Inclusion of quebracho tannin extract in a high-roughage cattle diet alters digestibility, nitrogen balance, and energy partitioning

Abstract

Condensed tannins (CT) might improve animal and system-level efficiency due to enhanced protein efficiency and reduced CH₄. This study evaluated the impact of quebracho tannin (QT) extract fed at 0%, 1.5%, 3%, and 4.5% of dry matter (DM), within a roughage-based diet on apparent digestibility of DM, organic matter (OM), fibrous fractions, and N retention and energy partitioning of growing steers (236 ± 16 kg BW). A Latin rectangle design with eight animals and four periods was used to determine the whole-animal exchange of CO₂, O₂, and CH₄ as well as the collection of total feces and urine over a 48-h period, using two open-circuit, indirect calorimetry respiration chambers. Following the removal of steers from respiration chambers, rumen inoculum was collected to determine ruminal parameter, including volatile fatty acids (VFA) and ammonia. Animals were fed a 56.5% roughage diet at 1.7% BW (dry matter basis). Dry matter and gross energy intakes were influenced by the level of QT inclusion (P ≤ 0.036). Digestibility of DM, OM, and N was reduced with QT inclusion (P < 0.001), and fiber digestibility was slightly impacted (P > 0.123). QTs altered the N excretion route, average fecal N-to-total N ratio excreted increased 14%, and fecal N-to-urinary N ratio increased 38% (P < 0.001) without altering the retained N. Increased fecal energy with QT provision resulted in reduced dietary digestible energy (DE) concentration (Mcal/kg DM; P = 0.024). There were no differences in urinary energy (P = 0.491), but CH₄ energy decreased drastically (P = 0.007) as QT inclusion increased. Total ruminal VFA concentration did not differ across treatments, but VFA concentration increased linearly with QT inclusion (P = 0.049). Metabolizable energy (ME) was not affected by the QT rate, and the conversion efficiency of DE-to-ME did not differ. Heat energy decreased (P = 0.013) with increased QT provision likely due to changes in the DE intake, but there was no difference in retained energy. There were no differences for retained energy or N per CO₂ equivalent emission produced (P = 0.774 and 0.962, respectively), but improved efficiency for energy retention occurred for 3% QT. We concluded that QT provided up to 4.5% of dry matter intake (about 3.51% of CT, dry matter basis) does not affect N and energy retention within the current setting. Feeding QT reduced energy losses in the form of CH₄ and heat, but the route of energy loss appears to be influenced by the rate of QT inclusion.

Introduction

Ruminant species are a vital source of human-edible protein and essential nutrients due to their capacity to upgrade low-quality feedstuffs (CAST, 1999) but gaseous byproducts, such as ammonia (NH₃), carbon dioxide (CO₂), and methane (CH₄), produced during anaerobic microbial fermentation have a perceived negative impact on the environment by possibly augmenting global warming. These gaseous byproducts are a result of microbial metabolism and assist in maintaining ruminal homeostasis (McAllister and Newbold, 2008), but they can also negatively affect the host animal by reducing energetic efficiency. In animal agriculture, CH₄ and nitrous oxide (N₂O) are considered major greenhouse gases (GHG), with enteric fermentation (~40%) and manure on pasture (~15%) representing 47% to 56% of total global agricultural non-CO₂ emissions in 2010 (Smith et al., 2014; Tubiello et al., 2014). However, on CO₂ equivalent emissions (CO₂e), basis agriculture accounts for approximately 14% of total global GHG emissions (IPCC, 2014) though discrepancies exist in these estimates (Tedeschi and Fox, 2018).

Although feed-grade antimicrobials may decrease ruminant morbidity and alter rumen dynamics, promoting feed and growth efficiency (Yang and Russell, 1993; Guan et al., 2006), consumer consumer concerns surrounding food safety have prompted the pursuit of natural rumen modulators (Patra and Saxena, 2010). Because condensed tannins (CT), a diverse group of naturally occurring secondary metabolites, display reactivity when in proximity to proteins and carbohydrates (Haslam, 1989), they could potentially serve as a ruminant feed additive. Although dependent upon the source, the inclusion of CT approaching 4% of dry matter (DM) has commonly resulted in reduced dry matter intake (DMI) and ruminal digestibility due to astringency, reduced passage rate, and increased microbial inhibition (Landau et al., 2000; Piñeiro-Vázquez et al., 2017). However, lower rates of CT have displayed the potential to improve nutrient and energy efficiency by reducing CH₄ production and ruminally protecting nitrogen (N) (Huyen et al., 2016; Piñeiro-Vázquez et al., 2017). The objective of this study was to determine the effect of feeding quebracho CT extract at four inclusion rates within a roughage-based diet on apparent digestibility of fibrous fractions, nitrogen retention, energy partitioning, and ruminal parameters.

Materials and Methods

The animals used in this experiment were registered and cared for according to guidelines approved by the Institutional Animal Care and Use Committee (AUP 2017-0306) at Texas A&M University.

Experimental design, equipment, and data collection

A 4 × 8 Latin rectangle design (Kuehl, 2000) consisting of four periods and eight British crossbred steers (236 ± 16 kg BW) was used to determine the effects of quebracho (Schinopsis balansae) CT extract (QT; SILVATEAM, San Michele, Mondovi, Italy) at 0%, 1.5%, 3%, and 4.5% of DM (QT₀, QT_1.5, QT₃, and QT_4.5) so that each treatment was replicated by two animals within each period. The levels of QT used in this study were chosen so that the dosage levels would encompass levels commonly used in forage-based beef cattle feeding trials while emulating levels expected to be observed in a grazing scenario. Quebracho extract CT fractions and total CT were determined by the protocol of Terrill et al. (1992) using the proposed modifications described by Wolfe et al. (2008). Measurements of protein precipitable phenolics (PPP), a proxy for protein-binding capacity, were completed in accordance with Hagerman and Butler’s (1978) scaled-down method as modified to determine protein precipitability of CT in two duplicate crude plant extracts (Naumann et al., 2014). The QT extract contained 77.99% total CT (36.07%, 41.43%, and 0.49% of extractable, protein-bound, and fiber-bound CT, respectively) and 31.47% PPP. The Ruminant Nutrition System (http://www.nutritionmodels.com/rns.html [accessed October 22, 2019]; Tedeschi and Fox, 2018) was used to formulate a roughage-based total mixed ration (56.5% roughage, DM basis; Table 1), with the addition of QT serving as dietary treatments. DMI of the basal diet was restricted to 1.7% of BW, to approximate a maintenance level of energy intake. The addition of pre-weighed QT were hand-mixed into individual animal feed prior to provision. Animals were housed outside within pens (9 × 12 m) fitted with Calan-gate feeders (American Calan, Northwood, NH). Feeding occurred once daily at 0800 hours and animals were provided free access to water; all feed was consumed within 3 h of provision. For each experimental period, the dietary adaptation of each animal spanned 12 d followed by relocation to open-circuit, indirect calorimetry respiration chambers for the measurement of gas exchange and total feces and urine over 48 h. Data from two steers were collected at one time given the availability of the respiration chambers, and the animal sequence was randomized prior to the commencement of the trial but remained consistent for the duration of the experiment. Upon completion of a 48-h measurement period, chambers were recalibrated, and a new pair of animals entered the chambers. Therefore, gas exchange and excretory data collection spanned 8 d within each period.

Table 1.

Ingredient and chemical composition of the high-roughage total-mixed ration utilized for metabolism and manure gas flux

Items1	Basal diet, %
Ingredient composition, % DM
Cottonseed hulls	37.00
Cracked corn	33.00
Alfalfa pellets	11.50
Bermudagrass hay	8.00
Molasses	7.00
Mineral	2.50
Urea	1.00
Chemical composition2
DM, %	87.20
CP, % DM	12.90
Soluble protein, % CP	45.05
aNDF, % DM	48.70
ADF, % DM	35.85
Lignin, % DM	10.27
Crude fat, % DM	3.21
Sugar, % DM	3.30
Starch, % DM	20.30
NFC, % DM	32.00
Ash, % DM	5.86
Calcium	0.75
Phosphorus	0.43
TDN, %	60.95
NEm, Mcal/kg	1.32
NEg, Mcal/kg	0.76
GE3, Mcal/kg	3.85

¹Items are feed ingredients and chemical composition of diets evaluated by Cumberland Valley Analytical Services (Waynesboro, PA).

²DM, dry matter; CP, crude protein; aNDF, neutral detergent fiber with amylase and sodium sulfate; ADF, acid detergent fiber; NFC, non-fiber carbohydrates; NE_m, net energy for maintenance; NE_g, net energy for gain; TDN, total digestible nutrients.

³GE measured by bomb calorimeter.

Open-circuit, indirect calorimetry respiration chambers

For all periods, on Day 12 for a pair of steers, BW were recorded before entering a predetermined single-stall open-circuit, respiration calorimetry chamber. Because all animals rapidly consumed all feed provided, the recorded BW were equivalent to 18-h shrunk BW (SBW) without water withdrawal, but no feed withdrawal was imparted. Respiration chambers had a volume of 11.5 m³ and were configured in a pull-type arrangement using a mass flow system (Flowkit model FK-500; Sable System Int., Henderson, NV), creating a slight negative pressure within chambers. Within this system, ambient air (baseline) and air from each chamber were sampled via a multiplexer (Respirometry Multiplexer V 2.0, Sable System Int., Henderson, NV) and an FC-1B O₂ analyzer, CA-2A CO₂ analyzer, and MA-10 CH₄ analyzer (Sable System Int., Henderson, NV) rotating every 4 min. Before initiating gas sampling for a pair of animals, SBW, dietary energy density, and volume of the chambers were used to calculate the time required for gas concentrations to stabilize and flow rate needed to maintain maximal chamber CO₂ concentrations between 0.35% and 0.37%. The assumed gas concentrations of baseline ambient air (O₂ = 20.95%, CO₂ = 0.04%, and CH₄ = 0.00%) were used to calibrate O₂, CO₂, and CH₄ analyzers using known gases, N (99.999% N₂; zeroing gas) and SPAN (19.4%, 1.1%, and 0.1% O₂, CO₂, and CH₄, respectively) before each set of steers entered for data collection. The measured gas was scrubbed of water vapor using fresh Drierite desiccant (Hammond Drierite Co. Ltd., Xenia, OH) for each 48-h collection, and the rate of O₂, CO₂, and CH₄ uptake and production (VO₂, VCO₂, and VCH₄; L/min) were determined (Lighton, 2008). Prior to each period, the sealing condition of each chamber was checked using a manometer. Once adequate chamber sealing was achieved, chamber measurements were validated using gravimetric N injection technique (Cooper et al., 1991) to perform oxygen dilutions, where expected (20.95% × volume of N) and observed VO₂ uptake was verified with an acceptable recovery ranging from 95% to 105% (Li et al., 2019). All flow rates were adjusted to a dry-gas basis by correcting for water vapor concentration calculated from temperature and relative humidity (RH) (Lighton, 2008).

Temperature and humidity

Chambers were maintained at thermoneutral conditions (18 ± 0.55 °C; 55 ± 1.2% RH), as determined by the temperature-humidity index, and corresponding to 18.9 °C based upon the current effective temperature index (Tedeschi and Fox, 2018). Thermoneutral environments were maintained using a line voltage thermostat (Ranco Enterprises, Inc., Model# ETC-111000-000) and dehumidifier (Hisense USA, Model# DH-70K1SDLE) with environmental conditions monitored using digital HOBO temperature and humidity data loggers (Onset Computer Corporation, Model# UX100- 003). Water intake and activity within chambers were monitored using a water meter (Neptune Technology Group, Inc., Model# T10-DR-075-G-F) and security cameras (FLIR Lorex Inc., Model# LBV1511W). Additionally, each chamber was equipped with a metabolism stand to allow the collection of total urine and fecal output. Following the 48-h period within chambers, rumen inoculum was collected, and animals were returned to Calan-gate pens to begin 12-d adaptation to subsequent diets for the next experimental period.

Sample collection, preservation, and analyses

Batch samples (250 g) of the basal diet were collected daily for the last 10 d of each period. A 50-g feed composite from each period was shipped to Cumberland Valley Analytical Services (Waynesboro, PA) for chemical analysis of DM (Goering and Van Soest, 1970), neutral detergent fiber with the addition of amylase and sodium sulfite (aNDF; Van Soest et al., 1991), acid detergent fiber (ADF; Method# 973.18; AOAC, 2000), ADF lignin using a modified version of the Goering and Van Soest (1970) method, crude protein (CP; Method# 990.03; AOAC, 2000) (Leco FP-528 Nitrogen Combustion Analyzer, Leco Corporation, St. Joseph, MO), soluble CP (Krishnamoorthy et al., 1982), fat (Method# 2003.05; AOAC, 2006), starch (Hall, 2009), sugar (Dubois et al., 1956), a complete mineral panel (Method# 985.01; AOAC, 2000) using a Perkin Elmer 5300 DV ICP (Perkin Elmer, Shelton, CT), and calculated nonfiber carbohydrates (NFC), total digestible nutrients, and net energies.

During the duration of this experiment, no feed refusals or orts or losses were observed. Following the removal of animals from chambers, feces were weighed, homogenized, subsampled and stored in a −20 °C freezer. Fecal samples were dried at 55 °C for 72 h or until weight loss ceased, then ground to pass through a 2-mm screen using a Wiley mill (Thomas Scientific, Swedesboro, NJ), and analyzed for DM, organic matter (OM), CP, aNDF, ADF, and gross energy (GE).

Total urine collection, acidification, and removal from chambers were accomplished using the method discussed by Crossland et al. (2018); total urine was weighed, and two 100-mL subsamples were stored at −20 °C. Total urinary N analysis was performed by Servi-Tech laboratories (Amarillo, TX) using the Dumas combustion method (Method# 990.03; AOAC, 2000).

Upon removal of steers from the respiration chambers, 500 mL of rumen inoculum was collected using an esophageal tube connected to a vacuum pump. Rumen inoculum was filtered through eight layers of cheesecloth and pH was immediately measured. Inoculum samples were allocated into duplicate containers for the preservation of volatile fatty acids (VFA), NH₃, and protozoa. Preservation methods were 8 mL of inoculum and 2 mL of 25% (wt/vol) metaphosphoric acid solution for VFA analyses, 2 mL of inoculum to 8 mL of 0.1 N HCl acid solution for NH₃ analyses, and 1 mL of inoculum and 10 mL of ethanol for protozoa counts. All samples were stored at –20 °C. The method of Chaney and Marbach (1962) was employed for colorimetric determination of ruminal NH₃ concentrations using and a spectrophotometer (Unico UV-2000; UNICO Instruments Co., Ltd., Shanghai, China). Allantoin and uric acid were measured colorimetrically using a commercial assay. VFAs were determined with an Agilent 6890N (Agilent Technologies, Santa Clara, Ca) gas chromatograph using helium as the carrier gas. Protozoa counts were determined by methods described by Dehority (1984) without staining. Using a Sedgewick Rafter counting chamber, protozoa within a 1-mL aliquot of the sample were counted using Nikon Eclipse E200 microscope (Nikon Corporation Tokyo, Japan) at 100× magnification with a 0.5-mm square counting grid; 25 random grids from the entire chamber surface were counted for each sample.

Energy partitioning and nitrogen balance

Gross energy was obtained on feed, fecal, urine, and QT samples using a bomb calorimeter (Parr adiabatic calorimeter; Parr Instruments Co., Moline, IL). The average measured GE value for QT was 5,099.75 cal/g DM. Then, GE intake (GEI; Mcal/d) was computed by summing the GE of the offered basal diet and QT, the GE of respective amendments was determined by multiplying the caloric value by kilograms offered. Fecal and urinary energy (FE and UE; Mcal/d) were calculated by multiplying the GE of respective samples by the daily output. Gaseous energy (GASE; Mcal/d) was determined by multiplying daily CH₄ production (L/d) by the density of CH₄ at normal temperature and pressure (0.668 g/L at 20 °C and 1 atm) and the energy density of CH₄ (13.3 Mcal/kg). Heat energy (HE) was calculated according to Brouwer (1965): HE (Mcal/d) = (3.866 × VO₂) + (1.2 × VCO₂) − (0.518 × VCH₄) − (1.431 × Urinary N). Final values of energy partitioning were calculated as follows: digestible energy intake (DEI; Mcal/d) = GEI − FE; metabolizable energy intake (MEI; Mcal/d) = DE − (UE + GASE); retained energy (RE; Mcal/d) is assumed as RE = MEI − HE, where MEI was calculated as the observed dietary metabolizable energy (ME) content (Mcal/kg) multiplied by the DMI (kg/d) of diet. Carbon dioxide equivalent emissions were calculated by multiplying daily production of CH₄ by its 100-year warming potential value of 28 (IPCC, 2014), with total CO₂e being the sum of CO₂ and CO₂e from CH₄. Retained energy and retained nitrogen (RN) per CO₂e produced were used as measures of efficiency.

Statistical analyses

Statistical procedures were performed using PROC MIXED of SAS (SAS Institute Inc., Cary, NC). All data were evaluated using a Latin rectangle design, with animals and periods as random factors. To account for any carry-over effects, the previous diet was included within the initial model (Ratkowsky et al., 1993). Because preliminary results indicated no effect of previous diet or improvement in goodness-of-fit; therefore, the carry-over effect (i.e., previous diet) was removed from the statistical model. The significance of covariance estimates for the random effects was tested by applying the Wald test using the COVTEST statement. Mean comparisons were performed using the LSMEANS statement with the adjustment proposed by Tukey–Kramer for all significant effects. Additional hypotheses were tested using the CONTRAST statement using an orthogonal contrast to determine the effect of QT inclusion, as well as orthogonal polynomial terms for linear and quadratic trends of QT doses assuming equally spaced levels of QT. Significance was established at P ≤ 0.05 and tendencies were assumed at P ≤ 0.10.

Results and Discussion

Intake, excretion, and digestibility

Table 2 shows the effect of QT upon intake and excretion profiles. There was no effect of QT upon daily water intake, water as a proportion of SBW, or water intake-to-DMI ratios (P > 0.380). Similarly, Landau et al. (2000) did not observe any effect of Aspidosperma quebracho CT on water consumption. During the experimental periods, there were no feed refusals. However, DMI and organic matter intake (OMI) were elevated (P < 0.036) in treatments receiving QT with no differences in the consumption of aNDF or ADF (P > 0.186) being observed. As all treatments received the basal diet at 1.7% of SBW with QT extract being added to the basal diet, the resultant DMI and OMI were elevated in treatments receiving QT, but potentially digestible nutrients remained similar across all treatments when assuming QT have minimal digestibility. Provision of CT commonly decreases DMI due to negative associations resulting from astringency and reduced passage rate (Landau et al., 2000; Frutos et al., 2004), as well as potential gastrointestinal distress at higher rates (Dawson et al., 1999; Hervás et al., 2003). Preliminary data from our research group utilizing identical diets noted reduced intake and indicators of potential gastrointestinal distress when limit-feeding with QT. However, in the current study, animals were limit-fed with all treatments being readily consumed, and no dietary aversion observed.

Table 2.

Effect of quebracho tannin percent on feed consumption and excretion profiles of steers fed high-roughage diets

Items	Quebracho extract, % of feed DM						Contrast1P-values
	02	1.5	3	4.5	SEM	P-value	L	Q	QT
SBW, kg	238.14	235.87	235.08	235.02	2.19	0.465	0.159	0.484	0.132
Water intake, kg/d	8.15	9.45	7.92	7.21	1.37	0.440	0.324	0.311	0.972
Water intake, % SBW	3.25	3.87	3.25	3.00	0.60	0.530	0.481	0.319	0.951
Water intake:DMI	2.01	2.33	1.90	1.69	0.33	0.380	0.204	0.274	0.893
DMI, kg/d	4.01b	4.03ab	4.07ab	4.13a	0.03	0.036	0.005	0.522	0.054
OMI, kg/d	3.78b	3.80ab	3.84ab	3.89a	0.03	0.026	0.003	0.517	0.041
aNDFI, kg/d	2.34	2.31	2.31	2.31	0.02	0.464	0.159	0.484	0.132
ADFI, kg/d	1.55	1.54	1.53	1.53	0.01	0.518	0.177	0.561	0.157
Fecal DM, kg/d	1.49a	1.61ab	1.61ab	1.77b	0.06	0.003	<0.001	0.594	0.003
Fecal DM, % SBW	0.62a	0.67ab	0.68ab	0.75b	0.02	<0.001	<0.001	0.692	<0.001
Fecal DM, %	27.55b	28.79ab	30.06a	27.56b	0.88	0.031	0.646	0.007	0.099
Fecal OM, kg/d	1.34a	1.45ab	1.43ab	1.59b	0.05	0.002	<0.001	0.513	0.003
Fecal aNDF, kg/d	0.99	1.03	1.00	1.09	0.04	0.186	0.079	0.450	0.213
Fecal ADF, kg/d	0.72	0.75	0.72	0.78	0.03	0.249	0.170	0.433	0.334
Urine, kg/d	5.36a	5.58a	4.26b	4.24b	0.33	<0.001	<0.001	0.602	0.025
Urine, % SBW	2.22a	2.32a	1.80b	1.77b	0.29	0.001	<0.001	0.556	0.046

¹Contrasts: L, linear; Q, quadratic; QT, no quebracho vs. quebracho inclusion.

²Quebracho extract contained 77.99% total condensed tannins, 28.9% protein precipitable phenolics, and 5.099 kcal/g of DM.

^a,bLeast squares means in a row with different superscripts differ at P ≤ 0.05.

Daily fecal output parameters were affected (P < 0.003) by QT supplementation. Daily fecal DM, OM, and DM as a proportion of SBW demonstrated linear increases with greater QT inclusion (P < 0.001). However, there were no differences for daily fecal aNDF or ADF (P > 0.186). A linear increase in fecal DM production with QT inclusion rate is presumed to be a result of reduced ruminal degradation, particularly in diets containing high levels of fibrous carbohydrates (Ahnert et al., 2015; Aguerre et al., 2016). However, this may be partly explained by the presence of QT in the feces that would influence fecal DM and OM but not fecal aNDF or ADF, similar to intake parameters. In contrast to fecal excretion, daily urine production and urine as a proportion of SBW decreased (P ≤ 0.001) in a linear fashion with increased provision of QT. The reduction at the two highest supplementation rates was unexpected as CT in other studies have not reported an effect on urinary output volume (Ahnert et al., 2015; Aguerre et al., 2016).

The inclusion of QT affected DM and OM digestibilities (P ≤ 0.001), with clear linear trends (Table 3). The inclusion of QT influenced DM digestibility (DMD) and OM digestibility (OMD) as QT_1.5 and QT₃ were reduced by 5%, on average, and QT_4.5 was decreased by 11%. There was a slight negative effect of QT on aNDF or ADF digestibilities (P > 0.123). Linear trends were observed (P ≤ 0.087) for both coefficients as QT_4.5 reduced aNDF and ADF digestibilities approximately 9% on average. The decrease in DM and OM digestibilities agrees with the study of Piñeiro-Vázquez et al. (2017), where the authors observed a reduction in DMD and OMD with QT supplementation in heifers fed a forage-based diet. The greater degree of reduction for OMD compared to aNDF and ADF suggested a reduced ruminal digestibility of NFC. de Oliveira et al. (2007) observed a similar outcome when feeding sorghum silage, as ruminal digestibility of starch decreased 7% in high-CT sorghum, but total-tract digestibility did not differ.

Table 3.

Effect of quebracho tannin percent on feed digestibility and N metabolism of steers fed high-roughage diets

Items	Quebracho extract, % of feed DM						Contrast1P-values
	02	1.5	3	4.5	SEM	P-value	L	Q	QT
DMD, %	62.80a	59.74a	59.33ab	55.72b	1.39	<0.001	<0.001	0.782	<0.001
OMD, %	64.60a	61.39a	61.58a	57.64b	1.40	0.001	<0.001	0.719	0.001
aNDFD, %	57.81	55.96	56.44	52.70	2.07	0.123	0.035	0.526	0.117
ADFD, %	53.43	51.60	52.76	48.83	2.21	0.204	0.087	0.508	0.205
N digestibility, %	48.66a	39.77b	41.10b	35.49b	2.24	<0.001	<0.001	0.314	<0.001
Feed N, g/d	66.38	65.75	65.45	65.61	0.55	0.391	0.159	0.328	0.106
Fecal N, g/d	34.11a	39.75b	38.44b	42.10b	1.44	<0.001	<0.001	0.341	<0.001
Fecal N, % N intake	51.34b	60.23a	58.90a	64.51a	2.24	<0.001	<0.001	0.314	<0.001
Urine N, g/d	21.23a	17.42ab	15.57ab	13.44b	2.04	0.007	<0.001	0.567	0.002
Urine N, % N intake	31.78a	26.27ab	23.59ab	21.04b	3.21	0.019	0.002	0.521	0.005
Fecal N, % N excreted	62.01b	69.57a	71.81a	75.69a	2.45	<0.001	<0.001	0.299	<0.001
Fecal N:Urinary N	1.68c	2.36bc	2.70ab	3.24a	0.30	<0.001	<0.001	0.749	<0.001
Retained N, g/d	11.04	8.56	11.44	10.07	2.81	0.744	0.994	0.782	0.661
Retained N, % N intake	16.89	13.50	17.50	14.46	4.63	0.795	0.825	0.958	0.652

¹Contrasts: L, linear; Q, quadratic; QT, no quebracho vs. quebracho inclusion.

²Quebracho extract contained 77.99% total condensed tannins, 28.9% protein precipitable phenolics, and 5.099 kcal/g of DM.

^a–cLeast Squares means in a row with different superscripts differ at P ≤ 0.05.

Apparent N digestibility was reduced (P < 0.001); all QT inclusion levels decreased 20% on average relative to QT₀ but there were no differences in the digestibility among treatments receiving QT. The digestibility of N was reduced to a larger degree than DM, OM, aNDF, or ADF digestibilities; this finding is consistent with previous research using QT that observed greater reductions in apparent digestibility of N relative to DM and aNDF (Aguerre et al., 2016). The prominent reduction in N digestibility observed when feeding CT appears to be a product of direct complexation with soluble proteins and the accompanied lesser degradation of feedstuffs, restricting the availability of cell-wall associated proteins and decreasing the absolute amount of ruminally degradable protein. This finding was substantiated by Beauchemin et al. (2007) and Koenig and Beauchemin (2018) in which the authors witnessed a large linear reduction in total-tract digestibility of neutral detergent and acid detergent insoluble N when QT was provided in silage and concentrate-based diets. Reduced cell-wall digestibility would result in CT having a more pronounced effect upon diets with a larger concentration of B₂ and B₃ N fractions, but in diets with greater relative proportions of nonprotein N and B₁ proteins, CT could potentially assist in improving N use efficiency through reduced proteolysis and increased microbial utilization of NH₃.

The provision of QT at any level resulted in greater daily fecal N (P < 0.001) than QT₀, but QT_1.5 exhibited the greatest fecal N concentration. A linear trend was observed for fecal N (% of N intake) with QT₀ lower than all other treatments (P < 0.001) and QT₃ having the least for treatments receiving QT. Correspondingly, daily urinary N excreted and urinary N (% of N intake) decreased with increased QT supplementation (P = 0.007 and P = 0.019, respectively) as QT₀ resulted in greater urinary N relative to the QT treatments (P = 0.002). The inclusion of QT drastically altered the N excretion route, with fecal N (% of N excreted) increasing 14% and the fecal N-to-urinary N ratio was 38% greater on average with QT supplementation (P < 0.001). However, QT did not affect N retention (P = 0.744). Similar to the current study, Grainger et al. (2009) witnessed increased fecal N and reduced urinary N with increasing CT levels, but no difference was observed for retained N. Due to the shift of N excretion from urine to feces with QT inclusion, N digestibility becomes artificially reduced, thereby making apparent digestibility unsuitable for estimating N retention when diets include CT.

In the current study, protein binding is evidenced by the considerable alteration in N excretion route. However, apparent N digestibility and retained N (% of N intake) are reduced relative to preliminary research from within our lab group (data not shown) utilizing the same diet and treatments. Decreased N utilization could indicate less post-ruminal disassociation of QT–protein complexes, but the animal physiological stage and the previous plane of nutrition may partly explain the discrepancy between studies. As fecal N is less volatile than urinary N, shifting the excretion of N to the feces can potentially assist in reducing, or at least slowing, environmental emissions and improve system efficiency by decreasing NH₃ and N₂O production, possibly improving N cycling within terrestrial ecosystems (Ndegwa et al., 2008; Patra and Saxena, 2011). Although there were no differences in N retention, the inclusion of QT may offer a method of improving system-level efficiency if whole-animal emissions are accounted for (i.e., enteric and excreta gas emissions).

Rumen parameters and purine derivatives

The feeding of QT did not have an observed impact on pH or protozoa (P ≥ 0.321; Table 4). Total VFA concentration increased linearly with QT inclusion (P = 0.049) and the provision of QT tended to result in more VFA concentration relative to QT₀ (P = 0.079). Across treatments, there was no difference in acetate concentration, but propionate concentration increased linearly with QT provision (P = 0.002) as QT inclusion resulted in more propionate production compared with QT₀ (P = 0.012). The resultant acetate-to-propionate ratio was lowest for QT_4.5 with the addition of QT, resulting in a lower acetate-to-propionate ratio compared to QT₀ (P < 0.001). Previous research has observed a reduction in acetate-to-propionate ratios by reducing the molar proportion of acetate as a consequence of lesser fiber carbohydrate digestion (Carulla et al., 2005; Beauchemin et al., 2007). However, when feeding QT in a high-roughage diet, Dschaak et al. (2011) observed a slight reduction in total VFA concentration and acetate-to-propionate ratio, but digestibility was not affected. In the current setting, increased propionate production resulted in the reduced acetate-to-propionate ratio in animals receiving QT with no effect on fiber digestibility being observed. Results similar to ours have been observed in vitro with increased propionate production thought to be a consequence of rumen microflora shifting toward propionate-producing bacteria (Hassanat and Benchaar, 2013).

Table 4.

Effect of quebracho tannin percent within a high-roughage diet on rumen and urine parameters

Items	Quebracho extract, % of feed DM						Contrast1P-values
	02	1.5	3	4.5	SEM	P-value	L	Q	QT
pH	6.96	7.00	6.92	6.92	0.07	0.619	0.386	0.614	0.870
Protozoa, log10/mL	5.73	5.63	5.66	5.74	0.06	0.321	0.791	0.074	0.347
Total VFA, mmol/L	46.08	58.75	60.05	70.58	11.24	0.225	0.049	0.894	0.079
Acetate, mmol/L	31.42	38.41	38.65	42.00	7.65	0.578	0.202	0.740	0.202
Propionate, mmol/L	6.58b	9.25ab	9.43ab	13.07a	1.80	0.015	0.002	0.708	0.012
Acetate:Propionate	4.68a	4.14a	4.11a	3.25b	0.25	<0.001	<0.001	0.357	<0.001
Butyrate, mmol/L	0.91	1.03	0.95	0.97	0.08	0.540	0.693	0.416	0.288
Isobutyrate, mmol/L	5.07b	7.41ab	8.08ab	10.70a	0.07	0.021	0.002	0.903	0.012
Isovalerate, mmol/L	1.38b	1.79b	2.16ab	2.96a	0.09	0.294	0.001	0.515	0.014
Valerate, mmol/L	0.71	0.85	0.77	0.86	0.09	0.294	0.185	0.734	0.120
Total BCVFA, mmol/L	3.00b	3.66ab	3.88ab	4.79a	0.56	0.035	0.005	0.755	0.024
NH3, mg/dL	2.48	2.34	1.89	1.73	0.31	0.081	0.013	0.982	0.066
Total purine derivatives, mmol/d	16.08a	10.21b	10.91ab	11.67ab	2.08	0.039	0.068	0.033	0.005
Allantoin, mmol/d	14.84a	8.90b	9.89ab	10.66ab	2.04	0.037	0.085	0.028	0.005
Uric acid, mmol/d	1.24a	1.31a	1.02b	1.00b	0.08	0.001	<0.001	0.441	0.055

¹Contrasts: L, linear, Q, quadratic, QT, no quebracho vs. quebracho inclusion.

²Quebracho extract contained 77.99% total condensed tannins, 28.9% protein precipitable phenolics, and 5.099 kcal/g of DM.

^a,bLeast Squares means in a row with different superscripts differ at P ≤ 0.05.

There was no treatment effect observed for either butyrate or valerate concentrations, but isobutyrate and isovalerate concentrations were highest for QT_4.5 with both acids increasing linearly with QT rate (P ≤ 0.021) and QT provision having greater concentration compared with QT₀ (P ≤ 0.014). Total branched-chain VFA concentration increased linearly with QT inclusion (P = 0.005) as QT_4.5 had the greatest concentration, but the inclusion of QT resulted in greater branched-chain VFA concentration relative to QT₀ (P = 0.024). Ruminal NH₃ concentration decreased linearly with increased QT inclusion (P = 0.01), as the feeding of QT tended to reduce ruminal NH₃ relative to QT₀ (P = 0.066). Increased branched-chain VFA and reduced NH₃ concentrations appear contradictory as both are products of protein deamination; however, this may simply be the result of ruminal bacterial populations shifting to those that synthesize branched-chain amino acids and convert them to branched-chain VFA. Purine derivatives were highest for QT₀ with QT inclusion resulting in lower purine levels compared with QT₀ (P = 0.005). Overall, the ruminal data do not agree with previous data from our laboratory (preliminary data) that indicated no effect of QT on VFAs.

In the current study, the daily purine derivatives observed are indicative of greater microbial synthesis in QT₀, conflicting with the greater total VFA concentration levels observed in treatments receiving QT. Since rumen fluid was collected following a period of fasting, these results should be interpreted with caution. A possible explanation is that since CT supplementation is recognized for decreasing the rate of ruminal degradation, resulting in greater retention time, it is plausible that at the time of collection a greater degree of fermentation was occurring in diets containing QT relative to QT₀. Therefore, these results may represent the VFA concentration in an extended post-feeding state but may not be a good representation of total or average-daily VFA production.

Open-circuit, indirect calorimetry

Estimates from the calorimetry assessment are shown in Table 5. There was an effect of treatment (P = 0.001) for respiratory quotient (RQ) with a quadratic trend. All treatments had relatively similar RQ values, but RQs of treatments receiving QT were lower than QT₀ (P < 0.001). The quadratic trend observed was not expected and is difficult to explain. Since the VFA data are questionable due to the timing of collection, we cannot associate propionate production with RQ. From the current data, a potential reason for the reduced RQ with QT inclusion is that starch degradation, ergo glucose uptake, may have been limited due to intestinal enzyme inhibition by QT. However, the true mechanisms are unknown at this time and are likely a culmination of factors including gluconeogenesis from amino acids and propionate (Young, 1977), as well as intestinal glucose absorption efficiency (Harmon and Mcleod, 2001). As DMI and OMI differed due to QT inclusion, GEI was different (P = 0.002). There was an effect of QT for FE (P = 0.001) as FE increased linearly with greater QT rate as QT_4.5 excreted 19% more FE than QT₀. The increase in FE did not affect daily DEI, but dietary digestible energy (DE) (Mcal//kg DM) decreased linearly with QT_4.5 being 8% less than QT₀. In dairy cows grazing ryegrass (Lolium spp.), Acacia themearnsii CT at 1% and 1.9% of DM increased FE with increased inclusion that resulted in a 21% and 36% reduction in DE, respectively (Grainger et al., 2009). The conversion of GE-to-DE was reduced with QT inclusion (P = 0.006) with a linear response being present (P = 0.003). A reduction in the conversion of GE-to-DE is commonly observed when feeding CT, particularly within roughage-based diets due to reduced ruminal digestibility. Compared to QT₀, the conversion of GE-to-DE was 5.5% lower for QT_4.5. This is much lower than the 17% reduction in conversion efficiency seen by Piñeiro-Vázquez et al. (2017) when QT was provided at ≥3% DM in a low-quality forage diet of Pennisetum purpureum. Similarly, the DE-to-GE ratio decreased 8% and 14% in dairy cows when supplementing A. mearnsii at approximately 0.9% and 1.35% of DMI, respectively (Grainger et al., 2009). The large reductions in DE-to-GE ratios observed in the previous studies are likely a result of reduced GEI with CT inclusion, due to lowered intake or not accounting for the energy content of the CT, whereas in the present study animals were limit-fed with all treatments receiving the same proportion of potentially fermentable substrate with QT energy content being included in GEI.

Table 5.

Effect of quebracho tannin percent within a high-roughage diet on steer energy metabolism using indirect calorimetry

Items	Quebracho extract, % of feed DM						Contrast1P-values
	02	1.5	3	4.5	SEM	P-value	L	Q	QT
RQ	1.04a	1.00b	1.00b	1.02ab	0.009	0.001	0.079	<0.001	<0.001
GEI, Mcal/d	15.82b	15.96b	16.19ab	16.47a	0.15	0.002	<0.001	0.497	0.006
GEI, kcal/MBW	260.86d	264.96c	269.41b	274.24a	0.62	<0.001	<0.001	0.420	<0.001
FE, Mcal/d	5.99b	6.57ab	6.45b	7.15a	0.24	0.001	<0.001	0.711	0.001
FE, Mcal/kg DM	1.48b	1.61ab	1.58ab	1.72a	0.05	0.005	0.001	0.878	0.003
FE, kcal/MBW	98.65b	108.65ab	107.53b	118.96a	3.84	<0.001	<0.001	0.796	<0.001
DE, Mcal/d	9.82	9.38	9.74	9.32	0.26	0.180	0.185	0.953	0.129
DE, Mcal/kg DM	2.45a	2.33ab	2.38ab	2.25b	0.05	0.024	0.009	0.868	0.016
DE, kcal/MBW	162.21	161.88	156.31	155.28	3.98	0.209	0.242	0.903	0.193
DE, %GE	62.20a	59.05ab	60.07ab	56.63b	1.44	0.009	0.003	0.890	0.006
UE, Mcal/d	0.27	0.24	0.22	0.24	0.03	0.491	0.284	0.292	0.181
UE, Mcal/kg DM	0.068	0.060	0.055	0.059	0.008	0.455	0.246	0.280	0.148
UE, kcal/MBW	4.55	4.05	3.72	4.10	0.55	0.540	0.352	0.282	0.209
GASE, Mcal/d	1.04a	0.98ab	0.98ab	0.87b	0.04	0.007	0.001	0.430	0.012
GASE, Mcal/kg DM	0.25a	0.24ab	0.24ab	0.21b	0.01	0.011	0.002	0.503	0.015
GASE, kcal/MBW	17.17a	16.22ab	16.33ab	14.50b	0.81	0.029	0.006	0.454	0.039
GASE, %GE	6.56a	6.10ab	6.06ab	5.30b	0.32	0.008	0.001	0.517	0.011
ME, Mcal/d	8.49	8.14	8.53	8.20	0.29	0.450	0.599	0.961	0.407
ME, Mcal/kg DM	2.12	2.03	2.08	1.98	0.06	0.218	0.110	0.879	0.131
ME, kcal/MBW	140.49	136.02	141.82	136.67	4.56	0.523	0.699	0.916	0.542
ME, %DE	86.57	86.90	87.57	87.96	0.91	0.435	0.110	0.958	0.240
ME, %GE	53.89	51.42	52.62	49.84	1.68	0.134	0.054	0.896	0.075
HE, Mcal/d	7.60a	7.46ab	7.23b	7.30ab	0.11	0.013	0.003	0.208	0.007
HE, Mcal/kg DM	1.88a	1.84ab	1.77bc	1.76c	0.02	<0.001	<0.001	0.374	<0.001
HE, kcal/kg MBW	125.19	123.79	120.42	121.54	1.76	0.058	0.019	0.325	0.035
HE, %GE	47.97a	46.69a	44.70b	44.31b	0.67	<0.001	<0.001	0.360	<0.001
RE, Mcal/d	0.89	0.67	1.30	0.90	0.34	0.356	0.560	0.709	0.817
RE, Mcal/kg DM	0.23	0.18	0.31	0.22	0.08	0.482	0.737	0.680	0.908
RE, kcal/kg MBW	15.29	12.23	21.39	15.13	5.57	0.435	0.628	0.689	0.835
RE, %ME	10.50	7.96	14.70	10.78	3.75	0.375	0.530	0.798	0.834
RE, %GE	5.92	4.73	7.92	5.52	2.08	0.483	0.762	0.686	0.934

¹Contrasts: L, linear; Q, quadratic; QT, no quebracho vs. quebracho inclusion.

²Quebracho extract contained 77.99% total condensed tannins, 28.9% protein precipitable phenolics, and 5.099 kcal/g of DM.

^a–dLeast Squares means in a row with different superscripts differ at P ≤ 0.05.

No difference for UE was present (P = 0.491), but the UE of QT₀ was approximately 20% greater than QT₃. The effect of CT from 0.5% to 4% DMI appears to have variable effects on UE as no difference was observed in cattle receiving concentrate or warm-season forage diets (Ebert et al.,; Piñeiro-Vázquez et al., 2017), but reduced UE has been reported in dairy cattle and sheep provided cool-season forages (Carulla et al., 2005; Grainger et al., 2009). There was a difference in daily GASE loss as CH₄ (P = 0.007) with a linear reduction (P = 0.001) in GASE as QT inclusion increased with QT₀ having greater CH₄ energy loss relative to when QT was included (P = 0.012). The GASE of QT_1.5, QT₃, and QT_4.5 were reduced approximately 6%, 6%, and 17%, respectively, compared with no QT provision. Methane energy, Mcal/kg DMI, and kcal/kg metabolic BW exhibited linear reductions with increased QT level (P ≤ 0.006) as the addition of QT resulted in lower GASE than QT₀ (P ≤ 0.039). Previous research regarding the effect of CT on GASE is inconsistent. Reduced GASE has been observed when supplementing QT ≥ 2% in a low-quality forage diet (Piñeiro-Vázquez et al., 2017) but no effect was evident when different CT sources were present within silage and concentrate-based diets at 0.5% to 2% of DM (Beauchemin et al., 2007; de Oliveira et al., 2007; Ebert et al., 2017). Methane energy, % of GEI, presented a similar trend with QT₀ having the greatest GASE (P = 0.008), representing roughly 6.6% of GEI. The conversion of GE to GASE observed in this study matched the conversion factor from IPCC (2006) inventory report (6.5 ± 1.0% for cattle grazing or fed low-quality byproducts); however, all QT containing treatments were on the lower end of the conversion factor range, 6.1%, 6.1%, and 5.3% for 1.5%, 3%, and 4.5% QT, respectively.

Daily MEI (Mcal/d) and dietary ME (Mcal/kg DM) did not demonstrate treatment differences (P > 0.218), although MEI and ME were reduced 4%, on average, for QT_1.5 and QT_4.5. The conversion efficiencies of DE-to-ME were not different as QT₀ and QT_1.5 had a ME-to-DE ratio between 0.86 and 0.87, whereas QT₃ and QT_4.5 exceeded 0.87. The ME-to-DE ratio observed within this study is greater than the 0.82 coefficient recommended by NASEM (2016), but our data fit within the range of 0.82 to 0.93 suggested by Vermorel and Bickel (1980). When evaluating computations of ME from DE using the 0.82 conversion factor and the equation developed by Galyean et al. (2016) for diets exceeding 2 Mcal/kg, estimates did not differ in precision (r² = 0.92) with Akaike’s information criterion indicating slightly improved fit for the 0.82 conversion compared with the Galyean’s et al. (2016) equation (−115 vs. −106). For the ME-to-GE ratio, there was a linear effect (P = 0.054) with a reduction in conversion efficiency as CT inclusion increased.

Daily HE was affected by QT inclusion rate (P = 0.013) in a linear fashion (P = 0.003) with the inclusion of QT, resulting in less HE relative to QT₀ (P = 0.007), a 3.5% reduction on average. On a metabolic BW basis, HE decreased linearly (P = 0.019) as the QT level increased. Heat energy (% of GE) decreased in a linear fashion (P < 0.001), with the provision of QT resulting in lesser GE being lost as HE compared with QT₀. Similarly, a reduction in HE when feeding CT has been observed previously in sheep and goats when using whole-animal respirometry (Carulla et al., 2005; Puchala et al., 2012). In contrast, HE was not different for finishing steers or dairy cows when CT was added to the diet at 0.5% to 1% DM (Huyen et al., 2016; Ebert et al., 2017). Lower HE values in treatments receiving QT could be an effect of less ruminally digestible protein and NH₃, resulting in lower liver ureagenesis and reducing liver O₂ uptake (Huntington and Archibeque, 2000). There was no treatment effect for all RE parameters (P > 0.356). For RE, either as Mcal/d or as Mcal/kg DM, QT₃ demonstrated the greatest RE values with 26% more Mcal/kg DM relative to QT₀. Estimates of RE (Mcal/kg DM) for QT₀, QT_1.5, and QT_4.5 only differed marginally. The RE per kilogram of metabolic BW did not have a treatment effect or trend, but QT₃ retained 28% more energy than QT₀. Neither the conversion efficiency of RE (% of MEI) nor RE (% of GEI) exhibited treatment differences (P = 0.375 and P = 0.483). However, QT₃ had the greatest conversion efficiency, demonstrating a 29% and 25% improvement relative to QT₀ for RE, as a percent of MEI and RE as a percent of GEI, respectively. The treatment QT_1.5 displayed the lowest conversion efficiency compared with all other treatments. Reduced detection of differences was evident for all RE factors and appeared to be due to animal and period accounting for 21% to 31% of the total variance in the model, with an animal associated variance for FE, UE, and GASE (Mcal/d) ranging from 40% to 93% (Table 6).

Table 6.

Variance partitioning of covariance parameters for metabolic and energy parameters of steers fed high-roughage diets

Items	Covariance parameter			P-value
	Animala	Period	Residual	Animal	Period
Metabolic parameters
DMD, %	15%	30%	55%	0.176	0.159
OMD, %	11%	18%	72%	0.258	0.209
aNDFD, %	8%	14%	78%	0.302	0.237
ADFD, %	9%	8%	83%	0.298	0.304
N digestibility, %	6%	60%	34%	0.244	0.126
Fecal N, g/d	45%	33%	22%	0.048	0.129
Fecal N, % N intake	6%	60%	34%	0.245	0.127
Urine N, g/d	28%	—	72%	0.135	—
Urine N, % N intake	5%	—	95%	0.393	—
Fecal N, % N excreted	—	22%	78%	—	0.200
Fecal N:Urinary N	1%	16%	83%	0.476	0.231
Retained N, g/d	17%	17%	66%	0.185	0.206
Retained N, %N intake	10%	17%	73%	0.269	0.216
Energy parameters
FE, Mcal/d	59%	20%	22%	0.044	0.142
FE, Mcal/kg DM	12%	24%	64%	0.227	0.180
FE. kcal/MBW	24%	27%	49%	0.114	0.159
DE, Mcal/d	78%	2%	28%	0.043	0.332
DE, Mcal/kg DM	10%	37%	53%	0.229	0.149
DE, kcal/MBW	14%	25%	61%	0.192	0.175
DE, % GEI	11%	29%	60%	0.226	0.165
UE, Mcal/d	40%	4%	56%	0.084	0.335
GASE, Mcal/d	66%	13%	20%	0.041	0.151
GASE, Mcal/kg DM	35%	12%	53%	0.091	0.215
GASE, kcal/MBW	46%	13%	41%	0.064	0.189
GASE, % GEI	33%	15%	52%	0.094	0.195
ME, Mcal/d	55%	5%	40%	0.057	0.282
ME, Mcal/kg DM	11%	34%	56%	0.221	0.155
ME, kcal/MBW	5%	28%	67%	0.355	0.175
ME, % DE	26%	16%	58%	0.120	0.199
ME, % GEI	12%	28%	61%	0.220	0.169
HE, Mcal/d	93%	—	7%	0.033	—
HE, Mcal/kg DM	24%	20%	56%	0.123	0.184
HE, kcal/kg MBW	67%	2%	31%	0.047	0.344
HE, % GEI	28%	7%	64%	0.122	0.283
RE, Mcal/d	16%	5%	79%	0.211	0.344
RE, Mcal/kg DM	24%	7%	69%	0.144	0.291
RE, kcal/kg MBW	21%	7%	72%	0.163	0.307
RE, % ME	24%	6%	70%	0.149	0.316
RE, % GEI	24%	7%	69%	0.147	0.300

^aBold values indicate significant effects.

Emissions

The provision of QT reduced the daily uptake/release of O₂, CO₂, CH₄, and CO₂e in a linear fashion (P ≤ 0.009; Table 7). A treatment effect was present for total O₂ uptake (P = 0.026) with QT₃ being 5% lower relative to QT₀. On a metabolic BW basis, O₂ consumption decreased linearly with QT inclusion (P = 0.041) and a tendency for reduced O₂ uptake with QT provision (P = 0.065). No difference in O₂ consumption was observed when providing 2.5% A. mearnsii CT while maintaining similar MEI in forage-fed sheep (Carulla et al., 2005). The inclusion of QT resulted in a 5.5% decrease in total CO₂ (P < 0.001) and a 4.5% reduction in CO₂ per kg metabolic BW (P = 0.001) compared with QT₀, with linear trends present for both the parameters (P ≤ 0.001). The inclusion of QT resulted in less daily CH₄ production relative to QT₀ (P = 0.012). The daily CO₂e decreased 6% and 11% for QT₃ and QT_4.5, respectively, when compared with QT₀ (P = 0.007). The total CO₂e per OM, aNDF, or ADF intakes decreased linearly with increased QT provision (P ≤ 0.007). However, CO₂e per digested OM, aNDF, or ADF were not different across treatments with no trends observed (P ≥ 0.277). The RE per CO₂e produced did not demonstrate treatment differences or trends (P ≥ 0.714). Similarly, there was no treatment effect or trends for the RN-to-CO₂e ratio (P ≥ 0.962).

Table 7.

Effect of quebracho tannin percent within a high-roughage diet on steer daily gas production/uptake, unit of gas per digestible nutrient, and retained nutrient per unit of carbon dioxide equivalent

Items	Quebracho tannin extract, % of feed DM						Contrast1P-values
	02	1.5	3	4.5	SEM	P-value	L	Q	CT
O2, L/d	1,508.41a	1,483.52ab	1,436.30b	1,453.30ab	23.28	0.026	0.009	0.214	0.014
O2, L/kg MBW	24.83	24.59	23.90	24.19	0.37	0.103	0.041	0.339	0.065
CO2, L/d	1,554.27a	1,514.09ab	1,469.24b	1,462.02b	19.31	<0.001	<0.001	0.243	<0.001
CO2, L/kg MBW	25.57a	25.07ab	24.44b	24.33b	0.30	0.001	<0.001	0.366	0.001
CH4, L/d	120.35a	113.39ab	112.79ab	99.97b	5.15	0.007	0.001	0.432	0.012
CO2e, L/d	4,924.14a	4,688.99ab	4,627.20ab	4,261.21b	155.55	0.004	<0.001	0.559	0.005
CO2e/OMI, L/g	1.29a	1.21ab	1.20ab	1.09b	0.04	0.004	<0.001	0.601	0.005
CO2e/OMD, L/g	2.00	2.00	1.95	1.90	0.10	0.707	0.277	0.714	0.543
CO2e/aNDFI, L/g	2.09a	2.00ab	2.00ab	1.84b	0.07	0.038	0.007	0.555	0.038
CO2e/aNDFD, L/g	3.63	3.63	3.57	3.53	0.22	0.966	0.637	0.905	0.789
CO2e/ADFI, L/g	3.15a	3.01ab	3.01ab	2.78b	0.11	0.038	0.007	0.549	0.038
CO2e/ADFD, L/g	5.94	5.95	5.77	5.76	0.40	0.936	0.572	0.970	0.730
RE/CO2e, cal/L	210.04	198.14	280.62	216.19	85.84	0.774	0.714	0.670	0.761
RN/CO2e, mg/L	2.47	2.13	2.50	2.34	0.78	0.962	0.991	0.864	0.814

¹Contrasts: L, linear, Q, quadratic, CT, no quebracho vs. quebracho inclusion.

²Quebracho extract contained 77.99% total condensed tannins, 28.9% protein precipitable phenolics, and 5.099 kcal/g of DM.

^a,bLeast squares means in a row with different superscripts differ at P ≤ 0.05.

In the present study, there were no differences in overall energy efficiency. Even so, QT₃ had the highest RE with only HE being lower as FE, UE, and GASE values were comparable relative to QT₀. The reduced HE observed for QT treatments is likely a result of reduced tissue metabolism associated with ruminal digestibility and route of nutrient absorption, albeit to varying degrees based upon the QT level. Within QT_4.5, lower HE appears to be a consequence of decreased digestibility due to reduced substrate availability depressing microbial activity, product formation, and associated maintenance of visceral tissues. In comparison to QT₀, OM and N digestibilities for QT_1.5 and QT₃ were reduced to a greater extent than fibrous fractions. This could indirectly indicate rumen escape or protection of precipitable carbohydrates and proteins, resulting in lesser ruminal degradation and fermentation products. Feeding of CT has resulted in less ruminally degraded NFC and lower total VFA concentration in previous studies (de Oliveira et al., 2007; Koenig and Beauchemin, 2018). Reducing ruminal digestion would likely reduce energetic costs associated with the digestive and absorptive function of portal-drained viscera as seen when comparing forage- vs.concentrate-fed animals (Reynolds et al., 1991). Increased O₂ consumption could also be due to time spent eating (Ferrell, 1988); however, fermentable OM of the diets was isocaloric and isonitrogenous and all diets were readily consumed (no losses, no orts). Since DMI was higher and O₂ consumption was lower in diets containing QT, intake and time spent eating do not appear to have played a substantial role in HE in this scenario. Instead, HE was likely affected to a more considerable degree by the energetic costs associated with the maintenance of portal-drained viscera for digestive, absorptive, and product conversion functions.

Across metabolic parameters, mean estimates for QT_1.5 and QT₃ were very similar, only exhibiting slight variation. Based upon this observation, provision of QT within the range of 1.5% to 3% (1.1% to 2.3% actual CT) may not impart a large change in digestive function and efficiency, whereas the threshold at which QT begins to depress digestion lies between the 3% and 4.5% (2.3 to 3.5% actual CT) inclusion rates. The primary mode of action for CT, substrate precipitation, suggests that the threshold at which CT will overwhelm the ruminal ecosystem is based upon the concentration of precipitable carbohydrates and proteins within the diet. When readily precipitated substrate is limited, increased binding of microbial matter should occur since more unbound CT is present in solution. Although scenario dependent, direct inhibition and interaction with ruminal microflora will likely affect digestion to a greater extent since the nutritional requirements of microflora will be increased during a period of nutrient constraint.

Conclusions

Quebracho CT inclusion affected metabolic parameters of steers fed a roughage-based diet. The provision of QT resulted in less GASE and HE while maintaining similar RE and RN values. A shift in the N excretion route was demonstrated, with a larger proportion of N excreted in the feces of animals receiving QT. Altering N excretion route could prove useful in retaining this element within ruminant systems and decrease N₂O and NH₃ emissions associated with urinary N. In total, there was no true difference among treatments for RN and RE in the current study. The effects of QT upon nutrient retention and overall efficiency are very dynamic on what appears to be vastly different methods of altering efficiency occurring across a very narrow range of supplementation. However, lack of investigation and understanding of CT-substrate interactions across a vast array of diets hinders our capacity to determine feasible methods of utilization in ruminant production systems. Since excreta represents the second-largest emissions pool, which is largely a result of its nutrient profile, enumeration of excreta gas fluxes should be used to assist in the determination of the most promising management practices and how these practices influence nutrient cycling within applied systems. Accordingly, due to the presence of significant discrepancies among studies feeding CT to cattle, more investigation of how different CT affect animals at varying growth stages within diverse production settings is required if results are to be applied in non-research settings. Considerable among-animal variation and potential carryover effects with CT, as well as other rumen modulators, may require the utilization of greater animal numbers in cross-over designs for discovery purposes.

Conflict of interest statement

The authors declare no real or perceived conflicts of interest.

Glossary

Abbreviations

ADF

acid detergent fiber

aNDF

neutral detergent fiber with the addition of amylase and sodium sulfite

CH₄

methane

CO₂

carbon dioxide

CP

crude protein

CT

condensed tannins

DE

digestible energy

DEI

digestible energy intake

DM

dry matter

DMD

DM digestibility

DMI

DM intake

FE

fecal energy

GASE

gaseous energy

GE

gross energy

GEI

GE intake

GHG

greenhouse gases

HE

heat energy

ME

metabolizable energy

MEI

metabolizable energy intake

N

nitrogen

N₂O

nitrous oxide

NFC

nonfiber carbohydrates

NH₃

ammonia

OM

organic matter

OMD

OM digestibility

OMI

OM intake

PPP

protein precipitable phenolics

QT

quebracho tannin

RE

retained energy

RH

relative humidity

RN

retained nitrogen

RQ

respiratory quotient

SBW

shrunk BW

UE

urinary energy

VFA

volatile fatty acids