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Prediction of digestible organic matter in dry matter in vivo from the chemical composition, in vitro and in situ measurements on native mountain forages
Animal FeedScience and Technology, 39 ( 1992) 323-333 Elsevier Science Publishers
323
.V., Amsterdam
I[.Andrighettoa, E. Gmber”, G. Cozzi”, G. Urayb, 6. Guidetti” and =Depavtment ofAnimal Science of Padova University, Padova, Italy bFederal Research Institute for Agriculture in Alpine Regions, BAL Gumpenstein. Austria (Received 23 July 1991; accepted 19 May 1992)
ABSTRACT Andrighetto, I., Gruber, L., Co&, G., Uray, C., Guidetti, G. and Buchgraber, K., 1992. Prediction of digestible organic matter in dry matter in vivo from the chemical composition, in vitro and in situ measurements on native mountain forages. Anim. Feed Sci. Technol., 39: 323-333. Assessment of forage nutritive value facilitates its appropriate inclusion in diets for ruminants. The objective of the present study was to determine the precision with which laboratory and in situ measurements could predict the digestible organic matter in dry matter (DGMD) in vivo of mountain forages, using multiple linear, step-wise regression analyses. A joint research was carried out between the Federal Research Institute for Agriculture in Alpine Regions (BAL Gumpenstein, Austria) and the Department of Animal Science of Padova University (Italy). The data set included 66 native mountain forages for which in vivo digestibility data were available. Forage harvesting methods (hay, silage (SIL) and fresh grass) were forced to enter as dummy variables in the equations. Four sets of independent variables: Weende constituents (crude protein, ash and crude fibre), Van Soest fibre constituents (NDF, ADF and ADL), in situ 48 h DM degradation and in vitro techniques (NDF-cellulase, pepsin-cellulase (PEPCEL), Tilley-Terry and gas production HFT) were submitted to a step-wise regression analysis. In the first stage of the regression, the four sets of variables were separately analysed and the best equation was obtained with the in vitro pepsin-cellulase procedure: DOMD=44.90-5.92HAY-7.61 SIL+O.35 PEPCEL (n=66; mean=57.68~5.06;RSD=3.43;R2=0.540). The second stage of regression implied the subsequent inclusion of the sets following a criterion based on the higher degree of complexity of the analytical methods (Weende plus Van Soest plus in situ plus in vitro). The resulting final equation was: Correspondence dova, Italy.
to: I. Andrighetto,
0 1992 Elsevier Science Publishers
Department
of Animal Science of Padova
B.V. All rights reserved 0377-8401/92/$05.00
University,
Pa-
324
1.ANDRIGHETTG ET AL.
DOMD= 19.85-5.94 HAY-4.97 SIL-0.70 ASH+0.25 NDF+0.64 PEPCEL (RSD=2.86;R2=0.681). The equation, which increased the precision in predicting DOMD in vivo, requires only a restricted number of laboratory determinations and may be suitable for a widespread utilisation by mountain farmers.
INTRODUCTION
Animal nutrition in mountain environments is largely based on the use of adapted native pastures. In fact, in these areas there are frequently no sown pastures available. Environmental constraints such as elevation, slope, orography, pedology and sun exposure, limit the production of sown pastures and native pastures are frequently the only feed available at reasonable cost. Assessment of the nutritive value of native forages is important in order to define their most appropriate use as components of diets for ruminants. The energy value of forages is often measured in terms of in vivo organic matter digestibility (OMD) (Aerts et al., 1977; Barber et al., 1989; Givens et al., 1989). However the in vivo procedures require animals, special devices, considerable time and money, as well as the availability of large quantities of test feed (Cottyn et al., 1987). These factors, especially in mountain areas, limit the use of the method and several attempts have been made to develop simple techniques for predicting in vivo OMD from less expensive analyses. The ideal characteristics of these methods should be simplicity, rapidity, low cost, precision and reliability (Cottyn et al., 1987). Chemical analysis such as crude fibre and some cell wall fractions (NDF, ADF, lignin) were used in the prediction of the nutritive value of forages (Joshi, 1972; Aerts et al., 1977). Several studies developed in vitro techniques based on incubation of the forages with rumen liquor (Tilley and Terry, 1963; Alexander and MC Gowan, 1969; Mbwile and Uden, 199 1 ), with cellfree cellulase-type enzymes (Jones and Hayward, 1975; Van Soest, 1982; Dowman and Collins, 1982)) or on the gas produced by an incubation with rumen liquor (Menke and Steingass, 1988 ). OMD was also estimated by in situ methods using cannulated animals (Aerts et al., 1977; Orskov et al., 1980). The objective of the present study was to show the precision with which laboratory and in situ measurements could predict the in vivo digestibility of native mountain forages, using multiple linear, step-wise regression analysis. Within the activities of the Alpe-Adria association, this research project was carried out jointly between the Federal Research Institute for Agriculture in Alpine Regions (Bal Gumpenstein, Austria) and the Department of Animal Science of Padova University (Italy).
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
MATERIALS AND METHODS
The study was based on all the s areas for which in vivo digestibility 66 samples of native pastures, co classified acceding to storage m nant forage species were P&z4
silage or fresh grass.
sis, Lolium perenne, Trisetumjlaves
small percentages of legu and Trifolium repens. The samples of fresh forage was then deep fro
ss were harvested an , packed in single
Forage chemical composition
1984 ). Cell wall co
days at 55°C. In situ dry matter
moisture content, as s
prediction by in situ i Cows were fed 1.8 age: concentrate ratio.
D&I disappearance.
degradability
325
326
1.ANDRIGHETTO ET AL.
In vitroOM digestibility Four methods measuring in vitro digestibility were adopted: ( 1) two-stage NDF-cellulase method (Dowman and Collins, 1982); the enzyme was a fungal cellulase ‘Onozuca’ R 10 from Trichodermaviridae (Yakult Honsha Co. Ltd, Tokyo, Japan); (2) two-stage pepsin-cellulase (PEPCEL) method (Jones and Hayward, 1975 ), modified by Aufrere ( 1982); the pepsin was Merk 7 190 (Merk, Darmstadt, Germany) and the cellulase was the same as in the previous method, ( 3) two-stage rumen inoculum-pepsin procedure (Tilley and Terry, 1963 )z modified by Alexander and MCGowan ( 1969). Donor animals were the same cows used in the in situ method and were fed the same diet; (4) gas production was measured according to the procedure of Menke and Steingass ( 1988 ). In vivomeasurements OMD of the forages was analysed using adult sheep. Austrian forage was evaluated with Mountain Sheep breed animals (60-70 kg LW ) using the procedures suggested by Van Es and Van der Meer ( 1989). OMD of the forages collected by Padova was tested following the procedures of the Italian Commitee of Feed Evaluation (Commissione Valutazione degli Alimenti, 1982 ) with Lamon breed sheep (50-60 kg LW). OMD data were converted to digestible organic matter in dry matter (DOMD) values considering the ash content of the forage (Ministry of Agriculture, Fisheries and Food, 1977). Fittingequations To estimate the DOMD of forage by multiple linear regression equations, several independent variables were considered according to a multistage stepwise regression analysis. Analysis was carried out using the Regression Procedure of SPSS-PC package (SPSS PC/XT, 1984). In the first stage, four sets of independent variables ( Weende chemical fractions, Van Soest fibre, in situ and in vitro values) were separately analysed. The Weende set considered crude protein, ash and crude fibre; ether extract was not included because of its extremely variable composition in forage, as noted by Van Soest ( 1982); nitrogen-free extract was also excluded because of lack of independence due to its determination by difference from the other Weende constituents. The Van Soest fibre set considered NDF, ADF and ADL.
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
327
stage of regressio ent inclusion of the sets following a criterion based on the hi methods. Three regression analyses were independent variables: in the first, Ween ered, whereas in the second and in the third, in situ added in turn. Two dummy variables were always forced to enter to identify the ty forage (hay and silage ) , using the intercept for the fresh grass.Equation fitted by the least-squares method following a step-wise procedure w 0.05 probability level for inclusion or deletion of variables. To revent biased estimations due to computational problems, a threshold value of tolerance of 0.0 1 (the proportion of variability not explained by the variables not yet entered) was adopted. Along with the regression coeffkients the analysis furnished the coefficient of determ’ adjusted for degrees of freedom ( the residual standard deviation and the residual variation coeffr RESULTS AND DISCUSSION
Variability in
content of fresh grass ( s, while wilting intensi variability of the silages. The lower protein conte the leaf losses during wilti
The in situ and in
gardless of forage typ which may be due to 1) because nitrogen c
Predictionsof first stage of the pendent variable
e regression analysis c rately (Table 4). The de
nation coefficient
I. ANDRIGHETTO ET AL.
328 TABLE 1 Forage chemical composition Forage type
Hay
Wage
Fresh grass
Number of samples
28
28
10
Dry matter (%) mean SD
87.4
1.8
29.8 9.0
28.4 13.7
7.6 1.6
10.8 3.1
2.2
Organic matter (% DM ) Mean SD
92.4 1.6
89.2 3.1
92.9 2.3
Crude protein (I DM ) Mean SD
9.6 1.6
12.4 2.5
12.4 4.1
Ether extract (% DM) Mean SD
1.8 .4
3.8 1.1
2.4 .8
34.1 3.9
31.6 4.5
32.5 5.4
46.8 3.2
41.5 3.0
45.7 2.1
Neutral detergent fibre (% DM) Mean SD
64.7 6.4
56.5 9.3
65.2 8.4
Acid detergent fibre (% DM) Mean SD
40.2 4.3
39.5 5.3
39.3 5.2
4.4 1.4
5.3 2.7
6.0 1.5
Ash (% DM ) Mean SD
Crude fibre (% DM) Mean SD
7.0
Nitrogen-free extract (I DM) Mean SD
Acid detergent lignin (% DM ) Mean SD
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
329
TABLE 2 Forage in situ DM degradation, in vitro GM digestibility and HFT gas production Forage type
Nay
Wage
Fresh grass
Number of samples
28
28
10
Dry matter (% ) Mean SD
87.4 1.8
29.8 9.0
28.4 13.7
In situ 48 h DM degradation # Mean SD
72.0 7.1
75.3 8.4
68.5 13.3
NDF-cellulase OMD 016 Mean SD
48.5 10.1
50.0 12.5
41.1 6.3
Pepsin-cellulase GMD % Mean SD
50.5 7.7
56.0 9.7
48.5 13.3
Tilley and Terry OMD % Mean SD
65.1 7.5
66.2 7.3
59.3 13.1
Gas prod. ml per 200 mg DM in 24 h Mean 42.0 SD 6.0
38.5 6.0
35.7 8.4
and the residual variation coeffkient o from simple chemical analyses to in also showed the poor capacity of the conforms to the results of Aerts et al. crude fibre is variable in composition a from one laboratory to another, even tho (Cottyn et al., 1987). The few cases fibre are limited to homogeneous b geographical areas (Korva and Tuori, 1986). The best equation was obtained with the in vitro set a
stage excluded all the
I. ANDRIGHETTO ET AL.
330 TABLE 3 Forage in vivo digestibility Forage type
Hay
Silage
Fresh grass
Number of samples
28
28
10
Dry matter (%) Mean SD
87.4 1.8
29.8 9.0
28.4 13.7
Organic matter in DM digest. % Mean SD
56.8 3.8
57.0 5.4
62.0 5.6
58.1 7.1
59.2 5.9
63.1 9.1
39.6 15.9
62.5 9.5
56.1 7.4
62.1 5.5
67.7 7.6
66.7 8.6
Crude pro1ein Mean SD
digest. %
Ether extract Mean SD
digest. %
Crude fibre Mean SD
digest. 96
.I
sion of DOMD prediction was further improved after adding the data obtained by the in situ procedure. In previous studies, the bag technique was shown to be an effective means of predicting OMD in viva, with forage marquilly and Chenost, 1969; Aerts et al., 1977), tropical grasses (Ishiz al., 1976) and fibrous by-products (Bittante et al., 1988). However, the relatively simple procedure of the bag technique requires, along with the maintainance of cannulated animals, a particular care in the choice of several factors, such as bag pore size, sample particle size, sample size to bag surface ratio, incubation time, washing procedure, which can influence the final results, leading to unreliable predictions (Lindberg, 1985;Nocek, 1988). The last stage of the multiple regression estimation included the in vitro procedures, and futher improved the precision of estimating DOMD in vivo. The final equation including ash and NDF content of the forage along with the pepsin-cellulase in vitro procedure showed a determination coefficient of 0.68 and the residual standard deviation was reduced,to 2.86. N in the last step of the regression analysis with a lower contribut The positive sign of the NDF estimated coeffkient is hardly explainable from a biological point of view. However, it is coefficient simultaneously fitted along wi the equation (ASH and PEPCEL).
ADL, Acid detergent lignin (U dry matter); ASH, Ash (96 dry matter); CF, Crude fibre (I dry matter); ‘DOMD, Digestible organic matter in dry matter ( W dry matter); HAY, Forage-type hay ( 1, yes; 0, no); IS, In situ dry matter degradation (%); NDF, Neutral detergent tibre (I dry matter); PEPCEL, Pepsin-cellulase organic matter digestibility (%); SIL, Forage-type silage ( 1, yes; 0, no).
DOMD=69.76-7.27 HAY-5.85 SIL- 1.3OADL DOMD=48.56-7.01 HAY-5.35 SIL+O.31 IS-O.58 ASH-O.66 ADL DOMD= 19.85-5.94 HAY -4.97 SIL-0.70 ASH+0.25 NDF+0.64 PEPCEL
SIL-0.82 CF-0.68 ASH SIL- l.JOADL SIL+0.34 IS SIL+O.35 PEPCEL
Weende + Van Soest + in situ + in vitro
HAY-3.10 HAY-5.85 HAY -7.28 HAY-7.61
DOMD=93.32-3.42 DOMD-69.76-7.27 DOMD=38.68-6.40 DOMD=44.90-5.92
Weende Van Soest In situ In vitro
Independent variables
Multiple regression estimation of in vivo DOMD’ (n=66; mean= 57.68 + 5.06 SD)
TABLE 4
6.90 6.17 4.96
3.98 3.56 2.86
6.92 6.90 6.54 5.95
3.99 3.98 3.77 3.43
0.377 0.379 0.445 0.540 0.379 0.506 0.681
RVC%
RSD
R2
%
g $ ij
0
: $ 3 E
2 o
332
I. ANDRIGHEm
ET AL.
This equation was better than that obtained in the first stage of the regression analysis, where the in vitro set was separately considered (R2=0.54, RSD= 3.43). However both equations indicate a high level of precision in predicting DOMD in vivo by the pepsin-cellulase method, which in comparison with other in vitro techniques, has been proposed specifically for the evaluation of this category of feeds. Furthermore the pepsin-cellulase method appears the simplest in vitro technique from the operative point of view, either because of its total enzymatic procedure free from donor animals, or due to the lack of any decanting and centrifuging which can cause sample losses, thus increasing variability.
REFERENCES Aerts, J.V., De Brabander, D.L., Cottyn, B.G. and Buysse, F.X., 1977. Comparison of laboratory methods for predicting the organic matter digestibility of forages. Anim. Feed Sci. Technol., 2: 337-349. Alexander, R.H. and MC Gowan, M., 1969. The assessment of the nutritive value of silage by determination of in vitro digestibility on homogenates prepared from fresh undried silage. J. Br. Grassl. Sot., 24: 195-198. Association of Official Analytical Chemists, 1984. Official Methods of Analysis. 14th Edition Assoc. Off. Anal. Chem., Washington, DC, 152 pp. Aufrere, J., 1982. Etude de la prevision de la digestibilite des fourrages par une methode enzymatiqye. Ann. Zootech., 31: 11 l-l 30. Barber, G.D., Offer, N.W. and Givens, D.I., 1989. Predicting the nutritive value of silage. In: W. Haresign and D.J.A. Cole (Editors), Recent Advances in Animal Nutrition. Butterworths, London, 141 pp. Bittante, G., Ramanzin, M. and Cozzi, G., 1988. Estimation of the organic matter in vivo digestibility and of the metabolizable energy content of feedstuffs and byproducts by means of the fibre bag technique. J. Anim. Sci., 66 (Suppl. 1): 495. Commissione Valutazione degli Alimenti, 1982. Valutazione degli alimenti di interesse zootecnice. 2. Aspetti metodologici della degradabilita in vivo. Zoot. Nutr. Anim., 8: 387-394. Cottyn, B.G., de Boever, J.L. and Vanacker, J.M., 1987. Estimation de la valeur alimentaire des fourrages grossiers des aliments concentres pour vaches laitieres. Rev. Agric., 40: 1537-l 55 1. Demarquilly,C. and Chenost, M., 1969. Etude de la digestion des fourrages dans le rumen par la mtthode des sachets de nylon. Liaisons avec la valeur alimentaire. Ann. Zootech., 18: 419-436. Dowman, M.G. and Collins, F.C., 1982. The use of enzymes to predict the digestibility of animal feeds. J. Sci. Food Agric., 33: 689-696. Givens, D-I., Everington, J.M. and Adamson, A.H., 1989. The digestibility and metabolizable energy content of grass silage and their prediction from laboratory measurements. Anim. Feed Sci. Technol., 24: 27-43. Givens, D-I., Everington, J.M. and Adamson, A.H., 1990. The nutritive value of spring-grown herbage produced on farms throughout England and Wales over 4 years. II. The prediction
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
333
of apparent digestibility in vivo from various laboratory measurements. Anim. Feed Sci. Technol., 27: 173-184. Goering, H.K. and van Soest, P.J., 1970. Forage Fiber Analysis, ARS, USDA, Agric. Handb. No. 379, Washington, DC, 20 pp. Ishizaki, S.M., Campbell, CM. and Toma, W.Y., 1976. Microdigestion techniques and chemical solubility methods as estimation of the digestibility of tropical grasses. J. Anim. Sci., 42: 1503-l 508. Jones, D.H. and Hayward, M.W., 1975. The effect of pepsin pretreatment of herbage on the prediction of dry matter digestibility from solubility in fungal cellulase solution. J. Sci. Food Agric., 26: 711-718. Joshi, D.C., 1972. Different measures in the prediction of the nutritive value of forages. Acta Agric. Stand., 22: 243-247. Korva, J. and Tuori, M., 1986. Prediction of the digestibility of silage and hay from the crude fibre and crude protein content. J. Agric. Sci. Finland, 58: 175-l 83. Lindberg, J.E., 1985. Estimation of rumen degradability of feed proteins with the in sacco technique and various in vitro methods: a review. Acta Agric. Stand., 25 (Suppl.): 64-97. Mbwile, R.P. and IJden, P., 1991. Comparison of laboratory methods on precision and accuracy of prediction forage organic matter digestibility. Anim. Feed. Sci. Technol., 32: 243-25 1. Menke, K.H. and Steingass, H., 1988. Estimation of the energetic feed value obtained from chemical analysis and in vitro gas production using rumen fluid. Anim. Res. Dev., 28: 7-55. Michalet-Doreau, B., Verite, R. and Chapoutot, P., 1987. Methodologie de mesure de la d&adabilite in sacco de l’azote des aliments dans le rumen. Bull. Tech. - Cent. Rech. Zootech. Vet., Theix, INRA 69: 5-7. Ministry of Agriculture, Fisheries and Food, 1977. Energy Allowance and Feeding System for Ruminants. Tech. Bull., 33,62 pp. Nocek, J.E., 1988. In situ and other methods to estimate ruminal protein and energy digestibility: a review. J. Dairy Sci., 7 1: 205 l-2069. SPSSPC/XT, 1984. SPSSInc., Chicago, IL, C-l 3 1 pp. uld, F., 1980. The use of nylon bag technique for the Orskov, E.R., Novell, Prod., 5: 195-213. evaluation of feed Tilley, J.M.A. and A two stage technique for the in vitro digestion of forage 89. Methods of analysis for predicting the energy and dology of Analysis of Feeding protein value of feeds for farm animals. Workshop Livestock Feeding and NutriStuff for Ruminants, Lelystad, NL, 27-29 May. In search, Lelystad. P.J., 1982.Nutritional Ecology of the Books, Corvallis, OR, 260 Va PP.
323
.V., Amsterdam
I[.Andrighettoa, E. Gmber”, G. Cozzi”, G. Urayb, 6. Guidetti” and =Depavtment ofAnimal Science of Padova University, Padova, Italy bFederal Research Institute for Agriculture in Alpine Regions, BAL Gumpenstein. Austria (Received 23 July 1991; accepted 19 May 1992)
ABSTRACT Andrighetto, I., Gruber, L., Co&, G., Uray, C., Guidetti, G. and Buchgraber, K., 1992. Prediction of digestible organic matter in dry matter in vivo from the chemical composition, in vitro and in situ measurements on native mountain forages. Anim. Feed Sci. Technol., 39: 323-333. Assessment of forage nutritive value facilitates its appropriate inclusion in diets for ruminants. The objective of the present study was to determine the precision with which laboratory and in situ measurements could predict the digestible organic matter in dry matter (DGMD) in vivo of mountain forages, using multiple linear, step-wise regression analyses. A joint research was carried out between the Federal Research Institute for Agriculture in Alpine Regions (BAL Gumpenstein, Austria) and the Department of Animal Science of Padova University (Italy). The data set included 66 native mountain forages for which in vivo digestibility data were available. Forage harvesting methods (hay, silage (SIL) and fresh grass) were forced to enter as dummy variables in the equations. Four sets of independent variables: Weende constituents (crude protein, ash and crude fibre), Van Soest fibre constituents (NDF, ADF and ADL), in situ 48 h DM degradation and in vitro techniques (NDF-cellulase, pepsin-cellulase (PEPCEL), Tilley-Terry and gas production HFT) were submitted to a step-wise regression analysis. In the first stage of the regression, the four sets of variables were separately analysed and the best equation was obtained with the in vitro pepsin-cellulase procedure: DOMD=44.90-5.92HAY-7.61 SIL+O.35 PEPCEL (n=66; mean=57.68~5.06;RSD=3.43;R2=0.540). The second stage of regression implied the subsequent inclusion of the sets following a criterion based on the higher degree of complexity of the analytical methods (Weende plus Van Soest plus in situ plus in vitro). The resulting final equation was: Correspondence dova, Italy.
to: I. Andrighetto,
0 1992 Elsevier Science Publishers
Department
of Animal Science of Padova
B.V. All rights reserved 0377-8401/92/$05.00
University,
Pa-
324
1.ANDRIGHETTG ET AL.
DOMD= 19.85-5.94 HAY-4.97 SIL-0.70 ASH+0.25 NDF+0.64 PEPCEL (RSD=2.86;R2=0.681). The equation, which increased the precision in predicting DOMD in vivo, requires only a restricted number of laboratory determinations and may be suitable for a widespread utilisation by mountain farmers.
INTRODUCTION
Animal nutrition in mountain environments is largely based on the use of adapted native pastures. In fact, in these areas there are frequently no sown pastures available. Environmental constraints such as elevation, slope, orography, pedology and sun exposure, limit the production of sown pastures and native pastures are frequently the only feed available at reasonable cost. Assessment of the nutritive value of native forages is important in order to define their most appropriate use as components of diets for ruminants. The energy value of forages is often measured in terms of in vivo organic matter digestibility (OMD) (Aerts et al., 1977; Barber et al., 1989; Givens et al., 1989). However the in vivo procedures require animals, special devices, considerable time and money, as well as the availability of large quantities of test feed (Cottyn et al., 1987). These factors, especially in mountain areas, limit the use of the method and several attempts have been made to develop simple techniques for predicting in vivo OMD from less expensive analyses. The ideal characteristics of these methods should be simplicity, rapidity, low cost, precision and reliability (Cottyn et al., 1987). Chemical analysis such as crude fibre and some cell wall fractions (NDF, ADF, lignin) were used in the prediction of the nutritive value of forages (Joshi, 1972; Aerts et al., 1977). Several studies developed in vitro techniques based on incubation of the forages with rumen liquor (Tilley and Terry, 1963; Alexander and MC Gowan, 1969; Mbwile and Uden, 199 1 ), with cellfree cellulase-type enzymes (Jones and Hayward, 1975; Van Soest, 1982; Dowman and Collins, 1982)) or on the gas produced by an incubation with rumen liquor (Menke and Steingass, 1988 ). OMD was also estimated by in situ methods using cannulated animals (Aerts et al., 1977; Orskov et al., 1980). The objective of the present study was to show the precision with which laboratory and in situ measurements could predict the in vivo digestibility of native mountain forages, using multiple linear, step-wise regression analysis. Within the activities of the Alpe-Adria association, this research project was carried out jointly between the Federal Research Institute for Agriculture in Alpine Regions (Bal Gumpenstein, Austria) and the Department of Animal Science of Padova University (Italy).
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
MATERIALS AND METHODS
The study was based on all the s areas for which in vivo digestibility 66 samples of native pastures, co classified acceding to storage m nant forage species were P&z4
silage or fresh grass.
sis, Lolium perenne, Trisetumjlaves
small percentages of legu and Trifolium repens. The samples of fresh forage was then deep fro
ss were harvested an , packed in single
Forage chemical composition
1984 ). Cell wall co
days at 55°C. In situ dry matter
moisture content, as s
prediction by in situ i Cows were fed 1.8 age: concentrate ratio.
D&I disappearance.
degradability
325
326
1.ANDRIGHETTO ET AL.
In vitroOM digestibility Four methods measuring in vitro digestibility were adopted: ( 1) two-stage NDF-cellulase method (Dowman and Collins, 1982); the enzyme was a fungal cellulase ‘Onozuca’ R 10 from Trichodermaviridae (Yakult Honsha Co. Ltd, Tokyo, Japan); (2) two-stage pepsin-cellulase (PEPCEL) method (Jones and Hayward, 1975 ), modified by Aufrere ( 1982); the pepsin was Merk 7 190 (Merk, Darmstadt, Germany) and the cellulase was the same as in the previous method, ( 3) two-stage rumen inoculum-pepsin procedure (Tilley and Terry, 1963 )z modified by Alexander and MCGowan ( 1969). Donor animals were the same cows used in the in situ method and were fed the same diet; (4) gas production was measured according to the procedure of Menke and Steingass ( 1988 ). In vivomeasurements OMD of the forages was analysed using adult sheep. Austrian forage was evaluated with Mountain Sheep breed animals (60-70 kg LW ) using the procedures suggested by Van Es and Van der Meer ( 1989). OMD of the forages collected by Padova was tested following the procedures of the Italian Commitee of Feed Evaluation (Commissione Valutazione degli Alimenti, 1982 ) with Lamon breed sheep (50-60 kg LW). OMD data were converted to digestible organic matter in dry matter (DOMD) values considering the ash content of the forage (Ministry of Agriculture, Fisheries and Food, 1977). Fittingequations To estimate the DOMD of forage by multiple linear regression equations, several independent variables were considered according to a multistage stepwise regression analysis. Analysis was carried out using the Regression Procedure of SPSS-PC package (SPSS PC/XT, 1984). In the first stage, four sets of independent variables ( Weende chemical fractions, Van Soest fibre, in situ and in vitro values) were separately analysed. The Weende set considered crude protein, ash and crude fibre; ether extract was not included because of its extremely variable composition in forage, as noted by Van Soest ( 1982); nitrogen-free extract was also excluded because of lack of independence due to its determination by difference from the other Weende constituents. The Van Soest fibre set considered NDF, ADF and ADL.
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
327
stage of regressio ent inclusion of the sets following a criterion based on the hi methods. Three regression analyses were independent variables: in the first, Ween ered, whereas in the second and in the third, in situ added in turn. Two dummy variables were always forced to enter to identify the ty forage (hay and silage ) , using the intercept for the fresh grass.Equation fitted by the least-squares method following a step-wise procedure w 0.05 probability level for inclusion or deletion of variables. To revent biased estimations due to computational problems, a threshold value of tolerance of 0.0 1 (the proportion of variability not explained by the variables not yet entered) was adopted. Along with the regression coeffkients the analysis furnished the coefficient of determ’ adjusted for degrees of freedom ( the residual standard deviation and the residual variation coeffr RESULTS AND DISCUSSION
Variability in
content of fresh grass ( s, while wilting intensi variability of the silages. The lower protein conte the leaf losses during wilti
The in situ and in
gardless of forage typ which may be due to 1) because nitrogen c
Predictionsof first stage of the pendent variable
e regression analysis c rately (Table 4). The de
nation coefficient
I. ANDRIGHETTO ET AL.
328 TABLE 1 Forage chemical composition Forage type
Hay
Wage
Fresh grass
Number of samples
28
28
10
Dry matter (%) mean SD
87.4
1.8
29.8 9.0
28.4 13.7
7.6 1.6
10.8 3.1
2.2
Organic matter (% DM ) Mean SD
92.4 1.6
89.2 3.1
92.9 2.3
Crude protein (I DM ) Mean SD
9.6 1.6
12.4 2.5
12.4 4.1
Ether extract (% DM) Mean SD
1.8 .4
3.8 1.1
2.4 .8
34.1 3.9
31.6 4.5
32.5 5.4
46.8 3.2
41.5 3.0
45.7 2.1
Neutral detergent fibre (% DM) Mean SD
64.7 6.4
56.5 9.3
65.2 8.4
Acid detergent fibre (% DM) Mean SD
40.2 4.3
39.5 5.3
39.3 5.2
4.4 1.4
5.3 2.7
6.0 1.5
Ash (% DM ) Mean SD
Crude fibre (% DM) Mean SD
7.0
Nitrogen-free extract (I DM) Mean SD
Acid detergent lignin (% DM ) Mean SD
PREDICTION OF DIGESTIBLE ORGANIC MATTER IN DRY MATTER
329
TABLE 2 Forage in situ DM degradation, in vitro GM digestibility and HFT gas production Forage type
Nay
Wage
Fresh grass
Number of samples
28
28
10
Dry matter (% ) Mean SD
87.4 1.8
29.8 9.0
28.4 13.7
In situ 48 h DM degradation # Mean SD
72.0 7.1
75.3 8.4
68.5 13.3
NDF-cellulase OMD 016 Mean SD
48.5 10.1
50.0 12.5
41.1 6.3
Pepsin-cellulase GMD % Mean SD
50.5 7.7
56.0 9.7
48.5 13.3
Tilley and Terry OMD % Mean SD
65.1 7.5
66.2 7.3
59.3 13.1
Gas prod. ml per 200 mg DM in 24 h Mean 42.0 SD 6.0
38.5 6.0
35.7 8.4
and the residual variation coeffkient o from simple chemical analyses to in also showed the poor capacity of the conforms to the results of Aerts et al. crude fibre is variable in composition a from one laboratory to another, even tho (Cottyn et al., 1987). The few cases fibre are limited to homogeneous b geographical areas (Korva and Tuori, 1986). The best equation was obtained with the in vitro set a
stage excluded all the
I. ANDRIGHETTO ET AL.
330 TABLE 3 Forage in vivo digestibility Forage type
Hay
Silage
Fresh grass
Number of samples
28
28
10
Dry matter (%) Mean SD
87.4 1.8
29.8 9.0
28.4 13.7
Organic matter in DM digest. % Mean SD
56.8 3.8
57.0 5.4
62.0 5.6
58.1 7.1
59.2 5.9
63.1 9.1
39.6 15.9
62.5 9.5
56.1 7.4
62.1 5.5
67.7 7.6
66.7 8.6
Crude pro1ein Mean SD
digest. %
Ether extract Mean SD
digest. %
Crude fibre Mean SD
digest. 96
.I
sion of DOMD prediction was further improved after adding the data obtained by the in situ procedure. In previous studies, the bag technique was shown to be an effective means of predicting OMD in viva, with forage marquilly and Chenost, 1969; Aerts et al., 1977), tropical grasses (Ishiz al., 1976) and fibrous by-products (Bittante et al., 1988). However, the relatively simple procedure of the bag technique requires, along with the maintainance of cannulated animals, a particular care in the choice of several factors, such as bag pore size, sample particle size, sample size to bag surface ratio, incubation time, washing procedure, which can influence the final results, leading to unreliable predictions (Lindberg, 1985;Nocek, 1988). The last stage of the multiple regression estimation included the in vitro procedures, and futher improved the precision of estimating DOMD in vivo. The final equation including ash and NDF content of the forage along with the pepsin-cellulase in vitro procedure showed a determination coefficient of 0.68 and the residual standard deviation was reduced,to 2.86. N in the last step of the regression analysis with a lower contribut The positive sign of the NDF estimated coeffkient is hardly explainable from a biological point of view. However, it is coefficient simultaneously fitted along wi the equation (ASH and PEPCEL).
ADL, Acid detergent lignin (U dry matter); ASH, Ash (96 dry matter); CF, Crude fibre (I dry matter); ‘DOMD, Digestible organic matter in dry matter ( W dry matter); HAY, Forage-type hay ( 1, yes; 0, no); IS, In situ dry matter degradation (%); NDF, Neutral detergent tibre (I dry matter); PEPCEL, Pepsin-cellulase organic matter digestibility (%); SIL, Forage-type silage ( 1, yes; 0, no).
DOMD=69.76-7.27 HAY-5.85 SIL- 1.3OADL DOMD=48.56-7.01 HAY-5.35 SIL+O.31 IS-O.58 ASH-O.66 ADL DOMD= 19.85-5.94 HAY -4.97 SIL-0.70 ASH+0.25 NDF+0.64 PEPCEL
SIL-0.82 CF-0.68 ASH SIL- l.JOADL SIL+0.34 IS SIL+O.35 PEPCEL
Weende + Van Soest + in situ + in vitro
HAY-3.10 HAY-5.85 HAY -7.28 HAY-7.61
DOMD=93.32-3.42 DOMD-69.76-7.27 DOMD=38.68-6.40 DOMD=44.90-5.92
Weende Van Soest In situ In vitro
Independent variables
Multiple regression estimation of in vivo DOMD’ (n=66; mean= 57.68 + 5.06 SD)
TABLE 4
6.90 6.17 4.96
3.98 3.56 2.86
6.92 6.90 6.54 5.95
3.99 3.98 3.77 3.43
0.377 0.379 0.445 0.540 0.379 0.506 0.681
RVC%
RSD
R2
%
g $ ij
0
: $ 3 E
2 o
332
I. ANDRIGHEm
ET AL.
This equation was better than that obtained in the first stage of the regression analysis, where the in vitro set was separately considered (R2=0.54, RSD= 3.43). However both equations indicate a high level of precision in predicting DOMD in vivo by the pepsin-cellulase method, which in comparison with other in vitro techniques, has been proposed specifically for the evaluation of this category of feeds. Furthermore the pepsin-cellulase method appears the simplest in vitro technique from the operative point of view, either because of its total enzymatic procedure free from donor animals, or due to the lack of any decanting and centrifuging which can cause sample losses, thus increasing variability.
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