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Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing
J. Dairy Sci. 99:1–6 http://dx.doi.org/10.3168/jds.2016-11351 © American Dairy Science Association®, 2016.
Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing Jennifer M. Chen,* Karin E. Schütz,† and Cassandra B. Tucker*1 *Department of Animal Science, University of California, Davis 95616 †AgResearch Ltd., Hamilton 3240, New Zealand
ABSTRACT
rarely resumed lying soon after standing up (0.4% of intervals between lying bouts were <30 s). However, shorter sample intervals may be needed in situations where cows more frequently transition between lying and standing. In contrast to lying in this study, cows visited the water trough and feed bunk for shorter periods (3.5 ± 1.7 and 25.6 ± 5.8 min, respectively) and frequently returned to these resources soon after leaving (17 and 7% of intervals between visits were <30 s long). As some of these events likely occurred between sample intervals, all sample intervals ≥30 s underestimated the number of times cows visited the water trough and feed bunk (18.5 ± 6.2 and 14.1 ± 4.4 per 24 h, respectively). Therefore, continuous observation is needed to determine how often cows visit these resources. Key words: behavior, methodology, validation, instantaneous sampling
Recording behavior at fixed intervals (instantaneous sampling) can reduce labor relative to observing continuously. However, instantaneous sampling may inaccurately estimate potentially important responses, such as how frequently cows perform a behavior (i.e., the number of bouts). Our objective was to validate the use of instantaneous sampling for capturing how long and how frequently cows in freestall housing lie down or visit the feed bunk and water trough. We predicted that more frequent sampling would be needed to accurately reflect the behaviors that cows spent less time performing. In addition, we predicted that instantaneous sampling would underestimate how often cows engaged in behaviors that they frequently performed in short bouts or with short intervals between bouts, as some of these events may occur between sample intervals. Continuous video observations of 18 lactating HolsteinFriesian dairy cows were conducted for 48-h periods. Instantaneous samples (1 and 30 s, and 1, 3, 5, 10, 15, and 30 min) were generated from continuous data, with the samples recorded at 1-s intervals representing true values. Estimates from each sample interval ≥30 s were compared pairwise to true values with regression analysis. Sample intervals were considered accurate if they met 3 criteria: coefficient of determination ≥0.9 (i.e., strongly related to true values), slope = 1, and intercept = 0 (i.e., did not over- or underestimate true values). The amount of time cows spent lying (12.1 ± 1.8 h/24 h, mean ± standard deviation) or visiting the water trough (1.1 ± 0.8 h/24 h) and feed bunk (5.6 ± 0.8 h/24 h) were accurately captured using sample intervals ≤30, 10, and 5 min, respectively. In addition, sample intervals ≤3 min accurately estimated the number of lying bouts (10.3 ± 2.4 per 24 h), likely because cows were recumbent for long periods (74.0 ± 17.4 min, on average, with <6% of bouts lasting <5 min) and
Technical Note
When studying animal behavior, research objectives will inform the types of information to collect. Relevant measures may include the total amount of time animals spend performing each behavior (duration) or the number and length of discrete occurrences (bouts) of the behavior. In some instances, the number of bouts may change in response to a treatment, even when the overall amount of time animals spend performing a behavior remains the same. For example, dairy cows did not change the total amount of time they spent at the feed bunk regardless of whether or not sprinklers were mounted overhead, but they visited less frequently and stayed for longer each time (Chen et al., 2016). This pattern was consistent with other evidence that suggested cows changed their behavior to avoid walking through spray and getting their heads wet (Chen et al., 2016). The gold standard for recording how frequently and for how long an animal performs a behavior is to determine the precise start and end time using continuous observation. A labor-saving alternative is to categorize which behavior an animal is engaged in at fixed time
Received April 22, 2016. Accepted June 20, 2016. 1 Corresponding author: [email protected]
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intervals (instantaneous sampling; Martin and Bateson, 2007), but it is important to validate how accurately this method captures each behavior. Instantaneous sampling is expected to more accurately reflect true values when (1) sampling frequency increases, (2) a behavior occurs in relatively long bouts, and (3) intervals between bouts are relatively long (Martin and Bateson, 2007), as instantaneous samples would be less likely to miss bouts and the intervals between them. Previous work with adult cattle has examined correlations between true values and the estimates from instantaneous samples during a limited time period (2 h/d of observation; Mitlöhner et al., 2001) or for a single behavior (feeding; Endres et al., 2005; Kitts et al., 2011). However, a rigorous test of accuracy examines not only the strength of the relationship, but also whether the instantaneous samples over- or underestimate true values. This type of test has shown that sample intervals up to 2 min accurately estimated feeding duration for calves in both the pre- and postweaning periods (Miller-Cushon and DeVries, 2011), and that data loggers with sample intervals up to 5 min (the maximum tested) accurately captured lying duration and the number of lying bouts for dairy cows in freestall housing (Ledgerwood et al., 2010). In contrast, all instantaneous samples ≥10 s failed to accurately estimate how frequently and for how long feedlot steers assumed a lateral lying posture (Stackhouse-Lawson et al., 2015). The accuracy of instantaneous sampling for capturing other behaviors in adult cattle has not been established using this rigorous method. Our objective was to validate the use of instantaneous sampling for capturing how frequently and for how long cows lie down or visit the feed bunk and water trough in freestall housing. We predicted that more frequent sampling would be needed to accurately reflect behaviors cows spent less time performing. In addition, we predicted that instantaneous sampling would underestimate the number of times cows performed behaviors that often occurred in short bouts, or with short intervals between bouts. Based on these predictions, we evaluated cattle behavior under warm and dry conditions using 2 approaches to managing heat abatement, as sprinklers affect how long and how frequently cows visit the feed bunk and water trough (Chen et al., 2016). We collected continuous behavioral data for this study (Chen et al., 2016) during the summer (July to August 2013) at the University of California–Davis dairy facility. All procedures were approved by the Institutional Animal Care and Use Committee. Eighteen lactating Holstein-Friesian dairy cows were used, with average parity 2.3 ± 1.0, DIM 199 ± 69, daily milk yield 45 ± 4 kg, and BW 721 ± 98 kg (mean ± SD); 15 Journal of Dairy Science Vol. 99 No. 10, 2016
of the cows were pregnant. Cows were housed in pairs, with 3 pairs tested at a time. Each pair of cows had an unshaded water trough, 4 to 8 shaded, sand-bedded freestalls, and ad libitum access to TMR formulated to NRC (1989) requirements. Feed was delivered at 0400 and 1600 h during milking, for which cows spent a total of 1.8 ± 0.6 h/24 h (mean ± SD) away from the home pen. The current study included 2 treatments: a control in which no water was applied, and a treatment with sprinklers (model TF-VP2 Turbo FloodJet wide angle flat spray tips, 1.3 L/min flow rate; Spraying Systems Co., Wheaton, IL) mounted above the feed bunk that sprayed intermittently 24 h/d (3 min on, 9 min off). All pairs of cows received both treatments in a crossover design, with each treatment period lasting 48 h. Video cameras recorded cows 24 h/d (for details, refer to Chen et al., 2016). Observers scored the video recordings continuously (with 48-h treatment periods beginning at 0400 h) to determine the start and end times (to the nearest second) for each behavior. A cow was considered lying when her flank was in contact with the ground or bedding surface. A cow was determined to be visiting the water trough beginning when any part of her head, neck, or shoulder crossed the edge of the water trough, and ending when this criterion was no longer met and either front hoof also changed position. A cow was scored as visiting the feed bunk when at least 1 hoof was on or over a black-and-white dashed line painted on the ground 1.85 m from the feed bunk (to where the spray radius extended in the sprinkler treatment). When a cow was visiting the feed bunk, we recorded an additional subset of this behavior, which was whether or not her head was in the bunk. This was defined as when her poll and at least 1 ear were through the head gates. The experimental unit was the individual cow. Although treatments were applied to pairs of cows, the objective of the current study was to validate the use of instantaneous sampling for recording the behavior of individual cattle. For each behavioral measure, from the initial sample of 18 cows, we excluded those with values ≥3 SD away from the mean, as we considered the behavior of these outliers to be unrepresentative of the broader population of lactating cattle (final n = 16 to 18 cows per measure; Tables 1 and 2). We converted the continuous data to samples at 1-s intervals using PROC EXPAND (refer to Supplemental Materials, http://dx.doi.org/10.3168/jds.2016-11351; SAS software version 9.4; SAS Institute Inc., 2014). From the 1-s intervals, we extrapolated instantaneous samples for 7 intervals (30 s, and 1, 3, 5, 10, 15, and 30 min), and converted these to the total duration and number of bouts or visits for each 48-h treatment period using
(0.8) (0.8) (6.3) (0.9) 1.0 (0.6) 1.8 (1.1) 32.4 (4.3) 12.2 (2.1)* 8.1 (1.1) 93.7 (15.3) 6.0 7.5 48.8 4.7
5.9 12.5 29.8 4.6
(0.9)* (4.3)* (5.3) (0.5)* 1.0 (0.5)* 14.4 (4.3)† 4.0 (1.5) 12.2 (1.8)* 10.5 (1.7)* 71.6 (11.1)
5.9 12.3 30.1 4.6
(0.9)* (4.0) (5.0) (0.5)* 1.0 (0.5)* 12.4 (3.3) 4.7 (1.9) 12.2 (1.8)* 10.5 (1.7)* 71.9 (11.0)
5.9 11.6 31.5 4.6
(0.9)* (3.2) (4.8) (0.5)* 1.0 (0.5)* 9.0 (2.5) 6.5 (2.3) 12.2 (1.8)* 10.3 (1.7)* 73.2 (12.2)
5.9 10.5 34.4 4.6
(0.9)* (2.2) (5.0) (0.5)* 1.0 (0.5)* 6.7 (2.4) 8.7 (2.7) 12.2 (1.8)* 10.0 (1.7) 75.8 (13.0)
5.9 9.6 37.8 4.6
(0.9)* (1.9) (5.3) (0.5) 1.0 (0.5)* 4.3 (1.5) 13.2 (3.6) 12.2 (1.8)* 9.4 (1.4) 80.2 (13.2)
5.9 8.7 40.9 4.6
(0.9)* (1.1) (5.9) (0.6) 1.0 (0.5) 3.3 (1.3) 18.1 (4.5 12.1 (1.9)* 9.2 (1.3) 81.9 (14.5)
30 min 15 min 10 min 5 min 3 min 1 min 30 s
18 18 18 18 17 17
Visiting feed bunk Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Time with head in bunk (h/24 h) Visiting water trough Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Lying Total duration (h/24 h) Number of bouts (per 24 h) Bout length (min/bout)
18 18 18 18
5.9 13.6 27.7 4.6
(0.9) (5.1) (5.6) (0.5) 1.0 (0.5) 18.0 (6.3) 3.3 (1.4) 12.2 (1.8) 10.6 (1.8) 71.4 (11.1)
1 s3 n2 Item
Sampling interval
Table 1. Means (SD) for behavioral data obtained using instantaneous samples that were extrapolated from continuous observations of cows with access to sprinklers mounted above the feed bunk1
PROC MEANS. The total duration of each behavior in minutes was calculated by multiplying the number of times the behavior was observed by the length of the sample interval (e.g., for 5-min sample intervals, a cow recorded as lying was considered to be recumbent for the following 5-min period). Lying bouts and visits to the feed bunk or water trough were defined as being separated by nonconsecutive observations (e.g., for 5-min sample intervals, a new bout or visit occurred if ≥10 min passed between observations of the behavior). We conducted pairwise comparisons between the true values (1-s sample intervals) and those generated from the 30-s to 30-min sample intervals using linear regressions (PROC REG). Regression analysis was conducted separately for the 2 treatments for each of 7 behavioral measures: the number of visits to the feed bunk and water trough, the number of lying bouts, the total duration of visits to the feed bunk and water trough, the total amount of time cows spent with their heads in the bunk, and the total lying duration. To account for the large number of comparisons, a Bonferroni correction was applied to the P-values for the slopes and intercepts (PROC MULTTEST). A sample interval was determined to accurately reflect true values if it met 3 criteria: the coefficient of determination (R2) was ≥0.9, the slope did not differ significantly from 1 (P > 0.05), and the intercept did not differ significantly from 0 (P > 0.05). Table 1 (sprinkler treatment) and Table 2 (control treatment) indicate whether each sample interval met all 3 accuracy criteria for estimating the total duration and number of bouts or visits, or only the R2 ≥ 0.9 criterion. In addition, we calculated the average bout or visit length by dividing the number of events into the total duration of each behavior. Average bout length was not included in regression analysis because its accuracy could not be evaluated independent of the measures from which it was derived. The means and SD for each behavioral measure are expressed on a per-24-h basis to facilitate comparisons with other studies. All sample intervals ≤30 min accurately reflected the amount of time cows spent lying (Tables 1 and 2) in both treatments. Several studies have found that, although lying time decreases in warmer weather, this response occurs regardless of sprinkler provision (Overton et al., 2002; Chen et al., 2013, 2016). Relatively infrequent sampling was likely able to accurately estimate total lying duration because in freestall housing, this behavior occurs in long bouts (averaging 74 and 66 min in this study and in Ito et al., 2014, respectively) and comprises a large portion of the total time budget (averaging 50% in this study and 43% across CA freestall dairies in Ito et al., 2014). In addition, cows rarely resumed lying down soon after standing up (only 0.4% of intervals between lying bouts were <30
1 The total duration and number of bouts or visits generated by each sample interval were compared pairwise to the true values (represented by samples at 1-s intervals) using regression analysis, and instantaneous samples were considered accurate (*) if they met 3 criteria: R2 ≥ 0.9, intercept not significantly different from 0 (P > 0.05), and slope not significantly different from 1 (P > 0.05). Sample intervals that met only the first criterion (R2 ≥ 0.9) are indicated (†). Average bout or visit length was not included in the regression analysis, as this measure was calculated by dividing the total duration by the number of bouts or visits. 2 Number of cows after outliers ≥3 SD from the mean were excluded. 3 The 1-s intervals represented true values based on continuous observation to the nearest second.
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12.0 8.6 88.6
1.3 3.4 18.8
12.0 9.0 85.1
1.3 4.5 14.7
11.9 9.6 78.9
1.3 6.8 9.6
12.0 9.8 78.1
1.3 8.7 7.6
11.9 9.9 77.4
1.3 12.7 5.3
11.9 9.9 77.4
1.3 14.8 4.6
11.9 10.1 76.7
1.3 19.0 3.7
18 17 17 18 17 17
(0.6) (3.7) (5.3) (0.7) (1.0) (6.1) (2.0) (1.9) (2.9) (22.1) 5.3 14.5 23.2 4.2 17 17 16 18
Visiting feed bunk Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Time with head in bunk (h/24 h) Visiting water trough Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Lying Total time (h/24 h) Number of bouts (per 24 h) Bout length (min/bout)
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1 The total duration and number of bouts or visits generated by each sample interval was compared pairwise to the true values (represented by samples at 1-s intervals) using regression analysis, and instantaneous samples were considered accurate (*) if they met 3 criteria: R2 ≥ 0.9, intercept not significantly different from 0 (P > 0.05), and slope not significantly different from 1 (P > 0.05). Sample intervals that met only the first criterion (R2 ≥ 0.9) are indicated (†). Average bout or visit length was not included in the regression analysis, as this measure was calculated by dividing the total duration by the number of bouts or visits. 2 Number of cows after outliers ≥3 SD from the mean were excluded. 3 The 1-s intervals represented true values based on continuous observation to the nearest second.
12.1 7.7 98.2
1.3 2.0 34.3
(0.7) (1.1) (8.9) (0.9) (0.9)* (0.9) (7.7) (2.0)* (1.5) (22.3) 5.5 7.4 46.6 4.2 (0.6) (1.6) (7.6) (0.9) (0.9)* (1.6) (4.5) (1.9)* (1.8) (22.0) 5.3 9.5 34.6 4.2
5.3 13.6 24.7 4.2
(0.6)* (3.2) (5.9) (0.6)* (1.0)* (4.2) (2.3) (1.9)* (2.6) * (21.4)
5.3 12.9 25.6 4.2
(0.6)* (2.9) (5.4) (0.7)* (1.0)* (2.9) (2.7) (1.9)* (2.6)* (21.4)
5.3 12.1 27.4 4.2
(0.5)* (2.6) (5.7) (0.7)* (1.0)* (2.1) (3.6) (1.9)* (2.5)* (21.0)
5.3 11.7 28.3 4.2
(0.5)* (2.3) (5.5) (0.7)* (1.0)* (2.2) (3.8) (1.9)* (2.3)† (20.7)
5.3 10.3 32.2 4.3
(0.5) (1.7) (5.5) (0.7)* (1.0)* (2.2) (4.9) (1.9)* (2.1)† (22.2)
15 min 10 min 5 min 3 min 1 min 30 s 1 s3 n2 Item
Sampling interval
Table 2. Means (SD) for behavioral data obtained using instantaneous samples that were extrapolated from continuous observations of cows without spray access1
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s), which likely explains why sample intervals ≤3 min accurately captured the number of lying bouts in this study. However, lying patterns, and thus the accuracy of instantaneous sampling, may differ across settings. Previous work evaluating automated data loggers found that sample intervals up to 5 min (the maximum tested) were accurate for estimating how frequently cows lie down in freestalls, but only intervals ≤30 s were accurate for doing so in bedded packs (Ledgerwood et al., 2010). The proportion of short lying bouts, which could occur between sample intervals, has been reported to be several-fold higher in bedded packs [approximately 24% of bouts were <5 min and 40 to 51% were <15 min in Krohn and Munksgaard (1993) and Ledgerwood et al. (2010)] than in freestalls (across studies, 2 to 6 were <5 min, 5 to 11 were <10 min, and 8 to 16 were <15 min in this study and in Cook et al., 2004; Tucker et al., 2009; Ledgerwood et al., 2010) and tie-stalls (approximately 20% were <15 min; Krohn and Munksgaard, 1993). As suggested by Ledgerwood et al. (2010), the higher proportion of short lying bouts in housing systems without stalls could perhaps be explained by greater ease of transitioning between lying and standing or disruption from conspecifics. Sample intervals ≤10 min accurately estimated the total duration of visits to the water trough in the sprinkler treatment (Table 1). Less frequent sample intervals (≤30 min) generated accurate estimates in the control treatment (Table 2), perhaps because cows spent 30% more time visiting the water trough when they lacked access to sprinklers, and this treatment difference was statistically significant (Chen et al., 2016). In contrast, for feedlot heifers, only 1-min sample intervals (the most frequent tested) generated correlation coefficients >0.9 for the amount of time cattle spent with their heads over or in the water trough (Mitlöhner et al., 2001). This was likely because it is difficult to capture rare behaviors using instantaneous sampling (Martin and Bateson, 2007), and the heifers spent <1% of the 2-h observation period at the water trough (Mitlöhner et al., 2001). Cows in our study spent more time at the water trough (5% of each 24-h period, on average), perhaps because water intake increases with lactation (Kume et al., 2010) and in warmer environmental conditions (Muller et al., 1994; Mader et al., 1997). Indeed, in hot, dry conditions, lactating cows on drylot dairies spent 3% of their time between 1000 and 1800 h at the water trough (Tresoldi et al., 2016). However, instantaneous sampling underestimated the number of times cows visited the water trough (R2 values <0.9 for all sampling intervals except 30 s in the sprinkler treatment). Instantaneous sampling likely missed some visits due to the high proportion that were
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short (visits lasted on average 3.5 min, with 39% lasting <1 min and 83% lasting <5 min), and may have also failed to distinguish between some unique visits to the water trough, as 17% of intervals between visits were <30 s long. Therefore, studies recording the number and length of visits to the water trough will likely require continuous observation to generate biologically relevant data. For example, continuous observation revealed that cows with subclinical hypocalcemia visited the water trough less frequently than healthy cows in the 2 wk after calving, despite no differences in overall water intake (Jawor et al., 2012). Sample intervals ≤5 min accurately estimated the amount of time cows spent at the feed bunk in the control treatment (Table 2). Less frequent sampling intervals (≤15 min) were able to generate accurate estimates in the sprinkler treatment (Table 1), perhaps because cows stood at the feed bunk for 19% longer during each visit, and this treatment difference was statistically significant (Chen et al., 2016). However, as with the water trough, instantaneous sampling underestimated the number of visits to the feed bunk (R2 values <0.9 except for 30 s in the sprinkler treatment). This is likely because cows frequently returned to the feed bunk after leaving only briefly, and these intervals between visits (7% were <30 s long) would be missed when they occurred between instantaneous samples. When cows visit the feed bunk, the time they spend there can be divided into more specific behaviors, depending on the research question. For example, feeding is commonly defined as occurring when cows place their heads past the feed barrier (e.g., DeVries et al., 2003b). In the current study, sample intervals ≤5 min accurately estimated the amount of time cows spent with their heads in this position in both treatments (4.6 vs. 4.2 h/24 in the sprinkler vs. control treatments), and past studies have shown high correlations between true values and estimates from ≤10 min instantaneous samples (Endres et al., 2005; Kitts et al., 2011). In addition, when cows have their heads in the bunk, this time can be further divided into whether or not they are actively manipulating the feed (based on movements observed in continuous video recordings). When sprinklers are activated, cows spend more time with their heads through the head gates, but without actively manipulating the feed, perhaps to protect their heads from spray (Chen et al., 2013). The remainder of time cows spend standing at the feed bunk without their heads in the bunk can also be of interest, and this behavior increases when the location has additional resources such as rubber flooring (Fregonesi et al., 2004). Depending on the research question, examining the number of times cows insert and remove their heads from the feed bunk can also be informative. For ex-
ample, the total number of times cows withdraw their heads from the feed bunk can serve as a measure of competitive displacements (e.g., DeVries et al., 2004). Alternatively, for questions about feeding patterns, which are affected by factors such as management, diet composition (e.g., live yeast supplementation; DeVries and Chevaux, 2014), and stage of lactation (DeVries et al., 2003a), it may be more meaningful to combine feeding events that occur close together into a single meal. Although previous work has shown that both the number and duration of meals in pre- and postweaned calves can be accurately measured using sample intervals ≤30 s and 1 min, respectively (Miller-Cushon and DeVries, 2011), research is needed to validate the use of instantaneous sampling to estimate these measures in adult cattle. In conclusion, sample intervals ≤5 min accurately reflect the total amount of time cows in freestall housing spend at the water trough and feed bunk, with their heads in the bunk, and lying down. However, continuous observation is needed to determine the number of times cows visit the water trough and feed bunk, as they frequently leave briefly (for <30 s) before returning to these resources, which sample intervals ≥30 s sometimes fail to capture. In addition, although sample intervals ≤3 min accurately estimated the number of lying bouts in this study, shorter sample intervals may be needed in situations where cows frequently lie down for brief periods (<5 min) or resume lying soon after standing up (within 30 s). ACKNOWLEDGMENTS
We appreciate the input from Erin Mintline (University of California, Davis) for creating the code used to extrapolate instantaneous samples from continuous behavioral data. Funding was provided by the USDA multi-state research project W2173 and the Henry A. Jastro Fund (Davis, CA). We gratefully acknowledge the infrastructure support of the Department of Animal Science, College of Agricultural and Environmental Sciences, and the University of California–Davis Agricultural Experiment Station. REFERENCES Chen, J. M., K. E. Schütz, and C. B. Tucker. 2013. Dairy cows use and prefer feed bunks fitted with sprinklers. J. Dairy Sci. 96:5035–5045. Chen, J. M., K. E. Schütz, and C. B. Tucker. 2016. Cooling cows efficiently with water spray: Behavioral, physiological, and production responses to sprinklers at the feed bunk. J. Dairy Sci. 99:4607–4618. Cook, N. B., T. B. Bennett, and K. V. Nordlund. 2004. Effect of free stall surface on daily activity patterns in dairy cows with relevance to lameness prevalence. J. Dairy Sci. 87:2912–2922.
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DeVries, T. J., and E. Chevaux. 2014. Modification of the feeding behavior of dairy cows through live yeast supplementation. J. Dairy Sci. 97:6499–6510. DeVries, T. J., M. A. G. von Keyserlingk, and D. M. Weary. 2004. Effect of feeding space on the inter-cow distance, aggression, and feeding behavior of free-stall housed lactating dairy cows. J. Dairy Sci. 87:1432–1438. DeVries, T. J., M. A. G. von Keyserlingk, D. M. Weary, and K. A. Beauchemin. 2003a. Measuring the feeding behavior of lactating dairy cows in early to peak lactation. J. Dairy Sci. 86:3354–3361. DeVries, T. J., M. A. G. von Keyserlingk, D. M. Weary, and K. A. Beauchemin. 2003b. Technical note: Validation of a system for monitoring feeding behavior of dairy cows. J. Dairy Sci. 86:3571– 3574. Endres, M. I., T. J. DeVries, M. A. G. von Keyserlingk, and D. M. Weary. 2005. Short communication: Effect of feed barrier design on the behavior of loose-housed lactating dairy cows. J. Dairy Sci. 88:2377–2380. Fregonesi, J. A., C. B. Tucker, D. M. Weary, F. C. Flower, and T. Vittie. 2004. Effect of rubber flooring in front of the feed bunk on the time budgets of dairy cattle. J. Dairy Sci. 87:1203–1207. Ito, K., N. Chapinal, D. M. Weary, and M. A. G. von Keyserlingk. 2014. Associations between herd-level factors and lying behavior of freestall-housed dairy cows. J. Dairy Sci. 97:2081–2089. Jawor, P. E., J. M. Huzzey, S. J. LeBlanc, and M. A. G. von Keyserlingk. 2012. Associations of subclinical hypocalcemia at calving with milk yield, and feeding, drinking, and standing behaviors around parturition in Holstein cows. J. Dairy Sci. 95:1240–1248. Kitts, B. L., I. J. H. Duncan, B. W. McBride, and T. J. DeVries. 2011. Effect of the provision of a low-nutritive feedstuff on the behavior of dairy heifers limit fed a high-concentrate ration. J. Dairy Sci. 94:940–950. Krohn, C. C., and L. Munksgaard. 1993. Behaviour of dairy cows kept in extensive (loose housing/pasture) or intensive (tie stall) environments. II. Lying and lying-down behaviour. Appl. Anim. Behav. Sci. 37:1–16. Kume, S., K. Nonaka, T. Oshita, and T. Kozakai. 2010. Evaluation of drinking water intake, feed water intake and total water intake in dry and lactating cows fed silages. Livest. Sci. 128:46–51.
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Ledgerwood, D. N., C. Winckler, and C. B. Tucker. 2010. Evaluation of data loggers, sampling intervals, and editing techniques for measuring the lying behavior of dairy cattle. J. Dairy Sci. 93:5129–5139. Mader, T. L., L. R. Fell, and M. J. McPhee. 1997. Behavior response of non-Brahman cattle to shade in commercial feedlots. Livest. Environ. 5:795–802. Martin, P., and P. Bateson. 2007. Measuring Behaviour: An Introductory Guide. 3rd ed. Cambridge University Press, Cambridge, UK. Miller-Cushon, E., and T. DeVries. 2011. Technical note: Validation of methodology for characterization of feeding behavior in dairy calves. J. Dairy Sci. 94:6103–6110. Mitlöhner, F. M., J. L. Morrow-Tesch, S. C. Wilson, J. W. Dailey, and J. J. McGlone. 2001. Behavioral sampling techniques for feedlot cattle. J. Anim. Sci. 79:1189–1193. Muller, C. J. C., J. A. Botha, and W. A. Smith. 1994. Effect of shade on various parameters of Friesian cows in a Mediterranean climate in South Africa. 1. Feed and water intake, milk production and milk composition. S. Afr. J. Anim. Sci. 24:49–55. NRC. 1989. Nutrient Requirements of Dairy Cattle. 6th rev. ed. National Academies Press, Washington, DC. Overton, M. W., W. M. Sischo, G. D. Temple, and D. A. Moore. 2002. Using time-lapse video photography to assess dairy cattle lying behavior in a free-stall barn. J. Dairy Sci. 85:2407–2413. SAS Institute Inc. 2014. SAS/STAT 13.2 User's Guide. SAS Institute Inc., Cary, NC. Stackhouse-Lawson, K. R., C. B. Tucker, M. S. Calvo-Lorenzo, and F. M. Mitloehner. 2015. Effects of growth-promoting technology on feedlot cattle behavior in the 21 days before slaughter. Appl. Anim. Behav. Sci. 162:1–8. Tresoldi, G., K. E. Schütz, and C. B. Tucker. 2016. Assessing heat load in drylot dairy cattle: Refining on-farm sampling methodology. J. Dairy Sci. http://dx.doi.org/http://dx.doi.org/10.3168/ jds.2016-11353. Tucker, C. B., N. R. Cox, D. M. Weary, and M. Špinka. 2009. Laterality of lying behaviour in dairy cattle. Appl. Anim. Behav. Sci. 120:125–131.
Technical note: Comparison of instantaneous sampling and continuous observation of dairy cattle behavior in freestall housing Jennifer M. Chen,* Karin E. Schütz,† and Cassandra B. Tucker*1 *Department of Animal Science, University of California, Davis 95616 †AgResearch Ltd., Hamilton 3240, New Zealand
ABSTRACT
rarely resumed lying soon after standing up (0.4% of intervals between lying bouts were <30 s). However, shorter sample intervals may be needed in situations where cows more frequently transition between lying and standing. In contrast to lying in this study, cows visited the water trough and feed bunk for shorter periods (3.5 ± 1.7 and 25.6 ± 5.8 min, respectively) and frequently returned to these resources soon after leaving (17 and 7% of intervals between visits were <30 s long). As some of these events likely occurred between sample intervals, all sample intervals ≥30 s underestimated the number of times cows visited the water trough and feed bunk (18.5 ± 6.2 and 14.1 ± 4.4 per 24 h, respectively). Therefore, continuous observation is needed to determine how often cows visit these resources. Key words: behavior, methodology, validation, instantaneous sampling
Recording behavior at fixed intervals (instantaneous sampling) can reduce labor relative to observing continuously. However, instantaneous sampling may inaccurately estimate potentially important responses, such as how frequently cows perform a behavior (i.e., the number of bouts). Our objective was to validate the use of instantaneous sampling for capturing how long and how frequently cows in freestall housing lie down or visit the feed bunk and water trough. We predicted that more frequent sampling would be needed to accurately reflect the behaviors that cows spent less time performing. In addition, we predicted that instantaneous sampling would underestimate how often cows engaged in behaviors that they frequently performed in short bouts or with short intervals between bouts, as some of these events may occur between sample intervals. Continuous video observations of 18 lactating HolsteinFriesian dairy cows were conducted for 48-h periods. Instantaneous samples (1 and 30 s, and 1, 3, 5, 10, 15, and 30 min) were generated from continuous data, with the samples recorded at 1-s intervals representing true values. Estimates from each sample interval ≥30 s were compared pairwise to true values with regression analysis. Sample intervals were considered accurate if they met 3 criteria: coefficient of determination ≥0.9 (i.e., strongly related to true values), slope = 1, and intercept = 0 (i.e., did not over- or underestimate true values). The amount of time cows spent lying (12.1 ± 1.8 h/24 h, mean ± standard deviation) or visiting the water trough (1.1 ± 0.8 h/24 h) and feed bunk (5.6 ± 0.8 h/24 h) were accurately captured using sample intervals ≤30, 10, and 5 min, respectively. In addition, sample intervals ≤3 min accurately estimated the number of lying bouts (10.3 ± 2.4 per 24 h), likely because cows were recumbent for long periods (74.0 ± 17.4 min, on average, with <6% of bouts lasting <5 min) and
Technical Note
When studying animal behavior, research objectives will inform the types of information to collect. Relevant measures may include the total amount of time animals spend performing each behavior (duration) or the number and length of discrete occurrences (bouts) of the behavior. In some instances, the number of bouts may change in response to a treatment, even when the overall amount of time animals spend performing a behavior remains the same. For example, dairy cows did not change the total amount of time they spent at the feed bunk regardless of whether or not sprinklers were mounted overhead, but they visited less frequently and stayed for longer each time (Chen et al., 2016). This pattern was consistent with other evidence that suggested cows changed their behavior to avoid walking through spray and getting their heads wet (Chen et al., 2016). The gold standard for recording how frequently and for how long an animal performs a behavior is to determine the precise start and end time using continuous observation. A labor-saving alternative is to categorize which behavior an animal is engaged in at fixed time
Received April 22, 2016. Accepted June 20, 2016. 1 Corresponding author: [email protected]
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intervals (instantaneous sampling; Martin and Bateson, 2007), but it is important to validate how accurately this method captures each behavior. Instantaneous sampling is expected to more accurately reflect true values when (1) sampling frequency increases, (2) a behavior occurs in relatively long bouts, and (3) intervals between bouts are relatively long (Martin and Bateson, 2007), as instantaneous samples would be less likely to miss bouts and the intervals between them. Previous work with adult cattle has examined correlations between true values and the estimates from instantaneous samples during a limited time period (2 h/d of observation; Mitlöhner et al., 2001) or for a single behavior (feeding; Endres et al., 2005; Kitts et al., 2011). However, a rigorous test of accuracy examines not only the strength of the relationship, but also whether the instantaneous samples over- or underestimate true values. This type of test has shown that sample intervals up to 2 min accurately estimated feeding duration for calves in both the pre- and postweaning periods (Miller-Cushon and DeVries, 2011), and that data loggers with sample intervals up to 5 min (the maximum tested) accurately captured lying duration and the number of lying bouts for dairy cows in freestall housing (Ledgerwood et al., 2010). In contrast, all instantaneous samples ≥10 s failed to accurately estimate how frequently and for how long feedlot steers assumed a lateral lying posture (Stackhouse-Lawson et al., 2015). The accuracy of instantaneous sampling for capturing other behaviors in adult cattle has not been established using this rigorous method. Our objective was to validate the use of instantaneous sampling for capturing how frequently and for how long cows lie down or visit the feed bunk and water trough in freestall housing. We predicted that more frequent sampling would be needed to accurately reflect behaviors cows spent less time performing. In addition, we predicted that instantaneous sampling would underestimate the number of times cows performed behaviors that often occurred in short bouts, or with short intervals between bouts. Based on these predictions, we evaluated cattle behavior under warm and dry conditions using 2 approaches to managing heat abatement, as sprinklers affect how long and how frequently cows visit the feed bunk and water trough (Chen et al., 2016). We collected continuous behavioral data for this study (Chen et al., 2016) during the summer (July to August 2013) at the University of California–Davis dairy facility. All procedures were approved by the Institutional Animal Care and Use Committee. Eighteen lactating Holstein-Friesian dairy cows were used, with average parity 2.3 ± 1.0, DIM 199 ± 69, daily milk yield 45 ± 4 kg, and BW 721 ± 98 kg (mean ± SD); 15 Journal of Dairy Science Vol. 99 No. 10, 2016
of the cows were pregnant. Cows were housed in pairs, with 3 pairs tested at a time. Each pair of cows had an unshaded water trough, 4 to 8 shaded, sand-bedded freestalls, and ad libitum access to TMR formulated to NRC (1989) requirements. Feed was delivered at 0400 and 1600 h during milking, for which cows spent a total of 1.8 ± 0.6 h/24 h (mean ± SD) away from the home pen. The current study included 2 treatments: a control in which no water was applied, and a treatment with sprinklers (model TF-VP2 Turbo FloodJet wide angle flat spray tips, 1.3 L/min flow rate; Spraying Systems Co., Wheaton, IL) mounted above the feed bunk that sprayed intermittently 24 h/d (3 min on, 9 min off). All pairs of cows received both treatments in a crossover design, with each treatment period lasting 48 h. Video cameras recorded cows 24 h/d (for details, refer to Chen et al., 2016). Observers scored the video recordings continuously (with 48-h treatment periods beginning at 0400 h) to determine the start and end times (to the nearest second) for each behavior. A cow was considered lying when her flank was in contact with the ground or bedding surface. A cow was determined to be visiting the water trough beginning when any part of her head, neck, or shoulder crossed the edge of the water trough, and ending when this criterion was no longer met and either front hoof also changed position. A cow was scored as visiting the feed bunk when at least 1 hoof was on or over a black-and-white dashed line painted on the ground 1.85 m from the feed bunk (to where the spray radius extended in the sprinkler treatment). When a cow was visiting the feed bunk, we recorded an additional subset of this behavior, which was whether or not her head was in the bunk. This was defined as when her poll and at least 1 ear were through the head gates. The experimental unit was the individual cow. Although treatments were applied to pairs of cows, the objective of the current study was to validate the use of instantaneous sampling for recording the behavior of individual cattle. For each behavioral measure, from the initial sample of 18 cows, we excluded those with values ≥3 SD away from the mean, as we considered the behavior of these outliers to be unrepresentative of the broader population of lactating cattle (final n = 16 to 18 cows per measure; Tables 1 and 2). We converted the continuous data to samples at 1-s intervals using PROC EXPAND (refer to Supplemental Materials, http://dx.doi.org/10.3168/jds.2016-11351; SAS software version 9.4; SAS Institute Inc., 2014). From the 1-s intervals, we extrapolated instantaneous samples for 7 intervals (30 s, and 1, 3, 5, 10, 15, and 30 min), and converted these to the total duration and number of bouts or visits for each 48-h treatment period using
(0.8) (0.8) (6.3) (0.9) 1.0 (0.6) 1.8 (1.1) 32.4 (4.3) 12.2 (2.1)* 8.1 (1.1) 93.7 (15.3) 6.0 7.5 48.8 4.7
5.9 12.5 29.8 4.6
(0.9)* (4.3)* (5.3) (0.5)* 1.0 (0.5)* 14.4 (4.3)† 4.0 (1.5) 12.2 (1.8)* 10.5 (1.7)* 71.6 (11.1)
5.9 12.3 30.1 4.6
(0.9)* (4.0) (5.0) (0.5)* 1.0 (0.5)* 12.4 (3.3) 4.7 (1.9) 12.2 (1.8)* 10.5 (1.7)* 71.9 (11.0)
5.9 11.6 31.5 4.6
(0.9)* (3.2) (4.8) (0.5)* 1.0 (0.5)* 9.0 (2.5) 6.5 (2.3) 12.2 (1.8)* 10.3 (1.7)* 73.2 (12.2)
5.9 10.5 34.4 4.6
(0.9)* (2.2) (5.0) (0.5)* 1.0 (0.5)* 6.7 (2.4) 8.7 (2.7) 12.2 (1.8)* 10.0 (1.7) 75.8 (13.0)
5.9 9.6 37.8 4.6
(0.9)* (1.9) (5.3) (0.5) 1.0 (0.5)* 4.3 (1.5) 13.2 (3.6) 12.2 (1.8)* 9.4 (1.4) 80.2 (13.2)
5.9 8.7 40.9 4.6
(0.9)* (1.1) (5.9) (0.6) 1.0 (0.5) 3.3 (1.3) 18.1 (4.5 12.1 (1.9)* 9.2 (1.3) 81.9 (14.5)
30 min 15 min 10 min 5 min 3 min 1 min 30 s
18 18 18 18 17 17
Visiting feed bunk Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Time with head in bunk (h/24 h) Visiting water trough Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Lying Total duration (h/24 h) Number of bouts (per 24 h) Bout length (min/bout)
18 18 18 18
5.9 13.6 27.7 4.6
(0.9) (5.1) (5.6) (0.5) 1.0 (0.5) 18.0 (6.3) 3.3 (1.4) 12.2 (1.8) 10.6 (1.8) 71.4 (11.1)
1 s3 n2 Item
Sampling interval
Table 1. Means (SD) for behavioral data obtained using instantaneous samples that were extrapolated from continuous observations of cows with access to sprinklers mounted above the feed bunk1
PROC MEANS. The total duration of each behavior in minutes was calculated by multiplying the number of times the behavior was observed by the length of the sample interval (e.g., for 5-min sample intervals, a cow recorded as lying was considered to be recumbent for the following 5-min period). Lying bouts and visits to the feed bunk or water trough were defined as being separated by nonconsecutive observations (e.g., for 5-min sample intervals, a new bout or visit occurred if ≥10 min passed between observations of the behavior). We conducted pairwise comparisons between the true values (1-s sample intervals) and those generated from the 30-s to 30-min sample intervals using linear regressions (PROC REG). Regression analysis was conducted separately for the 2 treatments for each of 7 behavioral measures: the number of visits to the feed bunk and water trough, the number of lying bouts, the total duration of visits to the feed bunk and water trough, the total amount of time cows spent with their heads in the bunk, and the total lying duration. To account for the large number of comparisons, a Bonferroni correction was applied to the P-values for the slopes and intercepts (PROC MULTTEST). A sample interval was determined to accurately reflect true values if it met 3 criteria: the coefficient of determination (R2) was ≥0.9, the slope did not differ significantly from 1 (P > 0.05), and the intercept did not differ significantly from 0 (P > 0.05). Table 1 (sprinkler treatment) and Table 2 (control treatment) indicate whether each sample interval met all 3 accuracy criteria for estimating the total duration and number of bouts or visits, or only the R2 ≥ 0.9 criterion. In addition, we calculated the average bout or visit length by dividing the number of events into the total duration of each behavior. Average bout length was not included in regression analysis because its accuracy could not be evaluated independent of the measures from which it was derived. The means and SD for each behavioral measure are expressed on a per-24-h basis to facilitate comparisons with other studies. All sample intervals ≤30 min accurately reflected the amount of time cows spent lying (Tables 1 and 2) in both treatments. Several studies have found that, although lying time decreases in warmer weather, this response occurs regardless of sprinkler provision (Overton et al., 2002; Chen et al., 2013, 2016). Relatively infrequent sampling was likely able to accurately estimate total lying duration because in freestall housing, this behavior occurs in long bouts (averaging 74 and 66 min in this study and in Ito et al., 2014, respectively) and comprises a large portion of the total time budget (averaging 50% in this study and 43% across CA freestall dairies in Ito et al., 2014). In addition, cows rarely resumed lying down soon after standing up (only 0.4% of intervals between lying bouts were <30
1 The total duration and number of bouts or visits generated by each sample interval were compared pairwise to the true values (represented by samples at 1-s intervals) using regression analysis, and instantaneous samples were considered accurate (*) if they met 3 criteria: R2 ≥ 0.9, intercept not significantly different from 0 (P > 0.05), and slope not significantly different from 1 (P > 0.05). Sample intervals that met only the first criterion (R2 ≥ 0.9) are indicated (†). Average bout or visit length was not included in the regression analysis, as this measure was calculated by dividing the total duration by the number of bouts or visits. 2 Number of cows after outliers ≥3 SD from the mean were excluded. 3 The 1-s intervals represented true values based on continuous observation to the nearest second.
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12.0 8.6 88.6
1.3 3.4 18.8
12.0 9.0 85.1
1.3 4.5 14.7
11.9 9.6 78.9
1.3 6.8 9.6
12.0 9.8 78.1
1.3 8.7 7.6
11.9 9.9 77.4
1.3 12.7 5.3
11.9 9.9 77.4
1.3 14.8 4.6
11.9 10.1 76.7
1.3 19.0 3.7
18 17 17 18 17 17
(0.6) (3.7) (5.3) (0.7) (1.0) (6.1) (2.0) (1.9) (2.9) (22.1) 5.3 14.5 23.2 4.2 17 17 16 18
Visiting feed bunk Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Time with head in bunk (h/24 h) Visiting water trough Total duration (h/24 h) Number of visits (per 24 h) Visit length (min/visit) Lying Total time (h/24 h) Number of bouts (per 24 h) Bout length (min/bout)
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1 The total duration and number of bouts or visits generated by each sample interval was compared pairwise to the true values (represented by samples at 1-s intervals) using regression analysis, and instantaneous samples were considered accurate (*) if they met 3 criteria: R2 ≥ 0.9, intercept not significantly different from 0 (P > 0.05), and slope not significantly different from 1 (P > 0.05). Sample intervals that met only the first criterion (R2 ≥ 0.9) are indicated (†). Average bout or visit length was not included in the regression analysis, as this measure was calculated by dividing the total duration by the number of bouts or visits. 2 Number of cows after outliers ≥3 SD from the mean were excluded. 3 The 1-s intervals represented true values based on continuous observation to the nearest second.
12.1 7.7 98.2
1.3 2.0 34.3
(0.7) (1.1) (8.9) (0.9) (0.9)* (0.9) (7.7) (2.0)* (1.5) (22.3) 5.5 7.4 46.6 4.2 (0.6) (1.6) (7.6) (0.9) (0.9)* (1.6) (4.5) (1.9)* (1.8) (22.0) 5.3 9.5 34.6 4.2
5.3 13.6 24.7 4.2
(0.6)* (3.2) (5.9) (0.6)* (1.0)* (4.2) (2.3) (1.9)* (2.6) * (21.4)
5.3 12.9 25.6 4.2
(0.6)* (2.9) (5.4) (0.7)* (1.0)* (2.9) (2.7) (1.9)* (2.6)* (21.4)
5.3 12.1 27.4 4.2
(0.5)* (2.6) (5.7) (0.7)* (1.0)* (2.1) (3.6) (1.9)* (2.5)* (21.0)
5.3 11.7 28.3 4.2
(0.5)* (2.3) (5.5) (0.7)* (1.0)* (2.2) (3.8) (1.9)* (2.3)† (20.7)
5.3 10.3 32.2 4.3
(0.5) (1.7) (5.5) (0.7)* (1.0)* (2.2) (4.9) (1.9)* (2.1)† (22.2)
15 min 10 min 5 min 3 min 1 min 30 s 1 s3 n2 Item
Sampling interval
Table 2. Means (SD) for behavioral data obtained using instantaneous samples that were extrapolated from continuous observations of cows without spray access1
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CHEN ET AL.
s), which likely explains why sample intervals ≤3 min accurately captured the number of lying bouts in this study. However, lying patterns, and thus the accuracy of instantaneous sampling, may differ across settings. Previous work evaluating automated data loggers found that sample intervals up to 5 min (the maximum tested) were accurate for estimating how frequently cows lie down in freestalls, but only intervals ≤30 s were accurate for doing so in bedded packs (Ledgerwood et al., 2010). The proportion of short lying bouts, which could occur between sample intervals, has been reported to be several-fold higher in bedded packs [approximately 24% of bouts were <5 min and 40 to 51% were <15 min in Krohn and Munksgaard (1993) and Ledgerwood et al. (2010)] than in freestalls (across studies, 2 to 6 were <5 min, 5 to 11 were <10 min, and 8 to 16 were <15 min in this study and in Cook et al., 2004; Tucker et al., 2009; Ledgerwood et al., 2010) and tie-stalls (approximately 20% were <15 min; Krohn and Munksgaard, 1993). As suggested by Ledgerwood et al. (2010), the higher proportion of short lying bouts in housing systems without stalls could perhaps be explained by greater ease of transitioning between lying and standing or disruption from conspecifics. Sample intervals ≤10 min accurately estimated the total duration of visits to the water trough in the sprinkler treatment (Table 1). Less frequent sample intervals (≤30 min) generated accurate estimates in the control treatment (Table 2), perhaps because cows spent 30% more time visiting the water trough when they lacked access to sprinklers, and this treatment difference was statistically significant (Chen et al., 2016). In contrast, for feedlot heifers, only 1-min sample intervals (the most frequent tested) generated correlation coefficients >0.9 for the amount of time cattle spent with their heads over or in the water trough (Mitlöhner et al., 2001). This was likely because it is difficult to capture rare behaviors using instantaneous sampling (Martin and Bateson, 2007), and the heifers spent <1% of the 2-h observation period at the water trough (Mitlöhner et al., 2001). Cows in our study spent more time at the water trough (5% of each 24-h period, on average), perhaps because water intake increases with lactation (Kume et al., 2010) and in warmer environmental conditions (Muller et al., 1994; Mader et al., 1997). Indeed, in hot, dry conditions, lactating cows on drylot dairies spent 3% of their time between 1000 and 1800 h at the water trough (Tresoldi et al., 2016). However, instantaneous sampling underestimated the number of times cows visited the water trough (R2 values <0.9 for all sampling intervals except 30 s in the sprinkler treatment). Instantaneous sampling likely missed some visits due to the high proportion that were
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short (visits lasted on average 3.5 min, with 39% lasting <1 min and 83% lasting <5 min), and may have also failed to distinguish between some unique visits to the water trough, as 17% of intervals between visits were <30 s long. Therefore, studies recording the number and length of visits to the water trough will likely require continuous observation to generate biologically relevant data. For example, continuous observation revealed that cows with subclinical hypocalcemia visited the water trough less frequently than healthy cows in the 2 wk after calving, despite no differences in overall water intake (Jawor et al., 2012). Sample intervals ≤5 min accurately estimated the amount of time cows spent at the feed bunk in the control treatment (Table 2). Less frequent sampling intervals (≤15 min) were able to generate accurate estimates in the sprinkler treatment (Table 1), perhaps because cows stood at the feed bunk for 19% longer during each visit, and this treatment difference was statistically significant (Chen et al., 2016). However, as with the water trough, instantaneous sampling underestimated the number of visits to the feed bunk (R2 values <0.9 except for 30 s in the sprinkler treatment). This is likely because cows frequently returned to the feed bunk after leaving only briefly, and these intervals between visits (7% were <30 s long) would be missed when they occurred between instantaneous samples. When cows visit the feed bunk, the time they spend there can be divided into more specific behaviors, depending on the research question. For example, feeding is commonly defined as occurring when cows place their heads past the feed barrier (e.g., DeVries et al., 2003b). In the current study, sample intervals ≤5 min accurately estimated the amount of time cows spent with their heads in this position in both treatments (4.6 vs. 4.2 h/24 in the sprinkler vs. control treatments), and past studies have shown high correlations between true values and estimates from ≤10 min instantaneous samples (Endres et al., 2005; Kitts et al., 2011). In addition, when cows have their heads in the bunk, this time can be further divided into whether or not they are actively manipulating the feed (based on movements observed in continuous video recordings). When sprinklers are activated, cows spend more time with their heads through the head gates, but without actively manipulating the feed, perhaps to protect their heads from spray (Chen et al., 2013). The remainder of time cows spend standing at the feed bunk without their heads in the bunk can also be of interest, and this behavior increases when the location has additional resources such as rubber flooring (Fregonesi et al., 2004). Depending on the research question, examining the number of times cows insert and remove their heads from the feed bunk can also be informative. For ex-
ample, the total number of times cows withdraw their heads from the feed bunk can serve as a measure of competitive displacements (e.g., DeVries et al., 2004). Alternatively, for questions about feeding patterns, which are affected by factors such as management, diet composition (e.g., live yeast supplementation; DeVries and Chevaux, 2014), and stage of lactation (DeVries et al., 2003a), it may be more meaningful to combine feeding events that occur close together into a single meal. Although previous work has shown that both the number and duration of meals in pre- and postweaned calves can be accurately measured using sample intervals ≤30 s and 1 min, respectively (Miller-Cushon and DeVries, 2011), research is needed to validate the use of instantaneous sampling to estimate these measures in adult cattle. In conclusion, sample intervals ≤5 min accurately reflect the total amount of time cows in freestall housing spend at the water trough and feed bunk, with their heads in the bunk, and lying down. However, continuous observation is needed to determine the number of times cows visit the water trough and feed bunk, as they frequently leave briefly (for <30 s) before returning to these resources, which sample intervals ≥30 s sometimes fail to capture. In addition, although sample intervals ≤3 min accurately estimated the number of lying bouts in this study, shorter sample intervals may be needed in situations where cows frequently lie down for brief periods (<5 min) or resume lying soon after standing up (within 30 s). ACKNOWLEDGMENTS
We appreciate the input from Erin Mintline (University of California, Davis) for creating the code used to extrapolate instantaneous samples from continuous behavioral data. Funding was provided by the USDA multi-state research project W2173 and the Henry A. Jastro Fund (Davis, CA). We gratefully acknowledge the infrastructure support of the Department of Animal Science, College of Agricultural and Environmental Sciences, and the University of California–Davis Agricultural Experiment Station. REFERENCES Chen, J. M., K. E. Schütz, and C. B. Tucker. 2013. Dairy cows use and prefer feed bunks fitted with sprinklers. J. Dairy Sci. 96:5035–5045. Chen, J. M., K. E. Schütz, and C. B. Tucker. 2016. Cooling cows efficiently with water spray: Behavioral, physiological, and production responses to sprinklers at the feed bunk. J. Dairy Sci. 99:4607–4618. Cook, N. B., T. B. Bennett, and K. V. Nordlund. 2004. Effect of free stall surface on daily activity patterns in dairy cows with relevance to lameness prevalence. J. Dairy Sci. 87:2912–2922.
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