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作物学报 ›› 2026, Vol. 52 ›› Issue (10): 3006-3022.doi: 10.3724/SP.J.1006.2026.64032

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

马铃薯产量和类黄酮含量的基因型与环境互作分析

雷鹏1(), 李丽2, 袁剑龙1, 夏露露1, 周小成1, 张峰1,*()   

  1. 1 甘肃农业大学农学院 / 省部共建干旱生境作物学国家重点实验室, 甘肃兰州 730070
    2 甘肃省山丹培黎学校, 甘肃张掖 734100
  • 收稿日期:2026-03-13 接受日期:2026-06-11 出版日期:2026-10-12 网络出版日期:2026-06-22
  • 通讯作者: 张峰, E-mail: zhangf@gsau.edu.cn
  • 作者简介:雷鹏, E-mail: 1060909384@qq.com
  • 基金资助:
    甘肃省科技重大专项项目(21ZD11NA009);甘肃省高等学校产业支撑计划项目(2023CYZC-44);甘肃省高校科研创新平台项目(2024CXPT-01)

Analysis of genotype-by-environment interaction for potato yield and flavonoid content

Lei Peng1(), Li Li2, Yuan Jian-Long1, Xia Lu-Lu1, Zhou Xiao-Cheng1, Zhang Feng1,*()   

  1. 1 Agronomy College, Gansu Agricultural University / State Key Laboratory of Arid Land Crop Science, Lanzhou 730070, Gansu, China
    2 Shandan Bailie School of Gansu Province, Zhangye 734100, Gansu, China
  • Received:2026-03-13 Accepted:2026-06-11 Published:2026-10-12 Published online:2026-06-22
  • Contact: Zhang Feng, E-mail: zhangf@gsau.edu.cn
  • Supported by:
    Major Science and Technology Project of Gansu Province(21ZD11NA009);Industrial Support Program for Higher Education Institutions of Gansu Province(2023CYZC-44);Scientific Research Innovation Platform Project for Higher Education Institutions of Gansu Province(2024CXPT-01)

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摘要：

为实现产量与营养品质的协同改良, 本研究通过基因型和基因型与环境互作(GGE)双标图方法, 系统解析不同生态类型区马铃薯产量与类黄酮含量的遗传差异、环境适应性与性状稳定性。以筛选适宜特定生态区高产、高类黄酮含量且稳定的优良基因型为核心, 为营养强化型马铃薯新品种选育提供理论支撑。试验共选取130份马铃薯品种(系), 于2021—2022年在甘肃省渭源县、安定区及永昌县3个生态区开展2年3点试验。收获后测定小区产量及儿茶素、芦丁、烟花苷、槲皮素和山奈酚含量, 并采用联合方差分析与GGE双标图对产量和品质性状进行基因型与环境互作分析。方差分析显示, 除小区产量在年份效应中无显著差异外, 各性状的基因型效应、环境效应及基因型与环境互作效应均达极显著水平(P < 0.01)。其中, 小区产量、儿茶素和芦丁含量主要受基因型效应影响, 而烟花苷、槲皮素和山奈酚含量以基因型与环境互作效应为主。小区产量GGE分析结果表明, G122在2021年安定、2022年安定、2022年渭源和2022年永昌试点产量最高; G27在2021年永昌试点产量最高; G36在2021年渭源试点产量最高; C18、G122、C6、G102、G42、G49、C3、G9高产且稳定; 试点区分力强弱依次为永昌、安定、渭源试点, 以安定试点代表性最强。类黄酮含量GGE分析结果表明, G79在3个试点儿茶素含量均最高, 在安定、渭源试点山奈酚含量最高, 在永昌试点烟花苷含量最高; C16在安定、渭源试点芦丁与烟花苷含量均最高; G37、G4、G46分别在永昌试点中芦丁、槲皮素、山奈酚含量最高; G32在安定、渭源试点槲皮素含量最高; G98、G63、G1、G129、G102儿茶素含量高且稳定; G37、G113、G49、C11、G93芦丁含量高且稳定; G37、G122、G13、G21烟花苷含量高且稳定; G46、G71、G124、G79槲皮素含量高且稳定; G9、C5、G27山奈酚含量高且稳定; 试点区分力强弱依次为永昌、渭源、安定, 以永昌试点代表性最强。结合小区产量和类黄酮含量的GGE模型, 筛选出G122、G102、G49和G93高产、高类黄酮含量且稳定的优良品系。综合试点区分力和代表性, 安定试点可作为产量评价的理想环境, 永昌试点则更适于特定环境下产量和类黄酮含量品种(系)的筛选。

关键词: 产量, 类黄酮, GGE双标图, 基因型环境互作, 多年多点, 试点评价

Abstract:

To achieve coordinated improvement in yield and nutritional quality, the GGE (genotype+genotype×environment interaction) biplot method was employed to systematically dissect the genetic differences, environmental adaptability, and trait stability of potato yield and flavonoid content across different ecological regions. The core objective was to screen elite genotypes with high yield, high flavonoid content, and stability adapted to specific ecological zones, thereby providing theoretical support for breeding nutritionally enhanced potato varieties. A total of 130 potato varieties (lines) were tested in a two-year (2021-2022), 3-location trial conducted in three ecological regions of Gansu province: Weiyuan county, Anding district, and Yongchang county. Plot yield and contents of catechin, rutin, nicotiflorin, quercetin, and kaempferol were measured after harvest. Joint analysis of variance and GGE biplot were used to analyze the genotype×environment interaction for yield and quality traits. The ANOVA showed that, except for plot yield which had no significant year effect, the effects of genotype, environment, and genotype×environment interaction were highly significant (P < 0.01) for all traits. Plot yield, catechin content, and rutin content were mainly influenced by genotype, whereas nicotiflorin, quercetin and kaempferol contents were predominantly affected by genotype×environment interaction. GGE analysis for plot yield indicated that G122 had the highest yield at Anding (2021, 2022), Weiyuan (2022), and Yongchang (2022). G27 had the highest yield at Yongchang in 2021, G36 had the highest yield at Weiyuan in 2021. C18, G122, C6, G102, G42, G49, C3, and G9 were high-yielding and stable. The discriminative power of test locations ranked as Yongchang > Anding > Weiyuan, with the Anding being the most representative. GGE analysis of flavonoid content revealed that G79 had the highest catechin content across all three locations, the highest kaempferol content at Anding and Weiyuan, and the highest nicotiflorin content at Yongchang. C16 had the highest rutin and nicotiflorin contents at Anding and Weiyuan. G37, G4, and G46 had the highest rutin, quercetin, and kaempferol contents, respectively, at Yongchang. G32 had the highest quercetin content at Anding and Weiyuan. G98, G63, G1, G129, and G102 had high and stable catechin content. G37, G113, G49, C11, and G93 had high and stable rutin content. G37, G122, G13, and G21 had high and stable nicotiflorin content. G46, G71, G124, and G79 had high and stable quercetin content. G9, C5, and G27 had high and stable kaempferol content. The discriminative power of test locations ranked as Yongchang > Weiyuan > Anding, with the Yongchang being the most representative for flavonoid traits. Using the GGE model combining plot yield and flavonoid content, elite lines (G122, G102, G49, and G93) were identified as high-yielding, high in flavonoid content, and stable. Considering both discriminatory power and representativeness, Anding is recommended as an ideal environment for yield evaluation, while Yongchang is more suitable for screening varieties (lines) for both yield and flavonoid content under specific environments.

Key words: yield, flavonoid, GGE biplot, genotype-environment interaction, multi-years and sites, pilot evaluation

表1

参试材料"

编号 品种(系) 编号 品种(系) 编号 品种(系)
Code Variety (line) Code Variety (line) Code Variety (line)
G1 CIP 381381.13 G63 CIP 394614.117 G128 CIP 391919.3
G4 CIP 392617.54 G64 CIP 394881.8 G129 CIP 391930.1
G5 CIP 392634.52 G65 CIP 395186.6 G131 CIP 394906.6
G8 CIP 393227.66 G67 CIP 395195.7 A1 215
G9 CIP 393228.67 G68 CIP 395196.4 A2 1867
G10 CIP 393371.164 G70 CIP 395432.51 A3 2137
G11 CIP 391004.18 G71 CIP 395434.1 A4 Range
G12 CIP 392657.171 G72 CIP 395436.8 A5 SC04
G13 CIP 393280.64 G74 CIP 396311.1 A6 SC05
G14 CIP 391047.64 G77 CIP 397014.2 A7 Russet Burbank
G15 CIP 391058.175 G79 CIP 397029.21 A8 Atlantic
G16 CIP 393085.5 G81 CIP 397039.51 A9 Shepody
G17 CIP 398192.213 G82 CIP 397044.25 E1 H0902
G21 CIP 398180.289 G84 CIP 397065.2 E2 H0913
G22 CIP 398180.292 G85 CIP 397067.2 E3 H0916
G23 CIP 398180.612 G86 CIP 397069.5 E4 H0931
G25 CIP 398203.509 G87 CIP 397073.15 E5 H0933
G27 CIP 398208.33 G88 CIP 397078.12 E6 H0938
G29 CIP 300054.29 G91 CIP 397098.12 E7 H0941
G30 CIP 301024.14 G92 CIP 397099.6 E8 H0951
G31 CIP 301029.18 G93 CIP 397100.9 E9 H0952
G32 CIP 301040.63 G94 CIP 397196.3 E10 H0953
G33 CIP 300046.22 G96 CIP 397197.9 E11 荷兰4 Helan 4
G35 CIP 300054.29 G98 CIP 388611.22 E12 Innovator
G36 CIP 300056.33 G99 CIP 388615.22 C1 北方002 Beifang 002
G37 CIP 300063.4 G100 CIP 389468.3 C2 北方106 Beifang 106
G39 CIP 300072.1 G102 CIP 391180.6 C3 定薯4号 Dingshu 4
G42 CIP 300101.11 G104 CIP 391724.1 C4 东农310 Dongnong 310
G43 CIP 379706.27 G105 CIP 392032.2 C5 甘农薯7号 Gannongshu 7
G44 CIP 385499.11 G106 CIP 392740.4 C6 甘农薯9号 Gannongshu 9
G45 CIP 385561.124 G107 CIP 392745.7 C7 丽薯13号 Lishu 13
G46 CIP 388676.1 G108 CIP 392759.1 C8 龙薯12号 Longshu 12
G48 CIP 390478.9 G110 CIP 393615.6 C9 龙薯4号Longshu 4
G49 CIP 391207.2 G112 CIP 397030.31 C10 陇薯10号 Longshu 10
G50 CIP 391382.18 G113 CIP 397035.26 C11 陇薯16号 Longshu 16
G51 CIP 392781.1 G114 CIP 302428.20 C12 陇薯7号 Longshu 7
G52 CIP 392797.22 G115 CIP 302476.108 C13 闽薯4号 Minshu 4
G53 CIP 392822.3 G116 CIP 302499.30 C14 青薯10号 Qingshu 10
G54 CIP 392973.48 G118 CIP 304350.100 C15 天薯12号 Tianshu 12
G56 CIP 394034.65 G121 CIP 304371.67 C16 云薯901 Yunshu 901
G57 CIP 394034.7 G122 CIP 304383.41 C17 中薯18号 Zhongshu 18
G59 CIP 394600.52 G124 CIP 304387.39 C18 中薯22号 Zhongshu 22
G61 CIP 394613.139 G125 CIP 304405.47
G62 CIP 394613.32 G127 CIP 397077.16

表2

试点气候基本信息"

试点
Location		 海拔
Altitude (m)		 年降水量
Annual precipitation (mm)		 年平均温度
Annual averaged temperature (℃)		 灌溉模式
Irrigation method		 年日照时数
Annual sunshine hours (h)
2021年渭源21-WY 2460 518.06 6.28 无Rain-fed 1824.58
2022年渭源22-WY 402.76 7.94 无Rain-fed 1906.83
2021年安定21-AD 1920 419.53 7.35 无Rain-fed 1659.52
2022年安定22-AD 295.67 7.41 无Rain-fed 1697.14
2021年永昌21-YC 1954 334.88 8.17 漫灌Flood irrigation 1897.07
2022年永昌22-YC 210.27 8.07 漫灌Flood irrigation 1881.65

表3

小区产量统计学描述"

性状
Trait		 环境
Environment		 最大值
Max.		 最小值
Min.		 平均值
Mean		 标准差
SD		 变异系数
CV (%)
小区产量
Yield per plot		 2021年安定21-AD 6.71 0.13 2.73 1.49 54.6
2021年渭源21-WY 8.98 1.19 3.70 1.64 44.3
2021年永昌21-YC 10.87 0.40 4.13 2.32 56.2
2022年安定22-AD 10.22 0.31 3.02 1.91 63.3
2022年渭源22-WY 7.69 0.59 2.81 1.41 50.2
2022年永昌22-YC 13.56 0.45 4.74 2.86 60.3

图1

小区产量显著性分析 AD、WY、YC分别代表安定、渭源和永昌试点。图中数值(2.45、2.79、3.54、2.49、3.87和4.08)为对应环境下小区产量的中位数, 单位为kg 1.98 m-2。不同小写字母表示在0.05水平的显著性差异。采用Duncan新复极差法进行多重比较。"

表4

小区产量方差分析"

产量性状
Yield trait		 变异来源
Source of variation		 平方和
Sum of square		 自由度
df		 均方
Mean square		 F检验
F test		 P-value 遗传力
H2 (%)
小区产量
Yield per plot		 基因型Genotype (G) 5248.926 129 40.689 23.52 < 0.001 66.8
年份Year (Y) 0.555 1 0.555 0.32 0.571
环境Environment (E) 996.504 2 498.252 288.02 < 0.001
年份×环境Y×E 247.416 2 123.708 71.51 < 0.001
基因型×年份G×Y 810.767 129 6.285 3.63 < 0.001
基因型×环境G×E 1657.553 258 6.425 3.71 < 0.001
基因型×年份×环境G×Y×E 1603.025 258 6.213 3.59 < 0.001
残差Residual 2698.898 1560 1.730
总变异Total variation 13,263.445 2339

图2

品种(系)小区产量适应性分析 绿色字体代表品种(系), 蓝色字体代表环境。"

图3

品种(系)小区产量稳定性分析 绿色字体代表品种(系), 蓝色字体代表环境。“○”代表平均环境; 带箭头的轴为平均环境轴。"

图4

基于小区产量的试点分析 绿色字体代表品种(系), 蓝色字体代表环境。“○”代表平均环境; 带箭头的轴为平均环境轴。"

图5

马铃薯类黄酮含量分布 AD、WY、YC分别代表安定、渭源和永昌试点。"

图6

马铃薯类黄酮平均含量及显著性分析 AD、WY、YC分别代表安定、渭源和永昌试点。图中数值为平均值±标准误。不同大写字母表示不同试点同一成分间差异显著 (P < 0.05), 不同小写字母表示同一试点不同成分间差异显著(P < 0.05)。采用Duncan新复极差法进行多重比较。"

表5

马铃薯类黄酮含量方差分析"

类黄酮
Flavonoid		 变异来源
Source of variation		 平方和
Sum of square		 自由度
df		 均方
Mean square		 F检验
F test		 P-value 遗传力
H2 (%)
儿茶素
(+)-Catechin		 基因型Genotype (G) 678,154.867 128 5298.085 58.101 < 0.001 82.2
环境Environment (E) 7777.558 2 3888.779 42.646 < 0.001
基因型×环境G×E 239,741.196 253 947.594 10.392 < 0.001
残差Residual 70,031.562 768 91.187
总变异Total variation 996,091.985 1151
芦丁
Rutin		 基因型Genotype (G) 270,237.273 128 2111.229 63.317 < 0.001 65.8
环境Environment (E) 27,651.806 2 13,825.903 414.648 < 0.001
基因型×环境G×E 183,944.222 254 724.190 21.719 < 0.001
残差Residual 25,674.664 770 33.344
总变异Total variation 505,062.501 1154
烟花苷
Nicotiflorin		 基因型Genotype (G) 95,291.403 128 744.464 157.680 < 0.001 28.4
环境Environment (E) 24,097.042 2 12,048.521 2551.915 < 0.001
基因型×环境G×E 135,118.727 255 529.877 112.230 < 0.001
残差Residual 3644.894 772 4.721
总变异Total variation 257,411.814 1157
槲皮素
Quercetin		 基因型Genotype (G) 231.739 128 1.810 17.926 < 0.001 36.7
环境Environment (E) 4.571 2 2.286 22.631 < 0.001
基因型×环境G×E 288.000 244 1.180 11.687 < 0.001
残差Residual 75.748 750 0.101
总变异Total variation 600.827 1124
山奈酚
Kaempferol		 基因型Genotype (G) 6.125 128 0.048 13.546 < 0.001 -7.8
环境Environment (E) 0.275 2 0.137 38.889 < 0.001
基因型×环境G×E 13.133 251 0.052 14.812 < 0.001
残差Residual 2.685 760 0.004
总变异Total variation 22.176 1141

图7

品种(系)类黄酮含量适应性分析 A: 儿茶素; B: 芦丁; C: 烟花苷; D: 槲皮素; E: 山奈酚。绿色字体代表品种(系), 蓝色字体代表环境。"

图8

品种(系)类黄酮含量稳定性分析 A: 儿茶素; B: 芦丁; C: 烟花苷; D: 槲皮素; E: 山奈酚。绿色字体代表品种(系), 蓝色字体代表环境。“○”代表平均环境; 带箭头的轴为平均环境轴。"

图9

基于类黄酮含量的试点分析 A: 儿茶素; B: 芦丁; C: 烟花苷; D: 槲皮素; E: 山奈酚。绿色字体代表品种(系), 蓝色字体代表环境。“○”代表平均环境; 带箭头的轴为平均环境轴。"

图10

马铃薯小区产量和类黄酮含量的相关性分析 *、**分别表示在0.05和0.01水平相关性显著。"

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