Use of ¹⁵N abundance in tail hair to predict feed efficiency and response to a urea supplement in young cattle fed a tropical grass forage

Introduction

Rangeland beef cattle in northern Australia often graze low-quality tropical pastures where nitrogen (N) is frequently the primary limiting nutrient (McLennan et al. 2017; Dixon et al. 2022). During periods of low forage quality, it is common to supplement cattle with N sources, including non-protein nitrogen (NPN) such as urea, which has been shown to improve rumen microbial digestion and liveweight (LW) gain (Winks et al. 1979; Holroyd et al. 1988; Dixon et al. 1998). Studies in northern Australia have demonstrated that N supplements, including NPN, can reduce dry-season LW loss by up to 35 kg in growing cattle grazing senesced tropical pastures (Dixon et al. 2022). The effectiveness of NPN supplementation in these systems is largely due to its provision of rumen-degradable N, which supports microbial activity and improves the intake of metabolisable energy (ME) from low-quality forages (Coates and Dixon 2008; McLennan et al. 2017). Poppi and McLennan (1995) further emphasise the importance of balancing N and energy intake in ruminants, as N availability often becomes the primary limiting factor. Conversely, energy intake can constrain growth when N is no longer limiting. This interplay between N and energy utilisation highlights the critical role of protein of N supplementation in improving productivity for cattle grazing in tropical systems with low forage quality.

Despite these nutritional interventions, there are significant variations in the ability of cattle to perform optimally in harsh conditions. Differences in N metabolism are associated with variations in growth rate and reproductive performance when cattle are on low-protein diets (Sinclair et al. 2000; Huntington et al. 2001). Cattle that lose less N through urine and faeces will be able to return more N to the rumen for microbial anabolism, compared with those that have higher N losses (Hailemariam et al. 2021). However, quantifying N losses and N recycling on large numbers of individual cattle is not an easy pursuit, as it requires total collection of faeces and urine. Therefore, metabolic markers, such as blood urea N, creatinine and 3-methylhistidine have been used to assess differences between animals (Lavery and Ferris 2021).

The natural abundance of the heavier ¹⁵N isotope (δ¹⁵N) in body tissues of cattle has been proposed as a proxy for N use efficiency (NUE) and feed efficiency when cattle are on low–protein diets (Cantalapiedra-Hijar et al. 2015; Silva et al. 2022). The two major N isotopes that are involved in the metabolism of protein in plants and animals are ¹⁴N and ¹⁵N. Of these two N isotopes, ¹⁴N is the most abundant form of N on Earth and requires less energy to break its bonds (Lavery and Ferris 2021). During rumen fermentation and N transactions in the liver and kidney, ¹⁴N-containing substrates are preferentially used by enzymes and fractionation occurs (Lavery and Ferris 2021). Therefore, cattle urine is enriched in ¹⁴N and body tissues contain a greater δ¹⁵N than that occurring in the diet (Nasrollahi et al. 2020), although the δ¹⁵N in tissue is influenced by diet composition (Cantalapiedra-Hijar et al. 2015). Body tissues, including tail hair, can be used to evaluate the δ¹⁵N.

Collection of tail hair is easy, non-invasive, requires no special collection or storage equipment and is shelf stable, as compared to plasma and urine samples (Tallo-Parra et al. 2017). As hair grows, it retains the dietary N conditions of the past. These qualities make tail hair an attractive option to study the association between δ¹⁵N and cattle performance. It is expected that, due to lower N losses in urine, cattle with lower δ¹⁵N in body tissues will be more feed efficient and have greater NUE (Cantalapiedra-Hijar et al. 2020; Silva et al. 2022).

Nitrogen is a major limiting nutrient in cattle. Insufficient dietary N may impair performance and thereby decrease ADG (Hendricksen et al. 1994). Supplementation of N to cattle is a common practice, often requiring significant financial investment. Performance can be improved in cattle with protein supplementation (McLennan et al. 2017); however, the expected value of the performance improvement should cover the cost of the supplement. Non-protein nitrogen, such as urea, is often an attractive, less expensive option that is safe to feed to cattle at appropriate concentrations (Köster et al. 2002).

The large individual variation in performance of cattle creates an economic and nutritional problem and creates a large variation of total N losses to the environment. Protein supplements are formulated based on the predicted average herd intake of the supplement and the subsequent response. A portion of the animals will excrete more N with no or very little increase in performance, while a portion of the animals will respond well. The ability to predict growth response to supplements would allow for better decisions on cattle breeding, group segregation, when to supplement with N, and more targeted supplement formulation, increasing total NUE of the overall system.

Thus, we hypothesised that cattle tail hair δ¹⁵N might assist in predicting differences in N metabolism parameters and growth rates of cattle when on low–protein diets and receiving a urea supplement.

Materials and methods

Approval was granted by The University of Queensland Production and Companion Animals Animal Ethics Committee (approval 2021/AE000013).

Results

There were significant individual variations in DMI and ADG for both diets. Total DMI varied from 14.5 g/kg BW to 18.8 g/kg BW, with an average of 16.5 g/kg BW on the baseline diet, and 15.2 g/kg BW to 20.8 g/kg BW, with an average of 17.9 g/kg BW on the urea supplemented diet (Tables 2 and 3). The ADG during the baseline diet ranged from −125 to 181 g/day, with an average of 64 g/day (Table 2). On average, urea supplementation resulted in an increase of 202 g/day in ADG, with a range from −11 g/day to 480 g/day. Thirty percent of the steers had less than a 100 g/day increase in ADG in response to urea supplementation, while 30% had an increase greater than 250 g/day.

All performance and metabolic variables are presented as means ± s.d. for each diet in Tables 2 and 3 to demonstrate the extent of inter-animal variation. Due to temporal differences confounded with diet effects, comparisons between diets could not be made in this study, and thus P-values for diet effects are not provided and the data is presented in two separate tables. For both diets, all variables, including tail hair δ¹⁵N, exhibited considerable individual variation (range and s.d.), highlighting the variability in N metabolism across animals.

Tail hair δ¹⁵N as a predictor of growth rate, nitrogen use efficiency (NUE) and feed conversion efficiency (FCE)

The growth rate, NUE, and FCE of steers on the urea supplemented diet were significantly correlated (P < 0.01), with the initial tail-hair δ¹⁵N measured during the baseline diet explaining 38% of the variation in ADG (Fig. 1), 26% of the variation in NUE (Fig. 2), and 21% of the variation in FCE (Fig. 3). Steers with lower δ¹⁵N in tail hair gained more weight and had greater NUE and FCE compared to those with higher δ¹⁵N values.

Fig. 1.

Variation of the average daily gain during urea diet to baseline natural abundance of the ¹⁵N isotope (δ¹⁵N).

Fig. 2.

Variation of the NUE during urea diet to baseline natural abundance of the ¹⁵N isotope (δ¹⁵N).

Fig. 3.

Variation of the feed conversion efficiency during urea diet to baseline natural abundance of the ¹⁵N isotope (δ¹⁵N).

Additionally, δ¹⁵N from the baseline diet was correlated with urinary losses (P < 0.01), explaining 31.6% of the variation in urine N losses (Fig. 4). Rumen fluid ammonia and PUN were not correlated with any performance parameters on either diet (Tables 4 and 5). The ranking of δ¹⁵N values remained consistent between the baseline and urea supplemented diets, with δ¹⁵N from the baseline diet explaining 68% of the variation in δ¹⁵N during the urea supplemented diet (Fig. 5).

Fig. 4.

Variation of the natural abundance of the ¹⁵N isotope (δ¹⁵N) during baseline diet to urine nitrogen loss.

Table 4.Pearson correlation coefficients for study variables in the baseline diet.

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1. δ15N in tail hair (‰)	–
2. ADG (g/day)	−0.64**	–
3. BW (kg)	0.23	−0.02	–
4. FCE1 (kg ADG/kg DM intake) A	−0.62**	0.99**	−0.03	–
5. N intake (g/day)	−0.30	0.44*	0.78**	0.44*	–
6. CP digestibility (%)	−0.52*	0.37†	−0.36†	0.35†	−0.07	–
7. DM digestibility (%)	0.24	−0.24	0.37†	−0.23	0.13	−0.03	–
8. NDF digestibility (%)	0.37†	−0.29	0.51*	−0.28	0.18	−0.20	0.96**	–
9. N urine (g/kg N intake)	0.56*	−0.48*	0.31	−0.49*	−0.19	−0.27	0.44*	0.54*	–
10. N faeces (g/kg N intake)	0.52*	−0.37†	0.36†	−0.35†	0.07	−1.00**	0.03	0.20	0.27	–
11. Total N excretion (g/kg N intake)	0.68**	−0.54*	0.42*	−0.54*	−0.09	−0.75**	0.32	0.49*	0.84**	0.75**	–
12. N balance (g/day)	−0.71**	0.55*	−0.45*	0.54*	0.09	0.73**	−0.36†	−0.52*	−0.85**	−0.73**	−0.99**	–
13. NUE (g N retained/kg N digested)	−0.68**	0.54*	−0.41*	0.54*	0.11	0.67**	−0.32	−0.48*	−0.89**	−0.67**	−0.99**	0.98**	–
14. Rumen N-NH3 (mg N/L) B	0.14	−0.12	−0.41*	−0.07	−0.47*	−0.08	−0.09	−0.07	0.02	0.08	0.06	−0.04	−0.05	–
15. PUN (mmol/L)	−0.09	0.09	−0.13	0.09	−0.13	0.27	−0.34	−0.32	−0.21	−0.27	−0.29	0.28	0.26	0.42*	–

ADG, average daily gain; CP, crude protein; FCE, feed conversion efficiency, NDF, neutral detergent fibre; NUE, nitrogen use efficiency; PUN, plasma urea nitrogen.

^†P < 0.10. *P < 0.05. **P < 0.01.

^A FCE1 and FCE2 were correlated at r = 0.999 (P < 0.01).

^B Average of two time points: 0 and 3 h after feeding.

Table 5.Pearson correlation coefficients for study variables in the urea diet.

Variables	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1. δ15N in tail hair (‰)	–
2. ADG (g/day)	−0.43	–
3. BW (kg)	0.11	0.37†	–
4. FCE1 (kg ADG/kg DM intake) A	−0.45*	0.97**	0.21	–
5. N intake (g/day)	−0.53**	0.65**	0.27	0.54**	–
6. CP digestibility (%)	0.32	−0.20	−0.38†	−0.13	−0.04	–
7. DM digestibility (%)	0.33	−0.31	−0.14	−0.29	−0.27	0.62**	–
8. NDF digestibility (%)	0.55**	−0.29	0.12	−0.31	−0.41	0.44*	0.89**	–
9. N urine (g/kg N intake)	0.47*	−0.24	0.26	−0.22	−0.69**	−0.09	0.33	0.55**	–
10. N faeces (g/kg N intake)	−0.32	0.20	0.38†	0.13	0.04	−1.00**	−0.62**	−0.44*	0.09	–
11. Total N excretion (g/kg N intake)	0.33	−0.15	0.36†	−0.16	−0.63**	−0.39†	0.11	0.37†	0.95**	0.39†	–
12. N balance (g/day)	−0.45*	0.23	−0.37†	0.23	0.70**	0.29	−0.19	−0.47*	−0.96**	−0.29	−0.98**	–
13. NUE (g N retained/kg N digested)	−0.37†	0.17	−0.35	0.17	0.65**	0.33	−0.15	−0.40	−0.97**	−0.33	−0.99**	0.98**	–
14. Rumen N-NH3 (mg N/L) B	0.08	−0.09	0.31	−0.08	−0.42	−0.34	−0.01	0.30	0.69**	0.34	0.72**	−0.72**	−0.69**	–
15. PUN (mmol/L)	0.09	−0.08	−0.24	0.05	−0.47*	0.06	0.15	0.10	0.26	−0.06	0.22	−0.24	−0.23	0.19	–

ADG, average daily gain; CP, crude protein; FCE, feed conversion efficiency, NDF, neutral detergent fibre; NUE, nitrogen use efficiency; PUN, plasma urea nitrogen.

^†P < 0.10. *P < 0.05. **P < 0.01.

^A FCE1 and FCE2 were correlated at r = 0.99 (P < 0.01).

^B Average of two time points: 0 and 3 h after feeding.

Fig. 5.

Linear regression of the natural abundance of the ¹⁵N isotope (δ¹⁵N) during the baseline and urea supplemented diets.

Discussion

The primary aim of this study was to evaluate whether δ¹⁵N could predict animal performance, particularly ADG, under different nutritional conditions, including supplementation with urea. There was uncertainty about whether the relationship between δ¹⁵N, NUE, and ADG would still hold when steers were supplemented with urea. One possibility was that more efficient animals would respond poorly to urea supplementation, as they might already recycle N effectively to the rumen. Alternatively, it was hypothesised that more efficient animals (those with lower δ¹⁵N and greater NUE) would respond better to urea supplementation, as their ability to recycle N would minimise N losses from spikes in PUN and support better utilisation (Reynolds and Kristensen 2008).

Cattle show significant variation in weight gain, feed intake, and NUE even when on the same diet (Koch et al. 1963). This variability, observed in both baseline and urea supplemented diets in our study, is partly attributed to differences in N recycling, which improves nutrient utilisation, particularly in low-protein diets (Silva et al. 2019; Hailemariam et al. 2021). The variation in ADG, DMI, NUE, and urinary N excretion suggests δ¹⁵N could be used to identify animals that respond better to urea supplementation. Specifically, we observed a significant variation in ADG responses to urea supplementation, with 30% of cattle showing either less than 100 g/day or more than 250 g/day of ADG improvement. Identifying these animals with δ¹⁵N could help select for more efficient animals or target supplementation to those most likely to benefit. However, it is important to recognise that factors such as feed quality and N intake also contribute to this variability.

This study demonstrates that tail hair δ¹⁵N, measured during the baseline diet, was a useful predictor of individual differences in N metabolism, and explained a portion of the variation in ADG and NUE during the urea supplemented diet. Although the R² values for ADG (0.38) and NUE (0.26) were moderate, δ¹⁵N was still able to identify more efficient animals (those with lower δ¹⁵N), who responded better to supplementation, likely due to their superior ability to retain N rather than excreting it in urine. This finding is particularly relevant in grazing systems, where cattle may intermittently consume urea supplements, and maintaining N balance is critical for improving performance.

The relationship between tail hair δ¹⁵N and FCE observed in this study agrees with findings from Guarnido-Lopez et al. (2022), who demonstrated that low residual feed intake (RFI) cattle, which are more feed-efficient, exhibited improved NUE, regardless of diet. These efficient RFI animals showed lower urinary N excretion and better protein retention, consistent with the metabolic processes reflected by δ¹⁵N. The improved NUE is associated with a reduced partitioning of N towards waste products, particularly urine, and more efficient utilisation of N for growth and body composition (Lapierre et al. 2006; Calsamiglia et al. 2010). Our findings further support the hypothesis that δ¹⁵N could reflect broader metabolic differences, including protein turnover and N recycling, directly influencing feed efficiency. While Guarnido-Lopez et al. (2022) focused primarily on high-starch diets, results from this study suggest that the δ¹⁵N relationship with feed efficiency holds across both forage-based and supplemented diets.

The observed variation in ADG and FCE in both baseline and urea supplemented diets is likely driven by differences in N metabolism. Individual variation in N kinetics has been well-documented (Marini and Van Amburgh 2003; Bailey et al. 2012), and this study further confirms that these metabolic differences contribute to variation in performance. Increasing dietary N typically enhances urea synthesis in the liver and N recycling into the rumen and intestinal system, although the proportion of N intake recycled to microbial production decreases as intake rises (Silva et al. 2019). Traditional N metabolism assessments are resource-intensive (Wickersham et al. 2008; Lavery and Ferris 2021; Parra et al. 2022), but alternative proxy measures, such as δ¹⁵N in tissue samples, offer promising solutions for measuring changes in N metabolism and NUE (Cantalapiedra-Hijar et al. 2022).

This study did not demonstrate significant individual variation in DM, OM, NDF and CP digestibility, suggesting other factors may account for the observed performance variation. More efficient steers may have a greater recycling of N without improving feed digestibility. It has been shown that glucose can decrease NDF digestibility (Bailey et al. 2012), and the addition of molasses may have influenced digestibility in the present study. Previous research has reported a decrease in NDF digestibility of 4.8 g/kg for every kg increase in DMI (Krizsan et al. 2010). Additionally, increasing CP has been shown to increase diet digestibility in cattle (Beaty et al. 1994). In the current study, the addition of M8U to the diet and the increase of DMI likely offset changes in digestibility, resulting in no significant differences.

Our study emphasises the need to consider the dietary context when interpreting δ¹⁵N values. On the baseline diet, δ¹⁵N correlated with ADG, CP digestibility, and total N excretion. On the urea supplemented diet, δ¹⁵N was associated with N intake and NDF digestibility. These results illustrate the variability in N metabolism across different diets and among individual cattle.

In addition to changes in digestibility, other factors like rumen fluid ammonia concentrations can be used as an indication of rumen microbial synthesis, reflecting protein available for animal performance (Calsamiglia et al. 2010). Low rumen ammonia concentration can limit fermentation efficiency and total microbial yield (Meng et al. 1999), and N recycling is strongly influenced by rumen ammonia (Li et al. 2019). Similarly, PUN concentration can reflect changes in rumen ammonia and N recycling (Obitsu and Taniguchi 2009), though it is not an ideal predictor of NUE. In this study, no correlation was found between rumen ammonia or PUN and performance or efficiency parameters, such as ADG and FCE. This lack of correlation supports the potential of δ¹⁵N in tail hair as an important proxy for N metabolism and performance.

Moreover, it was anticipated that steers with low δ¹⁵N in tail hair and lower urine N losses would exhibit higher rumen ammonia and PUN concentrations, but this was not observed. Ammonia not used for microbial synthesis is absorbed through the rumen and converted to urea in the liver (Lavery and Ferris 2021). The more efficient steers may be absorbing similar amounts of ammonia but recycling greater quantities of urea back to the rumen at a constant rate, which could explain why rumen ammonia and PUN were poor predictors of NUE in this study.

It is important to acknowledge the limitations of using δ¹⁵N as a proxy for NUE. Factors such as nutritional history, variations in feed quality, and differences in N intake can influence δ¹⁵N concentrations (Sponheimer et al. 2003; Bernard et al. 2020). Therefore, δ¹⁵N values should be compared only within animals consuming the same diet. In the present study, the different N sources between the baseline and urea supplemented diets likely affected the δ¹⁵N enrichment of body tissues, as urea is depleted in δ¹⁵N, compared to plant proteins (Choi et al. 2002; Ti et al. 2021). This makes it difficult to interpret δ¹⁵N values across diets and likely accounts for the similar δ¹⁵N values observed (Fig. 5) even though the diets had different NUE. Therefore, δ¹⁵N comparisons should be made only within animals consuming the same diet.

In the present study, the different sources of N supply between the baseline and the urea supplemented diet likely alters the ¹⁵N enrichment of body tissues, as urea is depleted of ¹⁵N (Choi et al. 2002; Ti et al. 2021). This limits the interpretation of δ¹⁵N across diets and likely explains the similar δ¹⁵N values observed across both diets (Fig. 5), reinforcing that δ¹⁵N comparisons should be made within animals on the same diet.

Despite these potential influences, this study demonstrated that δ¹⁵N in tail hair can be used to assess metabolic responses in cattle fed low CP diets and in response to molasses-urea supplementation. Importantly, the rankings of the steers’ δ¹⁵N from low to high remained consistent between the baseline and supplemented diets, showing that δ¹⁵N can be a reliable proxy for NUE, even with the addition of urea supplements, a common practice in grazing cattle (Harper et al. 2019). To our knowledge, this is the first study to report the consistency of δ¹⁵N rankings across diets of different protein levels.

It is also important to consider that during periods of negative energy balance, such as when cattle are mobilising body tissues, N is released into the bloodstream as muscle is degraded to supply amino acids for gluconeogenesis (Sadri et al. 2023). This process could potentially influence δ¹⁵N values and complicate the relationship between δ¹⁵N and NUE. However, despite this mobilisation, animals with more efficient N retention would likely have lower δ¹⁵N in tail hair due to reduced urinary N excretion. Although research on δ¹⁵N in such animals is limited, the general relationship between N efficiency and δ¹⁵N suggests that more efficient N retention may be reflected in lower δ¹⁵N, even during periods of negative energy balance.

The variability in intake observed in extensive grazing systems, where both ME and N intake fluctuate due to grazing preferences, activity, and environmental factors, must be considered when interpreting δ¹⁵N data. Previous research, including Silva et al. (2022), has addressed this challenge by using δ¹³C in tail hair to trace grazing patterns and diet selection. In that study, reproductive performance was not correlated with diet selection, as no differences in δ¹³C were found between groups. However, cows with higher productivity had lower δ¹⁵N values during the dry season, suggesting more efficient N metabolism and reduced N losses, regardless of diet choice. This indicates that grazing behaviour, such as selecting different plant species or plant parts, does not confound the relationship between δ¹⁵N and reproductive efficiency.

The potential variation in supplement intake within grazing herds, where individual animals may consume different amounts of supplements, represents a characteristic challenge of grazing systems. This variability could influence δ¹⁵N and its ability to identify more efficient animals, as faster-growing individuals may consume more supplements. However, this issue extends beyond δ¹⁵N and applies to all selection indices used to identify efficient animals in grazing systems, such as growth rate, fertility, calving interval, and weaning weight. One potential solution is to develop remote monitoring tools to track individual supplement intake, helping to account for this variability (Simanungkalit et al. 2020).

Conclusions

Identification of proxies for N metabolism is of great importance to research and commercial beef production. This study demonstrates that tail hair δ¹⁵N offers a promising, practical proxy for assessing N metabolism, enabling easier and faster research. The ADG and FCE of steers on a urea supplemented diet were significantly correlated with tail hair δ¹⁵N measured on a medium-protein diet. Tail hair δ¹⁵N effectively reflected N metabolic variables, including NUE and N-urine losses. Thus, δ¹⁵N in tail hair has potential as a management tool to identify cattle with superior N efficiency and better responses to urea supplementation. This could facilitate the selection of more nitrogen-efficient animals for retention in the breeding herd, enhancing overall productivity.