Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada
Abstract
:1. Introduction
2. Materials and Methods
2.1. Terminology
2.2. Founder Population, Crossing and Selfing to Begin Cycle 1
2.3. Cycles of Augmented S0,1 Family Selection
2.4. Pedigree Structure and Relationships
2.5. Field Trials and Phenotyping
2.6. Data Analysis
2.6.1. Preliminary Single Site Analysis
2.6.2. Base Univariate Model Across-Sites
2.6.3. Factor Analytic Modelling of Each Trait across Sites
2.6.4. Genotype Overall Performance and Stability
2.7. Economic Index
2.8. Optimal Contributions Selection and Crossing
2.9. Assessment of Genetic Gain
3. Results
3.1. Environmental Trends over Cycles and Countries
3.2. Genetic Relationships of Genotypes within and across Cycles
3.2.1. Connectivity of Genotypes within and across Cycles
3.2.2. Inbreeding Coefficients and Coefficients of Coancestry
3.3. Analysis of Sites and Cycles
3.3.1. Base Across-Sites Model
3.3.2. Optimum MMM-FA Models
3.3.3. Genetic Correlations across Trials
3.4. Pairwise Correlations of PBV across Traits
3.5. PBV, Overall Performance and Yield Stability for GY
3.6. Genetic Gain across Cycles
3.7. Genetic Gain in Historical Cultivars
3.8. Impact of Genetic Correlations between Traits on Genetic Gain
3.9. Predictions from OCS in Cycle 5 with and without RMSD GY in the Economic Index
4. Discussion
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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(a) | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Number of Genotypes in Trial | ||||||||||||||
Cycle | Trial Code | Trial Location | Country | Ranges | Rows | Plots | Total | Single Replicate | S0 | S1 | S2 | S4 | F2 | F3 |
1 | 2014AU1 | West Dale, WA | Australia | 24 | 89 | 2136 | 1557 | 1080 | 668 | 250 | 0 | 0 | 577 | 52 |
2 | 2016AU1 | York, WA | Australia | 24 | 68 | 1632 | 1175 | 898 | 511 | 0 | 569 | 0 | 11 | 55 |
2 | 2016AU2 | Rutherglen, VIC | Australia | 24 | 68 | 1632 | 1174 | 899 | 511 | 0 | 568 | 0 | 11 | 55 |
3 | 2018AU1 | York, WA | Australia | 24 | 88 | 2112 | 1919 | 1769 | 1565 | 0 | 151 | 166 | 13 | 0 |
3 | 2018AU2 | Rutherglen, VIC | Australia | 24 | 88 | 2112 | 1912 | 1771 | 1566 | 0 | 151 | 166 | 13 | 0 |
3 | 2018CA1 | Sun Valley, MB | Canada | 24 | 88 | 2112 | 1919 | 1772 | 1566 | 0 | 151 | 166 | 13 | 0 |
4 | 2020AU1 | Williams, WA | Australia | 24 | 40 | 960 | 674 | 436 | 653 | 0 | 0 | 0 | 0 | 0 |
4 | 2020AU2 | Wonwondah, VIC | Australia | 24 | 38 | 912 | 625 | 386 | 604 | 0 | 0 | 0 | 0 | 0 |
4 | 2020CA1 | Sun Valley, MB | Canada | 24 | 34 | 816 | 555 | 308 | 528 | 0 | 0 | 0 | 0 | 0 |
(b) | ||||||||||||||
Connectivity of Genotypes across Trials | ||||||||||||||
Cycle | Trial Code | 2014AU1 | 2016AU1 | 2016AU2 | 2018AU1 | 2018AU2 | 2018CA1 | 2020AU1 | 2020AU2 | 2020CA1 | ||||
1 | 2014AU1 | 1556 | 3 | 3 | 2 | 2 | 2 | 1 | 1 | 1 | ||||
2 | 2016AU1 | 3 | 1175 | 886 | 13 | 13 | 13 | 5 | 5 | 5 | ||||
2 | 2016AU2 | 3 | 886 | 1174 | 13 | 13 | 13 | 5 | 5 | 5 | ||||
3 | 2018AU1 | 2 | 13 | 13 | 1911 | 1911 | 1911 | 4 | 4 | 4 | ||||
3 | 2018AU2 | 2 | 13 | 13 | 1911 | 1912 | 1912 | 4 | 4 | 4 | ||||
3 | 2018CA1 | 2 | 13 | 13 | 1911 | 1912 | 1919 | 4 | 4 | 9 | ||||
4 | 2020AU1 | 1 | 5 | 5 | 4 | 4 | 4 | 674 | 625 | 548 | ||||
4 | 2020AU2 | 1 | 5 | 5 | 4 | 4 | 4 | 625 | 625 | 548 | ||||
4 | 2020CA1 | 1 | 5 | 5 | 4 | 4 | 9 | 548 | 548 | 555 |
Trait a | Population Mean (Units of Trait) | Range of PBV in Population (Units of Trait) | PBV of the Individual (Units of Trait) | Total GY of Individual (t ha−1) | Grain Price (US$ t−1) | Economic Weight for +1 PBV Unit | Contribution to Economic Index of the Individual (US$ ha−1) | Calculation of Economic Index (US$ ha−1) (Based on Economic Weight for +1 PBV in US$ t−1) | ||
---|---|---|---|---|---|---|---|---|---|---|
Min | Max | % Grain Price | US$ t−1 | |||||||
GY | 2.020 | −0.910 | +0.644 | +0.322 | 2.342 | 550.00 | $1288.10 | (Total GY of Individual) × (Grain Price) | ||
Oil | 44.757 | −6.673 | +3.686 | +1.383 | 1.50% | $8.25 | $26.72 | (PBV Oil) × (Total GY) × (Econ Wt +1 unit PBV) | ||
ProM | 41.088 | −4.062 | +5.508 | +0.554 | 3.00% | $16.50 | $21.41 | (PBV ProM) × (Total GY) × (Econ Wt +1 unit PBV) | ||
DTF | 80.180 | −13.507 | +15.639 | +2.213 | −1.00% | −$5.50 | −$28.51 | (PBV DTF) × (Total GY) × (Econ Wt +1 unit PBV) | ||
PlHt | 122.675 | −29.380 | +26.952 | +3.561 | −0.50% | −$2.75 | −$22.93 | (PBV PlHt) × (Total GY) × (Econ Wt +1 unit PBV) | ||
BL | 5.089 | −1.996 | +2.671 | +1.297 | 2.00% | $11.00 | $33.41 | (PBV BL) × (Total GY) × (Econ Wt +1 unit PBV) | ||
GSL | 11.297 | −5.637 | +16.325 | −1.749 | −1.50% | −$8.25 | $33.79 | (PBV GSL) × (Total GY) × (Econ Wt +1 unit PBV) | ||
SW100 | 0.325 | −0.030 | +0.039 | +0.024 | 0.20% | $1.10 | $0.06 | (PBV SW100) × (Total GY) × (Econ Wt +1 unit PBV) | ||
OL | 61.670 | −8.132 | +8.939 | +2.328 | 0.00% | $0.00 | $0.00 | (PBV OL) × (Total GY) × (Econ Wt +1 unit PBV) | ||
RMSD GY | 0.096 | 0.000 | +0.411 | +0.215 | −20.0% | −$110.00 | −$55.39 | (PBV RMSD GY) × (Total GY) × (Econ Wt +1 unit PBV) | ||
Economic index excluding RSMD GY | $1352.06 | sum of above excluding RMSD GY (t ha−1) | ||||||||
Economic index including RMSD GY | $1296.67 | sum of above including RMSD GY (t ha−1) |
MMM-FA Model | Number of Estimated Variance Components | RLL | AIC | BIC | %VAF |
---|---|---|---|---|---|
Grain yield (t ha−1) | |||||
Base | 44 | 8455.622 | −16,823.2 | −16,497.2 | |
FA(1) | 53 | 8635.382 | −17,164.8 | −16,772.1 | 63.31 |
FA(2) a | 59 | 8647.610 | −17,177.2 | −16,740.1 | 68.33 |
FA(3) | 65 | 8656.074 | −17,182.2 | −16,700.5 | 70.97 |
Days to 50% flower | |||||
Base | 25 | −11,863.700 | 23,777.41 | 23,950.84 | |
FA(1) a | 31 | −11,642.660 | 23,347.32 | 23,562.38 | 96.22 |
FA(2) | 34 | −11,638.730 | 23,345.45 | 23,581.33 | 96.40 |
Plant height (cm) | |||||
Base | 24 | −15,452.09 | 30,952.18 | 31,110.93 | |
FA(1) | 29 | −15,392.17 | 30,842.34 | 31,034.16 | 31.83 |
FA(2) a | 31 | −15,382.06 | 30,826.13 | 31,031.18 | 93.52 |
Seed oil (%) at 6% moisture | |||||
Base | 34 | −8169.558 | 16,407.12 | 16,649.38 | |
FA(1) | 41 | −7836.272 | 15,754.54 | 16,046.69 | 81.46 |
FA(2) a | 45 | −7825.844 | 15,741.69 | 16,062.33 | 94.57 |
Protein in meal (%) at 10% moisture | |||||
Base | 33 | −7462.394 | 14,990.79 | 15,225.92 | |
FA(1) | 40 | −7189.898 | 14,459.80 | 14,744.80 | 32.24 |
FA(2) a | 44 | −7188.877 | 14,465.75 | 14,779.26 | 84.99 |
Glucosinolates (μmole g−1 seed) | |||||
Base | 33 | −12,630.21 | 25,326.41 | 25,561.54 | |
FA(1) | 40 | −12,121.96 | 24,323.92 | 24,608.93 | 75.34 |
FA(2) a | 44 | −12,118.56 | 24,325.12 | 24,638.63 | 94.77 |
Oleic acid (% of total fatty acids) | |||||
Base | 22 | −5873.146 | 11,790.29 | 11,938.68 | |
FA(1) | 27 | −5556.775 | 11,167.55 | 11,349.66 | 90.85 |
FA(2) a | 29 | −5554.522 | 11,167.04 | 11,362.64 | 97.22 |
Phoma stem canker (blackleg) disease score: 1 (very susceptible) to 9 (very resistant) | |||||
Base | 16 | −3164.365 | 6360.730 | 6463.844 | |
FA(1) | 20 | −3149.209 | 6338.417 | 6467.310 | 74.05 |
FA(2) a | 21 | −3149.208 | 6340.417 | 6475.754 | 83.74 |
100 seed weight (g) | |||||
Base | 22 | 19,743.45 | −39,442.91 | −39,294.51 | |
FA(1) a | 27 | 19,808.11 | −39,562.21 | −39,380.09 | 51.93 |
Trait a | Population Mean | Units | Method of Breeding Value Assessment | Mean PBV of Candidate Genotypes in each Cycle (Number of Candidates in each Cycle) | Linear Regression of PBV of Candidate Genotypes from Cycles 2 to 4 | Annual Genetic Gain from Cycles 2 to 4b | ||||
---|---|---|---|---|---|---|---|---|---|---|
Cycle 2 (1426) | Cycle 3 (1896) | Cycle 4 (653) | Coefficient | Intercept | ||||||
Units Cycle−1 ± SE | Units ± SE | Change in Coefficient (units y−1) | Change in Coefficient (% y−1) | |||||||
Index | 963.8 | US$ ha−1 | PBV | 857.309 | 994.828 | 1106.341 | 139.910 ± 2.424 | 593.210 ± 7.008 | 69.955 | 7.26 |
944.6 | OP | 868.862 | 961.426 | 1061.069 | 95.430 ± 2.316 | 676.870 ± 6.696 | 47.714 | 5.05 | ||
GY | 2.02 | t ha−1 | PBV | −0.207 | 0.026 | 0.113 | 0.1741 ± 0.0095 | −0.5321 ± 0.0033 | 0.0870 | 4.31 |
OP | −0.188 | −0.04 | 0.032 | 0.1172 ± 0.0030 | −0.4099 ± 0.0087 | 0.0585 | 2.90 | |||
DTF | 80.2 | days | PBV | 1.872 | 2.135 | 0.474 | −0.5150 ± 0.0932 | 3.2127 ± 0.2695 | −0.258 | −0.32 |
OP | 1.793 | 1.945 | 0.343 | −0.5580 ± 0.0888 | 3.1916 ± 0.2568 | −0.279 | −0.35 | |||
PlHt | 122.7 | cm | PBV | 0.254 | 2.923 | −1.275 | −0.1711 ± 0.1776 | 1.7305 ± 0.5133 | −0.0860 | −0.07 |
OP | 0.212 | 2.927 | −1.419 | −0.1406 ± 0.1857 | 1.6337 ± 0.5369 | −0.0705 | −0.06 | |||
Oil | 44.8 | % | PBV | −0.996 | −0.366 | 0.070 | 0.5517 ± 0.0267 | −2.0681 ± 0.0772 | 0.2760 | 0.62 |
OP | −0.978 | −0.421 | −0.012 | 0.4970 ± 0.0261 | −1.9479 ± 0.0754 | 0.2485 | 0.55 | |||
ProM | 41.1 | % | PBV | 0.255 | 0.433 | 0.995 | 0.3331 ± 0.0268 | −0.4730 ± 0.0776 | 0.167 | 0.41 |
OP | 0.256 | 0.508 | 1.059 | 0.3729 ± 0.0264 | −0.5380 ± 0.0762 | 0.187 | 0.45 | |||
GSL | 11.3 | μmole g−1 | PBV | 0.314 | −0.859 | −1.030 | −0.7680 ± 0.0452 | 1.6885 ± 0.1306 | −0.384 | −3.40 |
OP | 0.290 | −0.910 | −1.075 | −0.7820 ± 0.0444 | 1.6868 ± 0.1284 | −0.391 | −3.46 | |||
OL | 61.7 | % | PBV | −0.194 | −0.541 | −0.645 | −0.2483 ± 0.0433 | 0.2629 ± 0.1253 | −0.124 | −0.20 |
OP | −0.181 | −0.585 | −0.671 | −0.2755 ± 0.0431 | 0.3190 ± 0.1245 | −0.138 | −0.22 | |||
BL | 5.1 | units | PBV | −0.283 | 0.911 | 1.234 | 0.8417 ± 0.0151 | −1.8255 ± 0.0437 | 0.421 | 8.25 |
OP | −0.239 | 0.739 | 1.057 | 0.7114 ± 0.0136 | −1.5556 ± 0.0393 | 0.356 | 6.97 | |||
SW100 | 0.325 | g | PBV | −0.003 | −0.005 | −0.006 | −0.0019 ± 0.0002 | 0.0010 ± 0.0005 | −0.001 | −0.30 |
OP | −0.001 | 0.001 | 0.001 | 0.0008 ± 0.0000 | −0.0020 ± 0.0001 | 0.001 | 0.15 |
(a) MateSel Output | |||||||
---|---|---|---|---|---|---|---|
Without RMSD GY in index | With RMSD GY in Index | Notes | |||||
No. male candidates | 653 | 653 | |||||
No. female candidates | 653 | 653 | |||||
No. selected males | 44 | 41 | moderate weighting against reciprocal matings, selfings and duplicates | ||||
No. selected females | 37 | 39 | moderate weighting against reciprocal matings, selfings and duplicates | ||||
No. matings used | 150 | 150 | |||||
Target degrees | 45 | 45 | conservative strategy to minimise coancestry and maximise index at 45 degrees | ||||
Achieved degrees | 45 | 45 | |||||
Achieved parental coancestry | 0.0850 | 0.0867 | low achieved parental coancestry | ||||
Starting mean candidate index | 1140.80 | 1106.34 | |||||
Achieved mean progeny index | 1307.22 | 1282.83 | aim to increase mean progeny index | ||||
Achieved standard deviation progeny index | 24.31 | 26.78 | |||||
Lowest selected male index | 1135.55 | 1113.01 | |||||
Lowest selected female index | 1121.90 | 1036.26 | |||||
Weighting on progeny mean inbreeding (F) | −1 | −1 | |||||
Achieved progeny mean inbreeding (F) | 0.0093 | 0.0103 | low due to optimised mating scheme | ||||
Random mating inbreeding (F) | 0.0779 | 0.0803 | predicted F based on random mating among parents | ||||
Maximum inbreeding (F) achieved | 0.0788 | 0.0843 | achieved following optimised design | ||||
(b) Predicted Responses in cycle 5 | |||||||
Without RMSD GY in Index | With RMSD GY in Index | ||||||
Units | Population Mean across Cycles 2, 3, 4 | Predicted Response in Cycle 5 (Units) | Predicted Response in Cycle 5 as % Population Mean | Predicted Response in Cycle 5 (Units) | Predicted Response in Cycle 5 as % Population Mean | Selection Aim | |
Economic index | US$ ha−1 | 166.42 | 176.49 | increase | |||
GY | t ha−1 | 2.017 | 0.1637 | 8.12% | 0.1696 | 8.41% | increase |
DTF | days | 80.2 | −2.5512 | −3.18% | −2.1776 | −2.72% | decrease |
PlHt | cm | 122.7 | −2.9254 | −2.38% | −2.6353 | −2.15% | decrease |
Oil | % | 44.8 | 0.2626 | 0.59% | 0.2816 | 0.63% | increase |
ProM | % | 41.1 | 0.4137 | 1.01% | 0.4426 | 1.08% | increase |
GSL | μmole g−1 | 11.3 | −0.6780 | −6.00% | −0.7987 | −7.07% | decrease |
OL | % | 61.7 | −0.0923 | −0.15% | −0.2025 | −0.33% | change |
BL | scale 1−9 | 5.1 | 0.1308 | 2.57% | 0.1820 | 3.57% | increase |
SW100 | g | 0.325 | 0.0022 | 0.69% | 0.0020 | 0.60% | increase |
RMSD GY | t ha−1 | 0.160 | −0.0317 | −19.78% | −0.0514 | −32.15% | decrease |
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Cowling, W.A.; Castro-Urrea, F.A.; Stefanova, K.T.; Li, L.; Banks, R.G.; Saradadevi, R.; Sass, O.; Kinghorn, B.P.; Siddique, K.H.M. Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada. Plants 2023, 12, 383. https://doi.org/10.3390/plants12020383
Cowling WA, Castro-Urrea FA, Stefanova KT, Li L, Banks RG, Saradadevi R, Sass O, Kinghorn BP, Siddique KHM. Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada. Plants. 2023; 12(2):383. https://doi.org/10.3390/plants12020383
Chicago/Turabian StyleCowling, Wallace A., Felipe A. Castro-Urrea, Katia T. Stefanova, Li Li, Robert G. Banks, Renu Saradadevi, Olaf Sass, Brian P. Kinghorn, and Kadambot H. M. Siddique. 2023. "Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada" Plants 12, no. 2: 383. https://doi.org/10.3390/plants12020383
APA StyleCowling, W. A., Castro-Urrea, F. A., Stefanova, K. T., Li, L., Banks, R. G., Saradadevi, R., Sass, O., Kinghorn, B. P., & Siddique, K. H. M. (2023). Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada. Plants, 12(2), 383. https://doi.org/10.3390/plants12020383