Estado actual de los conocimientos sobre genética y
la mejora del ganado caprino
(Present knowledge on goats: breeding and genetics)
Juan M. SerradillaDepartamento de Producción Animal
ETSIAM. Universidad de Có[email protected]
Máster de Mejora Genética Animal y Biotecnología de la reproducción
Valencia (Spain), April 23-24 2010CIHEAM UPV-UAB
Ernesto A. GómezCentro deTecnología Animal
Instituto Valenciano de Investigaciones [email protected]
GOATS DISTRIBUTION IN THE WORLD
STATE OF THE ART
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BarbariNubia
Boer
Mancha
Criolla
SaanenAlpinaToggenburg
Murciano-GMalagueñaACC
Damasco
SaanenAlpinaToggenburgMurciano-granadina
GOATS CENSUS AND YIELDS IN THE WORLD (2008)
Area Census2005 Meat Carcass weight Milk (x106) (x103 Tm) (kg/canal) (x103 Tm)
Africa 244 1152 12 3200
Estimated census in the Mediterranean area was 38 millions (Gabiña y Serradilla, 1999).
World 827 4919 12 15215
Asia 523 3470 12 8887Europe 18 124 10 2583America 40 149 14 542Oceania 1 23 21 0...
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STATE OF THE ART
Nigeria Etiopía
China, India,Turquía
México, Brasil, ArgentinaGrecia, España
STATE OF THE ART
Most goats in the world
are not milked
are milked for a family subsistence economy
Genetic programmes have always been developed
Recent development (since 50’s or 60’s)
In very organised milk marketing situations
Breeding through selection in pure breed
Effective programmes only in USA Canada, Norway and France
(1987) (1992)
Emerging programmes in other countries: U.K., Belgium, Italy, Mexico and Spain.
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Centro de Inseminación
Centro de Investigación
Asociación de ganaderos
Apoyo inicial administración
Controles productivos
Genealogías
Evaluación genética
Programa de Inseminación
Innovaciones protocolos
What do SELECTION PROGRAMMES require?
A breeders organisation with scientific and technical support, to:
Define the objectives and selection criteria
Carry out milk recording
Define and optimise a selection scheme
Implement tools like A.I.
Financial support, coming from:
Breeders, associations
Public investments
STATE OF THE ART
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En el centro de investigación se analizan esos datos y se estima qué animales son mejores (catálogo de
sementales)
Las asociaciones participan en recogida de datos
Los ganaderos, en función de la información dada por el centro de investigación, deciden qué
animales comprar y/o dejar como reproductoras
En el centro de inseminación se dispone de machos de alto valor genético que se utilizan para hacer inseminación artificial en las ganaderías que
participan en el programa de mejora. Esos machos proceden de las ganaderías.
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
They depend on milk destiny -In most cases = cheese
Main objective: Increase milk production and its cheese yield- Milk yield or protein yield/lactation- Protein (mainly casein) and fat contents- Lactose (Norway)
Other objectives:
- Breeding the standard, culling undesired animals
- Life in herd: longevity
morphological (mainly udder)
milking traits
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Índices no estáticos• Para mejorar leche sin penalizar contenido
– Combinación de FY y PY sustituyendo a MY– Incluir además FC y PC
• Francia:• 1995: ICC = PY + 0,4 PC• 1999: ICC = PY + 0,4 PC + 0,2 FY + 0,1 FC• 2007: Alpina 0,56 ICC + 0,44 IMC
Saanen 0,67 ICC + 0,33 IMC(IMC incluye: perfil, altura, inserción posterior y forma posterior de la ubre)
• Canadá:• Pindx: leche y grasa• MSindx: ubre (sistema mamario, inserción delantera y trasera y ligamento)• Tindx: MSindx y caracteres corporales (general, patas, capacidad, carácter
lechero)• = 0,6 Pindx + 0,4 Tindx
OTHER OBJECTIVES: LONGEVITY (HERD LIFE)
HERD-LIFE ANALYSIS OF A NUCLEUS OF MALAGUEÑA BREED
< 6% of goats reach 6ª lactation
Average number of lactation per goat = 2,58
No correlation between longevity and first lactation yield
Longevity is neither correlated to yields in latest lactation
Low longevity values seem to be mainly caused by casualties due to diseases and high rate of discarding MOSTLY due to udder problems
Selection for morphological traits correlated with lifespan is needed
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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BREEDING OBJECTIVES AND MAIN TRAITS FOR MEAT PRODUCTION
Related to kid production (growth and conformation)
When kids are sacrificed before/at weaning (30-45 days): the same objectives
used for milk yield
When kids are slaughtered later (60-90 days old):- Dairy and growth are negatively correlated with carcass and
conformation traits - Different breeding objectives- Different breeds or lines- None breeder’s selection schemes exist nowadays for kid’s growth and
conformation
Traits: Reproduction: fertility, litter sizeGrowth (weigths: birth, weaning and slaughter) and conformationResistance disease
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BREEDING OBJECTIVES AND MAIN TRAITS FOR FIBER PRODUCTION
MOHAIR & CASHMERE
Fleece yield, weight and density
Fibre diameter and length
Face cover (undesired)
Percentage of low quality fibre
Litter size, growth and conformation
Negative correlation between reproduction traits and fibre yield
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Fibra, 50% SudáfricaLana, China
MILK RECORDING
General characteristics of goat’s milk recording schemes:
High cost per unit of product (in relation to dairy cows)
Low herd sizes
ICRPMA (International Committee for Recording Productivity of
Milk Animals) admits a minimum of 4 records during the first 5
months of lactation.
- However, the frequency of records depends on each situation
- This Committee also admits the A4 system: one milking per day in the case of double milked goats
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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MILK RECORDING FREQUENCYComparison of estimations of milk yields obtained with records registered every month and every two months (simplified methods) vs. the reference recorded twice a month (reference method) (Number of lactations registered: 298 Murciano-Granadina, 842 Malagueña and 369 Payoya)
Pearson’s correlation coefficients (1st row), error % (1) (2nd row) and average bias (3rd row)
210 days
(1) variance (reference method-simplified method) / variance (reference method) (Poly & Poutous, 1967)
0,99 0,94 0,982,31 5,83 4,36
4,9 10,4 14,2Monthly
Every twomonths
0,96 0,92 0,947,75 13,1 10,619,8 26,9 30,5
Source:Hernández et al., 1992
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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Milk yield standardized to Recording Murciano Malagueña Payoyafrequency Granadina
MILK RECORDING OF DOUBLE MILKED GOATSSimplifying double milking recording
Recording Methods:
AFm Only morning milking recorded
AFt Only evening milking recorded
ATm Alternating recording, starting in the morning
ATt Alternating recording, starting in the evening
AFCm /AFCt /ATCm / ATCt Former methods with the following correction:
Daily yield
recorded yieldC=
Data from::Breed: Murciano -Granadina Reference : Both milking records registered monthlyNo. of herds: 22 No. of Lactations: 1327
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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MILK RECORDING OF DOUBLE MILKED GOATS
Simplifying double milking recordingAverage bias (kg) of milk yields estimated with different simplified methods (values in parenthesis are estimated yields recording morning and evening milking)
Método First day: only one recordUnadjusted Adjusted Unadjusted Adjusted
yield yield yield yield(488 kg) 210(436kg) 240 (458kg) 210 240
AFm -22.41 -17.78 -19.71 -17.75 -13.18 -15.12 AFt +23.00 + 17.78 +19.69 +17.72 +13.22 +15.13 ATm -3.57 -3.35 -3.50 -2.71 -3.09 ATt +4.23 +3.35 +2.68 +3.13 AFCm +0.49 -10.60 -4.36 +7.46 -4.39 AFCt -0.53 +10.64 -4.85 -0.26 -7.89 -5.00 ATCm -3.97 -0.70 -5.39 ATCt -0.12 +0.47 +5.25 +0.49 -2.28 -4.00
Source: Hernández et al., 1990
First day: two records
+0.08 -0.43
+3.47+0.05
-0.84
-2.99+3.00
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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MILK RECORDING - NURSING GOATS
Natural lactation of kids generates difficulties to milk recording
Less reliable records (particularly of dams)
Missing records
First control is recorded very late
Variable periods elapsed between kidding and first record
Solutions
Artificial lactation
Early and regular weaning of all replacement kids
BREEDING OBJECTIVES AND MAIN TRAITS FOR MILK PRODUCTION
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MILK RECORDING -ESTIMATING YIELDS OF NURSING GOATS
Pearson’s (CC) and Spearman’s (CR) coefficients of correlation between rankings of goats obtained with milk yields estimated with different methods and their corresponding BLUP values (higher values correspond to better results)
CC production. CC BLUP values CR production CR BLUP values
FUWO2 0,983 0,971 0,981 0,970REOC 0,877 0,967 0,978 0,961FUWO1 0,977 0,965 0,974 0,960PIWO 0,976 0,963 0,977 0,961TIRE 0,969 0,955 0,971 0,955LCCH 0,956 0,958 0,954 0,949
1st record not used 0,984 0,973 0,984 0,971
Source: Sánchez Palma et al., 1998
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Caracteres funcionales
• Diferentes propuestas: ADGA (1993), Francia, España (Sánchez et al., 2009)
• Ubre– Ligamento suspensor, Profundidad, Implantación,…
• Pezones– Tamaño, colocación
• Conformación general
• Baja correlación ubre-producción• Correlación negativa con ligamento suspensor
Caracteres de sanidad de la ubre
• SCC: células somáticas– Diferente a vacuno y ovino– Correlación nula con producción
• Recuento bacteriano: más recomendado en caprino.
• CMT (California mastitis test): cualitativo
Cinética de ordeño
• Velocidad de ordeño– h2 muy alta (0,5). Posible gen mayor.
• Menor importancia oxitocina por leche cisternal• Caracteres (producciones, tiempos y flujos)
– Flujo primer minuto– Flujo medio (f.leche máquina, f. apurado)– Duración del ordeño
Fuentes de variación• Rebaño-año-estación(-raza), mes, época parto• Nº lactación• Nº nacidos• Días de lactación (lineal y cuadrática)• Días de secado de lactación anterior• Edad al primer parto para primíparas• Efecto materno
SOURCES OF ENVIRONMENTAL VARIATION
Records (milk yield, protein content, udder scores, etc) are the consequence of genetics and environmental effects. To estimate breeding values we need to “separate” them.
For that we consider two types of environmental effects:
- Those with known categories where to classify animals(fixed effects) can be corrected
- Those which act in a continuous random way (random effect) model error (e)
Sire effectAnimal effect
Permanent effectMaternal (genetic) effect
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Environmental fixed factors influencing milk yield in Murciano-Granadina (MG), Malagueña (M), Payoya (P) and Verata (V) breeds. Average milk yields of the different categories
Parity number(*) Season No. of kids No. of milking
Sources: (1) Hernández, 1991(2) Díaz, 1993(3) Rabasco et al., 1993
(*) All lactations over 5th have been classified in this category
190 278 245 222 314 312 343 266 310 285 328341 456 476 443 243 274 247 302 245221 245 277 301
212 278 259 217315 297 235 181311 361 208 243497 340 278 399373 306 218263 264 247
245 274 323 257 321 374279 283 283 391 477 490 251 283 278 298 320
180 293285 485
1 2 3 4 5 A W Sp Su 1 2 3 1 2
MG (1)
MG (2)
M(1)
M(2)
P(1)
V(3)
SOURCES OF ENVIRONMENTAL VARIATION
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Caracteres fertilidad
• Muy baja heredabilidad– Tasa de preñez– Tiempo hasta concepción
• Desestacionalizar
For milk yield and composition:fat, lactose, protein, whole casein and casein fractions
Herd and year of kidding significantly influence all variables in all breeds
Kidding season affect significantly all variables except
and
casein contents
Parity number is a significant factor in all variables except casein fractions
The number of kids born only affects significantly milk yield in some breeds
Significant interactions exists among these factors which vary from one breed to other. However, herd-year-season interaction is significant for all breeds.
SOURCES OF ENVIRONMENTAL VARIATION
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2
3
4
5
6
7
1 2 3 4 5 6 7 8 9 10RECORD
CO
NT
EN
TS
(%)
1
1.2
1.4
1.6
1.8
2
2.2
2.4
DA
ILY
YIE
LD
(KG
)
PROTEIN CASEIN FAT LACTOSE YIELD
Variation of milk and milk components yields through lactation
Source: Díaz et al., 1999
SOURCES OF ENVIRONMENTAL VARIATION
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0
1
2
3
4
1 2 3 4 5 6 7 8 9 10
RECORD
CO
NT
EN
TS
(%)
CASEIN ALFA BETA KAPPA
Variation of contents (%) of milk components through lactation
Source: Diaz et al. , 1999
SOURCES OF ENVIRONMENTAL VARIATION
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Trait Milk yield % Fat %Protein
Milk yieldFat % Protein %
Multi-trait estimationsHeritability (diagonal), Genetic correlation (over
diagonal) and Phenotypic (under diagonal)
Source: Analla et al., 1996
Multi-trait estimations of repeatability (diagonal) and correlation between permanent (over diagonal) and temporal (under diagonal) environmental effects
Trait Milk yield % Fat % Protein
Milk yieldFat % Protein %
-0,38 -0,35 0,44
0,360,33
0,41
-0,89 -0,580,94
Trait h2
ee2 r
ee
Single-trait estimations of heritability and repeatability
Milk yield 0,18
0,04 0,39
0,08Fat % 0,16
0,04 0,36
0,05
Protein % 0,25
0,05 0,47
0,07
0,170,14
0,22
-0,89 - 0,650,93-0,48
-0,47 0,54
GENETIC PARAMETERS (Murciano-Granadina)
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MY (kg) PY (kg) PC (%) FY (Kg) FC (%)
MY (kg) 0,33 0,90 -0,3 0,8 -0,14
PY (kg) 0,35 0,15 0,85 0,10
PC (%) 0,54 0,18 0,55
FY (Kg) 0,38 0,53
FC (%) 0,59
(Bélinchon et al., 1998)
Efectos maternos genéticos
h2 hm2 m2 rg
MY (kg) 0,19 0,13 0,05 0,27
FY (kg) 0,21 0,11 0,10 0,73
PY (kg) 0,17 0,07 0,09 0,18
(en primera lactación)
(Wheppert y Hayes, 2003)
GENETIC PARAMETERS: HERITABILITIES
Trait Range AverageMilk yield 0,08-0,68 0,35Protein yield 0,30-0,60 0,33Fat yield 0,10-0,64 0,37Protein content (%) 0,25-0,67 0,50Fat content (%) 0,16-0,66 0,47Casein content (%) 0,66-0,90 0,73Flavour 0,20-0,30 0,27Litter size 0,07-0,24 0,13Birth weight 0,01Pre-waning live weight 0,51-0,63 0,54Post-weaning live weight (7 months) 0,23-0,55 0,42Fleece weight 0,15-0,26 0,20Fleece yield 0,48Fibre diameter 0,12Fibre length 0,22Milk flow 0,46
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GENETIC PARAMETERS: CORRELATIONS
0-0.11
Littersize
Fat %Age at firstkidding
-0.28-0.36 +0.12 -0.20+0.19 +0.41 -0.45
+0.82
-0.30 Adult +0.05 Milk -0.50 Protein % +0.41-0.22 weight +0.66 yield
+0.4 + -0.14 +0.45
7 months weight Lactose % Clotting protein %
+039
(Gall, 1981; Ricordeau, 1981)
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Inseminación• Permite conexiones entre rebaños• Permite el testaje de machos• Permite difusión de la mejora
• A mayor porcentaje de hembras inseminadas– Mejor conexión entre rebaños– Mayor fiabilidad de las evaluaciones– Mayor respuesta a la selección
Datos expuestos en París en la SIA 2002 (http://capra.iespana.es)
Macho Total
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
AEV02044 1 4 3 2 1 6 2 2 21
AEV02061 2 1 3
ATP03068 1 3 4 8
HAI02021 4 1 1 5 4 15
HS03044 3 3
JYJ02025 6 2 4 2 2 5 3 24
NS02023 3 3 4 1 2 4 5 4 26
NS02028 9 6 3 2 1 21
TT01112 3 2 2 1 3 5 4 20
TT02090 2 1 2 2 3 2 1 13
V03127 3 1 2 6
WS04001 2 3 1 6
XBA04001 2 1 4 7Total 19 0 0 9 7 6 3 8 15 12 9 18 20 0 11 4 12 9 11 173
Ganadería
Source: Martínez et al., 2008
Lactaciones finalizadas válidas obtenidas de primeros partos de cabras nacidas de IA según ganadería y macho utilizado en la inseminación.
FasesPuntual (%) Acumulada (%)
Diag. gestación 46,1 46,1 48,8Parto cabra inseminada 14,3 53,8 41,8Inscripción libro genealógico 33,1 69,1 27,9Partos hija de IA 26,1 77,2 20,6Lactación válida hija IA 4,9 78,2 19,7
Perdida de información Nº de hijas por cada 100 cabras inseminadas (Rendimiento)
Pérdidas de información y rendimiento según fase del programa
Se ha considerado una prolificidad media de 1,81 y que el 50% de los nacidos son hembras, partiendo de 1950 inseminaciones.
Source: Martínez et al., 2008
SELECTION SCHEMES - PRACTICAL DIFFICULTIES
It is necessary
Organisation and interest of breeders
Economic co-responsibility of breeders
Overcome traditional selection criteria
Breeders accepting new genetic indexes instead of raw yields
To implement a system for A.I. and herd connections
MOET schemes - Advantages - Disadvantages
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¿Debe ser este orden?
• Definir los objetivos de selección• Control de producciones• Control genealógico• Gestión datos para evaluaciones genéticas• Crear conexiones entre rebaños
El número de animales en control es pequeño
El tamaño del núcleo de selección (rebaños en control en los que se valoran seleccionan reproductores) es pequeño
No hay conexión entre rebaños
No existen sementales en prueba de descendencia
No existen aún sementales probados mejorantes
Se inseminan pocas hembras con el semen de sementales probados mejorantes
No se realizan valoraciones genéticas con metodología actual
No todos los ganaderos utilizan las valoraciones genéticas de sus animales para elegir la reposición en sus rebaños
El programa no tiene continuidad. Se producen interrupciones esporádicas del control de rendimientos y de los programas de valoración de sementales por falta de recursos económicos o por otras causas
Escasez de personal para llevar el esquema
Escasa participación de los ganaderos
La normativa existente no permite el desarrollo adecuado del esquema
Source: Serradilla et al., 2008
Algunos factores limitantes en el desarrollo de los esquema de selección
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THANK YOU FOR YOUR THANK YOU FOR YOUR
ATTENTION!ATTENTION!