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作物学报 ›› 2026, Vol. 52 ›› Issue (5): 1309-1325.doi: 10.3724/SP.J.1006.2026.53083

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

201份玉米自交系抗旱表型评价及可塑性分析

张宁宁1,2(), 滕雨菲1, 任娜娜2, 魏兴卓1, 闫书豪1, 樊可心1, 王永宏2, 陈文康1, 张兴华1, 朱万超1, 徐淑兔1,*(), 薛吉全1,*()   

  1. 1 西北农林科技大学农学院, 陕西杨凌 712100
    2 宁夏农林科学院农作物研究所, 宁夏银川 750011
  • 收稿日期:2025-10-27 接受日期:2026-02-27 出版日期:2026-05-12 网络出版日期:2026-03-11
  • 通讯作者: *薛吉全, E-mail: xjq2934@163.com; 徐淑兔, E-mail: shutuxu@nwafu.edu.cn
  • 作者简介:E-mail: 17711845472@163.com
  • 基金资助:
    陕西省中央引导地方资金项目(2024ZY-CGZY-17);陕西省关键核心技术攻关项目(2024NYGG001);国家“十三五”重点研发计划项目(2018YFD0100200)

Phenotypic evaluation and plasticity analysis of drought resistance in 201 maize inbred lines

Zhang Ning-Ning1,2(), Teng Yu-Fei1, Ren Na-Na2, Wei Xing-Zhuo1, Yan Shu-Hao1, Fan Ke-Xin1, Wang Yong-Hong2, Chen Wen-Kang1, Zhang Xing-Hua1, Zhu Wan-Chao1, Xu Shu-Tu1,*(), Xue Ji-Quan1,*()   

  1. 1 College of Agronomy, Northwest A&F University, Yangling 712100, Shaanxi, China
    2 Crop Research Institute of Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan 750011, Ningxia, China
  • Received:2025-10-27 Accepted:2026-02-27 Published:2026-05-12 Published online:2026-03-11
  • Contact: *Xue Ji-Quan, E-mail: xjq2934@163.com; Xu Shu-Tu, E-mail: shutuxu@nwafu.edu.cn
  • Supported by:
    Central Government’s Guidance Funds for Local Areas Project of Shaanxi Province(2024ZY-CGZY-17);Key Core Technology Research Project of Shaanxi Province(2024NYGG001);National Key R&D Program of China during the 13th Five-Year Plan Period(2018YFD0100200)

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摘要：

干旱是限制玉米产量提升的关键因素之一。表型可塑性指特定基因型对环境变化的响应模式。因此, 有必要评估玉米自交系的抗旱可塑性。本研究以2019—2020年在5个环境、2种水分处理下201份玉米材料抗旱性相关数据为基础, 基于因子分析等3种方法进行抗旱性鉴定, 将材料划分为强抗(HR)、抗(R)、中抗(MR)和弱抗(WR) 4个抗旱等级, 其中, KA105、KB020、综31等材料抗旱性较强。同时, 基于FW (Finlay-Wilkinson)回归方法对抗旱可塑性进行量化, 提出了2种玉米抗旱可塑性模式, 即有G×E正向可塑性(基因型在特定环境中具有显著优于其平均表现的正向响应)和无G×E正向可塑性(基因型在不同环境中表现相对稳定, 且未在特定环境中表现出显著优于其平均水平的正向响应)。其中, KA105、M1801等属于有G×E正向可塑性, 09B-6-2等属于无G×E正向可塑性。综合评价得出, KA105抗旱性强且具有G×E正向可塑性, 可作为适应未来抗旱育种的优异种源, 应用前景十分广阔。

关键词: 玉米, KA105, 基因型与环境互作, 抗旱可塑性, 产量

Abstract:

Drought is the primary constraint limiting maize yield improvement. Phenotypic plasticity describes how a given genotype responds to environmental variation; therefore, evaluating drought plasticity in maize inbred lines is essential. Using drought-resistance-related data for 201 inbred lines evaluated across five environments and two water regimes during 2019-2020, we assessed drought resistance using three approaches, including factor analysis, and classified the lines into four levels: highly resistant (HR), resistant (R), moderately resistant (MR), and weakly resistant (WR). Lines such as KA105, KB020, and Zong 31 showed strong drought resistance. Plasticity was then quantified using the Finlay-Wilkinson (FW) regression, and two drought plasticity patterns were defined: G×E positive plasticity (a genotype shows a significantly better positive response than its overall mean performance in specific environments) and no G×E positive plasticity (a genotype performs stably across environments and does not show a significantly better positive response relative to its overall mean in any environment). KA105 and M1801 were classified as the G×E positive plasticity type, whereas 09B-6-2 was classified as the no G×E positive plasticity type. Overall, KA105 combined strong drought resistance with G×E positive plasticity, indicating that it is a promising germplasm source for drought-resistance breeding with potential for broad application.

Key words: maize, KA105, genotype×environment interaction (G×E), drought resistant plasticity, yield

表1

201份玉米自交系名称及编号"

编号
No.		 自交系
Inbred line		 编号
No.		 自交系
Inbred line		 编号
No.		 自交系
Inbred line		 编号
No.		 自交系
Inbred line		 编号
No.		 自交系
Inbred line
1 09B-6-2 42 DH164-13 84 HS200 126 LYA81 168 WB10
2 11430 43 DH164-22 85 IBB14 127 LYB1831 169 WK858
3 137 44 DH165-4 86 ICI193 128 LYB29 170 XF68F
4 1408 45 DH169-3 87 ICI441 129 LYB70 171 XP3M
5 1475 46 DH218-9 88 ICI740 130 LYB92 172 Y06088
6 1503M 47 DH230-2 89 JH089 131 M1608 173 Y3011
7 1601 48 DH244-4 90 JH14251 132 M1801 174 YCZ17188
8 18KA14 49 DH259 91 JH49 133 M2902 175 YCZ1862
9 31778 50 DH3805 92 JL133 134 Mo17 176 YCZ1995
10 328M 51 DH448-5 93 JL230 135 NW/H537 177 YN3M
11 35S 52 DH469-4 94 JSHj94 136 P138 178 昌7-2 Chang 7-2
12 445 53 DH493-16 95 K10-140 137 PH4CV 179 京045 Jing 045
13 641 54 DH493-40 96 K10-96 138 PH6WC 180 京1472 Jing 1472
14 798-1 55 DH498-3 97 K12 139 PHJ89 181 京17 Jing 17
15 91227 56 DH509-9 98 K6 140 PHK42 182 京183 Jing 183
16 A4308 57 DH511-5 99 KA064 141 PHM49 183 京MT028 Jing MT028
17 C102 58 DH527-6 100 KA103 142 PHP85 184 ly0996
18 C113 59 DH564-15 101 KA105 143 PHPR5 185 ly8112
19 C141 60 DH567-1 102 KA115 144 PHR32 187 武9086 Wu 9086
20 C144 61 DH574-2 103 KA203 146 PHW52 188 新自3113 Xz3113
21 C145 63 DH604-17 105 KB020 147 PL101 189 新自5172 Xz5172
22 C39 64 DH679-10 106 KB081 148 RP06 190 新自5426 Xz5426
23 C40 65 DH775-13 107 KB089 149 沈137 Shen 137 191 新自6106 Xz6106
24 C50 66 DH783-11 108 KB102 150 W101 192 新自6177 Xz6177
25 C57 67 DH814-3-1 109 KB106 151 W106 193 新自618 Xz618
26 C71 68 DHB10Z5 110 KB182 152 W108 194 新自6423 Xz6423
27 C77 69 DHFKM9 111 KB207 153 W112 195 新自6453 Xz6453
28 C78 70 DHJ026-12 112 KH11-26 154 W120 196 新自6812 Xz6812
29 C93 71 DHJ030-11 113 KH1126 155 W15A 197 新自6845 Xz6845
30 Chang 7-2-1g 72 DF 114 KH128 156 W1901 198 新自7523 Xz7523
31 长S25 Chang S25 73 DM 115 KH980 157 W1902 199 郑58 Zheng 58
32 D121 74 F118 116 KY1M9 158 W414 200 自330 Zi 330
33 D201 75 F124 117 L314SL 159 W458 201 综31 Zong 31
34 DA1810 76 F141 118 L61F 160 W5387
35 DD1812 77 F3105 119 LF1011 161 W597
36 DH038-1-2 78 F7201 120 LH149 162 W72
37 DH060-8 79 FH1819 121 LM1305 163 W73
38 DH068-1 80 H159 122 LM1607 164 W74
39 DH103-3 81 H305 123 LYA1871 165 W75
40 DH129-3 82 H477 124 LYA49 166 W88
41 DH133-1 83 H901 125 LYA52 167 WA07

表2

产量及其他性状名称与定义"

性状
Trait		 定义
Definition
籽粒产量Grain yield (GY, kg) 单位面积玉米籽粒的总重量 Total weight of kernels per unit area
穗重Ear weight (EW, kg) 10个代表性果穗的总重量 Total weight of ten representative ears
单穗粒重Grain yield per plant (GYP, kg) 1个代表性果穗的总重量 Total weight of one representative ear
穗长Ear length (EL, cm) 果穗纵向最长的距离 Longest longitudinal distance of the ear
行粒数Kernel number per row (KNR) 果穗上每行籽粒的平均数量 Average number of grains per row on the ear
株高Plant height (PH, cm) 从地面到植株最高点的垂直距离
Vertical distance from the ground to the highest point of the plant
穗位高Ear height (EH, cm) 从地面到植株上第一个果穗着生节的垂直距离
Vertical distance from the ground to the node bearing the first ear on the plant
散粉期Days to anthesis (DTA, d) 播种至小区有50%的植株雄穗吐出的天数
Number of days from sowing to 50% tassel emergence in a plot
吐丝期Days to silking (DTS, d) 播种至小区有50%的植株雌穗散粉的天数
Number of days from sowing to 50% silking in a plot
散粉吐丝间隔期Anthesis-silking interval (ASI, d) 雄穗开始散粉到雌穗顶部花丝开始吐出之间的时间差
Time interval between tassel pollen shedding initiation and silk emergence from the ear tip

图1

2019年和2020年在正常灌水和干旱条件下各性状BLUP表现 缩写同表2。**和***分别表示在0.01和0.001水平差异显著; ns表示差异不显著。WW和DS分别代表正常灌水和干旱胁迫处理。BLUP: 最佳线性无偏预测。"

表3

不同水分处理下各性状BLUP值的描述统计"

处理
Treatment		 统计量
Statistic		 籽粒产量
GY (kg)		 单穗粒重
GYP (kg)		 穗重
EW (kg)		 穗长
EL (cm)		 行粒数
KNR
2019WW Mean ± SD 424.99±127.78 0.14±0.08 0.14±0.06 15.61±2.01 28.13±4.40
CV (%) 30.08 58.30 41.15 12.91 15.66
Range 83.00-882.79 0.02-0.59 0.03-0.40 4.50-23.37 0.10-43.20
Kurt -0.43 2.93 0.31 1.50 2.24
Skew 0.32 -0.09 -0.41 0.28 -0.03
2019DS Mean ± SD 297.65±127.12 0.09±0.05 0.11±0.05 14.03±1.96 26.10±4.05
CV (%) 42.71 54.06 44.18 13.95 15.53
Range 23.02-744.19 0-0.34 0.01-0.28 8.00-22.80 11.60-41.00
Kurt -0.13 0.07 -0.17 0.34 1.32
Skew -0.12 -0.09 0.20 0.13 -0.14
2020WW Mean ± SD 414.01±112.69 0.10±0.03 0.13±0.04 4.27±0.39 27.66±5.19
CV (%) 27.22 29.59 30.41 9.21 18.75
Range 27.85-687.56 0.03-0.23 0.04-0.32 1.80-5.60 7.40-44.20
Kurt -0.47 0.09 0.14 0.92 0.01
Skew 2.66 0.16 0.32 0.01 0.14
2020DS Mean ± SD 313.55±104.21 0.08±0.03 0.11±0.03 13.41±1.89 24.12±5.05
CV (%) 33.25 34.71 31.16 14.09 20.94
Range 36.34-606.94 0.01-0.19 0.02-0.24 6.80-21.60 6.13-39.00
Kurt -0.33 -0.12 -0.16 3.44 -0.01
Skew 0.05 0.21 0.20 -0.35 -0.33
处理
Treatment		 统计量
Statistic		 散粉期
DTA (d)		 吐丝期
DTS (d)		 散粉吐丝间隔期
ASI (d)		 株高
PH (cm)		 穗位高
EH (cm)
2019WW Mean ± SD 70.67±5.67 71.21±6.07 1.61±1.60 207.34±37.50 73.03±17.74
CV (%) 8.03 8.54 99.65 18.09 24.31
Range 54.00-84.00 54.00-84.00 0-9.00 94.67-315.60 32.33-134.55
Kurt 0.47 0.08 0.70 -0.21 0.49
Skew -0.64 -0.18 0.90 0.03 0.49
2019DS Mean ± SD 71.40±5.51 72.62±5.98 2.15±1.92 175.33±36.75 65.04±16.60
CV (%) 7.72 8.23 89.29 20.96 25.52
Range 54.00-82.00 55.00-88.00 0-10.00 68.17-262.73 22.33-126.00
Kurt -0.28 -0.79 -0.42 -0.55 0.20
Skew -0.65 -0.07 0.17 0.05 0.45
2020WW Mean ± SD 78.81±9.71 78.39±9.28 1.68±1.79 206.45±28.68 71.93±15.75
CV (%) 12.33 11.84 106.71 13.89 21.90
Range 50.00-96.00 50.00-97.00 0-10.00 107.20-288.70 22.60-120.70
Kurt 0.42 0.76 2.78 -0.10 -0.19
Skew 0.26 0.24 0.05 0.68 0.37
2020DS Mean ± SD 82.08±5.91 82.85±5.89 1.20±1.55 184.58±30.75 64.82±14.86
CV (%) 7.20 7.11 129.34 16.66 22.93
Range 51.00-105.00 50.00-97.00 0-9.00 88.00-673.67 14.67-120.70
Kurt 1.25 0.99 1.96 -0.14 0.37
Skew -0.43 -0.49 5.52 2.31 0.32

图2

抗旱性指标筛选及表型性状分析 缩写同表2。A: PC1与PC2分别解释了总表型变异的46.97%与27.29%。图中向量代表各指标, 其长度和方向反映其与2个主成分的相关性; B:不同性状在5个因子上的载荷程度, 反映抗旱性与多性状间的关联; 颜色由红色到蓝色, 关联度也随之降低。BLUP: 最佳线性无偏预测; WWBLUP和DSBLUP分别为正常灌水和干旱处理下产量的BLUP值; STI: 耐逆指数; SSI: 干旱敏感系数; TOL: 耐旱能力; MP: 平均生产力; DRC: 抗旱系数; GMP: 几何平均生产力; DRI: 抗旱指数。"

表4

方差极大正交旋转因子载荷"

性状 Trait 因子1 Factor 1 因子2 Factor 2 因子3 Factor 3 因子4 Factor 4 因子5 Factor 5
GYP 0.81 0.16 0.31 -0.06 0.05
EW 0.74 0.20 0.28 -0.07 -0.05
EL 0.84 -0.07 -0.22 -0.13 0.06
KNR 0.80 -0.24 -0.05 0.16 -0.01
ASI 0.09 -0.02 -0.03 0.98 -0.02
DTA 0.03 0.95 0.10 -0.12 0.06
DTS -0.02 0.95 0.15 0.03 -0.04
EH 0.10 0.18 0.94 0.03 0.01
PH 0.03 0.02 0.01 -0.02 0.99

图3

201份自交系抗旱等级划分 HR: 强抗; R: 抗; MR: 中抗; WR: 弱抗。"

图4

不同材料抗旱指数GEI效应值变化 A: 不同抗旱等级材料抗旱指数GEI效应值变化热图。纵坐标E1-E5为5个不同环境编号, 横坐标为材料编号, 揭示不同抗旱性材料对环境变异的响应模式。其中, 颜色深浅反映效应值的绝对值大小, 颜色越深(如深紫或深蓝)表明该环境下基因型与环境的互作效应越强。B: 不同抗旱等级材料抗旱指数GEI效应值在不同环境中的变化趋势。HR: 强抗; R: 抗; MR: 中抗; WR: 弱抗。E1: 陕西省榆林市; E2: 宁夏回族自治区银川市; E3: 山西省太原市; E4: 甘肃省张掖市; E5: 新疆维吾尔自治区乌鲁木齐市。GEI: 基因型与环境互作。"

图5

201份自交系产量在正常灌水、水分胁迫及其抗旱指数的可塑性模式和大小 A: 产量在WW处理下的可塑性模式; B: 产量在DS处理下的可塑性模式; C: 产量在DRI水平的可塑性模式; D: 产量在WW处理下环境梯度数值排序后材料的可塑性; E: 产量在DS处理下环境梯度数值排序后材料的可塑性; F: 产量在DRI水平环境梯度数值排序后材料的可塑性。DRI: 抗旱指数。缩写同表2和图4。处理同图1。"

图6

WW和DS条件下产量不同抗旱性材料可塑性变化趋势 A: 强抗旱性材料在WW和DS条件下的可塑性大小; B: 抗旱性材料在WW和DS条件下的可塑性大小; C: 中抗旱性材料在WW和DS条件下的可塑性大小; D: 弱抗旱性材料在WW和DS条件下的可塑性大小; E: 在DS条件下不同抗旱等级材料中可塑性升高材料数目的百分比; F: 不同抗旱等级材料在不同处理下的可塑性变化趋势。**表示P < 0.01; ***表示P < 0.001。缩写同图3。处理同图1。"

图7

可塑性与GEI存在的几种模式 A: GEI和可塑性均不存在; B: 只有可塑性存在, 没有GEI; C-D: 既有可塑性又有GEI; E: LYA81、09B-6-2、KY1M9、M1801在WW和DS条件下的可塑性。缩写同图3和图4。处理同图1。"

图8

WW和DS条件下201份自交系产量及抗旱指数可塑性表现 A: WW处理下产量的可塑性; B: DS处理下产量的可塑性; C: 产量的抗旱指数可塑性; D: WW和DS处理下产量的可塑性及产量的抗旱指数可塑性均较高的材料。DRI: 抗旱指数。缩写同表2。处理同图1。"

图9

各性状可塑性的四分位离散系数 A: WW和DS处理下10个性状的可塑性; B: 10个性状的抗旱指数可塑性; C: 不同抗旱等级材料10个性状的抗旱指数可塑性。缩写同表2和图3。处理同图1。"

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