Abbreviations
OMD, organic matter digestibility; TT, Tilley and Terry method; CM, pepsin-cellulase method; ME, metabolizable energy; WC, white clover; RC, red clover; LC, lucerne; BT, birdsfoot trefoil; KC, kura clover; RG, rotational grazing; CM-OMD, OMD based on pepsin-cellulase method; TTOMD, OMD based on Tilley and Terry method; MECM, ME estimated by pepsin-cellulase method; METT, ME estimated by Tilley and Terry method; MAT, mean average temperature; AP, average precipitation.
With the genetic advancement of new cultivars, improvement in the forage quality of legumes is expected to meet an improved animal performance. Both animal and forage plant-related factors are involved in the improvement. In animals, factors like breed, feed intake level and amount of concentrate in the diet will influence organic matter digestibility (OMD) of forages. In forage plants, agronomic traits like leaf:stem ratio, defoliation system and growth environment (site and year) may influence OMD. There is a need to do a systematic analysis of influencing factors to quantify the variation in feed quality prediction, especially the metabolizable energy (ME) content.
OMD seems to be the simplest way to compare the genetic progress in forage plants (Casler and Vogel, 1999). Currently, OMD is estimated using
Whereas numerous studies have shown a variation in the chemical composition of grasses depending on the growth season and development stage at harvest for prediction of ME content, the prediction of ME in forage legumes is poorly documented. Previous studies have shown a larger variation in the cell wall content of the perennial ryegrass growing in contrasting environments than forage legumes, and thus variable ME content (Gierus et al., 2007). Both TT and CM methods are endpoint measurements, i.e. both methods result in one replicable value that is used in the prediction equations. Therefore, it is hypothesized that both TT and CM are suitable for the prediction of ME of forage legumes growing in different defoliation systems, and both methods generate comparable ME values using OMD estimates with high precision for a range of forage legume species and harvest dates (the
A total of 431 samples were derived from two field trials in Noer, Germany (16 m ASL; 8.7°C MAT; 774 mm AP) and Gumpenstein, Austria (710 m ASL; 6.8°C MAT; 1010 mm AP), and these were harvested for two years. The experimental designs at both sites were carried out as randomized block designs with three replicates each. Up to five legume species (white clover (cv. Klondyke), WC; red clover (cv. Pirat), RC; lucerne (cv. Ameristand), LC; birdsfoot trefoil (cv. Rocco), BT; kura clover (cv. Endura), KC) were grown in binary mixtures with perennial ryegrass (
All available legume samples were scanned twice using near infrared spectrometry (NIRS) Systems 5000 scanning monochromator (Perstrop Analytical Inc., Silver Spring, MD, USA) and software (ISI-version) for data collection and manipulation was supplied by Infrasoft International® (ISI, Port Matilda, PA, USA). Samples with H-values exceeding 3.0 were excluded from the calibration procedure. The calibration subsets that were selected (H-value 0.6) represented the whole sample spectrum, while the validation subsets were randomly selected after ranking the spectral data according to their H distance. Calibrations were developed by regressing laboratory determined values against the NIR spectral data (Shenk and Westerhaus, 1991). The minimum F statistics for terms included in the equation was 8.0. Subsets of samples were chosen for wet chemical analysis.
N was analysed by a rapid combustion (850°C), conversion of all N products to N2, and subsequent measurement by thermoconductivity cell (elementar-analysator Vario MAX CN, Fa. Elementar Analysensysteme, Hanau, Germany). The results were expressed as crude protein, i.e. N × 6.25.
The pepsin-cellulase method (CM) was carried out according to De Boever et al. (1988) in Germany, following the guidelines of VDLUFA Standard Methodology (VDLUFA, 1993). Briefly, the method involved a preliminary incubation for 24 h with pepsin/HCl at 40°C, followed by heating for 45 min at 80°C and a second incubation with a commercial cellulase Onozuka R-10 from
The ME content by the CM method (MECM) was computed by applying the estimating equation for legumes derived by Weissbach et al. (1996) on the values obtained with the
where CA is crude ash content (g/kg DM), IOM is enzymatically insoluble organic matter (g/kg DM) and CP is crude protein content (g/kg DM).
Four standard samples with known
The two-stage method by Tilley and Terry (1963) (TT) was carried out with modifications in Austria. Rumen fluid was obtained prior to the morning feeding from two rumen-fistulated steers fed with a diet of seasonal green forage from mixed swards and supplemented with concentrates. The buffer solution was dispensed according to McDougall (1948). Prior to incubation, rumen fluid and buffer solution were mixed in the proportion 1:4 (v/v). The pepsin solution was prepared by dissolving 20 g of 1:10,000 pepsin (Sigma-Aldrich, Germany) in 1000 ml distilled water. Where required, steps were carried out under anaerobic conditions, flushing buffers and solutions with gaseous CO2.
Dried forage samples (0.5 g) were weighed in triplicate into 100 ml Erlenmeyer flasks and 50 ml of the rumen liquor-buffer solution were added. Remaining air was then expelled with CO2 and flasks sealed with perforated Parafilm, followed by incubation of samples and blanks at 38.5°C for 48 h in the dark. At the end of the first incubation period, pH value was adjusted to 1.5 units by using 2.2N HCl, 5 ml of pepsin solution was added and then the flasks were incubated again for 48 h at 38.5°C. At the end of the second incubation period, samples were filtered (Macherey Nagel MN 640w, Germany), dried at 104°C for 4 h and weighed before ashing at 450°C.
The TT-OMD was calculated as difference between the OM of the sample before incubation and the residual OM. Residues after incubation measured in blanks were deducted. Outliers (if the deviation of a replicate exceeded 3 % of the mean) were excluded from further calculations.
The same four standard samples with known
The TT-OMD values of the standard samples were compared within each run to their corresponding
A mixed model analysis was calculated for energy content data (ME) of each defoliation system and for the 3-cut system of both sites using PROC MIXED by considering cut, species and method as fixed factors (SAS Institute Inc., 2004). Years and site (data was available for the 3-cut system in both sites) were included in the data set, not as classificatory factors in the statistical model, but considered as replicates. Cuts (or grazing cycles) were treated as a repeated measurement assuming a symmetric covariance structure. In case of significant interactions (
The relationship between the NIRS-estimated ME contents based on the two different
Table 1 shows the descriptive statistics of the NIRS calibration results for all samples included in the evaluation, giving the range of estimated values for ME contents of the respective methods (MECM; METT). Additionally, the variation coefficient referred to as the standard deviation (CVSD = SEC × 100/SD) was calculated in order to assess the suitability of the respective method for reliable NIRS calibration, as suggested by Murray (1986). The NIRS calibration models obtained correlations with all nutrient and energy variables analyzed with R2 > 0.80, with the exception of METT with a considerably lower R2 of 0.69, compared to MECM (R2 = 0.97). The calibration model for METT is thus classified as poor. Estimation of the
NIRS calibration statistics of the determined parameters IOM (g/kg DM), MECM (MJ/kg DM), TT-OMD (%), and METT (MJ/kg DM) of the legume samples (
Tabelle 1. NIRS Kalibrationsstatistik für folgende Parameter: IOM (g/kg TM), MECM (MJ/kg TM), TT-DOM (%) und METT (MJ/kg TM)
Parameter | Number of samples included in the calibration | Range Minimum and maximum of the parameter values | Mean Mean of the parameter values | SD Standard deviation of the laboratory-determined values | SEC Standard error of calibration | R2 Coefficient of determination; relationship between NIRS- and laboratory-determined values | CVSD Variation coefficient referred to the SD of the reference method ( | |
---|---|---|---|---|---|---|---|---|
IOM IOM, enzymatically insoluble organic matter; MECM, ME content estimated with pepsin-cellulase method; TT-OMD, Tilley and Terry method estimated organic matter digestibility; METT, ME content estimated using Tilley and Terry method data | 77 | 90.60 | 353.73 | 204.42 | 72.18 | 11.52 | 0.98 | 15.96 |
MECM | 76 | 8.18 | 11.90 | 10.11 | 0.93 | 0.15 | 0.97 | 16.27 |
TT-OMD | 77 | 42.42 | 79.83 | 63.51 | 7.82 | 3.24 | 0.83 | 41.43 |
METT | 73 | 6.20 | 11.03 | 8.61 | 1.05 | 0.59 | 0.69 | 55.86 |
Table 2 shows the
Differences between the
Tabelle 2. Differenzen der
Standard samples | CM-OMD (%) | TT-OMD (%) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Range Minimum and maximum differences to the | Range Minimum and maximum differences to the | ||||||||||||
No. | Cuts/year | Cut | (%) | Number of runs in which standard samples was included | Mean Mean of the differences to the | SD Standard deviation of the differences of the laboratory-determined values to the | Mean Mean of the differences to the | SD Standard deviation of the differences of the laboratory-determined values to the | |||||
Min | Max | Min | Max | ||||||||||
198 | 1 | 1 | 41.9±3.92 | 5 | 0.72 | 3.30 | 2.06 | 1.13 | 24 | −15.44 | 1.89 | −2.44 | 3.99 |
232 | 3 | 1 | 68.4±2.13 | 5 | −3.91 | −2.88 | −3.63 | 0.43 | 24 | −10.82 | 1.09 | −3.45 | 3.16 |
246 | 4 | 2 | 75.2±2.26 | 4 | 2.92 | 4.34 | 3.78 | 0.63 | 24 | −7.74 | 0.93 | −3.50 | 3.07 |
298 | 1 | 1 | 46.7±4.15 | 5 | 2.65 | 3.65 | 2.98 | 0.40 | 23 | −15.56 | 1.22 | −3.20 | 4.68 |
Results of the statistical evaluation of the 2-way interactions are given in Table 3 for the 3-cut system at both study sites, and in Table 4 for the study site in Germany, separated for each defoliation system. The 2-way interactions species × cut, method × cut and method × species were significant (Table 3 and 4). In general, lower ME values were estimated based on TT compared to the CM method, with LSMeans being different (
ME contents of several forage legumes from the 3-cut system at three cutting dates over study sites and years, based on two different
Tabelle 3. ME Gehalt verschiedener Futterleguminosen (3-Schnittsystem) als Mittelwert über Standorte und Jahre, mittels zwei
Pepsin-cellulase method (MECM) | Tilley and Terry method (METT) | Means over methods | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Cut 1 | Cut 2 | Cut 3 | Cut 1 | Cut 2 | Cut 3 | Cut 1 | Cut 2 | Cut 3 | |||
White clover | 11.0 | 10.1 | 10.6 | 10.6 v,V | 10.1 | 8.8 | 9.4 | 9.4 w,V | 10.5 a,A | 9.4 a,C | 10.0 a,B |
Red clover | 10.3 | 9.7 | 10.0 | 10.0 v,W | 9.2 | 8.2 | 8.8 | 8.7 w,W | 9.8 b,A | 8.9 b,C | 9.4 b,B |
Lucerne | 9.9 | 9.5 | 9.5 | 9.6 v,X | 8.3 | 7.6 | 7.8 | 7.9 w,X | 9.1 c,A | 8.5 c,B | 8.6 c,B |
Birdsfoot trefoil | 9.9 | 9.3 | 9.4 | 9.5 v,X | 8.5 | 7.6 | 7.5 | 7.9 w,X | 9.2 c,A | 8.5 c,B | 8.4 d,B |
Mean | 10.3 g,G | 9.6 g,I | 9.9 g,H | 9.9 | 9.0 h,G | 8.1 h,I | 8.4 h,H | 8.5 |
a,b,c,d LSMeans differ between species within cutting date at
A,B,C LSMeans differ between cutting dates within species at
g,h LSMeans differ between methods within cutting date at
G,H,I LSMeans differ between cutting date within method at
v,w LSMeans differ between methods within species at
V,W,X,Y LSMeans differ between species within method at
For the dataset including both study sites (Table 3), higher ME values as means over cuts were consistently estimated for white clover, followed by RC in both sites. As means over species, forage of the first cut showed highest ME values, and lowest values were seen in the second cut. However, the range of ME for the species was only slightly larger within the METT dataset (1.5 MJ) than within MECM (1.1 MJ). Averaged over methods, ME values of most species did not differ between the second and third cut, but ME of BT was lower in the third cut (8.4 MJ). Such difference among species in the third cut was not detected by the methods individually.
MECM contents of forage legumes were always higher (
ME contents of forage legumes from different defoliation systems (3-cut system, 3C; 5-cut system, 5C; rotational grazing, RG) from the site in Germany over years, estimated by NIRS based on two different
Tabelle 4. ME Gehalte von Futterleguminosen verschiedener Nutzungssystems (3-Schnitt-, 3C; 5-Schnittsystem, 5C; Umtriebsweide, RG) aus dem Standort Deutschland als mittel über Jahre, geschätzt mittels NIRS aus zwei unterschiedlichen
Pepsin-cellulase method (MECM) | Tilley and Terry method (METT) | Means over methods | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cut 1 | Cut 2 | Cut 3 | Cut 4 | Cut 5 | Cut 1 | Cut 2 | Cut 3 | Cut 4 | Cut 5 | Cut 1 | Cut 2 | Cut 3 | Cut 4 | Cut 5 | |||
3-cut system ( | |||||||||||||||||
WC | 11.0 | 10.0 | 10.2 | 10.4 v,V | 10.6 | 8.8 | 9.3 | 9.6 w,V | 10.8 a,A | 9.4 a,C | 9.8 a,B | ||||||
RC | 10.4 | 9.7 | 9.4 | 9.8 v,W | 9.6 | 8.3 | 8.6 | 8.8 w,X | 10.0 c,A | 9.0 b,B | 9.0 b,B | ||||||
KC | 10.8 | 10.3 | 10.3 | 10.5 v,V | 9.9 | 9.0 | 8.9 | 9.2 w,W | 10.3 b,A | 9.6 a,B | 9.6 a,B | ||||||
LC | 9.8 | 9.5 | 9.0 | 9.4 v,X | 8.4 | 7.7 | 7.4 | 7.8 w,Y | 9.1 e,A | 8.6 c,B | 8.2 c,C | ||||||
BT | 10.0 | 9.7 | 8.9 | 9.6 v,X | 9.1 | 7.9 | 7.0 | 8.0 w,Y | 9.6 d,A | 8.8 bc,B | 8.0 c,C | ||||||
10.4 g,G | 9.8 g,H | 9.6 g,I | 9.9 | 9.5 h,G | 8.3 h,H | 8.2 h,H | 8.7 | ||||||||||
5-cut system ( | |||||||||||||||||
WC | 11.8 | 11.1 | 9.8 | 11.1 | 11.2 | 11.0 v,V | 10.1 | 9.9 | 8.6 | 9.7 | 9.5 | 9.5 w,V | 10.9 a,A | 10.5 a,B | 9.2 b,C | 10.4 a,B | 10.4 a,B |
RC | 11.2 | 10.8 | 9.9 | 10.4 | 10.7 | 10.6 v,X | 9.6 | 9.5 | 8.4 | 8.8 | 8.6 | 9.0 w,X | 10.4 b,A | 10.1 b,B | 9.1 b,D | 9.6 c,C | 9.6 c,C |
KC | 11.4 | 10.9 | 10.5 | 10.9 | 10.8 | 10.9 v,W | 9.6 | 9.5 | 9.0 | 9.4 | 9.2 | 9.3 w,W | 10.5 b,A | 10.2 b,B | 9.7 a,C | 10.1 b,B | 10.0 b,B |
LC | 10.8 | 10.4 | 10.0 | 10.1 | 10.4 | 10.4 v,Y | 8.8 | 8.6 | 8.0 | 8.2 | 8.2 | 8.4 w,Y | 9.8 c,A | 9.5 c,B | 9.0 b,D | 9.2 d,CD | 9.3 d,BC |
BT | 10.9 | 9.9 | 9.8 | 10.1 | 10.4 | 10.2 v,Z | 8.5 | 7.9 | 7.6 | 7.9 | 8.0 | 8.0 w,Z | 9.7 c,A | 8.9 d,C | 8.7 c,D | 9.0 e,C | 9.2 d,B |
11.2 g,G | 10.6 g,HI | 10.0 g,J | 10.5 g,I | 10.7 g,H | 10.6 | 9.3 h,G | 9.1 h,H | 8.3 h,J | 8.8 h,I | 8.7 h,I | 8.8 | ||||||
RG ( | |||||||||||||||||
WC | 11.5 | 10.9 | 10.6 | 11.2 | 11.5 | 11.1 v,V | 10.5 | 9.7 | 9.5 | 9.7 | 9.4 | 9.8 w,V | 11.0 a,A | 10.3 a,B | 10.0 a,C | 10.5 a,B | 10.4 a,B |
RC | 11.1 | 11.1 | 10.1 | 10.5 | 10.6 | 10.7 v,W | 9.6 | 9.6 | 8.8 | 8.7 | 8.7 | 9.1 w,W | 10.4 b,A | 10.4 a,A | 9.5 b,B | 9.6 b,B | 9.6 b,B |
LC | 10.6 | 10.5 | 10.4 | 10.2 | 10.4 | 10.4 v,X | 8.7 | 8.8 | 8.7 | 8.2 | 8.1 | 8.5 w,X | 9.6 c,A | 9.7 b,A | 9.6 b,A | 9.2 c,B | 9.2 c,B |
BT | 9.9 | 10.2 | 9.7 | 10.1 | 10.4 | 10.1 v,Y | 8.2 | 8.3 | 7.8 | 7.7 | 8.1 | 8.0 w,Y | 9.1 d,AB | 9.3 c,A | 8.7 c,C | 8.9 d,BC | 9.3 c,A |
a,b,c,d,e LSMeans differ between species within cutting date at
A,B,C,D LSMeans differ between cutting dates within species at
g,h LSMeans differ between methods within cutting date at
G,H,I,J LSMeans differ between cutting date within method at
v,w LSMeans differ between methods within species at
V,W,X,Y,Z LSMeans differ between species within method at
Figure 1 shows the relationship between ME of all samples included in the evaluation (
The main focus of the present study was on the measurement of the repeatability of ME estimation of two
As shown by the mixed model and regression analyses of all data, the determination of ME of forage legumes clearly differed depending on the
The general limitations given within the methods and the respective equations are possible reasons for this study. Whereas OMD values obtained with TT are dependent on the variation obtained for the standard samples measured simultaneously in each run, the CM method does not need simultaneous measurement of standard samples, as the equation is based on several
For the CM method, a regression equation was developed for ME estimation separately for legumes by Weissbach et al. (1996). This equation is based on 20
The defoliation frequency caused deviations of the intercepts, as the 5-cut system and RG were larger than zero (Figure 2). Compared to the 3-cut system, the plants in the 5-cut system and RG were harvested at an earlier development stage and thus showed high ME values (Table 4), as confirmed in previous experiments including grazing management (Kleen et al., 2011). The differences were consistent between sites and years.
Enzyme-based predictions of
Forage legumes may have leaves with higher digestibility than stems, compared to grasses. In this case, management systems resulting in higher leaf:stem ratio may substantially improve OMD in legumes with erect, crown-forming growing habit (Annicchiarico, 2007). For legumes like LC, RC or BT, higher leaf:stem proportions are observed for higher cutting frequency (Gierus et al., 2012). Thus, these legumes have a stronger influence on higher digestibility and ME content due to an altered leaf:stem ratio with low maturity at harvest in the 5-cut system in the present study. Ranking legumes based on the leaf:stem proportion as used in the present study (Table 3 and 4) confirms the observations by others (Nordkvist and Åman, 1986). LC samples confirmed having a higher ME content in the 5-cut system and RG system in comparison to the 3-cut system. Achieving higher leaf:stem proportion would be a management option to improve forage quality for certain forage legume species with erect, crown-forming growth habit. However, the prediction of ME of several legumes submitted to different management systems shows that the largest ME values were observed for white clover, while comparing the 3-cut system at both sites (Table 3) or among defoliation systems in Germany (Table 4). Both CM and TT methods were able to measure the higher ME content for white clover consistently in Austria and Germany.
The comparison of METT and MECM for individual data within legume species reveals that the higher ME values were equally well predicted compared to the lower ME contents for different legume species. Although higher in ME content, white clover did not show better prediction using either TT or CM in comparison to other species. Using legume forage samples with known
Compared to other forage legumes, the enzyme polyphenol oxidase is very active in RC (Eickler et al., 2011). Using substrates like caffeic acid, phaselic acid and clovamide present in the plant, the enzyme catalyses the reaction and produces quinones and in this way may cause a complexation of proteins (Jones et al., 1995). The complexation is comparable to that observed for condensed tannins, which are present in BT, and the extent of their presence is dependent on their concentration in forage and diet. One may suggest that condensed tannins or quinones cause a stronger impact on the rumen microbes when the TT method is the method of choice, resembling the determination of
The effect of polyphenols, either condensed tannins in BT or quinones in RC, on an annual basis was not apparent in the present study for the ME estimate. The ME estimates among legume species from TT and CM methods were lowest for BT and comparable for LC (Table 3 and 4), whereas the ME estimates of RC were only lower than white clover. The secondary plant components, quinones and condensed tannins, may have varied in their contents during the growing season, which was supported by the observed species × cut interactions over methods in the present study, and was also observed in other studies (Eickler et al., 2011). However, the variation was small but enough to show the influence of species (RC and BT) on a lower ME estimation as average over methods. This may be related to the content of condensed tannins or quinones formed within these species.
While
For forage legumes, the first cut of the year is the most important one in terms of ME content. Especially for white clover and KC, as they have the highest ME content, independent of management system. Achieving a higher leaf:stem proportion, for example by higher defoliation frequency, would be a management option to improve forage quality for the investigated forage legume species.
The estimation of ME contents of forage legumes based on the CM method is far more robust due to the higher precision and correlation to