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Prediction of metabolisable energy concentrations from nutrient digestibility and chemical composition in grass silages offered to sheep at maintenance
Animal Feed Science and Technology 117 (2004) 197–213
Prediction of metabolisable energy concentrations from nutrient digestibility and chemical composition in grass silages offered to sheep at maintenance T. Yan∗ , R.E. Agnew1 The Agricultural Research Institute of Northern Ireland, Hillsborough, Co Down, Northern Ireland BT26 6DR, UK Received 16 January 2004; received in revised form 26 August 2004; accepted 1 September 2004
Abstract A total of 174 perennial ryegrass silages were evaluated in nine studies for chemical composition, nutrient digestibility and urinary energy output with sheep (four sheep/silage) offered the silage as a sole diet at maintenance energy feeding level. Silage metabolisable energy (ME) concentration was estimated from measured energy intake and outputs from faeces and urine and predicted methane energy. All silage data were expressed on an alcohol corrected toluene dry matter (DM) basis. The objectives were to use these silage data to develop prediction equations for ME concentration and ME/GE (gross energy) and then validate these equations using published grass silage data. There was a large range in ME concentration (7.7–13.6 MJ/kg DM), ME/GE (0.432–0.668) and digestible organic matter in DM (DOMD; 0.530–0.769). The ME concentration and ME/GE were positively related to GE and DE concentration, DOMD and digestibility of DM, organic matter (OM), GE, crude protein (CP) and neutral detergent fibre (P < 0.05 or less). Prediction of ME concentration using digestible energy (DE) or GE digestibility plus residual GE concentration (GE—mean GE) produced a strong relationship (R2 = 0.98), while using DM or OM digestibility or DOMD as a sole predictor reduced R2 Abbreviations: CP, crude protein; DE, digestible energy; DM, dry matter; DOM, digestible organic matter; DOMD, digestible organic matter in dry matter; GE, gross energy; GE, residual gross energy (gross energy concentration minus mean gross energy concentration); ME, metabolisable energy; MPE; mean prediction error; MSPE, mean square prediction error; N, nitrogen; NDF, neutral detergent fibre; NIRS, near infrared reflectance spectroscopy; R, correlation coefficient ∗ Corresponding author. Tel.: +44 28 9268 2484; fax: +44 28 9268 9594. E-mail address: [email protected] (T. Yan). 1 Also a member of staff of Department of Agriculture and Rural Development of Northern Ireland, and The Queen’s University of Belfast, Belfast, Northern Ireland BT9 5PX. 0377-8401/$ – see front matter © 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.anifeedsci.2004.09.002
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values to approximately 0.73. The latter R2 values were marginally increased when CP concentration was added as a secondary predictor, and substantially increased to over 0.90 when residual GE was added. Prediction of ME/GE using GE digestibility produced a higher R2 value (0.97) than those (0.88–0.90) using DM or OM digestibility or DOMD. The R2 values were marginally increased when adding CP or residual GE concentration as a secondary predictor to the latter relationships. These equations were validated using published grass silage data since 1977 (n = 21) and the mean-squareprediction error. Prediction of ME using DE or GE digestibility with residual GE had the lowest mean prediction error (MPE), with the predicted ME close to observed ME, and the majority of error derived from random variation. Using DM or OM digestibility or DOMD as a sole predictor for ME concentration produced a relatively large MPE, while adding CP or residual GE generally reduced the MPE and errors derived from both bias (predicted−actual) and line (slope). Similar results also occurred for prediction of ME/GE. DE concentration is the most accurate predictor for ME concentration. Prediction of ME using OM digestibility or DOMD as a sole predictor can result in error, but the prediction accuracy can be improved by adding GE concentration as a secondary predictor. © 2004 Elsevier B.V. All rights reserved. Keywords: Grass silage; Digestibility; ME concentration; Prediction equation; Validation
1. Introduction Grass silage is a major feed for ruminants in western, eastern and northern Europe, but its quality varies according to variety, maturity, dry matter (DM) concentration and ensiling technique. The metabolisable energy (ME) concentration in grass silages, thus, has to be determined individually when formulating rations for ruminant animals under practical conditions. The common practice for determination of silage ME concentration is to relate it to its digestible nutrient proportion. In the UK, the digestible organic matter (OM) in DM (DOMD) (kg/kg) in grass silage is recommended (Agricultural and Food Research Council, AFRC, 1993) to calculate ME concentration (MJ/kg DM) by multiplying by a factor of 16. The DOMD can be measured in digestibility studies with sheep or cattle offered the silage at maintenance energy feeding level. However, this relationship ignores possible differences in nutrient proportions in DOMD (crude protein (CP), lipids and carbohydrates) among silages with similar DOMD and consequently variations in energy content per unit of DOMD. The latter was evidenced in the study of Terry and Osburn (1980), in which energy concentration in digestible OM (DOM) varied considerably in grass silages and the variability was highly correlated with the GE concentration in silages. This variation in energy concentration of DOM was further quantified by Givens et al. (1989) in 124 grass silages from 15.5 to 24.5 MJ/kg DOM, with a mean of 19.9. These findings indicate the importance of knowing the silage gross energy (GE) when predicting ME from DOMD (Givens et al., 1989). Using DOMD alone to predict ME concentration in grass silage, as recommended in AFRC (1993), can result in considerable error, especially for very poor or very good quality silages. Therefore, there is a need to develop equations to improve prediction accuracy of silage ME concentration using not only DOMD as the primary predictor but also other variables (e.g., GE and CP) as additional predictors. However, there is little information available in the literature on this approach.
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Since 1992, a total of 174 grass silages have been evaluated for nutrient digestibility and urinary energy output with sheep offered silages as the sole diet at maintenance energy feeding level in a range of studies at the Agricultural Research Institute of Northern Ireland. The objective of the present study was to develop prediction equations for ME concentration and ME/GE using digestible energy (DE) concentration, digestibility of GE, DM or OM or DOMD, and GE or CP concentration. These prediction equations were subsequently validated using previously published grass silage data.
2. Material and methods 2.1. Silages and digestibility trials with sheep The data used in the present study were derived from 174 grass silages. Among them, 136 silages were from a single study (Yan and Agnew, 2004) and selected from commercial farms in Northern Ireland according to their pH, ammonia nitrogen (N) as a proportion of total N, DM and predicted ME concentrations. The latter was estimated from DOMD that was predicted by near infrared reflectance spectroscopy (NIRS, Barber et al., 1990). The objective in selecting silages was to obtain a large range in quality with a relatively even distribution over the whole range. The remaining 38 silages were examined in eight studies with sheep (Gordon et al., 1995; Carrick et al., 1996; Yan et al., 1996; Keady and Mayne, 1998; Ferris et al., 1999, 2002, 2003; Keady et al., 1999). All silages (n = 174) were made from perennial ryegrass dominant swards and encompassed primary growth and first and second regrowth materials. The grass was either unwilted or wilted prior to ensiling and ensiled with or without application of silage additives (e.g., formic acid and inoculant additives). In each case, the 174 silages were offered to four wether sheep as the sole diet at maintenance energy feeding level for 3 or 4 weeks. The sheep were initially housed in individual pens for 13 or 20 days and afterwards in metabolism crates for 8 days with faeces and urine collected during the final 6 days. The crates were designed for separation of faeces and urine. Faeces were weighed daily, stored at 2–4 ◦ C and bulked for each sheep at the end of the 6-day collection period. The fresh faeces were then completely mixed and a sample taken for chemical analysis. The daily urine output was collected into 20 ml of 0.50 l/l sulphuric acid to ensure ammonia preservation, weighed, and a proportional 0.25 aliquot retained daily and bulked for the 6-day period of collection for subsequent energy determination. 2.2. Chemical analysis During the digestibility studies, a representative sample of each silage was retained for analysis of fermentation variables and nutrient concentration. Each sample was then divided into three portions. One portion (approximately 500 g) of fresh silage was used for analysis of oven DM, toluene DM, ammonia N, Kjeldahl N and acid insoluble N using methods described by Steen (1989), while ethanol, propanol, volatile fatty acids, and lactic acid concentration were determined using aqueous extracts of silage (Porter, 1992a). The
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pH of the silage was estimated according to a method (RB427, method 35) of Ministry of Agriculture, Fishery and Food (MAFF, 1981), while GE in silage was determined on a fresh silage sample ground in liquid N (Porter, 1992b). The second portion (approximately 500 g) of each silage was dried at 60 ◦ C for 48 h and milled for determination of watersoluble carbohydrates (Thomas, 1977). The third portion (approximately 500 g) of each silage was dried at 85 ◦ C for 18 h and ground through a 1 mm screen for determination of ash (RB427, method 6) and ether extract (RB427, method 61) (MAFF, 1981); neutral detergent fibre (NDF) (Van Soest, 1976); and acid detergent fibre (ADF) and acid insoluble lignin (method 973.18 (modified)) (Association of Official Analytical Chemists, 1980). NDF was determined with alpha amylase and without sodium sulphite and residual ash was corrected for measurements of both NDF and ADF. The N concentration in faeces was analysed in fresh samples using a tecator Kjeldhal Auto 1030 Analyser (Tecator, Hoganas, Sweden). A fresh sample of faeces was dried at 100 ◦ C over 48 h for determination of DM concentration. The dried sample of faeces was milled through a 1 mm screen and analysed for GE, NDF and ash. The GE concentration in urine was measured in a 10 mL freeze-dried sample, which was contained in a self-sealing polythene bag of known weight and energy concentration. The methods used for chemical analysis of faeces and urine were as previously described. The nutrient concentration and digestibility and pH and ammonia N as a proportion of total N in silages are in Table 1.
Table 1 Chemical composition, nutrient digestibility and energy concentration in grass silages No. of data Grass silage data (kg/kg or kg/kg DM) Dry matter 174 Ash 174 Crude protein 174 Acid detergent fibre 174 Neutral detergent fibre 158 pH 174 Ammonia-N/total-N 174
Mean
S.D.
Minimum
Maximum
0.227 0.081 0.137 0.352 0.545 4.1 0.121
0.0497 0.0136 0.0258 0.0399 0.0551 0.40 0.0644
0.155 0.049 0.079 0.264 0.413 3.5 0.037
0.429 0.124 0.212 0.531 0.756 5.5 0.385
Energy data (MJ/kg DM) Gross energy Digestible energy Metabolisable energya GE digestibility ME/GE
174 174 174 174 174
18.6 12.8 10.3 0.688 0.557
0.65 1.32 1.14 0.0626 0.0546
16.7 9.8 7.7 0.532 0.432
20.5 16.6 13.6 0.814 0.668
Nutrient digestibility Dry matter Organic matter Crude protein Neutral detergent fibre DOMDb
174 174 174 158 174
0.699 0.723 0.660 0.696 0.665
0.0636 0.0647 0.0706 0.0773 0.0584
0.549 0.568 0.445 0.496 0.530
0.813 0.834 0.785 0.819 0.769
a b
Methane energy output was predicted using the equation of Blaxter and Clapperton (1965). Digestible OM in DM.
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Table 2 The correlation coefficients in linear relationships between energy data and digestibility or energy concentration variables in grass silagesa No. of data
Nutrient digestibility Dry matter Organic matter Energy Crude protein Neutral detergent fibre DOMDb
174 174 174 174 158 174
Energy concentration (MJ/kg DM) GE 174 DE 174
Energy data DE (MJ/kg DM)
ME (MJ/kg DM)
GE digestibility
ME/GE
0.87 0.87 0.94 0.71 0.88 0.87
0.86 0.85 0.93 0.68 0.85 0.85
0.97 0.97 – 0.75 0.94 0.96
0.94 0.95 0.99 0.72 0.90 0.94
0.48 –
0.47 0.99
0.16 0.94
0.17 0.93
a All relationships are significant (P < 0.001), except for GE against GE digestibility and ME/GE for which the significance is P < 0.05. b Digestible OM in DM.
2.3. Data analysis The DM concentrations of all 174 silages were corrected for both toluene and alcohol concentrations. All nutrient concentrations and fermentation variables in silages were, therefore, based on the toluene and alcohol-corrected DM concentration. The DE concentration, DOMD and digestibility of DM, OM, CP, GE and NDF in grass silages were measured with sheep, while ME concentrations in silages were estimated as the difference between DE intake and energy outputs from urine and as methane. The latter was predicted using the equation of Blaxter and Clapperton (1965). Correlation coefficients (Table 2) were determined using linear regression between energy variables (DE and ME concentration, GE digestibility and ME/GE) and nutrient digestibility (DM, OM, GE, CP, NDF and DOMD) in silages (Eq. (i)). y = a + bx
(i)
y = a + b 1 x1 + b 2 x2
(ii)
The prediction equations for ME concentration and ME/GE were developed using linear regression with nutrient digestibility data (Eq. (i)) and multiple regression with nutrient digestibility data (x1 ) and concentration of CP or residual GE (GE = GE concentration minus mean GE concentration) (x2 ) (Eq. (ii)). These two equations were fitted, as relevant, to one of the following two equations to remove the experimental effects of the two groups of silage data (136 versus 38 silages); y = ai + b1 x1
(iii)
y = ai + b1 x1 + b2 x2
(iv)
where ai represents the effect of group i for i = 1–2 (136 versus 38 silages), x1 and x2 are the x-variables and b1 and b2 are their regression coefficients.
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All analyses were performed using Genstat, Sixth Edition, 2002 (Lawes Agricultural Trust, Rothamsted, England, UK). The prediction equations for ME concentration and ME/GE developed in the present study were then validated using published grass silage data. Prediction accuracy was examined using the mean-square prediction error (MSPE) as described by Rook et al. (1990). The MSPE is defined as Eq. (v) and can be regarded as the sum of three components (Eq. (vi)). 1 MSPE = (v) (P − A)2 n 2 ¯ 2 + SP2 (1 − b)2 + SA (1 − R2 ) MSPE = (P¯ − A)
(vi)
where P or A is predicted or actual ME concentration (or ME/GE); n is the number of pairs ¯ is the mean of P or A; S 2 or S 2 are the variances of P of values of P and A compared; P¯ or A P A or A, respectively; b and R are, respectively, the slope and correlation coefficient of the linear ¯ line bias (the ¯ A), regression of P on A. The three components are, thus, due to mean bias (P– deviation of the slope) and random variation of the slope. Mean prediction √ error (MPE), ¯ rather than MSPE, was used to describe the prediction accuracy (MPE = MSPE/A).
3. Results 3.1. Nutrient concentration and digestibility There was a large variation in nutrient concentration and digestibility and fermentation data among silages (Table 1). DM concentration ranged from 0.155 to 0.429 kg/kg, GE from 16.7 to 20.5 MJ/kg DM, CP from 0.079 to 0.212 kg/kg DM, NDF from 0.413 to 0.756 kg/kg DM, pH from 3.5 to 5.5 and ammonia N/total N from 0.037 to 0.385 kg/kg. In accordance with these variations, DOMD and digestibility of CP and NDF ranged, respectively, from 0.530 to 0.769, 0.445 to 0.785 and 0.496 to 0.819. DE and ME concentration ranged from 9.8 to 16.6 and 7.7 to 13.6 MJ/kg DM. 3.2. Relationships between energy data and digestibility variables The correlation coefficients (R), derived from linear relationships between energy data (DE and ME concentration and GE digestibility and ME/GE) and digestibility variables or energy concentration (GE or DE), are in Table 2. There was a positive relationship (P < 0.001) between GE concentration and DE or ME concentration, with the R values being 0.48 or 0.47, while the relationship between DE and ME concentration was highly significant (P < 0.001, R = 0.99). Increasing GE and DE concentration also enhanced, respectively, GE digestibility and ME/GE, but the relationships of GE digestibility and ME/GE with DE (P < 0.001, R = 0.94 and 0.93) were much stronger than that with GE concentration (P < 0.05, R = 0.16 and 0.17). The relationships between energy data and each of the digestibility variables were all positive (P < 0.001). In general, the R values in the relationships of each digestibility variable with DE or ME were 0.04–0.10 lower than those with GE digestibility or ME/GE. Relating energy data (DE and ME concentration and GE
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digestibility and ME/GE) to CP digestibility produced a relatively lower R value than those relating to other digestibility variables (0.68–0.75 versus 0.85–0.99). 3.3. Prediction equations for ME concentration and ME/GE Prediction equations for ME concentration and ME/GE in grass silage developed in the present study are in Table 3 and Fig. 1 shows relationships between ME and DE concentration and DOMD, and between ME/GE and GE digestibility and DOMD. All relationships were significant (P < 0.001) and each predictor had an effect (P < 0.05 or less) on the relationship. The prediction of ME concentration was based on DE concentration, GE digestibility plus residual GE concentration (GE = GE concentration − mean GE concentration (18.5 MJ/kg DM)), DOMD and digestibility of DM and OM. The R2 value was very high (0.98) when using DE or GE digestibility plus residual GE concentration as predictors
Table 3 Prediction equations for silage ME and ME/GE using digestibility data and GE or CP concentration (all relationships are significant (P < 0.001); the data in the brackets are S.E. values)a R2
Eq. no.
Equations
(1a) (1b) (2) (3a) (3b) (3c) (3d) (4a) (4b) (4c) (4d) (5a) (5b) (5c) (5d)
ME =
0.856(0.0098) DE − 0.58(0.125) 0.811(0.0011) DE 16.00(0.214) GEd + 0.59(0.021) GE − 0.68(0.148) 15.38(0.705) DMd − 0.40(0.495) 14.80(0.064) DMd 15.09(0.364) DMd + 0.77(0.035) GE − 0.25(0.256) 14.11(0.834) DMd + 5.60(2.052) CP − 0.28(0.488) 15.07(0.700) OMd + 0.54(0.508) 14.32(0.062) OMd 14.89(0.343) OMd + 0.79(0.034) GE − 0.46(0.282) 13.95(0.846) OMd + 4.86(2.116) CP − 0.40(0.506) 16.64(0.781) DOMD − 0.71(0.521) 15.58(0.068) DOMD 16.25(0.438) DOMD + 0.76(0.039) GE − 0.40(0.293) 14.94(0.884) DOMD + 7.32(1.998) CP − 0.56(0.504)
0.98 0.98 0.98 0.74 0.73 0.93 0.75 0.73 0.73 0.94 0.74 0.73 0.72 0.91 0.75
(6a) (6b) (7a) (7b) (7c) (8a) (8b) (8c) (9a) (9b) (9c) (9d)
ME/GE =
0.859(0.0111) GEd − 0.033(0.0077) 0.811(0.0011) GEd 0.811(0.0216) DMd − 0.010(0.0151) 0.797(0.0019) DMd 0.807(0.0197) DMd + 0.012(0.0019) GE − 0.007(0.0138) 0.799(0.0208) OMd − 0.020(0.0151) 0.771(0.0019) OMd 0.796(0.0185) OMd + 0.013(0.0018) GE − 0.019(0.0134) 0.875(0.0252) DOMD − 0.024(0.0168) 0.839(0.0022) DOMD 0.869(0.0235) DOMD + 0.011(0.0021) GE − 0.021(0.0157) 0.838(0.0291) DOMD + 0.159(0.0658) CP − 0.021(0.0166)
0.97 0.97 0.89 0.89 0.91 0.90 0.90 0.92 0.88 0.87 0.89 0.88
a DMd, DM digestibility (kg/kg); DOMD, digestible OM in DM (kg/kg); GEd, GE digestibility (MJ/MJ); GE, residual GE (GE concentration − mean GE concentration (18.5 MJ/kg DM)); OMd, OM digestibility (kg/kg); The unit for DE and ME is MJ/kg DM and for CP kg/kg DM.
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Fig. 1. Relationships between ME and DE concentration (MJ/kg DM) (a), digestible OM in DM (b), between ME/GE and GE digestibility (c), and digestible OM in DM (d) in grass silages (n = 174) with sheep at maintenance energy feeding level.
(Eqs. (1a), (1b) or (2)). Prediction accuracy was reduced (R2 = 0.72–0.74) when DM or OM digestibility or DOMD was used as a single predictor (Eqs. (3a), (3b), (4a), (4b), (5a) or (5b)). Including CP concentration as a secondary predictor in the latter equations slightly increased R2 values (Eqs. (3d), (4d) and (5d)), while including residual GE concentration (Eqs. (3c), (4c) and (5c)) substantially increased R2 values to approximately 0.93, a value which is close to that in Eqs. (1a) and (2). Relating ME/GE to GE digestibility produced a high R2 value (0.97) (Eqs. (6a) and (6b)) that was in accordance with the relationship between ME and DE concentration. The R2 values (0.87–0.90) were also high when using DM or OM digestibility or DOMD alone as a predictor (Eqs. (7a), (7b), (8a), (8b), (9a) or (9b)) and over 15 units higher than those when used alone to predict ME concentration (Eqs. (3a), (3b), (4a), (4b), (5a) and (5b)). Including residual GE concentration as a secondary predictor to the relationships between ME/GE and, respectively, DM and OM digestibility and DOMD slightly increased R2 values (0.89–0.92) (Eqs. (7c), (8c) and (9c)). Addition of CP concentration as a secondary predictor in Eqs. (7a) and (8a) had no significant effect on the relationship between ME/GE and DM or OM digestibility. Addition of CP concentration was, however, significant (P < 0.05) on the relationship between ME/GE and DOMD (Eq. (9d)), although the R2 value remained unchanged.
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4. Discussion 4.1. Prediction of silage ME concentration and ME/GE In comparison with previously published data sets for grass silages (Givens et al., 1989, 1993a,b), the present data set has three unique aspects, in that the data contained a large number of silages (n = 174), the silages used had a large range in nutritional quality, and the data were relatively evenly distributed over the range. Therefore, in the present study, there was a strong relationship between ME concentration and DOMD or digestibility of DM, OM, GE or NDF, with the R values ranging from 0.85 to 0.93 (Table 2). The R values in the relationships between ME/GE and digestibility data were even higher (0.90–0.99), although R value was relatively lower in the relationship of CP digestibility with ME concentration (0.68) or with ME/GE (0.72). There is little comparable information published on this aspect, although Givens et al. (1989) reported a low R value in the relationship between ME concentration and DOMD estimated from pepsin-cellulase (0.57), rumen fluid (0.49) or NDF-cellulase (0.44), using a data set containing 124 clamp grass silages. The relationships between ME concentration and DOMD estimated from rumen fluid and NDF-cellulase (Givens et al., 1989) are recommended in AFRC (1993) to predict the ME concentration for grass silage. Givens et al. (1993a) observed a similar low R value (0.42, 0.45 or 0.48) in the relationship between ME concentration and DOMD estimated from pepsin-cellulase, rumen fluid or NDF-cellulase in big bale grass silages (n = 37). The DM and OM digestibility, and DOMD, were used to predict ME concentration in silages, as they represent the total amount of digestible DM or OM. The prediction of ME concentration using digestibility of NDF and CP are, thus, not considered in the present study. ME concentrations (MJ/kg DM) were 14.8, 14.3 and 15.6 of digestible DM (kg/kg) and DOM (kg/kg) and DOMD (kg/kg DM), respectively (Table 3), when omitting the constant. The latter is similar to that obtained with big bale silages (Givens et al., 1993a), but marginally lower than that recommended in AFRC (1993) (i.e., 16.0) and reported in clamp grass silages (Givens et al., 1989) (16.0). However, prediction of ME concentration using DOMD as a single predictor could result in large errors, as nutrient contents (i.e., CP, lipids and carbohydrates) of DOM can differ in silages with similar DOMD values. This was demonstrated in Fig. 1(b), where the relationship between DOMD and ME concentration obtained in the present study shows that. At a similar DOMD, the range in ME concentration can be over 2 MJ/kg DM between two silages. Therefore, relating DM or OM digestibility, or DOMD to ME/GE (Table 3), rather than relating to ME concentration, substantially increased the R2 from approximately 0.72 to 0.87 (e.g., (b) versus (d) in Fig. 1). The addition of residual GE concentration (i.e., GE concentration minus mean GE concentration) as a secondary predictor to the prediction equations for ME using DM and OM digestibility and DOMD increased the R2 values to over 0.90 (0.91–0.94). Furthermore, addition of CP concentration also increased slightly the R2 values (Table 3). A similar improvement in prediction accuracy was also reported in clamp grass silages (Givens et al., 1989) and in big bale grass silages (Givens et al., 1993a). The R2 values were increased from 0.20 to 0.71 in the former or 0.20 to 0.78 in the latter when GE concentration was added as a
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secondary predictor to the relationship between ME concentration and DOMD estimated from NDF-cellulase. The most accurate predictor for ME concentration in grass silage is likely to be the DE concentration. The R2 value in this relationship was 0.98 in the present study and all plots were very close to the x = y line with only a few data relatively apart from the line (Fig. 1(a)). Similarly, the relationship of ME/GE with GE digestibility also produced a R2 value of 0.97 (Fig. 1(c)). Omitting the constant, ME concentration, or ME/GE, was 0.811 of DE concentration or GE digestibility. This value is similar to that (0.81) reported in the UK feeding stuff tables for grass silage (n = 218) (Ministry of Agriculture Fisheries and Food, 1990) and the same as the mean ME/DE (0.811) in perennial ryegrass silages reported in the French energy feeding system (Institut National De la Recherche Agronomique, 1989). 4.2. Validation of prediction equations developed in the present study using published data The objective of the present validation was to examine the accuracy of all prediction equations developed in the present study when using grass silage data from eight studies published since 1977 (Kelly and Thomas, 1978; Morgan et al., 1980; Thompson et al., 1981; McLellan and McGinn, 1981, 1983; Givens et al., 1989, 1993a,b). The forages used in these studies were grass silages offered alone as a sole feed at or at near maintenance energy feeding level. The animals used were cattle in the studies of Morgan et al. (1980) and Thompson et al. (1981), while in the remaining six studies sheep were used. All data (n = 21) were derived from single silages (n = 18), with the exception of the studies of Givens et al. (1989, 1993a,b) in which the data were mean values from 124, 37 and 9 silages, respectively. Because Thompson et al. (1981) and Givens et al. (1989, 1993a,b) did not report DM digestibility, there were 16 data for the valuation of prediction equations with DM digestibility as a predictor. The results of the validation using the MSPE technique are in Table 4. Results with Eqs. (1b), (3b), (4b), (5b), (6b), (7b), (8b) and (9b) are not presented because they are similar to those of Eqs. (1a), (3a), (4a), (5a), (6a), (7a), (8a) and (9a), respectively. Silage DM concentration in the studies used for the present validation was based on a toluene corrected DM basis, while in the present study silage DM concentration was corrected for both toluene and alcohol. Therefore, the predicted values using the equations developed in the present study were adjusted from MJ/kg TADM (toluene and alcohol-corrected DM) to MJ/kg TDM (toluene-corrected DM), using the mean alcohol proportion in the alcohol and toluene-corrected DM obtained in the present study. Prediction of ME concentration using DE concentration (Eq. (1a)) or GE digestibility with residual GE concentration (GE concentration minus mean GE concentration) (Eq. (2)) produced a low MPE. The MPE values were much higher in the prediction of ME concentration from equations using DM or OM digestibility or DOMD alone or with CP or residual GE concentration (Eqs. (3a)–(5d) and AFRC (1993)). The ME concentration predicted from Eqs. (1a) and (2) was close, or equal to, actual ME concentration with the majority of prediction errors derived from random variation. The ME concentration was under-predicted by 0.2–0.4 MJ/kg DM when using digestibility data alone (Eqs. (3a), (4a), (5a) and AFRC (1993)). Adding CP or residual GE concentration as a secondary predictor (Eqs. (3c), (3d), (4c), (4d), (5c) and (5d)) reduced
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Table 4 Validation of prediction equations for silage ME and ME/GE developed in the present study using grass silage data published since 1977a Predictors
Equations
No. of data
ME content Predicted
S.E.
MPEb
Actual
Proportion of MSPE Bias
Line
Random
Prediction of ME concentration (MJ/kg DM) DE (1a) 21 11.1 GEd + GE (2) 21 11.2 DMd (3a) 16 11.1 DMd + GE (3c) 16 11.2 DMd + CP (3d) 16 11.2 OMd (4a) 21 11.0 OMd + GE (4c) 21 11.1 OMd + CP (4d) 21 11.1 DOMD (5a) 21 10.9 DOMD + GE (5c) 21 11.1 DOMD + CP (5d) 21 11.1 DOMD AFRCc 21 11.0
11.2 11.2 11.4 11.4 11.4 11.2 11.2 11.2 11.2 11.2 11.2 11.2
0.31 0.29 0.37 0.38 0.44 0.31 0.34 0.40 0.29 0.32 0.42 0.27
0.029 0.031 0.061 0.052 0.050 0.050 0.039 0.046 0.061 0.046 0.050 0.058
0.14 0.01 0.33 0.20 0.23 0.11 0.02 0.03 0.24 0.04 0.07 0.12
0.00 0.09 0.05 0.04 0.00 0.18 0.08 0.03 0.21 0.17 0.03 0.27
0.86 0.90 0.62 0.76 0.77 0.71 0.90 0.94 0.55 0.79 0.90 0.61
Prediction of ME/GE (MJ/MJ) GEd (6a) DMd (7a) DMd + GE (7c) OMd (8a) OMd + GE (8c) DOMD (9a) DOMD + GE (9c) DOMD + CP (9d)
0.60 0.61 0.61 0.60 0.60 0.60 0.60 0.60
0.015 0.019 0.019 0.016 0.017 0.014 0.015 0.017
0.031 0.054 0.052 0.041 0.039 0.051 0.050 0.046
0.01 0.26 0.18 0.05 0.01 0.20 0.17 0.12
0.10 0.05 0.04 0.16 0.11 0.21 0.19 0.12
0.90 0.69 0.77 0.80 0.88 0.59 0.63 0.76
21 16 16 21 21 21 21 21
0.60 0.59 0.60 0.59 0.60 0.58 0.59 0.59
a DMd, DM digestibility; DOMD, digestible OM in DM; GEd, GE digestibility; GE, residual GE (GE concentration minus mean GE concentration); OMd, OM digestibility. √ b MPE, mean prediction error (= MSPE/A; ¯ A, ¯ actual mean value). c AFRC equation (ME (MJ/kg DM) = 16 DOMD (kg/kg DM)) (AFRC, 1993).
this under-prediction to 0.1–0.2 MJ/kg DM and, therefore, decreased the prediction error of mean bias (predicted−actual ME concentration) and increased the error of random variation. The inclusion of a secondary predictor also reduced the error derived from the line (slope) in Eqs. (3c), (3d), (4c), (4d), (5c) and (5d). Similar results (Table 4) were also obtained with prediction of ME/GE using GE, DM, OM digestibility and DOMD alone or with CP (Eq. (9d) only) and residual GE concentration. Residual plots were also used to validate the prediction accuracy by graphing the predicted ME concentration or ME/GE (x-axis) against the corresponding difference (y-axis) between predicted and actual data. The results are in Fig. 2(a) and (b) for ME concentration and in Fig. 3 for ME/GE. The residual plots using DE concentration (Eq. (1a)) or GE digestibility with residual GE concentration (Eq. (2)) as predictors were distributed around the 0 line, with the predicted ME concentrations ranging from 9.5 to 12.5 MJ/kg DM. The residual plots were much more scattered when using digestibility of DM (Eq. (3a)) and OM (Eq. (4a)) and DOMD (Eq. (5a)) and equation of AFRC (1993) alone as a single predictor. The range of predicted ME concentrations was between 10 and 12 MJ/kg DM. Adding CP or residual GE concentration as a secondary predictor increased the range of predicted
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Fig. 2. Predicted (equations developed in the present study) (x axis) against residual (predicted minus actual) (y axis) ME concentration (MJ/kg DM) using grass silage data published since 1977 (n = 16 for Eqs. (3a)–(3d), n = 21 for others) (DOMD, digestible OM in DM).
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Fig. 3. Predicted (equations developed in the present study) (x-axis) against residual (predicted minus actual) (y-axis) ME/GE using grass silage data published since 1977 (n = 16 for Eqs. (7a) and (7c), n = 21 for others) (DOMD, digestible OM in DM).
ME concentrations, although the residual plots were still relatively scattered. However, the residual plots for prediction of ME/GE using digestibility of GE, DM and OM and DOMD were all relatively evenly distributed around the 0 line, although the range of predicted ME/GE with Eqs. (6a) and (8c) was greater than that with Eqs. (7a), (7c), (8a), (9a), (9c) and (9d). Based on these results, we conclude that ME concentration and ME/GE in grass silages can be very accurately predicted using DE concentration and GE digestibility as a sole predictor, respectively. The prediction error for ME concentration using DE concentration or GE digestibility with residual GE concentration, or for ME/GE using GE digestibility,
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was very small and mainly derived from random variation. Using DM and OM digestibility and DOMD as a sole predictor to predict ME concentration can result in error, but this error can be largely reduced by adding residual GE concentration as a secondary predictor. 4.3. Validity of prediction of silage ME concentration using DOMD as a sole predictor AFRC (1993) recommends a factor of 16 to calculate ME concentration (MJ/kg DM) in grass silage based on its DOMD (kg/kg). This concept is widely used in UK livestock feeding programmes. However, this equation, which assumes that ME concentration in DOM is a constant, is not justified. The energy concentrations in DOM can vary between silages, as CP, lipid and carbohydrate contents in DOM can differ in accordance with their concentrations in total DM of grass silages. For example, in the present study the energy concentration in DOM followed a normal distribution (16.6–21.8, mean 19.2 (S.D. 0.99) MJ/kg DOM), with peak values being between 18.6 and 19.7 MJ/kg DOM (Fig. 4). A similar normal distribution of energy concentrations for DOM was also reported by Givens et al. (1989) in 124 grass silages and the range (15.5–24.5 MJ/kg DOM) was even greater than that in the present study. This large difference in energy concentration of DOM cannot be accounted for by differences in energy outputs in urine and methane when calculating ME concentration. This is supported by the findings in Table 5, that there were positive relationships between ME content per unit of DOMD and energy and CP concentrations in grass silages. In the data set of grass silages (n = 21) published since 1977, used in the previous validation, ME content per unit of DOMD increased with increasing DOMD (P < 0.05) and concentrations of GE (P < 0.01), DE (P < 0.001), ME (P < 0.001) and CP (P < 0.05). Similar results were also found when using the present data set of grass silages (n = 174), although there was no significant relationship between ME content per unit of DOMD and DOMD. These findings indicate that the ME per unit of DOMD is not constant,
Fig. 4. The distribution of energy concentration of digested OM in grass silages (n = 174) used in the present study.
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Table 5 The relationships between the ratio of ME concentration over DOMD (ME/DOMD) and GE, ME or CP concentration or DOMD in grass silages (the data in the brackets are S.E. values)a Equations Grass silage data published since 1977 (n = 21) ME/DOMD = 1.29(0.437) GE − 7.88(8.174) 0.68(0.112) DE + 7.18(1.508) 0.82(0.094) ME + 7.10(1.052) 10.66(4.712) CP + 14.54(0.804) 15.44(5.622) DOMD + 5.72(3.860) Grass silage data obtained in the present study (n = 174) ME/DOMD = 1.14(0.060) GE − 5.55(1.108) 0.38(0.044) DE + 10.75(0.559) 0.47(0.049) ME + 10.71(0.506) 11.70(2.468) CP + 13.93(0.345)
R2
Significanceb
0.32 0.66 0.80 0.21 0.28
** *** *** * *
0.68 0.30 0.35 0.12
*** *** *** ***
a
DOMD, digestible OM in DM (kg/kg); The unit for GE and ME concentration is MJ/kg DM and for CP concentration kg/kg DM. b *, P < 0.05; **, P < 0.01; ***, P < 0.001.
but varies with differing silage chemical composition. This may account for the finding in the present study (Table 3) that addition of residual GE concentration as a secondary predictor to equations for ME concentration using DM or OM digestibility or DOMD substantially improved the relationship, with R2 values being increased from approximately 0.73 to over 0.90. This improvement was evidenced in the previous validation using the grass silage data (n = 21) published since 1977. Adding residual GE concentration as a secondary predictor (Eqs. (3c), (4c) and (5c) in Table 4), in comparison with the prediction of ME concentration using DM or OM digestibility or DOMD alone, reduced MPE and markedly increased the error derived from the random variation. Prediction of silage ME concentration using DOMD alone, as recommended in AFRC (1993), results in substantial errors in ME estimation. This error may be greater for very poor or very good quality silages. For example, when validating the equation of AFRC (1993) using grass silage data published since 1977 as reported previously, for very poor quality silage the maximum over-prediction of ME concentration was 1.2 MJ/kg DM or proportionately 0.13 of actual ME concentration. The corresponding value for the maximum under-prediction with very good quality silage was 1.3 MJ/kg DM or 0.10. If data for GE concentration are available, they should be used as a secondary predictor (Eq. (5c)) to improve the prediction accuracy.
5. Conclusions DE concentration is the most accurate predictor for ME concentration in grass silage. Prediction of silage ME concentration using DOMD, or digestibility of DM or OM, as a single predictor can result in error, especially for very poor or very good quality silages, as ME content per unit of DOM can vary greatly. Addition of GE concentration as a secondary predictor can substantially improve the relationship between ME concentration and each of the digestibility data and the prediction accuracy for ME concentration. If DOMD continues
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to be used to predict ME concentration in grass silages, as recommended in AFRC (1993), GE concentration should be considered as a secondary predictor to improve prediction accuracy. This can be achieved by using the NIRS technique that has been demonstrated by Park et al. (1997) to have the ability to predict both DOMD and GE concentration in grass silage.
Acknowledgements The authors wish to thank their colleagues at the Agricultural Research Institute of Northern Ireland for access to the data used in the present study.
References Agricultural and Food Research Council (AFRC), 1993. Energy and Protein Requirements of Ruminants, CAB International, Wallingford, Oxon, UK. Association of Official Analytical Chemists, 1980. Official Methods of Analysis, AOAC, Washington, DC, USA. Barber, G.D., Givens, D.I., Kridis, M.S., Officer, N.W., Murray, I., 1990. Prediction of the organic matter digestibility of grass silage. Anim. Feed Sci. Technol. 28, 115–128. Blaxter, K., Clapperton, J.L., 1965. Prediction of the amount of methane produced by ruminants. Br. J. Nutr. 19, 511–522. Carrick, I.M., Patterson, D.C., Gordon, F.J., Mayne, C.S., 1996. The effect of quality and level of protein on the performance of dairy cattle of differing genetic merits. Anim. Sci. 62, 642, Abstr. Ferris, C.P., Gordon, F.J., Patterson, D.C., Mayne, C.S., McCoy, M.A., 2003. A short-term comparison of the performance of four grassland-based systems of milk production for autumn-calving dairy cows. Grass Forage Sci. 58, 192–209. Ferris, C.P., Gordon, F.J., Patterson, D.C., Porter, M.G., Yan, T., 1999. The effect of genetic merit and concentrate proportion in the diet on nutrient utilisation by lactating dairy cows. J. Agric. Sci., Cambridge 132, 483–490. Ferris, C.P., McCoy, M.A., Lennox, S.D., Catney, D.C., Gordon, F.J., 2002. Nutrient utilisation and energy balance associated with two contrasting winter milk production systems for high genetic merit autumn calving dairy cows. Ir. J. Agric. Food Res. 41, 55–70. Givens, D.I., Everington, J.M., Adamson, A.H., 1989. The digestibility and metabolisable energy content of grass silage and their prediction from laboratory measurements. Anim. Feed Sci. Technol. 24, 27–43. Givens, D.I., Moss, A.R., Adamson, A.H., 1993a. Prediction of the digestibility and energy value of grass silage conserved in big bales. Anim. Feed Sci. Technol. 41, 297–312. Givens, D.I., Moss, A.R., Adamson, A.H., 1993b. The digestibility and energy value of badly preserved grass silages. Anim. Feed Sci. Technol. 42, 97–107. Gordon, F.J., Patterson, D.C., Yan, T., Porter, M.G., Mayne, C.S., Unsworth, E.F., 1995. The influence of genetic index for milk production on the response to complete diet feeding and the utilisation of energy and nitrogen. Anim. Sci. 61, 199–210. Institut National De la Recherche Agronomique, 1989. Ruminant Nutrition—Recommended Allowances and Feed Tables, John Libbey Eurotext, Paris/London/Rome, France. Keady, T.W.J., Mayne, C.S., 1998. The effects of concentrate energy source on silage feeding behaviour and energy utilisation by lactating dairy cows offered grass silages with differing intake characteristics. Anim. Sci. 67, 225–236. Keady, T.W.J., Mayne, C.S., Fitzpatrick, D.A., Marsden, M., 1999. The effects of energy source and level of digestible undegradable protein in concentrates on silage intake and performance of lactating dairy cows offered a range of grass silages. Anim. Sci. 68, 763–777. Kelly, N.C., Thomas, P.C., 1978. The nutritive value of silages. Energy metabolism in sheep receiving diets of grass silage or grass silage and barley. Br. J. Nutr. 40, 205–219.
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McLellan, A.R., McGinn, R.A., 1981. Calorimetric investigation of the nutritive value of formic acid- and formaldehyde-formic acid-treated grass silages. Anim. Feed Sci. Technol. 6, 245–256. McLellan, A.R., McGinn, R.A., 1983. Energy and nitrogen balance, intake and growth rate of lambs fed on unwilted grass silages treated with a formaldehyde-acid mixture or untreated. Anim. Feed Sci. Technol. 9, 107–119. Ministry of Agriculture, Fisheries and Food (MAFF) 1990. In: Givens, D.I., Moss, A.R. (Eds.), UK Tables of Nutritive Value and Chemical Composition of Feedingstuffs, Rowett Research Services Ltd., Aberdeen, UK. Ministry of Agriculture, Fisheries and Food (MAFF) 1981. The Analysis of Agricultural Materials, HMSO, London. Morgan, C.A., Edwards, R.A., McDonald, P., 1980. Intake and metabolism studies with fresh and wilted silages. J. Agric. Sci., Cambridge 94, 287–298. Park, P.S., Agnew, R.E., Gordon, F.J., Steen, R.W.J., 1997. The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters. Anim. Feed Sci. Technol. 72, 155–167. Porter, M. G., 1992a. Comparison of five methods for the determination of lactic acid in silage. in: Proceedings of the Br. Grass. Soc. Third Res. Conf., Antrim, UK, 123–124. Porter, M.G., 1992b. Comparison of sample preparation methods for the determination of the gross energy concentration of fresh silage. Anim. Feed Sci. Technol. 37, 201–208. Rook, A.J., Dhanoa, M.S., Gill, M., 1990. Prediction of the voluntary intake of grass silages by beef cattle. 3. Precision of alternative prediction models. Anim. Prod. 50, 455–466. Steen, R.W.J., 1989. A comparison of soya-bean, sunflower and fish meals as protein supplements for yearling cattle offered grass silage-based diets. Anim. Prod. 48, 81–89. Terry, R. A., Osburn, D. F. 1980. Determination and prediction of digestible energy in silages. In: Forage Conservation in the 80’s, British Grassland Society Occasional Symposium No. 11, 315-318, UK. Thomas, T.A., 1977. An automated procedure for the determination of soluble carbohydrates in herbage. J. Sci. Food Agric. 28, 639–642. Thompson, D.J., Beever, D.E., Lonsdale, C.R., Haines, M.J., Cammell, S.B., Austin, A.R., 1981. The digestion by cattle of grass silage made with formic acid and formic acid-formaldehyde. Br. J. Nutr. 46, 193–207. Van Soest, P.J., 1976. Laboratory mentods for evaluating the energy value of feedstuffs. In: Swan, H., Lewis, D. (Eds.), Feed and Energy Sources for Livestock. Butterworths, London, UK. Yan, T., Patterson, D.C., Gordon, F.J., Porter, M.G., 1996. The effects of wilting of grass prior to ensiling on the response to bacterial inoculation. 1. Silage fermentation and nutrient utilisation over three harvests. Anim. Sci. 62, 405–417. Yan, T., Agnew, R.E., 2004. Prediction of nutritive values in grass silages: I. Nutrient digestibility and energy concentrations using nutrient compositions and fermentation characteristics. J. Anim. Sci. 82, 1367–1379.
Prediction of metabolisable energy concentrations from nutrient digestibility and chemical composition in grass silages offered to sheep at maintenance T. Yan∗ , R.E. Agnew1 The Agricultural Research Institute of Northern Ireland, Hillsborough, Co Down, Northern Ireland BT26 6DR, UK Received 16 January 2004; received in revised form 26 August 2004; accepted 1 September 2004
Abstract A total of 174 perennial ryegrass silages were evaluated in nine studies for chemical composition, nutrient digestibility and urinary energy output with sheep (four sheep/silage) offered the silage as a sole diet at maintenance energy feeding level. Silage metabolisable energy (ME) concentration was estimated from measured energy intake and outputs from faeces and urine and predicted methane energy. All silage data were expressed on an alcohol corrected toluene dry matter (DM) basis. The objectives were to use these silage data to develop prediction equations for ME concentration and ME/GE (gross energy) and then validate these equations using published grass silage data. There was a large range in ME concentration (7.7–13.6 MJ/kg DM), ME/GE (0.432–0.668) and digestible organic matter in DM (DOMD; 0.530–0.769). The ME concentration and ME/GE were positively related to GE and DE concentration, DOMD and digestibility of DM, organic matter (OM), GE, crude protein (CP) and neutral detergent fibre (P < 0.05 or less). Prediction of ME concentration using digestible energy (DE) or GE digestibility plus residual GE concentration (GE—mean GE) produced a strong relationship (R2 = 0.98), while using DM or OM digestibility or DOMD as a sole predictor reduced R2 Abbreviations: CP, crude protein; DE, digestible energy; DM, dry matter; DOM, digestible organic matter; DOMD, digestible organic matter in dry matter; GE, gross energy; GE, residual gross energy (gross energy concentration minus mean gross energy concentration); ME, metabolisable energy; MPE; mean prediction error; MSPE, mean square prediction error; N, nitrogen; NDF, neutral detergent fibre; NIRS, near infrared reflectance spectroscopy; R, correlation coefficient ∗ Corresponding author. Tel.: +44 28 9268 2484; fax: +44 28 9268 9594. E-mail address: [email protected] (T. Yan). 1 Also a member of staff of Department of Agriculture and Rural Development of Northern Ireland, and The Queen’s University of Belfast, Belfast, Northern Ireland BT9 5PX. 0377-8401/$ – see front matter © 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.anifeedsci.2004.09.002
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values to approximately 0.73. The latter R2 values were marginally increased when CP concentration was added as a secondary predictor, and substantially increased to over 0.90 when residual GE was added. Prediction of ME/GE using GE digestibility produced a higher R2 value (0.97) than those (0.88–0.90) using DM or OM digestibility or DOMD. The R2 values were marginally increased when adding CP or residual GE concentration as a secondary predictor to the latter relationships. These equations were validated using published grass silage data since 1977 (n = 21) and the mean-squareprediction error. Prediction of ME using DE or GE digestibility with residual GE had the lowest mean prediction error (MPE), with the predicted ME close to observed ME, and the majority of error derived from random variation. Using DM or OM digestibility or DOMD as a sole predictor for ME concentration produced a relatively large MPE, while adding CP or residual GE generally reduced the MPE and errors derived from both bias (predicted−actual) and line (slope). Similar results also occurred for prediction of ME/GE. DE concentration is the most accurate predictor for ME concentration. Prediction of ME using OM digestibility or DOMD as a sole predictor can result in error, but the prediction accuracy can be improved by adding GE concentration as a secondary predictor. © 2004 Elsevier B.V. All rights reserved. Keywords: Grass silage; Digestibility; ME concentration; Prediction equation; Validation
1. Introduction Grass silage is a major feed for ruminants in western, eastern and northern Europe, but its quality varies according to variety, maturity, dry matter (DM) concentration and ensiling technique. The metabolisable energy (ME) concentration in grass silages, thus, has to be determined individually when formulating rations for ruminant animals under practical conditions. The common practice for determination of silage ME concentration is to relate it to its digestible nutrient proportion. In the UK, the digestible organic matter (OM) in DM (DOMD) (kg/kg) in grass silage is recommended (Agricultural and Food Research Council, AFRC, 1993) to calculate ME concentration (MJ/kg DM) by multiplying by a factor of 16. The DOMD can be measured in digestibility studies with sheep or cattle offered the silage at maintenance energy feeding level. However, this relationship ignores possible differences in nutrient proportions in DOMD (crude protein (CP), lipids and carbohydrates) among silages with similar DOMD and consequently variations in energy content per unit of DOMD. The latter was evidenced in the study of Terry and Osburn (1980), in which energy concentration in digestible OM (DOM) varied considerably in grass silages and the variability was highly correlated with the GE concentration in silages. This variation in energy concentration of DOM was further quantified by Givens et al. (1989) in 124 grass silages from 15.5 to 24.5 MJ/kg DOM, with a mean of 19.9. These findings indicate the importance of knowing the silage gross energy (GE) when predicting ME from DOMD (Givens et al., 1989). Using DOMD alone to predict ME concentration in grass silage, as recommended in AFRC (1993), can result in considerable error, especially for very poor or very good quality silages. Therefore, there is a need to develop equations to improve prediction accuracy of silage ME concentration using not only DOMD as the primary predictor but also other variables (e.g., GE and CP) as additional predictors. However, there is little information available in the literature on this approach.
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Since 1992, a total of 174 grass silages have been evaluated for nutrient digestibility and urinary energy output with sheep offered silages as the sole diet at maintenance energy feeding level in a range of studies at the Agricultural Research Institute of Northern Ireland. The objective of the present study was to develop prediction equations for ME concentration and ME/GE using digestible energy (DE) concentration, digestibility of GE, DM or OM or DOMD, and GE or CP concentration. These prediction equations were subsequently validated using previously published grass silage data.
2. Material and methods 2.1. Silages and digestibility trials with sheep The data used in the present study were derived from 174 grass silages. Among them, 136 silages were from a single study (Yan and Agnew, 2004) and selected from commercial farms in Northern Ireland according to their pH, ammonia nitrogen (N) as a proportion of total N, DM and predicted ME concentrations. The latter was estimated from DOMD that was predicted by near infrared reflectance spectroscopy (NIRS, Barber et al., 1990). The objective in selecting silages was to obtain a large range in quality with a relatively even distribution over the whole range. The remaining 38 silages were examined in eight studies with sheep (Gordon et al., 1995; Carrick et al., 1996; Yan et al., 1996; Keady and Mayne, 1998; Ferris et al., 1999, 2002, 2003; Keady et al., 1999). All silages (n = 174) were made from perennial ryegrass dominant swards and encompassed primary growth and first and second regrowth materials. The grass was either unwilted or wilted prior to ensiling and ensiled with or without application of silage additives (e.g., formic acid and inoculant additives). In each case, the 174 silages were offered to four wether sheep as the sole diet at maintenance energy feeding level for 3 or 4 weeks. The sheep were initially housed in individual pens for 13 or 20 days and afterwards in metabolism crates for 8 days with faeces and urine collected during the final 6 days. The crates were designed for separation of faeces and urine. Faeces were weighed daily, stored at 2–4 ◦ C and bulked for each sheep at the end of the 6-day collection period. The fresh faeces were then completely mixed and a sample taken for chemical analysis. The daily urine output was collected into 20 ml of 0.50 l/l sulphuric acid to ensure ammonia preservation, weighed, and a proportional 0.25 aliquot retained daily and bulked for the 6-day period of collection for subsequent energy determination. 2.2. Chemical analysis During the digestibility studies, a representative sample of each silage was retained for analysis of fermentation variables and nutrient concentration. Each sample was then divided into three portions. One portion (approximately 500 g) of fresh silage was used for analysis of oven DM, toluene DM, ammonia N, Kjeldahl N and acid insoluble N using methods described by Steen (1989), while ethanol, propanol, volatile fatty acids, and lactic acid concentration were determined using aqueous extracts of silage (Porter, 1992a). The
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pH of the silage was estimated according to a method (RB427, method 35) of Ministry of Agriculture, Fishery and Food (MAFF, 1981), while GE in silage was determined on a fresh silage sample ground in liquid N (Porter, 1992b). The second portion (approximately 500 g) of each silage was dried at 60 ◦ C for 48 h and milled for determination of watersoluble carbohydrates (Thomas, 1977). The third portion (approximately 500 g) of each silage was dried at 85 ◦ C for 18 h and ground through a 1 mm screen for determination of ash (RB427, method 6) and ether extract (RB427, method 61) (MAFF, 1981); neutral detergent fibre (NDF) (Van Soest, 1976); and acid detergent fibre (ADF) and acid insoluble lignin (method 973.18 (modified)) (Association of Official Analytical Chemists, 1980). NDF was determined with alpha amylase and without sodium sulphite and residual ash was corrected for measurements of both NDF and ADF. The N concentration in faeces was analysed in fresh samples using a tecator Kjeldhal Auto 1030 Analyser (Tecator, Hoganas, Sweden). A fresh sample of faeces was dried at 100 ◦ C over 48 h for determination of DM concentration. The dried sample of faeces was milled through a 1 mm screen and analysed for GE, NDF and ash. The GE concentration in urine was measured in a 10 mL freeze-dried sample, which was contained in a self-sealing polythene bag of known weight and energy concentration. The methods used for chemical analysis of faeces and urine were as previously described. The nutrient concentration and digestibility and pH and ammonia N as a proportion of total N in silages are in Table 1.
Table 1 Chemical composition, nutrient digestibility and energy concentration in grass silages No. of data Grass silage data (kg/kg or kg/kg DM) Dry matter 174 Ash 174 Crude protein 174 Acid detergent fibre 174 Neutral detergent fibre 158 pH 174 Ammonia-N/total-N 174
Mean
S.D.
Minimum
Maximum
0.227 0.081 0.137 0.352 0.545 4.1 0.121
0.0497 0.0136 0.0258 0.0399 0.0551 0.40 0.0644
0.155 0.049 0.079 0.264 0.413 3.5 0.037
0.429 0.124 0.212 0.531 0.756 5.5 0.385
Energy data (MJ/kg DM) Gross energy Digestible energy Metabolisable energya GE digestibility ME/GE
174 174 174 174 174
18.6 12.8 10.3 0.688 0.557
0.65 1.32 1.14 0.0626 0.0546
16.7 9.8 7.7 0.532 0.432
20.5 16.6 13.6 0.814 0.668
Nutrient digestibility Dry matter Organic matter Crude protein Neutral detergent fibre DOMDb
174 174 174 158 174
0.699 0.723 0.660 0.696 0.665
0.0636 0.0647 0.0706 0.0773 0.0584
0.549 0.568 0.445 0.496 0.530
0.813 0.834 0.785 0.819 0.769
a b
Methane energy output was predicted using the equation of Blaxter and Clapperton (1965). Digestible OM in DM.
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Table 2 The correlation coefficients in linear relationships between energy data and digestibility or energy concentration variables in grass silagesa No. of data
Nutrient digestibility Dry matter Organic matter Energy Crude protein Neutral detergent fibre DOMDb
174 174 174 174 158 174
Energy concentration (MJ/kg DM) GE 174 DE 174
Energy data DE (MJ/kg DM)
ME (MJ/kg DM)
GE digestibility
ME/GE
0.87 0.87 0.94 0.71 0.88 0.87
0.86 0.85 0.93 0.68 0.85 0.85
0.97 0.97 – 0.75 0.94 0.96
0.94 0.95 0.99 0.72 0.90 0.94
0.48 –
0.47 0.99
0.16 0.94
0.17 0.93
a All relationships are significant (P < 0.001), except for GE against GE digestibility and ME/GE for which the significance is P < 0.05. b Digestible OM in DM.
2.3. Data analysis The DM concentrations of all 174 silages were corrected for both toluene and alcohol concentrations. All nutrient concentrations and fermentation variables in silages were, therefore, based on the toluene and alcohol-corrected DM concentration. The DE concentration, DOMD and digestibility of DM, OM, CP, GE and NDF in grass silages were measured with sheep, while ME concentrations in silages were estimated as the difference between DE intake and energy outputs from urine and as methane. The latter was predicted using the equation of Blaxter and Clapperton (1965). Correlation coefficients (Table 2) were determined using linear regression between energy variables (DE and ME concentration, GE digestibility and ME/GE) and nutrient digestibility (DM, OM, GE, CP, NDF and DOMD) in silages (Eq. (i)). y = a + bx
(i)
y = a + b 1 x1 + b 2 x2
(ii)
The prediction equations for ME concentration and ME/GE were developed using linear regression with nutrient digestibility data (Eq. (i)) and multiple regression with nutrient digestibility data (x1 ) and concentration of CP or residual GE (GE = GE concentration minus mean GE concentration) (x2 ) (Eq. (ii)). These two equations were fitted, as relevant, to one of the following two equations to remove the experimental effects of the two groups of silage data (136 versus 38 silages); y = ai + b1 x1
(iii)
y = ai + b1 x1 + b2 x2
(iv)
where ai represents the effect of group i for i = 1–2 (136 versus 38 silages), x1 and x2 are the x-variables and b1 and b2 are their regression coefficients.
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All analyses were performed using Genstat, Sixth Edition, 2002 (Lawes Agricultural Trust, Rothamsted, England, UK). The prediction equations for ME concentration and ME/GE developed in the present study were then validated using published grass silage data. Prediction accuracy was examined using the mean-square prediction error (MSPE) as described by Rook et al. (1990). The MSPE is defined as Eq. (v) and can be regarded as the sum of three components (Eq. (vi)). 1 MSPE = (v) (P − A)2 n 2 ¯ 2 + SP2 (1 − b)2 + SA (1 − R2 ) MSPE = (P¯ − A)
(vi)
where P or A is predicted or actual ME concentration (or ME/GE); n is the number of pairs ¯ is the mean of P or A; S 2 or S 2 are the variances of P of values of P and A compared; P¯ or A P A or A, respectively; b and R are, respectively, the slope and correlation coefficient of the linear ¯ line bias (the ¯ A), regression of P on A. The three components are, thus, due to mean bias (P– deviation of the slope) and random variation of the slope. Mean prediction √ error (MPE), ¯ rather than MSPE, was used to describe the prediction accuracy (MPE = MSPE/A).
3. Results 3.1. Nutrient concentration and digestibility There was a large variation in nutrient concentration and digestibility and fermentation data among silages (Table 1). DM concentration ranged from 0.155 to 0.429 kg/kg, GE from 16.7 to 20.5 MJ/kg DM, CP from 0.079 to 0.212 kg/kg DM, NDF from 0.413 to 0.756 kg/kg DM, pH from 3.5 to 5.5 and ammonia N/total N from 0.037 to 0.385 kg/kg. In accordance with these variations, DOMD and digestibility of CP and NDF ranged, respectively, from 0.530 to 0.769, 0.445 to 0.785 and 0.496 to 0.819. DE and ME concentration ranged from 9.8 to 16.6 and 7.7 to 13.6 MJ/kg DM. 3.2. Relationships between energy data and digestibility variables The correlation coefficients (R), derived from linear relationships between energy data (DE and ME concentration and GE digestibility and ME/GE) and digestibility variables or energy concentration (GE or DE), are in Table 2. There was a positive relationship (P < 0.001) between GE concentration and DE or ME concentration, with the R values being 0.48 or 0.47, while the relationship between DE and ME concentration was highly significant (P < 0.001, R = 0.99). Increasing GE and DE concentration also enhanced, respectively, GE digestibility and ME/GE, but the relationships of GE digestibility and ME/GE with DE (P < 0.001, R = 0.94 and 0.93) were much stronger than that with GE concentration (P < 0.05, R = 0.16 and 0.17). The relationships between energy data and each of the digestibility variables were all positive (P < 0.001). In general, the R values in the relationships of each digestibility variable with DE or ME were 0.04–0.10 lower than those with GE digestibility or ME/GE. Relating energy data (DE and ME concentration and GE
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digestibility and ME/GE) to CP digestibility produced a relatively lower R value than those relating to other digestibility variables (0.68–0.75 versus 0.85–0.99). 3.3. Prediction equations for ME concentration and ME/GE Prediction equations for ME concentration and ME/GE in grass silage developed in the present study are in Table 3 and Fig. 1 shows relationships between ME and DE concentration and DOMD, and between ME/GE and GE digestibility and DOMD. All relationships were significant (P < 0.001) and each predictor had an effect (P < 0.05 or less) on the relationship. The prediction of ME concentration was based on DE concentration, GE digestibility plus residual GE concentration (GE = GE concentration − mean GE concentration (18.5 MJ/kg DM)), DOMD and digestibility of DM and OM. The R2 value was very high (0.98) when using DE or GE digestibility plus residual GE concentration as predictors
Table 3 Prediction equations for silage ME and ME/GE using digestibility data and GE or CP concentration (all relationships are significant (P < 0.001); the data in the brackets are S.E. values)a R2
Eq. no.
Equations
(1a) (1b) (2) (3a) (3b) (3c) (3d) (4a) (4b) (4c) (4d) (5a) (5b) (5c) (5d)
ME =
0.856(0.0098) DE − 0.58(0.125) 0.811(0.0011) DE 16.00(0.214) GEd + 0.59(0.021) GE − 0.68(0.148) 15.38(0.705) DMd − 0.40(0.495) 14.80(0.064) DMd 15.09(0.364) DMd + 0.77(0.035) GE − 0.25(0.256) 14.11(0.834) DMd + 5.60(2.052) CP − 0.28(0.488) 15.07(0.700) OMd + 0.54(0.508) 14.32(0.062) OMd 14.89(0.343) OMd + 0.79(0.034) GE − 0.46(0.282) 13.95(0.846) OMd + 4.86(2.116) CP − 0.40(0.506) 16.64(0.781) DOMD − 0.71(0.521) 15.58(0.068) DOMD 16.25(0.438) DOMD + 0.76(0.039) GE − 0.40(0.293) 14.94(0.884) DOMD + 7.32(1.998) CP − 0.56(0.504)
0.98 0.98 0.98 0.74 0.73 0.93 0.75 0.73 0.73 0.94 0.74 0.73 0.72 0.91 0.75
(6a) (6b) (7a) (7b) (7c) (8a) (8b) (8c) (9a) (9b) (9c) (9d)
ME/GE =
0.859(0.0111) GEd − 0.033(0.0077) 0.811(0.0011) GEd 0.811(0.0216) DMd − 0.010(0.0151) 0.797(0.0019) DMd 0.807(0.0197) DMd + 0.012(0.0019) GE − 0.007(0.0138) 0.799(0.0208) OMd − 0.020(0.0151) 0.771(0.0019) OMd 0.796(0.0185) OMd + 0.013(0.0018) GE − 0.019(0.0134) 0.875(0.0252) DOMD − 0.024(0.0168) 0.839(0.0022) DOMD 0.869(0.0235) DOMD + 0.011(0.0021) GE − 0.021(0.0157) 0.838(0.0291) DOMD + 0.159(0.0658) CP − 0.021(0.0166)
0.97 0.97 0.89 0.89 0.91 0.90 0.90 0.92 0.88 0.87 0.89 0.88
a DMd, DM digestibility (kg/kg); DOMD, digestible OM in DM (kg/kg); GEd, GE digestibility (MJ/MJ); GE, residual GE (GE concentration − mean GE concentration (18.5 MJ/kg DM)); OMd, OM digestibility (kg/kg); The unit for DE and ME is MJ/kg DM and for CP kg/kg DM.
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Fig. 1. Relationships between ME and DE concentration (MJ/kg DM) (a), digestible OM in DM (b), between ME/GE and GE digestibility (c), and digestible OM in DM (d) in grass silages (n = 174) with sheep at maintenance energy feeding level.
(Eqs. (1a), (1b) or (2)). Prediction accuracy was reduced (R2 = 0.72–0.74) when DM or OM digestibility or DOMD was used as a single predictor (Eqs. (3a), (3b), (4a), (4b), (5a) or (5b)). Including CP concentration as a secondary predictor in the latter equations slightly increased R2 values (Eqs. (3d), (4d) and (5d)), while including residual GE concentration (Eqs. (3c), (4c) and (5c)) substantially increased R2 values to approximately 0.93, a value which is close to that in Eqs. (1a) and (2). Relating ME/GE to GE digestibility produced a high R2 value (0.97) (Eqs. (6a) and (6b)) that was in accordance with the relationship between ME and DE concentration. The R2 values (0.87–0.90) were also high when using DM or OM digestibility or DOMD alone as a predictor (Eqs. (7a), (7b), (8a), (8b), (9a) or (9b)) and over 15 units higher than those when used alone to predict ME concentration (Eqs. (3a), (3b), (4a), (4b), (5a) and (5b)). Including residual GE concentration as a secondary predictor to the relationships between ME/GE and, respectively, DM and OM digestibility and DOMD slightly increased R2 values (0.89–0.92) (Eqs. (7c), (8c) and (9c)). Addition of CP concentration as a secondary predictor in Eqs. (7a) and (8a) had no significant effect on the relationship between ME/GE and DM or OM digestibility. Addition of CP concentration was, however, significant (P < 0.05) on the relationship between ME/GE and DOMD (Eq. (9d)), although the R2 value remained unchanged.
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4. Discussion 4.1. Prediction of silage ME concentration and ME/GE In comparison with previously published data sets for grass silages (Givens et al., 1989, 1993a,b), the present data set has three unique aspects, in that the data contained a large number of silages (n = 174), the silages used had a large range in nutritional quality, and the data were relatively evenly distributed over the range. Therefore, in the present study, there was a strong relationship between ME concentration and DOMD or digestibility of DM, OM, GE or NDF, with the R values ranging from 0.85 to 0.93 (Table 2). The R values in the relationships between ME/GE and digestibility data were even higher (0.90–0.99), although R value was relatively lower in the relationship of CP digestibility with ME concentration (0.68) or with ME/GE (0.72). There is little comparable information published on this aspect, although Givens et al. (1989) reported a low R value in the relationship between ME concentration and DOMD estimated from pepsin-cellulase (0.57), rumen fluid (0.49) or NDF-cellulase (0.44), using a data set containing 124 clamp grass silages. The relationships between ME concentration and DOMD estimated from rumen fluid and NDF-cellulase (Givens et al., 1989) are recommended in AFRC (1993) to predict the ME concentration for grass silage. Givens et al. (1993a) observed a similar low R value (0.42, 0.45 or 0.48) in the relationship between ME concentration and DOMD estimated from pepsin-cellulase, rumen fluid or NDF-cellulase in big bale grass silages (n = 37). The DM and OM digestibility, and DOMD, were used to predict ME concentration in silages, as they represent the total amount of digestible DM or OM. The prediction of ME concentration using digestibility of NDF and CP are, thus, not considered in the present study. ME concentrations (MJ/kg DM) were 14.8, 14.3 and 15.6 of digestible DM (kg/kg) and DOM (kg/kg) and DOMD (kg/kg DM), respectively (Table 3), when omitting the constant. The latter is similar to that obtained with big bale silages (Givens et al., 1993a), but marginally lower than that recommended in AFRC (1993) (i.e., 16.0) and reported in clamp grass silages (Givens et al., 1989) (16.0). However, prediction of ME concentration using DOMD as a single predictor could result in large errors, as nutrient contents (i.e., CP, lipids and carbohydrates) of DOM can differ in silages with similar DOMD values. This was demonstrated in Fig. 1(b), where the relationship between DOMD and ME concentration obtained in the present study shows that. At a similar DOMD, the range in ME concentration can be over 2 MJ/kg DM between two silages. Therefore, relating DM or OM digestibility, or DOMD to ME/GE (Table 3), rather than relating to ME concentration, substantially increased the R2 from approximately 0.72 to 0.87 (e.g., (b) versus (d) in Fig. 1). The addition of residual GE concentration (i.e., GE concentration minus mean GE concentration) as a secondary predictor to the prediction equations for ME using DM and OM digestibility and DOMD increased the R2 values to over 0.90 (0.91–0.94). Furthermore, addition of CP concentration also increased slightly the R2 values (Table 3). A similar improvement in prediction accuracy was also reported in clamp grass silages (Givens et al., 1989) and in big bale grass silages (Givens et al., 1993a). The R2 values were increased from 0.20 to 0.71 in the former or 0.20 to 0.78 in the latter when GE concentration was added as a
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secondary predictor to the relationship between ME concentration and DOMD estimated from NDF-cellulase. The most accurate predictor for ME concentration in grass silage is likely to be the DE concentration. The R2 value in this relationship was 0.98 in the present study and all plots were very close to the x = y line with only a few data relatively apart from the line (Fig. 1(a)). Similarly, the relationship of ME/GE with GE digestibility also produced a R2 value of 0.97 (Fig. 1(c)). Omitting the constant, ME concentration, or ME/GE, was 0.811 of DE concentration or GE digestibility. This value is similar to that (0.81) reported in the UK feeding stuff tables for grass silage (n = 218) (Ministry of Agriculture Fisheries and Food, 1990) and the same as the mean ME/DE (0.811) in perennial ryegrass silages reported in the French energy feeding system (Institut National De la Recherche Agronomique, 1989). 4.2. Validation of prediction equations developed in the present study using published data The objective of the present validation was to examine the accuracy of all prediction equations developed in the present study when using grass silage data from eight studies published since 1977 (Kelly and Thomas, 1978; Morgan et al., 1980; Thompson et al., 1981; McLellan and McGinn, 1981, 1983; Givens et al., 1989, 1993a,b). The forages used in these studies were grass silages offered alone as a sole feed at or at near maintenance energy feeding level. The animals used were cattle in the studies of Morgan et al. (1980) and Thompson et al. (1981), while in the remaining six studies sheep were used. All data (n = 21) were derived from single silages (n = 18), with the exception of the studies of Givens et al. (1989, 1993a,b) in which the data were mean values from 124, 37 and 9 silages, respectively. Because Thompson et al. (1981) and Givens et al. (1989, 1993a,b) did not report DM digestibility, there were 16 data for the valuation of prediction equations with DM digestibility as a predictor. The results of the validation using the MSPE technique are in Table 4. Results with Eqs. (1b), (3b), (4b), (5b), (6b), (7b), (8b) and (9b) are not presented because they are similar to those of Eqs. (1a), (3a), (4a), (5a), (6a), (7a), (8a) and (9a), respectively. Silage DM concentration in the studies used for the present validation was based on a toluene corrected DM basis, while in the present study silage DM concentration was corrected for both toluene and alcohol. Therefore, the predicted values using the equations developed in the present study were adjusted from MJ/kg TADM (toluene and alcohol-corrected DM) to MJ/kg TDM (toluene-corrected DM), using the mean alcohol proportion in the alcohol and toluene-corrected DM obtained in the present study. Prediction of ME concentration using DE concentration (Eq. (1a)) or GE digestibility with residual GE concentration (GE concentration minus mean GE concentration) (Eq. (2)) produced a low MPE. The MPE values were much higher in the prediction of ME concentration from equations using DM or OM digestibility or DOMD alone or with CP or residual GE concentration (Eqs. (3a)–(5d) and AFRC (1993)). The ME concentration predicted from Eqs. (1a) and (2) was close, or equal to, actual ME concentration with the majority of prediction errors derived from random variation. The ME concentration was under-predicted by 0.2–0.4 MJ/kg DM when using digestibility data alone (Eqs. (3a), (4a), (5a) and AFRC (1993)). Adding CP or residual GE concentration as a secondary predictor (Eqs. (3c), (3d), (4c), (4d), (5c) and (5d)) reduced
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Table 4 Validation of prediction equations for silage ME and ME/GE developed in the present study using grass silage data published since 1977a Predictors
Equations
No. of data
ME content Predicted
S.E.
MPEb
Actual
Proportion of MSPE Bias
Line
Random
Prediction of ME concentration (MJ/kg DM) DE (1a) 21 11.1 GEd + GE (2) 21 11.2 DMd (3a) 16 11.1 DMd + GE (3c) 16 11.2 DMd + CP (3d) 16 11.2 OMd (4a) 21 11.0 OMd + GE (4c) 21 11.1 OMd + CP (4d) 21 11.1 DOMD (5a) 21 10.9 DOMD + GE (5c) 21 11.1 DOMD + CP (5d) 21 11.1 DOMD AFRCc 21 11.0
11.2 11.2 11.4 11.4 11.4 11.2 11.2 11.2 11.2 11.2 11.2 11.2
0.31 0.29 0.37 0.38 0.44 0.31 0.34 0.40 0.29 0.32 0.42 0.27
0.029 0.031 0.061 0.052 0.050 0.050 0.039 0.046 0.061 0.046 0.050 0.058
0.14 0.01 0.33 0.20 0.23 0.11 0.02 0.03 0.24 0.04 0.07 0.12
0.00 0.09 0.05 0.04 0.00 0.18 0.08 0.03 0.21 0.17 0.03 0.27
0.86 0.90 0.62 0.76 0.77 0.71 0.90 0.94 0.55 0.79 0.90 0.61
Prediction of ME/GE (MJ/MJ) GEd (6a) DMd (7a) DMd + GE (7c) OMd (8a) OMd + GE (8c) DOMD (9a) DOMD + GE (9c) DOMD + CP (9d)
0.60 0.61 0.61 0.60 0.60 0.60 0.60 0.60
0.015 0.019 0.019 0.016 0.017 0.014 0.015 0.017
0.031 0.054 0.052 0.041 0.039 0.051 0.050 0.046
0.01 0.26 0.18 0.05 0.01 0.20 0.17 0.12
0.10 0.05 0.04 0.16 0.11 0.21 0.19 0.12
0.90 0.69 0.77 0.80 0.88 0.59 0.63 0.76
21 16 16 21 21 21 21 21
0.60 0.59 0.60 0.59 0.60 0.58 0.59 0.59
a DMd, DM digestibility; DOMD, digestible OM in DM; GEd, GE digestibility; GE, residual GE (GE concentration minus mean GE concentration); OMd, OM digestibility. √ b MPE, mean prediction error (= MSPE/A; ¯ A, ¯ actual mean value). c AFRC equation (ME (MJ/kg DM) = 16 DOMD (kg/kg DM)) (AFRC, 1993).
this under-prediction to 0.1–0.2 MJ/kg DM and, therefore, decreased the prediction error of mean bias (predicted−actual ME concentration) and increased the error of random variation. The inclusion of a secondary predictor also reduced the error derived from the line (slope) in Eqs. (3c), (3d), (4c), (4d), (5c) and (5d). Similar results (Table 4) were also obtained with prediction of ME/GE using GE, DM, OM digestibility and DOMD alone or with CP (Eq. (9d) only) and residual GE concentration. Residual plots were also used to validate the prediction accuracy by graphing the predicted ME concentration or ME/GE (x-axis) against the corresponding difference (y-axis) between predicted and actual data. The results are in Fig. 2(a) and (b) for ME concentration and in Fig. 3 for ME/GE. The residual plots using DE concentration (Eq. (1a)) or GE digestibility with residual GE concentration (Eq. (2)) as predictors were distributed around the 0 line, with the predicted ME concentrations ranging from 9.5 to 12.5 MJ/kg DM. The residual plots were much more scattered when using digestibility of DM (Eq. (3a)) and OM (Eq. (4a)) and DOMD (Eq. (5a)) and equation of AFRC (1993) alone as a single predictor. The range of predicted ME concentrations was between 10 and 12 MJ/kg DM. Adding CP or residual GE concentration as a secondary predictor increased the range of predicted
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Fig. 2. Predicted (equations developed in the present study) (x axis) against residual (predicted minus actual) (y axis) ME concentration (MJ/kg DM) using grass silage data published since 1977 (n = 16 for Eqs. (3a)–(3d), n = 21 for others) (DOMD, digestible OM in DM).
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Fig. 3. Predicted (equations developed in the present study) (x-axis) against residual (predicted minus actual) (y-axis) ME/GE using grass silage data published since 1977 (n = 16 for Eqs. (7a) and (7c), n = 21 for others) (DOMD, digestible OM in DM).
ME concentrations, although the residual plots were still relatively scattered. However, the residual plots for prediction of ME/GE using digestibility of GE, DM and OM and DOMD were all relatively evenly distributed around the 0 line, although the range of predicted ME/GE with Eqs. (6a) and (8c) was greater than that with Eqs. (7a), (7c), (8a), (9a), (9c) and (9d). Based on these results, we conclude that ME concentration and ME/GE in grass silages can be very accurately predicted using DE concentration and GE digestibility as a sole predictor, respectively. The prediction error for ME concentration using DE concentration or GE digestibility with residual GE concentration, or for ME/GE using GE digestibility,
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was very small and mainly derived from random variation. Using DM and OM digestibility and DOMD as a sole predictor to predict ME concentration can result in error, but this error can be largely reduced by adding residual GE concentration as a secondary predictor. 4.3. Validity of prediction of silage ME concentration using DOMD as a sole predictor AFRC (1993) recommends a factor of 16 to calculate ME concentration (MJ/kg DM) in grass silage based on its DOMD (kg/kg). This concept is widely used in UK livestock feeding programmes. However, this equation, which assumes that ME concentration in DOM is a constant, is not justified. The energy concentrations in DOM can vary between silages, as CP, lipid and carbohydrate contents in DOM can differ in accordance with their concentrations in total DM of grass silages. For example, in the present study the energy concentration in DOM followed a normal distribution (16.6–21.8, mean 19.2 (S.D. 0.99) MJ/kg DOM), with peak values being between 18.6 and 19.7 MJ/kg DOM (Fig. 4). A similar normal distribution of energy concentrations for DOM was also reported by Givens et al. (1989) in 124 grass silages and the range (15.5–24.5 MJ/kg DOM) was even greater than that in the present study. This large difference in energy concentration of DOM cannot be accounted for by differences in energy outputs in urine and methane when calculating ME concentration. This is supported by the findings in Table 5, that there were positive relationships between ME content per unit of DOMD and energy and CP concentrations in grass silages. In the data set of grass silages (n = 21) published since 1977, used in the previous validation, ME content per unit of DOMD increased with increasing DOMD (P < 0.05) and concentrations of GE (P < 0.01), DE (P < 0.001), ME (P < 0.001) and CP (P < 0.05). Similar results were also found when using the present data set of grass silages (n = 174), although there was no significant relationship between ME content per unit of DOMD and DOMD. These findings indicate that the ME per unit of DOMD is not constant,
Fig. 4. The distribution of energy concentration of digested OM in grass silages (n = 174) used in the present study.
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Table 5 The relationships between the ratio of ME concentration over DOMD (ME/DOMD) and GE, ME or CP concentration or DOMD in grass silages (the data in the brackets are S.E. values)a Equations Grass silage data published since 1977 (n = 21) ME/DOMD = 1.29(0.437) GE − 7.88(8.174) 0.68(0.112) DE + 7.18(1.508) 0.82(0.094) ME + 7.10(1.052) 10.66(4.712) CP + 14.54(0.804) 15.44(5.622) DOMD + 5.72(3.860) Grass silage data obtained in the present study (n = 174) ME/DOMD = 1.14(0.060) GE − 5.55(1.108) 0.38(0.044) DE + 10.75(0.559) 0.47(0.049) ME + 10.71(0.506) 11.70(2.468) CP + 13.93(0.345)
R2
Significanceb
0.32 0.66 0.80 0.21 0.28
** *** *** * *
0.68 0.30 0.35 0.12
*** *** *** ***
a
DOMD, digestible OM in DM (kg/kg); The unit for GE and ME concentration is MJ/kg DM and for CP concentration kg/kg DM. b *, P < 0.05; **, P < 0.01; ***, P < 0.001.
but varies with differing silage chemical composition. This may account for the finding in the present study (Table 3) that addition of residual GE concentration as a secondary predictor to equations for ME concentration using DM or OM digestibility or DOMD substantially improved the relationship, with R2 values being increased from approximately 0.73 to over 0.90. This improvement was evidenced in the previous validation using the grass silage data (n = 21) published since 1977. Adding residual GE concentration as a secondary predictor (Eqs. (3c), (4c) and (5c) in Table 4), in comparison with the prediction of ME concentration using DM or OM digestibility or DOMD alone, reduced MPE and markedly increased the error derived from the random variation. Prediction of silage ME concentration using DOMD alone, as recommended in AFRC (1993), results in substantial errors in ME estimation. This error may be greater for very poor or very good quality silages. For example, when validating the equation of AFRC (1993) using grass silage data published since 1977 as reported previously, for very poor quality silage the maximum over-prediction of ME concentration was 1.2 MJ/kg DM or proportionately 0.13 of actual ME concentration. The corresponding value for the maximum under-prediction with very good quality silage was 1.3 MJ/kg DM or 0.10. If data for GE concentration are available, they should be used as a secondary predictor (Eq. (5c)) to improve the prediction accuracy.
5. Conclusions DE concentration is the most accurate predictor for ME concentration in grass silage. Prediction of silage ME concentration using DOMD, or digestibility of DM or OM, as a single predictor can result in error, especially for very poor or very good quality silages, as ME content per unit of DOM can vary greatly. Addition of GE concentration as a secondary predictor can substantially improve the relationship between ME concentration and each of the digestibility data and the prediction accuracy for ME concentration. If DOMD continues
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to be used to predict ME concentration in grass silages, as recommended in AFRC (1993), GE concentration should be considered as a secondary predictor to improve prediction accuracy. This can be achieved by using the NIRS technique that has been demonstrated by Park et al. (1997) to have the ability to predict both DOMD and GE concentration in grass silage.
Acknowledgements The authors wish to thank their colleagues at the Agricultural Research Institute of Northern Ireland for access to the data used in the present study.
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