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Digestibility - Department of Animal Sciences

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DIGESTIBILITY


Apparent v. true digestibility<br />

True digestibility involves correction for endogenous losses,<br />

apparent digestion does not.<br />

Endogenous losses<br />

– Include:<br />

• Sloughed <strong>of</strong>f intestinal cells<br />

• Digestive juices (enzymes)<br />

• Microbial matter<br />

– Quantified by measuring fecal output <strong>of</strong> fasted animals<br />

– Can be 9.8 to 12.9 % DMI<br />

– Should they be quantified?


In vivo digestibility methods<br />

Direct or total/complete collection<br />

Difference method<br />

Regression method<br />

Indirect method


1. Total collection


In vivo digestibility trials in<br />

metabolism crates


In vivo digestibility trials in pens


Total collection<br />

calculations<br />

<strong>Digestibility</strong> (g/kg) =<br />

Nutrient in feed - Nutrient in feces x 1000<br />

Nutrient in feed<br />

Dry matter digestibility (DMD, g/kg) =<br />

DM in feed - DM in feces x 1000<br />

DM in feed<br />

Organic matter digestibility (OMD, g/kg) =<br />

OM in feed - OM in feces x 1000<br />

OM in feed<br />

Can be expressed as a proportion, % or g/kg


<strong>Digestibility</strong> indices that estimate<br />

energy value<br />

Digestible organic matter content (DOMD) (g/kg DM)<br />

= OM in feed - OM in feces x 1000<br />

DM in feed<br />

TDN = DCP + DCF + DNFE + DEE(2.25)<br />

– DCP= Digestible Crude Protein<br />

– DCF= Digestible Crude Fiber<br />

– DNFE= Digestible Nitrogen-Free Extract<br />

– DEE= Digestible Ether Extract (2.25)


2. Difference method<br />

Allows digy calculation for 2 feeds fed simultaneously<br />

Assumptions<br />

– No interaction b/w the digy <strong>of</strong> the feeds<br />

– Must know digy & fecal DM output (DMO) <strong>of</strong> base<br />

feed<br />

Test feed DMD =<br />

Cons<br />

Test feed DMI – (Fecal DMO- Base feed DMO)<br />

Test feed DMI<br />

– Assumptions may be invalid


3. Regression method<br />

Schneider & Flatt (1975)<br />

Also allows digy. estimation for two feeds<br />

– Feed different ratios <strong>of</strong> the two feeds<br />

– Estimate digy <strong>of</strong> each <strong>of</strong> the ratios<br />

– Fit regression <strong>of</strong> test feed inclusion vs. digy<br />

– Extrapolate to estimate digy <strong>of</strong> test feed.<br />

Cons<br />

– Considerable expense and labor for estimating digy<br />

<strong>of</strong> one feed.


DMD (g/kg)<br />

Regression method<br />

800<br />

Base feed digy.<br />

600<br />

400<br />

Test feed digy.<br />

200<br />

20 40 60 80 100<br />

% inclusion <strong>of</strong> test feed in ration


Digy trial issues<br />

Changeover designs<br />

– necessary if period effects are an issue e.g.<br />

• <strong>Animal</strong> physiological changes<br />

• Forage physiological changes<br />

Adaptation period<br />

– Necessary to adapt the animals to<br />

• New feed (microbial population changes)<br />

• Strange equipment<br />

• Strange housing<br />

– 6 – 14 day period is the norm


Marker digestibility trials<br />

Particularly useful for grazing animals<br />

Procedure<br />

– Add indigestible marker to feed eg chromic oxide<br />

– Measure concentration in feed & feces<br />

– Estimate disappearance <strong>of</strong> marker from gut.<br />

E.g. if a feed contains 1% Cr 2 O 3 & feces contains 2%<br />

Cr 2 O3, diet digestibility = 50%<br />

– Since Cr 3 O 2 conc. has doubled, 50% <strong>of</strong> DM must have<br />

been digested


Marker trials contd.<br />

For the digy <strong>of</strong> a specific nutrient,<br />

must also know the % nutrient in feed & feces<br />

%Nutrient = 100 – 100 x % indicator feed X % nutrient feces<br />

<strong>Digestibility</strong> % indicator feces % nutrient feed<br />

Homework:<br />

If lambs are fed a bahia grass diet containing 7%<br />

protein & 1% chromic oxide, and their feces contains<br />

5% CP and 2% chromic oxide. Calculate CP digy.


Marker digestibility<br />

Pros<br />

– Total feces collection not necessary<br />

– Total intake determination not necessary<br />

– Easier, less labor<br />

Cons<br />

– Representative sampling essential<br />

– Accurate estimation <strong>of</strong> nutrient or marker conc.<br />

essential<br />

– Assumes complete excretion <strong>of</strong> marker hence<br />

Recovery <strong>of</strong> marker determines accuracy <strong>of</strong> digy


Marker types<br />

External<br />

– Chromic oxide<br />

– Dysporium<br />

– Polyamide<br />

Can contaminate<br />

forage<br />

Internal<br />

– Lignin<br />

– AIA<br />

– ADF<br />

– n-alkanes<br />

Easier, less labor


Marker issues<br />

Difficulty <strong>of</strong> mixing marker with forages<br />

– Dose cows instead- ( s handling)<br />

Marker migration<br />

– Must not affect feed digy<br />

External markers may contaminate forage


Problems with in vivo<br />

experiments<br />

<strong>Animal</strong> trials are:<br />

– Expensive<br />

– Protracted<br />

– Laborious<br />

– Public concerns<br />

– <strong>Animal</strong> stress ???<br />

Must estimate nutritive value with less animal<br />

dependent techniques


Ideal in vitro methods should be:<br />

– Rapid (one step) & routinely practicable<br />

– Accurate<br />

– Cheap & not laborious<br />

– Repeatable & robust<br />

– Biologically meaningful<br />

– Broad-based (apply to all forage types)<br />

– Handle large nos. <strong>of</strong> samples<br />

– Laboratory-based


Rumen fluid –pepsin in vitro<br />

digestibility (IVOMD)<br />

•Developed by Tilley & Terry<br />

(1967)<br />

•Measures apparent digy in rumen<br />

fluid (48 h) and acid pepsin (48 h)<br />

•Gives accurate predictions <strong>of</strong> in<br />

vivo digy for most forages


Prediction <strong>of</strong> silage OMD in vivo from<br />

different methods (g/kg DM)<br />

Method r 2 RSD<br />

KMnO 4 lignin 21.8 54.6<br />

ADF 32.1 50.9<br />

NDF 45.7 45.5<br />

(M) ADF 55.8 40.9<br />

IVOMD 74.1 33.6<br />

(Givens et al., 1989)


Rumen fluid problems<br />

Variation in Inoculum composition & activity due to<br />

– Host animal diet<br />

– <strong>Animal</strong> species<br />

– Collection time<br />

– Processing (blending vs. filtration)


Rumen fluid problems<br />

Analytical issues<br />

– Maintenance <strong>of</strong> anaerobic media; optimal pH, temp<br />

– High viscosity hinders filtration<br />

– Offensive odors<br />

– Hygiene – (Prevent pathogen infection)


In vivo DOMD<br />

Relationship between in vivo and<br />

in vitro DOMD <strong>of</strong> wheat silage (g/kg DM)<br />

690<br />

670<br />

650<br />

Year One<br />

Year Two<br />

630<br />

r 2 =0.24<br />

610<br />

590<br />

570<br />

550<br />

530<br />

530 580 630 680<br />

Rumen fluid-pepsin DOMD<br />

(Adesogan et al. 1998)


Rumen fluid technique -<br />

problems<br />

Standards needed to correct for variability in rumen<br />

fluid composition & activity<br />

Disregards / inappropriately represents:<br />

– Ruminal outflow (uses a batch process)<br />

– Digests maillard product not digested in vivo<br />

– Associative effects between feeds<br />

– Endogenous secretions<br />

– Post abomasal digestion


Alternatives to Tilley & Terry<br />

1. Rumen fluid – Neutral detergent (Van Soest, 1967)<br />

– More akin to true digestibility<br />

– Gives higher digy. values<br />

– Still requires rumen fluid<br />

2. Feces<br />

– Gives lower digestibility estimates<br />

3. Enzyme- based assays


Prediction <strong>of</strong> DMD in vivo from in vitro<br />

fecal liquor DMD<br />

Spp. <strong>of</strong> feces donor<br />

r 2 range<br />

Ovine 0.33 – 0.98<br />

Bovine 0.77 – 0.97<br />

Equine 0.90<br />

Caprine 0.96-0.97<br />

(Ohmed et al., 2001)


Cell-free enzyme in vitro digestibility<br />

Examples <strong>of</strong> procedures used:<br />

1. Cellulase<br />

2. Neutral detergent- cellulase<br />

3. Neutral detergent-cellulase +gammanase<br />

4. Pepsin cellulase<br />

Amylase pre-treatment important for starch-rich feeds<br />

Gammanase for oil-rich feeds


Relationships between DMD in vivo and<br />

enzyme predicted DMD<br />

Method R 2<br />

Cellulase 0.83<br />

Neutral detergent cellulase 0.94<br />

Acid pepsin – cellulase 0.88<br />

Rumen fluid 0.83<br />

(Bughara & Sleper, 1986)


Prediction <strong>of</strong> in vivo OMD <strong>of</strong><br />

forages from different methods<br />

Method r RSD (%) AE(+)<br />

ND + cellulase 0.90 3.3 0.9<br />

Pepsin + cellulase 0.94 2.6 0.3<br />

(McLeod & Minson, 1982)<br />

Higher analytical error with ND – cellulase technique<br />

may outweigh shorter processing time


Prediction <strong>of</strong> in vivo OMD <strong>of</strong> spring<br />

grass from different methods<br />

Method r 2 RSD<br />

ND + cellulase 76.6 27.1<br />

Pepsin + cellulase 75.9 28.8<br />

Rumen fluid-pepsin 67.0 33.2<br />

(M) ADF 66.9 33.3<br />

Poorer relationships found for autumn grass (r 2 = 13- 20)<br />

(Givens et al., 1990)


Effect <strong>of</strong> enzyme source on cellulase<br />

activity<br />

% DM solubilized<br />

Fungi Herbage Cellulose paper<br />

Trichoderma spp. 57 69<br />

Basidiomycete 48 20<br />

Aspergillus niger 45 10<br />

Rhizopus spp. 35 7<br />

(Jones & Hayward, 1975)


14<br />

C-Casein hydrolysis (mg/ml)<br />

0.5 Co-culture<br />

0.0 0.25<br />

S. bovis<br />

0.0<br />

S. ruminantium<br />

10 20<br />

Time (h)<br />

Commercial enzymes don’t fully simulate microbial<br />

activity <strong>of</strong> mixed rumen microbes


Enzyme method problems<br />

Equations are species-specific<br />

Represent effect <strong>of</strong> a few enzymes<br />

Variability in enzyme activity<br />

– Due to enzyme source & batch


The ANKOM equipment


tube<br />

tube<br />

Ankom digestibility validation<br />

Prediction <strong>of</strong> tube app. DOMD from bag app. DOMD<br />

Prediction <strong>of</strong> tube true DOMD from bag true DOMD<br />

80<br />

y = 0.87x + 4.25<br />

r 2 = 0.83; rsd = 4.04<br />

80<br />

y = 0.99x + 3.61<br />

70<br />

r 2 = 0.93; rsd=2.93<br />

70<br />

60<br />

50<br />

60<br />

40<br />

bag<br />

40 50 60 70 80<br />

50<br />

bag<br />

50 55 60 65 70 75 80 85


ANKOM pros & cons<br />

Pros<br />

– Simplifies filtration, incubation and mixing<br />

– Uses a batch process (& ash-free bags)<br />

Cons<br />

– Bag pore size may allow excess outflow or restrict<br />

microbial colonization<br />

– Bag material & pore size may affect results<br />

• Mon<strong>of</strong>ilamentous cloth – precise aperture<br />

• Multifilamentous cloth – pore size affected by stresses<br />

e.g. dacron


In vitro digestibility summary<br />

Pros<br />

– Predicts in vivo digy more accurately than NDF or<br />

lignin<br />

– Handles several samples & are biologically<br />

meaningful<br />

Cons<br />

– May require fistulated animals<br />

– Labor intensive & protracted<br />

– Plagued by variability in composition & activity <strong>of</strong><br />

inoculum/enzyme<br />

– Doesn’t indicate the kinetics <strong>of</strong> digestion


<strong>Digestibility</strong> references<br />

Chapters 6 – 8 In: D.I. Givens, E. Owen, R.F.E. Axford and H.M. Omed (Editors) 2000,<br />

Forage Evaluation in Ruminant Nutrition. CABI Publishing, Wallingford, UK, pp. 113-<br />

134.<br />

Adesogan, A.T, Givens D.I. and Owen. E. Measuring chemical composition and nutritive<br />

value in forages. Field and Laboratory methods for grassland and animal production<br />

research. CABI Publishing. P 263<br />

Tilley, J.M.A. and Terry, R.A., 1963. A two stage technique for the in vitro digestion <strong>of</strong><br />

forage crops. Journal <strong>of</strong> the British Grassland Society, 18: 104-111.<br />

Van Soest, P.J., Wine, R.H. and Moore, L.A., 1966. Estimation <strong>of</strong> the true digestibility <strong>of</strong><br />

forages by the in vitro digestion <strong>of</strong> cell walls. Proceedings <strong>of</strong> , The Xth International<br />

Grassland Congress, Helsinki. Finish Grassland Association., pp 438-441.<br />

Vogel, K.P., Pedersen, J.F., Masterson, S.D. and Toy, J.J., 1999. Evaluation <strong>of</strong> a filter bag<br />

system for NDF, ADF, and IVDMD forage analysis. Crop Science, 39: 276-279.<br />

Wilman, D. and Adesogan, A., 2000. A comparison <strong>of</strong> filter bag methods with conventional<br />

tube methods <strong>of</strong> determining the in vitro digestibility <strong>of</strong> forages. <strong>Animal</strong> Feed Science and<br />

Technology, 84: 33-47.

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