Skip to main content
NCBI home page
Journal of Animal Science logoLink to Journal of Animal Science
. 2020 Jun 9;98(6):skaa192. doi: 10.1093/jas/skaa192

Increasing the content of physically effective fiber in high-concentrate diets fed to beef heifers affects intake, sorting behavior, time spent ruminating, and rumen pH

Lourdes Llonch 1, Lorena Castillejos 1,✉, Alfred Ferret 1
PMCID: PMC7320828  PMID: 32516372

Abstract

AbstractThe importance of fiber particle size in ruminal health is well known, but there are fewer studies to assess the requirements of physically effective NDF (peNDF) in beef cattle than in dairy cattle. The objective of this study was to establish the optimal peNDF proportion in high-concentrate diets fed to beef cattle, to reduce the risk of subacute ruminal acidosis. The experimental design was a replicated Latin Square 4 × 4, with four periods of 21 d. Treatments consisted of four diets with different peNDF proportions: 6.4%, 10.4%, 13.6%, and 15.4%, offered ad libitum as total mixed ration, and containing 15% barley straw and 85% concentrate. Diets, which differed in proportions of straw > 4 mm (considered peNDF) and straw < 4 mm, were manually mixed with concentrate. This concentrate was the same for all diets. A ruminal bolus was orally administered to each heifer for pH measurement. Intake, water consumption, intake by particle size, feed sorting, feeding behavior, behavioral activities, and rumen pH were recorded. Chemical composition and particle sizes of diets offered were assessed in the last week of each period. Data were analyzed using the MIXED procedure of SAS. Orthogonal contrasts determined the linear and quadratic effects of increasing peNDF proportion. T-test procedure determined whether heifers carried out sorting behavior. Particles >4 mm linearly increased (P = 0.001), and particles <4 mm linearly decreased (P = 0.001) as peNDF increased. Water consumption and feeding behavior were unaffected by treatment. As peNDF increased, intakes of DM and NDF linearly decreased (P = 0.001), whereas peNDF intake increased (P = 0.001). Intake of particles > 4 mm linearly increased, whereas intake of particles < 4 mm linearly decreased (P = 0.001) as peNDF increased. Diet 6.4% performed sorting for particles > 4 mm (P < 0.01), and diets 13.6% and 15.4% against particles > 4 mm (P < 0.01). Diet 10.4% tended to sort against particles > 4 mm (P < 0.10). Time spent ruminating linearly increased (P = 0.001) as peNDF increased. Diets did not differ in mean and minimum rumen pH, but time under rumen pH thresholds (5.8, 5.7, 5.6, and 5.5) linearly decreased as peNDF increased (P < 0.05). The results suggested that the diet that best met the requirements of not compromising intake, limiting sorting behavior, and promoting time spent ruminating to reduce the number of hours under rumen pH thresholds, was the 10.4% diet.

Keywords: beef cattle, behavior, physically effective fiber, rumen pH

Introduction

High-energy feedlot diets in beef cattle are commonly used by current beef cattle feeding programs. High-concentrate intake increases the incidence of subacute ruminal acidosis (SARA), which is defined as periods of moderately depressed ruminal pH, usually without clear visual signs but resulting in reduced performance (Stock and Britton, 1993). SARA is associated with a diet low in fiber and high in energy, and a ruminal environment that does not maintain ruminal pH within a physiological range of about 5.5 to 7.0 (Krause and Oetzel, 2006). In order to maintain ruminal health, forage is usually supplied to ruminants. However, forage is included at lower levels in finishing diets because of lower energy values and digestibility (Allen, 1997; Mertens, 1997). On the other hand, the ability of forage to stimulate chewing has been investigated extensively because of the relationship between chewing and the flow of salivary buffers into the rumen, which are required to neutralize fermentation acids (Allen, 1997).

Beauchemin (1991) and Mertens (1997) indicated that some feed characteristics, primarily particle size, can promote chewing and rumination, which are important in maintaining a desirable rumen pH. Smaller particle size feeds typically result in reduced chewing time and ruminal pH (Grant et al., 1990). Mertens (1997) introduced the term physically effective NDF (peNDF) to clarify the concept of effective NDF (eNDF) originally proposed for dairy cows to represent the ability of a feed to allow for an adequate milk fat percentage. While the eNDF of a feed depends on its particle length, buffering capacity, fermentation rate, and other inherent characteristics, peNDF incorporates information on particle size and NDF content of the feed, though peNDF is also related to particle shape, fragility, type of preservation, and feed moisture (Mertens, 1997). Recent studies have determined the effects of dietary peNDF on chewing activity, rumen function, and feed utilization using dairy cows (Einarson et al., 2004; Yang and Beauchemin, 2009).

Mertens (1997) used 1.18 mm as the critical size at which feed particles are considered physically effective for dairy cows, based on the assumption that particles smaller than 1.18 mm can readily pass through the reticulo-omasal orifice without mastication and may be able to escape ruminal fermentation (Poppi et al., 1980). Subsequently, Maulfair et al. (2011) concluded that critical particle size for rumen escape is larger than 1.18 mm in dairy cattle, as suggested by Yang et al. (2001) and Oshita et al. (2004). On the basis of the literature, Heinrichs (2013) recommended 4 mm as a more suitable particle size for estimating peNDF. Overall, the impact of peNDF has been more thoroughly researched in dairy cattle than in beef cattle. Though not well defined, the ideal particle size of feed in finishing diets would promote intake, generate rumination, maintain desirable performance, and prevent acidotic events (Gentry et al., 2016). Weiss et al. (2017) concluded that a diet with a lower inclusion of roughage with a larger particle size may stimulate rumination at the same level as one with a higher inclusion of roughage with smaller particle size. Mertens (2002) recommended 15% peNDF (on DM basis), for feedlot cattle, with a range from 12% to 18%. Fox and Tedeschi (2002) suggested that beef cattle feedlot diets should have between 7% and 10% peNDF (on DM basis) to keep ruminal pH above 5.7. These recommendations were based on the equations of Pitt et al. (1996) and mentioned in NASEM (2016). There is less experimental research in beef cattle than in dairy cattle about peNDF requirements that ensure a correct rumen function and reduce the risk of SARA. Our hypothesis was that increasing the proportion of peNDF in beef cattle diets would increase peNDF intake, promote chewing activity, and reduce time under a critical rumen pH. Thus, the objective of this experiment was to test increased proportions of peNDF in a high-concentrate diet fed to beef heifers to establish the optimal level to minimize the risk of SARA.

Materials and Methods

Animal procedures were approved by the Institutional Animal Care and Use Committee (reference CEEAH 9963) of the Universitat Autònoma de Barcelona (Spain) in accordance with the European directive 2010/63/EU.

Animals, housing, experimental design, and diets

Eight Simmental heifers (206 ± 1.6 d old and with an average initial BW of 258 ± 5.7 kg) were randomly assigned to one of four treatments in a replicated Latin Square 4 × 4, and individually allocated in roofed pens (12.5 m2) separated by a metal fence that allowed contact between animals. Heifers were purchased from a commercial farm where animals were allocated in groups and fed concentrate and barley straw in separate feed bunks, as a free choice. Before the experiment started, animals were fed for a week with an ad libitum total mixed ration (TMR) diet. The experiment was performed in four periods of 21 d on the Experimental Farm of the Universitat Autònoma de Barcelona between March and June 2018. Each period was composed of 14 d of adaptation, and 7 d of sampling. At the end of each period, animals changed treatment randomly. Treatments were four diets all containing 15% barley straw and 85% concentrate but differing in proportions of peNDF: (1) 6.4%, (2) 10.4%, (3) 13.6%, and (4) 15.4%. Concentrate, which was the same for the four diets, was made up of 47.8% barley grain, 38.9% corn grain, 11.0% soybean meal, 0.8% salt, 0.6% calcium carbonate, 0.46% dicalcium phosphate, and 0.44% of a vitamin–mineral premix. This premix contained per kilogram (as fed): 2,000 kIU vitamin A, 500 kIU vitamin D3, 2.5 g vitamin E, 1.5 g vitamin B1, 3 mg vitamin B12, 10 g Zn, 150 mg Co, 0.5 g Cu, 5 g Mn, 125 mg I, and 25 mg Se. The concentrate was used in flour form after grinding with a 3-mm screen to ensure that concentrate did not supply peNDF, and its chemical composition was 90% DM, 13.0% CP, and 15.8% NDF. Barley straw, with a chemical composition of 91.5% DM, 4.2% CP, and 72.1% NDF, was initially chopped with a feeder wagon, with a standardized parameter of load, speed, and time. TMRs were formulated to meet the recommendations of Fundación Española para el Desarrollo de la Nutrición Animal (FEDNA, 2008) for beef cattle to obtain a weight gain of 1.2 kg/d. The chemical composition of the diets is shown in Table 1. Straw particle sizes were sorted with a Penn State Particle Separator (PSPS; PennState Extension, University Park, PA), with four plastic separator boxes to obtain four different fractions: (1) long particles (>19 mm), (2) medium particles (19 to 8 mm), (3) short particles (8 to 4 mm), and (4) fine particles (<4 mm). The sifting process involved putting ~200 g of chopped straw in the upper sieve, shaking the PSPS in one direction five times on a flat surface, rotating it one-quarter turn, and repeating this process a total of eight times for each sample. Straw particle size > 4 mm, which is the particle size considered peNDF, was obtained by sifting chopped straw with the three-screen PSPS and removing the straw from the bottom pan. The NDF content of the straw particle size > 4 mm was 72.0%. Straw particle size < 4 mm was obtained by grinding chopped straw in a hammer mill through a 2-mm screen, verifying that more than 95% particles fell in the bottom pan. TMRs were manually mixed, supplied daily at 0900 hours, and offered as ad libitum, which was increased daily by 15% in relation to the previous day’s intake. Heifers were weighed before feeding on two consecutive days at the beginning and the end of the experiment, and weekly during the experiment using a scale (AG 500/E; Trusted Pro II, l’Hospitalet de Llobregat, Spain).

Table 1.

Chemical composition (% on DM basis) of the offered diets

peNDF1
Item2 6.4% 10.4% 13.6% 15.4%
CP 12.3 11.8 11.2 12.3
NDF 29.5 28.4 29.9 29.4
ADF 13.5 13.4 14.0 13.9
EE 2.1 2.2 2.1 2.1
Ash 4.1 4.1 4.3 4.2
NFC 52.0 53.5 52.5 52.0
ME, Mcal/kg DM 2.85 2.85 2.85 2.85
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2NFC = nonfiber carbohydrates calculated as 100 − (CP + ash + NDF + EE).

Intake, feed sampling, and sorting analysis

Individual feed bunks (120-L capacity) were mounted on waterproof digital platform scales (DI-160; Digi I’s Ltd, Maesawa, Japan) to measure DMI. The information was downloaded onto a computer with appropriate data capture software (LabView; National Instruments Corporation, Austin, TX). DMI was calculated as the difference between amounts offered and refused based on DM determination. Water provision was ad libitum and registered by individual drinking cups fitted with direct measurement flow meters (Invensys 510 C; Tashia S.L., Artesa de Segre, Spain). Feed offered and refusal samples of each heifer were collected daily for 5 d in the sampling week of each period, and stored at −18 °C. Prior to analysis, samples had been defrosted at ambient temperature and divided into three sub-samples: sub-sample 1 for particle size analysis, sub-sample 2 for DM determination, and sub-sample 3 for chemical composition analysis. Particle size analysis was made by the PSPS, and particle size proportions of each diet are described in Table 2. Physically eNDF of the offered diets was calculated by multiplying the sum of the proportion of long, medium, and short particles (particles > 4 mm) by the NDF content of barley straw particles of this size. Sorting was calculated as the actual intake of each fraction size expressed as a percentage of the predicted intake, where the predicted intake of each fraction equals the product of as-fed intake and as-fed fraction in the diet. Values <100% indicate selective refusals, >100% indicate preferential consumption, and equal than 100% indicate no sorting (Leonardi and Armentano, 2003).

Table 2.

Particle separation and estimated physically effective neutral detergent fiber of the offered diets

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Particle size3, % DM
 Long (>19 mm) 2.0c 4.1b 5.5a 6.0a 0.48 0.001 0.001 0.023
 Medium (8 to 19 mm) 4.1c 6.1b 8.1a 9.3a 0.56 0.001 0.001 0.311
 Short (4 to 8 mm) 2.8d 4.2c 5.3b 6.1a 0.23 0.001 0.001 0.097
 Fine (<4 mm) 91.1a 85.6b 81.1c 78.6c 0.91 0.001 0.001 0.027
 Particles > 4 mm 8.9c 14.4b 18.9a 21.4a 0.91 0.001 0.001 0.027
Physically effective NDF4, % DM 6.4c 10.4b 13.6a 15.4a 0.66 0.001 0.001 0.027
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

3Particle size determined by Penn State Particle Separator (PSPS; PennState Extension, University Park, PA).

4Physically eNDF = Sum of long, medium and short particles (particles > 4 mm) determined by Penn State Particle Separator × average NDF content of these particle sizes.

a−dWithin a row, means without a common superscript differ statistically (P < 0.05).

Chemical analysis

Feed samples were dried in a forced-air oven at 55 °C for 48 h and ground in a hammer mill through a 1-mm screen (SM200/1390; Retsch, Sabadell, Spain). DM was determined by drying samples for 24 h at 103 °C in a forced-air oven (AOAC, 1990; ID 950.05). CP was determined by the Kjeldahl procedure (AOAC, 1990; ID 976.05). Ether extract (EE) was performed according to AOAC (1990; ID 920.39). The NDF and ADF contents were determined sequentially by using an Ankom Fiber Analyzer (A200; Ankom Technology, Fairport, NY) in accordance with the methodology provided by the company. This is based on the methods described by van Soest et al. (1991), using a thermostable α-amylase and sodium sulfite, and expressed on an ash-free basis. Ash was determined according to AOAC (1990; ID 950.05).

Feeding behavior and behavioral activities

Feeding behavior data were recorded for 7 d in each sampling week and analyzed as described by González et al. (2008). Feeding behavior was registered by an automated system where each scale was programmed to transmit the feed weight at intervals of 5 s. The information was downloaded onto a computer with appropriate data capture software (LabView; National Instruments Corporation, Austin, TX). Briefly, the length of all inactive intervals in which feeding did not occur was log-transformed and used to calculate the meal criterion, which is the minimum time required to consider two periods of eating activity as separate events. The Mixed Distributions Package of the R software was used for this purpose, and model fitting was done in accordance with the study by Yeates et al. (2001). Meal frequency (meals/d) was the number of intervals where eating activity was registered and that exceeded the meal criterion. Meal length (min/meal) was calculated as the time from the first eating observation to the time of the last eating observation (within a meal) before an inactive interval that exceeded the meal criterion. Meals were further characterized by DM ingested (meal size; g DM/meal) and rate of DM ingested per meal (eating rate; g DM/min), calculated as the ratio of the amount of feed ingested and the corresponding meal length.

Animal behavior was video-recorded for 24 h on two nonconsecutive days in each sampling week using a digital video-recording device (VS-101P VioStor NVR; QNAP Systems Inc., Taipei City, Taiwan). A digital color camera (VIVOTEK IP7142; Vivotek Inc., Taipei City, Taiwan) was set up in front of the feeding area of each pen at a height of 3 m. Infrared light with photoelectric cells (830 nm and 500 W; Dennard 2020, Hants, UK) was set up at each end of the pen to allow video-recording at night. Data processing was carried out by scan sampling at 5-min intervals. Observations were performed by a single observer. Windows media player software was used to watch videos. Microsoft Excel software (Microsoft Office 2007; Microsoft Corp., Redmond, WA) was used to record all the observations during the assessment. The behavioral activities observed were previously defined and presented as the total time, expressed in min, in which the animal maintained this specific activity. A heifer was considered to be eating when the animal had its muzzle in the feed bunk or was chewing or swallowing food with its head over the feed bunk. Ruminating included the regurgitation, mastication, and swallowing of the bolus. Total chewing is the sum of eating and ruminating. Eating, ruminating, and total chewing times were also expressed as min/kg total DM, min/kg NDF, and min/kg peNDF. To do this, data were calculated considering times spent eating, ruminating and total chewing, and total DM, NDF, and peNDF intake recorded on the 2 d of behavior observation.

Rumen pH

For continuous measurement of rumen pH, wireless, and indwelling data transmitting rumen boluses (smaXtec Premium Bolus; Animal Care GmbH, Graz, Austria) were used. Data were recorded every 10 min and uploaded wirelessly to one of the several receivers within the barn. Data were obtained by smaXtec messenger computer software, logged on an Excel spreadsheet (Microsoft Office 2007; Microsoft Corp., Redmond, WA), including the date and time when rumen pH was recorded. Boluses were orally administered to each animal at the beginning of the study. Boluses were shock-proof and resistant to rumen fluid. Calibration of the pH-probes was performed using pH 4 and pH 7 buffer solutions before the introduction into animals.

Statistical analysis

Heifer was considered the experimental unit in all the analyses. In each experimental period, the daily mean value was calculated as the average of 7 d for rumen and feeding behavior data, 5 d for particle separation and proportion of peNDF, DM and nutrient intake, water consumption, DM intake by particle size, and sorting behavior, or 2 d for behavioral activities. The normality of the data was checked with UNIVARIATE procedure of SAS (v. 9.3; SAS Institute Inc., Cary, NC). All these data were statistically analyzed using the MIXED procedure of SAS (v. 9.3; SAS Institute Inc., Cary, NC). The model contained the fixed effects of Latin square, treatment and period, and the random effect of heifer nested within Latin square and period, the day is included as a repeated measure. The Tukey multiple comparison test was applied to separate means when P < 0.10. Orthogonal contrasts were used to determine the linear and quadratic effects of increasing the proportion of peNDF in the diet. To determine whether heifers sorted against or for each particle size, sorting behavior was tested for a difference from 100 using the t-test procedure. Significance was declared at P < 0.05, and tendencies were discussed at P < 0.10.

Results and Discussion

Final BW of heifers, after the experimental period of 84 d, was on average 385 ± 9.2 kg, resulting in an ADG of 1.6 ± 0.1 kg/d (µ ± SE).

The experimental design sought to include the range of peNDF recommendations proposed by Fox and Tedeschi (2002), thus treatment diets were designed to contain from 5% to 11% of peNDF. Considering these intended levels and the NDF content of the straw particles larger than 4 mm, the proportion of these particles that should be included in each diet was calculated. These proportions were maintained daily across the experiment to avoid the introduction of a factor of variation. Grinding of concentrate with a 3-mm screen was made in order to make sure that particles larger than 4 mm only came from barley straw, and to facilitate the daily preparation of the diets. Once the experiment was finished, the particle size separation of diet samples taken per heifer and period was carried out and the levels of peNDF were 6.4%, 10.4%, 13.6%, and 15.4% (Table 2). As was expected, long, medium, and short particle size, and the sum of these particles, which are considered to include peNDF, linearly increased from diet 6.4% to diet 15.4% (P = 0.001). Obviously, fine particles linearly decreased (P = 0.001) from diet 6.4% to diet 15.4%. Physically eNDF offered in each diet were different among treatment diets except between 13.6% and 15.4% diets (P = 0.001), where the difference was only numerical.

Treatment diets were formulated and offered with the same concentrate to barley straw ratio. However, intake of DM and NDF linearly decreased (P = 0.001) as the proportion of peNDF increased, being DM and NDF intake greater in diet 6.4% than in diets 13.6% and 15.4%, but without differences between diets 6.4% and 10.4% (Table 3; P = 0.001). However, water consumption was unaffected by treatment. When DM intake was separated by particle size, linear and quadratic increases (P = 0.001) were detected for long, medium, and short particles, whereas increasing peNDF resulted in a linear decrease for fine particles (P = 0.001). In terms of differences among treatment diets, intake of long particles was lesser in diet 6.4% than in the remaining diets, and greater in diets 10.4% and 13.6% than in diet 15.4% (P = 0.001). Intakes of medium and short particles increased from diet 6.4% to diet 15.4% (P = 0.001). Intake of fine particles was greater in diet 6.4% than in the remaining diets, and lesser in diets 13.6% and 15.4% than in diet 10.4% (P = 0.001). Linear and quadratic increases (P = 0.001) were detected for the intake of particles larger than 4 mm and peNDF intake expressed as kg DM/d. These intakes were lesser in diet 6.4% than in the remaining diets, and greater in diets 13.6% and 15.4% than in diet 10.4% (P = 0.001). No differences in peNDF intake between 13.6% and 15.4% diets were due to similar DMI, and no differences in peNDF content between both diets. The effects of increasing the peNDF content in the diet on intake were similar to the results obtained by Teimouri Yansari et al. (2004), who observed that a reduction of forage particle size increased DMI, NDF intake, and ruminal particle passage rate, but decreased peNDF intake in a TMR fed to dairy cows. In the present study, decreased DMI could be explained by the fact that increasing straw particle size could increase the filling effects in the rumen and decrease the ruminal passage rate (Allen, 2000). In the same way, Gentry et al. (2016) recorded a decrease in DMI when peNDF passed from 11.3% to 13.0%, working with steers fed diets based on steam-flaked corn and either 30% wet corn gluten feed with 5% long-grind corn stalks, or 25% wet corn gluten feed with 10% short-grind corn stalks. These authors suggested that increasing particle size of forage may be a means to decrease forage inclusion while maintaining rumination and performance. These results contrast with those obtained by Madruga et al. (2018) who compared the DMI of fattening Simmental heifers fed a TMR with 10% barley straw and TMR diets with an increasing proportion of alfalfa hay from 13% to 19%. These authors reported that DMI linearly increased together with NDF intake and the ratio between peNDF intake and DMI passed from 11.3% for the 10% barley straw diet to an average of 13.3% for the alfalfa diets. The main differences with our study are that these authors obtained these high proportions of peNDF using a forage source of better quality, as is alfalfa hay, and used the sum of particle sizes larger than 1.18 mm and the NDF content of the complete diet to define the peNDF. Taking into account the lesser DMI recorded in diets 13.6% and 15.4%, and the possible consequences that this decrease could cause on ADG, diets 10.4% and 6.4% could be considered those with an optimal peNDF in terms of achieving high intake and performance. The ratio between the intake of peNDF and the total DMI revealed that the levels tested were actually 6.6%, 10.3%, 12.4%, and 12.9%. Linear and quadratic increases (P = 0.001) were detected for the intake of peNDF expressed as the percentage of DMI, being different among treatment diets except between diets 13.6% and 15.4% (P = 0.001). There was, therefore, a numerically great coincidence between the estimated proportions of peNDF in the diets and the intake of peNDF expressed as the percentage of DMI for 6.4% and 10.4% diets, but not for 13.6% and 15.4%. This could be explained by the differential incidence of sorting behavior depending on the diet.

Table 3.

Effect of increasing the proportion of peNDF in the diet on intake of DM and NDF, intake by particle size, intake of peNDF and water consumption

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Intake
 DM, kg/d 8.13a 8.03ab 7.67bc 7.37c 0.149 0.001 0.001 0.347
 NDF, kg DM/d 2.40a 2.26ab 2.23b 2.04c 0.631 0.001 0.001 0.560
Intake by particle size3, kg DM/d
 Long (>19 mm) 0.17c 0.33a 0.33a 0.25b 0.022 0.001 0.001 0.001
 Medium (8 to 19 mm) 0.34d 0.48c 0.59b 0.64a 0.019 0.001 0.001 0.001
 Short (4 to 8 mm) 0.23d 0.33c 0.39b 0.43a 0.010 0.001 0.001 0.001
 Fine (< 4 mm) 7.39a 6.89b 6.36c 6.06c 0.131 0.001 0.001 0.292
 Particles > 4 mm 0.74c 1.14b 1.31a 1.32a 0.043 0.001 0.001 0.001
peNDF intake
 kg DM/d4 0.53c 0.82b 0.94a 0.95a 0.031 0.001 0.001 0.001
 % DMI5 6.6c 10.3b 12.4a 12.9a 0.33 0.001 0.001 0.001
Water consumption, L/d 26.2 24.6 25.5 24.4 0.88 0.131 0.105 0.659
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

3Particle size determined by Penn State Particle Separator (PSPS; PennState Extension, University Park, PA).

4Physically eNDF = sum of long, medium, and short particles (particles > 4 mm) determined by Penn State Particle Separator × average NDF content of these particle sizes.

5Intake of peNDF (kg DM/d) divided by intake of DM (kg/d).

a−dWithin a row, means without a common superscript differ statistically (P < 0.05).

Increasing the proportion of peNDF in the diet resulted in a linear decrease (P = 0.001) in the extent of sorting of long, medium, and short particle sizes, and their sum, and a linear increase (P = 0.001) in the extent of sorting of fine particle size (Table 4). A quadratic effect was also detected for the extent of sorting of long, medium, and fine particle size (P = 0.001). Extent of sorting of long particle size was greater in diets 6.4% and 10.4% than in diets 13.6% and 15.4%, and lesser in diet 15.4% than in diet 13.6% (P = 0.001). The extent of sorting of medium particle size was greater in diet 6.4% than in the remaining diets, and lesser in diets 13.6% and 15.4% than in diet 10.4% (P = 0.001). Extent of sorting of short particle size decreased from diet 6.4% to diet 15.4% (P = 0.001). Extent of sorting of fine particles was lesser in diets 6.4% and 10.4% than in diets 13.6% and 15.4%, and greater in diet 15.4% than in diet 13.6% (P = 0.001). The extent of sorting of particles larger than 4 mm decreased from diet 6.4% to diet 15.4% (P = 0.001). Heifers fed diet 6.4% sorted for medium and short particles, and particles larger than 4 mm (P < 0.01), and against fine particles (P < 0.01). Heifers fed diet 10.4% tended to sort against particles larger than 4 mm (P < 0.10). Heifers fed diets 13.6% and 15.4% sorted against long, medium, and short particles, and particles larger than 4 mm (P < 0.01), and sorted for fine particles (P < 0.01). Sorting for larger particles in the diet can be considered a strategy to attenuate the discomfort associated with low ruminal pH conditions (DeVries et al., 2008, 2014). Heifers fed diet 6.4% were those which registered the longer times under ruminal pH considered SARA thresholds. Thus, this longer period of low rumen pH could explain that heifers had to sort for larger particles to stabilize their rumen conditions. Feeding systems based on TMR are designed to provide a balanced intake of nutrients to all animals without allowing for individual preferences or sorting (Coppock, 1977). However, sorting behavior has been detected in growing calves (Miller-Cushon et al., 2013; Groen et al., 2015; Gordon and DeVries, 2016), growing heifers (Greter et al., 2008; DeVries et al., 2014; Madruga et al., 2017), and fattening heifers (Madruga et al., 2018). Gentry et al. (2016) claimed that increasing particle size of forage may be limited by the potential of cattle to sort forage in the bunk, which is in accordance with our results. In summary, the content of peNDF in the 10.4% diet was the only one which limited or avoided sorting behavior by heifers fed this diet, so this peNDF content could be considered optimal to avoid selective refusals and preferential consumption of a particular particle size.

Table 4.

Effect of increasing the proportion of peNDF in the diet on sorting behavior

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Particle size3
 Long (> 19 mm) 102.2a 95.7a 77.7b** 51.6c** 4.23 0.001 0.001 0.001
 Medium(8 to 19 mm) 103.8a** 98.4b 95.4c** 95.2c** 0.91 0.001 0.001 0.001
 Short (4 to 8 mm) 102.1a** 99.4b 97.6c** 96.0d** 0.49 0.001 0.001 0.148
 Fine (< 4 mm) 99.7c** 100.2c 102.0b** 104.4a** 0.27 0.001 0.001 0.001
 Particles > 4 mm 103.2a** 98.3b+ 91.1c** 83.6d** 1.27 0.001 0.001 0.143
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

3Particle size determined by Penn State Particle Separator (PSPS; PennState Extension, University Park, PA).

a−dWithin a row, means without a common superscript differ statistically (P < 0.05).

Values < 100% indicate selective refusals (sorting against), > 100% indicate preferential consumption (sorting for), and = 100% indicate no sorting. Statistical differences from 100% are expressed as: **P < 0.01, *P < 0.05, and +P < 0.10.

Sorting behavior did not affect feeding behavior, where number of meals per day, length of meal, meal size, and eating time were not affected by the treatment diet (Table 5). Meal criterion did not differ among diets, being on average 29.6 ± 13.2 min. However, as peNDF increased in the diet, the extent of sorting of particles larger than 4 mm linearly decreased in correspondence with the effect on the time spent eating, ruminating, and total chewing. In the present study, daily time spent eating was unaffected by diet (Table 6). This unexpected result, in spite of the sorting behavior performed by the heifers, could be related with the decreasing DMI as peNDF increased because, when expressed as min/kg DM and min/kg NDF, time spent eating linearly increased (P = 0.048 and P = 0.019, respectively) as the proportion of peNDF increased. Time spent eating when expressed as min/kg NDF tended to be shorter in diet 6.4% than in diet 15.4% (P = 0.073). There was a linear and quadratic effect (P = 0.001) of the proportion of peNDF in the diet on time spent eating expressed as min/kg peNDF, this time being longer in diet 6.4% than in the remaining diets. Time spent ruminating and time spent on total chewing linearly increased as the proportion of peNDF increased (P = 0.001), expressed as min/d, min/kg DM, or min/kg NDF. These results agree with those reported by Gentry et al. (2016) in beef cattle, who stated that as particle size increased in the diet, daily ruminating time also increased. In the same way, Weiss et al. (2017), when determining the effects of corn stalk inclusion rate and particle size in finishing diets fed beef steers, concluded that using a lower inclusion of roughage (5%) with larger particle size may stimulate rumination to the same degree as a higher inclusion of roughage (10%) with smaller particle size. In addition, according to Yang and Beauchemin (2009), increased chewing activity is most consistently caused by increased ruminating activity when increasing the content of peNDF in the diet, but in some cases, increased chewing activity can also result from increased eating activity. Heifers fed diet 6.4% spent a shorter daily time ruminating and on total chewing than heifers fed the remaining diets (P = 0.001). Time spent ruminating and time spent on total chewing, when expressed as min/kg DM and min/kg NDF, were shorter in diet 6.4% than in the remaining diets, and longer in diet 15.4% than in diets 10.4% and 13.6% (P = 0.001). The linear decrease in ruminating and total chewing when expressed as min/kg peNDF (P = 0.016 and P = 0.001, for time spent ruminating and on total chewing, respectively) is in agreement with Beauchemin and Yang (2005). Time spent ruminating expressed as min/kg peNDF was longer in diet 6.4% than in diet 13.6% (P = 0.026). Time spent on total chewing expressed as min/kg peNDF was longer in diet 6.4% than in diets 13.6% and 15.4% (P = 0.001). This result corresponds with the increase in peNDF intake as peNDF of the diet increased, which moved from 0.53 kg in diet 6.4%, when time spent ruminating per kilogram of peNDF was 1.9 times of daily time spent ruminating, to 0.95 kg in diet 15.4%, when time spent ruminating per kilogram of peNDF was close to daily time spent ruminating. Beauchemin et al. (2006) suggested that with diets low in peNDF each additional kilogram of peNDF would increase chewing time more than with diets containing adequate peNDF. In agreement with Zebeli et al. (2006), dietary peNDF may affect chewing activity either through prolonging chewing time (min/d) or decreasing chewing index (min/kg of peNDF). Considering that approximately half of the bicarbonate that enters the rumen comes from saliva during eating and ruminating (Owens et al., 1998), increasing the time spent on these behaviors should increase the buffering capacity of the rumen and may aid in controlling ruminal pH. Time spent drinking was shorter when expressed as min/d (P = 0.036) or tended to be shorter when expressed as min/L (P = 0.053) in diet 10.4% than in diet 13.6%.

Table 5.

Effect of increasing the proportion of peNDF in the diet on feeding behavior

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Meal frequency, meals/d 8.8 8.7 8.4 8.1 0.49 0.431 0.115 0.723
Meal length, min/meal 42.5 42.3 41.0 40.9 1.33 0.494 0.155 0.948
Meal size, g/meal 917 908 933 931 55.2 0.961 0.702 0.925
Eating rate, g/min 22 22 23 23 1.5 0.781 0.344 0.910
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

Table 6.

Effect of increasing the proportion of peNDF in the diet on behavioral activities.

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Eating,
 min/d 84.8 90.9 87.9 87.4 4.66 0.638 0.742 0.328
 min/kg DM 10.7 11.3 11.5 12.1 0.66 0.246 0.048 0.915
 min/kg NDF 36.7z 40.0yz 39.1yz 43.8y 2.68 0.073 0.019 0.721
 min/kg peNDF 166.1a 112.2b 94.9b 96.3b 10.40 0.001 0.001 0.001
Ruminating
 min/d 319.3b 441.9a 437.4a 476.6a 21.12 0.001 0.001 0.007
 min/kg DM 40.5c 55.7b 57.6b 65.4a 2.71 0.001 0.001 0.062
 min/kg NDF 139.4c 198.0b 197.2b 236.1a 11.87 0.001 0.001 0.242
 min/kg peNDF 616.1a 554.8ab 473.8b 521.2ab 46.20 0.026 0.016 0.103
Total chewing3
 min/d 403.9b 532.6a 525.2a 564.1a 22.04 0.001 0.001 0.006
 min/kg DM 51.3c 67.0b 69.1b 77.5a 2.99 0.001 0.001 0.088
 min/kg NDF 176.1c 238.0b 237.0b 279.9a 13.30 0.001 0.001 0.312
 min/kg peNDF 782.2a 667.0ab 568.8b 617.4b 50.98 0.001 0.001 0.027
Drinking,
 min/d 24.0ab 18.1b 27.2a 23.5ab 3.03 0.036 0.434 0.612
 min/L 0.9yz 0.8z 1.2y 0.9yz 0.14 0.053 0.291 0.781
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

3Total chewing = sum of eating and ruminating

a−cWithin a row, means without a common superscript differ statistically (P < 0.05).

y−zWithin a row, means without a common superscript tended to differ (P < 0.10).

The definition of SARA has been based on a single pH-value falling below a threshold, which varied between 5.5 and 5.8 in several studies (Keunen et al., 2002; Beauchemin et al., 2003; Plaizier et al., 2008). However, the length of time per day in which ruminal pH is under “suboptimal” levels seems a better determinant of fiber degradation and presence of SARA (Beauchemin et al., 2003; Krause et al., 2003). Current recommendations are that the risk of SARA increases when daily mean ruminal pH is lower than 6.16 (Zebeli et al., 2008), and when ruminal pH drops below 5.6 for more than 3 h/d (Gozho et al., 2006; Plaizier et al., 2008), or below 5.8 for more than 5.24 h/d (Zebeli et al., 2008). In the present study, mean and minimum pH were unaffected by treatment, whereas there was a quadratic effect for maximum pH (Table 7; P = 0.005). Heifers fed diet 6.4% had greater maximum pH than heifers fed diet 10.4% (P = 0.020). Times under 5.8, 5.7, 5.6, and 5.5 pH decreased linearly (P = 0.008, P = 0.009, P = 0.023, and P = 0.049, respectively) as the proportion of peNDF increased. This effect was not observed when the area under the curve for each rumen pH threshold was considered (data not shown). Time under 5.8 pH was longer in diet 6.4% than in the remaining diets (P = 0.008). Time under 5.7 pH was longer in diet 6.4% than in diet 13.6% (P = 0.024). Time under 5.6 pH showed a tendency without differences between diets (P = 0.082). Daily mean rumen pH was above the recommended value in all treatment diets, daily minimum pH was equal or above 5.8, and durations below 5.6 and 5.8 pH were above recommended times. These results suggest that heifers did not suffer SARA, which was confirmed by the fact that SARA symptomatology was not present in any treatment, probably because heifers had been adapted for a long time to an intensive feeding system. Fox and Tedeschi’s (2002) recommendation that beef cattle feedlot diets should contain between 7% and 10% of peNDF on a DM basis to keep ruminal pH above 5.7, the results of the present study demonstrated that neither daily mean pH nor daily minimum ruminal pH was lower than 5.7 pH in diets containing a range between 6.4% and 15.4% peNDF. Regarding durations below 5.8 pH, heifers fed the diet 6.4% were those which had a time closer to the threshold proposed by Zebeli et al. (2008) in comparison with the other diets studied. The duration of time below critical thresholds decreased as the content of peNDF increased, in agreement with the increase in time spent ruminating and on total chewing. Thus, considering the more consistent results of ruminal pH, the optimal content of peNDF to facilitate an adequate rumen environment would correspond to heifers fed diet 10.4%.

Table 7.

Effect of increasing the proportion of peNDF in the diet on rumen pH

peNDF1 P-value
Effects2
Item 6.4% 10.4% 13.6% 15.4% SEM Overall effect L Q
Rumen pH
 Mean 6.64 6.65 6.69 6.65 0.031 0.428 0.350 0.299
 Minimum 5.89 5.83 5.92 5.83 0.053 0.206 0.633 0.605
 Maximum 7.42a 7.33b 7.37ab 7.41ab 0.032 0.020 0.852 0.005
Duration, h/d
 pH < 5.8 2.24a 1.11b 0.92b 1.11b 0.421 0.008 0.008 0.028
 pH < 5.7 1.58a 0.85ab 0.61b 0.68ab 0.353 0.024 0.009 0.108
 pH < 5.6 1.08 0.60 0.40 0.43 0.292 0.082 0.023 0.220
 pH < 5.5 0.63 0.47 0.22 0.23 0.229 0.221 0.049 0.594
Open in a new tab

1Physically eNDF proportion in the diets (DM basis).

2L, linear; Q, quadratic effects.

a−bWithin a row, means without a common superscript differ statistically (P < 0.05).

In conclusion, the present results suggest that diet 10.4% was the best option to meet the requirements of not compromising DM intake, limiting sorting behavior, and promoting sufficient time spent ruminating and on total chewing to reduce the number of hours under critical rumen pH. Heifers fed diet 6.4%, with a high DMI, showed preferential intake of particles larger than 4 mm, sorted against fine particles, and spent a shorter time ruminating and on total chewing, although without presenting high risk of SARA. Finally, when the peNDF content rose above 10%, as in diets 13.6% and 15.4%, longer times spent ruminating and on total chewing were recorded, but without any relevant advantage in time under critical ruminal pH thresholds and with a decreased DMI together with a preferential consumption of fine particles and selective refusal of particles larger than 4 mm.

Acknowledgments

Financial support from the Spanish Ministry of Economy and Competitiveness, and the European Regional Development Fund (Research Project AGL2015-68373-C2-1-R) is acknowledged.

Glossary

Abbreviations

DM

dry matter

DMI

dry matter intake

EE

ether extract

eNDF

effective neutral detergent fiber

NDF

neutral detergent fiber

peNDF

physically effective neutral detergent fiber

PSPS

Penn State Particle Separator

SARA

subacute ruminal acidosis

TMR

total mixed ration

Conflict of interest statement

The authors declare no real or perceived conflicts of interest.

Literature Cited

  1. AOAC. 1990. Official methods of analysis. 15th ed.Arlington, VA: Association of Official Analytical Chemists. [Google Scholar]
  2. Allen M. S. 1997. Relationship between fermentation acid production in the rumen and the requirement for physically effective fiber. J. Dairy Sci. 80:1447–1462. doi: 10.3168/jds.S0022-0302(97)76074-0 [DOI] [PubMed] [Google Scholar]
  3. Allen M. S. 2000. Effects of diet on short-term regulation of feed intake by lactating dairy cattle. J. Dairy Sci. 83:1598–1624. doi: 10.3168/jds.S0022-0302(00)75030-2 [DOI] [PubMed] [Google Scholar]
  4. Beauchemin K. A. 1991. Ingestion and mastication of feed by dairy cattle. Vet. Clin. North Am. Food Anim. Pract. 7:439–463. doi: 10.1016/s0749-0720(15)30794-5 [DOI] [PubMed] [Google Scholar]
  5. Beauchemin K. A., and Yang W. Z.. . 2005. Effects of physically effective fiber on intake, chewing activity, and ruminal acidosis for dairy cows fed diets based on corn silage. J. Dairy Sci. 88:2117–2129. doi: 10.3168/jds.S0022-0302(05)72888-5 [DOI] [PubMed] [Google Scholar]
  6. Beauchemin K. A., Yang W. Z., and Penner G. B.. . 2006. Effective fiber for dairy diets. In: Proceedings of 67th Minnesota Nutrition Conference, St. Paul, MN; p 107–119. [Google Scholar]
  7. Beauchemin K. A., Yang W. Z., and Rode L. M.. . 2003. Effects of particle size of alfalfa-based dairy cow diets on chewing activity, ruminal fermentation, and milk production. J. Dairy Sci. 86:630–643. doi: 10.3168/jds.S0022-0302(03)73641-8 [DOI] [PubMed] [Google Scholar]
  8. Coppock C. E. 1977. Feeding methods and grouping systems. J. Dairy Sci. 60:1327–1336. doi: 10.3168/jds.S0022-0302(77)84030-7 [DOI] [Google Scholar]
  9. Devries T. J., Dohme F., and Beauchemin K. A.. . 2008. Repeated ruminal acidosis challenges in lactating dairy cows at high and low risk for developing acidosis: feed sorting. J. Dairy Sci. 91:3958–3967. doi: 10.3168/jds.2008-1347 [DOI] [PubMed] [Google Scholar]
  10. DeVries T. J., Schwaiger T., Beauchemin K. A., and Penner G. B.. . 2014. The duration of time that beef cattle are fed a high-grain diet affects feed sorting behavior both before and after acute ruminal acidosis1,2. J. Anim. Sci. 92:1728–1737. doi: 10.2527/jas.2013-7252 [DOI] [PubMed] [Google Scholar]
  11. Einarson M. S., Plaizier J. C., and Wittenberg K. M.. . 2004. Effects of barley silage chop length on productivity and rumen conditions of lactating dairy cows fed a total mixed ration. J. Dairy Sci. 87:2987–2996. doi: 10.3168/jds.S0022-0302(04)73430-X [DOI] [PubMed] [Google Scholar]
  12. FEDNA 2008. Necesidades nutricionales para rumiantes de cebo: Normas FEDNA. Madrid, SP:Fundación Española para el Desarrollo de la Nutrición Animal; Spanish. [Google Scholar]
  13. Fox D. G., and Tedeschi L. O.. . 2002. Application of physically effective fiber in diets for feedlot cattle. In: Proceedings of Plains Nutrition Council Spring Conference, San Antonio, TX AREC 02-20; p. 67–81. [Google Scholar]
  14. Gentry W. W., Weiss C. P., Meredith C. M., McCollum F. T., Cole N. A., and Jennings J. S.. . 2016. Effects of roughage inclusion and particle size on performance and rumination behavior of finishing beef steers. J. Anim. Sci. 94:4759–4770. doi: 10.2527/jas.2016-0734 [DOI] [PubMed] [Google Scholar]
  15. González L. A., Ferret A., Manteca X., and Calsamiglia S.. . 2008. Increasing sodium bicarbonate level in high-concentrate diets for heifers. II. Effects on chewing and feeding behaviors. Animal 2:713–722. doi: 10.1017/S1751731108001663 [DOI] [PubMed] [Google Scholar]
  16. Gordon L. J., and DeVries T. J.. . 2016. Technical note: impact of a molasses-based liquid feed supplement on the feed sorting behavior and growth of grain-fed veal calves. J. Anim. Sci. 94:3519–3526. doi: 10.2527/jas.2015-0195 [DOI] [PubMed] [Google Scholar]
  17. Gozho G. N., Krause D. O., and Plaizier J. C.. . 2006. Rumen lipopolysaccharide and inflammation during grain adaptation and subacute ruminal acidosis in steers. J. Dairy Sci. 89:4404–4413. doi: 10.3168/jds.S0022-0302(06)72487-0 [DOI] [PubMed] [Google Scholar]
  18. Grant R. J., Colenbrander V. F., and Mertens D. R.. . 1990. Milk fat depression in dairy cows: role of particle size of alfalfa hay. J. Dairy Sci. 73:1823–1833. doi: 10.3168/jds.S0022-0302(90)78862-5 [DOI] [PubMed] [Google Scholar]
  19. Greter A. M., DeVries T. J., and von Keyserlingk M. A.. . 2008. Nutrient intake and feeding behavior of growing dairy heifers: effects of dietary dilution. J. Dairy Sci. 91:2786–2795. doi: 10.3168/jds.2008-1052 [DOI] [PubMed] [Google Scholar]
  20. Groen M. J., Steele M. A., and DeVries T. J.. . 2015. Short communication: effect of straw inclusion rate in a dry total mixed ration on the behavior of weaned dairy calves. J. Dairy Sci. 98:2693–2700. doi: 10.3168/jds.2014-8978 [DOI] [PubMed] [Google Scholar]
  21. Heinrichs A. J. 2013. The Penn state particle separator. Penn State Extension, University Park, PA: DSE 2013-186; p. 1–8. [Google Scholar]
  22. Keunen J. E., Plaizier J. C., Kyriazakis L., Duffield T. F., Widowski T. M., Lindinger M. I., and McBride B. W.. . 2002. Effects of a subacute ruminal acidosis model on the diet selection of dairy cows. J. Dairy Sci. 85:3304–3313. doi: 10.3168/jds.S0022-0302(02)74419-6 [DOI] [PubMed] [Google Scholar]
  23. Krause K. M., Combs D. K., and Beauchemin K. A.. . 2003. Effects of increasing levels of refined cornstarch in the diet of lactating dairy cows on performance and ruminal pH. J. Dairy Sci. 86:1341–1353. doi: 10.3168/jds.S0022-0302(03)73719-9 [DOI] [PubMed] [Google Scholar]
  24. Krause K. M., and Oetzel G. R.. . 2006. Understanding and preventing subacute ruminal acidosis in dairy herds: a review. Anim. Feed Sci. Technol. 126:215–36. doi: 10.1016/j.anifeedsci.2005.08.004 [DOI] [Google Scholar]
  25. Leonardi C., and Armentano L. E.. . 2003. Effect of quantity, quality, and length of alfalfa hay on selective consumption by dairy cows. J. Dairy Sci. 86:557–564. doi: 10.3168/jds.S0022-0302(03)73634-0 [DOI] [PubMed] [Google Scholar]
  26. Madruga A., González L. A., Mainau E., Ruíz de la Torre J. L., Rodríguez-Prado M., Manteca X., and Ferret A.. . 2018. Effect of increasing the level of alfalfa hay in finishing beef heifer diets on intake, sorting, and feeding behavior. J. Anim. Sci. 96:1–10. doi: 10.1093/jas/skx051 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Madruga A., Mainau E., González L. A., Rodríguez-Prado M., Ruíz de la Torre J. L., Manteca X., and Ferret A.. . 2017. Effect of forage source included in total mixed ration on intake, sorting and feeding behavior of growing heifers fed high-concentrate diets. J. Anim. Sci. 95:3322–3330. doi: 10.2527/jas.2017.1608 [DOI] [PubMed] [Google Scholar]
  28. Maulfair D. D., Fustini M., and Heinrichs A. J.. . 2011. Effect of varying total mixed ration particle size on rumen digesta and fecal particle size and digestibility in lactating dairy cows. J. Dairy Sci. 94:3527–3536. doi: 10.3168/jds.2010-3718 [DOI] [PubMed] [Google Scholar]
  29. Mertens D. R. 1997. Creating a system for meeting the fiber requirements of dairy cows. J. Dairy Sci. 80:1463–1481. doi: 10.3168/jds.S0022-0302(97)76075-2 [DOI] [PubMed] [Google Scholar]
  30. Mertens D. R. 2002. Measuring fiber and its effectiveness in ruminant diets. In: Proceedings of Plains Nutrition Council Spring Conference, San Antonio, TX AREC 02-20; p. 40–66. [Google Scholar]
  31. Miller-Cushon E. K., Bergeron R., Leslie K. E., Mason G. J., and DeVries T. J.. . 2013. Effect of early exposure to different feed presentations on feed sorting of dairy calves. J. Dairy Sci. 96:4624–4633. doi: 10.3168/jds.2013-6670 [DOI] [PubMed] [Google Scholar]
  32. NASEM. 2016. Nutrient requirements of beef cattle. 8th rev. ed.Washington, DC: National Academies Press. doi: 10.17226/19014 [DOI] [Google Scholar]
  33. Oshita T., Nonaka K., Kume S., and Nakui T.. . 2004. Effects of forage type on particle size distribution of ruminal digesta and faeces of non-lactating cows fed high quality forage. Livest. Prod. Sci. 91:107–115. doi: 10.1016/j.livprodsci.2004.07.015 [DOI] [Google Scholar]
  34. Owens F. N., Secrist D. S., Hill W. J., and Gill D. R.. . 1998. Acidosis in cattle: a review. J. Anim. Sci. 76:275–286. doi: 10.2527/1998.761275x [DOI] [PubMed] [Google Scholar]
  35. Pitt R. E., Van Kessel J. S., Fox D. G., Pell A. N., Barry M. C., and Van Soest P. J.. . 1996. Prediction of ruminal volatile fatty acids and pH within the net carbohydrate and protein system. J. Anim. Sci. 74:226–244. doi: 10.2527/1996.741226x [DOI] [PubMed] [Google Scholar]
  36. Plaizier J. C., Krause D. O., Gozho G. N., and McBride B. W.. . 2008. Subacute ruminal acidosis in dairy cows: the physiological causes, incidence and consequences. Vet. J. 176:21–31. doi: 10.1016/j.tvjl.2007.12.016 [DOI] [PubMed] [Google Scholar]
  37. Poppi D. P., Norton B. W., Minson D. J., and Hendricksen R. E.. . 1980. The validity of the critical size theory for particles leaving the rumen. J. Agric. Sci. 94:275–280. doi: 10.1017/S0021859600028859 [DOI] [Google Scholar]
  38. Stock R., and Britton R.. . 1993. Acidosis in feedlot cattle. In: C. Parrott. 1993. Secondary benefits from feeding Rumensin. In: Scientific Update on Rumensin/Tylan for the Professional Feedlot Consultant. Indianapolis, IN:Elanco Animal Health; p. A1-A13. [Google Scholar]
  39. Teimouri Yansari A., Valizadeh R., Naserian A., Christensen D. A., Yu P., and Eftekhari Shahroodi F.. . 2004. Effects of alfalfa particle size and specific gravity on chewing activity, digestibility, and performance of Holstein dairy cows. J. Dairy Sci. 87:3912–3924. doi: 10.3168/jds.S0022-0302(04)73530-4 [DOI] [PubMed] [Google Scholar]
  40. Van Soest P. J., Robertson J. B., and Lewis B. A.. . 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 74:3583–3597. doi: 10.3168/jds.S0022-0302(91)78551-2 [DOI] [PubMed] [Google Scholar]
  41. Weiss C. P., Gentry W. W., Meredith C. M., Meyer B. E., Cole N. A., Tedeschi L. O., McCollum F. T., and Jennings J. S.. . 2017. Effects of roughage inclusion and particle size on digestion and ruminal fermentation characteristics of beef steers. J. Anim. Sci. 95:1707–1714. doi: 10.2527/jas.2016.1330 [DOI] [PubMed] [Google Scholar]
  42. Yang W. Z., and Beauchemin K. A.. . 2009. Increasing physically effective fiber content of dairy cow diets through forage proportion versus forage chop length: chewing and ruminal pH. J. Dairy Sci. 92:1603–1615. doi: 10.3168/jds.2008-1379 [DOI] [PubMed] [Google Scholar]
  43. Yang W. Z., Beauchemin K. A., and Rode L. M.. . 2001. Barley processing, forage:concentrate, and forage length effects on chewing and digesta passage in lactating cows. J. Dairy Sci. 84:2709–2720. doi: 10.3168/jds.S0022-0302(01)74725-X [DOI] [PubMed] [Google Scholar]
  44. Yeates M. P., Tolkamp B. J., Allcroft D. J., and Kyriazakis I.. . 2001. The use of mixed distribution models to determine bout criteria for analysis of animal behaviour. J. Theor. Biol. 213:413–425. doi: 10.1006/jtbi.2001.2425 [DOI] [PubMed] [Google Scholar]
  45. Zebeli Q., Dijkstra J., Tafaj M., Steingass H., Ametaj B. N., and Drochner W.. . 2008. Modeling the adequacy of dietary fiber in dairy cows based on the responses of ruminal pH and milk fat production to composition of the diet. J. Dairy Sci. 91:2046–2066. doi: 10.3168/jds.2007-0572 [DOI] [PubMed] [Google Scholar]
  46. Zebeli Q., Tafaj M., Steingass H., Metzler B., and Drochner W.. . 2006. Effects of physically effective fiber on digestive processes and milk fat content in early lactating dairy cows fed total mixed rations. J. Dairy Sci. 89:651–668. doi: 10.3168/jds.S0022-0302(06)72129-4 [DOI] [PubMed] [Google Scholar]

Articles from Journal of Animal Science are provided here courtesy of Oxford University Press

RESOURCES