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Acta Agronomica Sinica ›› 2022, Vol. 48 ›› Issue (9): 2137-2154.doi: 10.3724/SP.J.1006.2022.11105

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A critical review on the principles and procedures for cultivar development and evaluation

YAN Weikai*()   

  1. Ottawa Research and Development Center, Agriculture and Agri-Food Canada, Ottawa K1A 0C6, Ontario, Canada
  • Received:2021-11-18 Accepted:2022-03-21 Online:2022-09-12 Published:2022-03-28
  • Contact: YAN Weikai E-mail:weikai.yan@agr.gc.ca
  • Supported by:
    The work was partially supported by ASP-001

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Abstract:

Plant breeding plays an indispensable role in meeting the increasing need for food and comfort of the mankind in a changing climate. Numerous concepts and procedures aiming at improving breeding efficiency have been put forward, such as various strategies for dealing with genotype by environment interaction, stability analyses, mega-environment analyses, experimental designs and analyses, biplot analyses, and selection indices. In addition, genomic selection has evolved into a stage that plant breeders must consider and cannot ignore. It is of practical importance to understand the relationships among these concepts and procedures, their usefulness, drawbacks, and pitfalls, as well as their place in the theoretical framework of plant breeding and genotype evaluation. Based primarily on personal research and experience, this article attempted to develop a systematic narrative on the principles, key concepts, and analytic procedures related to cultivar development and evaluation, with demonstrations using real-world data.

Key words: Breeder’s equation, heritability, genotype-by-environment interaction, mega-environment analysis, adequate testing, stability analysis, index selection, genomic selection

Fig. 1

A schematic presentation of the Complete Breeder’s Equation"

Table 1

The minimum probability for false selection (α) and the maximum allowable selection intensity (i) as determined by the population size (n) under the assumption of normal distribution"

n α i = z
10000 0.0001 3.71
1000 0.001 3.00
100 0.01 2.33
50 0.02 2.05

Table 2

The allowable selection intensity (ih), the culling rate (1-α), the risk of false culling (α), and the number of genotypes to be retained (N) at different levels of heritability (h2), assuming a population of n = 10,000 and a selection intensity of i = 3.7"

h2 h ih = 3.7h 1-α α N 1/N
0.0 0.00 0.00 0.5000 0.5000 5000 1/5000
0.1 0.32 1.17 0.8790 0.1210 1210 1/1210
0.2 0.45 1.65 0.9505 0.0495 495 1/495
0.3 0.55 2.03 0.9788 0.0212 212 1/212
0.4 0.63 2.34 0.9904 0.0096 96 1/96
0.5 0.71 2.62 0.9959 0.0041 41 1/41
0.6 0.77 2.87 0.9980 0.0020 21 1/21
0.7 0.84 3.10 0.9990 0.0010 10 1/10
0.8 0.89 3.31 0.9995 0.0005 5 1/5
0.9 0.95 3.51 0.9998 0.0002 2 1/2
1.0 1.00 3.70 0.9999 0.0001 1 1

Table 3

Selection/culling intensity at different stages of the breeding cycle in the Ottawa oat breeding program"

育种周期的不同阶段
Stages in a breeding cycle		 试点数
No. of
locations
(l)		 重复数
No. of
replicates
(r)		 选前群体大小
Population size
before selection
(n)		 选后群体大小
Population size
after selection
(N)		 对应遗传力
Assumed accumulative
heritability
(Hrly)
1 亲本选择和杂交
Parent selection and hybridization		 — — — — —
2 温室加代
Generation advance		 — — 10000 10000 —
3.1 第1年目测选择
Visual selection - yr1 (Observational hills)		 1 1 10000 1200 0.1
3.2 第2年目测选择
Visual selection - yr2 (Observational plots)		 1 1 1200 250 0.3
4.1 第1年预备试验
Preliminary test - yr1 (“Home test”)		 4 2 250 60 0.5
4.2 第2年预备试验
Preliminary test - yr2 (“ENCORE”)		 8-10 2-3 60 20 0.6
4.3 第1年注册试验
Registration test - yr1		 8-10 3 20 10 0.7
4.4 第2年注册试验
Registration test - yr2		 8-10 3 10 5 0.8
4.5 第3年注册试验
Registration test - yr3		 8-10 3 5 2 0.9

Fig. 2

GGE biplot to display the relative yield of 118 oat genotypes tested in 63 trials in the 2013-2019 Quebec provincial oat trials The genotypes are represented by “+” in blue and the trials by their location-year combinations in red. Each trial is displayed by the code of the relevant location and the last two digits of the year. The number immediately following the location code indicates the agro-ecological zone it belongs. For example, “CAUS3_13” refers to the trial at the location CAUS (Causapscal, a zone 3 location) in 2013."

Fig. 3

GE+GGL biplot to show the two oat mega-environments in Quebec The upper group of locations included NORM3, HEBE3, CAUS3, PRIN2, STET3, and STAU2, all from zones 2 and 3. The lower group of locations included NDHY1, STHU1, LAPO3, and OTT, from zones 1 and 3 of Quebec plus Ottawa, Ontario. The two mega-environments were not always distinct as there were overlaps between them."

Fig. 4

LG biplot to show the two oat mega-environments in Quebec Based on the yield data from the 2013-2019 Quebec provincial oat trials."

Fig. 5

GGE biplots to show the mean yield and stability of 13 oat cultivars in the two Quebec oat mega-environments a) subregion ME2a, and b) subregion ME2b. Data from the 2013-2019 Quebec provincial oat trials."

Table 4

The minimum number of years (ymin) required to achieve a heritability (H) of 0.75, estimated on the yield data of three-year spans from the Quebec provincial oat registration trials"

年份跨度
Three-year span		 共同品系数
No. of common genotypes		 σC σCY σCLY σP H ymin
2013-2015 26 0.63 0.25 0.50 0.71 0.88 1.2
2014-2016 23 0.70 0.34 0.58 0.81 0.86 1.5
2015-2017 27 0.48 0.53 0.73 0.65 0.73 3.3
2016-2018 27 0.30 0.64 0.80 0.52 0.59 6.3
2017-2019 27 0.52 0.49 0.70 0.68 0.76 2.8
2019-2020 30 0.29 0.42 0.64 0.43 0.68 4.3
平均 Mean — — — — — — 3.2

Table 5

The estimated minimum number of locations in comparison to the actual number of locations in the Quebec provincial oat trials"

年份
Year		 参试品种数
No. of entries		 实际试验点数
Actual no. of test locations		 σG σGL 最适试验点数
Estimated minimum (optimum)
no. of test locations
2013 41 8.0 91,043 339,803 11.2
2014 46 9.0 108,230 246,673 6.8
2015 44 10.0 124,695 281,369 6.8
2016 42 9.9 86,231 170,524 5.9
2017 43 10.0 129,192 354,402 8.2
2018 44 10.0 46,273 114,468 7.4
2019 46 10.0 61,079 255,019 12.5
平均Mean 9.6 8.4

Fig. 6

GGE biplots to show the highest yielding cultivar(s) in each of the trials in the two Quebec oat mega-environments a) subregion ME2a, and b) subregion ME2b. Data from 2013-2019 Quebec provincial oat trials."

Fig. 7

An example of spatial analysis using within-block multiple regression smoothing Data source: crown rust scores (0 to 9) from an oat variety trial conducted at Ottawa in 2021."

Table 6

Mean trait values of 13 oat cultivars tested in the 2013-2019 Quebec provincial oat trials and their GYT (genotype by yield×trait) index"

品种
Genotype		 性状、权重及符号 Traits and their weight and sign
产量
Yield
(kg hm-2)		 β-葡聚糖
β-glucan
(%)		 麦仁率
Groat
(%)		 油分
Oil
(%)		 蛋白质
Protein
(%)		 容重
Test weight
(kg hL-1)		 千粒重
1000-kernel
weight (g)		 倒伏
Lodging
(0-9)		 GYT指数
GYT
index
1 1 -1 1 1 1 -1
Nicolas 5948 4.3 73.9 6.1 13.2 53.4 35.8 2.9 1.3
Akina 5853 4.8 72.7 7.1 13.4 52.3 38.0 2.4 1.2
Kara 5680 4.7 71.9 8.0 14.0 54.0 38.1 2.0 0.9
Richmond 5631 3.8 71.7 5.4 12.6 55.1 39.2 3.0 0.5
Canmore 5447 4.6 71.6 7.6 14.2 54.9 39.5 3.3 0.3
Nice 5559 4.4 72.6 8.4 13.5 53.3 38.5 3.9 0.1
Orrin 5468 4.4 71.1 6.9 13.3 54.2 38.5 3.5 0.1
Adele 5354 4.6 75.3 8.4 12.8 54.0 38.7 4.5 -0.3
Dieter 5183 4.1 73.4 5.7 14.0 54.3 38.9 3.6 -0.4
Synextra 5171 4.3 72.0 7.3 14.9 56.0 37.3 3.7 -0.4
Vitality 5049 4.0 75.7 7.9 13.6 53.9 40.3 3.9 -0.9
Hidalgo 5158 4.7 74.3 8.0 13.1 53.1 34.5 4.0 -0.9
Avatar 5060 3.9 74.8 7.9 12.2 56.6 36.2 4.9 -1.3

Fig. 8

GYT biplot to show the superiority and trait profiles of 13 oat cultivars tested in the 2013-2019 Quebec provincial oat trials The arrow in red points to a higher GYT index and the arrows in blue point to strengths or weaknesses of each genotype in terms of yield-trait combinations. For example, it shows that Richmond was strong in “Y×Oil(-1)” but poor in “Y×BGL”."

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