DOI: 10.5061/dryad.573n5tb73
title: Continuous bite monitoring method (GPEP)

description: Determining herbage intake is pivotal for studies on grazing ecology.
 Direct observation of animals allows describing the interactions of
 animals with the pastoral environment along the complex grazing process.
 The objectives of the study were to evaluate the reliability of the
 continuous bite monitoring (CBM) method in determining herbage intake in
 grazing sheep compared to the standard double-weighing technique (DW)
 method during 45-min feeding bouts; evaluate the degree of agreement
 between the two techniques; and to test the effect of different potential
 sources of variation on the reliability of the CBM. The CBM method has
 been used to describe the intake behaviour of grazing herbivores. In this
 study, we evaluated a new approach to this method, i.e., whether it is a
 good proxy for determining the intake of grazing animals. Three
 experiments with grazing sheep were carried out in which we tested for
 different sources of variations, such as the number of observers, level of
 detail of bite coding grid, forage species, forage allowance, sward
 surface height heterogeneity, experiment site, and animal weight, to
 determine the short-term intake rate (45 min). Observer (Pexp1 = 0.018,
 Pexp2 = 0.078 and Pexp3 = 0.006), sward surface height (Pexp2 &lt;
 0.001), total number of bites observed per grazing session (Pexp2 &lt;
 0.001 and Pexp3 &lt; 0.001) and sward depletion (Pexp3 &lt; 0.001)
 were found to affect the absolute error of intake estimation. The results
 showed a high correlation and agreement between the two methods in the
 three experiments, although intake was overestimation by CBM on experiment
 2 and 3 (181.38 and 214.24 units, respectively). This outcome indicates
 the potential of CBM to determining forage intake with the benefit of a
 greater level of detail on foraging patterns and components of the diet.
 Furthermore, direct observation is not invasive nor disrupts natural
 animal behavior.
description: MATERIALS AND METHODS <i>Site,
 treatments and experimental design</i> Three
 independent studies were conducted in which we tested for different
 sources of variation: number of observers, level of detail of BC grid
 (Figure 1), forage species, forage allowance, sward surface height (SSH)
 heterogeneity, experiment site, and animal breed. Experiment 1 was carried
 out between 15 September and 15 October 2014, on an area of approximately
 0.50 ha of self-seeding Italian ryegrass (<i>Lolium
 multiflorum</i> Lam.) at the experimental farm of the Federal
 University of Rio Grande do Sul, Brazil (30°05´27” S, 51°40’18” W). The
 area was divided into two paddocks of 0.25 ha (experimental areas) with
 salt and water freely available. In this protocol, there were no defined
 criteria for managing the sward pre-grazing structure. Only average sward
 surface height measurements were collected at the time of
 observation. Experiments 2 and 3 were carried out at
 the Canguiri experimental station of the Federal University of Paraná,
 Brazil (25°26'30''S and 49°7'30''W). The
 experiments were established in a 0.3 ha experimental area of tall fescue
 cv. INIA Aurora (<i>Schedonorus arundinaceus</i> [Schreb.]
 Dumort) sown in June 2015 on a prepared seedbed, at 55 kg
 ha<sup>-1</sup>. Beginning in September 2015, the experimental
 area was managed under continuous stocking with sward surface height
 maintained between 10 and 15 cm, except just prior to and during the
 grazing events when the different pre-grazing SSH treatments were imposed.
 Experiment 2 was carried out between 24 June and 12 July 2016 and
 Experiment 3 was carried out between 15 and 24 November 2016. In
 Experiment 2, five homogeneous pre-grazing SSH (14, 17, 20, 23, and 26 cm)
 were evaluated in a randomized complete block design with four replicates.
 In Experiment 3, five levels of depletion (0, 20, 40, 60, and 70%) of
 average SSH (20 cm) were evaluated in a randomized complete block design
 with four replicates, through grazing with non-experimental animals prior
 to grazing sessions to measure behaviour. A more detailed description
 management protocol can be found in Szymczak et al. (2020).
 <i>Sward measurements</i> Five
 hundred SSH measurements were taken in the two experimental paddocks of
 Experiment 1 to characterize the vegetation structure. Mean SSH was 38.0
 cm (±13.12 cm) and 38.7 cm (±12.98 cm) for paddocks 1 and 2. For
 Experiments 2 and 3, 150 points pre-grazing SSH within each sampling unit
 were measured. Pre-grazing SSH were 14.2 (±0.19), 17.3 (±0.20), 19.7
 (±0.27), 22.8 (±0.28) and 25.9 (±0.26) cm, for treatment of 14, 17, 20, 23
 and 26 cm in experiment 2, respectively. The measured pre-grazing SSH were
 20.2 (±0.18), 16.5 (±0.52), 12.2 (±0.52), 8.3 (±0.48) and 5.9 (±0.37) cm,
 for treatments 0, 20, 40, 60 and 70% of depletion in experiment 3,
 respectively. <b>Intake and grazing behavior
 evaluations</b> <i>Animals and experimental
 procedures</i> Procedures involving the
 experimental animals were conducted under the Guidelines for the Use of
 Animals (2012) and complied with ethical guidelines published by the
 International Society for Applied Ethology. All procedures involving
 animals were approved by the Commission for Ethics in the Use of Animals
 of the Sector of Agricultural Sciences of the Federal University of Paraná
 (024/2016). Two methodologies were used simultaneously
 during grazing tests to measure short-term intake rate (STIR): the double
 weighing technique (DW) as the reference practice (Penning &
 Hooper, 1985) and the continuous bite monitoring (CBM) method (Agreil
 & Meuret, 2004; Bonnet et al. 2015). In Experiment 1, eight Texel
 ewes (42.07 ± 3.15 kg LW) were used. Sixty days before the data
 collection, ewes were allocated on an adjacent Italian ryegrass pasture
 for acclimation to forage and adaptation to observers and equipment.
 During the experimental procedure, animals were distributed in two groups
 of four testers per paddock, where two testers per paddock were used for
 evaluation of the continuous bite monitoring and double-weighing. After
 the evaluations, animals were placed back on the adjacent pasture for the
 remaining of the day. In Experiments 2 and 3, six White Dorper x Suffolk
 ewes were used with an average weight of 61.9 ± 5.5 kg. Two animals were
 chosen as testers, all previously adapted to the experimental procedure
 and maintained in an area similar and adjacent to the experimental
 paddocks. <i>Continuous bite
 monitoring</i> Experiment 1 involved three
 observers: one with previous experience on the methodology with wild
 herbivores and cattle (EO; Bonnet et al., 2015), and two new observers
 (TO1 and TO2) were trained by EO. Experiments 2 and 3 involved four
 different observers, all inexperienced. Prior to the beginning of the
 experiments, a mutual familiarization phase was adopted for three weeks.
 During this phase, animals were handled daily to acclimate to observers
 and protocols, and for observers to familiarize with pasture and grazing
 behavior. Once the tester animals were identified and familiarized with
 the evaluators, all bites observed were described and classified into
 categories based on the observation of the animals' intake behavior
 before the experiments under the following aspects: <i>i</i>)
 structural and nutritional distribution of the components in the sward;
 <i>ii</i>) the nature, size, density, and position of selected
 plant parts by animals, as a set of leaves, isolated leaves or
 inflorescences; and <i>iii</i>) handling (gathering herbage
 into the mouth, severing the herbage, ingestive mastication and
 swallowing, Laca et al., 1994). Simple codes were established for each
 bite category agreed upon by all observers, composing a grid of codes for
 the identification of bites in real-time (Fig. 1A and 1B). The level of
 detail for each BC grid differed based on SSH, phenological stages, plant
 density heterogeneity, and species diversity. For Experiments 2 and 3 the
 same grid was used, but the dimensions and masses varied (Annex 1 and
 2). After three weeks of training, both experienced and
 naïve observers were able to codify with confidence every bite observed
 (Bonnet et al., 2011). The three observers in Experiment 1 (one observer
 per tester animal per paddock in each session evaluated) and four
 observers on Experiments 2 and 3 (two observers per experiment, one
 observer per tester animal, and one tester per paddock) collected data by
 standing close to the animals (within 1 m), during 45-min grazing
 sessions. Thirty-two (Experiment 1) and twenty (Experiments 2 and 3)
 sessions were conducted. These sessions were blocked into morning and
 afternoon periods, arranged in a completely randomized design. After each
 grazing session had finished and while the animals remained in a common
 pen for determining insensible weight losses, each bite category was
 simulated (minimum 22 hand-plucks for each type of bite, for bite codes
 more frequent we replicated the samples). Samples were collected in paper
 bags and placed in a thermal box and weighed immediately after collection
 to estimate fresh matter (FM) intake. Intake was calculated as a sum of FM
 for all recorded bites. Data were registered using a Sony ICD-PX312 (Sony
 Corp., Japan) digital voice recorder and, subsequently, transcribed using
 the J Watcher software (www.jwatcher.ucla.edu). <i>Short-term intake rate</i> During the experimental period each day around 5:40 am (Experiment 1) or 6:30 am (Experiments 2 and 3), animals were moved to the handling area, fitted with harnesses for a total collection of urine and feces, and weighed at <i>t<sub>1</sub></i> (<i>W<sub>1</sub></i> = initial weight for estimating the rate of insensitive weight losses (H<sub>2</sub>O evaporation, CO<sub>2</sub> and CH<sub>4</sub> losses; RIWL pre-grazing). After being weighed, the animals remained in a common pen for 45 min without access to feed or water and then weighed again at <i>t<sub>2</sub></i> (<i>W<sub>2</sub></i> = final weight for pre-grazing RIWL and pre-grazing weight). Immediately after, all the animals were conducted and allotted to their paddocks for the 45-min grazing session (<i>ET</i>). Once the grazing session was finished, the animals were led to the handling area and the tester animals were weighed at <i>t<sub>3</sub></i> (<i>W<sub>3</sub></i> = post-grazing weight and initial weight for the post-grazing RIWL). The tester animals then remained in a common area without access to feed, water or shade for 45 min until being weighed at <i>t<sub>4</sub></i> (<i>W<sub>4</sub></i>= final weight for post-grazing RIWL). The harnesses were then immediately removed, and the animals returned to the adjacent area. This same procedure was repeated in the afternoon (between 2:15 pm and 6:30 pm for Experiment 1 and between 2:30 and 6:30 pm, for Experiments 2 and 3). The animals were weighed using an electronic scale (MGR-3000 Junior, Toledo, Canoas, Brazil) with a capacity of 200 kg (5-g increments). Short-term intake rate (g FM min<sup>-1</sup>; Eq. 1) was calculated by measuring the weight change, corrected for insensible weight loss, and the time spent grazing, according to Penning & Hooper (1985). <i>STIR=W2-W1 (t2-t1)+W3-W4(t4-t3) X t2-t1ET</i>        Eq.1 <i>Statistical Analysis</i> The data were analyzed using the R software (R Development Core Team, 2016). Animal test group was the experimental unit. We systematically verified normality and homogeneity of the residuals. Pearson correlation was used as mean accuracy between the methods and was considered poor (&lt;0.4), reasonable (0.4 to 0.6), good (0.6 to 0.8), or excellent (0.8 to 1.0). Bland–Altman plots were created to indicate the degree of agreement between the two techniques (Bland and Altman, 1999). The limits of agreement were determined by calculating the bias and standard deviation of the paired differences. The standard deviation was multiplied by the 1.96 quantiles of a normal distribution and then, the amount of the calculated average was added or subtracted to provide the upper or lower limits, respectively. Thus, the agreement limits were calculated as bias ± standard deviation. One Sample T-Test, at a significance level of 95%, was performed to check if there was a significant difference from zero, for the comparison between the methods.