Presenter: Vasilia A. Fasoula Institution: Center for Applied Genetic Technologies University of Georgia Subject Country: India

1. Consideration of some scientific justifications underlying the success of SRI: A plant breeding perspective Vasilia A. Fasoula Center for Applied Genetic Technologies University of Georgia, USA

2. Difficulties inefficient early generation selection for yield soil heterogeneity genotype × environment interaction long time frame to release a cultivar Plant breeding

3. Factors affecting selection efficiency Density and competition Soil heterogeneity Heterozygosity G × E interaction

5. 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

6. The masking effect of density on the plant-to-plant yield differences between two maize hybrids Density (plants/m 2 ) Pioneer 3902 Dekalb 29 Grain yield per plant (g) Pioneer 3902 Single-cross hybrid DeKalb 29 Double-cross hybrid Source: Fasoula and Tollenaar 2005

7. Grain yield per plant (g) 0.5 24 Density (plants/m 2 ) 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

8. The effect of density on seed yield per plant 1.4 plants/m 2 38 plants/m 2 Soybean

9. The effect of density on root growth in soybean 1.4 plants/m 2 commercial plant density Soybean

10. The effect of density on the coefficient of variation (CV) of single-plant yields Source: Edmeades and Daynard 1979 Density (plants/m 2 ) CV (%)

11. To optimize efficiency the unit of selection and evaluation in plant breeding should be the individual plant grown at spacings of zero plant-to-plant interference

12. Can the yield potential per plant assessed at ultra-low plant density predict the crop yield potential at dense stand? ?

13. 2. Honeycomb field designs 1. Component analysis of the crop yield potential Yes, under two preconditions:

14. Yield potential per plant Stability of performance Adaptability Component analysis of the Crop Yield Potential and estimation parameters 1 2 3 Selection for a broader range of optimal plant density Development of density-independent cultivars favored by the farmers

15. Example of density-independent and density-dependent cultivars in tomato Density (Plants/m 2 ) Yield (t/ha) Source: Fery and Janick 1970

16. Parameters measuring the three components of each progeny line at ultra-low densities Reliable estimation of the parameters constitutes an important prerequisite which is ensured by: (1) successful growing of honeycomb trials, and (2) the unique properties of the honeycomb field designs

17. Switchgrass honeycomb trial

18. 19 progeny lines arranged in horizontal rows in an ascending order repeated regularly This layout facilitates field establishment and reduces the possibility for errors Facilitates mechanical har- vesting and computerization of selection Number of tested lines: X 2 +2XY+Y 2 X and Y are whole numbers from 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 15 14 13 12 11 10 8 7 9 row no.

19. Fasoula and Fasoula 2000, 2002, 2003 Even allocation of plants of any progeny line across the whole field The triangular pattern of plants places lines under comparable soil growing conditions Honeycomb design handling a maximum of 19 progeny lines Reliable estimates of the means and variances for each progeny line R-19 1 2 3 4 5 6 16 15 14 13 12 11 10 8 7 9 row no. 5 9 7 1 2 3 4 6 8 11 17 2 19 13 14 15 16 18 1 3 4 4 9 13 11 5 6 7 8 14 15 16 2 6 4 17 18 19 1 3 5 7 8 8 13 17 15 9 11 14 16 18 19 1 6 8 2 3 4 5 7 9 11 17 2 19 13 14 15 16 18 1 3 4 5 14 6 7 8 9 11 13 15 16 16 2 6 4 17 18 19 1 3 5 7 8 9 14 18 16 11 13 15 17 19 1 1 6 8 2 3 4 5 7 9 11 13 18 3 1 14 15 16 17 19 2 4 5 5 14 6 7 8 9 11 13 15 16 17 3 7 5 18 19 1 2 4 6 8 9 9 14 18 16 11 13 15 17 19 1 2 7 11 9 3 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

20. Each plant is evaluated on the basis of the unitless coefficient of ring-record (CR) x = the yield of each plant x r = the mean yield of the plants within each ring The CR erases the masking effect of soil heterogeneity on 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 row no.

21. Wheat honeycomb trial

22. 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 in favorable as well as marginal environments Density-independent cultivars 1 2 3 4 5 6

23. Example of maize population improvement in honeycomb breeding Honeycomb selection for 3 yr in a poorly drained field B Single-plant selection for yield in the F 2 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 trials in Field A and Field B Source: Onenanyoli and Fasoulas 1989; Constantinidou and Fasoulas 1988; Fasoulas 1993

24. RCB trial results of maize population improvement Half-sib families 5-7 and 6-5 outyielded the hybrid and population at both sites Selection at ultra-low plant density can predict crop yield performance Source: Onenanyoli and Fasoulas 1989; Constantinidou and Fasoulas 1988; Fasoulas 1993 Inferences The best inbred line extracted from this population lagged behind PR-3183 in yielding ability by 8% only 100 90 80 70 60 50 100 90 80 70 60 50 Hybrid Population F 2 Generation 5-7 6-5 2-2 6-1 % % FIELD A well drained FIELD B poorly drained

25. Yield (% of hybrids) Data from Meghji et al. 1984, Evgenidis 1997 Reducing the productivity gap between hybrids and inbred lines Selection for crop yield potential

26. Selection at ultra-low plant densities leads to multi-culm and multi-ear maize plants This specific plant belongs to the half-sib family 5-7 of the improved maize population described previously

27. First picture of maize - Fuchs’ 1542 American Indian Maize Ideotype: multi-culmed and multi-eared Maize - the greatest achievement of man-conditioned evolution

28. The evolution of the maize ideotype Uni-culm Density-dependent Multi-culm Density-independent

29. Release of the rice cultivar ‘Olympiad’ Selection for plant yield starting in the F 2 1,607 rice plants of the commercial hybrid ‘1992’ Plant-to-plant spacing 100 cm Continue selection till the F 6 generation Release of ‘Olympiad’ and evaluation in randomized complete block trials over two years Source: Danos 1998; Fasoula and Fasoula 2000

31. Honeycomb selection within elite cultivars to maintain uniformity and upgrade their performance and quality Cultivar yield decline

32. IR8 in 1998 IR8 in 1968 The green revolution in rice – IR8 was released in 1966 N rate (kg/ha) Grain yield (t/ha) The maximum yield of the rice cultivar IR8 has been declining at a rate of 2 t/ha in the past 30 yr (Peng et al. 1999)

33. 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

34. Evaluation trials for the cultivar ‘Macedonia’ Locations Yield of Macedonia (% Sindos 80) ‘ Sindos 80’ shallow root system Farmers report that Macedonia has a deep root system and does not need as much irrigation as Sindos 80

35. Honeycomb selection within ‘Macedonia’ - Identification of two lines resistant to Verticillium Source: Fasoulas 2000 Degree of infection (Scale: 0-4) susceptible

36. Divergent selection for seed protein and oil content within elite soybean cultivars identified lines with significantly higher or lower protein and oil content Source: Fasoula and Boerma 2005

37. Crop yield is maximized when all plants have approximately the same yield Equal sharing of growth resources Better stand uniformity Crop yield maximization – Precondition 1

38. The unequal sharing of growth resources due to genetic or acquired differences, called competition, reduces crop yield and is measured by the CV of the individual plant yields Larger CV Reduced crop yield Smaller CV Higher crop yield

39. Prerequisites for equal sharing of growth resources among plants 1 All plants must be genetically identical 2 Possess high individual homeostasis 3 Have a crop yield independent of density

40. Density (plants/m 2 ) Yield (t/ha) Source: adapted from Russell (1986) 1970 era single-cross hybrids 1930 era double-cross hybrids Crop yield maximization – 1. Use of monogenotypic cultivars to erase the plant differences due to genetic competition

41. Grain yield (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 cultivars that possess high individual homeostasis (stability)

42. Crop yield maximization 3. Utilization of density-independent monogenotypic cultivars Choice of the plant ideotype Many fertile tillers Deep and extensive root system

43. Maize ideotype: uni-culmed and single-eared Maize hybrids have become heavily dependent on a specific plant density The case of density-dependence in maize

44. Density (plants/m 2 ) Crop yield (t/ha) Pioneer 3902 Maize hybrids tend to be density-dependent Source: Fasoula and Tollenaar 2005

45. Maize hybrids were not selected for high plant yield Source: Duvick 1997

46. Example of density-independent and density-dependent cultivars in tomato Density (Plants/m 2 ) Yield (t/ha) Source: Fery and Janick 1970

47. Disadvantages More frequent weeding (farmers may favor high densities as a means to suppress weeds) Medium plant densities Advantages Lower seed cost Better drought and lodging resistance Fewer disease problems Security in adversity

48. SRI advantage Wider plant spacing – many tillers Source: Uphoff 2006

49. Advantages Many 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

50. Growth resources must be ample, readily available, and evenly distributed across the field Crop yield maximization – Precondition 2 SRI advantage Careful field and soil preparation Enhanced soil organic matter Increased soil aeration Careful water management

51. 1. Germination and growth of plants must be fast and synchronous SRI advantage: early transplanting Younger 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

52. SRI achieves better stand uniformity and thus higher crop yield Source: Uphoff 2006 Smaller CV

53. Cultivars selected for the environments that are destined 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 visually select the best plants for the following year (Participatory Breeding) Frequent weeding weeds will interfere with the even growth

54. Cultivars not adapted to the environments utilized 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

55. 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