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O Nutricionista

9 março 19:00

(toda segunda quarta feira do mês)

Dr. Sally Flis—Dairy One, Ralph Ward—CVAS, Dave Taysom--DairyLand

Análises, digestibilidades, shredlage, etc...

Totally independent laboratory providing extensive

testing of Feed, Forage, Soil, Manure and Water.

From Dave Taysom – Director for Dairyland Laboratories Inc.

Low Lignin? Reduced Lignin? Highly Digestible Alfalfa?

Provides strength to plants

Allows the plant vascular system to transport water in the plant without leakage.

Sequesters atmospheric carbon into vegetation

Is one of the most slowly decomposing components of dead vegetation, contributing a major fraction of soil organic matter.

Company Lignin Reduction

Pioneer 5%

Alforex 7 to 10%

Forage Genetics 10 to 15%

5 10 15 20 25 30 35 40 44

Days of Regrowth

5 10 15 20 25 30 35 40 44

Days of Regrowth

Yield Forage Quality

5 10 15 20 25 30 35 40 44

Days of Regrowth

Reduced Lignin Quality

5 10 15 20 25 30 35 40 44

Days of Regrowth

5 10 15 20 25 30 35 40 44

Days of Regrowth

Less and/or different lignin in stem ◦ Genetic effect

◦ Environmental effect

Less sunlight (cloudy days) reduces lignin content

Cooler temperature reduces lignin content

More leaves ◦ Favorable leaf growth environment

◦ Less leaf disease

◦ Reduce harvesting leaf loss

1st cutting

2nd cutting

3rd cutting

4th cutting

Season Total

2nd year 3 cut 2.97 2.43 2.15 ---- 7.55

4 cut 1.66 1.48 1.71 1.68 6.53

3rd year 3 cut 2.32 1.53 1.24 ---- 5.09

4 cut 1.31 1.18 0.75 0.83 4.07

1st cutting

2nd cutting

3rd cutting

4th cutting

Season Total

2nd year 3 cut 2.97 2.43 2.15 ---- 7.55

4 cut 1.66 1.48 1.71 1.68 6.53

3rd year 3 cut 2.32 1.53 1.24 ---- 5.09

4 cut 1.31 1.18 0.75 0.83 4.07

1st cutting

2nd cutting

3rd cutting

4th cutting

Season Total

2nd year 3 cut 2.97 2.43 2.15 ---- 7.55

4 cut 1.66 1.48 1.71 1.68 6.53

3rd year 3 cut 2.32 1.53 1.24 ---- 5.09

4 cut 1.31 1.18 0.75 0.83 4.07

Improved forage quality

Wider harvest window?

Improved forage quality

Wider harvest window?

Later harvest ◦ Greater tonnage per cutting

◦ Make use of full growing season

◦ Reduce number of cuttings

15 to 18% lignin reduction harvest 8 to 10 days later

Forage Genetics Team

Entry Yield ADL % checks RFQ % checks

2014 2015 2014 2015 2014 2015

EXP1 96% 100% 80% 82% 113% 117%

EXP2 98% 103% 79% 82% 115% 113%

EXP3 101% 105% 79% 81% 113% 116%

EXP4 94% 100% 77% 77% 122% 124%

EXP5 100% 105% 79% 80% 117% 119%

EXP6 100% 103% 82% 82% 106% 113%

EXP7 96% 100% 80% 80% 114% 120%

Control1 99% 99% 100% 99% 104% 101%

Control2 101% 101% 100% 101% 96% 99%

The FGI trial demonstrates that ADL of the HarvXtra™ alfalfa varieties harvested at 35 days is slightly less than the checks harvested at 28 days. ◦ This should allow growers to

adopt a less aggressive cutting management program (e.g. 3 vs 4 cuts) without sacrificing forage quality.

HarvXtra ChecksA

HarvXtra™ Alfalfa checks: Consistency 4.0RR and WL355RR

Effect of low lignin genes on in vivo digestibility

Digestibility of low lignin alfalfa types and controls fed to lambs, diet was

100% alfalfa hay fed ad libitum.

100% alfalfa hay diet aNDF % DM

ADL % DM

NDFD % NDF

DMD % DM

COMT Inactive 38.2 5.3 57.5* 67.5*

COMT Active (Control) 39.0 5.8 49.1 64.5

CCOMT Inactive 39.4 5.2 50.1 65.3

CCOMT Active (Control) 39.4 5.9 46.4 63.7

*Significant, P < 0.05

SOURCE: Mertens et al. 2008. J. Dairy Sci. Supple. 1

Measuring Lignin

Two methods: Use potassium permanganate to solubilize lignin,

wash and measure weigh loss. Use sulfuric acid to solubilize cellulose,

hemicellulose. Klason method developed in early 1900s

NIR estimate of lignin

Based on wet chemistry reference method

Method shows same variability

Company Lignin Reduction

Unit reduction (assuming 7% lignin)

Pioneer 5% 0.35

Alforex 7 to 10% 0.5 to 0.7

Forage Genetics 10 to 15% 0.7 to 1.1

<3.5 5 7 9 11 13 15 17 19 21 23 25 27 29 >29.5

Mixed Haylage: Lignin & uNDFom240 % DM , 12000 samples

Lignin uNDFom240

<1.5 2 3 4 5 6 7 8 9 10 11 12 13 14 15 >15.5

Corn Silage: Lignin & uNDFom240, %DM 12,000 samples

Lignin uNDFom240

Acknowledgements: Dan Undersander Ph.D. – UW Extension Agronomist David Weakly Ph.D. – Winnfield Technologies.

Thank you

The Nutritionist Forage Lab Forum

Dr. Sally Flis—Dairy One Forage Lab

Shredlage and Forage NIR

Allenwaite Farm Shredlage Project 2015

Sally Flis, Ph.D.

Feed and Crop Support Specialist

Dairy One

Ithaca, NY

Project Design

• 12 week study • Started feeding on 3/13 • Pre-trial Milk analysis on 3/11 • Two pens – 2+ Lactation • 10.5 kg DM of Shreldage or Conventionally Processed Corn Silage (38 % of

DM) • 3.5 kg DM Haylage • 12.7 kg DM Premix Concentrate • 0.36 kg DM Whey

• Diets Formulated by Cargill (Sue Greth and Russ Saville) • 3 week Switch at the end

Objectives

1. Help the farm decide what direction to go in processing corn silage

2. Explore and develop lab measurement to better characterize the differences in shredlage and conventionally processed corn silage

Cow Numbers

• Started with 152 in each pen

• Start DIM Avg • Shredlage – 115

• Conventional– 120

• Number of cows in pens for all 12 weeks • Shredlage – 143

• Conventional – 136

• Shredlage Health • Mastitis – 5

• Feet – 9

• Pneumonia – 1

• Conventional Health • Mastitis – 9

• Feet – 14

Dry Matter Intake by Week, kg/day

Milk Production by Week, kg/day Diet 0 1 2 3 4 5 6 7 8 9 10 11 12

Shredlage 41.98 44.85 42.71 42.51 41.93 41.50 41.29 41.35 40.28 41.09 40.11 39.98 38.62 Standard Error 0.62 0.71 0.69 0.68 0.47 0.67 0.67 0.68 0.70 0.73 0.74 0.76 0.75

Conventional 41.69 43.29 41.08 41.06 40.75 40.34 40.00 40.04 39.30 40.04 39.33 39.10 38.06 Standard Error 0.60 0.66 0.63 0.63 0.41 0.63 0.64 0.64 0.66 0.68 0.69 0.70 0.72

Difference 0.29 1.56 1.63 1.45 1.18 1.16 1.30 1.31 0.98 1.05 0.78 0.89 0.55

Diet 0 1 2 3 4 5 6 7 8 9 10 11 12

Shredlage 24.02 27.11 25.75 25.33 25.38 25.31 25.18 25.12 24.90 26.62 26.26 26.22 25.92

Standard Error 1.82 0.18 0.22 0.32 0.37 0.09 0.33 0.08 0.17 0.17 0.12 0.20 0.11

Conventional 24.72 25.12 25.15 24.35 25.68 25.09 25.54 25.91 24.98 25.60 26.01 26.45 26.61

Standard Error 0.23 0.11 0.12 0.26 0.13 0.26 0.29 0.14 0.23 0.24 0.11 0.08 0.24

Difference -0.70 1.98 0.60 0.98 -0.30 0.22 -0.36 -0.79 -0.08 1.03 0.25 -0.23 -0.69

Corn Silage Analysis

Week Dry Matter Starch, % DM Starch Digestibility NDF, % DM NDFD 30h, % NDF CP, % DM

Conv Shredlage Conv Shredlage Conv Shredlage Conv Shredlage Conv Shredlage Conv Shredlage 0 29.9 29.2 28.5 31.5 79 88 46.9 43.3 55 56 7.1 7.4 1 31.0 31.0 32.2 35.6 77 74 45.7 41.8 57 54 6.9 6.7 2 32.0 31.4 31.8 33.3 78 90 43.8 42.8 57 65 7.0 8.0 3 32.3 32.5 33.4 34.3 83 81 43.4 42.2 55 57 6.8 7.6 4 32.9 32.0 34.8 34.7 85 82 42.5 41.5 56 57 6.8 7.8 5 32.0 32.4 32.1 33.4 85 81 44.5 43.4 60 57 7.5 7.7 6 31.6 32.2 35.4 34.1 88 83 41.4 41.9 57 59 7.1 7.7 7 31.9 33.5 32.4 33.7 83 77 43.2 42.1 58 57 7.1 7.8 8 32.8 33.0 32.0 33.9 86 81 44.1 41.5 57 57 7.2 7.3 9 32.3 32.8 33.5 33.3 85 84 42.6 44.8 57 53 7.0 7.6

10 32.3 33.2 32.0 34.0 90 84 44.1 42.5 56 55 7.4 7.8 11 32.4 32.7 30.5 36.5 85 83 44.8 43.8 55 56 7.7 7.8 12 31.4 33.3 29.2 35.6 90 88 46.0 41.6 55 56 7.4 8.1

Milk Quality

Week 6 Week 12

Treatment Fat % Protein %

SCC x1000

MUN Fat % Protein %

SCC x1000

Shredlage 3.68 ± 0.67

3.09 ± 0.33

75.2 ± 127.8

12.9 ± 1.99

3.68 ± 0.83

3.01 ± 0.46

76.1 ± 277.9

13.0 ± 2.34

Conventional 3.73 ± 0.67

3.10 ± 0.33

88.8 ± 277.3

13.2 ± 2.08

3.71 ± 0.72

3.06 ± 0.39

53.6 ± 87.2

12.9 ± 2.09

No differences

Fecal Starch

Treatment 6 Week Fecal

Starch

6 Week ±

12 Week Fecal

Starch

12 Week

Shredlage 2.18

1.16 1.46 0.64

Conventional 1.95 0.78 1.66 0.86

• Fecal starch less than 2 % indicates complete use of starch in the diet

• Fecal NDF was measured • Shredlage Week 6 – 48.0 %

• Conventional Week 6 – 49.8 %

• Shredlage Week 12 – 49.7 %

• Conventional Week 12 – 49.7 %

Shredlage Results - Summary

• UW Trial 1 – 50% Shredlage or 50% Conventional as a % of DM • No sorting

• 0.80 kg/day milk increase (NS)

• Shredlage cows consumed 0.70 kg DM/day more

• No difference in milk quality

• Total Tract Starch Digestibility was higher with shredlage – Fecal starch not reported

• UW Trial 2 – 45% Shredlage or 45% Conventional as a % of DM • No sorting

• No difference in DMI

• Varied milk response over 14 weeks

• No difference in milk quality

Shredlage Results - Summary

• Cornell Trial - 45% Shredlage or 45% Conventional as a % of DM • No difference in milk • No difference in DMI • No difference in milk quality

• Allenwaite Project • No sorting • No Milk quality differences • Lower CS inclusion rate (38% of DM) • Similar DMI • Milk response of 0.45 to 1.6 kg/cow/day • No Fecal Starch Difference

Characterizing Corn Silage

• Chemical Analysis

• Penn State Shaker

• Corn Silage Processing Score (CSPS)

• Others?

Corn Silage Penn State Box Sample % Upper % Middle % Lower % Bottom

Shredlage 36.8 39.1 22.9 1.2

Conv CS 13.9 64.8 20.2 1.0

Shredlage Top Penn State Screen Conventional CS Top Penn State Screen

Corn Silage Processing Score (CSPS)

• Coarse Fraction - material on sieves > 4.75 mm • Stimulates chewing activity

• Starch in the particles will be poorly digested

• Rate of digestion will be slow and may escape the rumen as unchewed particles

• Medium Fraction – material on sieves between 4.75 and 1.18 mm

• Fine Fraction - materials that pass through the < 1.18 mm • May not contribute to chewing activity or physical effectiveness

• Starch in the fine particles may ferment very rapidly in the rumen and cause problems when rations low in effective fiber

• Knowing what in in this fraction may be a useful tool for trouble shooting some feeding problems.

0 1 2 3 4 5 6 7 8 9 10 11 12

Corn Silage Processing Score

Shredlage CSPS

Conventional CSPS

Optimum CSPS

Adequate CSPS

Inadequate CSPS

Is CSPS Enough to Explain Milk Response?

Maybe, but can we do better?

101,00

48,0 53,0 58,0 63,0 68,0 73,0

CCSPS Score

CSPS vs. Milk Production

Shredlage

Conventional

57,0 59,0 61,0 63,0 65,0 67,0 69,0

CSPS Score

CSPS vs. Milk Response

More detailed measures of CSPS Fractions - Starch

0 1 2 3 4 5 6 7 8 9 10 11 12

Coarse % Starch

Shredlage Conventional

0 1 2 3 4 5 6 7 8 9 10 11 12

Medium % Starch

0 1 2 3 4 5 6 7 8 9 10 11 12

Fine % Starch

101,00

25,0 30,0 35,0 40,0

% Starch

Coarse Starch vs. Milk Production

Shredlage

Conventional

101,00

30,0 35,0 40,0 45,0

% Starch

Medium Starch vs. Milk Production

Shredlage

Conventional

101,00

40,0 45,0 50,0 55,0 60,0

% Starch

Fine Starch vs. Milk Production

Shredlage

Conventional

More detailed measures of CSPS Fractions - Starch

More detailed measures of CSPS Fractions - aNDF

0 1 2 3 4 5 6 7 8 9 10 11 12

Coarse % aNDF

0 1 2 3 4 5 6 7 8 9 10 11 12

Medium % aNDF

0 1 2 3 4 5 6 7 8 9 10 11 12

Fine % aNDF

101,00

40,0 42,0 44,0 46,0 48,0 50,0 52,0

% aNDF

Coarse aNDF vs. Milk Production

Shredlage

Conventional

101,00

34,0 36,0 38,0 40,0 42,0 44,0 46,0

% aNDF

Medium aNDF vs. Milk Production

Shredlage

Conventional

101,00

25,0 27,0 29,0 31,0 33,0 35,0 37,0

% aNDF

Fine aNDF vs. Milk Production

Shredlage

Conventional

More detailed measures of CSPS Fractions - aNDF

Corn Silage Measures

• CSPS does not look like the best measure for cow performance

• Fine Fraction measures do not appear to be related to cow performance

• Medium % Starch and % aNDF may be related to cow performance

• More samples and production information to build data set

Where to go next?

• More samples with milk response for aNDF and Starch in Medium CSPS Fraction

• Follow cows that were in 12 week study into early lactation for any carryover

Thank You

• Allenwaite Farm and Staff

• Sue Greth and Russ Seville from Cargill

• Dairy One Lab Staff

Percent Grass NIR

Predicted vs Actual Grass Percentage in Samples

R² = 0,9914

0 10 20 30 40 50 60 70 80 90 100

Actual

Percent Grass and Percent Alfalfa • Why is it important to know the alfalfa-grass ratio both pre- and post-

harvest? • Help to identify the optimum quality harvest date.

• Allow ranking of fields for harvest, based on alfalfa %.

• Help to decide when to start treating a stand like grass, from a fertility standpoint.

• Provide information for deciding when to rotate a field.

• Assess stand deterioration due to alfalfa insect/disease problems, such as alfalfa-snout beetle in northern NY.

• Some nutrient record keeping software requires input of alfalfa %. • Required information for some forage quality software, such as MILK2006, alfalfa-

grass version.

• May help with ration balancing.

• Quality control: serves as a check on just how representative the forage sampling is. Highly variable alfalfa % over time indicates unrepresentative sampling.

The Nutritionist Forage Lab Forum

Matt Michonski—Cumberland Valley Analytical

Services

Fatty Acids and NIR for Intestinal Protein Digestibility

The Nutritionist Webinar Series

Current Focus Concepts at CVAS:

Fatty Acid Evaluations by NIR

Intestinal Protein Digestibility Assay

Matt Michonski Cumberland Valley Analytical Services

www.foragelab.com

Why consider fatty acids?

• Crude fat is the traditional method for evaluation fat in feedstuffs – “ether extract”.

• Ether extract is not a uniform entity – may include waxes, cutin, fermentation acids and chemical entities that are not fatty acids.

• For many feed ingredients there is little difference between crude fat and total fatty acids.

Why consider fatty acids?

• However, for fermented feeds and some byproducts there may be significant differences between crude fat and total fatty acids.

Total Fatty Acids as a Percent of Fat in Hay Crop Silage

<25 30 35 40 45 50 55 60 65 70 75 80 85 >85

Total Fatty Acids as Percent of Fat

N=11,883 Ave. = 51.4 St. Dev. = 7.68

Fatty Acid Determination

• Fatty acid determination is generally an involved extraction followed by analysis by gas chromatography. This is expensive and time consuming.

• NIR can be an applicable technology for routine analysis of total fatty acids and even individual fatty acids.

Fatty Acids by NIR

Successful NIR calibrations are based on the following characteristics:

• Organic bonding and chemical uniformity

• Range in the nutrient being analyzed

• Precision in the analysis being performed by chemistry analysis

Fatty Acids by NIR

Fatty Acid evaluation of corn silage, corn grain, and TMR by NIR meet the criteria for generating quality NIR calibrations:

• They are well defined organic compounds;

• There is significant range in composition;

• Chemistry evaluation by gas chromatography provides significant precision of analysis.

Fatty Acids in Corn Silage NIR Equation Statistics (CVAS, 2016)

Fatty Acid Mean SEC RSQ

C18_1 .521 .046 .86

C18_2 1.22 .057 .94

C18_3 .150 .019 .88

RUFAL 1.89 .075 .96

Total Fatty Acids 2.50 .092 .94

Fatty Acids in Corn Grain NIR Equation Statistics (CVAS, 2016)

Fatty Acid Mean SEC RSQ

C18_1 .895 .069 .84

C18_2 2.05 .101 .93

C18_3 .059 .006 .51

RUFAL 3.03 .109 .96

Total Fatty Acids 3.72 .135 .95

Distribution of Total Fatty Acids (%DM) in Corn Silage

CVAS 2016

<1.25 1.55 1.85 2.15 2.45 2.75 3.05 3.35

Total Fatty Acids, %DM

N=2481 Ave. =

Distribution of Rumen Unsaturated Fatty Acids

(RUFAL, %DM) in Corn Silage, CVAS 2016

0%2%4%6%8%

10%12%14%16%18%20%

RUFAL, %DM

N=2481 Ave. =

Distribution of Total Fatty Acids (%DM) in Corn Grain CVAS 2016

N=1534 Ave. = 3.73

(RUFAL, %DM) in Corn Grain, CVAS 2016

RUFAL, %DM

N=1534 Ave. =

Distribution of Total Fatty Acids (%DM) In Production Dairy TMR

CVAS 2015

N=6262 Ave. =

(RUFAL, %DM) in Production Dairy TMR, CVAS 2015

RUFAL, %DM

N=6262 Ave. =

In-vitro N Indigestibility Assay (Ross et al., 2013)

• We refer to it as the “Multi-Step Protein Evaluation” (MSPE) Assay;

• Multiple labs have adopted this assay in the last several years;

• Provides a tool for evaluating protein sources and byproduct materials allowing for characterization of indigestible nitrogen (protein).

Why the need for the MSPE?

• Availability of metabolizable protein (MP) is a function of intestinal digestibility (ID) and ID is a static library value

• Most model (NRC, CNCPS) feed libraries have static values for ID

• We know this is not true and monogastric species rely on ID to balance for protein and amino acids

Source: Van Amburgh

Unavailable Nitrogen as calculated within the CNCPS

uN = [PB2 * (kd / (kd + kp) * (1- 0.8)] + ADIN

where,

• PB2 = (NDIN – ADIN),

• Kd in the rate of degradation for each ingredient,

• Kp is the passage rate for solids (0.05/h),

• 0.80 is the intestinal digestibility constant of PB2 (NDIN) (NRC, 1989)

Source: Van Amburgh

A2 B1 B2 C

100% ID 80% ID

Bound fiber

0% ID 100% ID

INTESTINAL DIGESTIBILITY

Potentially rumen un-degradable

protein

Source: Van Amburgh

New/Updated In Vitro ID assay

• Modification of existing methods to better estimate N unavailable fraction

– flasks instead of bags (sample loss, lag time)

–physiological enzyme mix

• reduce variation in proteolytic activity

• filtering residue on 1.5 μm, 90 mm glass filter paper (Whatman AH 934 or equivalent) instead of TCA precipitation

Source: Van Amburgh

• Filtration may not always be appropriate for recovery of treated fractions however.

• If nitrogen source is soluble or significantly micronized it may pass through the filter and will lead to a perception of lower rumen ungradable protein.

• In order to overcome the limitations of filtration, the use of freeze drying for recovery of materials in the assay is critical for RUP definition.

• Blood meal or feed mixes containing blood meal are key examples of materials where freeze drying is necessary.

• It is important to characterize feed materials submitted to the lab so that the correct procedural approach may be applied.

• Why not always use freeze drying? Cost and time involved.

Blood meal filtered through 1.5μm glass fiber filter – may be significantly soluble

Comparison of Filtration vs Freeze Drying in Three Blood Meals (CVAS, 2015)

CP %DM

Soluble Protein

Filter RUP % CP

Freeze Dry RUP % CP

Total Tract Undig. CP

Blood Meal 1

98.3 48.8 28.0 74.2 7.9

Blood Meal 2

98.8 2.0 96.3 97 23.9

Blood Meal 3

99.1 2.2 94.4 95.8 18.7

• Why not always use freeze drying? Cost and time involved:

– Basic freeze drying units cost $25K to $30K;

– Operational costs: operating a compressor and vacuum pump for multiple days per run;

– Run time can be 3 to 5 days.

Procedure in a single flask

N determination

Kjeldahl or Leco

Enzyme Mix

trypsin, chymotrypsin,

amylase, lipase and bile

Incubation 39°C, 24-h Shaking

Rumen fluid

Rumen buffer pH 6.8

Acidify 3 M HCl (pH 1.8 - 2)

Gastric Digestion (pH 2 HCl) + Pepsin

Neutralize 2 M NaOH

Fermentation anaerobic 16-h, 39°C

kp = 6.25 %/h

Filter

Sample

Source: Van Amburgh

What the Ross intestinal digestibility assay was not designed to do…

According to Van Amburgh:

• “It was not designed to provide a robust RUP value”;

• “We provided the single time point estimate of RUP because no one would believe the uN value unless we provided the RUP”;

• “A more robust RUP determination requires multiple time points and is not part of this assay”.

Comparison of ADIN and Ross in-vitro indigestible N

Feed N (% DM)

ADIN (%N) Ross In-vitro

indigestible N (% N)

Regular blood meal

16.2 4.7 16

Heat damaged blood meal

16.1 1.8 93

Soybean meal solvent extracted

7.6 6.7 8

Soybean meal heat treated

7.3 7.9 11

Source: Ross, 2013 Slide Source: Van Amburgh

Example MSPE Data CVAS, 2015

RUP, % CP Total tract uCP, % CP

Blood 1 94.1 65.7

Blood 2 90.0 11.5

Canola 1 31.3 20.6

Canola 2 43.8 11.3

Distillers 1 53.3 16.3

Distillers 2 81.2 8.7

Untreated SBM 32.8 4.1

Treated SBM 1 51.2 7.9

Does The Cow Care?

Source: Van Amburgh

Research at Cornell

Objective:

• Test the accuracy and precision of the in-vitro N indigestibility assay (Ross et al., 2013) in lactating dairy cattle

• Evaluate the use of the uN values in the CNCPS to predict cattle performance

Source: Van Amburgh

Experimental Design

• 128 cows

– 96 multiparous (1,587 lb (720 kg) BW; 147 DIM)

– 32 primiparous (1,338 lb (610 kg) BW; 97 DIM)

• Cattle distributed by BW and DIM

• 8 pens of 16 cows (12 multiparous and 4 primiparous)

• Pens stratified into four levels by milk production and each stratum randomly allocated to treatments

• Random allocation of pens to treatments

Source: Van Amburgh

Treatment Diets

• Diets designed to iso-energetic and iso-nitrogenous

• Treatment difference was created by using two different blood meals

• One blood meal was 9% uN, the other was 34% uN

• The calculated difference in N digestibility between the two treatments was 38 g N – cattle were consuming ~667 g N (5.8% of intake)

Source: Van Amburgh

Nitrogen Intake (LS means)

0 1 2 3 4 5 6 7 8 9

Week of experiment

LOW uN HIGH uN

(P<0.77)

Source: Van Amburgh

Energy Corrected Milk (LS Means)

0 1 2 3 4 5 6 7 8 9

Week of experiment

LOW uN HIGH uN

(P<0.01)

Source: Van Amburgh

Summary

• Total Fatty Acids is a more significant nutritional entity than Crude Fat;

• NIR is able to predict Total Fatty Acids and Unsaturated Fatty Acids with significant accuracy and precision.

Summary

• The Intestinal Digestibility Assay of Ross and Van Amburgh (MSPE) is a significant improvement in a laboratory approach to evaluate the indigestible fraction in feed materials.

• The use of freeze drying in place of filtration is necessary for proper characterization of products that contain significant soluble or micronized sources of nitrogen.

• The assay was meant to evaluate the indigestible protein fraction in feeds and not rumen ungradable protein. While RUP values are provided in this assay and have some value, they are not meant to be formally defining.

The Nutritionist Webinar Series

Thank you for your attention!

Matt Michonski mmichonski@foragelab.com

Cumberland Valley Analytical Services

www.foragelab.com

13 de abril 19:00

(toda segunda quarta feira do mês)

Dr. Jim Drackley, PhD, Professor, University of Illinois

Alimentação de bezerras—estratégias para casinha e pós casinha

Sua empresa pode ser parceira no próximo Webinar. Ajude-nos a trazer aos

nutricionistas Brasileiros o que existe de mais novo em nutrição de vacas

leiteiras no mundo.

eventos@3rlab.com.br

Cadastre-se nos nossos meios de comunicação para receber os slides

em português e o Webinar gravado:

http://3rlab.wordpress.com/

https://www.facebook.com/3rlab

Excelente material para treinamento de equipes/grupos de estudos

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