Individual Cow Characteristics Research Articles

Effect of oxytocin use during colostrum harvest and association of cow characteristics with colostrum yield and IgG concentration in Holstein dairy cows

Our objectives were to determine the effect of oxytocin use during colostrum harvest on colostrum yield (CY) and IgG concentration in Holstein dairy cows on a commercial dairy in New York and to describe associations of cow characteristics with these outcomes. Animals were enrolled between July and October 2023 using a randomized block design, with day of enrollment as the unit of randomization. A median (range) of 10 (3 to 19) cows were enrolled/d. Treatments were 1) 40 IU Oxytocin (OXY40), 2) 20 IU Oxytocin (OXY20), and 3) an untreated control group (CNTR). Oxytocin was administered intramuscularly (IM) approximately 45 s before unit attachment in a rotary parlor. Colostrum weight was measured using the colostrum bucket-embedded scale or a platform scale when the yield was less than the smallest bucket scale. The concentration of IgG ([IgG]) in colostrum was determined using radial immunodiffusion (RID) and used to calculate total IgG, and dry matter (%) was determined by oven drying. Individual cow characteristics such as parity, calf sex, weight, dystocia score, stillbirth, milk production in wk 4 of lactation, and for multiparous cows, dry period length, previous lactation dry off linear score (LS) were collected. Data were analyzed separately for primiparous and multiparous cows using backward stepwise elimination to produce final mixed effects ANOVA models Primiparous cows (n = 201) were randomized to 35.8% (n = 72) OXY40, 32.8% (n = 66) OXY20, and 31.3% (n = 63) CNTR. Multiparous groups (n = 435) were randomized to 34.7% (n = 151) OXY40, 29.7% (n = 129) OXY20, and 35.6% (n = 155) CNTR. The median (range) CY was 6.0 (0 to 20.6) kg and [IgG] was 98.5 (0.1 to 293.6) g/L in the study population. In primiparous cows, OXY40 had a higher colostrum yield (LSM [95% CI]) of 5.4 (4.9 to 5.9) kg compared with both OXY20 (4.1 [3.5 to 4.7] kg) and CNTR (3.8 [3.3 to 4.3] kg) (P < 0.001). In multiparous cows, OXY40, OXY20, and CTNR did not differ in CY (5.9 [5.3 to 6.5], 5.7 [6.3 to 5.1], and 5.4 [6.0 to 4.8] kg, respectively, P = 0.43), but colostrum yield was greater in parity 2 compared with all other parities, cows giving birth to male calves, cows with the highest milk production at wk 4 of lactation, and with a dry period of >65 d. Oxytocin use did not affect [IgG] in either primiparous or multiparous cows (P > 0.56), but [IgG] was highest in cows in parity ≥4 and lowest in cows dry >65 d. In summary, oxytocin use at 40 IU IM in primiparous was associated with a higher CY but not [IgG]. Oxytocin use likely addressed disturbed milk ejection and therefore increased CY in heifers milked for the first time in a rotary parlor. This study confirms cow characteristics associated with colostrum production within a single herd.

Review and analysis on fertility and milk production in commercial dairy farms with customized lactation length during the last ten years

Approximately 150 million households around the globe are engaged in milk production. In most developing countries, milk is produced by smallholders, and milk production contributes to household livelihoods, food security and nutrition. Milk provides relatively quick returns for small-scale producers and is an important source of cash income. In recent decades, developing countries have increased their share in global dairy production. This growth is mostly the result of an increase in numbers of producing animals rather than a rise in productivity per head. In many developing countries, dairy productivity is constrained by poor-quality feed resources, diseases, limited access to markets and services (e.g., health, credit and training) and dairy animals’ low genetic potential for milk production. Unlike developed countries, many developing countries have hot and/or humid climates that are unfavourable for dairying. Traditionally, dairy farmers are recommended to aim for a 1-yr calving interval, as this would maximize milk production and income. Longer calving intervals would extend the period in late lactation, when milk production is lower. However, there may be several reasons to re-evaluate the traditional lactation length, including increased productivity of modern dairy cows, and potential benefits of longer lactations for cow health and welfare. Moreover, although farmers are advised to aim for a 1-yr calving interval, in practice calving intervals mostly exceed 1 yr. Some cows might be better suited for an extended CInt than others, due to differences in milk yield level, lactation persistency, or health status, which would justify a customized CInt based on individual cow characteristics. This study aims to investigate 13 farms with customized CInt, with respect to calving to first service interval (CFSI), accomplished CInt, services per conception (SC), conception rate at first artificial insemination (CR1AI), peak yield, lactation persistency, 305-d yield, and effective lactation yield. In total, 4,858 complete lactations of Holstein Friesian cows between 2012 and 2022 from the 13 farms were grouped by parity and CFSI or CInt.

Fusion of udder temperature and size features for the automatic detection of dairy cow mastitis using deep learning

Mastitis seriously reduces the welfare and milk yield of dairy cows and affects the economic value of farms. Most dairy cow mastitis detection algorithms based on computer vision used the threshold classification method to detect mastitis only according to the temperature feature of cows’ udders, and the results were easily affected by the farm environment and individual cow characteristics. In this work, an automatic detection method for dairy cow mastitis using the fusion of udder temperature and size features based on deep learning was proposed. First, you only look once version 7 (YOLOv7) network was used to automatically detect the eye and udder regions of dairy cows, extract the corresponding temperatures, and construct an udder temperature feature vector. Then, the CenterNet network was used to automatically detect the keypoints of the udder region, calculate its corresponding size, and construct an udder size feature vector. Finally, both the temperature and size features of udders were fused, and the support vector machine (SVM) algorithm based on the wrapper was used to automatically detect the degree of mastitis. Thermal infrared videos of 196 dairy cows were used as the dataset for evaluating the performance of the proposed method, and the accuracy of the proposed method was 88.61%. The sensitivity and specificity values of the model for clinical mastitis (CM) were 87.50% and 94.03%, respectively, those for subclinical mastitis (SCM) were 81.25% and 91.94%, respectively. The proposed method constitutes a promising approach for automatic diagnosis in the early stages of dairy cow mastitis, and it can be used for objective monitoring and optimal management of commercial farms.

Individual cow characteristics influence adaptation to an automatic milking system in dairy cows

Individual cow characteristics influence adaptation to an automatic milking system in dairy cows

Effect of voluntary waiting period on metabolism of dairy cows during different phases of the lactation.

An extended calving interval (CInt) by extending the voluntary waiting period (VWP) could be associated with altered metabolism in dairy cows. The aim of this study was first to evaluate the effects of VWP on metabolism and body condition during the first 305 d after the first calving in the experiment (calving 1), around the end of the VWP, and during pregnancy (280 d before calving 2). Second, the effects of the VWP on metabolism were determined from 2 wk before until 6 wk after calving 2. Third, individual cow characteristics were used to predict milk production and body condition of cows after different VWP. Holstein-Friesian cows (N = 154, 41 primiparous [PP], 113 multiparous [MP]) were blocked for parity, milk production, and lactation persistency, randomly assigned to a VWP of 50, 125, or 200 d (VWP50, VWP125, or VWP200) and followed from calving 1 until 6 wk after calving 2. In the first 6 wk after calving 1 and from 2 wk before until 6 wk after calving 2, weekly plasma samples were analyzed for nonesterified fatty acids (NEFA), β-hydroxybutyrate, glucose, insulin, and insulin-like growth factor 1 (IGF-1). From wk 7 after calving 1 until 2 wk before calving 2, insulin and IGF-1 were analyzed every 2 wk. Fat- and protein-corrected milk (FPCM) and body weight (BW) gain were measured weekly. Cows were divided in two parity classes based on calving 1 (PP and MP) and remained in these classes after calving 2. During pregnancy, MP cows in VWP200 had greater plasma insulin and IGF-1 concentration and lower FPCM compared with MP cows in VWP125 (insulin: 18.5 vs. 13.9 µU/mL, CI 13.0-19.7, P < 0.01; IGF-1: 198.5 vs. 175.3 ng/mL ± 5.3, P = 0.04; FPCM: 22.6 vs. 30.0 kg/d ± 0.8, P < 0.01) or VWP50 (insulin: 15.8 µU/mL, P < 0.01; IGF-1: 178.2 ng/mL, P < 0.01; FPCM: 26.6 kg/d, P < 0.01) and had a greater daily BW gain compared with cows in VWP50 (3.6 vs. 2.5 kg/d ± 0.2; P < 0.01). After calving 2, MP cows in VWP200 had greater plasma NEFA concentration (0.41 mmol/liter) compared with MP cows in VWP125 (0.30 mmol/liter, P = 0.04) or VWP50 (0.26 mmol/liter, P < 0.01). For PP cows, the VWP did not affect FPCM or body condition during the first lactation in the experiment, or metabolism after calving 2. Independent of the VWP, higher milk production and lower body condition before insemination were associated with higher milk production and lower body condition at the end of the lactation. Variation in these characteristics among cows could call for an individual approach for an extended VWP.

Extending lactation length: consequences for cow, calf, and farmer.

Traditionally, a 1-yr calving interval is advised to farmers from an economical point of view, to realize a yearly peak in milk yield. A 1-yr calving interval, however, implies a yearly event of drying-off, calving and start of lactation, which are all associated with an increased risk for diseases and disorders. Deliberately extending the lactation length by extending the voluntary waiting period (VWP) for first insemination reduces the frequency of these challenging events. This reduction in frequency of calvings can be beneficial for cow health and fertility, but also can be of interest to reduce the number of surplus calves and labor associated with drying off, calving, and disease treatments. Current concerns with respect to an extended lactation are that milk yield is too low in late lactation, which might be associated with an increased risk of fattening of cows in late lactation, and compromised economic returns at herd level. In addition, limited knowledge is available with respect to consequences for cow performance in the subsequent lactation and for calves born to cows with an extended lactation. Moreover, response of dairy cows to an extended VWP depends on individual cow characteristics like parity, milk yield level or body condition. A customized strategy based on individual cow characteristics can be a future approach to select high-producing cows with persistent lactation curves for an extended lactation to limit the risk for fattening and milk yield reduction at the end of the lactation while benefitting from a reduction in challenging events around calving.

Assessment of a non-invasive accelerometer for detecting cattle urination and defecation events

Nitrogen (N) excreted in the urine from cattle is the primary source of N leaching loss from grazed pasture systems. The objective of this study was to use non-invasive accelerometer sensors to detect the time and duration of urination and defecation events from grazing cattle. Two accelerometer sensors were attached to cows to detect the back arching of cows during urination and defecation events. Trials were conducted under outdoor grazing conditions in autumn and summer with a total of 160 urination recorded events. Changes in tilt angle of 8–22.5 degrees were observed during most urination and defecation events. Ensemble machine learning models to predict urination and defecation events were developed based on 18 selected features of a cow back arching event. The accelerometer urination event classifier had an F1 statistic of 0.80 (harmonic mean of precision (0.82) and sensitivity (0.78)) and the defecation event classifier had an F1 statistic of 0.73 (based on 408 h of data obtained 9a.m. to 3p.m. from 19 cows). Models to predict urination event duration were significant but had low performance partly due to the moderate association between the duration of back arching and the duration of the urination event (R2 of 0.29 and 0.47 for the autumn and summer trials, respectively). This demonstrates the potential for non-invasive accelerometer sensors to identify the urination characteristics of individual cows and provide individual farm information that could be used as an input parameter in farm decision support tools (e.g. urine-N excretion) and farm management decisions (e.g. culling/breeding).

Effects of extended voluntary waiting period from calving until first insemination on body condition, milk yield, and lactation persistency

A 1-yr calving interval (CInt) is usually associated with maximized milk output, due to the calving-related peak in milk yield. Extending CInt could benefit cow health and production efficiency due to fewer transition periods per unit of time. Extending CInt can affect lactation performance by fewer days dry per year, delayed pregnancy effect on milk yield, and greater milk solid yield in late lactation. This study first investigated the effects of 3 different voluntary waiting periods (VWP) from calving until first insemination on body weight, body condition, milk yield, and lactation persistency. Second, individual cow characteristics in early lactation were identified that contributed to milk yield and persistency of cows with different VWP. Holstein-Friesian dairy cows (n = 154) within 1 herd were blocked for parity, calving season, and expected milk yield. Cows were randomly assigned within the blocks to 1 of 3 VWP (50, 125, or 200 d: VWP50, VWP125, or VWP200, respectively) and monitored through 1 complete lactation and the first 6 wk of the subsequent lactation, or until culling. Minimum and mean CInt (384 vs. 452 vs. 501 d for VWP50 vs. VWP125 vs. VWP200) increased with increasing VWP, but maximum CInt was equal for the 3 VWP. Fat- and protein-corrected milk yield (FPCM) was analyzed weekly. Milk yield and FPCM were also expressed per day of CInt, to compare yields of cows with different VWP. Persistency was determined between d 100 and d 200 of the lactation, as well as between d 100 and dry-off. Values are presented as least squares means ± standard error of the mean. During the first 44 wk of lactation, VWP did not affect FPCM yield in both primiparous and multiparous cows. The VWP did not affect milk yield per day of CInt. The VWP did not affect FPCM yield per day of calving interval for primiparous cows. Multiparous cows in VWP125 had FPCM yield per day of CInt similar to that of VWP50. Multiparous cows in VWP200 had lower FPCM yield per day of CInt compared with VWP50 (27.2 vs. 30.4 kg/d). During the last 6 wk before dry-off, cows in VWP125 had lower yield compared with cows in VWP50, which could benefit their udder health in the dry period and after calving. Persistency was better for cows in VWP200 compared with cows in VWP50 (-0.05 vs. -0.07 kg/d). Body weight was not different among VWP groups. Multiparous cows in VWP200 had a higher body condition score in the last 3 mo before dry-off and the first 6 wk of the next lactation, compared with multiparous cows in VWP125 and VWP50. The VWP could be extended from 50 d to 125 d without an effect on daily yield per day of calving interval. Extending VWP until 200 d for primiparous cows did not affect their daily milk yield, but multiparous cows with a 200-d VWP had a reduced milk yield per day of calving interval and an increased body condition in late lactation and the subsequent lactation, compared with multiparous cows with a 50-d VWP.

Cow- and herd-level factors associated with lameness in dairy farms in Peninsular Malaysia

Lameness is a major welfare issue in dairy cows. This study was aimed at investigating the cow- and herd –level factors associated with lameness in dairy farms from four states in Peninsular Malaysia. The study population was 1001 lactating cows from 28 dairy farms located in Selangor (n = 9), Perak (n = 8), Negeri Sembilan (n = 6) and Johor (n = 5). Lameness was assessed by locomotion scoring. Individual cow characteristics such as breeds, parity, body condition score (BCS), hock condition, leg hygiene, presence of claw lesion and claw overgrowth were recorded. Data on herd characteristics, management practices and housing design were collected by on-farm inspection and farmers’ interview. Mixed-eff ;ects logistic regressions were used to model the data and to assess the factors associated with lameness. Cow-level lameness prevalence was 34.2 % (95 % CI 22.2–50.0 %), with all the farms having at least one case of lameness. Claw lesions were recorded in 470 cows (46.9 %; CI 33.3–63.3 %) of which 296 (62.9 %) of them were lame. Of these, 78.9 % of the lesions were present on the rear feet and 25.5% of the cows had more than one foot affected. The proportion of cows having non-infectious and infectious claw lesions were 81.9 % and 18.1 %, and the predominant claw lesions were sole ulcers (24.9 %), white line disease (19.6 %), sole haemorrhage (10.2%), swelling of coronet (9.6 %), toe ulcers (8.4 %), and digital dermatitis (5.6%). Cows at third or more parities had higher odds of lameness (OR = 2.2; 95 % CI 1.2–4.1) compared to primiparous cows. Low BCS (< 2.5) increased the odds of lameness (OR = 4.8; 95 % CI 2.9–7.9) relative to cows with moderate BCS, and cows with hair loss around the hock (OR = 1.4; 95 % CI 1.1–1.9) relative to those with normal hock condition. Greater odds of being lame was observed in cows having claw lesion (OR = 15.2; 95 % CI 10.4–19.2) and those with overgrown claw (OR = 3.3; 95 % CI 2.4–4.5). There was increased odds of lameness in farms with high stocking density (OR = 1.8; 95 % CI 1.1−3.1), concrete floored walkways (OR = 1.9; 95 % CI 1.0–3.6), dirty floors (OR = 2.3; 95 % CI 1.9–3.7), and practicing preventive claw trimming (OR = 2.3; 95 % CI 1.9–4.6). Based on the high lameness prevalence, these findings could assist dairy farmers to make informed decisions on areas to implement on-farm changes to reduce lameness in the studied herds.

Accurate detection of lameness in dairy cattle with computer vision: A new and individualized detection strategy based on the analysis of the supporting phase

Lameness has a considerable influence on the welfare and health of dairy cows. Many attempts have been made to develop automatic lameness detection systems using computer vision technology. However, these detection methods are easily affected by the characteristics of individual cows, resulting in inaccurate detection of lameness. Therefore, this study explores an individualized lameness detection method for dairy cattle based on the supporting phase using computer vision. This approach is applied to eliminate the influence of the characteristics of individual cows and to detect lame cows and lame hooves. In this paper, the correlation coefficient between lameness and the supporting phase is calculated, a lameness detection algorithm based on the supporting phase is proposed, and the accuracy of the algorithm is verified. Additionally, the reliability of this method using computer vision technology is verified based on deep learning. One hundred naturally walking cows are selected from video data for analysis. The results show that the correlation between lameness and the supporting phase was 0.864; 96% of cows were correctly classified, and 93% of lame hooves were correctly detected using the supporting phase-based lameness detection algorithm. The mean average precision is 87.0%, and the number of frames per second is 83.3 when the Receptive Field Block Net Single Shot Detector deep learning network was used to detect the locations of cow hooves in the video. The results show that the supporting phase-based lameness detection method proposed in this paper can be used for the detection and classification of cow lameness and the detection of lame hooves with high accuracy. This approach eliminates the influence of individual cow characteristics and could be integrated into an automatic detection system and widely applied for the detection of cow lameness.

Fertility and milk production on commercial dairy farms with customized lactation lengths

Drying-off, calving, and start of lactation are critical transition events for a dairy cow. As a consequence, most animal health issues occur during these periods. By extending the voluntary waiting period for first insemination after calving, calving interval (CInt) can be extended, with possible positive effects for fertility and health. Some cows might be better suited for an extended CInt than others, due to differences in milk yield level, lactation persistency, or health status, which would justify a customized CInt based on individual cow characteristics. This study aims to investigate 13 farms with customized CInt, with respect to calving to first service interval (CFSI), accomplished CInt, services per conception (SC), conception rate at first artificial insemination (CR1AI), peak yield, lactation persistency, 305-d yield, and effective lactation yield. In total, 4,858 complete lactations of Holstein Friesian cows between 2014 and 2019 from the 13 farms were grouped by parity (1 or 2+) and CFSI (CFSI class; CFSI-1 < 84; 84 ≤ CFSI-2 < 140; 140 ≤ CFSI-3 < 196; 196 ≤ CFSI-4 < 252, CFSI-5 ≥ 252 d) or CInt (CInt class; CInt-1 < 364; 364 ≤ CInt-2 < 420; 420 ≤ CInt-3 < 476; 476 ≤ CInt-4 < 532, CInt-5 ≥ 532 d). Cow inseminations, available for 11 out of 13 farms (3,597 complete lactations), were grouped by parity (1 and 2+) and CFSI class or CInt class. The fertility and milk production characteristics were analyzed with generalized and general linear mixed models. The CFSI class was not associated with SC, but extended CInt class was associated with increased SC (CInt-1-5; 1.11-3.70 SC). More than 50% of cows in the CFSI class <84 d ended up in longer than expected CInt (>364 d), showing that these cows were not able to conceive for the desired CInt. More than 50% of cows in CInt classes 3 and higher (CInt ≥ 420 d) had an earlier first insemination before successful insemination (CFSI class 1; <196 d), showing that these extended CInt classes consisted of both cows with an extended waiting period for first insemination and cows that failed to conceive at earlier insemination(s). On most farms, lactation persistency was greatest in CInt class 1 (<364 d), probably related to the low peak yield in this class. When this shortest CInt class was excluded, persistency increased with extended CInt classes on most farms. Although at the majority of farms 305-d yield was greater in CInt ≥ 532 d, effective lactation yield at most farms was greatest in CInt from 364 to 531 d, especially for multiparous cows. Based on the results of this study, a CInt between 364 and 531 days seems most optimal for milk production, when high-yielding cows were selected.

Persistence of sociality in group dynamics of dairy cattle

In many species, animals live in highly structured groups. In these groups, individual differences in the number and identity of social contacts (alters) of each ego define the social network structure of the animal group. The composition of groups can be disturbed by grouping animals according to age or production stage, which can in turn induce stress. We investigated whether the preference of two animals to stay together depends on the sociality of each individual (defined by the time it spends close to other animals) or on the composition of the group. We observed 158 dairy cows distributed in 6 pens during 17 weeks. The precise positions of the cows were monitored with positional loggers 24/7 in two groups with fixed independent populations and during the formation of new groups with varying population. In fixed groups, the sociality of a cow was maintained over the entire observation period, but this trait depended on the area contacts occurred (inside vs. outside the resting area). When introducing foreign individuals into social groups, the sociality of individual cows was maintained independently of the group; this sociality was therefore not necessarily influenced by the time spent in the group but by the social characteristics of individual cows. During the formation of new groups, newly introduced cows dynamically interacted with resident ones, forming a few strong short-lasting contacts between newcomers and resident cows. However, a few long-lasting interactions occurred between resident and newcomers and the whole network is weakened. Our study suggests that each cow has its own sociality independent of the group and tend to establish relations with specific partners when the population is fixed. In addition, when introducing cows into a group, the social network of the group is weakened, with absence of strong links between newcomers and resident cows and a decrease in the links between resident cows for at least 2 weeks.

Validation of a mathematical model of the bovine estrous cycle for cows with different estrous cycle characteristics

A recently developed mechanistic mathematical model of the bovine estrous cycle was parameterized to fit empirical data sets collected during one estrous cycle of 31 individual cows, with the main objective to further validate the model. The a priori criteria for validation were (1) the resulting model can simulate the measured data correctly (i.e. goodness of fit), and (2) this is achieved without needing extreme, probably non-physiological parameter values. We used a least squares optimization procedure to identify parameter configurations for the mathematical model to fit the empirical in vivo measurements of follicle and corpus luteum sizes, and the plasma concentrations of progesterone, estradiol, FSH and LH for each cow. The model was capable of accommodating normal variation in estrous cycle characteristics of individual cows. With the parameter sets estimated for the individual cows, the model behavior changed for 21 cows, with improved fit of the simulated output curves for 18 of these 21 cows. Moreover, the number of follicular waves was predicted correctly for 18 of the 25 two-wave and three-wave cows, without extreme parameter value changes. Estimation of specific parameters confirmed results of previous model simulations indicating that parameters involved in luteolytic signaling are very important for regulation of general estrous cycle characteristics, and are likely responsible for differences in estrous cycle characteristics between cows.

Effect of dry period length on milk yield over multiple lactations

Shortening or omitting the dry period (DP) can improve the energy balance of dairy cows in early lactation through a decrease in milk yield after calving. Little is known about the effect of a short or no DP on milk yield over multiple lactations. Our objectives were (1) to assess the effect of DP length over multiple lactations on milk yield, and (2) to assess if the prediction of milk yield in response to DP length could be improved by including individual cow characteristics before calving. Lactation data (2007 to 2015) of 16 Dutch dairy farms that apply no or short DP were used to compute cumulative milk yield in the 60 d before calving (additional yield) and in the 305 d after calving (305-d yield), and the mean daily yield over the interval from 60 d before calving to 60 d before next calving (effective lactation yield). The DP categories were no (0 to 2 wk), short (3 to 5wk), standard (6 to 8 wk), and long (9 to 12 wk). The effect of current DP and previous DP on yields was analyzed with mixed models (n=1,420 lactations). The highest effective lactation yield of fat- and protein-corrected milk (FPCM) was observed for cows with a standard current DP (27.6kg per day); a daily decrease was observed of 0.6kg for a long DP, 1.0kg for a short DP, and 2.0kg for no DP. Previous DP did not significantly affect the effective lactation yield. Thus, cows can be managed with short or no DP over consecutive lactations without a change in quantity of milk losses. Cows that received no DP for consecutive lactations had a lower additional yield before calving (−172kg of FPCM), but a higher 305-d yield (+560kg of FPCM), compared with cows that received no DP for the first time. This could lessen the improvement of the energy balance in early lactation when no DP is applied a second time compared with the first time. For the second objective, a basic model was explored to predict effective lactation yield based on parity, DP length, and first-parity 305-d yield (n=2,866 lactations). The basic model was subsequently extended with data about recent yield, days open, and somatic cell count. Extending the model reduced the error of individual predictions by only 6%. Therefore, the basic model seems sufficient to predict the effect of DP length on effective lactation yield. Other individual cow characteristics can still be relevant, however, to make a practical and tailored decision about DP length.

Effects of dairy system, herd within dairy system, and individual cow characteristics on the volatile organic compound profile of ripened model cheeses

The objective of this work was to study the effect of dairy system, herd within dairy system, and characteristics of individual cows (parity, days in milk, and daily milk yield) on the volatile organic compound profile of model cheeses produced under controlled conditions from the milk of individual cows of the Brown Swiss breed. One hundred fifty model cheeses were selected from 1,272 produced for a wider study of the phenotypic and genetic variability of Brown Swiss cows. In our study, we selected 30 herds representing 5 different dairy systems. The cows sampled presented different milk yields (12.3–43.2kg/d), stages of lactation (10–412 d in milk), and parity (1–7). In total, 55 volatile compounds were detected by solid-phase microextraction and gas chromatography-mass spectrometry, including 14 alcohols, 13 esters, 11 free fatty acids, 8 ketones, 4 aldehydes, 3 lactones, 1 terpene, and 1 pyrazine. The most important sources of variation in the volatile organic profiles of model cheeses were dairy system (18 compounds) and days in milk (10 compounds), followed by parity (3 compounds) and milk yield (5 compounds). The model cheeses produced from the milk of tied cows reared on traditional farms had lower quantities of 3-methyl-butan-1-ol, 6-pentyloxan-2-one, 2-phenylethanol, and dihydrofuran-2(3H)-one compared with those reared in freestalls on modern farms. Of these, milk from farms using total mixed rations had higher contents of alcohols (hexan-1-ol, octan-1-ol) and esters (ethyl butanoate, ethyl pentanoate, ethyl hexanoate, and ethyl octanoate) and lower contents of acetic acid compared with those using separate feeds. Moreover, dairy systems that added silage to the total mixed ration produced cheeses with lower levels of volatile organic compounds, in particular alcohols (butan-1-ol, pentan-1-ol, heptan-1-ol), compared with those that did not. The amounts of butan-2-ol, butanoic acid, ethyl-2-methylpropanoate, ethyl-3-methylbutanoate, and 6-propyloxan-2-one increased linearly during lactation, whereas octan-1-ol, 3-methyl-3-buten-1-ol, 2-butoxyethanol, 6-pentyloxan-2-one, and 2,6-dimethylpyrazine showed a more complex pattern during lactation. The effect of the number of lactations (parity) was significant for octan-1-ol, butanoic acid, and heptanoic acid. Finally, concentrations of octan-1-ol, 2-phenylethanol, pentanoic acid, and heptanoic acid increased with increasing daily milk yield, whereas dihydrofuran-2(3H)-one decreased. In conclusion, the volatile organic compound profile of model cheeses from the milk of individual cows was affected by dairy farming system and stage of lactation and, to lesser extent, by parity and daily milk yield.

Variability of microbial teat skin flora in relation to farming practices and individual dairy cow characteristics

This study is the first that assessed the influence of farming practices and individual cow characteristics on a large number of microbial groups (n = 10) and cow samples (n = 192). Its aim was to establish how farming practices and intrinsic characteristics of dairy cows can influence the microbiota on teat skin. Microbial flora of 96 cow teat skin from 16 farms, sampled during milking and before washing, was counted on ten dairy-specific media. Gram-positive catalase-positive bacteria including coagulase-negative staphylococci, were at high level on teat skin (4.7 ± 1.5 log cfu.mL−1) whereas lactobacilli, enterococci, Gram-negative bacteria, moulds and yeasts were at a level below 3 log cfu.mL−1. Gram-positive catalase-positive bacteria and yeasts were lower in heifers and when milking hygiene practices were intensive. Higher Lactobacillus and Enterococcus counts were linked to a silage-based diet, free stalls with straw bedding and moderate milking hygiene but also to multiparous cows. This study showed that dairy cow characteristics could interact with farming practices to affect the counts of microbial flora on teat skin. It offered prospects to better control teat microbial balance taking into account the milking hygiene practices, the parturition and the type of animal housing.

The cost of different types of lameness in dairy cows calculated by dynamic programming

Traditionally, studies which placed a monetary value on the effect of lameness have calculated the costs at the herd level and rarely have they been specific to different types of lameness. These costs which have been calculated from former studies are not particularly useful for farmers in making economically optimal decisions depending on individual cow characteristics. The objective of this study was to calculate the cost of different types of lameness at the individual cow level and thereby identify the optimal management decision for each of three representative lameness diagnoses. This model would provide a more informed decision making process in lameness management for maximal economic profitability. We made modifications to an existing dynamic optimization and simulation model, studying the effects of various factors (incidence of lameness, milk loss, pregnancy rate and treatment cost) on the cost of different types of lameness. The average cost per case (US$) of sole ulcer, digital dermatitis and foot rot were 216.07, 132.96 and 120.70, respectively. It was recommended that 97.3% of foot rot cases, 95.5% of digital dermatitis cases and 92.3% of sole ulcer cases be treated. The main contributor to the total cost per case of sole ulcer was milk loss (38%), treatment cost for digital dermatitis (42%) and the effect of decreased fertility for foot rot (50%). This model affords versatility as it allows for parameters such as production costs, economic values and disease frequencies to be altered. Therefore, cost estimates are the direct outcome of the farm specific parameters entered into the model. Thus, this model can provide farmers economically optimal guidelines specific to their individual cows suffering from different types of lameness.

Use of Age and Milk Production Data to Improve the Ability of Enzyme-Linked Immunosorbent Assay Test Results to PredictMycobacterium Aviumssp.ParatuberculosisFecal Culture Status

Cows from 2 California dairies were tested for paratuberculosis at the end of lactation by using fecal culture and a commercially available serum enzyme-linked immunosorbent assay (ELISA) test kit. Individual cow characteristics and production variables were evaluated along with ELISA testing results as predictors of fecal culture status. In multivariable logistic regression analysis, age and a herd-standardized version of 305-day mature equivalent (305 ME) milk production were significant predictors of fecal culture status after adjusting for herd, quarter of the study year, and ELISA sample-to-positive (S/P) ratio. The area under a nonparametric receiver operating characteristic curve was significantly greater for a multivariable model that included age and the level of milk production when compared with a model without these covariates. In conclusion, consideration of cow-level covariates was useful as an aid in predicting Mycobacterium avium ssp. paratuberculosis (MAP) fecal culture status. For a given ELISA S/P ratio, older cows and those with lower 305 ME milk production relative to other cows in the herd were significantly more likely to be shedding MAP in their feces at the end of lactation.

Frequency of traumatic cow injuries in relation to housing systems in Swiss organic dairy herds.

A study was performed to estimate the extent of cow injuries as an indicator of animal welfare in organic dairy farms in Switzerland. The study was conducted during the winter feeding period of 1997/98 and was part of a larger project on animal health, nutrition and production in certified organic dairy herds in Switzerland. Potential predictors of injuries related to animal housing were quantified and relations between occurrence of injuries and nutritional status and production were evaluated. The investigation was designed as a cross-sectional study and included a representative sample of 152 farms and 1856 cows. Every farm was visited once and each cow was scored for claw-, skin- and joint-lesions and body condition. Statistical analyses were performed appropriate for a stratified and one-stage cluster sample weighted for the entire population of organic dairy farms in Switzerland. Possible individual and environmental predictors of cow injuries were analysed using multinomial logit models for ordinal outcomes. The overall frequencies of injuries were 10.4% for joint lesions, 12.8% for soft-tissue injuries and 3.6% for claw lesions. Most joint injuries (84.9%) were observed at the hock joint, 9.4% at the carpus and 3.1% at the knee joint. The analysis of the association between frequency of injuries and potential predictors revealed heterogeneous results and the risk profiles were different between the categories of injuries measured in the study. These observations support the assumption that variations in type and severity of injuries are due to specific differences of animal management, housing design and due to different characteristics of individual cows.

Modelling lactation curves of dairy cows with emphasis on individual variability

AbstractFive published equations were compared on their ability to adjust different patterns of lactation curves. The equation y(t) = a exp(b1t'2/2 + b2/t – c(l + t'/2)t') with t' = (t – 21·4)/l00 (i) was retained because of the quality of the adjustment and the absence of convergence problems when applied on individual curves. Including an effect of season (SE) and an effect of pregnancy (PE) improved the quality of individual adjustments (no. = 339). The final equation was equal to (i) + SE + PE with SE = a + b cos (2π(wc+ w - l)/52) + c sin(2n(wc+ w - 1)/52), with wc= week of the year at calving, w = week after calving and a = 0·0065, b = -1·26 and c = 0·374, and PE = a (wp–18) e-bwp, with wp= week of pregnancy and a, b fixed parameters. Individual cow characteristics were used to analyse equation (i) parameters. The predictions obtained with this equation and several predictive functions of the equation (i) parameters, which differed in the way they included or not the potential of production, were compared. With no indication of this potential, the prediction was very poor. With the initial production (mean production of the 4th, 5th and 6th days of lactation) as an estimate of this potential, 75% of the lactations had the median of absolute values of errors less than 2·95 kg/day. The results were highly improved by using the yield during the 5th week of lactation. The threshold of 2·95 was reduced to about 2 kg/day. The quality of the individual prediction was better for primiparous than for multiparous cows, and for French Friesian and Montbeliarde cows than for pure or crossbred Holstein cows. Although individual predictions were not always satisfactory, they provided excellent agreement when averaged per group (20 cows).