山西谷子种质资源耐瘠性鉴定及综合评价

doi:10.3864/j.issn.0578-1752.2026.11.003

中国农业科学 ›› 2026, Vol. 59 ›› Issue (11): 2325-2339.doi: 10.3864/j.issn.0578-1752.2026.11.003

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

山西谷子种质资源耐瘠性鉴定及综合评价

谢永祥¹^,²(), 潘怡敏¹^,², 黄蕊², 秦慧彬², 侯森², 贺强³, 凌亮⁴^,⁵(), 穆志新²(), 王海岗²()

¹ 山西农业大学农学院，山西太谷 030801
² 山西农业大学农业基因资源研究中心，太原 030031
³ 中国农业科学院作物科学研究所/作物基因资源与育种全国重点实验室，北京 100081
⁴ 山西农业大学山西功能食品研究院，太原 030031
⁵ 新疆生产建设兵团第六师农业科学研究所，新疆五家渠 830301

收稿日期:2025-10-31 接受日期:2025-12-15 出版日期:2026-06-01 发布日期:2026-06-03
通信作者:
凌亮，E-mail：478781770@qq.com。
穆志新，E-mail：muzx2008@sina.com。
王海岗，E-mail：wanghg@sxau.edu.cn
联系方式: 谢永祥，E-mail：2874911460@qq.com。
基金资助:
国家自然科学基金(32241041); 国家自然科学基金(32522080); 山西省科技重大专项计划“揭榜挂帅”项目(202101140601027); 山西省基础研究计划(202203021212472); 国家农作物种质资源保护与利用(22250319); 国家农作物种质资源平台(NCGRC-2025-026); 山西农业大学生物育种工程(YZGC149); 山西省现代农业产业技术体系建设专项(2025CYJSTX10-5)

Identification and Comprehensive Evaluation of the Barren-Tolerant Germplasm Resources of Foxtail Millet in Shanxi

XIE YongXiang¹^,²(), PAN YiMin¹^,², HUANG Rui², QIN HuiBin², HOU Sen², HE Qiang³, LING Liang⁴^,⁵(), MU ZhiXin²(), WANG HaiGang²()

¹ College of Agronomy, Shanxi Agricultural University, Taigu 030801, Shanxi
² Center for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan 030031
³ Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/State Key Laboratory of Crop Gene Resources and Breeding, Beijing 100081
⁴ Shanxi Institute for Functional Food, Shanxi Agricultural University, Taiyuan 030031
⁵ Agricultural Science Research Institute of the Sixth Division of Xinjiang Production and Construction Corps, Wujiaqu 830301, Xinjiang

Received:2025-10-31 Accepted:2025-12-15 Published:2026-06-01 Online:2026-06-03

摘要/Abstract

摘要：

【目的】通过对山西谷子种质资源进行系统耐瘠性鉴定与综合评价，筛选优异耐瘠种质，建立评价模型，筛选鉴定指标，为谷子耐瘠品种的高效选育提供理论依据与方法支撑。【方法】以617份山西谷子地方品种为试验材料，于2023—2024年分别在太原（23TY，24TY，瘠薄胁迫）和东阳（23DY，24DY，正常肥力）种植，测定节数、茎粗、穗粗、株高、颈长、穗长、叶长、叶宽、穗重、穗粒重、千粒重11个指标，通过正态分布检验、耐瘠薄系数差异分析、相关性分析、聚类分析和回归分析等方法，对谷子种质资源的耐瘠性进行综合评价鉴定。【结果】各农艺性状的变异幅度存在差异，变异系数为9.23%—48.05%，其中，23TY叶宽的变异系数最小，为9.23%；24TY穗粒重的变异系数最大，为48.05%。K-S检验结果表明，除了节数、穗长、叶宽和穗重之外，其他性状在不同环境中均存在不同程度的正态性分布（P>0.05）。通过对两年两点4个环境中测量的表型值进行相关性分析，穗重和穗粒重呈显著正相关，且相关系数最大，其次是节数与株高、穗长与叶长。此外，颈长与节数在23TY、23DY呈显著负相关；叶长与株高、节数在23TY呈显著负相关；颈长与穗粗在23TY呈显著负相关；颈长与株高在23DY呈显著负相关。主成分分析结果表明，将11个表型性状转化为2个综合指标，累积解释率达到59.68%。利用隶属函数法计算综合耐瘠薄评价值（D值），进行聚类分析，按照耐瘠薄强弱分为3种类型，第Ⅰ类不耐瘠品种有13个，D值为0.09—0.28；第Ⅱ类中度耐瘠品种包括595个，D值为0.40—0.81；第Ⅲ类耐瘠品种有9个，D值为0.84—0.93，其中，来源于阳泉市的毛软谷为耐瘠性最强的品种。采用多元回归分析方法，建立耐瘠薄预测评价模型Y=-0.031+0.129X₉+0.167X₁₀+0.141X₆+0.233X₈+0.205X₄（R²=0.951，P<0.001）。【结论】采用多元统计分析方法可有效评价与预测谷子种质的耐瘠薄性，筛选出株高、穗长、叶宽、穗重、穗粒重5个表型性状作为耐瘠薄鉴定评价指标，鉴定到阳泉市的毛软谷为耐瘠性最强的种质。

关键词: 谷子, 种质资源, 耐瘠薄, 综合评价, 隶属函数法

Abstract:

【Objective】This study aimed to select superior barren-tolerant germplasm, establish an evaluation model, and identify diagnostic indicators in foxtail millet germplasm resources from Shanxi, so as to provide the theoretical basis and methodological support for the efficient breeding of barren-tolerant foxtail millet varieties. 【Method】617 local foxtail millet varieties were used as experimental materials. Trials were carried out under low-fertility stress in Taiyuan (23TY, 24TY) and under normal fertility conditions in Dongyang (23DY, 24DY) from 2023 to 2024. Eleven indicators were measured, including stem node number (SNN), stem diameter (SD), panicle diameter (PD), plant height (PH), peduncle length (PeL), panicle length (PaL), leaf length (LL), leaf width (LW), spike weight per plant (SWP), grain weight per plant (GWP), and thousand-grain weight (TGW). A comprehensive evaluation and identification were carried out using multiple analytical methods, such as normal distribution test, barren tolerance coefficient difference analysis, correlation analysis, cluster analysis, and regression analysis. 【Result】The results showed significant differences in agronomic traits, with coefficients of variation ranging from 9.23% to 48.05%. Specifically, the coefficient of variation for LW in 23TY was the smallest (9.23%), while the coefficient for GWP in 24TY was the largest (48.05%). K-S test results indicated that, except for SNN, PaL, LW, and SWP, other traits showed varying degrees of normal distribution in different environments (P>0.05). Correlation analysis showed that SWP and GWP exhibited a significant positive correlation with the highest correlation coefficient, followed by SNN with PH, PaL with LL. In addition, PeL and SNN showed a significant negative correlation in 23TY and 23DY; LL and PH, LL and SNN, PeL and PD had a significant negative correlation in 23TY; and PeL was significantly negatively correlated with PH in 23DY. Principal component analysis results revealed that 11 phenotypic traits were converted into 2 comprehensive indices, with a cumulative explanation rate of 59.68%. Using the membership function method calculated the barren tolerance (D value), and cluster analysis was performed. The varieties were classified into three categories: Class I included 13 barren-sensitive varieties with D values ranging from 0.09 to 0.28; Class Ⅱ included 595 moderately barren-tolerant varieties with D values ranging from 0.40 to 0.81; Class Ⅲ included 9 barren-tolerant varieties with D values ranging from 0.84 to 0.93. Maorangu was the most barren-tolerant variety from Yangquan city. Through multiple regression analysis, a predictive evaluation model for barren tolerance was established: Y=-0.031+0.129X₉+0.167X₁₀+0.141X₆+0.233X₈+ 0.205X₄ (R²=0.951, P<0.001). 【Conclusion】Using multivariate statistical analysis methods, it is reliable to evaluate and predict the barren tolerance of foxtail millet germplasm. Five phenotypic traits are selected as evaluation indicators for barren tolerance: plant height, panicle length, leaf width, spike weight per plant, grain weight per plant. The Maorangu variety from Yangquan city was the strongest barren tolerance.

Key words: foxtail millet, germplasm resources, barren tolerance, comprehensive evaluation, subordinate function method

谢永祥, 潘怡敏, 黄蕊, 秦慧彬, 侯森, 贺强, 凌亮, 穆志新, 王海岗. 山西谷子种质资源耐瘠性鉴定及综合评价[J]. 中国农业科学, 2026, 59(11): 2325-2339.

XIE YongXiang, PAN YiMin, HUANG Rui, QIN HuiBin, HOU Sen, HE Qiang, LING Liang, MU ZhiXin, WANG HaiGang. Identification and Comprehensive Evaluation of the Barren-Tolerant Germplasm Resources of Foxtail Millet in Shanxi[J]. Scientia Agricultura Sinica, 2026, 59(11): 2325-2339.

图/表 10

表 1

图1

表2

617份谷子种质资源的农艺性状的统计分析"

性状Trait	环境Environment	平均值Mean	变异系数Coefficient variation (%)	偏度Skewness	峰度Kurtosis	P值P value
节数 SNN	23TY	11.75±1.43	12.24	-0.01	1.03	0.000
	24TY	11.20±1.60	14.36	-0.26	0.05	0.000
	23DY	10.79±1.81	16.75	-0.05	0.00	0.000
	24DY	11.43±1.68	14.71	-0.07	-0.30	0.000
茎粗 SD	23TY	4.03±0.76	18.77	0.62	1.21	0.001
	24TY	5.44±1.12	20.63	0.64	1.28	0.000
	23DY	7.29±0.99	13.63	0.46	2.63	0.200*
	24DY	5.88±1.02	17.30	0.18	0.03	0.200*
穗粗 PD	23TY	15.51±2.72	17.52	1.19	5.46	0.000
	24TY	19.08±3.97	20.83	0.88	1.14	0.000
	23DY	23.94±4.60	19.29	0.28	0.02	0.200*
	24DY	24.29±4.78	19.73	0.62	1.59	0.000
株高 PH	23TY	80.91±13.37	16.55	-0.15	0.13	0.200*
	24TY	89.82±16.67	18.57	-0.09	-0.37	0.011
	23DY	106.17±16.41	15.42	-0.26	0.13	0.060*
	24DY	104.14±16.84	16.18	-0.32	-0.02	0.000
颈长 PeL	23TY	38.41±5.01	13.04	0.07	1.20	0.001
	24TY	36.97±5.83	15.84	0.34	0.43	0.009
	23DY	33.93±6.81	20.05	0.24	0.03	0.077*
	24DY	33.98±5.69	16.77	0.35	0.45	0.000
穗长 PaL	23TY	18.75±3.85	20.53	0.46	0.43	0.001
	24TY	18.41±4.87	26.47	0.51	-0.14	0.001
	23DY	25.58±4.80	18.86	0.21	0.21	0.004
	24DY	26.61±5.49	20.71	0.48	0.23	0.001
叶长 LL	23TY	34.28±5.14	15.06	0.28	0.14	0.171*
	24TY	33.45±6.78	20.33	0.21	-0.48	0.077*
	23DY	39.94±4.98	12.54	0.11	0.59	0.009
	24DY	41.07±6.26	15.32	0.12	0.53	0.184*
叶宽 LW	23TY	2.17±0.20	9.23	1.51	7.42	0.000
	24TY	2.34±0.44	18.93	0.36	0.26	0.003
	23DY	2.90±0.41	14.24	0.07	1.09	0.000
	24DY	2.72±0.30	10.99	1.08	3.29	0.000
穗重 SWP	23TY	11.85±4.61	38.81	0.50	1.47	0.000
	24TY	12.20±5.46	45.08	0.66	0.20	0.000
	23DY	21.19±5.67	26.80	0.52	0.52	0.003
	24DY	17.87±4.61	26.01	0.37	0.06	0.022
穗粒重 GWP	23TY	8.67±3.87	44.52	0.52	1.65	0.006
	24TY	6.57±3.15	48.05	0.60	-0.15	0.000
	23DY	16.91±4.78	28.41	0.51	0.49	0.029
	24DY	13.58±4.00	29.74	0.39	0.20	0.200*
千粒重 TGW	23TY	2.88±0.34	11.84	-0.72	4.23	0.000
	24TY	3.04±0.39	12.83	-0.73	3.07	0.004
	23DY	3.43±0.39	11.50	-0.08	0.04	0.200*
	24DY	3.40±0.39	11.69	-0.13	0.40	0.200*

表2

图2

图3

表3

图4

表4

表5

表6

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地点 Location	全氮 Total nitrogen (g·kg^-1)	有效磷 Available phosphorus (mg·kg^-1)	速效钾 Available potassium (mg·kg^-1)	有机质 Organic matter (g·kg^-1)	酸碱度 pH
太原TY	0.58	5.67	116.90	9.45	8.51
东阳DY	0.80	5.30	118.05	13.95	8.65

指标 Index	主成分1 Principal component 1	主成分2 Principal component 2
节数SNN	0.689	-0.271
茎粗SD	0.668	-0.242
穗粗PD	0.703	-0.057
株高PH	0.748	-0.210
颈长PeL	0.470	0.071
穗长PaL	0.764	-0.148
叶长LL	0.751	-0.334
叶宽LW	0.772	-0.238
穗重SWP	0.664	0.687
穗粒重GWP	0.646	0.715
千粒重TGW	0.592	0.239
特征值Eigenvalue	5.150	1.41
贡献率Contributive rate (%)	46.82	12.86
累积贡献率 Cumulative contributive rate (%)	46.82	59.68

指标Index	相关系数Correlation coefficient
节数SNN	0.579**
茎粗SD	0.567**
穗粗PD	0.654**
株高PH	0.653**
颈长PeL	0.471**
穗长PaL	0.687**
叶长LL	0.619**
叶宽LW	0.668**
穗重SWP	0.837**
穗粒重GWP	0.828**
千粒重TGW	0.637**

多元回归方程 Multiple regression equation	相关系数 r	判定系数 R²	F值 F value	P值 P value
Y=0.354+0.227X₉+0.182X₁₀	0.847	0.718	779.906	≤0.001
Y=0.174+0.159X₉+0.172X₁₀+0.319X₆	0.925	0.856	1217.475	≤0.001
Y=0.048+0.14X₉+0.174X₁₀+0.189X₆+0.286X₈	0.958	0.917	1699.921	≤0.001
Y=0.027+0.138X₉+0.161X₁₀+0.154X₆+0.244X₈+0.121X₃	0.966	0.932	1681.664	≤0.001
Y=-0.031+0.129X₉+0.167X₁₀+0.141X₆+0.233X₈+0.205X₄	0.975	0.951	2386.573	≤0.001
Y=-0.039+0.128X₉+0.158X₁₀+0.12X₆+0.207X₈+0.186X₄+0.089X₃	0.979	0.959	2381.147	≤0.001
Y=-0.133+0.124X₉+0.134X₁₀+0.117X₆+0.162X₈+0.161X₄+0.098X₃+0.188X₁₁	0.992	0.983	5131.342	≤0.001
Y=-0.138+0.122X₉+0.139X₁₀+0.082X₆+0.128X₈+0.143X₄+0.102X₃+0.186X₁₁+0.082X₇	0.994	0.988	6237.503	≤0.001

材料 Materials	地点 Location	节数 SNN	茎粗 SD	穗粗 PD	株高 PH	颈长 PeL	穗长 PaL	叶长 LL	叶宽 LW	穗重 SWP	穗粒重 GWP	千粒重 TGW
竹叶青 Zhuyeqing	TY	11.33	5.48	17.88	69.48	38.98	24.28	36.37	2.34	14.51	9.85	3.10
竹叶青 Zhuyeqing	DY	9.50	5.91	21.82	91.83	38.83	25.17	38.67	2.62	13.03	9.50	2.86
称锤白谷 Chengchuibaigu	TY	10.17	4.55	15.95	78.83	42.18	18.14	40.77	2.08	11.90	7.81	3.02
称锤白谷 Chengchuibaigu	DY	8.50	3.67	15.28	93.33	31.33	17.50	36.67	2.10	11.94	8.96	3.45
羊毛糙 Yangmaocao	TY	13.63	4.06	16.81	111.30	38.73	22.66	39.60	2.23	19.00	11.43	2.74
羊毛糙 Yangmaocao	DY	12.83	6.91	32.19	118.00	25.33	19.50	35.67	2.85	15.03	11.95	2.85
青达谷 Qingdagu	TY	12.17	4.37	16.14	84.78	34.58	21.25	34.52	2.38	17.18	11.15	3.05
青达谷 Qingdagu	DY	11.50	6.17	16.06	106.67	27.33	19.00	39.33	2.72	13.68	10.42	3.40
刘沟谷 Liugougu	TY	13.23	6.90	12.40	76.93	22.33	20.66	34.73	3.98	20.50	12.31	2.88
刘沟谷 Liugougu	DY	11.83	9.54	28.91	83.67	18.00	20.83	35.17	4.36	15.54	10.73	2.96
一层黄 Yicenghuang	TY	14.37	6.02	28.15	113.23	32.60	25.58	45.67	2.55	21.05	13.82	2.57
一层黄 Yicenghuang	DY	13.50	6.57	29.34	127.67	28.00	29.33	46.17	2.53	17.32	13.12	2.89
红石榴 Hongshiliu	TY	12.03	5.85	19.31	97.47	37.30	23.05	39.43	2.74	20.55	15.91	3.39
红石榴 Hongshiliu	DY	10.83	7.11	22.99	108.83	33.17	31.50	43.17	2.83	14.90	11.16	3.22
黄熟谷 Huangshugu	TY	10.10	4.37	17.62	81.83	48.22	20.59	45.35	2.49	13.62	6.96	3.01
黄熟谷 Huangshugu	DY	8.50	5.73	18.62	90.83	45.50	28.33	45.17	2.92	7.70	5.40	3.22
毛软谷 Maoruangu	TY	12.67	5.20	23.49	93.00	35.88	25.30	36.62	2.23	14.30	10.33	2.71
毛软谷 Maoruangu	DY	10.50	5.99	22.22	103.00	33.33	20.67	32.17	2.20	11.69	8.04	2.68

山西谷子种质资源耐瘠性鉴定及综合评价

Identification and Comprehensive Evaluation of the Barren-Tolerant Germplasm Resources of Foxtail Millet in Shanxi

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