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作物学报 ›› 2022, Vol. 48 ›› Issue (9): 2137-2154.doi: 10.3724/SP.J.1006.2022.11105

• 综述 •    下一篇

品种选育与评价的原理和方法评述

严威凯*()   

  1. 加拿大农业与农业食品部渥太华研发中心, 加拿大安大略省K1A 0C6
  • 收稿日期:2021-11-18 接受日期:2022-03-21 出版日期:2022-09-12 网络出版日期:2022-03-28
  • 通讯作者: 严威凯
  • 基金资助:
    本研究部分由ASP-001支持

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 Published:2022-09-12 Published online:2022-03-28
  • Contact: YAN Weikai
  • Supported by:
    The work was partially supported by ASP-001

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摘要：

植物育种对于满足人们日益增长的对衣食住行的需求并适应不断变化的气候条件起着不可或缺的作用。育种过程包括制定育种目标、创建育种群体、选择优良品系三大环节。研究者围绕提高育种效率, 特别是选择效率提出了许多概念和方法, 比如各种应对基因型-环境互作的策略, 各种稳定性分析方法, 各种品种生态区划分方法, 各种试验设计和分析方法, 各种双标图分析方法, 以及各种多性状综合评价方法等等。另外, 全基因组预测已经发展成为育种工作者必须考虑和不能忽视的方法。了解这些概念、方法之间的关系, 哪些是有用的, 哪些是不必要的, 哪些是有问题的, 它们在整个育种体系中处于什么位置, 对提高育种效率具有实际意义。本文以个人长期的研究、思考和育种实践为基础, 对育种目标制定、育种群体创建, 特别是后代选择的基本原理、概念和方法进行了梳理、澄清和补充, 以期对品种选育和评价的理论和方法形成一个较完整、系统的论述, 并用实例演示一些重要的分析方法。

关键词: 育种家公式, 遗传力, 基因型-环境互作, 品种生态区, 充分试验, 稳定性分析, 选择指数, 全基因组选择

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

图1

正态分布下的后代选择方程"

表1

正态分布下由群体大小(n)来确定最小误选概率(α)和最大选择强度(i)"

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

表2

不同遗传力(h2)下所允许的选择强度(ih)、淘汰率(1-α)、误选率(α)、必须保留的个体数目(N)及选择成功率(1/N)(设n = 10,000, 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

表3

渥太华燕麦育种程序中各选择阶段的选择(淘汰)强度"

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

图2

显示魁北克2013-2019年燕麦试验中产量结果的GGE双标图 图中118个品系用蓝色“+”代表; 63个试验(地点-年份组合)用红字标出。每个试验标示为地点缩写加年份的后两位数字。紧跟地点缩写后面的数字表示其所属农业生态区。如CAUS3_13表示在CAUS这个地点在2013年的试验, 而CAUS (Causapscal)属于第三农业生态区。"

图3

显示魁北克2个燕麦生态区的GGE+GGL双标图 图上方的品种生态区包括来自第二、三农业生态区的6个试验点(NORM3, HEBE3, CAUS3, PRIN2, STET3, STAU2), 图下方的品种生态区包括来自第1、3生态区的3个试验点及渥太华(NDHY1, STHU1, LAPO3, OTT)。2个品种生态区偶有交叉。"

图4

显示魁北克2个燕麦生态区的LG双标图 基于2013-2019年魁北克省燕麦试验的产量数据。"

图5

显示13个燕麦品种在魁北克2个燕麦生态区内平均产量和稳定性的GGE双标图 a) ME2a亚区; b) ME2b亚区。数据来自2013-2019魁北克省燕麦区域试验。"

表4

按魁北克燕麦试验的产量数据所估算的最适试验年数(ymin)"

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

表5

魁北克省燕麦实际试验点数与按产量数据估算的最少(适)试验点数"

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

图6

显示在魁北克2个燕麦生态区内各环境中最高产品种的GGE双标图 a) ME2a亚区; b) ME2b亚区。数据来自2013-2019魁北克省燕麦区域试验。"

图7

多元回归校正区组内田间变异趋势 数据来源: 一个燕麦品比试验中的冠锈病数据, 渥太华, 2021。"

表6

13个燕麦品种的8个性状值及其GYT指数(2013-2019)"

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

图8

显示13个燕麦品种综合排名及性状构成的GYT双标图(2013-2019) 品种用蓝字标出, 产量-性状结合用红字标出。红色箭头指向较高的GYT指数, 蓝色箭头指向各品种的优势或劣势性状。"

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