Consideration of some scientific justifications

underlying the success of SRI:A plant breeding perspective

Vasilia A. FasoulaCenter for Applied Genetic Technologies

University of Georgia, USA

Difficultiesinefficient early generation selection for yield

soil heterogeneity

genotype × environment interaction

long time frame to release a cultivar

Plant breeding

Factors affecting selection efficiency

Density and competition

Soil heterogeneity

Heterozygosity

G×E interaction

Steps to optimize selection efficiency

1. Elucidation of the role of competition and density on selection efficiency

2. Development of the honeycomb field designs that sample effectively soil heterogeneity

3. Partitioning of the crop yield potential into genetic components

4. Accurate single-plant field phenotyping for high and stable crop yield potential

Density and competition reduce response to selection in 5 ways:

1. by reducing the selection differential

2. by reducing heritability through an increase of the progeny CV

4. by selecting competitive plants at the expense of the productive ones

3. by correlating negatively the progeny mean yield with the progeny CV

5. by reducing grain yield per plant

0

50

100

150

200

250

300

350

400

0.5 1 2 4 8 12 18 24

The masking effect of density on the plant-to-plant yielddifferences between two maize hybrids

Density (plants/m2)

Pioneer 3902

Dekalb 29

Gra

in y

ield

per

pla

nt (

g)

Pioneer 3902Single-cross hybrid

DeKalb 29Double-cross hybrid

Source: Fasoula and Tollenaar 2005

0

50

100

150

200

250

300

350

400

Gra

in y

ield

pe

r p

lan

t (g)

0.5 24

Density (plants/m2)

Yield reduction at high plant density in 2 maize hybrids

Pioneer 3902

DeKalb 29

0.5 24

160 g

320 g

Source: Fasoula and Tollenaar 2005

The effect of density on seed yield per plant

1.4 plants/m238 plants/m2

Soybean

The effect of density on root growth in soybean

1.4 plants/m2 commercial plantdensity

Soybean

0

20

40

60

80

100

120

20 15 10 5

The effect of density on the coefficient of variation (CV)of single-plant yields

Source: Edmeades and Daynard 1979

Density (plants/m2)

CV

(%

)

To optimize efficiencythe unit of selection and evaluation

in plant breeding should be the individual plantgrown at spacings of zero plant-to-plant interference

Can the yield potential per plant assessed at ultra-low plant density

predict the crop yield potentialat dense stand?

?

2. Honeycomb field designs

1. Component analysis of the crop yield potential

Yes, under two preconditions:

Yield potentialper plant

Stability of performance

Adaptability

sxxsel /x sx /

Component analysis of the Crop Yield Potentialand estimation parameters

1 2 3

Selection for a broader range of optimal plant densityDevelopment of density-independent cultivars

favored by the farmers

Example of density-independent and density-dependentcultivars in tomato

Density (Plants/m2)

Yie

ld (

t/ha

)

Source: Fery and Janick 1970

0.75 1.75 4.25 10.25 2511

22

34

4556

112

IndeterminateJointlessDeterminateMiniatureDwarf

MULTIPLE HARVEST

Parameters measuring the three componentsof each progeny line at ultra-low densities

x

sx /

sxxsel /

Reliable estimation of the parameters constitutesan important prerequisite which is ensured by:(1) successful growing ofhoneycomb trials, and (2)the unique properties of thehoneycomb field designs

Switchgrass honeycomb trial

19 progeny lines arrangedin horizontal rows in anascending order repeatedregularly

This layout facilitates fieldestablishment and reducesthe possibility for errors

Facilitates mechanical har-vesting and computerizationof selection

Number of tested lines:X2+2XY+Y2

X and Y are whole numbersfrom zero to infinity

Fasoulas and Fasoula 1995

12

16

19 1 2 3 4 5 6 7 8 9 10 11

12 13 14 15 16 17 18 19 1 2 3 4

4 5 6 7 8 9 10 11 12 13 14 15

16 17 18 19 1 2 3 4 5 6 7 8

8 9 10 11 12 13 14 15 16 17 18 19

1 2 3 4 5 6 7 8 9 10 11

12 13 14 15 16 17 18 19 1 2 3 4

5 6 7 8 9 10 11 12 13 14 15

16 17 18 19 1 2 3 4 5 7 8

9 10 11 12 13 14 15 16 17 18 19 1

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

13 14 15 16 17 18 19 1 2 3 4 5

5 6 7 8 9 10 11 12 13 14 15 16

17 18 19 1 2 3 4 5 6 7 8 9

9 10 11 12 13 14 15 16 17 18 19 1

2 3 4 5 6 7 8 9 10 11 12 13

R-19

6

Honeycomb design handling a maximum of 19 progeny lines

1

2

3

4

5

6

16

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13

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10

8

7

9

rowno.

R-19

1

2

3

4

5

6

16

15

14

13

12

11

10

8

7

9

rowno.

5 971 2 3 4 6 8 11

17 21913 14 15 16 18 1 3 4

4 9 13115 6 7 8 14 15

16 2 6417 18 19 1 3 5 7 8

8 13 17159 11 14 16 18 19

1 6 82 3 4 5 7 9 11

17 21913 14 15 16 18 1 3 4

5 146 7 8 9 11 13 15 16

16 2 6417 18 19 1 3 5 7 8

9 14 181611 13 15 17 19 1

1 6 82 3 4 5 7 9 11

13 18 3114 15 16 17 19 2 4 5

5 146 7 8 9 11 13 15 16

17 3 7518 19 1 2 4 6 8 9

9 14 181611 13 15 17 19 1

2 7 1193 4 5 6 8 13

19 10

10

10

10

10

10

10

10

10

10

12

12

12

12

12

12

12

12

12

12

12

Fasoula and Fasoula 2000, 2002, 2003

Even allocation of plants of anyprogeny line across the wholefield

The triangular pattern of plantsplaces lines under comparablesoil growing conditions

Honeycomb design handling a maximum of 19 progeny lines

Reliable estimates of the meansand variances for each progenyline

Each plant is evaluated on thebasis of the unitless coefficientof ring-record (CR)

2/ rxxCR x = the yield of each plant

xr = the mean yield of the

plants within each ring

The CR erases the maskingeffect of soil heterogeneityon single-plant yields

Software available by Mauromoustakos et al. 2006

Honeycomb design handling a maximum of 19 progeny lines

12

16

19 1 2 3 4 5 6 7 8 9 10 11

12 13 14 15 16 17 18 19 1 2 3 4

4 5 6 7 8 9 10 11 12 13 14 15

16 17 18 19 1 2 3 4 5 6 7 8

8 9 10 11 12 13 14 15 16 17 18 19

1 2 3 4 5 6 7 8 9 10 11

12 13 14 15 16 17 18 19 1 2 3 4

5 6 7 8 9 10 11 12 13 14 15

16 17 18 19 1 2 3 4 5 7 8

9 10 11 12 13 14 15 16 17 18 19 1

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

13 14 15 16 17 18 19 1 2 3 4 5

5 6 7 8 9 10 11 12 13 14 15 16

17 18 19 1 2 3 4 5 6 7 8 9

9 10 11 12 13 14 15 16 17 18 19 1

2 3 4 5 6 7 8 9 10 11 12 13

R-19

6

11

6

1

2

3

4

5

6

16

15

14

13

12

11

10

8

7

9

rowno.

Wheat honeycomb trial

Highlights of honeycomb breeding

Accurate field phenotyping of single plants

Many tillers and extensive root system

Shorter time frame to release a cultivar

Efficient selection within released cultivars

Exploitation of adaptive variation infavorable as well as marginal environments

Density-independent cultivars

1

2

3

4

5

6

Example of maize population improvementin honeycomb breeding

Honeycomb selection for 3 yr in a poorly drained field B

Single-plant selection for yield in the F2 of PR-3183

Plant-to-plant spacing 125 cm

Honeycomb selection for 1 yr in a well drained field A

Testing of the best 4 half-sib families in RCB trialsin Field A and Field B

Source: Onenanyoli and Fasoulas 1989; Constantinidou and Fasoulas 1988; Fasoulas 1993

RCB trial results of maize population improvement

Half-sib families 5-7 and 6-5outyielded the hybrid and populationat both sites

Selection at ultra-low plantdensity can predict crop yieldperformance

100

90

80

70

60

50

100

90

80

70

60

50

Hybrid

Population

F2 Generation

5-7

6-52-

2

6-1

% %

FIELD Awell drained

FIELD Bpoorly drained

Source: Onenanyoli and Fasoulas 1989; Constantinidou and Fasoulas 1988; Fasoulas 1993

Inferences

The best inbred line extracted fromthis population lagged behind PR-3183in yielding ability by 8% only

0

20

40

60

80

100

1930 1950 1970

Hybrids

Inbreds

Yie

ld (

% o

f hy

brid

s)

Data from Meghji et al. 1984, Evgenidis 1997

Reducing the productivity gap betweenhybrids and inbred lines

Selection forcrop yieldpotential

Selection at ultra-low plant densities leads to multi-culmand multi-ear maize plants

This specific plant belongs tothe half-sib family 5-7 of theimproved maize populationdescribed previously

First picture of maize - Fuchs’ 1542

American Indian Maize Ideotype:

multi-culmed and multi-eared

Maize - the greatest achievement of man-conditioned evolution

The evolution of the maize ideotype

Uni-culmDensity-dependent

Multi-culmDensity-independent

Release of the rice cultivar ‘Olympiad’

Selection for plant yield starting in the F2

1,607 rice plants of the commercial hybrid ‘1992’

Plant-to-plant spacing 100 cm

Continue selection till the F6 generation

Release of ‘Olympiad’ and evaluation in randomizedcomplete block trials over two years

Source: Danos 1998; Fasoula and Fasoula 2000

‘Olympiad’

- 8% superiorover hybrid ‘1992’

- 22% superiorover the best local check

- Very productivecultivar in Greece(up to 12 t/ha)

Source: Crop Sci 2001

Honeycomb selectionwithin elite cultivars

to maintain uniformity and upgrade their performance and quality

Cultivar yield decline

3

4

5

6

7

8

9

10

0 60 120

IR8 in 1998

IR8 in 1968

The green revolution in rice –IR8 was released in 1966

N rate (kg/ha)

Gra

in y

ield

(t/h

a)

The maximum yield of the rice cultivar IR8 has beendeclining at a rate of 2 t/ha in the past 30 yr (Peng et al. 1999)

Honeycomb selection within an elite cultivar

10,000 plants using a 125 cm plant spacing

Selection material: Cotton cultivar ‘Sindos 80’- productive, but with shallow root system- susceptible to Verticillium wilt

Honeycomb selection for yield and quality for 2 years

RCB evaluations in 16 envs and release of ‘Macedonia’which exhibited a 10% yield superiority over ‘Sindos 80’

Source: Fasoulas 2000

Honeycomb selection for yield within Macedonia in 2 fields- Verticillium wilt free and Verticillium infected

Identification of lines resistant to Verticillium wilt

Evaluation trials for the cultivar ‘Macedonia’

90

95

100

105

110

115

120

125

130

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

Locations

Yie

ld o

f M

aced

onia

(%

Sin

dos

80)

‘Sindos 80’shallow rootsystem

Farmers report that Macedonia has a deep root systemand does not need as much irrigation as Sindos 80

Honeycomb selection within ‘Macedonia’ -Identification of two lines resistant to Verticillium

Source: Fasoulas 2000

0

0.5

1

1.5

2

2.5

3

3.5

4

AcalaS.J.2

AcalaS.J.5

7E 2B Sindos80

5F 4F

Deg

ree

of in

fect

ion

(Sca

le:

0-4)

su

sce

pti

ble

Divergent selection for seed protein and oil content within elitesoybean cultivars identified lines with significantly higher or

lower protein and oil content

Source: Fasoula and Boerma 2005

Crop yield is maximized when all plantshave approximately the same yield

Equal sharing of growth resourcesBetter stand uniformity

Crop yield maximization – Precondition 1

The unequal sharing of growth resources due togenetic or acquired differences, called competition,reduces crop yield and is measured by the CVof the individual plant yields

Larger CVReduced crop yield

Smaller CVHigher crop yield

1 All plants must be genetically identical

2 Possess high individual homeostasis

3 Have a crop yield independent of density

Prerequisites for equal sharing ofgrowth resources among plants

55

65

75

85

95

105

115

3 4.5 6

Density (plants/m2)

Yie

ld (

t/ha)

Source: adapted from Russell (1986)

1970 era single-cross hybrids

1930 era double-cross hybrids

Crop yield maximization – 1. Use of monogenotypic cultivarsto erase the plant differences due to genetic competition

2

3

4

5

6

7

Inbredlines

open-poll

doublecrosses

3-waycrosses

hybrids

Gra

in y

ield

(t/

ha)

Source: Jugenheimer 1976; Fasoula and Tollenaar 2005

CV=33%

CV=26%

CV=24%

CV=23.5%

CV=22%

Crop yield maximization – 2. Use of monogenotypic cultivarsthat possess high individual homeostasis (stability)

Crop yield maximization

3. Utilization of density-independentmonogenotypic cultivars

Choice of the plant ideotypeMany fertile tillersDeep and extensive root system

Maize ideotype: uni-culmed and single-eared

Maize hybrids have become heavilydependent on a specific plant density

The case of density-dependence in maize

0

2

4

6

8

10

0.5 1 2 4 8 12 18 24

Density (plants/m2)

Cro

p y

ield

(t/h

a)

Pioneer 3902

Maize hybrids tend to be density-dependent

Source: Fasoula and Tollenaar 2005

Year of introduction

1930 1940 1950 1960 1970 1980 1990

Yie

ld (

t/h

a)

0

2

4

6

8

10

12

14

1 plant/m2, r

2= 0.06

7.9 plants/m2 , r

2 = 0.86

3 plants/m2 , r

2= 0.56

Maize hybrids were not selected for high plant yield

Source: Duvick 1997

Example of density-independent and density-dependentcultivars in tomato

Density (Plants/m2)

Yie

ld (

t/ha

)

Source: Fery and Janick 1970

0,75 1,75 4,25 10,25 2511

22

34

4556

112

IndeterminateJointlessDeterminateMiniatureDwarf

MULTIPLE HARVEST

DisadvantagesMore frequent weeding (farmers may favor

high densities as a means to suppress weeds)

Medium plant densities

AdvantagesLower seed cost

Better drought and lodging resistance

Fewer disease problems

Security in adversity

SRI advantage

Wider plant spacing – many tillers

Source: Uphoff 2006

AdvantagesMany tillers

Extensive and deep root system (less water)

Better resistance to drought and lodging

Fewer disease problems

Crop yield compensation in case of adversity

Exploitation of the plant yield genetic

potential

SRI Rice plant ideotype in wider spacing

Growth resources must be ample, readilyavailable, and evenly distributed across the field

Crop yield maximization – Precondition 2

SRI advantageCareful field and soil preparationEnhanced soil organic matterIncreased soil aerationCareful water management

1. Germination and growth of plants must be fast and synchronous

SRI advantage: early transplantingYounger seedlings can achieve more uniform growth and will mature quicker

SRI advantage: square grid pattern

2. Plants must be evenly distributed across the field

Crop yield maximization – Precondition 3

SRI achieves better stand uniformity and thus higher crop yield

Source: Uphoff 2006

Smaller CV

Cultivars selected for the environments that aredestined to exploit

marginal environments (poor soils, drought, etc)favorable environments

Monogenotypic cultivars with high stability

Density-independent cultivars (less variable yields)25 × 25, 30 × 30, 50 × 50

Conditions that will maximize SRI efficiency

Wider spacings (50 × 50) can allow farmers to visuallyselect the best plants for the following year(Participatory Breeding)

Frequent weedingweeds will interfere with the even growth

Cultivars not adapted to the environmentsutilized by the farmers

Density-dependent cultivars

Cultivars with low tillering capacity (i.e., NPT of IRRI)

Conditions that will minimize SRI yields

Weeds in the field

A final thought

The plant genome is dynamic and plastic and can

activate mechanisms that release adaptive

variation to the constantly changing environmental

conditions, whether these are favorable or unfavorable