Mizeck G. G. Chagunda

On the use of physical activity monitoring for estrus detection in dairy cows.

Detection of estrus in dairy cattle is effectively aided by electronic activity tags or pedometers. Characterization of estrus intensity and duration is also possible from activity data. This study aimed to develop an algorithm to detect and characterize behavioral estrus from hourly recorded activity data and to apply the algorithm to activity data from an experimental herd. The herd comprised of Holstein (n=211), Jersey (n=126), and Red Dane (n=178) cattle, with virgin heifers (n=132) and lactating cows in the first 4 parities; n=895 cow-parities, with a total of 3,674 activity episodes. The algorithm was based on deviations from exponentially smoothed hourly activity counts and was used to identify onset, duration, and intensity of estrus. Learning data included 461 successful inseminations with activity records over a 2-wk period before and after the artificial insemination. Rates of estrus detection and error rate depended on the chosen threshold level. At a threshold giving 74.6% detection rate, daily error rate was 1.3%. When applied to a subset of the complete data where milk progesterone was also available, concordance of days to first activity-detected estrus with the similar trait based on progesterone was also dependent on the chosen threshold so that, with stricter thresholds, the agreement was closer. A single-trait mixed model was used to determine the effects of systematic factors on the estrus activity traits. In general, an activity episode lasted 9.24h in heifers and 8.12h in cows, with the average strength of 1.03 ln units (equivalent to a 2.8-fold increase) in both age groups. Red Danes had significantly fewer days to first episode of high activity than Holsteins and Jerseys (29.4, 33.1, and 33.9 d, respectively). However, Jerseys had significantly shorter duration and less strength of estrus than both Red Danes and Holsteins of comparable age. The random effect of cow affected days to first episode of high activity and strength as well as estrus duration. Days from calving to first episode of high activity correlated negatively with body condition scores in early lactation. The results suggest that data from activity monitors could supply valuable information about fertility traits and could thereby be helpful in management of herd fertility. To establish the complementarities or interdependence between progesterone and activity measurements, further studies with more information from different sources of measuring estrus are needed.

L-lactate dehydrogenase and N-acetyl-β-D-glucosaminidase activities in bovine milk as indicators of non-specific mastitis

Systematic factors affecting the activities of L-lactate dehydrogenase (LDH) and N-acetyl-beta-D-glucosaminidase (NAGase) and somatic cell count (SCC), the association between the activities of LDH and NAGase and SCC with respect to udder health status, and the ability of LDH and NAGase to classify cows in udder health categories for early detection of mastitis were studied. A dataset of records from 74 Danish Holstein, 76 Danish Red and 47 Jersey cows on one research farm was used. Cows were grouped into healthy and clinically mastitic. A healthy cow was defined as having no veterinary treatment and SCC<100,000 cells/ml. A clinically infected cow was one receiving veterinary treatment after showing clinical signs of mastitis and SCC >800,000 cells/ml. Breed, month of production, and days in milk significantly influenced (P<0.001) LDH activity, NAGase activity and SCC in both healthy and clinically mastitic cows. In healthy cows, LDH activity, NAGase activity and SCC started at a high level immediately after calving and decreased to low levels approximately 30-40 d post partum. All the three parameters increased due to clinical mastitis. NAGase activity had numerically higher variation in healthy cows than in clinically mastitic cows (CV=56.2% v. CV=53.5%). The relationship between LDH activity and SCC was stronger in milk from clinically mastitic than from healthy cows (r=0.76 v. r=0.48 and r=0.67 v. r=0.44 for correlation of observed values and residuals, respectively). LDH activity had higher sensitivity than NAGase activity (73-95% v. 35-77%) while specificities were in a similar range (92-99%). Further, sensitivities for LDH activity were more robust to changes in the threshold value than those for NAGase activity. Opportunities for automated, in-line real-time mastitis detection are discussed.

Low body condition predisposes cattle to lameness: An 8-year study of one dairy herd

Lameness in dairy cows is a multifactorial and progressive disease with complex interactions between risk factors contributing to its occurrence. Detailed records were obtained from one United Kingdom dairy herd over an 8-yr period. Weekly locomotion scores were used to classify cows as not lame (score 1 to 2), mildly lame (score 3) and severely lame (score 4 to 5). These outcomes were used to investigate the hypothesis that low body condition score (BCS) is associated with an increased risk of lameness in dairy cows. Mixed effect multinomial logistic regression models were used to investigate the association between prior BCS and repeat lameness events during the longitudinal period of the study. Discrete time survival models were used to explore the relationship between prior BCS and first lifetime lameness events. In total, 79,565 cow weeks at risk were obtained for 724 cows. The number of lameness events was 17,114, of which 8,799 were categorized as mildly lame and 8,315 as severely lame. The median BCS was 2.25 (range, 0.75 to 4.25) and the mean body weight (BW) and age at first calving were 619.5 kg (range, 355.6 to 956.4 kg) and 25.8 mo (range, 20.5 to 37.8 mo), respectively. Subsets of the data were used in the discrete time survival models: 333 mild and 211 severe first lifetime lameness events in heifers (first lactation cows), and 81 mild and 49 severe first lifetime lameness events in cows second lactation or greater. Low BCS 3 wk before a repeated lameness event was associated with a significantly increased risk of lameness. Cows with BCS<2 were at greatest risk of mild or severe lameness, and an increased BCS above 2 was associated with a reduced risk of mild or severe lameness. Low BCS 16 or 8 wk before a first mild or severe lifetime lameness event, respectively, also had a positive association with risk of lameness in cows second lactation or greater. This provides evidence to support targeting management toward maintaining BCS to minimize the risk of lameness. Low BW (independent of BCS) and increased age at first calving above 24 mo were also associated with increased long-term risk of repeated lameness events. Overall, the model explained 62 and 60% of the variability for mild and severe lameness, respectively, highlighting the importance of these variables as risk factors and hence where management could be targeted to significantly affect reducing the risk of lameness.

Short communication: Genetic variation in estrus activity traits

Genetic variation in estrus traits derived from hourly measurements by electronic activity tags was studied in an experimental herd of Holstein (n = 211), Jersey (n = 126), and Red Dane (n = 178) cows. Both virgin heifers (n = 132) and lactating cows in the first 4 parities (n = 895 cow parities) were used, giving a total of 3,284 high-activity episodes indicating estrus. The first estrus after calving was predicted to occur on average, at 39, 44, and 45 d in milk for Red Danes, Holsteins, and Jerseys, respectively. Genetic variance was detected for the trait days to first high activity with a heritability of 0.18 +/- 0.07. The heritability for the period of increased activity was small (0.02 to 0.08) and of similar magnitude as that for the level of activity (0.04 to 0.08). Compared with fertility traits based on artificial insemination field data, activity traits have higher heritability than traditional fertility traits, and could therefore be helpful in selection for improved fertility.

Current trends in British dairy management regimens

This paper presents a summary of results from a 2012 survey that investigated feeding and housing management regimens currently adopted by dairy farmers in Britain. Responses from 863 farms provide a snapshot of dairy industry structure and a description of the range of management systems currently in operation. Outcomes highlight a diversity of management practices, showing that 31% of farms maintained a traditional grazing system with no forage feeding indoors during the summer, whereas 38% of farmers indicated that all their milking cows received some feeding indoors during the summer. A system of housing dairy cows for 24 h/d while they are lactating was implemented by 8% of farms, whereas 1% of farms did not house their cows at any time of the year. Statistical analyses were carried out on 3 distinct groups identified from survey responses: (1) farmers who did not undertake any indoor feeding during the summer; (2) farmers who fed all their milking cows indoors during the summer; and (3) farmers who continuously housed their cows for 24h/d while lactating. Results showed a significant relationship between management type and herd size, and between management type and breed type; on average, herd sizes were larger within systems that feed indoors. No significant relationship was found between management type and farm location when classified by estimated grassland productivity. The results indicate that traditional all-summer grazing is no longer the predominant system adopted by dairy farmers and that other systems such as all-year-round indoor feeding and continuous housing are becoming more prevalent in Britain.

Genetic parameters for predicted methane production and laser methane detector measurements.

Enteric ruminant methane is the most important greenhouse gas emitted from the pastoral agricultural systems. Genetic improvement of livestock provides a cumulative and permanent impact on performance, and using high-density SNP panels can increase the speed of improvement for most traits. In this study, a data set of 1,726 dairy cows, collected since 1990, was used to calculate a predicted methane emission (PME) trait from feed and energy intake and requirements based on milk yield, live weight, feed intake, and condition score data. Repeated measurements from laser methane detector (LMD) data were also available from 57 cows. The estimated heritabilities for PME, milk yield, DMI, live weight, condition score, and LMD data were 0.13, 0.25, 0.11, 0.92, 0.38, and 0.05, respectively. There was a high genetic correlation between DMI and PME. No SNP reached the Bonferroni significance threshold for the PME traits. One SNP was within the 3 best SNP for PME at wk 10, 20, 30, and 40. Genomic prediction accuracies between dependent variable and molecular breeding value ranged between 0.26 and 0.30. These results are encouraging; however, more work is required before a PME trait can be implemented in a breeding program.

Evaluation of the laser methane detector to estimate methane emissions from ewes and steers.

The laser methane detector (LMD) has been proposed as a method to characterize enteric methane (CH4) emissions from animals in a natural environment. To validate LMD use, its CH4 outputs (LMD-CH4), were compared against CH4 measured with respiration chambers (chamber-CH4). The LMD was used to measure CH4 concentration (µL/L) in the exhaled air of 24 lactating ewes and 72 finishing steers. In ewes, LMD was used on 1 d for each ewe, for 2-min periods at 5 hourly observation periods (P1 to P5, respectively) after feeding. In steers fed either low- or high-concentrate diets, LMD was used once daily for a 4-min period for 3 d. The week after LMD-CH4 measurement, ewes or steers entered respiration chambers to quantify daily CH4 output (g/d). The LMD outputs consisted of periodic events of high CH4 concentrations superimposed on a background of oscillating lower CH4 concentrations. The high CH4 events were attributed to eructation and the lower background CH4 to respiration. After fitting a double normal distribution to the data set, a threshold of 99% of probability of the lower distribution was used to separate respiration from eructation events. The correlation between mean LMD-CH4 and chamber-CH4 was not high, and only improved correlations were observed after data were separated in 2 levels. In ewes, a model with LMD and DMI (adjusted R(2) = 0.92) improved the relationship between DMI and chamber-CH4 alone (adjusted R(2) = 0.79) and between LMD and chamber-CH4 alone (adjusted R(2) = 0.86). In both experiments, chamber-CH4 was best explained by models with length of eructation events (time) and maximum values of CH4 concentration during respiration events (µL/L; P < 0.01). Correlation between methods differed between observation periods, indicating the best results of the LMD were observed from 3 to 5 h after feeding. Given the short time and ease of use of LMD, there is potential for its commercial application and field-based studies. Although good indicators of quantity of CH4 were obtained with respiration and eructation CH4, the method needed to separate the data into high and low levels of CH4 was not simple to apply in practice. Further assessment of the LMD should be performed in relation to animal feeding behavior and physiology to validate assumptions of eructation and respiration levels, and other sources of variation should be tested (i.e., micrometeorology) to better investigate its potential application for CH4 testing in outdoor conditions.

Predisposing factors for involuntary culling in Holstein–Friesian dairy cows

The objective was to identify predisposing factors for increased risk of involuntary culling in adult Holstein-Friesian dairy cows. Data were sourced from Scotlands Rural College (SRUC) Dairy Research Centre. Between September 2003 and August 2010 175 cows were culled, a herd culling rate of 33.7%. The major reasons for involuntary culling were fertility (27.4%) and udder problems (26.9%). In the analysis, the culled cows were matched with their cohorts that survived to a later lactation. To identify predisposing factors, a binary logistic model was applied. Cows with higher than average body condition score (BCS) at last service were five times [Odds Ratio (OR) = 4.8] more likely to be culled due to infertility. Cows with low protein yield on day 60 ± 5 in lactation were ten times less likely (OR = 0.1) to be culled. In first lactation heifers, only BCS at last service increased the risk of involuntary culling due to infertility (OR = 13.0). A high milk yield acceleration was a significant (P = 0.04) factor in increasing the risk, five times (OR = 5.2) more, of culling cows due to udder problems. In conclusion, a high BCS at last service, high milk protein yield at around day 60 in lactation and acceleration of milk yield after calving exposed cows to a risk of being culled involuntarily. In practice, monitoring of traits that indicate metabolic imbalance could assist identifying cows at high risk of being culled and contribute to reducing the associated risk through a more effective timely decision.

Evaluation of the breeding strategy for milk yield of Holstein Friesian cows on large-scale dairy farms in Malawi

Over the last two decades, dairy cattle management in Malawi has been oriented towards increasing milk yield per animal. One consequence of this process has been reliance on Holstein Friesian bull semen from temperate regions. The aim of the current study was to evaluate the performance of Holstein Friesian cows on large-scale farms in Malawi. A data set of 60640 test-day records from Holstein Friesian cows in first, second and third lactation from three large-scale dairies in Malawi were utilized. Fixed effects of herd, year and season of calving were tested. (Co)variance components were estimated through the restricted maximum likelihood (REML) procedure. Heritability, genetic and phenotypic correlations for milk yield, lactation length, age at first calving, and calving interval were determined. In general, milk yield decreased over the years and there was significant (P<0.001) variation in milk yield between herds. The genetic base, as indicated by the genetic trend, remained almost constant in the studied period. This entails genotype by environment interaction, culminating in the additive genetic effect not expressing itself fully in the phenotype. It is therefore apparent that considerable improvement could be achieved by improving the production environment.

Opportunities and challenges in the use of the Laser Methane Detector to monitor enteric methane emissions from ruminants.

The objective of this review was to examine the application and relative efficiency of the proprietary hand-held Laser Methane Detector (LMD) in livestock production, with a focus on opportunities and challenges in different production systems. The LMD is based on IR absorption spectroscopy, uses a semiconductor laser as a collimated excitation source and uses the second harmonic detection of wavelength modulation spectroscopy to establish a methane (CH4) concentration measurement. The use of the LMD for CH4 detection in dairy cows is relatively recent. Although developed for entirely different purposes, the LMD provides an opportunity for non-invasive and non-contact scan sampling of enteric CH4. With the possibility for real-time CH4 measurements, the LMD offers a molecular-sensitive technique for enteric CH4 detection in ruminants. Initial studies have demonstrated a relatively strong agreement between CH4 measurements from the LMD with those recorded in the indirect open-circuit respiration calorimetric chamber (correlation coefficient, r = 0.8, P < 0.001). The LMD has also demonstrated a strong ability to detect periods of high-enteric CH4 concentration (sensitivity = 95%) and the ability to avoid misclassifying periods of low-enteric CH4 concentration (specificity = 79%). Being portable, the LMD enables spot sampling of methane in different locations and production systems. Two challenges are discussed in the present review. First is on extracting a representation of a point measurement from breath cycle concentrations. The other is on using the LMD in grazing environment. Work so far has shown the need to integrate ambient condition statistics in the flux values. Despite the challenges that have been associated with the use of the LMD, with further validation, the technique has the potential to be utilised as an alternative method in enteric CH4 measurements in ruminants.