The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems
Abstract
:1. Introduction
2. Materials and Methods
2.1. The North Wyke Farm Platform
- i.
- Legumes; white clover (Trifolium repens)/high sugar grass (perennial ryegrass; Lolium perenne L. cv. AberMagic) (WC), with the aim of maintaining clover ground cover of 30%. No N fertiliser was applied to this treatment due to clover’s atmospheric N fixation capacity.
- ii.
- Perennial ryegrass monoculture (HS), utilising a high sugar variety (Lolium perenne L. cv. AberMagic). This system received N fertiliser at the standard recommended rate as in the control farmlet.
2.2. Sample and Data Collection, Chemical Analysis and Feed Intake
2.3. Approaches Used for the Prediction of N Excretion
2.4. Approaches Used for Estimation of N Losses at System Level
2.5. Statistical Analysis
3. Results
3.1. Effect of Prediction Model
3.2. Interactions between Prediction Approach and Production Period
3.3. Interactions between Prediction Approach and Forage Type
3.4. Interactions between Prediction Approach and Gender
4. Discussion
4.1. Calculation of N Excretion Using IPCC or Literature Equations
4.2. Accounting for N Partitioning between Urine and Faeces in the Calculation of N Emissions
4.3. Effect of Using IPCC or Individual Animal Equations on the Calculated Forms of N Loss
4.4. Potential Effect of Management Periods and Forage Type on N Loss Calculations
4.5. Implications of N Loss Prediction Methods
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Equation | Source | |
---|---|---|
a. | UNO = 14.3(3.18) + 0.510(0.0121) NI | Equation (9); Reed et al., 2015 [27] |
b. | MNO = 15.1(2.50) + 0.828(0.0106) NI | Equation (13); Reed et al., 2015 [27] |
c. | UNO = –26.49(3.117) + 0.597(0.0158) NI | Equation (2e); Angelidis et al., 2019 [12] |
d. | MNO = –5.681(3.1652) + 0.761(0.0157) NI | Equation (1d); Angelidis et al., 2019 [12] |
Parameter | Mean 1 | |||||
---|---|---|---|---|---|---|
Angelidis et al. | Reed et al. | IPCC 2006 | IPCC 2019 | SE | p-Value | |
Nex (g/d) | 188.6 c | 196.1 b | 210.9 a | 210.9 a | 14.70 | <0.001 |
NexU (g/d) | 125.3 | 115.6 | - | - | 8.100 | <0.001 |
NexF (g/d) | 62.74 | 79.91 | - | - | 3.530 | <0.001 |
NH3-N (g/d) | 30.55 c | 28.05 d | 71.01 a | 69.77 b | 4.020 | <0.001 |
NH3-N (%Nex) | 18.24 c | 16.48 d | 37.49 a | 36.55 b | 0.110 | <0.001 |
NH3-N (kg/kg lwg) | 0.076 b | 0.070 b | 0.154 a | 0.149 a | 0.021 | <0.001 |
N2O-N (g/d) | 3.290 c | 3.330 c | 4.790 a | 3.760 b | 0.260 | <0.001 |
N2O-N (%Nex) | 1.989 c | 1.960 d | 2.279 a | 2.028 b | 0.014 | <0.001 |
N2O-N (kg/kg lwg) | 0.011 | 0.011 | 0.012 | 0.011 | 0.002 | 0.800 |
Nlos (g/d) | 59.49 c | 58.02 c | 140.3 a | 123.1 b | 7.080 | <0.001 |
Nlos (%Nex) | 34.27 c | 32.51 d | 71.42 a | 62.66 b | 0.400 | <0.001 |
Nlos (kg/kg lwg) | 0.116 b | 0.113 b | 0.240 a | 0.210 a | 0.030 | <0.001 |
NH3-Nhg (g/d) | 14.81 c | 13.80 d | 36.35 a | 34.49 b | 1.820 | <0.001 |
N2O-Nhg (g/d) | 1.460 b | 1.470 b | 2.360 a | 0.960 c | 0.100 | <0.001 |
NO-Nhg (g/d) | 0.310 a | 0.310 a | 0.000 b | 0.000 b | 0.010 | <0.001 |
N2O-Nhgv (g/d) | 0.150 c | 0.140 d | 0.360 a | 0.340 b | 0.020 | <0.001 |
Nglea (g/d) | 8.600 c | 9.040 c | 28.92 a | 23.18 b | 1.240 | <0.001 |
N2O-Nglea (g/d) | 0.060 c | 0.070 c | 0.220 b | 0.250 a | 0.010 | <0.001 |
N2-Nhg (kg/d) | 4.360 b | 4.400 b | 5.110 a | 1.730 c | 0.330 | <0.001 |
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Angelidis, A.E.; McAuliffe, G.A.; Takahashi, T.; Crompton, L.; Yan, T.; Reynolds, C.K.; Stergiadis, S.; Misselbrook, T. The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems. Sustainability 2022, 14, 7260. https://doi.org/10.3390/su14127260
Angelidis AE, McAuliffe GA, Takahashi T, Crompton L, Yan T, Reynolds CK, Stergiadis S, Misselbrook T. The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems. Sustainability. 2022; 14(12):7260. https://doi.org/10.3390/su14127260
Chicago/Turabian StyleAngelidis, Angelos E., Graham A. McAuliffe, Taro Takahashi, Les Crompton, Tianhai Yan, Christopher K. Reynolds, Sokratis Stergiadis, and Tom Misselbrook. 2022. "The Impact of Using Novel Equations to Predict Nitrogen Excretion and Associated Emissions from Pasture-Based Beef Production Systems" Sustainability 14, no. 12: 7260. https://doi.org/10.3390/su14127260