9 de agosto 19:00

Dr. Charlie Sniffen, PhD, Fencrest, LLC

Otimização de dietas para vacas em transição e lactação em

função de carboidratos fermentáveis

Discussão e comentários – Prof. Marcos Neves Pereira – UFLA

Tradução simultânea – Marcelo Hentz Ramos – 3rlab

Webinar – O Nutricionista Onde os grandes nomes da nutrição de vacas leiteiras se encontram!

Mais informações: www.3rlab.com.br

Introduction

We have historically formulated rations based on NEL and CP.

We are now formulating rations based on ME and MP.

We have also been formulating for RDP & RUP

Of course we have been formulating for

The amount of fiber or forage, minerals and vitamins.

2

Our Nutrition programs have become sophisticated

We are now using the CNCPS model 6.5.5 which is based on rumen dynamics

The feed analyses needed for this model is very extensive compared to the old days.

We now formulate for amino acids, starch, fatty acids and of course minerals and vitamins

3

The discussion today is formulating for carbohydrates

We have routinely formulated for NDF, peNDF, starch and sugar

With the analyses that we now have available, we are now formulating for fermentable carbohydrate fractions

This area is complicated and still controversial because

of assays and requirements

4

Classification of Carbohydrates

Total Carbohydrates in Cow Diet

Plant Cell Contents Plant Cell Wall

Organic

Acids Sugars Starches Fructans Pectins

&

B-Glucans

Hemicellulose Cellulose

ADF Soluble Fiber

NDF NSC (Soluble Carbohydrates)

Insoluble Fiber

Differences in Fermentation pH from In Vitro Fermentation of Carbohydrates Source: M.B. Hall and C Herejk, J. Dairy Science Nov. 2001

6.6

6.7

6.8

6.9

7

7.1

7.2

Fermentation pH

NDF ONLY NDF+

Sucrose

NDF +

Pectin

NDF+ Corn

Starch

Carbohydrate Type

a

b b c

Pectin = Citrus Pectin, Corn Starch was a fine powder from Sigma Chemical

Differences in Fermentation Pattern from In Vitro Fermentation of Carbohydrates 60:40 Blends of NDF and NSC Source: M.B. Hall and C Herejk, J. Dairy Science Nov. 2001

-5

0

5

10

15

20

25

30

35

0 2 4 6 8 10 12 14 16 18 20 22 24 26Fermentation Hour

MCP, mg

NDF Only

NDF + Sucrose

NDF + Pectin

NDF + Starch

Pectin = Citrus Pectin, Corn Starch was a fine powder from Sigma Chemical

Shaver, 2004

Shaver, 2004

As more starchy feed is eaten, pH declines, and the balance of rumen

microflora and VFA changes, followed by acidosis

80

60

40

20

0 7.0 6.5 6.0 5.5 5.0 4.5

Lactic acid (10x more acidic

Than VFA)

Acetic acid Butyric acid Propionic acid

mmol/L Cellulolytic

Flora

Amylolytic

Flora

Lactobacilli

Sub acute acidosis Acidosis

forage grain

pH

Bach, 2005

Rapidly

fermentale carbohydrates

Adapted from Nocek 1997 Bach, 2005

Step-by-step microbial mechanisms of occurrence of acidosis in the rumen :

Rapidly

fermentable carbohydrates

Lactate

Lactate producing

bacteria (S. bovis)

pH

VFA

Bacterial growth rates

Detoxifying action of lactate-utilizing

bacteria (M.elsdenii, S.ruminantium)

Adapted from Nocek 1997 Bach, 2005

Step-by-step microbial mechanisms of occurrence of acidosis in the rumen :

Rapidly

fermentable carbohydrates

Lactate

Lactate producing

bacteria (S. bovis)

pH

VFA

Bacterial growth rates

Detoxifying action of lactate-utilizing

bacteria (M.elsdenii, S.ruminantium)

pH<5.5

Action of

lactate-utilizing bacteria

Enzymatic

activities

Growth rate of

several bacterial species

pH < 6

Subacute

acidosis

Adapted from Nocek 1997 Bach, 2005

Step-by-step microbial mechanisms of occurrence of acidosis in the rumen :

Rapidly

fermentable carbohydrates

D(-)

Lactate

S. bovis

D-lactate producers (Lactobacillus sp.)

pH

Acute acidosis

Lactate

Lactate producing

bacteria (S. bovis)

pH

VFA

Bacterial growth rates

Detoxifying action of lactate-utilizing

bacteria (M.elsdenii, S.ruminantium)

pH<5.5

Action of

lactate-utilizing bacteria

Enzymatic

activities

Growth rate of

several bacterial species

pH < 6

Subacute

acidosis

Adapted from Nocek 1997 Bach, 2005

Bach, 2005

Bach, 2005

Bach, 2005

Bach, 2005

Bach, 2005

Bach, 2005

Effects Infusion of Nutrients on Milk Yield and Composition1

Response (% of control)

Product of Digestion

Site of Absorption

Milk

(kg/d)

Fat

(%)

Protein

(%)

Lactose

(%)

Acetate Rumen +8 +9 -1 +2

Propionate Rumen -2 -8 +7 +1

Butyrate Rumen -5 +14 +2 +2

Glucose Sm. Intestine +6 -10 -1 +1

Amino Acids Sm. Intestine +7 -3 +6 +1

LCFA Sm. intestine +2 +13 ---- ----

1. Thomas and Martin (1988). Basal rations provided required energy and protein.

Variation in rumen pH among individual cows. Thirteen of the 16 cows experienced a pH drop below 5.8 for some portion of the day.

Beauchemin, 2003

Ruminal pH of dairy cows fed high moisture corn (HMC) vs cracked shelled corn (DC). The forage was coarsely chopped (CS) alfalfa silage (from Krause et al. 2002).

Using NDF Digestibility in Rations Programs

We have many labs doing NDF digestibility by in vitro methods There have been issues in standardization of

the in vitro procedures There have been NIR equations developed

with high predictability

The in vitro assays have measured 12h, 24h, 30h and 40h digestibilities

The 24 and 30h measurements have been the most commonly used

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The New Fiber System

In 6.1 and 6.5 An enhanced fiber digestibility based on measuring

NDFd at 30, 120 and 240 hours of in vitro digestibility 240 hr is the new estimate of the indigestible fiber (uNDF)

It is not constant and varies among forages and within forages This will replace lignin*2.4

A new model that predicts the digestion rate of one and two pools – in 6.1/6.5 it will be a one pool estimate

The new digestibility will be closer to the truth Will come closer to the forages we are feeding and what

the cows are telling you

26

Average distribution of fast and slow pool and indigestible fractions in the forages analyzed, averaged by forage group. Numbers within pools represent the respective average fractional rates (%/h)

0%

20%

40%

60%

80%

100%

pdNDF1

pdNDF2

iNDF1.6

2.4 1.6 0.7

2.4 7.3 8.7 9.4 3.9 13.0

uNDF

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A change in Forage NDF rate of passage with 6.5.5

The rate of passage was basically reduced by 50%

This resulted in a significant increase the amount of fiber digested in the rumen The result was an increase in

2 – 3 Mcal of ME 150 to 300g more MP from microbial protein

With optimization of rations a higher %forage in the ration and a potential of exceeding the rumen fill, reducing DMI

28

The New Fiber System In CNCPS 7.0

Same in vitro digestion and same model

There will be fast and slow pools

There will be revised predictions of passage rates for forages Based on the work going on now on particle size

This will result in the ability To better predict true performance from forages

Minimum fiber needed for rumination and maximum to predict rumen fill or when DMI decreases

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Comparisons on forage

With ration programs using 6.5 we would formulate 50 to 55% forage rations

With the new model (6.5.5) we can be formulating 55 to 70% forage rations We now need to consider uNDF30 and

uNDF240

This puts emphasis on providing enough NH3 to meet fiber bacteria’s needs as well as some AA’s and sugars

30

Starch

For typical rations being fed to dairy cows starch is the next major fermentable CHO source.

We historically formulate rations for just starch amount in the ration

With the availability of 7hr starch assay we have begun to formulate for Ferm Starch

31

Vitreousness & Starch Availability Shaver, 2002

Variation in Starch Degradability in Corn Silage

Frequency

1241 samples

New York Corn Silages 2006 to 2007 5,569 samples, 26 to 36% DM

Available Starch in Corn Silage (%Total Starch)

10

12

14

16

18

20

22

Augus

t

Septe

mbe

r

Octob

er

Nov

embe

r

Dec

embe

r

Janu

ary

Febru

ary

Mar

ch

April

May

June Ju

ly

Month

Differences in starch availability by year 2006 vs. 2007

Available Starch in Corn Silage

(% Total Starch) by Year

10

12

14

16

18

20

22

August September October November

2006

2007

Effects of dietary treatment on passage of starch from the rumen

Experiment Treatment Kp, %/h Rumen retention, hr

P value

Ying & Allen, 2005

HMC Dry gnd corn

7.1 16.3

14.1 6.15

0.0001

Vitreous Floury

16.0 7.5

6.25 13.3

0.001

Taylor & Allen, 2005

Vitreous Floury

21.2 16.2

4.72 6.17

.10

Allen et al 2008 Vitreous floury

25.7 16.0

3.89 6.25

0.001

36 Adapted from Allen, 2015

Starch Dynamics

Vitreous starch Floury starch

floury floury

Vitreous or Prolamin

Vitreous or Prolamin

High Degradability Low density Slow passage Easy grinding

Low Degradability High density Fast passage Hard grinding

Higher bushel wt. Lower bushel wt.

37

Starch Digestion Relationships

The lower the ruminal starch fermentation rate the more escapes

The residual starch is potentially less digested in the SI

The starch escapes to the hind gut

Some will be digested there

The rest escapes

Starch digestibility assays

The 7hr measurement was a start and has been good for ranking but not very sensitive for formulation purposes

Most labs currently have 2hr and 7hr assays or a soluble starch measurement

At this point the model can only handle one pool and one Kd.

39

Enzymatic Starch Degradation

0

10

20

30

40

50

60

70

80

90

0 5 10 15 20 25 30

Time Hours

% S

tarc

h D

eg

rad

ati

on

125 w hole

126 crimped

127 flaked

128 CM #6

129 CM #8

167 KSU CM

168 Exp Low

169 Exp High

Starch Digestion Concepts

Starch can be divided into two components

Fast starch – that starch that disappears in 2 hours by enzymatic assay

90 to 100 % will be digested in the rumen and 100% of this starch that escapes fermentation will be digested in the small intestine

Slow starch - that starch that does not digest in 2h and will have a slow digestion rate and the extent of digestion in the rumen and small intestine can be influenced by

Particle size, shape and density

Starch source and type (sorghum, corn, wheat)

Processing – steam flaking, steam rolling

Calculating Starch Kd’s – based on de Ondarza and Allen

42

Sugars

We used to assume in the earlier versions of the model that 100% of the sugars in feeds were digestible in the rumen

This has been changed with reintroduction

Liquid rate of passage

The Kd’s are in the 30 to 50 %/h range

No assays for rates

43

Soluble Fiber

Soluble fiber in our current model is still the residual (NFC – individual VFA – Starch – sugar)

We have other organic acids but there currently is not a commercial lab assay

There are assumed Kd’s and Kp’s

44

Requirements – what to balance for?

First Balance DMI

ME

MP

peNDF, Forage NDF

NFC

Peptide & NH3 RDP, %DM

Second Balance Fermentable NDF

Lignin

Fermentable Starch

Sugars

Soluble fiber

Fat & FA

Amino acids – Lys then Met and others?

Final Balance Minerals & Vitamins

Ration formulation

The best approach is to use least cost optimization for the fermentable CHO fractions

We can put Mins and Maxes for each of the fermentable CHO areas

This allows us to take into account the cost of providing the fermentable CHO’s from each feed

46

Using Optimization to Formulate Rations

Establish Mins and Maxes based on the environment

The concept – the models that we use assume the cows eat 24 times/day and that each meal is equal

We know when cows are comfortable they will eat 10 to 12 meals per day.

If we think there will be uneven eating then we will need to adjust rations accordingly

Using Optimization to Formulate Rations

Feed mins and maxes

Establish inventories and safe constraints for sensitive feeds

If forages have mold

Save space for minerals, vitamins and additives

Tentative Fermentation Constraints & Rumen fill

Fermentable CHO, %DM

Close up Fresh

Minimum Maximum Minimum Maximum

Fiber 24 27 13 17

Starch 13 14 18 20

Sugars 2.5 3.5 4 6

Sol Fiber 4 6 4 7

uNDF30, %BW

? ? ? ?

uNDF240, %BW

? ? 0.35 0.40

49

Tentative Starch and Starch Fermentability – Transition and Lactating cows

50 Based on Allen Recommendations

Fiber Recommendations Nutrient Kg %Fraction %DM Good

Environment Average

Environment Poor

Environment

Min Max Min Max Min Max

Dry Matter2

24.5

Ferm CHO Dry Matter

10.5 43 43 42 45 41 44 38 41

Total NDF 7.4 30 30 36 28 33 27 31

Forage NDF 5.2 70 22 21 23 22 24 23 25

peNDF 5.6 76.6 23 23 25 23 25 23 25

Lignin 0.9 11.7 3.5 3 4 3 5 4 6

Fermentable NDF 2.6 >32 10 9 11 10 12 11 13

NFC Guidelines for the Early Lactation Cow

Close-up Group Fermentation constraints - AMTS

53

Close-up group Ingredient CHO fermentation results

54

Close-up Group Ration AMTS

55

Fresh Group Fermentation constraints AMTS

56

Fresh Group Fermentation Profiles AMTS

57

Fresh Group Ration AMTS

58

Summary We need better assays for starch

digestibility We need to account for more than one pool We need to account for particle size

Our starch model for the rumen is relatively primitive – passage/digestion It is a second order model – Allen

We need better definition of the other CHO fractions Sugars and soluble fiber fractions

59

Summary

The goal is to understand the group and then to formulate for the correct fermentation pattern

Temperature and humidity

Stocking rate, etc.

We need to better understand the impact of eating behavior and then how to balance the CHO fermentation

60

Summary

The bottom line is we need to start balancing fermentable CHO fractions for

Replacements

Dry cows

Fresh cows

High groups

Low groups

We still have some work to do!!

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14 de setembro 19:00

(toda segunda quarta feira do mês)

Tom Tylutki, PhD - AMTS Estratégias avançadas para máxima produção de leite

Discussão e comentários – Prof. Marcos Neves Pereira – UFLA

Tradução simultânea – Marcelo Hentz Ramos – 3rlab

Webinar – O Nutricionista Onde os grandes nomes da nutrição de vacas leiteiras se encontram!

Mais informações: www.3rlab.com.br

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