of menstrual pain. The primary hypothesis was that women with high levels of menstrual pain would demonstrate compromised EIH. Secondary aims were to explore relationships between EIH and emotional state, sleep quality, body mass index (BMI) or physical activity levels. Methods: Pressure pain thresholds (PPT) were measured in 64 participants using a digital handheld algometer before and after a submaximal isometric-handgrip exercise. EIH index was compared between low (VAS 0–3), moderate (VAS 4–7) and high (VAS 8–10) pain groups, using a linear mixed model analysis with participant as a random effect, and site, menstrual pain category and the interaction between the two, as fixed effects. Results: EIH was consistently induced in all groups. However, there was no statistically significant difference between the pain groups for EIH index (p=0.835) or for any co-variates (p>0.05). Conclusions: EIH was not found to differ between women who report regular low, moderate or high levels of menstrual pain, when measured at a point in their menstrual cycle when they are pain free. Implications: This study provides insight that EIH does not vary in women with differing levels of menstrual pain when they are not currently experiencing pain. The current findings indicate that, although menstrual pain can involve regular episodes of high pain levels, it may not be associated with the same central nervous system dysfunctions as seen in sustained chronic pain conditions.

scholarly journals Detection of Methane Eructation Peaks in Dairy Cows at a Robotic Milking Station Using Signal Processing

Animals ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Ali Hardan ◽  
Philip C. Garnsworthy ◽  
Matt J. Bell
Keyword(s):  
Signal Processing ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Air Sampling ◽  
Analysis Software ◽  
Sampling Volume ◽  
Ch4 Concentration ◽  
Robotic Milking

The aim of this study was to investigate the use of signal processing to detect eructation peaks in CH4 released by cows during robotic milking, and to compare recordings from three gas analysers (Guardian SP and NG, and IRMAX) differing in volume of air sampled and response time. To allow comparison of gas analysers using the signal processing approach, CH4 in air (parts per million) was measured by each analyser at the same time and continuously every second from the feed bin of a robotic milking station. Peak analysis software was used to extract maximum CH4 amplitude (ppm) from the concentration signal during each milking. A total of 5512 CH4 spot measurements were recorded from 65 cows during three consecutive sampling periods. Data were analysed with a linear mixed model including analyser × period, parity, and days in milk as fixed effects, and cow ID as a random effect. In period one, air sampling volume and recorded CH4 concentration were the same for all analysers. In periods two and three, air sampling volume was increased for IRMAX, resulting in higher CH4 concentrations recorded by IRMAX and lower concentrations recorded by Guardian SP (p < 0.001), particularly in period three, but no change in average concentrations measured by Guardian NG across periods. Measurements by Guardian SP and IRMAX had the highest correlation; Guardian SP and NG produced similar repeatability and detected more variation among cows compared with IRMAX. The findings show that signal processing can provide a reliable and accurate means to detect CH4 eructations from animals when using different gas analysers.

scholarly journals 163 Annual differences in fecal egg counts in a forage-based ram test

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 172-172
Author(s):  
Morgan Van Davelaar ◽  
David R Notter ◽  
D Lee Wright ◽  
Anna M Zajac ◽  
Scott P Greiner ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Negative Binomial ◽  
Random Effect ◽  
Summer Precipitation ◽  
Parasite Load ◽  
Least Square ◽  
Birth Type ◽  
Normally Distributed

Abstract The objective was to determine the magnitude of yearly differences in parasite load in growing ram lambs. Data were obtained from the Southwest Virginia Agriculture Research and Extension Center in Glade Spring, VA. The center conducts a forage-based ram growth test during the summer where rams also undergo a parasite challenge. Data consisted of 488 Katahdin rams tested from 2012 to 2018. Rams were dewormed at delivery, and at the start of the test, each ram received an oral dose of 5,000 H. contortus larvae adjusted for body weight. Fecal egg count was measured 70 d later when rams were on average (SD) 200 (18) d old. Fecal egg counts were not normally distributed. The Box-Cox procedure indicated that a log transformation was appropriate, but the residuals were not normally distributed for several linear models. A zero-inflated negative binomial generalized linear mixed model was used for data analysis with the glmmTMB package in R. The model included fixed effects of centered and scaled weight, centered and scaled age, year, birth type, and rearing type, and the random effect of consignor. Birth type, rear type, and age were not significant (P &gt; 0.10). The least square mean (SE) fecal egg counts by year were 344 (118) for 2012, 623 (214) for 2013, 574 (195) for 2014, 1,125 (409) for 2015, 745 (253) for 2016, 408 (142) for 2017, and 239 (86) for 2018. Differences in summer precipitation could affect average parasite load. Despite similar total summer precipitation, 2012 had 1 extremely wet month whereas, 2015 had consistent precipitation throughout the summer. We conclude that producers should not compare fecal egg counts across years because the overall average may be multiple-fold different from year to year. Ranking rams within year will be more effective to select for improved parasite resistance.

scholarly journals Analysis of Fluid Velocity inside an Agricultural Sprayer Using Generalized Linear Mixed Models

2020 ◽  
Vol 10 (15) ◽  
pp. 5029
Author(s):  
Ángel Javier Aguirre ◽  
Guillermo E. Guevara-Viera ◽  
Carlos S. Torres-Inga ◽  
Raúl V. Guevara-Viera ◽  
Antonio Boné ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Goodness Of Fit ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Fluid Velocity ◽  
Random Effect ◽  
Information Criteria ◽  
Liquid Level ◽  
Residual Variance ◽  
Operational Parameters

The fluid velocity inside the tank of agricultural sprayers is an indicator of the quality of the mixture. This study aims to formulate the best generalized linear mixed model to infer the fluid velocity inside a tank under specific operational parameters of the agitation system, such as liquid level, circuit pressures, and number of active nozzles. A complex model was developed that included operational parameters as fixed effects (FE) and the section of the tank as the random effect. The goodness of fit of the model was evaluated by considering the lowest values of Akaike’s information criteria and Bayesian information criterion, and by estimating the residual variance. The gamma distribution and log-link function enhanced the goodness of fit of the best model. The Toeplitz structure was chosen as the structure of the covariance matrix. SPSS and SAS software were used to compute the model. The analysis showed that the greatest influence on the fluid velocity was exerted by the liquid level in the tank, followed by the circuit pressure and, finally, the number of active nozzles. The development presented here could serve as a guide for formulating models to evaluate the efficiency of the agitation system of agricultural sprayers.

scholarly journals PSVI-38 Impact of PRRSV infection during gestation on the protein levels in the blood of piglets

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 200-200
Author(s):  
Haley E Rymut ◽  
Courtni R Sizemore ◽  
Laurie A Rund ◽  
Alexandra K Houser ◽  
Rodney W Johnson ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Organ Damage ◽  
Respiratory Syndrome Virus ◽  
Serum Concentrations ◽  
Weaned Piglets ◽  
Swine Industry ◽  
Protein Levels

Abstract Costs and productivity losses associated with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks impact the swine industry. The objective of this study was to evaluate the effect of maternal immune activation (MIA) from a PRRSV challenge during gestation on the piglet serum concentrations of albumin and globulin, indicators of inflammation or organ damage. Eighteen pregnant Camborough gilts were inoculated with either PRRSV or saline on gestational day 76. After farrowing 106 piglets remained with the gilts until postnatal day (PD) 21. One group of piglets was weaned and group-housed while another group remained with the gilts until PD22. At PD 60, a group of weaned piglets was fasted for one day while the rest was fed to meet nutritional requirements. Serum concentrations of globulin and albumin were measured on PD 22 and 61 and were analyzed using a linear mixed model including the fixed effects of gilt challenge, piglet treatment and sex and the random effect of gilt. On PD 22, albumin was higher in weaned relative to suckled piglets from saline-treated gilts (P &lt; 0.0305). Globulin was higher in weaned relative to suckled piglets (P &lt; 0.0014) and in piglets from PRRSV-treated relative to saline-treated gilts (P &lt; 0.0201). The albumin/globulin ratio was higher in weaned piglets from saline relative to PRRSV-treated gilts (P &lt; 0.0367). On PD 61, albumin was higher in fasted relative to fed piglets (P &lt; 0.0072). Globulin was higher in males relative to females from PRRSV-treated gilts (P &lt; 0.0326), and the albumin/globulin ratio was higher in fasted relative to fed piglets (P &lt; 0.0043). Our results indicate a positive correlation between serum protein concentrations and MIA, weaning or fasting stress that may be indicative of inflammation, organ dysfunction or nutritional imbalance. This study is supported by USDA NIFA AFRI, grant number 2018-67015-27413.

Milking efficiency of swingover herringbone parlours in pasture-based dairy systems

2013 ◽  
Vol 80 (4) ◽  
pp. 467-474 ◽  
Author(s):  
J Paul Edwards ◽  
Bernadette O'Brien ◽  
Nicolas Lopez-Villalobos ◽  
Jenny G Jago
Keyword(s):  
Mathematical Model ◽  
Fixed Effects ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Random Effect ◽  
Herd Size ◽  
Similar Data ◽  
Herd Management ◽  
Management Software ◽  
Harvesting Efficiency

The objective of this study was to collect and analyse milking data from a sample of commercial farms with swingover herringbone parlours to evaluate milking efficiency over a range of parlour sizes (12–32 milking units). Data were collected from 19 farms around the Republic of Ireland equipped with electronic milk metres and herd management software that recorded data at individual milking sessions. The herd management software on each farm was programmed to record similar data for each milking plant type. Variables recorded included cow identification, milking date, identification time, cluster-attachment time, cluster/unit number, milk yield, milking duration, and average milk flow rate. Calculations were performed to identify efficiency benchmarks such as cow throughput (cows milked per h), milk harvesting efficiency (kg of milk harvested per h) and operator efficiency (cows milked per operator per h). Additionally, the work routine was investigated and used to explain differences in the benchmark values. Data were analysed using a linear mixed model that included the fixed effects of season-session (e.g. spring-AM), parlour size and their interaction, and the random effect of farm. Additionally, a mathematical model was developed to illustrate the potential efficiency gains that could be achieved by implementing a maximum milking time (i.e. removing the clusters at a pre-set time regardless of whether the cow had finished milking or not). Cow throughput and milk harvesting efficiency increased with increasing parlour size (12 to 32 units), with throughput ranging from 42 to 129 cows/h and milk harvesting efficiency from 497 to 1430 kg/h (1–2 operators). Greater throughput in larger parlours was associated with a decrease in operator idle time. Operator efficiency was variable across farms and probably dependent on milking routines in use. Both of these require consideration when sizing parlours so high levels of operator efficiency as well as cow throughput can be achieved simultaneously. The mathematical model indicated that application of a maximum milking time within the milking process could improve cow throughput (66% increase in an 18-unit parlour when truncating the milking time of 20% of cows). This could allow current herd milking durations to be maintained as herd size increases.

scholarly journals Milk Urea Concentration to the Evaluation of Nitrogen Efficiency Transformation on Dairy Farms

2021 ◽  
Vol 65 (3) ◽  
pp. 30-39
Author(s):  
I. Maskaľová ◽  
V. Vajda
Keyword(s):  
Multiple Regression ◽  
Nitrogen Concentration ◽  
Nutrient Content ◽  
Nitrogen Efficiency ◽  
Regression Equations ◽  
Urea Nitrogen ◽  
Regression Relationship ◽  
Milk Urea ◽  
Nutritional Effects ◽  
Milk Urea Nitrogen

Abstract The aim of this study was to evaluate the effects of nutrition on the milk urea nitrogen (MUN) concentration; on the transformation of N in the farm’s conditions; and there-by allow the milk urea nitrogen concentration to serve as a tool to maximize the protein nutrition and the metabolism of the cows. The relations evaluated by linear or multiple regression confirmed that the highest nutritional effects of the crude protein (CP) on the MUN concentration, which represented a 69.3 % variation in the MUN content. According to the CP content in the total mix ration (TMR) and MUN content (3150 milk samples) under farm conditions, a regression relationship was determined for the estimated of MUN (mg.dl–1) = –13.2 + 0.16 × CP (g.kg–1 dry matter). For multiple regression, the rate of variation expressed by this relationship increased to 72 for nutrient content and 78.3 % for nutrient intake in the TMR. The efficiency of nitrogen utilization (ENU) determined by calculations based on the MUN content according to the regression equations represented a negative correlation (P < 0.0001; R2 = 0.854) with respect to the CP content in the TMR and that the increased CP content by 1 % in the range of 14 to 18 % in the TMR decreased the ENU by 1.48 %. Validation of the models for prediction of nitrogen transformation (ENU) for practical application on the farms determined the best equation, which used the available data from the routine analysis of Breeding services of Slovakia. After taking into consideration of our breeding conditions, it was confirmed that the equation of ENU had taken into account the MUN, in addition to the amount of the milk produced.

scholarly journals Effects of herd, season and days in milk on milk urea nitrogen of crossbred dairy cows in Sylhet

2015 ◽  
Vol 2 (2) ◽  
pp. 287-292
Author(s):  
Nusrat Zahan Shoshe ◽  
Md Abdul Baset ◽  
Md Tariqul Islam ◽  
Shiekh MA Matin ◽  
Md Abdullah Al Mahmud
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Milk Fat ◽  
Wet Season ◽  
Urea Nitrogen ◽  
Lactation Stage ◽  
Milk Urea ◽  
Daily Milk Yield ◽  
Daily Milk ◽  
Milk Urea Nitrogen

The study included 724 crossbred cows (Local × Holstein Friesian) from 9 dairy farms of Sylhet district from July 2013 to June 2014 to determine the effect of herd, season, and days in milk in milk urea nitrogen and the effect of milk production and composition on milk urea nitrogen. According to the season, milk samples were divided into two groups: wet season (June - October) and dry season (November - February). Days in milk (DIM) were grouped into two lactation stages: Lactation 1 (?100 days in milk) and Lactation 2 (?100 days in milk). Milk urea nitrogen was grouped into five categories by increments of 5 mg/dl, started with those less than 10 mg/dl and finishing with concentration greater than 25 mg/dl. The daily milk yield was 6.78 kg ranged from 2.00 to 18.00 kg. The mean of milk urea nitrogen (MUN) concentration was 14.58 mg/dl. Mean values for milk fat and protein contents were 3.74 % and 3.72 %. Among the 9 herds, the highest content of milk urea (MU) was 16.37 mg/dl which was found in herd 2 and the second highest estimation of MU content were in herd 1, 3, 6 and 9 (15.58, 15.51, 15.12 and 14.45 mg/dl, respectively). In the district of Sylhet, the lowest MU content was estimated in herd 4, 5, 7 and 8 (13.59, 13.48, 13.16 and 13.60 mg/dl, respectively). Difference of MUN concentration was not significant between the dry and wet season. The MUN concentrations were 14.82 mg/dl and 14.90 mg/dl in dry and wet season respectively. The concentration of MUN in Lactation 1 was 13.61 mg/dl and in Lactation 2 was 16.26 mg/dl. Milk fat (%) were 3.56, 3.77, 3.64, 4.15 and 3.66 when MUN concentration were ?10.00, 10.01- 15.00, 15.01-20.00, 20.01-25.00 and ?24.01 mg/dl respectively. Daily milk yield did not increase with the increase of MUN concentration. Milk yield were 6.37, 7.21, 6.23, 7.31 and 7.00 Kg/d while MUN concentration were ?10.00, 10.01-15.00, 15.01-20.00, 20.01-25.00 and ?25.01 mg/dl. It may be concluded that herd category and lactation stage influence the milk urea nitrogen concentration of crossbred dairy cows in the Sylhet district.Res. Agric., Livest. Fish.2(2): 287-292, August 2015

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