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Identifying the target environmentsin breeding for rainfed ecosystems        B.P. Mallikarjuna Swamy            August 3, ...
Outline• The concept of the target population of environments(TPE)• Complexity of rainfed ecosystem• Factors to be conside...
Target population of environments(TPE)Comstock (1977) defined the concept of a targetpopulation of environments (TPE) asso...
Concept of the TPE• TPE is the set of all environments, fields and seasons in which  an improved variety is targeted to pe...
Concept of the TPE• Seasonal variation can result in very different conditions  in the same field in different years• Weat...
Concept of the TPE• Development of appropriate research strategy and  prioritization of rice research activities requires ...
Rianfed EcosystemsRainfed Upland   DroughtRainfed shallow Lowland        Drought Rainfed shallow Lowland                 F...
Complexity of rainfed environments• Large variations in rain fed ecosystems – rainfed upland,  rainfed lowland• rainfall• ...
Factors in delineating the TPE• Environmental factors  Rainfall, topography, Soil type, Insect-pest  Many breeding program...
Methods of Grouping sites in TPE• Crop Models• Environmental parameters• Currently used varieties• Statistical analysis of...
Crop modeling• The need to manage and predict crops behavior over a  wide range of planting dates, geographies and situati...
Grouping sites in TPE: Crop Models• Use of crop models to identify environments in terms of  water stress has been suggest...
Grouping sites in TPE: Environmental                  parameters• Sites with similar rainfall  pattern, soil types and  de...
Sites                  Target environment       Soil type                   Field topography    Drought                 Pr...
Grouping sites in TPE: Currently used varieties• Predominant farmers variety can also be used to  characterize the target ...
Sites categorization into favorable (F) or unfavorable(U) environments based on the ranking of mean yield                 ...
Genotypes under favorable and unfavorable               environment: IndiaGenotypes       Favorable environment       Geno...
Grouping sites in TPE: Principal component analysis• Pattern analysis to group sites on the basis of minimum G  x E within...
IRRI-India Drought Breeding Network                                                                      % grain yield of ...
Genotype x environment interactions-1     AMMI1 BIPLOT OF MAIN EFFECTS AND INTERACTIONS                12                 ...
Grouping the sites in TPE: Correlation of cultivar means • An easy and effective way of assessing the G x E across   envir...
Correlations among line means in          Eastern Indian OYT -URSBN         Pusa    Patna    Gerua    Bhaw    Chin    Cutt...
Results of correlations• Shallow sites tend to be correlated• Deeper sites (Cuttack and Chinsurah are correlated)• Correla...
Grouping sites in TPE: GIS• Geographical information system (GIS) and crop  modeling is used to predict the performance of...
Grouping sites in TPE: GIS
Relationship between the selection      environment (SE) and the TPE• SE is the nursery in which breeder makes selections•...
Requirements for the SE•   The SE must predict performance in seasons and    locations within the TPE - genetic correlatio...
Examples of SE for specific requirements  • In addition to the yield potential, local quality    preferences, SE may requi...
How to make SE more close to TPE• Multi location testing under diverse set of  environments – Many national programs follo...
Setting goals and prioritizing traits• Determining farmers preferences:- Focus group discussions. Farmers are asked about ...
Main objectives of a breeding program• Generally, to develop a cultivar that is superior to  farmers’ varieties in a parti...
Breeding goals: specific traits and strategies  • Deficiencies of currently grown varieties  • List of required traits wit...
Breeding goals: specific traits and strategies  • A high-quality locally-preferred variety should be used as    a parent i...
Appropriate breeding strategy: Broad    adaptations vs. specific adaptation• Irrigated ecosystem is more uniform as compar...
Appropriate breeding strategy• Among G, G x E and E variance – G is comparatively high  in irrigated situation but G x E i...
TPE classification: A case study from Thailand• A water balance model was used to estimate the level of  standing water in...
A successful breeder must:• Be in close touch with the farmers• Know the constraints in the target environment• Know the m...
A case study from ThailandParameter              Nong Khai             Nakhon RatchasimaTotal Rainfall         2000 mm    ...
A superior cultivar is one that:• Will be grown by the farmer because it performs  better (or obtains a better price) than...
A Case study from Thailand: Village level                surveys• Earlier, the target domain was classified using G x E  i...
A Case study from Thailand: Village level                surveys• Surveys at village and house hold level have  been used ...
Identifying target environments drought rbc 2012
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Transcript of "Identifying target environments drought rbc 2012"

  1. 1. Identifying the target environmentsin breeding for rainfed ecosystems B.P. Mallikarjuna Swamy August 3, 2012 Rice Breeding Course 2011
  2. 2. Outline• The concept of the target population of environments(TPE)• Complexity of rainfed ecosystem• Factors to be considered in delineating the TPE• Methods of grouping locations into TPE• Relationship between selection environments and TPE• Setting goals and prioritizing traits• Appropriate breeding strategy for a TPE• A case study
  3. 3. Target population of environments(TPE)Comstock (1977) defined the concept of a targetpopulation of environments (TPE) associated with abreeding program as the complete set of "types" ofenvironments in which cultivars can be grown within thegeographical area targeted by a breeding program.
  4. 4. Concept of the TPE• TPE is the set of all environments, fields and seasons in which an improved variety is targeted to perform well.• TPE consists of – Not a single environment but a set of present and future production environments.• Environmental variability changes the performance of varieties.• Breeders wish to develop cultivars that are superior to currently used varieties in most years and on most farms within the TPE.
  5. 5. Concept of the TPE• Seasonal variation can result in very different conditions in the same field in different years• Weather records for a certain location shows- Favorable years - 10 Years with drought at seedling stage - 4 Years with drought at flowering - 6 Years with submergence - 0 Blast - 10 BPH - 0 BLB - 3
  6. 6. Concept of the TPE• Development of appropriate research strategy and prioritization of rice research activities requires - 1. In depth understanding of TPE (More relevant with the Global climate change scenario) 2. Farmers traditional knowledge and farming practices 3. Socio-economic environments 4. Farmers perception of the new technologies being introduced
  7. 7. Rianfed EcosystemsRainfed Upland DroughtRainfed shallow Lowland Drought Rainfed shallow Lowland Favorable Rainfed shallow Lowland Drought, submergence Rainfed shallow Lowland Submergence Rainfed medium Lowland Submergence Rainfed LowlandDeficit Water Surplus
  8. 8. Complexity of rainfed environments• Large variations in rain fed ecosystems – rainfed upland, rainfed lowland• rainfall• soil type• topography• occurrence of abiotic stresses- drought, submergence• prevalent-insect-pests• low input use• quality preference• socio-economic conditions of the farmers
  9. 9. Factors in delineating the TPE• Environmental factors Rainfall, topography, Soil type, Insect-pest Many breeding programs considers this and have separate breeding program• Socioeconomic factors Resource capacity, Input use availability Very few breeding programs takes this into account
  10. 10. Methods of Grouping sites in TPE• Crop Models• Environmental parameters• Currently used varieties• Statistical analysis of multi environment data - Principal component analysis -Tests of fixed environmental effects - Examination of correlations of cultivar means across sites• Geographical information system (GIS)
  11. 11. Crop modeling• The need to manage and predict crops behavior over a wide range of planting dates, geographies and situations has become increasingly important.• Use of crop simulation models incorporating local climatic conditions with management operations increases our ability to make more timely and educated decisions.• The time has finally arrived in which crop modeling tools are increasingly being deployed to help address questions and problems on a larger, farm scale size. The full potential and value of crop models have not yet been realized in production agriculture.
  12. 12. Grouping sites in TPE: Crop Models• Use of crop models to identify environments in terms of water stress has been suggested• Historical weather data required• Information can be obtained from farmers if environmental information is not available: -Rapid rural appraisal -Agro system analysis
  13. 13. Grouping sites in TPE: Environmental parameters• Sites with similar rainfall pattern, soil types and depths of standing water accumulation within each region may be grouped together for breeding purposes
  14. 14. Sites Target environment Soil type Field topography Drought Presently grown varietiesIndira Gandhi Krishi Rainfed low land Clay, clay loam, low Bunded shallow Reproductive, early MTU 1010, IR 64,Vishwavidyalaya ecosystem organic carbon lowland to mid stage Swarna, Mahamaya(IGKV), lowlandNDUAT, Faizabad Rainfed shallow low Clay, clay loam, low Bunded Early season drought Sarjoo 52, Swarna, land drought prone organic carbon and reproductive NDR 97, NDR 359, and submergence stage Baranideep proneCRURRS, Hazaribag Rainfed shallow low acidic in nature, very Highly undulating Drought at all stages IR 36, IR 64, MTU land and bunded poor in fertility, low in of growth 1010, Hazaridhan, uplands available N and Sadabahar, Birsa 201, organic carbon Some other land racesCRRI, Cuttack Costal region, rainfed sandy loam and clay Bunded low lands seedling stage, and Lalat, Swarna, upland and lowland loam soil vegetative stage Varshadhan Naveen, MTU 1010, Khandagiri, Vandana,TNAU, Coimbatore Irrigated Lowland Clay Bunded lowland Reproductive stage IR 64, Co-47TNAU, Paramakudi Rainfed Upland Clay loam Bunded Reproductive stage PMK-3, ADT 38, Local racesUAS, Bangalore Eastern Dry Zone red, loamy and light Unbunded Reproductive stage MTU 1001, IR 64, drought Jyoti, MTU 1010, BPT 5204, Rasi,BF, Hydrabad Low land Clay loam Bunded Reproductive stage Samba Masuri, Swarna, MTU 1010BAU, Ranchi Rainfed shallow low acidic in nature, very Highly undulating Drought at all stages Lalat, IR 36, IR 64, land and bunded poor in fertility, low in of growth MTU 1010, Birsa 201, uplands available N and Some other land races organic carbon
  15. 15. Grouping sites in TPE: Currently used varieties• Predominant farmers variety can also be used to characterize the target environment• Variety Brown Gora grown in Chhotonagpur plateau region of eastern India can be classified as upland TPE• Variety Swarna grown in much of south Asia can be classified as shallow rainfed lowland• Most reliable and simplest way to define TPE• Adverse situations that these cultivars face in these ecosystems, and performance under such situation has to be taken into account
  16. 16. Sites categorization into favorable (F) or unfavorable(U) environments based on the ranking of mean yield in different years SITE Site mean yield (t/ha) Mean Ranking Category 2003 2004 2005 2003 2004 2005Santhapur 2.35 2.39 2.37 1 1 FSemiligud a 2 2.24 1.2 1.82 1 2 5 FFaizabad 1.75 1.4 1.58 3 4 FJagdalpur 1.86 1.02 1.76 1.54 2 4 3 FAmbikapur 1.36 0.62 1.77 1.25 6 7 2 F Ranchi 1.59 0.54 0.79 0.97 5 8 7 U Almora 0.94 0.76 0.9 0.86 7 6 6 UHazaribag 1.65 0.36 0.39 0.8 3 10 9 U Rewa 1.64 0.46 0.26 0.78 4 9 10 U Derol 0.59 0.77 0.68 8 5 UBanswara 0.54 0.23 0.74 0.5 9 11 8 U
  17. 17. Genotypes under favorable and unfavorable environment: IndiaGenotypes Favorable environment Genotypes Unfavorable emvironment  Designation Low Input High Input Designation Low Input High InputVR 379-5 2.07 2.36 Ashoka 228 0.92 1.03VL 3288 1.57 2.62 DDR 13 0.89 1RR385-249 1.53 2.31 DDR 97 0.87 1.19RR 433-2 1.49 2.66 Richa 6 0.84 1.05RR 363-5 1.49 2.51 Richa 5 0.83 1.04RR 356-74 1.48 2.16 Ashoka 200F 0.82 1.02Anjali 1.48 2.58 IC 267974 0.78 1.07DDR 106 1.42 2.13 VL 6309 0.76 0.95VL 6394 1.41 2.07 DDR 105 0.74 1.22DDR 117 1.4 2.31 RR 434-3 0.74 1.1RR 383-21 1.39 2.34 DDR 102 0.74 0.97BAU 249-92 1.36 2.3 VL 6747 0.72 0.82Vandana 1.22 1.86 Vandana 0.59 0.94Kalinga III 1.17 1.66 Kalinga III 0.66 0.6Brown Gora 1.15 1.9 Brown Gora 0.71 0.6Ashoka 228 0.93 2.19 Anjali 0.59 1.05Mean 1.21 2 Mean 0.61 0.9SED0.05 0.2298 0.3658 SED0.05 0.1698 0.2176
  18. 18. Grouping sites in TPE: Principal component analysis• Pattern analysis to group sites on the basis of minimum G x E within groups and maximum G x E among groups• Used when TPE is very large and diverse• Used when researchers do not have a good hypothesis about the causes of G x E• Use of probe and reference genotypes (known for their adaptation in each environment) is very helpful
  19. 19. IRRI-India Drought Breeding Network % grain yield of control Entry Name Barwale Faizabad Hazaribag Raipur Ranchi 40 medium duration 1 IR55419-04 3.5 64.3 79.4 44.4 43.7 2 IR74371-3-1-1 2.2 93.1 81.0 38.6 100.0advanced breeding lines 3 IR74371-54-1-1 1.9 82.1 7.5 34.2 71.4 4 IR77298-14-1-2 1.1 85.7 71.2 35.0 27.7 selected with different 5 IR78875-131-B-1-1 3.9 78.0 70.8 42.5 35.0 6 IR78875-131-B-1-4 2.2 59.1 74.5 26.5 75.0 performance across 7 IR78877-181-B-1-1-2 8.1 50.0 68.8 55.3 85.7 8 IR78877-208-B-1-4 6.4 42.9 94.0 50.4 45.0 environments 9 IR78878-53-2-2-2 4.6 71.4 58.9 29.1 66.7 10 IR78878-53-2-2-4 5.1 92.3 76.9 19.6 88.9 11 IR79899-B-179-2-3 2.5 69.2 74.2 16.8 70.0 12 IR79906-B-192-2-1 2.4 60.5 65.6 4.5 37.0 13 IR697515-72-1-3 1.7 54.6 87.5 34.4 44.5 14 IR80431-B-44-4 11.6 75.0 56.4 18.6 40.0 15 IR82870-58 0.6 65.5 84.2 21.1 62.5Source d.f. Sum of squares Mean squares % of total sum of squaresGenotype 39 29446.3 755.0 11.4Environment 4 103737.0 25934.0 40.0GxE 151 126104.0 835.1 48.6 GxE regression 39 1220.3 313.3 9.7 Stability deviations 112 11388.4 1016.8 90.3 AMMI component 1 42 73300.4 1745.3 58.1 AMMI component 2 40 27333.1 683.3 21.7 AMMI component 3 38 18698.5 492.1 14.8 AMMI component 4 36 6772.0 188.1 5.4Total 194 259287.3
  20. 20. Genotype x environment interactions-1 AMMI1 BIPLOT OF MAIN EFFECTS AND INTERACTIONS 12 5 Ranchi 7.2 28 Barwale 26 22 23 34 27 2.4 10 2 20 11 25 15 18 6 16 17 14 9 12 3 29 7 3 Hazaribag IPCA1 1 13139 33 248 45 2 40 19 38 37 36 31 -2.4 30 21 Faizabad 35 -7.2 32 Raipur 4 -12 2.295 18.695 35.095 51.495 67.895 84.295 MEANS VARIATE: RGY DATA FILE: AMMI MODEL FIT: 79.6% OF TABLE SS"
  21. 21. Grouping the sites in TPE: Correlation of cultivar means • An easy and effective way of assessing the G x E across environments within target region • If correlations are above 0.3 for a single 3 replicate trial, G x E is unlikely to be large • If lower than 0.3: - either G x E is large or - trial have high error and little genetic variations among cultivars – F value for cultivars is not significant
  22. 22. Correlations among line means in Eastern Indian OYT -URSBN Pusa Patna Gerua Bhaw Chin Cutt Mott Nlak TitaMaso 0.36 0.51 0.31 0.21 -0.08 -0.10 0.24 0.64 0.35Pusa 0.41 0.19 0.21 0.01 0.18 0.29 0.26 0.46Patna 0.24 0.06 0.10 0.14 0.41 0.34 0.37Gerua 0.15 -0.31 -0.05 0.12 0.33 0.18Bhaw 0.01 0.06 -0.01 0.27 0.17Chin 0.42 0.18 -0.25 0.32Cutt 0.29 -0.14 0.35Nlak 0.12 0.38
  23. 23. Results of correlations• Shallow sites tend to be correlated• Deeper sites (Cuttack and Chinsurah are correlated)• Correlation between shallow and deep sites is poor
  24. 24. Grouping sites in TPE: GIS• Geographical information system (GIS) and crop modeling is used to predict the performance of a variety for a range of environmental conditions.• These performance ranges can be combined with known spatial variation of key environmental variables contained in GIS to generate performance domain over space.• These tools also help to identify areas that are relatively homogeneous in terms of key constraints to productivity
  25. 25. Grouping sites in TPE: GIS
  26. 26. Relationship between the selection environment (SE) and the TPE• SE is the nursery in which breeder makes selections• The chosen SE should predict performance in the TPE• May need more than one SE if TPE is highly variable• SE is not the same as TPE, so the relationship must be monitored
  27. 27. Requirements for the SE• The SE must predict performance in seasons and locations within the TPE - genetic correlation (rG) between TPE and SE must be high• The SE must clearly and repeatably differentiate among genotypes under evaluation.• Heritability (H) for screening in the SE must be high• The SE must permit relatively large numbers of genotypes to be screened at low cost.• SE must permit a high selection intensity (i) to be achieved.
  28. 28. Examples of SE for specific requirements • In addition to the yield potential, local quality preferences, SE may require to screen for – Insect-disease (Bacterial blight) resistance – Submergence tolerance – Drought tolerance – Salinity tolerance
  29. 29. How to make SE more close to TPE• Multi location testing under diverse set of environments – Many national programs follow this approach• Testing under managed screens- Identify few promising lines and carry multi location testing with them
  30. 30. Setting goals and prioritizing traits• Determining farmers preferences:- Focus group discussions. Farmers are asked about positive and negative features of present cultivars - Preference analysis. Farmers are asked to rate experimental lines in a trial - In some cases, future farmer preferences must be predicted (i.e., they may not be aware of new options/technologies)
  31. 31. Main objectives of a breeding program• Generally, to develop a cultivar that is superior to farmers’ varieties in a particular target population of environments• Specific objectives – Replace a specific cultivar – Develop a new product – Change a single trait
  32. 32. Breeding goals: specific traits and strategies • Deficiencies of currently grown varieties • List of required traits with parents that are sources of these traits • Strategy for generating populations and selection for the desired traits
  33. 33. Breeding goals: specific traits and strategies • A high-quality locally-preferred variety should be used as a parent in most crosses. Because it can be difficult to recover quality characteristics in a single cross, the high- quality parent may be used as the recurrent parent in generating a BC-derived population • Quality parameters should be the focus of early- generation selection, because they are highly heritable, whereas yield is not. • The program should be structured to generate a large population of breeding lines with acceptable quality, which can then be evaluated for yield under farmer management.
  34. 34. Appropriate breeding strategy: Broad adaptations vs. specific adaptation• Irrigated ecosystem is more uniform as compared to the rainfed ecosystem• Broad adaptation has been very successful• Rainfed ecosystem is highly diverse• Broad adaptation through reduced G x E interaction effect not clearly visible in rainfed ecosystem?
  35. 35. Appropriate breeding strategy• Among G, G x E and E variance – G is comparatively high in irrigated situation but G x E is high in rainfed ecosystem.• G x E interactions have been earlier considered a hindrance to the crop improvement.• Nevertheless, G x E offer opportunity in selection and adoption of genotypes showing positive interactions with the location*.• However, if G x E is small, possible advantage of breeding for specific adaptation is reduced.
  36. 36. TPE classification: A case study from Thailand• A water balance model was used to estimate the level of standing water in paddy using weekly rainfall data from 1987 to 2001 for Nong Khai and Nakhon Ratchasima provinces of Thailand• Time and duration of standing water in the paddy (Boonrat et al. 2006)
  37. 37. A successful breeder must:• Be in close touch with the farmers• Know the constraints in the target environment• Know the market requirements• Know the plant traits considered important by the farmers• Imply all these information in his breeding program
  38. 38. A case study from ThailandParameter Nong Khai Nakhon RatchasimaTotal Rainfall 2000 mm 1000 mmGrowing season Earlier Later (High chance ofbeginning early drought)Rainfall withdrawl 8-14 Oct. 8-14 Oct.Chances of late High HighdroughtVarietal requirement Late season drought Cultivars with tolerance tolerant cultivars to drought at early as well as at late season
  39. 39. A superior cultivar is one that:• Will be grown by the farmer because it performs better (or obtains a better price) than the existing cultivar• Under management practices currently used or available to the farmer Economic benefit
  40. 40. A Case study from Thailand: Village level surveys• Earlier, the target domain was classified using G x E interaction and cluster analysis of multi location trials• Because of year to year variation, the TPE changed from year to year.
  41. 41. A Case study from Thailand: Village level surveys• Surveys at village and house hold level have been used to define the TPE• Hydrology of rice paddies even at local level in farmers fields is utilized.• Four terrace paddy levels are identified- Upper – drought prone Middle - drought prone Middle - Favorable Lower - Flooded

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