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Alma Mater Studiorum – University of Bologna – Department of Veterinary Medicine

The University of Bologna was probably the first University in the western world. Its history is one of great thinkers in science and the humanities, making it an indispensable point of reference in the panorama of European culture. The institution that we today call the University began to take its structure in Bologna at the end of the eleventh century, when masters of Grammar, Rhetoric and Logic began to devote themselves to the law. In the nineteenth century a committee of historians, led by Giosuè Carducci, attributed the birth of the University to the year 1088.

The Faculty of Veterinary Medicine was born in 1784. But it was only in 1991 that the Faculty took place where it is today. The old buildings are now in downtown Bologna, where it is difficult to maintain farms and research facilities. Close to the core building, there are other scientific and educational structures: a centralised library, a teaching hospital, a teaching slaughterhouse, an experimental farm and a centre for artificial insemination of various animal species. A detached structure is the Cesenatico

Centre for Aquaculture and Ittiopathology. Many major groups are involved in scientific research and educational activities: Clinical, Surgery, Public Health, Animal Pathology, Biochemistry, Morphophysiology and Nutrition and Feeding.The Nutrition and Feeding section works mainly in several major species: dogs and cats, pigs and dairy cattle. Within the last 5 years, the Dairy Cattle group expanded its research: the experimental farm houses now 75 cows in lactation, allowing us to design trials on diets composition, milk production and animal behaviour; in a strict relationship, our lab can now afford several determination: wet chemistry and NIRS for forage analysis, chromatography for VFAs and long chain fatty acids in milk, forages and rumen content, two Tilley and Terry systems for fibre and starch in vitro digestibility, and the new space for rumen microbiology.

University of Bologna, Faculty of Veterinary Medicine

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International Symposium

12th May 2011 – Castel san Pietro Terme, Italy

With the support of

4

Benvenuto!

Welcome! By Professor Giovanni Savoini, Department of Veterinary Sciences and Technologies for Food Safety,

Università degli Studi di Milano, Italy.

Today, agricultural products are not only used as a source of nutrients for human beings and animals, but they are also used to produce energy and eco-friendly goods. The more appropriate example is the use of corn for the production of ethanol and biodegradable plastic. Moreover, agricultural crops can be fermented to produce biogas. These processes usually have a positive impact on the public opinion, as they are considered means to reduce pollution, using renewal raw materials to produce fuels and goods. Unfortunately, this approach creates a competition between the utilization of agricultural crops as nutrient sources and as non-food materials, and the result is often an increase in price. The prices of cereals indeed varied significantly in the last years and reached high values that made difficult the purchase of these essential energetic feed to many people in the world.

Within this scenario it is quite clear that it is important, and probably it will be even more important in the future, to reduce in the diet of animals the amount of valuable nutrients for human consumption (starch and protein) in favour of fibrous sources. Among food producing animals, ruminants are the only ones able to transform great amounts of fibre into energy that can be utilized for maintenance and for milk and meat production. But fibre plays also a dietetic role in human nutrition and can be used to produce energy too, implying that the production of fibre sources has to be oriented according to its different uses.

The general tendency in ruminant nutrition is to increase the use of home-grown feeds, mainly forages, as this allows a greater use of grains for human consumption and it can prevent rumen fermentation disorders such as (sub)acute acidosis, resulting in lower performance and other metabolic disorders. But, on the other hand, high yielding dairy cattle must be fed diets with a high energy content to sustain their nutrient requirements linked to high milk production. This implies that cows must be fed highly digestible forages. Moreover, the increase of fibre digestibility positively influences the rumen rate of passage allowing cows to eat more.

The goal of increasing fibre utilization implies the knowledge of the factors that affect its degradation and kinetic in the rumen, and the knowledge of the rumen microbiota and how to increase the fibrolytic populations and activities. Moreover it is also important to investigate the dietetic role of fibre, the non dietary factors that could affect rumen function, and finally how to include all these information in mathematical models to simulate the animal response to dietary changes.

Prof. Giovanni Savoini

Fibre: a key element for dairy production profitability?

5

Bienvenue!

Welcome

By Olivier Clech, Vice President, Lallemand Animal Nutrition, Human Health and Pharmaceuticals, Lallemand SAS, France. Dear Participants, I would like to extend my grateful appreciation to the University of Bologna for allowing Lallemand Animal Nutrition to take part in this event. At Lallemand, we believe that micro-organisms will take an increasingly important role in animal nutrition, in ruminants in particular. Yeasts and bacteria have clearly demonstrated their value in industries such as baking, brewing, winemaking, and, more recently, bioethanol and plant care …due to their exceptional capacity to add value to carbohydrates and other organic and mineral compounds. Over the past decades, micro-organisms have demonstrated their benefits in ruminant diets too, in preventing some well known metabolic disorders worth millions to the dairy industry, such as sub-acute acidosis, and in participating to a better utilization of highly concentrated diets. Today, we are learning that those beneficial micro-organisms can do more by enhancing the digestion of fibre, allowing to extract additional energy and nutrients from the largest and least used source of dietary carbohydrate on earth: the fibre. With high fluctuations in feed and milk prices, improving feed efficiency and maximizing Income Over Feed Cost becomes crucial. It is necessary to evaluate different feeding strategies and the use of efficient microbial solutions exerting a positive impact on the rumen ecosystem, in order to optimize digestion and utilization of the fibre fraction of the diets while safeguarding the animal health and welfare. It is an honour for Lallemand Animal Nutrition to be associated with some of the world’s best ruminants scientists and leading nutrition experts for this convention, and I am sure you will bring back with you a lot of very valuable information that you will be able to translate into day-to-day feeding and herd management recommendations. Moreover, it is a rare opportunity that we should all take for exchanging experiences and points of view, so enjoy these sessions, and take the best out of it.

Very sincerely,

Olivier Clech


6

Benvenuto!

Welcome

By Philippe Bruneau, Managing Director Filozoo Srl, Italy

Dear Participants, The year 2010 and the first months of 2011 have shown strong changes that will leave a mark on the beginning of this new Millennium: -the INSTABILITY of our economical model based on financial speculation -the FRAGILITY of Western society no longer able to find its balance -the impressive GROWTH of China and India allowing these countries to compete for the leadership on the international scene -the regular DEFICIT between the offer and demand of raw materials from Agriculture and other sources -the INCREASE of a world medium social class consuming more animal proteins produced from grains and feedstuffs dependant on climatic factors Here lay the main reasons explaining the observed unpredictable price variations of feed stuffs and grains. Unlike others who are disoriented in front of such drastic changes, partners Lallemand & Filozoo-InVivo NSA in collaboration with the prestigious Veterinary Faculty of Bologna see a fantastic opportunity to contribute together to the improvement of animal production performances. This Symposium is the occasion to offer a fruitful meeting around a current issue: how to further improve fibre digestibility in ruminants. We hope you will return home with new solutions to a recurrent customer problem. Philippe Bruneau


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Fibre: a key element for dairy production profitability? Chairman: Pr . Giovanni Savoini (University of Milan, Italy) 9:30 Registration & coffee

10: 00 Welcome address by Pr A. Formigoni, University of Bologna, Italy.

10: 15 Introduction: The dietetic role of fibre

(Pr A. Formigoni, Uni of Bologna, Italy)

11: 00 Fibre degradation (and kinetics) and the factors that affect it

(Dr D. Mertens, Mertens Innovation & Research LLC, Wisconsin , USA)

11: 45 Fibre degrading microbiota in the ruminant gut and effect of active dry yeast on fibrolytic populations and activities

(Dr F. Chaucheyras-Durand INRA/Lallemand Animal Nutrition, France )

12: 30 Lunch

14:30 Non-dietary factors influencing rumen function and dairy cow performance

(Dr A. Bach, IRTA Spain).

15:15 Impact of rumen modifiers on ration formulation

(Dr C. Sniffen, Fencrest LLC New Hampshire, USA)

16:00 Conclusions

16:30 End


9

Contents

Introductory Notes /Preface 2

Contents 9

The Speakers 11

Pr . Giovanni Savoin 1

Pr . Andrea Formigoni

Dr David Mertens 11

Dr Frédérique Chaucheyras-Durand 11

Dr Alex Bach 11

Dr Charles Sniffen 1

The dietetic role of fibre, by A. Formigoni 13

Fibre degradation (and kinetics) and the factors that affect it, by D. Mertens 23

Fibre degrading microbiota in the ruminant gut and effect of active dry yeast on fibrolytic

populations and activities, by F. Chaucheyras-Durand 33

Non-dietary factors influencing rumen function and dairy cow performance, by A. Bach 39

Impact of rumen modifiers on ration formulation, by C. Sniffen 49


11

The Speakers

Pr . Giovanni Savoini, University of Milan ([email protected]) Professor Giovanni Savoini is an expert in dairy nutrition and feed technology. He is full Professor in Animal Nutrition at the Università degli Studi di Milano, Department of Veterinary Sciences and Technologies for Food Safety, in Italy. He is also a member of the Scientific Commission for Research and Technological Transfer and is the Scientific Director of the Animal Production Research and Teaching Centre of the Polo Univesitario of Lodi (Università degli Studi di Milano). He is involved in various animal nutrition research projects and acts as a consultant on feed additives European dossiers. He has recently developed methods for

feed analysis based on modern analytical techniques.

Pr . Andrea Formigoni, University of Bologna ([email protected]). Andrea Formigoni is full Professor of Animal Nutrition and Feeding at the University of Bologna, Faculty of Veterinary Medicine and responsible of the Dairy unit centre. His main research interest are in dairy cow nutrition, focusing in particular on the relationship between feeding and milk yield, feeding techniques, animal welfare and health, quality of feedstuffs (mainly forage). As nutritional and managerial specialist, he is also member of the Certification Committee of the Department for the control of the quality of Parmigiano- Reggiano. Dr David Mertens, Mertens Innovation & Research LLC, Wisconsin ([email protected]) Dr. David R. Mertens is known nationally and internationally as an expert on the analysis of fibre in feeds, the maximum and minimum fibre requirements of dairy cows, and the mathematical modeling of the intake and digestion of fibre. While on the faculties of Iowa State University and the University of Georgia, Dr. Mertens developed a reputation as an outstanding teacher for animal nutrition and dairy science. From 1984 to 2009, he focused on dairy nutrition research at the U.S. Dairy Forage Research Center in Wisconsin. In 2010, he formed Mertens Innovation & Research LLC to provide expertise in feed evaluation analyses,

research management, data interpretation, and mathematical modeling of digestion. He wants to see the results of his efforts used by the people feeding and managing livestock on the farm.

Dr Frédérique Chaucheyras-Durand, INRA/Lallemand Animal Nutrition ([email protected]) Frédérique Chaucheyras-Durand obtained a PhD in Microbiology in 1995 at Blaise Pascal University, Clermont-Ferrand, France. She has been involved in the last steps of selection of Saccharomyces cerevisiae I-1077 as a rumen specific yeast strain, under the financial support of Lallemand and the scientific collaboration of INRA, unit of Microbiology. Her main activities are focused on interactions between S.cerevisiae I-1077 and the rumen microbiota under a collaborative research program with INRA. Moreover, she is also involved into evaluation of

effects and mechanisms of action of other probiotic microorganisms or silage bacterial inoculants used in ruminant nutrition and health.

Dr Alex Bach, IRTA,Spain ([email protected]) Dr Àlex Bach heads the Department of Ruminant Production of IRTA (Institut de Recerca i Tecnologia Agroalimentàries), devoted to study ruminant production systems (nutrition, management, development...) and he is a research professor of ICREA (Institut Català de Recerca i Estudis Avançats), an institution formed by high-quality researchers throughout the world that fosters research in Catalonia, Spain. He currently conducts research on management, nutrition, and metabolism of dairy cows and replacements.

Charles Sniffen, Fencrest LLC New Hampshire, USA ([email protected]) Sniffen has taught nutrition and management of dairy cows at the Universities of Maine,

Cornell and Michigan since 1970. Most of his career has been dedicated to research in the amino acid area. He is the one who introduced solubility and rumen degradability of protein and other feed components into feed evaluation systems. In the last 20 years a significant part of his time has been devoted to the development of dairy nutrition models. Today, Sniffen is still actively involved in feeding of dairy cattle as President of Fencrest LLC, located in Holderness, NH.


Dietetic Role of fibre

Andrea [email protected]

Castel S. Pietro Terme, 12 maggio 2011

14

Introduction: The dietetic role of fibres

Andrea Formigoni

Dipartimento Scienze Mediche Veterinarie

Alma Mater Studiorum – Università di Bologna

[email protected]

The rumen is incredibly able to utilize fibre, in particular from young and barely lignified forages

Fibre (aNDF) is a mixture of several organic compounds, differing in rumen digestibility; it is possible to identify in particular: - Potentially digestible, rapidly digested - Potentially digestible, slowly digested - Indigestible

The fibre indigestible fraction is related to the lignin content of the cell wall, but this relation is not constant, as so far thought.

To be utilized, fibre is selectively retained into the rumen for a long time, while teeth reduce particles size during eating and rumination.

Major part of fibre dietetic role is due to the ability of forages (the main fibrous compound of any diet) to stimulate chewing activity; native structure (straw is more efficient than grass, and grasses are more efficient than legumes) and particles size and shape are probably the main factors involved. Besides,more chewing activity can slow down the feed intake rate, which is important to: prevent a dangerous amount of digestible organic matter in the rumen, increase saliva production (buffering effect), improve rumen motility and passage rate. Adequate dietary fibre levels can.also improve digestion efficiency, affecting positively pH dynamics in the rumen.

While easily digestible fibre disappears rapidly from the rumen, the dietetic role is played mainly by the indigestible and slowly digestible fibre fractions: these components had to be chewed for a longer time and remain into the rumen longer, thus regulating the intake rate.


15

Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h

da: P. Huhtanen et al. / Animal Feed Science and Technology 133 (2007) 206–227

Ruminal passage rate (%/h) depends

on fibre particles size and digestibility

Knowledge of passage rate is a key point to a good estimation of digested fibre

Many studies show that passage rate and retention time are different for digestible and indigestible fraction

New mechanistic models are required to better define

digested fibre (nutritional concept) and ruminal retention time (dietetic concept)

Ruminal NDF passage rate

NDF nutritional and dietetic functions

Fraction

Role

Nutritional Dietetic

Rapidly digested (fast pool) +++ +

Slowly digested (slow pool) +/- ++

Non Digestible none +++

fibre digestion

More than 90% of the potentially digestible fibre from forages is degraded in the rumen (Huhtanen, 2007),

mainly because of:

Teeth effect on particles reduction

More cell surface exposed to bacterial degradation

High ruminal retention time

• ++ Larger and soft particles

• -- Heavier and smaller particles

Dietetic Roles of fibre

Feed intake Meal number and length

Feed consumption NDF: 0.8-1.4 % body weight (Mertens, 1997)

retained fibre “fill” effect (Mertens, 2010)

Chewing activity induction Two phases: eating and rumination

Saliva production – buffering effect

274 ml saliva/min. chewing (Beauchemin, 2008)

Rumen passage rate modulation

Limit dangerous pH drops (Allen, 2007)


Andrea Formigoni [email protected]



16


Chewing and rumination time

Cow chew during feed intake and during rumination, which usually happens after feeding and while resting

Chewing (55-60 times/min) stimulate saliva production and rumen motility

Saliva production = 274ml/min. chewing

Sodium Bicarbonate = 7 g/liter saliva

It is possible to record 6-8 daily rumination periods of 40-50 min each

Average S.D. Min. Max.

Wheat bran 2.63 0.27 2.36 2.90

Soy hulls 0.80 0.20 0.56 0.93

Beet pulp 0.20 0.14 0.10 0.37

Wheat midd 1.77 0.85 0.83 2.49

Alfalfa hay 2.26 0.34 1.59 2.62

Early cutting 2.07 0.37 1.59 2.52

Late cutting 2.39 0.26 1.90 2.62

Corn silage 3.32 0.83 1.55 5.18

Grass hay 2.70 0.55 1.77 3.93

Triticale hay 3.20 0.49 2.31 3.73

iNDF / lignin relationship in

different feeds (IVNDFd-240h)

(Palmonari & Canestrari, 2011)

Dynamic model for ruminal retained

NDF estimation

8 meals

4 meals

Feeds iNDF

Traditional equation to define iNDF is:

% lignin * 2.4 (CNCPS, CPM)

But iNDF is variable

Very long and expensive analysis

Faster, accurate and cheaper analytic systems to

determine iNDF are needed

NIR

Kd and iNDF effects on ruminal filling

Considering the high ability of the rumen to retain and

degrade the potentially digestible NDF, is very important to

well define the digestion rate (kD) and the indigestible fraction (iNDF)

Better definition of intake

Avoid rumen emptiness and prevent changes in eating behaviour

and metabolic disorders

Particles size (mm)

Pas

sag

e R

ate

(%/h

.) Indigestible fibre

Digestible fibre

Ruminal passage rate depends


17

Guidelines for peNDF requirement and

relation with ruminal pH

Minimum requirement of peNDF around 21 e 24% DM basis based on DM intake

Chewing time around 750 min/day

ruminal pH = 6.67 - 0.143 (1/%peNDF)

22.3% peNDF per rumen pH at 6.0

Zebeli (2008) proposed a peNDF requirement of more than 30% DM

Rumen pH = 5.59+0.0218*peNDF

Class cm Grass

hay

Grass

Silage

Corn

silage

Alfalfa

hay

Alfalfa

silage

Long 1.00

Coarse chop >5 0.95 0.95 0.90

Med-coarse 2.5-5 0.90 0.90 0.90 0.85

Medium chop 1.2-2.5 0.85 0.85 0.85 0.80

Med-fine chop 0.6-1.2 0.80 0.80

Fine chop <0.6 0.70 0.70

Ground >0.6 0.40 0.40

Fine ground <0.6 0.30 0.30

Mertens guidelines for feeds peNDF

(Mertens, 1997)

Chewing time estimation

Allen (1997) proposed a system based on fibre source (in forages) and particles size, clustered in three groups (Particle Lenght Index)

long (PLI1); > 0.3 cm (PLI2); < 0.3 cm (PLI3)

Two different equations to estimate chewing time and rumination

To these equations, cows eating more spend less time chewing, but in proportion longer rumination phase

Chewing time estimation

Mertens (1997) proposed a system based on feed particles size and NDF content in the diet

peNDF = physically effective fibre diet fraction > 1.18 mm x % NDF

Ro-Tap: gold standard

chewing: 150 min/kg peNDF Cows can chew for at least 1000 min/day

fibre intake limit

Chewing time

It is well known that insufficient time spent chewing can led to

metabolic concerns

Rumen acidosis (Nocek, 1997)

Decrease in Milk fat

Decrease in fibre digestion

Allen (1997) reported that chewing time cannot completely

explain rumen pH; it depends also on the relationship between

VFA production and absorption

Rumination goals

Feed transfer

To the mouth, to reduce particles size

From reticulum to the rumen, to retain fibre

From the rumen to omasum and abomasum

Allow the best fermentation process possible

Better distribution of feedstuff and bacteria in the rumen

pH maintenance in the whole rumen


18


Straw and hay usually not enough chopped Cows choose small particles against coarse (lack in peNDF intake)

Water addition is useful when it reaches 40% of the DM

fermentation problems in the feed bunk mainly in summer

Without water addition, forage length must be < 20-30 mm to avoid the ability of cows to choose

Finely chopped rations – lack in peNDF and behaviour changes

Farm crew attention and mixer “feature” are also key

points

TMR and forage structure TMR related concerns

Nordic Feed Evaluation System for

the structure of the ration (2007)

Each feed in the ration can influence intake and rumination time, depending on NDF – iNDF content, particles size

Eating Time Index (EI)

EI=4 min/kg/DM (fixed) x particles size <6mm

Rumination Time Index (RI)

RI=0 min/kg/DM x particles size < 2 mm

EI + RI = Chewing Time Index (CI)

Nordic Feed Evaluation System for

the structure of the ration

Alfalfa : 50-75 min/kg/DM

Grass : 65-100 min/kg/DM

Corn Silage: 50-75 min/kg/DM

Straw : 95-115 min/kg/DM

Guidelines: 32 min/kg/DMI

Es. DMI = 24kg/d = 768 min.

System PSPS

as fed

PSPS

d.m. RO-TAP Z-BOX

Observations 38 38 38 38

pef % NDF 68.9 62.4 55.1 48.72

peNDF % ration 22,98 20,83 18,37 16,27

(Dip.S.Med.Vet. 2009)

Relationship between different systems

on the same dry TMR At – the – farm peNDF evaluation

issue

Useful methods to focus daily on the ration structure and

homogeneity

It is important to relate these data with the Ro-Tap to

validate them and train farm crew

A right NDF evaluation of the diet, as for each sieve –

residue, should be required

19

Studies on chewing activity

Farms Time after unloading

Chop length H2O n° 0 8 24

Short No 4 3,12 3,77 12,28

Short Yes 3 2,23 5,26 9,03

Average No 5 7,23 6,43 12,52

Average Yes 10 6,46 7,69 23,00

Long No 1 13,82 14,39 25,40

Long Yes 15 14,83 B 17,56 B 39,38 A

A, B 0,01;

(Mordenti e Fustini, 2009)

Forage length (> 20 mm) changes in

feed bunk during the day

Total Chewing Time with different

forages

Forages Intake

min/d.

Rumination

min/d.

Total

min/d.

Grass “short” 282 410 692

Grass “long” 352 384 737

Alfalfa “high digestibilty” 236 308 544

Alfalfa “low digestibilty” 262 359 620

Straw “short” 404 352 756

(Dip.S.Med.Vet, 2009)

DIET COMPOSITION

Grass

Hay Straw

Grass hay Kg./cow/d 15.0 9.3

Straw Kg./cow/d - 3.0

Corn Flour Kg./cow/d 6.5 9.5

Soybean meal ( 44% P.G.) Kg./cow/d 2.8 2.0

Aminoplus Kg./cow/d 1.6 2.1

Molasses Kg./cow/d 1.0 1.0

Mineral Kg./cow/d 0.4 0.4

Forages (% DM) 55 45

Effects of different CHO sources in

rations

Grass hay Straw

Avg S.D. Avg S.D. P

Milk kg/cow/d 28,00 ± 5,65 28,90 ± 5,95 NS

Fat % 3,40 ± 0,75 3,22 ± 0,73

NS

Protein % 3,37 ± 0,34 3,48 ± 0,35

< 0,05

Lactose % 4,76 ± 0,36 4,87 ± 0,24

< 0,05

Effects of different CHO sources on

milk production and composition


Feed intake

Grass Hay Straw

Avg. S.D. Avg. S.D. P

Water liters/cow/d 147,07 ± 9,77 147,53 ± 15,00 NS

DM Kg/cow/d 24,64 ± 1,25 24,36 ± 2,04 NS

NDF Kg/cow/d 10,80 ± 0,55 10,10 ± 0,85 NS

starch Kg/cow/d 3,80 ± 0,19 5,46 ± 0,46 <0,01

peNDF Kg/cow/d 5,29 ± 0,27 3,78 ± 0,32 NS


20


Physiological condition, production and

rumination time

Physiological

condition

cows, n. rumination, min/day

Lactation 79 424±73

Dry 17 518±72

Avg. production cows, n. rumination, min/day

40 kg 4 511±60

35 kg 8 470±80

30 kg 14 436±57

25 kg 10 447±77

20 kg 15 428±69

20 kg 8 406±37

R=0,93

Rumination time : RAct vs IGER

Suggestions

Dietetic = Straw is more effective than predicted just with

structural composition (peNDF)

Dissimilar NDF distribution

Rumen Milieu not influenced by starch content of diet

RuminAct vs IGER Behaviour Recorder

peNDF

Eating

Min /Kg peNDF 59,60

±10,04 98,92

±14,96 <0,01

Ruminating

Min /Kg peNDF 82,45

±11,69 115,25

±23,00 <0,05

Total

Min /Kg peNDF 142,05 ± 14,31 214,17 ± 28,18 <0,01

Grass

Hay Straw

Avg S.D, Avg S.D.

Time

Eating min/d 316,00

±57,27 373,40

±63,93 NS

Ruminating

min/d 435,80

±61,96 430,20

±51,49

NS

Total

min/d 751,80

±81,01 803,60

±62,07

NS

N° meal 12,00

±0,82 12,00

±1,73

NS

Chewing and Ruminating

Grass Hay Straw

Avg S.D. Avg S.D. P

pH 6,38 0,15 6,50 0,19 NS

acetic % mmol 64,72 2,26 64,49 2,12 NS

propionic % mmol 19,08 2,44 20,04 4,04 NS

butyric % mmol 13,6 1,73 12,87 2,08 NS


rumen pH and VFA

21

Thanks !!

…to

Alberto Palmonari

Mattia Fustini

Giorgia Canestrari

Beatrice Zoratti

Attilio Mordenti

Nicola Panciroli

Nico Brogna

Andrea Panciroli

Conclusions

Evaluation of rumination and chewing time can help farmer and nutritionist improving formulation accuracy

Physical structure evaluation with sieves in field is important, but not sufficient

New methods available, once validated, could be more efficient and useful

peNDF intake and rumination time

Ru

min

ati

on

(m

in/d

)

peNDF intake (kg)

Among forages, straw is the best chewing promoter, and could represent a good solution to meet peNDF requirements

We do need a new model which describes chewing activity, rumination and ruminal retention time in order to define NDF filling and passage dynamics, and how these rates can affect intake, meal number and intake patterns

Conclusions


Fiber Degradation Kinetics and the Factors that Affect It

David R. MertensMertens Innovation & Research LLC

Madison, WI

24

Fibre degradation (and kinetics) and the factors that affect it

David Mertens

Mertens Innovation & Research LLC, Belleville WI 53508 USA

[email protected]

Fibre is an important measurement for feed evaluation because it distinguishes between the easily digested non-fibre fraction and the slowly and incompletely digested fibre fraction. Neutral detergent fibre is the best routine method for measuring the total dietary fibre in feeds, which can be used in summative equations to estimate digestibility. Because fibre digestion is slow, ruminants, such as cows and sheep have evolved a digestive system that is designed to slow the passage of fibre through the animal. Ruminants swallow larger particles, and retain them in the rumen until they are reduced in size by rumination to allow passage. While fibre is retained in the rumen, a diverse population of bacteria is responsible for fibre degradation. Digestion of fibre is the result of the competition between rates of passage and degradation. Thus, understanding the dynamic processes of digestion and passage, and the factors affecting them, are the keys to improving forage intake and utilization.

Digestion curves appear to have three distinct phases. During the initial lag phase, fibre becomes hydrated and bacteria penetrate plant cells and attach to the fibrous cell walls. During the rate phase, fibre is degraded at a constant fractional rate that varies from 0.02 to 0.16/h. The rate of digestion is determined by unknown factors that appear to be related to plant maturity. However, in the anaerobic environment of the rumen, fibre digestion is incomplete. This creates the last phase of digestion, which is characterized by an asymptote or plateau of digestion that is less than 100%. The indigestible fibre in forages is related to lignin concentration in the fibre. Not only is lignin itself indigestible, but it also inhibits the digestion of some of the cellulose and hemicellulose in fibre. Indigestible fibre is 2.5 to 3.5 times lignin content of fibre. Reducing lignin and decreasing the maturity of forages will result in the most rapid and complete degradation of fibre. Dietary factors such as starch can also affect fibre digestion by direct effects on the microbial population or indirect effects associated with low ruminal pH. It also appears that individual cows have unique populations of ruminal microbes that may affect fibre digestion. Rate of passage affects fibre digestion by affecting the time fibre is retained in the rumen for fermentation. Passage is primarily a function of fibre particle size and animal feed intake. Smaller particles pass out of the rumen more quickly and we observed that finely chopped or ground forages typically have lower fibre digestibility. Perhaps the greatest impact on passage rate is the level of feed intake. Dairy cows have high nutrient demands, which results in high levels of feed intake. As intake increases rate of passage also has to increase. Lower retention times associated with faster rates of passage result in reduced fibre digestion. To optimize fibre digestion, we need to minimize the indigestible fibre fraction, maximize rate of fibre digestion, and maintain a ruminal environment that maximizes the population of fibre digesting bacteria. We also need to manage diet composition and particle size so that we optimize the intake and digestion of fibre.


25





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h



on fibre particles size and digestibility •

•

© micro.magnet.fsu.edu/cells/plantcell.html

Fiber particles are

hollow – rigid plant

cell wall occupies

more space than its

mass indicates

Van Soest (1994)

hotel theory for the

filling effect of fiber

Component Corn

Grain

Grass

Silage

Cereal

Silage

Corn

Silage

Alfalfa

Silage

aNDF, % of DM 9.0 50.0 55.0 45.0 40.0

Fractional NDFD 0.50 0.64 0.58 0.58 0.46

Digestible NDF, % of DM 4.5 32.1 31.6 26.2 18.6

NDS, % of DM 91.0 50.0 45.0 55.0 60.0

Digestible NDS, % of DM 89.2 49.0 44.1 53.9 58.8

True DMD 93.7 81.1 75.7 80.1 77.4

Endogenous DM loss -12.9 -12.9 -12.9 -12.9 -12.9

Apparent DMD1X 80.8 68.2 62.8 67.2 64.5

•

–

–

•

•

•

•

•–

–

•

•

•

–

–

–

•

•

•

–


26





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





•

•

•

•

Mathematical models are needed

to use digestion kinetics

Models allow the effects of

changes in rates of digestion and

passage to be determined

•

–

–

–

•

–

–

–

•

–

–

–

–

•

–

Akin (1979) J. Animal Sci 48:701

–

–

–

•

–

–

– Rumination reduces

particle size and digestion

increases density

– After rumination, dense

small particles sink into

the liquid and pass out

27





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h



on fibre particles size and digestibility •

•

•

•

–

–

•

•

–

•

•

–•

•

•

•–

–

•

–

–

NDF Intake pdNDF

iNDF iNDF

udNDF

dNDF rd

ri

kd

kp

kp uNDF

•

–

–

–

Indigestible NDF

Potentially Digestible NDF

and Rate of Digestion

Lag phase

•

•

•


28





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Smith et al., 1972 J Dairy Sci 55:1140

Forage

iNDF

(% DM)

iNDF

(% NDF)

Lignin

(% DM)

iNDF/

Lignin

Average legume 20.0 48.8 9.6 2.08

Average grass 19.0 31.3 6.2 3.06

Immature average 10.6 27.6 4.6 2.30

Mature average 28.4 52.6 11.2 2.54

iNDF was measured as uNDF after 72 hours of fermentation

Legumes have more lignin and more iNDF per unit of NDF

Mature forages have more iNDF than immature forages

Rate of digestion phase

•

–

–

–

NDF Intake pdNDF

iNDF iNDF

udNDF

dNDF rd

ri

kd

kp

kp uNDF

Forage

Rate

(h-1)

NDF

(%)

Average legume 0.116 39.5

Average grass 0.096 54.1

Immature average 0.152 38.8

Mature average 0.060 54.8

Legumes typically have faster rates of digestion than grasses

Immature forages have faster rates than mature forages

•

–

•–

–

–

29





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





ec = encapsulated cocci ib = irregular bacilli

Attachment of Bacteria to Fiber Akin (1980)

Fibrolytic bacteria must be attached or closely associated with fiber

•

•–

–

–

–

Grass

Forage

Lag

(h)

Rate

(h-1)

iNDF

(% DM)

NDF

(% DM)

13/10 C regimen 2.7 0.041 8.8 38.0

20/18 C regimen 3.6 0.037 11.6 42.7

30/27 C regimen 2.8 0.033 16.2 50.1

Warmer growth temperatures increase maturity and iNDF

and reduce rate of digestion

Lag phase

•

–

–

–

•

–

Grass stage

Lag

(h)

Rate

(h-1)

iNDF

(% DM)

NDF

(% DM)

Flag leaf emergence 6.5 0.056 20.4 67.0

14 d after flag leaf 6.0 0.050 29.0 70.6

21 d after flag leaf 6.5 0.044 33.4 72.5

Maturity decreases rate and increases iNDF

(Long lag times suggest an effect of the in vitro technique)

30





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





pH No Starch 45% Starch

Lag

(h)

Rate

(/h)

iNDF

%NDF

Lag

(h)

Rate

(/h)

iNDF

%NDF

5.8 7.36a 0.056a 49.6 7.04a 0.049a 60.7

6.2 4.94b 0.085b 48.8 3.12b 0.068b 59.8

6.8 4.35b 0.086b 48.2 2.70b 0.076b 62.2

Low pH increased lag and decreased rate of NDF digestion

Adding starch decreased lag and rate and increased iNDF

•

–

•

–

•

–

•

–

•

–

•

–

•

•

–

–

•

kp

Digestible

Fiber Fiber Intake

Fiber Digested

Fiber Passed

•

–

–

•

–

–

•

•

•

–

rate of Digestibility Digestibility

digestion passage depression

0.05 0.04 0.56

0.05 0.05 0.50 0.90

0.20 0.04 0.83

0.20 0.05 0.80 0.96

0.20 0.08 0.71

0.20 0.10 0.67 0.93

31





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




Rate of pdNDF (h-1)

Response .04 .05 .06 .07

OMD .663 .692 .712 .727

NDFD .615 .663 .697 .720

pdNDFD .739 .795 .836 .865

NDF pool (kg) 7.91 7.20 6.65 6.25

Rate of pdNDF digestion is the 2nd most important characteristic

affecting digestibility and ruminal fill (Huhtanen, 2006)

iNDF (% of ration DM)

Response 6.0 10.0 14.0

OMD .733 .700 .667

NDFD .727 .673 .620

pdNDFD .808 .808 .808

NDF pool (kg) 6.76 7.47 8.18

iNDF is the most important forage characteristic affecting

digestibility and ruminal fill (Huhtanen, 2006)

Intake Passed

Non-escapable

potentially

digestible

Escapable

potentially

digestible

Non-escapable

indigestible

Escapable

indigestible

Absorbed

Rumen

fd

fi

kd kd

kr

kr

ke

ke

Two-Pool Rumen Passage Model

of Allen and Mertens (1988)

Related to Typical Single-Pool Models

kp

•

•

•

•

•

–

–

•

–

–

–

–

•–

–

•

•

•

•

•

•

–


32





Fraction

Role















•

•

•

•

•

Ruminal retention time (h)

Response 30 35 40 45 50

OMD .657 .676 .691 .703 .713

NDFD .608 .637 .659 .678 .693

pdNDFD .730 .764 .791 .814 .832

NDF pool (kg) 6.01 6.59 7.11 7.59 8.03

Rate of passage or ruminal retention time also has a

large impact on digestibility and ruminal fill

Questions?

Fibre degrading microbiota in the ruminant gut and effect of

active dry yeast on fibrolytic populations and activities

Frédérique Chaucheyras-Durand INRA unit of Microbiology,

Lallemand Animal Nutrition, France

34

Fibre degrading microbiota in the ruminant gut and effect of active dry

yeast on fibrolytic populations and activities

Frédérique Chaucheyras-Durand

Lallemand Animal Nutrition and INRA Unit of Microbiology, Research Centre of Clermont-Ferrand/Theix, 63122

Saint Genès Champanelle, France

[email protected]

Ruminant animals represent a key component of agricultural systems thanks to their ability to convert fibrous plant materials into milk, meat, wool and hides. Most of the digestion of plant material is performed in the rumen by a complex symbiotic microbiota, composed of anaerobic bacteria, fungi and ciliate protozoa. The ruminal microbial populations colonise, hydrolyze and ferment forage cell wall polysaccharides and thereby provide volatile fatty acids and proteins which represent essential energy and nitrogen sources for the host animal. Efficacy of fibre digestion in the rumen relies on the nature of the plant material. In addition, the rate and extent to which fibre is degraded depends on physiological characteristics of fibre degrading microbes, microbial interactions or physico-chemical conditions of the ruminal environment.

In vitro and in vivo studies have demonstrated that a specific strain of Saccharomyces cerevisiae increases fibre degradation of fibrous materials, by promoting substrate colonisation by rumen bacteria and fungi. In addition, abundance of cellulolytic bacterial species, and polysaccharide and glycoside hydrolase activities of fibrolytic communities have been maintained at high levels in the rumen of sheep fed with high concentrate diets, which represent a risk for ruminal acidosis. The mechanisms underlying these effects are linked to the yeast metabolic activities, such as the capacity of sugar fermentation and oxygen scavenging, and also to nutrient and vitamin supply to the fibrolytic populations within their microhabitat. Active dry yeast can positively affect fibre digestion in the rumen, which should lead to increased feed efficiency and optimised animal health.

Key words : fibrolytic microbiota, rumen, active dry yeast, feed efficiency.


35





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




Fibre degrading microbiota in the ruminant gut and effect of active dry yeast on fibrolytic populations and activities

Lactate Succinate

Formiate

H2 CO

2

CO2

36





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





37





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




0 7 14 2c 60

Strictly Anaerobic bacteria

Cellulolytic bacteria Archaea methanogens

Fibrolytic fungi

Ciliate protozoa

to Oba and Allen (1999)

Fibre degrading microbiota in the ruminant gut and effect of active dry yeast on fibrolytic populations and activities

38





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Non-dietary FactorsInfluencing Rumen Function and Dairy Cow Performance

Alex Bach IRTA

INVESTIGATION Y TECHNOLOGIA AGROALIMENTARIAS

40

Non-dietary factors influencing rumen function and dairy cow

performance

Alex Bach

Institut de Recerca i Tecnologia Agroalimentàries (IRTA)

Unitat de Remugants, Barcelona, Spain.

[email protected]

Nutritional models calculate nutrient requirements under the assumption that animals have ad libitum access to feed and water and are kept under dry and clean conditions. Some nutritional models incorporate correcting factors to the energy requirements for maintenance based on the environment surrounding the animals. However, herd performance is affected by several factors including nutrition, reproduction, genetics, environment, and management. Among these factors, the impact of management and environment where cows are housed is the least known. Some of these management and environmental factors modify herd performance by causing a reduction on animal well-being and a subsequent increase in stress. In addition, these factors may directly influence eating and lying behaviour of cows potentially affecting rumen function, digestion, and feed efficiency.


41





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




Non-dietary Factors Influencing Rumen Function and Dairy Cow Performance

The Dataset

CP 16.1% NDF 35.8% NFC 40.4% EE 3.3% NEl 1.62 Mcal/

Cooperative La Pirenaica

Common TMR

Delivered daily

Similar genetic background

Common veterinary services (breeding, etc...)

The Dataset

Some models incorporate correcting factors to energy requirements for maintenance based on the environment surrounding the animals.

NRC (2001) increases by a factor of 10% the energy requirements for maintenance when animals are housed in free stalls or bedded packs as opposed to tie-stalls.

The Cornell Net Carbohydrate and Protein System (CNCPS; Fox et al., 1992) was revised to incorporate equations that would modify nutrient requirements based on ambient temperature, humidity, and housing conditions (Fox and Tylutki, 1998).

Introduction

Herd performance is affected by:

Nutrition

Reproduction

Genetics

Environment

Management

Introduction

Nutritional models calculate nutrient requirements under the assumption that animals have ad libitum access to feed and water and are kept under dry and clean conditions.

Furthermore, they are based on individual animal specifications, although they are commonly applied to groups of several animals.

Introduction Non-dietary Factors

Influencing Rumen Function and

Dairy Cow Performance

Alex Bach

42





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Heifers

Bach, 2011

Age

at fi

rst c

alvi

ng, d

P < 0.05

Average breeding age: 16.9 months

Average AFC 27.7 months

Heifers

Bach et al., 2008

Calves

Moallem et al., 2010

Milk

yie

ld, k

g/d

Calves

Bach and Ahedo, 2008

The amount of TMR that was delivered daily to each farm during the 8-mo period was recorded and averaged within herd and multiplied by the average DM content (51%) of the TMR

The number of lactating cows present daily in each herd was crossed with TMR delivered to estimate DMI.

The Dataset The Dataset

47 herds within a radius of 59 km

3,129 lactating cows

Herd size: 68 cows (23 to 232)

Starting 8 mo before the time the survey was performed:

Daily milk production

Milk quality records every 2 wk

Survey performed in 60 d.

43





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




Lactating Cows Some producers pushed the feed up to 4 times per day, whereas others just pushed feed once daily.

There was no relationship (P = 0.67) between the number of daily feed push-ups and milk yield.

DeVries et al., 2003

Lactating Cows

Feed bunk management affects milk production.

Bach et al., 2008

DIM

Lactating Cows Lactating Cows

The average feed bunk space was 69 cm/animal (with less than 20% of herds with < 50 cm of feed bunk per animal).

No relationship was found between feed bunk space and milk yield.

Grant and Albright (2001) concluded that the minimum critical bunk space for dairy cattle was 20 cm/head.

Despite all herds fed the same ration, there were important differences in milk yield among herds.

Lactating Cows

Milk yield, kg/cow/d

Dry Cows C

ows

culle

d fo

r la

men

ess,

% o

f tot

al c

ullin

gs P = 0.12


44





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h






Bach et al., 2007

Knonoff et al., 2003


Lactating Cows

Huzzey et al., 2006 Nordlund et al., 2006

Lactating Cows

45





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h




Guasch and Bach, 2010

•Diagonal Distance and Lying Times

Lactating Cows •When primiparous and multiparous animals are

commingled, resting time is more reduced for heifers than for older cows (Matzke, 2003).

Lactating Cows

Item Coefficient SE P-value

a 28.4 4.4 <0.001

Age at first calving, months -0.26 0.1 0.05

Orts (Yes=1, no=0) 0.64 0.3 0.09

Cubicles/Cow 5.91 1.4 <0.001

Pushing TMR (Yes=1, No=0) 1.29 0.6 0.05

Bach et al., 2008

Lactating Cows

DeVries et al., 2005

Lactating Cows

When the regression model considered the maintenance status of the stall, it accounted for about 38% of the variation observed in milk production (r = 0.62; P < 0.01)

In addition, a negative relationship (r = 0.39; P < 0.05) between the number of stalls per cow and the proportion of cows culled was found.


Bach et al., 2008


46





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h






•Diagonal Distance and Lying Times


Lyin

g, m

in/d


•Curb Height

Min

/d

Week relative to a pen change Week relative to a pen change

Lactating Cows


%


Lactating Cows

%


Herds that moved cows between pens in groups of several animals had a lower

incidence of lameness than those that moved cows individually.

Lactating Cows

Lactating Cows

Ste

ps/

h

Week relative to a pen change


47













Thank you

[email protected]

Take Home Messages

Variability is part of biology

Individual animal responses to nutrition are variable

At a herd level, variation is much greater

Main factors contributing to deviations in milk yield are (besides nutrition) include:

Growth rate during the first months of life

Age at first calving

Stall availability, maintenance, and design

Feed bunk management


Impact of rumen modifiers on ration formulation

Charles J. Sniff en, Ph.D. [email protected]

Fencrest, LLCHolderness, NH, USA

50


Charles J. Sniffen, Ph.D.

Fencrest, LLC

Holderness, NH, USA

[email protected]

Rumen modifiers can be identified as any compounds that when fed can have a positive impact on rumen fermentation. There has been, in recent years, a significant increase in the number of modifiers available that can alter rumen function. For some of these modifiers there has been excellent research that have demonstrated the mechanisms involved in the changes in rumen function. Unfortunately, there has not been rumen submodels developed for our nutrition models and platforms that adequately take advantage of this knowledge. The only attempt was an ionophore submodel developed within the CNCPS system. This was initially active for both the lactating and non lactating growing ruminant. Now it is restricted to the growing ruminant. The development of a submodel that can reflect the mechanistic effects of different rumen modifiers it will be possible to formulate rations that will reflect the responses from the different modifiers available. Examples of possible approaches that can be used to achieve this will be discussed with specific examples using research conducted with yeast and other modifiers. Examples will also be given to show how this will modify ration outcomes and the positive economic consequences.


51





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





CNCPS Based Models

The models are defining by chemical, invitro and enzymatic means

Specific protein, CHO and lipid components in feeds that are unique in their characteristics in the rumen and intestine.

These are defined as pools

The extent of ruminal digestion of these pools is defined by rates of digestion and rates of passage – Bn*Kd/(Kd + Kp)

6

Aggregated NRC 2001 Microbial Flow Model

5

Introduction

The objective of this discussion today is to discuss how to enhance our current models to improve prediction of rumen modifiers

Need to first understand a current rumen model

We will then explore how we might develop a submodel to better reflect the mode of action of a modifier

3

NRC 2001 microbial model

Constant efficiency

Based on whole tract OM digestibility

Insensitive to changes in rumen

conditions

4

Introduction

It is now recognized by many scientists and field nutritionists that our ability to predict microbial growth and efficiency can be improved.

Historically we have used empirical models to predict microbial flow to the SI

There are now attempts to develop more mechanistic models

2


Charles J. Sniffen, Ph.D.

Fencrest, LLC

Holderness, NH, USA

[email protected]

1

52





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Microbial growth

The bacteria have a theoretical maximum yield of 0.5g cells/g CHO fermented.

The figure shows 0.4g cell due to the inclusion of protozoal predation

Bacteria have a maintenance requirement

The NSC bacteria are stimulated by peptides mainly from the B1 & B2 protein pools

8

Russell mechanistic microbial model

7

Prediction of microbial flow from Beef & Dairy Data

9

Increasing the sensitivity of the microbial model

With CPM, the CHO model was expanded increasing the sensitivity of

the microbial submodel

10

12

Increasing the sensitivity of the microbial submodel

With CNCPS 6.1

Expanded the CHO submodel more

Introduced liquid turnover

Changed the soluble protein pools

Going forward

Will improve the recycled N prediction

Will develop a protozoal submodel

Will develop a Rumen VFA model

11

53





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h



on fibre particles size and digestibility NFC Bacteria

The bacteria grow at a very fast rate and without control can dominate the ecology & drop rumen pH

With control they produce the high quality protein that the cow needs

a significant part of the energy she needs

This is good

18

NFC Bacteria

This is a broad category

The substrate is a mixture of starch, sugars and soluble fiber

The bacteria, on the whole, are more tolerant of lower rumen pH

They grow well with peptides and NH3

The starch bacteria are stimulated by peptide

They are more readily predated by protozoa

17

Fiber Bacteria

Optimizing fiber digestion in dairy cattle is often difficult

It starts with the substrate

We need a fiber pool that has a high potential digestibility

This fiber pool has to be both digestible and have enough structure to provide chewing, saliva flow and rumen pH control

15

Fiber Bacteria

These bacteria need access to the inner part of the fiber matrix

The fungi play a role here

They need NH3 and isoacids

Isoacids come from the breakdown of

peptides by proteolytic bacteria

They need a stable rumen mat

16

Rumen Ecology Imbalances

The balances can be disturbed by many factors:

Inadequate effective fiber to produce adequate

buffering

High fermentable starch levels in the ration

Low rumen available peptides and NH3

Excessive rumen degraded protein containing peptides with Histidine

Uneven feed consumption throughout the day

14

Microbial submodel

13

Protozoa

New Prot

Fiber Bacteria

New bacteria

NFC Bacteria

New bacteria

Fungi

New Fungi Predation

Fiber, NH3

NH3, peptides, starch, soluble fiber, Lactic. sugars

Predation

Net Microbial

Flow to intestine

VFA


54





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Microbial Growth

CHO Digested, g/d

Microbial N, g/kg CHO digested

Low peptide Low pH

Good env., feed additives

24

The Pirt Equation – the basis for modification

22

Fungi

Fungi are not well understood

It is strongly suggested that they open the fiber matrix allowing fiber bacteria

access and colonization

The do not deal with low pH well

They are stimulated by sugars

We need to know more

20

Protozoa

They are 45% of the microbial mass

The contribute little to the protein delivered to the SI.

They can help maintain rumen pH

They are vociferous predators

Reducing bacterial N flow to the SI

They contribute to the recycled N pool

19

Dynamics in microbial sub model

Russell (Cornell) demonstrated that microbial growth was a combination of meeting a requirement for maintenance and then for growth

He also developed the concept of uncoupled

fermentation when there was low rumen pH or inadequate N and other precursors the fermentation becomes uncoupled, leading to energy spilling

21

Microbial Yield in CNCPS

23

55





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h



on fibre particles size and digestibility Rumen Modifiers

Rumen Modifier = feed additives which alter ruminal fermentation, microbial growth with positive impact on feed efficiency

Ionophores

Live Yeasts

Yeast fermentation products

Fermentation products

Essential oils

Enzymes

30

Uncoupled Fermentation

29

Microbes New Microbes

VFA

Fermentation heat increment or energy spilling

NFC Bacteria

Optimized when the peptide supply is 14% of fermentable NFC.

Greatest microbial yield is from the NFC bacteria.

27

Ruminal microbial growth

Maintenance

20 to 40% of ATP

Energy spilling

Up to 18% of ATP

Net yield to SI is a combination of above and

Predation by protozoa and death

25

Coupled Fermentation

28

Microbes New Microbes

VFA

Fermentation heat increment

Or energy spilling – up to 18%

Fiber Bacteria losses in CNCPS

Rumen pH When rumen pH goes below 6.4 there is a reduction in max yield and increase in maintenance

Below 6.2 the changes are rapid peNDF is the key driving factor

Ammonia requirement Bacterial growth limited to the ammonia available

Need isoacid submodel

26


56





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h





Rumen Additives

We have been using different rumen products for a long time.

We have measured response in terms of more milk, better components, improved feed efficiency

Only recently we have been looking closer at these additives in terms of the impact in the rumen

32

We can Modify Rumen Parameters

If we determine that a management practice or a feed additive enhances microbial flow we can potentially modify

Rumen pH

Maintenance – reduction of energy spilling Increase the coupled fermentation

Protozoal predation

We would like this done automatically in the model and a submodel could be developed to do this

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Yeast as a Modifier

Dried yeast and fermentation products and live yeast

We have known for a long time that yeast has a positive effect on rumen function

There have been many studies now that are showing the positive effects on microbial yield and ruminal digestion

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Live Yeast

How do we modify the CNCPS model to reflect the impact of Lallemand SC? Need to know the mechanisms then we can potentially develop a submodel for the product Potential Control points in rumen submodel

Lactate reduction – improve rumen pH Reduce proteolysis Increase microbial yield – reduce maintenance

34

Carbohydrates Ammonia + Peptides +

VFA

Microbial Growth

Uncoupled Fermentation

VFA/Microbe Ratio VFA/Microbe Ratio

Acidosis

Lactic acid and Acidosis

Live Yeast :

…a higher degree of coupling and higher fermentation efficiency ... with the right balance of

degradable protein fraction and fermentable carbohydrate fraction

(Sniffen, 2003)

: move to slide 35 Modes of action of Levucell SC, F. Chaucheyras-Durand

Interactions with ruminal microbial species (establishment, growth, activities)

lactate

concentration risk of acidosis

fibre

degradation microbial

proteins

Competition

for sugar

utilization

Growth factors

supply

Oxygen

scavenging

pH stabilization

+ - +

+ +

35

57





Fraction

Role



















fibre digestion


mainly because of:






Size (mm)

>1.0 0.5-1.0 0.2-0.5 0.04- 0.2

pdNDF 0.07 1.10 1.64 1.65

iNDF 0.23 3.70 4.30 4.30

NDF-kd = 6.67%/h



on fibre particles size and digestibility Biochlor & Fermenten

Relatively new products on the market

Research has shown that there is

Increased microbial yield

Increased microbial efficiency

A improved coupled fermentation

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Additive submodels

We need more research to show the ruminal changes for the additives coming on the market so that we can alter rumen function

When I say ruminal changes I mean changes in specific bacterial niches, protozoa, and fungi.

This information will allow us to develop improved rumen modifiers

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Essential Oils

There have been several studies that point to the fact that the oils can

increase protein bypass

Modify fermentation pattern

Increase N efficiency

Decrease starch digestion

Need VFA submodel

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Monensin : Can optimize feed

efficiency

C. J. VAN NEVEL AND D. I. DEMEYER

Effect of Monensin on Rumen Metabolism In Vitro Applied and Environmental Microbiology, Sept. 1977, p. 251-257

Demonstrated the following: Decreased methane

Inhibition of H2 production

Increased propionate

Decreased Microbial growth – specifically Gm+ organisms – Russell

No change in CHO degradation – decreased miccrobial efficiency

Decreased degradation of protein and reduced NH3

Need VFA and protozoal submodels

CNCPS Rumen submodel for yeast

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SC bacteria NFC bacteria

SC bacteria NFC bacteria

Energy spilling -

Reduce maintenance

Yeast SC

Lactic

acid

Microbial Yield

-

- -

+ +

+ +

NDFd+

Increase Rumen pH +

Prot Deg +

Live Yeast :… Can optimize feed efficiency

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• 14 trials with 1 600 dairy cows, • One dose and One strain of Live Yeast :

•1010 CFU/dairy cow/d •CNCM I 1077

• increased milk production by 1 kg of milk/d

• without altering feed intake,

Significant Improvement in feed efficiency (1.70 vs. 1.75 ; P< 0.01 )

Greater effect for cows producing (:38 kg) milk/d (1.78 vs. 1.85 ; P<0.05).

Multiple study analysis of the effect of Levucell SC on milk and milk component production and feed efficiency

M.B. de Ondarza, C.J. Sniffen – ADSA 2009

*

P<0. 001

*

P<0. 05 0

* P<0.05

* * P<0.001


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Fraction

Role















Additive submodels

Need to also be able to develop submodels for metabolism

Changes in energetic efficiency

Partial ƒ ruminal and metabolic efficiencies

Changes in substrate from ruminal fermentation and intestinal digestion

Changes in AA efficiency

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Summary

We are now, belatedly, beginning to explore the opportunities of enhancing

rumen function again

We do need more well trained rumen microbiologists

The opportunities are exciting for the future

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Summary

Need a better understanding of the nutrients needed to optimize rumen function

Need a better understanding of the interactions of the different microbial niches in the rumen

Then development of new rumen modifiers can be achieved that are based on good science

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