efficient long-term cycling strategy

DaDa work 2001-2003

Efficient long-term Efficient long-term cycling strategycycling strategy

Contents of 1 hContents of 1 h

Introduction and our studies (5 min.)Introduction and our studies (5 min.)

Main finding (2 min)Main finding (2 min)

Testing strategy: optimization and Testing strategy: optimization and timing (50 min):timing (50 min):Single-stage strategies compared,Single-stage strategies compared,

Two-stage strategies compared,Two-stage strategies compared,

Amplified case: Progeny testing versus Amplified case: Progeny testing versus Pheno/Progeny.Pheno/Progeny.

Main finding separately for pine and Main finding separately for pine and spruce (5 min.)spruce (5 min.)

4: BP size optimised

3: Ph/Prog amplified (pine), effect of J-M.

Seminar 2004.03.02

1-2: Best testing strategy

The Road to this semianrThe Road to this semianr

Breeding cycler

Hungry shark

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15

Main findings: Main findings: cloningcloning is the best is the best strategystrategy


Main findingsMain findings

•CClonallonal test is superior (use for test is superior (use for spruce)spruce)

•ProgenyProgeny testing not efficient testing not efficient

•For Pine, use 2 stage For Pine, use 2 stage PhenoPheno//ProgenyProgeny

•Pine flowers not needed before age Pine flowers not needed before age ~~ 10-15 10-15


General M&MGeneral M&M

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15Basic advantage of our Basic advantage of our

approachapproach

Gain per time

Cost

Diversity

Is a Is a completecomplete comparison as it comparison as it simultaneouslysimultaneously considers: considers:

Other things, e.g. to well see the road

The long-term The long-term programprogram

Recurrent cycles of mating, testing and balanced selectionAdaptive environment

Testing

Within family

selection

Mating

We consider one such breeding population

Breeding population


Benefit Benefit == Group Merit/Year Group Merit/Year

Gain Diversity

Time

Diversity loss was set to be as important as gain

Main inputs and Main inputs and scenariosscenarios

While testing an alternative parameter value, the other parameters were at main scenario values

Low

lower reasonable

bound

Genetic parameters

Time components

Cost components

Main

typical for Pine or spruce

High

higher reasonable

bound


•Cost per test plant = 1 ’cost unit’, all the other Cost per test plant = 1 ’cost unit’, all the other

costs expressed as ratio of this 1. costs expressed as ratio of this 1.

•Such expression also helped to set the budget Such expression also helped to set the budget

constraint corresponding to the present-day constraint corresponding to the present-day

budget budget

The time and cost explainedThe time and cost explained

Established in 5 years after seed harvest

Field trial

Establishment, maintenance and

assessments

Cutting of ramets Rooting of

ramets (1 year)

TransportationCrossing

Recombination cost=20, Time=4

Plant dependent cost=1 (per ramet)Genotype

depend. cost=2 (per ortet)

Nursery

Production of sibs (4 years)

Mating time

Time before

Testing time

Lag


All these costs should fit to All these costs should fit to a present-day budgeta present-day budget

Budget estimate is taken from pine and spruce Budget estimate is taken from pine and spruce breeding plan ~ test size expressed per year breeding plan ~ test size expressed per year and BP member.and BP member.

~ 10 ’cost units’ for pine, 20- for spruce.~ 10 ’cost units’ for pine, 20- for spruce.

Established in

5 years after

seed harvest

Field trial

Establishment,

maintenance and

assessments

Cutting of

rametsRooting of

ramets (1 year)

Transportation

Crossing

Recombination

cost=20-50,

Time=3

Plant dependent cost=1 (per ramet)

Genotype

depend. cost=0.1

(per ortet)

Nursery

Production of

sibs (4 years)

Mating time

Time beforeTesting time Lag

Established in

5 years after

seed harvest

Field trial

Establishment,

maintenance and

assessmentsEstablished in

5 years after

seed harvestEstablished in

5 years after

seed harvest

Field trial

Establishment,

maintenance and

assessments

Cutting of

rametsRooting of

ramets (1 year)Cutting of

rametsCutting of

rametsRooting of

ramets (1 year)Rooting of

ramets (1 year)

TransportationTransportation

Crossing

Recombination

cost=20-50,

Time=3

Crossing

Recombination

cost=20-50,

Time=3



Genotype

depend. cost=0.1

(per ortet)

Nursery

Production of

sibs (4 years)

Genotype

depend. cost=0.1

(per ortet)

Nursery

Production of

sibs (4 years)

Nursery

Production of

sibs (4 years)

Mating timeMating time

Time beforeTime before

Testing timeTesting time LagLag Budget

constraint


Why budget constraint per Why budget constraint per BP member and year?BP member and year?

• Because costs expressed per BP Because costs expressed per BP member = easier to handlemember = easier to handle

• Gain efficiency should be assessed Gain efficiency should be assessed per unit of timeper unit of time

• Optimization= optimum combination Optimization= optimum combination of of testing timetesting time and and testing sizetesting size to to obtain max obtain max GM/YearGM/Year and to satisfy and to satisfy the the budget constraintbudget constraint (use Solver) (use Solver)


The Relativity theory holds The Relativity theory holds for the Cycler as well… It for the Cycler as well… It

optimizes “your case”optimizes “your case”What if budget is suchWhat if budget is such

What if costs are suchWhat if costs are such

What if we reduce themWhat if we reduce them

What if heritably is suchWhat if heritably is such

What if J-M correlation What if J-M correlation isis

So, interpretation So, interpretation should consider that should consider that everything is relative to everything is relative to each othereach other


Single-stage Single-stage testing testing

strategiesstrategies

Objective: Objective: compare strategies based on compare strategies based on phenotypephenotype, , cloneclone or or progenyprogeny testing testing

(…n) (…n)

Phenotype testing

N=50

(…n), (…m) and selection age were optimized

Clone or progeny testing

N=50

(…n) (…n)

(…m)(…m)(…m)(…m)(…m)(…m)OBS: Further result on numbers and costs- for one of these families

Parameters- for referenceParameters- for referenceParameters Main scenario Alternative scenarios

Additive variance A2 ) 1

Dominance variance, % of the additive variance in BP D2) 25 0; 100

Narrow-sense heritability (h2) (obtained by changing E2) 0.1 0.05; 0.5

Additive standard deviation at mature age (Am), % 10 5; 20

Diversity loss per cycle, % 0.5 0.25;1

Rotation age, years 60 10; 120

Time before establishment of the selection test (TBEFORE), years

1 (phenotype) 3; 5 (phenotype)

5 (clone) 3; 7 (clone)

17 (progeny) 5; 7 (progeny)

Recombination cost (CRECOMB), $ 30 15; 50

Cost per genotype (Cg), $ 0.1 (clone), 1; 5 (clone),

1 (progeny) 0.1; 5 (progeny)

Cost per plant (Cp), $ 1 0.5; 3

Cost per year and parent (constraint) 10 5; 20

Group Merit Gain per year (GMG/Y) To be maximized


CVa at mature age CVa at mature age •CVCVaa=14 % is based on pine tests in =14 % is based on pine tests in

south Sweden Jansson south Sweden Jansson et alet al (1998), (1998),

•1/2 of additive var in pop is within full 1/2 of additive var in pop is within full sib families, sib families,

•Our program is balanced= gain only Our program is balanced= gain only from within full-sib selection, from within full-sib selection,

•Thus, CVThus, CVaa within fam= CVa in pop within fam= CVa in pop divided by the square root of 2, thus divided by the square root of 2, thus a CV = 10%, which we use here a CV = 10%, which we use here (even if not quite correct).(even if not quite correct).CVa within =CVa within = sqrt(sqrt(22/2)/2)= = sqrt(sqrt(22)/sqrt(2)= )/sqrt(2)=

22/sqrt(2) /sqrt(2)


Results-Results-clonalclonal best, best, progenyprogeny worst worst

At all the scenarios, Clonal was superior, except high h2.

Test 26 clones with 21 ramet (18/15 budget), select at age 20

Test 182 phenotypes; select at age 15, ( budget: 86, for 17 years) (second best)

Test 11 female parents with 47 progeny each; select at age 34 ( budget: 8/34, 40 years)

Ann

ual G

roup

Mer

it, %

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.1 0.2 0.3 0.4 0.5 0.6

Narrow-sense heritability

PhenotypeClone

Progeny

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15GM/Y digits after comma are GM/Y digits after comma are

importantimportant• If for Clone GM/Y=0.25%; cycle= If for Clone GM/Y=0.25%; cycle=

30 years then 30 years then

•Cycle GMCycle GM=8 % (gain 8.5 - 0.5 div =8 % (gain 8.5 - 0.5 div loss) loss)

•Thus GM/Y reduction by 0.03 (10%) Thus GM/Y reduction by 0.03 (10%) = = Cycle gainCycle gain reduction by 1% reduction by 1%

•Loss of Loss of Cycle gainCycle gain by 1% = by 1% = important lossimportant loss


0.10

0.15

0.20

0.25

0.30

4(59) 10(25) 15(18) 20(14) 30(10) 40(8)

Clone no (ramets per clone)

An

nu

al G

rou

p M

erit

, %

How flat are the optima How flat are the optima ((cloneclone)?)?

Clone number (ramet per Clone number (ramet per clone) = clone) = 1212((2222)-)-2424 ( (1414))

Less ramets at optimum Less ramets at optimum clone number is clone number is sensitive: no > than 5, sensitive: no > than 5, (not shown)(not shown)

If problems with cloning, If problems with cloning, better-> clones with < better-> clones with < rametsramets

If hIf h22 is higher , see next is higher , see next

GM/Y by Pheno

hh22=0.1, lower budget, at optimum testing =0.1, lower budget, at optimum testing timetime

Optimum 18(15)

17 18 20 22 23 25

Test time

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15If not enough cuttings, better more clones with less If not enough cuttings, better more clones with less

ramets, rather than to reduce ramet number at ramets, rather than to reduce ramet number at optimum clone numberoptimum clone number

0.436

0.3300.3400.3500.360

0.3700.3800.3900.4000.4100.420

0.4300.4400.450

19(1

9)

20(1

8)

21(1

8)

22(1

6)

24(1

5)

26(1

4)

28(1

3)

30(1

2)

32(1

1)

36(1

0)

39(9

)

45(8

)

50(7

)

57(6

)

70(5

)

Optimum for clone number (ramet no per clone)

Budget=20, h2=0.1, Cycling cost=20, time 4, Tbefore=5, Cg=2, J-M corr by L(2001), c=100

This line marks loss of GM/Y > 0,03

Variation in these outlined numbers will not cause marked loss of benefit

GM/Y by Phenotype=0,275

12 12 12 12 12 13 13 13 14 14 15 15 15 15 17

testing time


Higher hHigher h22 = more clones = more clones and less rametsand less ramets

Spruce plan 40/15

Ola’s thesis, paper I, Fig. 9= 40 cl with 7 ram at test size 280

0.00

0.10

0.20

0.30

0.40

0.50

0 0.1 0.2 0.3 0.4 0.5

Narrow-sense heritability

GM

/Y, %

13/23

18/1528/9

46/5Clone no/ramet no

Optimum then is between 18/15 and 30/10

Budget= 10


Clone strategy

0.00

0.05

0.10

0.15

0.20

0.25

0.30

15 16 17 18 19 20 21 22 23 24 25

Testing time, years

An

nu

al G

rou

p M

erit

, %

The optimal testing time 18-The optimal testing time 18-2020

•No effect to test longer than 18-20 years

•These 18-20 years with conservative J-M function (Lambeth 1980)

•With Lambeth 2001, about 15-17 years Figure with optimum at main scenario parameters (budget=10)

clones/ramets 18/15


How realistic are the How realistic are the optima?optima?• Optima depends on Optima depends on budgetbudget, , hh22, , J-M J-M

correlation- how realistic are they?correlation- how realistic are they?

1.1.Budget Budget is the present-day allocation. is the present-day allocation. Increase will result in more gain. But Increase will result in more gain. But we test how to optimise the resources we test how to optimise the resources we have.we have.

2.2.hh22 =0,1 seems to be reasonable =0,1 seems to be reasonable

3.3.J-M functions taken from southerly J-M functions taken from southerly pines, it affects the timing with stand. pines, it affects the timing with stand. error of 2 years (7-10-12).error of 2 years (7-10-12).


Why Why Phenotype Phenotype ≥≥Progeny Progeny ??

• Drawbacks of Drawbacks of ProgenyProgeny: long time and : long time and high cost (important to consider for high cost (important to consider for improvement)improvement)

• PhenotypePhenotype generates less gain but this generates less gain but this is compensated by cheaper and faster is compensated by cheaper and faster cycles.cycles.


Dominance seems to matter Dominance seems to matter littlelittle

Ann

ual G

roup

Mer

it, %Dominance would Dominance would

not markedly not markedly affect superior affect superior performance of performance of clonal testingclonal testing 0.0

0.10.20.30.40.50.6

0 25 50 75 100 125Dominance variance (% of

additive)

Clone

ProgenyPhenotype


On Genotype cost TbeforeOn Genotype cost Tbefore

0.05

0.10

0.15

0.20

0.25

0.30

0 1 2 3 4 5 6

Cost per genotype

0.05

0.10

0.15

0.20

0.25

0.30

0 3 6 9 12 15 18Delay before establishment of

selection test (years)

Expensive genotypes are of interest only if it would markedly shorten T before for Progeny or improve cloning

Clone

Progeny

Phenotype

Clone

Progeny


Recombinatin cost and total Recombinatin cost and total budgetbudget

Clone

Progeny

Phenotype

0.0

0.1

0.2

0.3

0 5 10 15 20 25

Budget per year and parent

0.05

0.10

0.15

0.20

0.25

0.30

10 20 30 40 50 60

Recombination cost

Clone

Progeny

Phenotype

Important factors; what happens if they Important factors; what happens if they fluctuate?fluctuate?

Phenotype get more attractive at low budget, Phenotype get more attractive at low budget, strategy choice not depending on strategy choice not depending on recombination costrecombination cost

An

nu

al G

rou

p M

erit

, %


ConclusionsConclusions

• Clonal testing is the best breeding strategy

•Phenotype 2nd best, except very low h2 or high budget

•Superiority of the Phenotype over Progeny is minor = additional considerations may be important (idea of a two-stage strategy).


Let’s do it in 2 Let’s do it in 2 stages?stages?


Stage 2:.Sexual propagation of

pre-selected individuals

Reselection based on

performance of the progeny

Mating

Testing of the progeny

Stage 2:.Sexual propagation of

pre-selected individuals

Reselection based on

performance of the progeny

Mating

Stage1: Phenotype test and pre-selection

Testing of the progeny

Phenotype/Progeny strategy


Values- study 2Values- study 2Parameters Main scenario Alternative

scenarios Additive variance A

2 ) 1 - Dominance variance, % of the additive variance in BP D

2) 25 0; 100

Environmental variance, % of total variance (E2) 88 0; 38; 94

Additive standard deviation at mature age (Am), % 10 5; 20 Diversity loss per cycle, % 0.5 0.25;1; 5 Rotation age, years 60 10; 20; 120

1 (phenotype) 3; 5 (phenotype) 5 (clone;

phenotype/clone) 3; 7 (clone;

phenotype/clone) Time before establishment of the selection test (TBEFORE), years

17 (progeny; phenotype/progeny)

5; 7 (progeny; phenotype/progeny)

Recombination cost (CRECOMB), $ 30 - 0.1 (clone), 1; 5 (clone), Cost per genotype (Cg), $ 1 (progeny) 0.1; 5 (progeny)

Cost per plant (Cp), $ 1 0.5; 3 Budget per year and parent (the constraint) 10 5; 20; 50 Group Merit Gain per year (GMG/Y) To be maximized


arrows show main scenario

0.10

0.15

0.20

0.25

0.30

1 3 5 7 9 11 13 15 17

Delay before establishment of selection test (years)

•If Progeny initiated early, may~ PhenotypePhenotype//ProgenyProgeny = need for a amplification

•Phenotype/Progeny is shown with a restriction for Phenotype selection age > 15

•CloneClone = = PhenotypePhenotype//CloneClone = no = no need for 2 stages.need for 2 stages.•PhenotypePhenotype//ProgenyProgeny is is 2nd best = best for Pine2nd best = best for Pine

Clone

ProgenyPhenotype

Pheno/Progeny

Results: two-stage 2nd bestResults: two-stage 2nd best


Budget cuts = switching to Budget cuts = switching to PhenotypePhenotype tests in Pine tests in Pine

If budget is cut by half = simple Phenotype test

0.1

0.2

0.3

0 5 10 15 20Budget per year and parent (%)

Ann

ual G

roup

Mer

it, %

Clone

Progeny

Phenotype

Pheno/Progeny


Budget cuts for Budget cuts for PhenoPheno//ProgenyProgeny

Budget = resources reallocated on cheaper Phenotype testTesting time 10 (stage 1) and 14 (stage 2) little affected by the budget

2

3

4

5

Budget=10 Budget=5

Ge

ne

tic

ga

in, %

Stage 1 Phenotype

Stage 2 Progeny

17

32

5(44) 5(72)


Why Why Pheno/Pheno/ProgenyProgeny was so was so good?good?

• It generated extra gain by taking It generated extra gain by taking advantage of the time before the advantage of the time before the candidates reach their sexual maturity candidates reach their sexual maturity

• This was more beneficial than single-This was more beneficial than single-stage stage ProgenyProgeny test at a very early test at a very early age age

• Question for the next study: is there Question for the next study: is there any feasible case where any feasible case where ProgenyProgeny can can be better?be better?

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15 ProgenyProgeny test with and test with and

without without phenotypicphenotypic pre- pre-selectionselection•Is there any realistic situation where

Progeny testing is superior over Pheno/Progeny (reasonable interactions and scenarios)

•What and how flat is the optimum age of pre-selection for Pheno/Progeny? (when do we will need flowers?)

Phenotype test Pre-selection age?

Progeny test


Simply- where best to invest?Simply- where best to invest?

Phenotype-Phenotype-based pre-based pre-selection selection

Early Early flowering flowering inductioninduction


Time and cost componentsTime and cost components

CPer CYCLE = Crecomb + n (CG + m CP),

Tcycle = Trecomb + TMATING + TLAG + Tprogtest

TLAG is crossing lag for progeny test (polycross, seed maturation,

seedling production)

TTMATINGMATING age of sufficient flowering capacity to initiate age of sufficient flowering capacity to initiate

progeny test (for 2-stage strategy it corresponds to the age progeny test (for 2-stage strategy it corresponds to the age of phenotypic pre-selectionof phenotypic pre-selection

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15 Parameters study 3Parameters study 3

Parameters Main scenario

values Alternative

scenario values* Interactive

scenario values

Additive variance A2 ) 1 - -

Dominance variance, % of the additive variance D

2) 25 0; 100 -

Narrow-sense heritability (h2) (obtained by changing E

2) 0.1 0.01; 0.5 0.01

Additive standard deviation at mature age % 10 - -

Diversity loss per cycle, % 0.5 - -

J-M genetic correlation function L (2001) L(1980); G(2000) L(1980)

Age of mating for progeny test (age of sufficient flowering capacity for progeny testing), years 3 to 25 by 1 - -

Crossing lag for progeny test (crossing; seed maturation, seedling production), years

3 5; 8 -

Rotation age (RA), years 50 20; 30; 80 80

Recombination cost (CRECOMB), $ 30 0; 100 -

Cost per genotype (Cg), $ 1 0.1; 10 -

Cost per plant (Cp), $ 1 0.1; 2 -

Budget per year and parent, $ (the constraint) 10 5; 20 -

Annual progress in Group Merit (GM/Y) To be maximized

1


J-M correlation functionsJ-M correlation functions

•Lambeth (1980)= phenotypic fam mean corrs from many trials of 3 temperate conifers

•

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Ratio selection/rotation age (Q)

J-M

gen

etic

co

rrel

atio

n c

oef

fici

ent

Lambeth (1980)

Lambeth & Dill (2001)

Gwaze et al. (2000)

•Gwaze et al. (2000)= genetic correlations from 19 trials with 190 fams of P taeda western USA.

•Lambeth (2001) Main = genetic corrs in 4 series (15 trials) P taeda (296 fams)


Results: 2 stage is betterResults: 2 stage is better

• 2 stage strategy 2 stage strategy was better under was better under most reasonable most reasonable valuesvalues

Main scenario

0.0

0.3

0.6

0 5 10 15 20 25

An

nu

al G

rou

p M

erit

(%

)

Age of mating for progeny test (years)

•No marked loss No marked loss would occur if would occur if mating is mating is postponed to age postponed to age 15 15

Pheno/Progeny

Progeny

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15J-M correlation affects pre-selection J-M correlation affects pre-selection

ageage•Optimum selection age Optimum selection age depends on efficiency depends on efficiency of of PhenotypePhenotype to to generate enough gain to generate enough gain to motivate prolongation of motivate prolongation of testing for an unit of testing for an unit of time. time.

•

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Ratio selection/rotation age (Q)

J-M

gen

etic

co

rrel

atio

n c

oef

fici

ent

Do we have J-M estimates for spruce and pine?

Gwaze et al. (2000)

7

Lambeth & Dill (2001)

10

Lambeth (1980)

12

Gain increases fast by time

Gain would increase faster if switching to progeny test

•The gain generating The gain generating

efficiency mainly efficiency mainly

depends on slope of J-M depends on slope of J-M

correlation function.correlation function.


When the loss from optimum When the loss from optimum is important?is important?

Rotation age = 20

0.0

0.3

0.6

0 5 10 15 20 25

When early testing is advantageous

hh22 is high but is high but then then Phenotype Phenotype alone is betteralone is better

0.0

0.3

0.6

0 5 10 15 20 25

Plant cost= 0.1

0.0

0.3

0.6

0 5 10 15 20 25

Rotation is Rotation is shortshort

Plants are cheapPlants are cheap

h2= 0.5

0.0

0.2

0.4

0.6

0.8

0 5 10 15 20 25

Pheno/Progeny

Progeny

An

nu

al G

rou

p M

erit

(%

)


Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15 Better crossings are Better crossings are

motivatedmotivated

Crossing lag and genotype costs had no Crossing lag and genotype costs had no

marked effect = the crosses can be made over marked effect = the crosses can be made over

a longer time to simultaneously test all pre-a longer time to simultaneously test all pre-

selected individuals and their flowering may be selected individuals and their flowering may be

induced at a higher cost.induced at a higher cost.

Crossing lag= 5

0.23

0.0

0.1

0.2

0.3

0.4

0.5

0 5 10 15 20 25

10; 0.26

Crossing lag= 8

0.22

0.0

0.1

0.2

0.3

0.4

0.5

0 5 10 15 20 25

10; 0.25

Pheno/Progeny

Progeny

An

nu

al G

rou

p M

erit

(%

)



These are as for our interactive scenario:

•low heritability (0,01),

•long rotation (80 y)= less J-M at pre-selection,

•weak J-M correlation (L1980)

ProgenyProgeny is motivated when is motivated when conditions disfavour conditions disfavour

PhenotypePhenotype

But the optima flat and scenario unrealistic

Pheno/Progeny

Progeny

Interactive scenario

0.00

0.03

0.06

0 5 10 15 20 25An

nu

al G

rou

p M

erit

(%

)


Optimum test time and size for Optimum test time and size for pine pine (for one of the 50 full sib fams)(for one of the 50 full sib fams)

Long-term

breedingStage 2. Progeny-test each of those 5 with 30 offspring

Stage 1: Test 70 full-sibs

Mating

2-4 years, at a high cost if feasible

Lag- 3-4 years

Cycle time~ 27 Gain=8 % GM/Y= 0,27%

Select back the best of 5

when progeny- test

age is 10

Select 5 at age 10

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15What if no pine flowers until age What if no pine flowers until age

25?25?

•Pheno/Progeny is still leading

•Phenotype with selection age of 25 is better

•Progeny is the last

•Budget cuts, high h2 will favour Phenotype

This means, singe stage Phenotype cycle time > 25 years and For the two-stage, pre-selection not at its optimum age (10 years)Main (h=0.1, budget=10), Flowers at age 25

0.179

0.135 0.140

0.00

0.05

0.10

0.15

0.20

Pro

geny

Phe

noty

pe Pheno/Progeny

Ann

ual G

roup

Mer

it, %

Clonal- best; progeny- worst; Pine- phenotype pre-selection and progeny; flowers at age 15 May be 2 cycles of May be 2 cycles of

PhenotypePhenotype instead of instead of PhenoPheno//ProgenyProgeny??

CycleCycle, , yearsyears

GM/GM/year, %year, %

GM/GM/cyclecycle

2 cycle 2 cycle s of s of PhenoPheno

PhenotypPhenotypee

2020 0,1520,152 3,043,04 6,086,08

PhenoPheno//ProgProg

4040 0,1810,181 7,267,26

Answer is No: 7,26 is > 6,08


ConclusionsConclusions

•Under all realistic values, Pheno/Progeny better than Progeny

•Sufficient flowering of pine at age 10 is desirable, but the disadvantage to wait until the age of 15 years was minor,

•If rotation short, h2 high, testing cheap, delays from optimum age could be important


Our main findings


Main findingsMain findings- - sprucespruce

(18) (18)

(15) (15) (15) (15) (15) (15)

Clonal test by far the best

Select at age 15 (20) depending on J-M correlation

If higher h2 more clones less ramets

Present plans: size 40/15, selection age: 10 years

With L(2001), Cycle time~ 21 Gain=8.2 % GM/Y= 0,34%


MMain findingsain findings- P- Pineine

(70) (70)

Use 2 stage Pheno/Progeny strategy

Stage 1 Phenotype select at age 10 (15 only 3% GM lost)

Stage 2 Progeny test select at ca 10(30) (30)(30)(30)(30) (30) (30)(30)(30)(30)

With L(2001), Cycle time~ 27 Gain=8 % GM/Y= 0,27%


Research needs- Faster Research needs- Faster cloning cloning


Research needs (a PhD Research needs (a PhD thesis)thesis)

•Faster, better cloning: embryogenesis, Faster, better cloning: embryogenesis, rooting, C-effects (especially for pine) rooting, C-effects (especially for pine)

•Sufficient flowering at age 10 (15) for Sufficient flowering at age 10 (15) for pinepine

•Documentation of flowering in breeding Documentation of flowering in breeding stockstock

•How sexual maturation, flowering How sexual maturation, flowering abundance are related to breeding value? abundance are related to breeding value?


In breeding, thanks to Dag there may be less risk to enter a wrong

way ...

The endThe end

efficient long-term cycling strategy

Documents