Changing Forage QualityChanging Forage Quality...

Changing Forage QualityChanging Forage QualityChanging Forage Quality Changing Forage Quality Testing for Alfalfa Hay Testing for Alfalfa Hay

MarketsMarkets

Daniel H. Putnam, PhDDaniel H. Putnam, PhDDaniel H. Putnam, PhDDaniel H. Putnam, PhDDepartment of Plant SciencesDepartment of Plant SciencesUniversity of California, DavisUniversity of California, DavisDepartment of Plant SciencesDepartment of Plant SciencesUniversity of California, DavisUniversity of California, Davisy ,y ,y ,y ,

2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage Symposium

Thesis:Thesis:Q li d kQ li d k

Thesis:Thesis:Q li d kQ li d kHay Quality and Markets:Hay Quality and Markets:Hay Quality and Markets:Hay Quality and Markets:

Current System is nearly entirelyCurrent System is nearly entirely Current System is nearly entirelyCurrent System is nearly entirely Current System is nearly entirely Current System is nearly entirely based upon low fiber (ADF, NDF) = based upon low fiber (ADF, NDF) = high qualityhigh quality

Current System is nearly entirely Current System is nearly entirely based upon low fiber (ADF, NDF) = based upon low fiber (ADF, NDF) = high qualityhigh qualityhigh qualityhigh quality

This system is effective to some This system is effective to some degree but misses importantdegree but misses important

high qualityhigh qualityThis system is effective to some This system is effective to some

degree but misses importantdegree but misses importantdegree, but misses important degree, but misses important quality attributesquality attributes

Prone to AbusesProne to Abuses

degree, but misses important degree, but misses important quality attributesquality attributes

Prone to AbusesProne to AbusesProne to AbusesProne to AbusesProne to AbusesProne to Abuses


What is Hay Quality?What is Hay Quality?What is it worth?What is it worth?

What is Hay Quality?What is Hay Quality?What is it worth?What is it worth?What is it worth?What is it worth?

How should it be measured?How should it be measured?What is it worth?What is it worth?

How should it be measured?How should it be measured?


What is a quality Car?What is a quality Car?What is a quality Car?What is a quality Car?What is a quality Car?What is a quality Car?What is a quality Car?What is a quality Car?Nice StylingSafety Airbags

Great Suspensionp

Good Milage

Quality Wheels:

Engine PowerG d P i t J b


Good Paint Job:Many Aspects of Quality!!

What is Quality Hay?What is Quality Hay?What is Quality Hay?What is Quality Hay?

A NutritionistA Nutritionist would say:would say:A NutritionistA Nutritionist would say:would say:1. Total 1. Total Digestible EnergyDigestible Energy (TDN, NEL, (TDN, NEL, Total Total

potential biological energy of foragepotential biological energy of forage))2 E i i2 E i i (I k P i l)(I k P i l)

1. Total 1. Total Digestible EnergyDigestible Energy (TDN, NEL, (TDN, NEL, Total Total potential biological energy of foragepotential biological energy of forage))

2 E i i2 E i i (I k P i l)(I k P i l)2. Energy per unit time 2. Energy per unit time (Intake Potential)(Intake Potential)3. Effectively Absorbed 3. Effectively Absorbed ProteinProtein (both rumen (both rumen

available and rumenavailable and rumen undegradableundegradable))

2. Energy per unit time 2. Energy per unit time (Intake Potential)(Intake Potential)3. Effectively Absorbed 3. Effectively Absorbed ProteinProtein (both rumen (both rumen

available and rumenavailable and rumen undegradableundegradable))available and rumen available and rumen undegradableundegradable))4. Nutritionally Effective 4. Nutritionally Effective FiberFiber (physical (physical

value)value)

available and rumen available and rumen undegradableundegradable))4. Nutritionally Effective 4. Nutritionally Effective FiberFiber (physical (physical

value)value)value)value)5. Mineral Content (ion balance)5. Mineral Content (ion balance)

value)value)5. Mineral Content (ion balance)5. Mineral Content (ion balance)

Problem: Total Digestible Energy and feed intake

2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage SymposiumMany Aspects of Quality!!

are the most important issues, but cannot be directly measured!!!

A i l P fA i l P fA i l P fA i l P fAnimal PerformanceAnimal Performance(True Feeding Value)(True Feeding Value)

Animal PerformanceAnimal Performance(True Feeding Value)(True Feeding Value)( g )( g )( g )( g )

Potential Forage Potential Forage Potential AnimalPotential AnimalPotential Forage Potential Forage Feeding ValueFeeding Value

SpeciesSpecies

Potential AnimalPotential AnimalPerformancePerformance

Species, BreedSpecies, BreedMaturityMaturity

Leaf/Stem RatioLeaf/Stem RatioWeeds, Climate, Soils,Weeds, Climate, Soils,

Genetics, Age, Sex, Genetics, Age, Sex, Stage of lactation, Stage of lactation,

Health, Climate, Health, Climate,


Pests, Variety, etcPests, Variety, etc.. ManagementManagement

Forage Quality is MultiForage Quality is Multi--Forage Quality is MultiForage Quality is Multi--FacetedFacetedFacetedFaceted

Hi h C d P t iHi h C d P t iHigh Crude ProteinHigh Crude ProteinLow FiberLow FiberHigh Fiber DigestibilityHigh Fiber Digestibility

Hi h TDNHi h TDNHigh TDN High TDN Good mineral balanceGood mineral balanceNo WeedsNo Weeds


Good texture/odorGood texture/odor

B tB tB tB tBut…But…But…But…

Does our marketing System Does our marketing System incorporate important aspects of incorporate important aspects of

Does our marketing System Does our marketing System incorporate important aspects of incorporate important aspects of p p pp p pquality?quality?

Is it subject to abuse?Is it subject to abuse?

p p pp p pquality?quality?

Is it subject to abuse?Is it subject to abuse? Is it subject to abuse?Is it subject to abuse? Is it subject to abuse?Is it subject to abuse?


What is Hay Quality What is Hay Quality What is Hay Quality What is Hay Quality y Q yy Q yWorth?Worth?

y Q yy Q yWorth?Worth?

California markets more hay than California markets more hay than any other stateany other state

California markets more hay than California markets more hay than any other stateany other stateany other stateany other state

>95% of hay is bought, sold>95% of hay is bought, soldLik l >80% f h i t t d t l tLik l >80% f h i t t d t l t

any other stateany other state>95% of hay is bought, sold>95% of hay is bought, sold

Lik l >80% f h i t t d t l tLik l >80% f h i t t d t l t Likely >80% of hay is tested at least Likely >80% of hay is tested at least onceonce

Likely >80% of hay is tested at least Likely >80% of hay is tested at least onceonce

Fiber Based Marketing SystemFiber Based Marketing SystemDomestic: 95%, export <5%Domestic: 95%, export <5% Fiber Based Marketing SystemFiber Based Marketing SystemDomestic: 95%, export <5%Domestic: 95%, export <5%


, p, p, p, p

Long-Term California Hay Prices (1999-2009, all markets)

$250.00

$200.00

$100 00

$150.00

Pric

e/To

n ($

)

$50 00

$100.00P

Supreme

Premium(US Inflation Rate)

$0.00

$50.00Good

Fair

(US Inflation Rate)


$0.001998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

TDN is Predicted from ADFTDN is Predicted from ADF

60TDN (90% dm)

57585960

{ ( %)}

GoodPremiumSupreme Fair

54555657 {TDN = 82.38 - (.7515 x ADF%)}

(x.9 for 90% DM)

51525354

5051

24 25 26 27 28 29 30 31 32 33 34 35

2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage SymposiumPutnam & Tombaugh

ADF (100% dm)

RFV is calculated from RFV is calculated from NDF & ADFNDF & ADF

RFV is calculated from RFV is calculated from NDF & ADFNDF & ADFNDF & ADFNDF & ADFNDF & ADFNDF & ADF

Figure 6. RFV as a function of NDF (CA Data)(CA Data)

270

y = 20032x-1.3297

R2 = 0.992220

V

120

170RF

70

120

25 30 35 40 45 50 55

Although RFV is calculated from ADF and NDF, it can almost entirely be predicted from NDF alone.


25 30 35 40 45 50 55

NDFRFV is essentially = NDF (Weiss, 2002)

$170

Influence of Quality on Alfalfa Hay Price- Ten Year Average, all California Markets, 2000-2009

$150

$160 Average Difference due to Quality: $46/tonAverage Difference per unit ADF: $6.14/unit %ADF

y = -5.816x + 309.1R² = 0.9987

$130

$140

$150

$120

$130

$/to

n

$100

$110 'Supreme' 'Premium' 'Good' 'Fair'

$80

$90 ADF (%)

[<34] [34-36] [36-40] [40-44]NDF (%)

[<27] [27-29] [29-32] [32-35]


$70

[<34] [34 36] [36 40] [40 44]NDF (%)

(Ave. 13 reporting regions, approximate volume 6.5 - 7.5 million tons/year)

Does the FiberDoes the Fiber--Based Based Does the FiberDoes the Fiber--Based Based Marketing System Work?Marketing System Work?Marketing System Work?Marketing System Work? It works mostly, since low fiber It works mostly, since low fiber

hays are largely better in qualityhays are largely better in quality It works mostly, since low fiber It works mostly, since low fiber

hays are largely better in qualityhays are largely better in qualityDoes not incorporate other Does not incorporate other

analysis analysis Does not incorporate other Does not incorporate other

analysis analysis a a ys sa a ys sProne to AbusesProne to Abuses

a a ys sa a ys sProne to AbusesProne to Abuses


Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemDemanding Unrealistic Precision Demanding Unrealistic Precision

in lab testsin lab testsDemanding Unrealistic Precision Demanding Unrealistic Precision

in lab testsin lab testsin lab testsin lab testsArguments over a few tenths of a Arguments over a few tenths of a

i l b li l b l

in lab testsin lab testsArguments over a few tenths of a Arguments over a few tenths of a

i l b li l b lpercent in lab valuespercent in lab valuespercent in lab valuespercent in lab values


CommonlyCommonly-- Observed Observed V i i i H T iV i i i H T i

CommonlyCommonly-- Observed Observed V i i i H T iV i i i H T iVariation in Hay Testing Variation in Hay Testing Variation in Hay Testing Variation in Hay Testing

Sampling Between Within LabsSampling Variation

Between Labs

Within Labs

Probe- Lab-Lab Run-RunProbeProbe

Lab Lab Run Run

ADF 3.0 - 8.0 0.7 - 3.0 0.3 - 1.6NDF 4.0 – 9.0 1.0 – 4.0 0.4 – 2.0CP 2 0 6 0 0 5 2 0 0 2 1 0CP 2.0 – 6.0 0.5 – 2.0 0.2 – 1.0TDN 2.0 – 6.0 0.3 – 2.0 0.2 – 1.5


Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemTaking a Poor SampleTaking a Poor Sample

F ll P P t lF ll P P t lTaking a Poor SampleTaking a Poor Sample

F ll P P t lF ll P P t l–– Follow Proper Protocols Follow Proper Protocols –– 20 cores, sampling protocols20 cores, sampling protocols–– Follow Proper Protocols Follow Proper Protocols –– 20 cores, sampling protocols20 cores, sampling protocols–– Certify your hay sampleCertify your hay sample–– Certify your hay sampleCertify your hay sample


Variation Between cores Variation Between cores in a stackin a stack

( %d )

5960

TDN (90%dm)

575859

Mean:

545556 56.6

5354

1 3 5 7 9 11 13 15 17 19


Pure alfalfa hay from a single ‘uniform’ stack, 20 separate cores from separate bales

The lab results are only as good as the sample.


Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemUse of a Single NumberUse of a Single Number

O h i ( ) TDN RFVO h i ( ) TDN RFVUse of a Single NumberUse of a Single Number

O h i ( ) TDN RFVO h i ( ) TDN RFV–– Overemphasis on (e.g.) TDN or RFV Overemphasis on (e.g.) TDN or RFV ignores protein, ignores protein, digestibiltydigestibilty, ash, or , ash, or other attributesother attributes

–– Overemphasis on (e.g.) TDN or RFV Overemphasis on (e.g.) TDN or RFV ignores protein, ignores protein, digestibiltydigestibilty, ash, or , ash, or other attributesother attributesother attributesother attributes

–– Important to incorporate visual Important to incorporate visual judgementjudgement

other attributesother attributes–– Important to incorporate visual Important to incorporate visual

judgementjudgementjudgementjudgementjudgementjudgement


Visual EvaluationVisual EvaluationVisual EvaluationVisual Evaluation Species (alfalfa)Species (alfalfa) Leaf/Stem Ratio (subjective)Leaf/Stem Ratio (subjective) Maturity (presence of bloom)Maturity (presence of bloom)

Species (alfalfa)Species (alfalfa) Leaf/Stem Ratio (subjective)Leaf/Stem Ratio (subjective) Maturity (presence of bloom)Maturity (presence of bloom) Maturity (presence of bloom)Maturity (presence of bloom) Stem Thickness (feel them Stem Thickness (feel them –– are they are they

fibrous?)fibrous?) WeedsWeeds

Maturity (presence of bloom)Maturity (presence of bloom) Stem Thickness (feel them Stem Thickness (feel them –– are they are they

fibrous?)fibrous?) WeedsWeeds WeedsWeeds

–– Poisonous, noxious, irritantsPoisonous, noxious, irritants Molds/DustinessMolds/Dustiness

WeedsWeeds–– Poisonous, noxious, irritantsPoisonous, noxious, irritants

Molds/DustinessMolds/Dustiness AntiAnti--palatability Factorspalatability Factors

–– Poor texturePoor texture hard stems, coarsenesshard stems, coarseness

AntiAnti--palatability Factorspalatability Factors–– Poor texturePoor texture

hard stems, coarsenesshard stems, coarseness–– Evidence of heating (blackened color)Evidence of heating (blackened color)–– Evidence of excessive pests (black mold)Evidence of excessive pests (black mold)–– Unpleasant odorsUnpleasant odors

–– Evidence of heating (blackened color)Evidence of heating (blackened color)–– Evidence of excessive pests (black mold)Evidence of excessive pests (black mold)–– Unpleasant odorsUnpleasant odors


pppp

Relative Reliability of Visual Relative Reliability of Visual Relative Reliability of Visual Relative Reliability of Visual Vs. Lab AnalysisVs. Lab AnalysisVs. Lab AnalysisVs. Lab Analysis

QUALITY FACTORQUALITY FACTOR VISUALVISUAL LABLABQUALITY FACTORQUALITY FACTOR VISUALVISUAL LABLABQUALITY FACTORQUALITY FACTOR VISUALVISUAL LABLABStage of MaturityStage of Maturity PoorPoor ExcellentExcellentLeafinessLeafiness FairFair ExcellentExcellent

QUALITY FACTORQUALITY FACTOR VISUALVISUAL LABLABStage of MaturityStage of Maturity PoorPoor ExcellentExcellentLeafinessLeafiness FairFair ExcellentExcellentLeafinessLeafiness FairFair ExcellentExcellentFiber Fiber PoorPoor ExcellentExcellentP t iP t i PP E ll tE ll t

LeafinessLeafiness FairFair ExcellentExcellentFiber Fiber PoorPoor ExcellentExcellentP t iP t i PP E ll tE ll tProtein Protein PoorPoor ExcellentExcellentMineralsMinerals PoorPoor ExcellentExcellentN i W dN i W d E ll tE ll t PP

Protein Protein PoorPoor ExcellentExcellentMineralsMinerals PoorPoor ExcellentExcellentN i W dN i W d E ll tE ll t PPNoxious WeedsNoxious Weeds ExcellentExcellent PoorPoorTexture/OdorTexture/Odor ExcellentExcellent PoorPoorNoxious WeedsNoxious Weeds ExcellentExcellent PoorPoorTexture/OdorTexture/Odor ExcellentExcellent PoorPoorRecommended: Use Visual Evaluation Plus


Recommended Use V sual Evaluat on lusLab Analysis

Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemEncouraging Lab BiasEncouraging Lab Bias

D bl Ch k L b BiD bl Ch k L b BiEncouraging Lab BiasEncouraging Lab Bias

D bl Ch k L b BiD bl Ch k L b Bi–– Double Check Lab BiasDouble Check Lab Bias–– Split Sample testsSplit Sample tests–– Double Check Lab BiasDouble Check Lab Bias–– Split Sample testsSplit Sample tests–– Reduce demandReduce demand--driven biasdriven bias–– Reduce demandReduce demand--driven biasdriven bias


Variation BetweenVariation Between LabsLabs SplitSplitVariation BetweenVariation Between LabsLabs SplitSplitVariation Between Variation Between LabsLabs——Split Split Sample TrialSample Trial

Variation Between Variation Between LabsLabs——Split Split Sample TrialSample Trial

33343536

(A 30 5)

2930313233

DF

(%) (Ave=30.5)

2526272829

AD

(S D without outliers = 0 8 %)2425

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Lab Number

(S.D. without outliers 0.8 %)


Lab Number

Putnam & Tombaugh

Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemMisinterpreting Calculated ValuesMisinterpreting Calculated Values

R b RFV TDN RFQ NEL MER b RFV TDN RFQ NEL MEMisinterpreting Calculated ValuesMisinterpreting Calculated Values

R b RFV TDN RFQ NEL MER b RFV TDN RFQ NEL ME–– Remember, RFV, TDN, RFQ, NEL, ME Remember, RFV, TDN, RFQ, NEL, ME are all calculated valuesare all calculated valuesKnow the origins of theseKnow the origins of these

–– Remember, RFV, TDN, RFQ, NEL, ME Remember, RFV, TDN, RFQ, NEL, ME are all calculated valuesare all calculated valuesKnow the origins of theseKnow the origins of these–– Know the origins of these Know the origins of these calculations, since it can be confusingcalculations, since it can be confusingIf confusion persists refer to actualIf confusion persists refer to actual

–– Know the origins of these Know the origins of these calculations, since it can be confusingcalculations, since it can be confusingIf confusion persists refer to actualIf confusion persists refer to actual–– If confusion persists, refer to actual If confusion persists, refer to actual analyzed values.analyzed values.

–– If confusion persists, refer to actual If confusion persists, refer to actual analyzed values.analyzed values.


Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemMisinterpreting DM DataMisinterpreting DM Data

DM d t h ld b d t k t fDM d t h ld b d t k t fMisinterpreting DM DataMisinterpreting DM Data

DM d t h ld b d t k t fDM d t h ld b d t k t f–– DM data should be used to market for DM data should be used to market for YIELD, not for qualityYIELD, not for qualityALL forage analyses should be basedALL forage analyses should be based

–– DM data should be used to market for DM data should be used to market for YIELD, not for qualityYIELD, not for qualityALL forage analyses should be basedALL forage analyses should be based–– ALL forage analyses should be based ALL forage analyses should be based upon 100% DM data for NDF, ADF, upon 100% DM data for NDF, ADF, CP,CP, NDFdNDFd, etc., etc.

–– ALL forage analyses should be based ALL forage analyses should be based upon 100% DM data for NDF, ADF, upon 100% DM data for NDF, ADF, CP,CP, NDFdNDFd, etc., etc.CP, CP, NDFdNDFd, etc., etc.

–– High moisture High moisture –– look for mold or look for mold or other difficultiesother difficulties

CP, CP, NDFdNDFd, etc., etc.–– High moisture High moisture –– look for mold or look for mold or

other difficultiesother difficultiesother difficultiesother difficultiesother difficultiesother difficulties


Abuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current SystemAbuses of Current System Failure to Consider Additional Failure to Consider Additional

Analyses which may be moreAnalyses which may be more Failure to Consider Additional Failure to Consider Additional

Analyses which may be moreAnalyses which may be moreAnalyses which may be more Analyses which may be more predictivepredictiveAnalyses which may be more Analyses which may be more predictivepredictive


Intake:Intake:Intake:Intake:Intake:Intake:Intake:Intake:

Very Important to High Very Important to High Producing Dairy CowsProducing Dairy Cows

Very Important to High Very Important to High Producing Dairy CowsProducing Dairy Cowsg yg y

Less important to beef/nonLess important to beef/non--lactating cowslactating cows

g yg y Less important to beef/nonLess important to beef/non--

lactating cowslactating cowslactating cowslactating cowsPrediction difficultPrediction difficult

lactating cowslactating cowsPrediction difficultPrediction difficult


What about Intake??

20

22

d)

16

18

take

(kg/

Multi - MF

12

14

Mat

ter I

nt Primi - MFMulti - HF

6

8

10

Dry

M

6-21 -14 -7 0 7 14 21 28

Time (Day Relative to Calving)


Alfalfa’s Value in a Alfalfa’s Value in a R tiR tiRationRation

AlfalfaAlfalfa CornCorn BermudaBermudaAlfalfaAlfalfa CornCorn BermudaBermudaMilk kg/dayMilk kg/day 2323 2020 1818Concentrate (%)Concentrate (%) 3030 4545 6060( )( )Intake (kg/day)Intake (kg/day) 2424 2020 1919TDN (mix)TDN (mix) 6565 7272 7171Net Energy (NEL)Net Energy (NEL) 1.501.50 1.611.61 1.531.53TDN Intake (kg/d)TDN Intake (kg/d) 14.614.6 12.712.7 11.811.8Milk (kg)/Mcal NEMilk (kg)/Mcal NE 1.441.44 1.401.40 1.371.37(Data from Mertens, 1983)(Data from Mertens, 1983)


The importance of time in The importance of time in ti ti i ldti ti i ldestimating energy yieldestimating energy yield

Timothy

ergy

ib

le E

ne

Alfalfa

Dig

esti

0 12 24 36 48

2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage SymposiumHours of Fermentation0 12 24 36 48

(Adapted from Van Soest, 1995)

NDF DigestibilityNDF DigestibilityNDF DigestibilityNDF DigestibilityNDF DigestibilityNDF DigestibilityNDF DigestibilityNDF DigestibilityRELATIONSHIP BETWEEN ADF AND NDF DIGESTIBILITY

- 319 Samples, Western Hays

55

60

45

50

35

40

y = 0.0222x2 - 1.8041x + 77.565R 2 = 0.1285

3018 20 22 24 26 28 30 32 34 36 38 40

ADF


Ash Content of AlfalfaAsh Content of AlfalfaAsh Content of AlfalfaAsh Content of Alfalfas Co te t o a as Co te t o a as Co te t o a as Co te t o a aRELATIONSHIP BETWEEN ADF AND ASH - 560 Western hay samples

24

20

22

24

y = 0.0538x + 10.089

R2 = 0.0128

14

16

18

10

12

6

8

18 23 28 33 38 43 48A DF ( %)


PURPOSES OF HAY PURPOSES OF HAY TESTING:TESTING:

1) Formulate 1) Formulate 1) Formulate 1) Formulate RationsRations

2) D t i2) D t iRationsRations

2) D t i2) D t i2) Determine 2) Determine EconomicEconomic

2) Determine 2) Determine EconomicEconomicEconomic Economic WorthWorthEconomic Economic WorthWorth

2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage SymposiumPutnam & Tombaugh, 2004

A fiberA fiber--based Market System:based Market System:A fiberA fiber--based Market System:based Market System:

EFFECT OF FIBER VALUE ON PRICE - Common Market Curve

$150

$120$130$140$150

(Area of Critical Concern)

A B C

$90$100$110$120

$/to

n

$60$70$80$90

TDN (CA equation, 90%DM):

$50$60

20 22 24 26 28 30 32 34 36 38

ADF

59.3 57.9 56.5 55.2 53.9 52.5 51.1 49.8


ADF

H Q lit C tH Q lit C tH Q lit C tH Q lit C tHay Quality Concepts: Hay Quality Concepts: (evolution of predictive tools)(evolution of predictive tools)

Hay Quality Concepts: Hay Quality Concepts: (evolution of predictive tools)(evolution of predictive tools)

VisualVisualVisualVisual

ProximateProximateProximateProximate

RFV for marketing (Midwest)RFV for marketing (Midwest)

ADFADF TDN (N i i i /M k )TDN (N i i i /M k )

RFV for marketing (Midwest)RFV for marketing (Midwest)

ADFADF TDN (N i i i /M k )TDN (N i i i /M k )ADF ADF –– TDN (Nutritionists/Marketers)TDN (Nutritionists/Marketers)

S ti E ti i lS ti E ti i l

ADF ADF –– TDN (Nutritionists/Marketers)TDN (Nutritionists/Marketers)

S ti E ti i lS ti E ti i l

Major Question: Can Summative Equations be


Summative Equations using many analysesSummative Equations using many analysesSummative Equations using many analysesSummative Equations using many analysesq

used for Marketing? RFQ?

STANDARD HAY TEST REPORT:Dry Matter Basis Dry Matter Basis

Lab Analysis ResultsLab Analysis Results11: : As As Rc’dRc’d 90%dm 100% dm90%dm 100% dmDry Matter (dm)Dry Matter (dm) 87%87% 90%90% 100%100%

Dry Matter Basis Dry Matter Basis Lab Analysis ResultsLab Analysis Results11: : As As Rc’dRc’d 90%dm 100% dm90%dm 100% dmDry Matter (dm)Dry Matter (dm) 87%87% 90%90% 100%100%Dry Matter (dm)Dry Matter (dm) 87%87% 90%90% 100%100%ADFADF 26.126.1 2828 31.031.0NDFNDF 33.533.5 34.734.7 38.538.5CPCP 17.417.4 18.018.0 20.020.0

Dry Matter (dm)Dry Matter (dm) 87%87% 90%90% 100%100%ADFADF 26.126.1 2828 31.031.0NDFNDF 33.533.5 34.734.7 38.538.5CPCP 17.417.4 18.018.0 20.020.0

Calculated ValuesCalculated Values22::TDNTDN 52.152.1 55.255.2 59.859.8NELNEL 0.530.53 0.550.55 0.610.61DDMDDM 57 057 0 59 059 0 65 565 5

Calculated ValuesCalculated Values22::TDNTDN 52.152.1 55.255.2 59.859.8NELNEL 0.530.53 0.550.55 0.610.61DDMDDM 57 057 0 59 059 0 65 565 5DDMDDM 57.057.0 59.059.0 65.565.5RFVRFV 150150CATEGORY:CATEGORY:Supreme (<27 ADF)Supreme (<27 ADF)

DDMDDM 57.057.0 59.059.0 65.565.5RFVRFV 150150CATEGORY:CATEGORY:Supreme (<27 ADF)Supreme (<27 ADF)Premium (27Premium (27--30 ADF)30 ADF)Good (29Good (29--32 ADF)32 ADF)Fair (32Fair (32--35 ADF)35 ADF)1. 1. A minimum of .5 percentage point variation is expected in lab resultsA minimum of .5 percentage point variation is expected in lab results

Premium (27Premium (27--30 ADF)30 ADF)Good (29Good (29--32 ADF)32 ADF)Fair (32Fair (32--35 ADF)35 ADF)1. 1. A minimum of .5 percentage point variation is expected in lab resultsA minimum of .5 percentage point variation is expected in lab results


u o 5 pe ce tage po t a at o s e pected ab esu tsu o 5 pe ce tage po t a at o s e pected ab esu tsRFV = NFTA EquationRFV = NFTA Equation TDN = CA EquationTDN = CA Equation

u o 5 pe ce tage po t a at o s e pected ab esu tsu o 5 pe ce tage po t a at o s e pected ab esu tsRFV = NFTA EquationRFV = NFTA Equation TDN = CA EquationTDN = CA Equation

New Standard Hay Test:New Standard Hay Test:New Standard Hay Test:New Standard Hay Test:Core Hay Analysis:Core Hay Analysis:Core Hay Analysis:Core Hay Analysis:Core Hay Analysis:Core Hay Analysis: DM DM –– Not for quality Not for quality –– but for yieldbut for yield NDF NDF -- Neutral Detergent Neutral Detergent FiberFiber

Core Hay Analysis:Core Hay Analysis: DM DM –– Not for quality Not for quality –– but for yieldbut for yield NDF NDF -- Neutral Detergent Neutral Detergent FiberFiber CP CP -- Crude ProteinCrude Protein NDFdNDFd –– NDF digestibilityNDF digestibility AshAsh

CP CP -- Crude ProteinCrude Protein NDFdNDFd –– NDF digestibilityNDF digestibility AshAsh Ash Ash Additional Analyses:Additional Analyses: Lignin Lignin –– Many nutritionists value ligninMany nutritionists value lignin DCADDCAD CloseClose upup animalsanimals

Ash Ash Additional Analyses:Additional Analyses: Lignin Lignin –– Many nutritionists value ligninMany nutritionists value lignin DCADDCAD CloseClose upup animalsanimals DCAD DCAD –– Close Close up up animalsanimalsCalculate:Calculate: TDN, RFV, RFQ, Summative TDN, RFV, RFQ, Summative Energy Values, Energy Values, NEL, NEL,

RFVRFV RFQ etcRFQ etc

DCAD DCAD –– Close Close up up animalsanimalsCalculate:Calculate: TDN, RFV, RFQ, Summative TDN, RFV, RFQ, Summative Energy Values, Energy Values, NEL, NEL,

RFVRFV RFQ etcRFQ etcRFV, RFV, RFQ, etc.RFQ, etc.Emphasize:Emphasize: What is actually measured!What is actually measured!Remember:Remember: Only as good as the sampling procedureOnly as good as the sampling procedure

RFV, RFV, RFQ, etc.RFQ, etc.Emphasize:Emphasize: What is actually measured!What is actually measured!Remember:Remember: Only as good as the sampling procedureOnly as good as the sampling procedure


What’s in a Forage Plant?Contribution to Energy

Non Fiber Carbohydrates (NSC)S S h P i

100% Dry Matterto Energy(TDN)

100%Sugars, Starches, Pectin

Crude

20-35%

CrudeProtein (soluble, bound)large

When ADF or NDF go up,

15-24%CP

30-50%Structural Carbohydrates (NDF)

(soluble bound)Some

Forage Quality goes down!NFC – Non Fiber

Carbohydrates need NDF 30 50%(soluble, bound)

Fat

ADF

100%

yseveral analyses

1-3%

NDF


AshNone 5-12%

Marketing:Marketing:Marketing:Marketing:Marketing:Marketing:Marketing:Marketing:Use of NDF as the first Use of NDF as the first

approximation of qualityapproximation of qualityUse of NDF as the first Use of NDF as the first

approximation of qualityapproximation of qualityapproximation of qualityapproximation of qualityAdditional interpretation of Additional interpretation of NDFdNDFd, ,

CP d hCP d h

approximation of qualityapproximation of qualityAdditional interpretation of Additional interpretation of NDFdNDFd, ,

CP d hCP d hCP, and ashCP, and ashCP, and ashCP, and ash


Summary:Summary:Summary:Summary:yyyy Quality is a complex trait, not conducive Quality is a complex trait, not conducive

to a single numberto a single numberib b d k i hilib b d k i hil

Quality is a complex trait, not conducive Quality is a complex trait, not conducive to a single numberto a single numberib b d k i hilib b d k i hil Fiber based marketing systems, while Fiber based marketing systems, while

simple and effective, are prone to several simple and effective, are prone to several abusesabuses

Fiber based marketing systems, while Fiber based marketing systems, while simple and effective, are prone to several simple and effective, are prone to several abusesabuses

Shifting Largely to:Shifting Largely to:–– Emphasis on NDF, Drop ADFEmphasis on NDF, Drop ADF

Use 100% DM valuesUse 100% DM values

Shifting Largely to:Shifting Largely to:–– Emphasis on NDF, Drop ADFEmphasis on NDF, Drop ADF

Use 100% DM valuesUse 100% DM values–– Use 100% DM valuesUse 100% DM values–– Incorporate Incorporate NDFdNDFd, Ash, Ash

Use calculated values (TDN, RFV, RFQ) Use calculated values (TDN, RFV, RFQ)

–– Use 100% DM valuesUse 100% DM values–– Incorporate Incorporate NDFdNDFd, Ash, Ash

Use calculated values (TDN, RFV, RFQ) Use calculated values (TDN, RFV, RFQ) ( , , Q)( , , Q)but know where they come from.but know where they come from.

Visual Evaluation still important.Visual Evaluation still important.

( , , Q)( , , Q)but know where they come from.but know where they come from.

Visual Evaluation still important.Visual Evaluation still important.


2010 CA Alfalfa & Forage Symposium2010 CA Alfalfa & Forage Symposium Larry Teuber, photo

Changing Forage QualityChanging Forage Quality...

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