SlideShare une entreprise Scribd logo
1  sur  23
Dr. Ken Andries
Collage of Agriculture, Food Science, and
Sustainable Systems
Kentucky State University
J.L. Lush, Animal Breeding Plans. 1945
 Dairy herds started measuring performance in
the 50’s and 60’s for milk production.
 Beef cattle started BIF to standardize
Performance programs in 1968.
 Beef moved to performance pedigrees and then
to EPDs in the 80’s
 NSIP stared in 1986 and produced flock EPD
for sheep and offered to Meat Goat Industry.
 Research into use of DNA assisted selection
(genomics) in the 2000’s for many species.
 Average weaning weight has increased by 150%
(175 lbs.) with only a small increases in birth
weight.
 Calving difficulty has been reduced greatly.
 Carcass traits are now an economical trait for
cow/calf producers
 Most commercial beef cattle producers utilize data
in selecting bulls.
 AI has become very wide spread in the commercial
industry partly due to performance data.
 Key point: it did not happen over night and started
with simple data collection.
 Austria started in 1990.
 Quality issues were identified as a problem as
wool market was decreasing.
 Research and selection resulted in increased
carcass weight and increased economic value.
 Most of the increase was due to improved
performance (growth).
 A common industry goal of improved meat
quality was part of the success.
 LAMBPLAN was key to allowing producers to
improve selection effectiveness.
 Reproduction has one of the greatest impacts
on profitability.
 Growth traits are often second in importance.
 Health traits influence both reproduction and
growth greatly so they are critical.
 For meat goats, currently carcass traits have
less value due to market trends.
 To be profitable we must optimize
reproduction, growth, and health traits.
 Average goat producer keeps no records of
performance.
 Basic performance records from birth to
weaning can be used to make progress.
 Adjusted weights provide a better picture of
performance, remove some environmental
factors.
 EBVs and EPDs are possible with meat goats if
we have data to process.
Variable Observations Mean Std Deviation
Birth Weight 7791 7.55 1.73
Weaning Age 7041 89.31 20.13
Weaning Weight 7022 37.47 11.68
Average Daily Gain 6910 0.42 0.11
Weight per day of age 7022 0.52 0.12
90 day Weight 7023 38.23 10.55
Adjusted Weaning Weight 6986 43.41 12.65
Number Born 4501 1.84 0.65
Number Weaned 4376 1.59 0.69
 Data collection gives you information to make
progress towards goals.
 Can impact health traits as well as
performance.
 Individual data such as on-farm performance
data is not as effective as national evaluations.
 Individual/on-farm data only apply to
individuals within the contemporary group.
 This limits their use when purchasing or
comparing individuals from multiple groups.
Year BWT WWT Age at
Wean
ADG 90DWT AWWT
2008 7.28 32.52 89.88 0.28 32.94 35.80
2009 7.65 26.35 71.50 0.26 31.02 36.07
2010 7.43 29.89 67.40 0.34 38.07 41.29
2011 6.95 25.38 60.98 0.30 34.10 36.87
2012 6.54 30.76 96.91 0.25 29.05 31.62
2013 7.01 27.08 84.02 0.25 29.49 31.34
• Purchase of a large number of yearlings that entered
production in 2011 and 2012.
• Introduction of the purchased doe kids and breed sires,
without data, moved our selection back several years.
146
859
616
ID Seasons BWT WN Wt 90D Wt ADJ WWT
146 3 7.24 34.15 35.28 39.5
616 7 8.2 38.71 41.84 43.87
859 5 7.62 33.53 35.76 39.59
Sires used in spring and fall breeding programs entered the herd the same
year.
ID WWT Value $ /20 kids $ /30 kids $ /40 kids $/50 kids
146 34.15 $58.05 $1,161.10 $1,741.65 $2,322.20 $2,902.75
616 38.71 $65.81 $1,316.14 $1,974.21 $2,632.28 $3,290.35
859 33.53 $57.00 $1,140.02 $1,710.03 $2,280.04 $2,850.05
* Price based on $1.70/lb kid price in the 40 to 60 lb range.
• At this price with only 20 kids of average
weight, $176.12 difference in income.
• With 50 kids the difference is $440.30.
• This value difference could cover the cost of
membership for several years in NSIP.
 Currently the NSIP version provides genetic evaluation
of goats across different breeds and across different
flocks within a breed group.
 KIDPLAN is the goat version of LAMBPLAN, this is
the program used by NSIP.
 An Australian Sheep Breeding Value (ASBV) describes
a goat’s genetic performance expressed in terms of the
expected genetic performance of it’s offspring.
 The breeding value is calculated by a BLUP analysis
that can include information on the goat’s own
performance and/or its relative’s performance.
 ASBV data is submitted to KIDPLAN through NSIP by
members.
 Birth Weight (BWT) - direct genetic effects on weight at birth. It is
positively correlated with weaning and postweaning body weight
EBVs.
 Maternal Birth Weight (MBWT) - genetic effects of the doe on the
birth weight of her kids.
 Weaning Weight (WWT) – direct genetic effect on preweaning
growth potential.
 Maternal Weaning Weight (MWWT) - estimates genetic merit for
mothering ability, mainly reflects genetic differences in doe milk
production though other aspects of maternal behavior may also be
involved.
 Postweaning Weight (PWWT) - combines information on
preweaning and postweaning growth to predict genetic merit for
postweaning weight at 150 days.
 Yearling Weight (YWT) – genetic merit for growth to 12 months
of age.
 Hogget Weight (HWT) - genetic effects on body weight at 18
months of age.
 Number of Kids Born (NLB) - evaluates genetic potential for
prolificacy. This EBV is expressed as numbers of kids born per
100 does kidding. Selection on Number of Kids Born EBV is
expected to increase prolificacy in the flock.
 Number of Kids Weaned (NLW) - evaluates combined doe effects
on prolificacy and kid survival to weaning. The EBV is expressed
as numbers of kids weaned per 100 does kidding. Selection on the
Number of Kids Weaned EBV is expected to increase weaning
rates in the flock.
 Scrotal Circumference (SC) - may be used to improve breeding
capacity in males and reproductive performance in females.
Selection of animals with positive Scrotal Circumference EBVs is
expected to be most useful in improving reproductive
performance in young does via desirable effects on rate of sexual
maturation.
 Worm Egg Count (WEC) - evaluates genetic merit for parasite
resistance based on worm egg counts recorded at weaning or at
early or late postweaning ages. Animals with low Worm Egg
Count EBVs are expected to have greater parasite resistance, and
selection to reduce Worm Egg Count EBVs is recommended in
areas where internal parasites are a problem.
 Postweaning Fat Depth (CF) – evaluates genetic differences in
carcass fatness between the 12th and 13th ribs. It is derived from
ultrasonic measurements of fat depth in live animals and adjusted
to standard weights of 110 lb. (55 kg).
 Postweaning Loin Muscle Depth (EMD) – evaluates genetic
differences in muscling. It is derived from ultrasonic
measurements of loin muscle depth between the 12th and 13th ribs
in live animals and adjusted to standard weights of 110 lb. (55 kg).
 Scanning data must be accompanied by a body weight and
recorded at the same time as (or at least within ± 7 days of) the
corresponding postweaning or yearling weights. Scans must be
conducted by a certified technician.
 BVs are designed to be used to compare the genetic
potential of animals independent of the environment and
location.
 The traits to focus on will depend on your herd objectives
and markets.
 When selecting, consider your current performance and
where you wish to move your herd.
 The program provides some Selection Indexes that can be
used as a way of weighing up different traits for a particular
breeding objective.
 Indexes can be helpful to narrow down selection however
the individual trait values must be considered.
 The program also provides percentile band reports can be
useful to determine how an animal ranks relative to the rest
of the breed for individual traits.
BWT WWT PWWT YWT HWT CF WEC
Top Value -0.2 4.4 7.1 8.7 9.8 -0.1 -2
Top 1 % -0.16 3.6 5.6 7 7.8 -0.1
Top 5% -0.12 2.9 4.6 5.8 6.6 -0.1
Top 10% -0.09 2.1 3.8 4.7 5.5 -0.1 -2
Top 20% -0.05 1.2 2.3 3 3.4 -0.1 -1
Top 30% -0.01 0.9 1.5 2.2 2.5 -0.1 -1
Top 40% 0.01 0.6 1 1.8 2 0 1
Top 50% 0.03 0.4 0.6 1.3 1.5 0 3
Top 60% 0.06 0.2 0.2 0.8 1 0.1 5
Top 70% 0.1 0 -0.1 0.4 0.5 0.1 6
Top 80% 0.13 -0.2 -0.5 0 0 0.1 10
Top 90% 0.19 -0.5 -1.1 -0.8 -0.8 0.1 10
Bottom value 0.39 -2 -4.3 -4.5 -3.4 0.2 12
ID BWT WWT PWWTPFAT WEC MWWT Carcass Plus SRC
Sire 1 0.3 1.2 1.9 -0.6 109 102
72% 79% 82% 20% 63% 39%
Sire 2 0.05 1.8 208 -0.06 116 106
83% 86% 89% 36% 69% 43%
Sire 3 -0.07 -0.1 -0.3 -0.03 98 99
80% 83% 87% 19% 67% 40%
Sire 4 -0.01 -0.04 -1.1 -0.4 93 96
52% 41% 49% 10% 35% 22%
Sire 5 -0.08 0.6 1.9 -3 -0.2 111 100
88% 93% 95% 61% 73% 75% 58%
Sire 6 0.18 0.5 0.3 -0.4 103 90
81% 85% 87% 45% 69% 49%
Sire 7 -0.01 -1.1 -1.2 -0.2 93 87
81% 85% 88% 55% 71% 54%
 Easy to participate in the program.
 Sign up information can be found at:
http://nsip.org/.
 Fees are explained on the enrolment sheet.
 At this time there is a need for goat producers
to participate.
 We can make progress but we must have
participation.
 Genetic progress can only be made through
evaluation and selection towards a set of goals.
 EBV’s are a critical tool to use in comparing
animals on genetic potential.
 Progress from individual data is limited,
participation in NSIP will greatly improve
accuracy of selection and result in sustainable
improvement in performance.
“In each generation of animals in his herd or
flock, the breeder must select those to be saved
for breeding from those to be used for other
purposes. Perhaps he will also select animals
from other herds for use as breeders in his.
These are the most important things he does.”
Breeding Better Livestock. Rice, Andrews, and Warwick 1953

Contenu connexe

Tendances

The Economics of Heat Stress- Albert DeVries
The Economics of Heat Stress- Albert DeVriesThe Economics of Heat Stress- Albert DeVries
The Economics of Heat Stress- Albert DeVriesDAIReXNET
 
Dr. Mark Knauer - Evaluating Body Condition & Reproductive Performance
Dr. Mark Knauer - Evaluating Body Condition & Reproductive PerformanceDr. Mark Knauer - Evaluating Body Condition & Reproductive Performance
Dr. Mark Knauer - Evaluating Body Condition & Reproductive PerformanceJohn Blue
 
Dr. George Foxcroft - Risk Factors For Sow Culling
Dr. George Foxcroft - Risk Factors For Sow CullingDr. George Foxcroft - Risk Factors For Sow Culling
Dr. George Foxcroft - Risk Factors For Sow CullingJohn Blue
 
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity John Blue
 
Finding More Value With Genomic Testing
Finding More Value With Genomic TestingFinding More Value With Genomic Testing
Finding More Value With Genomic TestingDAIReXNET
 
Discovering Hidden Feed Costs for the Milking Herd
Discovering Hidden Feed Costs for the Milking HerdDiscovering Hidden Feed Costs for the Milking Herd
Discovering Hidden Feed Costs for the Milking HerdDAIReXNET
 

Tendances (20)

Buck development
Buck developmentBuck development
Buck development
 
The value of EBVs for the US meat goat industry
The value of EBVs for the US meat goat industryThe value of EBVs for the US meat goat industry
The value of EBVs for the US meat goat industry
 
The Economics of Heat Stress- Albert DeVries
The Economics of Heat Stress- Albert DeVriesThe Economics of Heat Stress- Albert DeVries
The Economics of Heat Stress- Albert DeVries
 
Growth and performance of lambs and kids on pasture
Growth and performance of lambs and kids on pastureGrowth and performance of lambs and kids on pasture
Growth and performance of lambs and kids on pasture
 
Replacement ewe selection and culling underperforming ewes
Replacement ewe selection and culling underperforming ewesReplacement ewe selection and culling underperforming ewes
Replacement ewe selection and culling underperforming ewes
 
Tips for Improving Lambing/Kidding Percentage
Tips for Improving Lambing/Kidding PercentageTips for Improving Lambing/Kidding Percentage
Tips for Improving Lambing/Kidding Percentage
 
Raising your own replacements
Raising your own replacementsRaising your own replacements
Raising your own replacements
 
PastureNutritionIV
PastureNutritionIVPastureNutritionIV
PastureNutritionIV
 
Ewe efficiency
Ewe efficiencyEwe efficiency
Ewe efficiency
 
Dr. Mark Knauer - Evaluating Body Condition & Reproductive Performance
Dr. Mark Knauer - Evaluating Body Condition & Reproductive PerformanceDr. Mark Knauer - Evaluating Body Condition & Reproductive Performance
Dr. Mark Knauer - Evaluating Body Condition & Reproductive Performance
 
Dr. George Foxcroft - Risk Factors For Sow Culling
Dr. George Foxcroft - Risk Factors For Sow CullingDr. George Foxcroft - Risk Factors For Sow Culling
Dr. George Foxcroft - Risk Factors For Sow Culling
 
Challenges to moving to a performance-based flock
Challenges to moving to a performance-based flockChallenges to moving to a performance-based flock
Challenges to moving to a performance-based flock
 
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity
Dr. Rob Knox - Gilt Management/Puberty Induction and Sow Longevity/Productivity
 
Crossbreeding with Katahdins
Crossbreeding with KatahdinsCrossbreeding with Katahdins
Crossbreeding with Katahdins
 
Breeding better sheep
Breeding better sheepBreeding better sheep
Breeding better sheep
 
10 Things Every Goat Producers Should Do
10 Things Every Goat Producers Should Do10 Things Every Goat Producers Should Do
10 Things Every Goat Producers Should Do
 
Can you make money with a small flock (or herd)?
Can you make money with a small flock (or herd)?Can you make money with a small flock (or herd)?
Can you make money with a small flock (or herd)?
 
Finding More Value With Genomic Testing
Finding More Value With Genomic TestingFinding More Value With Genomic Testing
Finding More Value With Genomic Testing
 
Breeding systems
Breeding systemsBreeding systems
Breeding systems
 
Discovering Hidden Feed Costs for the Milking Herd
Discovering Hidden Feed Costs for the Milking HerdDiscovering Hidden Feed Costs for the Milking Herd
Discovering Hidden Feed Costs for the Milking Herd
 

Similaire à How the goat industry can benefit from NSIP

An Overview of Genomic Selection and Fertility
An Overview of Genomic Selection and FertilityAn Overview of Genomic Selection and Fertility
An Overview of Genomic Selection and FertilityDAIReXNET
 
Complementarity of value chain analysis, consumption patterns and nutrition i...
Complementarity of value chain analysis, consumption patterns and nutrition i...Complementarity of value chain analysis, consumption patterns and nutrition i...
Complementarity of value chain analysis, consumption patterns and nutrition i...ILRI
 
Slideshare wws spring 2015
Slideshare  wws spring 2015Slideshare  wws spring 2015
Slideshare wws spring 2015Wws Ireland
 
Dr. Ken Stalder - Industry Productivity Analysis
Dr. Ken Stalder - Industry Productivity AnalysisDr. Ken Stalder - Industry Productivity Analysis
Dr. Ken Stalder - Industry Productivity AnalysisJohn Blue
 
Dr. Ken Stalder - Pork Industry Productivity Analysis
Dr. Ken Stalder - Pork Industry Productivity AnalysisDr. Ken Stalder - Pork Industry Productivity Analysis
Dr. Ken Stalder - Pork Industry Productivity AnalysisJohn Blue
 
Pork Industry Productivity Analysis
Pork Industry Productivity AnalysisPork Industry Productivity Analysis
Pork Industry Productivity AnalysisNational Pork Board
 
Sustainable Use of Animal Genetic Resources - Examples from Uganda & Rwanda
Sustainable Use of Animal Genetic Resources - Examples from Uganda & RwandaSustainable Use of Animal Genetic Resources - Examples from Uganda & Rwanda
Sustainable Use of Animal Genetic Resources - Examples from Uganda & RwandaSIANI
 
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...John B. Cole, Ph.D.
 
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime Productivity
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime ProductivityDr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime Productivity
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime ProductivityJohn Blue
 
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...2damcreative
 
Northcoast Lamp Co-Op 2016 OEFFA Workshop
Northcoast Lamp Co-Op 2016 OEFFA WorkshopNorthcoast Lamp Co-Op 2016 OEFFA Workshop
Northcoast Lamp Co-Op 2016 OEFFA WorkshopLaura DeYoung
 
360° Benchmarking for Pork Production
360° Benchmarking for Pork Production360° Benchmarking for Pork Production
360° Benchmarking for Pork ProductionNational Pork Board
 
Vasse presentation stephen lee
Vasse presentation stephen leeVasse presentation stephen lee
Vasse presentation stephen leeVasseSep2010
 
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivity
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivityDr. Joe Cassady - Effects of preweaning factors on sow lifetime productivity
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivityJohn Blue
 
From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...ILRI
 
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...essp2
 
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implic...
The increasing costs of Animal Source Foods in Ethiopia:  Evidence and Implic...The increasing costs of Animal Source Foods in Ethiopia:  Evidence and Implic...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implic...essp2
 

Similaire à How the goat industry can benefit from NSIP (20)

Irish catalog
Irish catalogIrish catalog
Irish catalog
 
An Overview of Genomic Selection and Fertility
An Overview of Genomic Selection and FertilityAn Overview of Genomic Selection and Fertility
An Overview of Genomic Selection and Fertility
 
Complementarity of value chain analysis, consumption patterns and nutrition i...
Complementarity of value chain analysis, consumption patterns and nutrition i...Complementarity of value chain analysis, consumption patterns and nutrition i...
Complementarity of value chain analysis, consumption patterns and nutrition i...
 
Slideshare wws spring 2015
Slideshare  wws spring 2015Slideshare  wws spring 2015
Slideshare wws spring 2015
 
Dr. Ken Stalder - Industry Productivity Analysis
Dr. Ken Stalder - Industry Productivity AnalysisDr. Ken Stalder - Industry Productivity Analysis
Dr. Ken Stalder - Industry Productivity Analysis
 
Dr. Ken Stalder - Pork Industry Productivity Analysis
Dr. Ken Stalder - Pork Industry Productivity AnalysisDr. Ken Stalder - Pork Industry Productivity Analysis
Dr. Ken Stalder - Pork Industry Productivity Analysis
 
Pork Industry Productivity Analysis
Pork Industry Productivity AnalysisPork Industry Productivity Analysis
Pork Industry Productivity Analysis
 
Selective Procedures for Meat Goat Breeding Programs
Selective Procedures for Meat Goat Breeding ProgramsSelective Procedures for Meat Goat Breeding Programs
Selective Procedures for Meat Goat Breeding Programs
 
Sustainable Use of Animal Genetic Resources - Examples from Uganda & Rwanda
Sustainable Use of Animal Genetic Resources - Examples from Uganda & RwandaSustainable Use of Animal Genetic Resources - Examples from Uganda & Rwanda
Sustainable Use of Animal Genetic Resources - Examples from Uganda & Rwanda
 
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...
Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...
 
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime Productivity
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime ProductivityDr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime Productivity
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime Productivity
 
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...
8. Friday - Ruminant Sessions dr bill stone diamond v tech service director -...
 
Northcoast Lamp Co-Op 2016 OEFFA Workshop
Northcoast Lamp Co-Op 2016 OEFFA WorkshopNorthcoast Lamp Co-Op 2016 OEFFA Workshop
Northcoast Lamp Co-Op 2016 OEFFA Workshop
 
360° Benchmarking for Pork Production
360° Benchmarking for Pork Production360° Benchmarking for Pork Production
360° Benchmarking for Pork Production
 
2015 Benchmarking Performance
2015 Benchmarking Performance2015 Benchmarking Performance
2015 Benchmarking Performance
 
Vasse presentation stephen lee
Vasse presentation stephen leeVasse presentation stephen lee
Vasse presentation stephen lee
 
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivity
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivityDr. Joe Cassady - Effects of preweaning factors on sow lifetime productivity
Dr. Joe Cassady - Effects of preweaning factors on sow lifetime productivity
 
From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...From contemporary comparison to genomic selection: Trends in the principles f...
From contemporary comparison to genomic selection: Trends in the principles f...
 
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implica...
 
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implic...
The increasing costs of Animal Source Foods in Ethiopia:  Evidence and Implic...The increasing costs of Animal Source Foods in Ethiopia:  Evidence and Implic...
The increasing costs of Animal Source Foods in Ethiopia: Evidence and Implic...
 

Plus de University of Maryland Extension Small Ruminant Program

Plus de University of Maryland Extension Small Ruminant Program (20)

Making a profit with small ruminants (sheep/goats)
Making a profit with small ruminants (sheep/goats)Making a profit with small ruminants (sheep/goats)
Making a profit with small ruminants (sheep/goats)
 
Health Care of Pregnant ewes
Health Care of Pregnant ewesHealth Care of Pregnant ewes
Health Care of Pregnant ewes
 
Hoof Care of Sheep/Goats
Hoof Care of Sheep/GoatsHoof Care of Sheep/Goats
Hoof Care of Sheep/Goats
 
Proper deworming methods
Proper deworming methodsProper deworming methods
Proper deworming methods
 
Show me the signs
Show me the signsShow me the signs
Show me the signs
 
Copper: its complicated
Copper: its complicatedCopper: its complicated
Copper: its complicated
 
Pregnancy Toxemia in sheep
Pregnancy Toxemia in sheepPregnancy Toxemia in sheep
Pregnancy Toxemia in sheep
 
Goat Hoof Health
Goat Hoof HealthGoat Hoof Health
Goat Hoof Health
 
MinimizingDrugUse
MinimizingDrugUseMinimizingDrugUse
MinimizingDrugUse
 
Beyond antibiotics: minimizing drug use in small ruminants
Beyond antibiotics: minimizing drug use in small ruminantsBeyond antibiotics: minimizing drug use in small ruminants
Beyond antibiotics: minimizing drug use in small ruminants
 
Goats 101
Goats 101Goats 101
Goats 101
 
Marketing them
Marketing themMarketing them
Marketing them
 
Keeping them healthy
Keeping them healthyKeeping them healthy
Keeping them healthy
 
Feeding them
Feeding themFeeding them
Feeding them
 
Raising them
Raising themRaising them
Raising them
 
Sheep 101
Sheep 101Sheep 101
Sheep 101
 
Management of Internal Parasites in Small Ruminants
Management of  Internal Parasites in Small RuminantsManagement of  Internal Parasites in Small Ruminants
Management of Internal Parasites in Small Ruminants
 
FAMACHA For the Control of Barber Pole Worm (Haemonchus contortus) in Small R...
FAMACHA For the Control of Barber Pole Worm (Haemonchus contortus) in Small R...FAMACHA For the Control of Barber Pole Worm (Haemonchus contortus) in Small R...
FAMACHA For the Control of Barber Pole Worm (Haemonchus contortus) in Small R...
 
Dewormers and Dewormer Resistance: Introduction to Eye Scores
Dewormers and Dewormer Resistance: Introduction to Eye ScoresDewormers and Dewormer Resistance: Introduction to Eye Scores
Dewormers and Dewormer Resistance: Introduction to Eye Scores
 
FAMACHA eye anemia system
FAMACHA eye anemia systemFAMACHA eye anemia system
FAMACHA eye anemia system
 

Dernier

ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTiammrhaywood
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxiammrhaywood
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️9953056974 Low Rate Call Girls In Saket, Delhi NCR
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYKayeClaireEstoconing
 
Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxAshokKarra1
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfTechSoup
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxDr.Ibrahim Hassaan
 
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxGrade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxChelloAnnAsuncion2
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Celine George
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxAnupkumar Sharma
 
Science 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxScience 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxMaryGraceBautista27
 
ENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomnelietumpap1
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxthorishapillay1
 

Dernier (20)

ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPTECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
ECONOMIC CONTEXT - LONG FORM TV DRAMA - PPT
 
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for Beginners
 
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptxLEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
LEFT_ON_C'N_ PRELIMS_EL_DORADO_2024.pptx
 
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptxFINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
FINALS_OF_LEFT_ON_C'N_EL_DORADO_2024.pptx
 
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
call girls in Kamla Market (DELHI) 🔝 >༒9953330565🔝 genuine Escort Service 🔝✔️✔️
 
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITYISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
 
Karra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptxKarra SKD Conference Presentation Revised.pptx
Karra SKD Conference Presentation Revised.pptx
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdfInclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
Inclusivity Essentials_ Creating Accessible Websites for Nonprofits .pdf
 
Gas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptxGas measurement O2,Co2,& ph) 04/2024.pptx
Gas measurement O2,Co2,& ph) 04/2024.pptx
 
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptxGrade 9 Q4-MELC1-Active and Passive Voice.pptx
Grade 9 Q4-MELC1-Active and Passive Voice.pptx
 
Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17Difference Between Search & Browse Methods in Odoo 17
Difference Between Search & Browse Methods in Odoo 17
 
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptxMULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
MULTIDISCIPLINRY NATURE OF THE ENVIRONMENTAL STUDIES.pptx
 
OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...OS-operating systems- ch04 (Threads) ...
OS-operating systems- ch04 (Threads) ...
 
Science 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptxScience 7 Quarter 4 Module 2: Natural Resources.pptx
Science 7 Quarter 4 Module 2: Natural Resources.pptx
 
ENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choomENGLISH6-Q4-W3.pptxqurter our high choom
ENGLISH6-Q4-W3.pptxqurter our high choom
 
Proudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptxProudly South Africa powerpoint Thorisha.pptx
Proudly South Africa powerpoint Thorisha.pptx
 

How the goat industry can benefit from NSIP

  • 1. Dr. Ken Andries Collage of Agriculture, Food Science, and Sustainable Systems Kentucky State University
  • 2. J.L. Lush, Animal Breeding Plans. 1945
  • 3.  Dairy herds started measuring performance in the 50’s and 60’s for milk production.  Beef cattle started BIF to standardize Performance programs in 1968.  Beef moved to performance pedigrees and then to EPDs in the 80’s  NSIP stared in 1986 and produced flock EPD for sheep and offered to Meat Goat Industry.  Research into use of DNA assisted selection (genomics) in the 2000’s for many species.
  • 4.  Average weaning weight has increased by 150% (175 lbs.) with only a small increases in birth weight.  Calving difficulty has been reduced greatly.  Carcass traits are now an economical trait for cow/calf producers  Most commercial beef cattle producers utilize data in selecting bulls.  AI has become very wide spread in the commercial industry partly due to performance data.  Key point: it did not happen over night and started with simple data collection.
  • 5.  Austria started in 1990.  Quality issues were identified as a problem as wool market was decreasing.  Research and selection resulted in increased carcass weight and increased economic value.  Most of the increase was due to improved performance (growth).  A common industry goal of improved meat quality was part of the success.  LAMBPLAN was key to allowing producers to improve selection effectiveness.
  • 6.  Reproduction has one of the greatest impacts on profitability.  Growth traits are often second in importance.  Health traits influence both reproduction and growth greatly so they are critical.  For meat goats, currently carcass traits have less value due to market trends.  To be profitable we must optimize reproduction, growth, and health traits.
  • 7.  Average goat producer keeps no records of performance.  Basic performance records from birth to weaning can be used to make progress.  Adjusted weights provide a better picture of performance, remove some environmental factors.  EBVs and EPDs are possible with meat goats if we have data to process.
  • 8. Variable Observations Mean Std Deviation Birth Weight 7791 7.55 1.73 Weaning Age 7041 89.31 20.13 Weaning Weight 7022 37.47 11.68 Average Daily Gain 6910 0.42 0.11 Weight per day of age 7022 0.52 0.12 90 day Weight 7023 38.23 10.55 Adjusted Weaning Weight 6986 43.41 12.65 Number Born 4501 1.84 0.65 Number Weaned 4376 1.59 0.69
  • 9.  Data collection gives you information to make progress towards goals.  Can impact health traits as well as performance.  Individual data such as on-farm performance data is not as effective as national evaluations.  Individual/on-farm data only apply to individuals within the contemporary group.  This limits their use when purchasing or comparing individuals from multiple groups.
  • 10. Year BWT WWT Age at Wean ADG 90DWT AWWT 2008 7.28 32.52 89.88 0.28 32.94 35.80 2009 7.65 26.35 71.50 0.26 31.02 36.07 2010 7.43 29.89 67.40 0.34 38.07 41.29 2011 6.95 25.38 60.98 0.30 34.10 36.87 2012 6.54 30.76 96.91 0.25 29.05 31.62 2013 7.01 27.08 84.02 0.25 29.49 31.34 • Purchase of a large number of yearlings that entered production in 2011 and 2012. • Introduction of the purchased doe kids and breed sires, without data, moved our selection back several years.
  • 12. ID Seasons BWT WN Wt 90D Wt ADJ WWT 146 3 7.24 34.15 35.28 39.5 616 7 8.2 38.71 41.84 43.87 859 5 7.62 33.53 35.76 39.59 Sires used in spring and fall breeding programs entered the herd the same year.
  • 13. ID WWT Value $ /20 kids $ /30 kids $ /40 kids $/50 kids 146 34.15 $58.05 $1,161.10 $1,741.65 $2,322.20 $2,902.75 616 38.71 $65.81 $1,316.14 $1,974.21 $2,632.28 $3,290.35 859 33.53 $57.00 $1,140.02 $1,710.03 $2,280.04 $2,850.05 * Price based on $1.70/lb kid price in the 40 to 60 lb range. • At this price with only 20 kids of average weight, $176.12 difference in income. • With 50 kids the difference is $440.30. • This value difference could cover the cost of membership for several years in NSIP.
  • 14.  Currently the NSIP version provides genetic evaluation of goats across different breeds and across different flocks within a breed group.  KIDPLAN is the goat version of LAMBPLAN, this is the program used by NSIP.  An Australian Sheep Breeding Value (ASBV) describes a goat’s genetic performance expressed in terms of the expected genetic performance of it’s offspring.  The breeding value is calculated by a BLUP analysis that can include information on the goat’s own performance and/or its relative’s performance.  ASBV data is submitted to KIDPLAN through NSIP by members.
  • 15.  Birth Weight (BWT) - direct genetic effects on weight at birth. It is positively correlated with weaning and postweaning body weight EBVs.  Maternal Birth Weight (MBWT) - genetic effects of the doe on the birth weight of her kids.  Weaning Weight (WWT) – direct genetic effect on preweaning growth potential.  Maternal Weaning Weight (MWWT) - estimates genetic merit for mothering ability, mainly reflects genetic differences in doe milk production though other aspects of maternal behavior may also be involved.  Postweaning Weight (PWWT) - combines information on preweaning and postweaning growth to predict genetic merit for postweaning weight at 150 days.  Yearling Weight (YWT) – genetic merit for growth to 12 months of age.  Hogget Weight (HWT) - genetic effects on body weight at 18 months of age.
  • 16.  Number of Kids Born (NLB) - evaluates genetic potential for prolificacy. This EBV is expressed as numbers of kids born per 100 does kidding. Selection on Number of Kids Born EBV is expected to increase prolificacy in the flock.  Number of Kids Weaned (NLW) - evaluates combined doe effects on prolificacy and kid survival to weaning. The EBV is expressed as numbers of kids weaned per 100 does kidding. Selection on the Number of Kids Weaned EBV is expected to increase weaning rates in the flock.  Scrotal Circumference (SC) - may be used to improve breeding capacity in males and reproductive performance in females. Selection of animals with positive Scrotal Circumference EBVs is expected to be most useful in improving reproductive performance in young does via desirable effects on rate of sexual maturation.
  • 17.  Worm Egg Count (WEC) - evaluates genetic merit for parasite resistance based on worm egg counts recorded at weaning or at early or late postweaning ages. Animals with low Worm Egg Count EBVs are expected to have greater parasite resistance, and selection to reduce Worm Egg Count EBVs is recommended in areas where internal parasites are a problem.  Postweaning Fat Depth (CF) – evaluates genetic differences in carcass fatness between the 12th and 13th ribs. It is derived from ultrasonic measurements of fat depth in live animals and adjusted to standard weights of 110 lb. (55 kg).  Postweaning Loin Muscle Depth (EMD) – evaluates genetic differences in muscling. It is derived from ultrasonic measurements of loin muscle depth between the 12th and 13th ribs in live animals and adjusted to standard weights of 110 lb. (55 kg).  Scanning data must be accompanied by a body weight and recorded at the same time as (or at least within ± 7 days of) the corresponding postweaning or yearling weights. Scans must be conducted by a certified technician.
  • 18.  BVs are designed to be used to compare the genetic potential of animals independent of the environment and location.  The traits to focus on will depend on your herd objectives and markets.  When selecting, consider your current performance and where you wish to move your herd.  The program provides some Selection Indexes that can be used as a way of weighing up different traits for a particular breeding objective.  Indexes can be helpful to narrow down selection however the individual trait values must be considered.  The program also provides percentile band reports can be useful to determine how an animal ranks relative to the rest of the breed for individual traits.
  • 19. BWT WWT PWWT YWT HWT CF WEC Top Value -0.2 4.4 7.1 8.7 9.8 -0.1 -2 Top 1 % -0.16 3.6 5.6 7 7.8 -0.1 Top 5% -0.12 2.9 4.6 5.8 6.6 -0.1 Top 10% -0.09 2.1 3.8 4.7 5.5 -0.1 -2 Top 20% -0.05 1.2 2.3 3 3.4 -0.1 -1 Top 30% -0.01 0.9 1.5 2.2 2.5 -0.1 -1 Top 40% 0.01 0.6 1 1.8 2 0 1 Top 50% 0.03 0.4 0.6 1.3 1.5 0 3 Top 60% 0.06 0.2 0.2 0.8 1 0.1 5 Top 70% 0.1 0 -0.1 0.4 0.5 0.1 6 Top 80% 0.13 -0.2 -0.5 0 0 0.1 10 Top 90% 0.19 -0.5 -1.1 -0.8 -0.8 0.1 10 Bottom value 0.39 -2 -4.3 -4.5 -3.4 0.2 12
  • 20. ID BWT WWT PWWTPFAT WEC MWWT Carcass Plus SRC Sire 1 0.3 1.2 1.9 -0.6 109 102 72% 79% 82% 20% 63% 39% Sire 2 0.05 1.8 208 -0.06 116 106 83% 86% 89% 36% 69% 43% Sire 3 -0.07 -0.1 -0.3 -0.03 98 99 80% 83% 87% 19% 67% 40% Sire 4 -0.01 -0.04 -1.1 -0.4 93 96 52% 41% 49% 10% 35% 22% Sire 5 -0.08 0.6 1.9 -3 -0.2 111 100 88% 93% 95% 61% 73% 75% 58% Sire 6 0.18 0.5 0.3 -0.4 103 90 81% 85% 87% 45% 69% 49% Sire 7 -0.01 -1.1 -1.2 -0.2 93 87 81% 85% 88% 55% 71% 54%
  • 21.  Easy to participate in the program.  Sign up information can be found at: http://nsip.org/.  Fees are explained on the enrolment sheet.  At this time there is a need for goat producers to participate.  We can make progress but we must have participation.
  • 22.  Genetic progress can only be made through evaluation and selection towards a set of goals.  EBV’s are a critical tool to use in comparing animals on genetic potential.  Progress from individual data is limited, participation in NSIP will greatly improve accuracy of selection and result in sustainable improvement in performance.
  • 23. “In each generation of animals in his herd or flock, the breeder must select those to be saved for breeding from those to be used for other purposes. Perhaps he will also select animals from other herds for use as breeders in his. These are the most important things he does.” Breeding Better Livestock. Rice, Andrews, and Warwick 1953