苑乂川^1,*, 陈小雨^1,*, 李明明¹, 李萍¹, 贾亚涛¹, 韩渊怀^1,2,3, 邢国芳^,1,2,3,*1 山西农业大学农学院, 山西太谷 030801
2 山西农业大学农业生物工程研究所, 山西太谷 030801
3 杂粮种质资源发掘与遗传改良山西省重点实验室, 山西太谷 030801

Screening of germplasm tolerant to low phosphorus of seedling stage and response of root protective enzymes to low phosphorus in foxtail millet

YUAN Yi-Chuan^1,*, CHEN Xiao-Yu^1,*, LI Ming-Ming¹, LI Ping¹, JIA Ya-Tao¹, HAN Yuan-Huai^1,2,3, XING Guo-Fang^,1,2,3,* 1 College of Agronomy, Shanxi Agricultural University, Taigu 030801, Shanxi, China
2 Institute of Agricultural Bioengineering, Shanxi Agricultural University, Taigu 030801, Shanxi, China
3 Shanxi Key Laboratory of Genetic Resources and Genetic Improvement of Minor Crop, Taigu 030801, Shanxi, China

通讯作者: ^*邢国芳, E-mail: sxauxgf@126.com

收稿日期:2018-07-25接受日期:2018-12-24网络出版日期:2019-01-04

基金资助:

本研究由国家自然科学基金项目.31200914 本研究由国家自然科学基金项目.31501323 山西省高等学校科技创新项目.2015145 山西省重点研发计划项目.201803D221008-4 山西省主要农作物种质创新与分子育种重点科技创新平台.201605D151002

Received:2018-07-25Accepted:2018-12-24Online:2019-01-04

Fund supported:

This study was supported by the National Natural Science Foundation of China.31200914 This study was supported by the National Natural Science Foundation of China.31501323 Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi.2015145 Key R&D Program of Shanxi Province.201803D221008-4 Key Scientific and Technological Innovation and Molecular Breeding Platform of Major Crop Germplasm in Shanxi Province.201605D151002

作者简介 About authors
sxtyyyc@163.com。









摘要
本研究旨在探讨不同基因型谷子苗期耐低磷特性, 建立其筛选的评价体系, 筛选出苗期耐低磷谷子种质材料。对160份核心谷子种质资源的苗期株高、根长、地上鲜重、地下鲜重、叶长、叶宽、茎粗、地上磷含量、地下磷含量、地上干重和地下干重11个指标的耐低磷系数进行变异分析、相关性分析、主成分分析和聚类分析, 采用隶属函数法综合评价不同谷子耐低磷相关指标和耐低磷特性; 针对筛选出的低磷敏感和耐低磷品种, 在生理水平上分析其根系超氧化物歧化酶(SOD)、过氧化物酶(POD)、过氧化氢酶(CAT)的活性。结果表明, 9份材料属于低磷敏感品种, 66份材料属于低磷较敏感品种, 70份材料属于较耐低磷品种, 15份材料属于耐低磷品种; 低磷胁迫促使谷子根系SOD、POD、CAT活性增加。总之, 以综合指标对谷子耐低磷特性的鉴定更为客观; 根系保护酶系统对谷子在低磷胁迫下的适应性具有重要作用。
关键词： 谷子;低磷胁迫;种质资源;综合评价;根系保护酶

Abstract
The purpose of this paper was to explore the characteristics of low-phosphate tolerance in different genotypes of foxtail millet and establish an evaluation system for screening and breeding new cultivars with low-phosphate tolerance. Correlation analysis, principal component analysis, membership function and cluster analysis were carried out on 11 indicators of 160 core foxtail millet varieties, including plant heights, root lengths, fresh weights of aerial part and underground part, leaf lengths and widths, stem thicknesses, phosphorus contents of aerial part and underground part, dry weights of aerial part and underground part, to comprehensively evaluate indicators and characters related to low-phosphorous tolerance. Furthermore, a hydroponic experiment was conducted to cultivate selected varieties with low-phosphorus sensitivity and low-phosphorus tolerance under low phosphorus (LP) and normal phosphorus (NP) conditions, and superoxide dismutase (SOD) activity, peroxidase (POD) activity, and catalase (CAT) activity in roots were analyzed. There were nine varieties with low-phosphorus sensitivity, 66 and 70 varieties with medium low-phosphate tolerance and 15 varieties with low-phosphorus tolerance. The activities of SOD, POD, and CAT were increased under low phosphorus condition. It was concluded that the comprehensive index is more objective to evaluate the low-phosphorus tolerance of 160 foxtail millet variation at the seedling stage, and the root protective enzymes are important for the adaptability of foxtail millet to low-phosphorus stress.
Keywords：foxtail millet;low-phosphorus stress;germplasm resources;comprehensive evaluation;root protecting enzyme


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本文引用格式
苑乂川, 陈小雨, 李明明, 李萍, 贾亚涛, 韩渊怀, 邢国芳. 谷子苗期耐低磷种质筛选及其根系保护酶系统对低磷胁迫的响应[J]. 作物学报, 2019, 45(4): 601-612. doi:10.3724/SP.J.1006.2019.82029
YUAN Yi-Chuan, CHEN Xiao-Yu, LI Ming-Ming, LI Ping, JIA Ya-Tao, HAN Yuan-Huai, XING Guo-Fang. Screening of germplasm tolerant to low phosphorus of seedling stage and response of root protective enzymes to low phosphorus in foxtail millet[J]. Acta Crops Sinica, 2019, 45(4): 601-612. doi:10.3724/SP.J.1006.2019.82029


磷(P)是作物必需的营养元素之一^[1], 对植物生长发育起着至关重要的作用。但土壤中能被作物吸收利用的有效磷仅占土壤全磷的1%^[2], 土壤有效磷不足已成为制约作物产量和品质提高的主要因素之一。另外, 磷是不可再生资源, 50~400年内将会被耗尽^[3,4]。为了应对未来的磷缺陷对农业生产带来的危机, 了解作物磷胁迫响应机制, 培育耐低磷品种显得尤为重要^[5]。

了解作物磷胁迫响应机制, 培育耐低磷品种, 筛选耐低磷种植资源, 鉴定耐低磷材料是关键。目前关于耐低磷种质资源的筛选与评价, 在水稻、玉米等作物中已经开展了大量的试验。郭再华等^[6]对来自不同国家的多个水稻品种开展苗期土培筛选, 设置多个磷浓度处理, 确定了水稻苗期耐低磷指标筛选的最适营养液配比和鉴定指标。湛静等^[7]在缺磷条件下对玉米苗期进行了性状和生理机制的研究, 获得了一套比较完善的玉米耐低磷指标筛选体系。刘渊等^[8]以酸性磷酸酶的耐低磷系数作为评判基础, 分析了不同磷水平下大豆株高、干重、磷含量等指标, 发现不同基因型品种耐低磷差异极大, 并筛选出耐低磷种质。深入研究同一作物不同基因型品种间所表现的磷吸收和利用的生理特点差异, 它的意义不仅在于筛选磷高效品种, 还致力于形成完善的耐低磷筛选体系。

谷子(Setaria italica L.)是原产我国北方的小杂粮, 耐旱, 耐贫瘠, 具有养分高效利用的特质和潜力^[9,10], 是中国北方地区最主要的种植作物之一^[11]。谷子对磷缺乏有着相应的适应机制, 不同基因型谷子在磷吸收方面存在很大差异^[12,13,14]。缺磷会对谷子的生长发育造成一定影响, 杨艳君等^[15]发现磷缺乏导致收获期谷穗重量降低, Ceasar等^[16]在处理后前2周, 发现300 μmol L^-1与10 μmol L^-1供磷量对谷子生物量的影响无差异, 5周后, 10 μmol L^-1供磷水平下的谷子出现叶片变紫等缺磷症状。据报道, 谷子中存在12个磷转运载体PHR家族成员, 并且不同成员之间存在组织特异性表达^[16]。然而, 目前关于谷子耐低磷基因型品种筛选的相关研究并未深入。

植物体内的保护性酶如超氧化物歧化酶(SOD)、过氧化物酶(POD)和过氧化氢酶(CAT), 是抵抗营养胁迫引起氧化应激的关键^[17]。逆境胁迫不仅会影响植物的正常生理功能, 还会导致植物的新陈代谢失去平衡^[18]。植物的抗逆能力与植物保护性酶系统的活性变化之间存在密切的关联性。本研究从实验室1500多份材料中挑选了160份核心种质资源, 综合鉴定与评价了它们苗期的株高、根长、地上部鲜重、地下部鲜重、叶长、叶宽、茎粗、地上部磷含量、地下部磷含量、地上部干重和地下部干重, 筛选出耐低磷特性的指标和苗期具有耐低磷特性的谷子种质, 并进一步研究苗期根系保护酶系统在低磷胁迫下的响应, 为在遗传育种研究中利用这些优异种质资源提供理论依据。

1 材料与方法

1.1 供试材料

160份核心谷子种质资源, 由中国农业科学院作物科学研究所刁现民研究员提供。

1.2 试验设计

在山西农业大学农学院温室内进行随机排列的盆栽试验, 以石英沙培养和营养液浇灌, 筛选耐低磷品种。挑选整齐饱满的种子, 播于育苗盆(长32.5 cm, 宽25.0 cm, 深7.0 cm), 盆内放置总体积4/5的石英沙, 播种行距4.5 cm, 株距3.5 cm, 双粒点播。待幼苗生长至一叶一心期时, 向盆内加Hoagland营养液, 待幼苗至三叶期时间苗, 培育至30 d。另以水培试验用于谷子根系酶活性鉴定, 先在石英沙中盆栽培育至一心一叶期, 然后移栽到Hoagland营养液中, 每3天更换1次营养液, 培育至30 d。

试验条件均为温度25℃, 光照175 μmol m^-2 s^-1, 光周期16 h光照/8 h黑暗。设低磷水平(LP, 0.005 mmol L^-1)和正常磷水平(NP, 0.25 mmol L^-1) 2个处理。

1.3 指标测定

测量生长30 d谷子幼苗的株高、叶长、叶宽、茎粗和根长; 用 H₂SO₄-H₂O₂消解和钒钼黄比色法测定地上和地下磷含量^[19], 氮蓝四唑(NBT)光化还原法测定根系SOD活性, 愈创木酚法测定根系POD活性, 紫外吸收法测定根系CAT活性^[20]。

1.4 数据处理

采用Origin 8和Microsoft Excel 2003作图表, 利用SPSS 19.0进行相关性分析、主成分分析、方差分析, 采用LSD进行显著性检验, 利用DPS 7.05和R语言进行聚类分析, 采用隶属函数法对160份核心谷子种质进行耐低磷综合评价, 参考相关文献^[21]计算指标。

(1)耐低磷系数 = 低磷时的测量值/正常磷的测量值

(2)μ(X_j) = (X_j-X_min)/(X_max-X_min) j =1, 2, 3, …, n

式中, μ (X_j)表示第j个综合指标的隶属函数值, X_j表示第 j 个综合指标值; X_max表示第j个综合指标的最大值, X_min表示第j个综合指标的最小值。

(3)\[{{W}_{j}}={{P}_{j}/}\sum\limits_{j=1}^{m}{{P}_{j} \ \ \ \ \ \ j=1,2,3,...,n}\ \]

式中, W_j表示第j个综合指标在所有综合指标中的重要程度及权重; P_j为各品种第j个综合指标的贡献率。

(4)$D=\sum _{j=1}^{m}[\mu(x_{j})×W_{j}] \ \ \ \ \ \ j=1,2,3,...,n $

式中, D表示在低磷胁迫条件下各品种耐低磷能力的综合评价值。

2 结果与分析

2.1 不同品种单项指标耐低磷系数的分析

160份不同基因型的谷子在NP与LP环境下各指标均存在不同程度的变化。为避免作物的生物学固有差异, 采用了能准确反映品种耐低磷能力的耐低磷系数(相对值)作为判断谷子耐低磷特性的依据^[22]。株高、地上部鲜重、叶长、地上部磷含量、地下部磷含量和地上部干重耐低磷系数均小于1, 叶宽有9个品种耐低磷系数大于1, 茎粗仅有1个品种耐低磷系数大于1, 综合说明低磷胁迫抑制地上部各性状生长, 低磷下谷子磷含量低于正常环境下磷含量。大部分品种根长、地下部鲜重和地下部干重耐低磷系数大于1, 说明低磷影响植物的根系发育。11个指标的相对值变异系数均在10%以上, 可以看出, 不同基因型谷子的耐低磷特性存在较大差异, 160份种质在不同磷水平下存在广泛的遗传变异。鉴于上述各指标在不同磷环境中变异情况均较大, 说明这些指标都可能是鉴定谷子耐低磷能力较好的筛选指标(表1)。

Table 1
表1
表1谷子部分性状耐低磷系数(LP/NP)的变化范围及变异系数
Table 1Coefficient and variation for tolerance to low-phosphorus in some foxtail millet traits

性状 Trait	变化范围 Variation range (%)	平均值 Average (%)	变异系数 Coefficient of variance (%)
株高Plant height	56.15-93.05	71.16	11.00
根长Root length	51.92-140.88	105.48	15.61
地下鲜重Underground fresh weight	92.47-151.40	149.02	18.42
地上鲜重Aboveground fresh weight	35.04-90.63	67.13	14.19
叶长Leaf length	37.90-59.86	46.69	26.69
叶宽Leaf width	50.00-122.73	81.84	12.93
茎粗Diameter of main stem	44.96-106.20	74.26	11.39
地上磷含量Aboveground phosphorus content	36.00-95.00	72.09	15.80
地下磷含量Subsurface phosphorus content	24.00-89.00	58.85	20.69
地上干重Aboveground dry weight	36.00-91.00	66.89	14.98
地下干重Underground dry weight	41.00-124.00	75.74	17.34

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2.2 指标间耐低磷指数的相关性分析

地上部磷含量的耐低磷系数与株高、地上部鲜重、叶长、叶宽、地下部磷含量、地上部干重、地下部干重等指标的耐低磷系数呈极显著正相关, 与地下部鲜重耐低磷系数呈极显著负相关; 株高的耐低磷系数与地上部鲜重、叶长、叶宽、茎粗、地上部磷含量、地下部干重等指标的耐低磷系数呈极显著正相关, 与地上部干重耐低磷系数呈显著正相关, 与地下部鲜重耐低磷系数呈极显著负相关; 根长的耐低磷系数与地下部鲜重耐低磷系数极显著正相关, 与叶长耐低磷系数呈极显著负相关; 株高、地上部鲜重、叶长和茎粗4个指标的耐低磷系数均存在两两之间极显著正相关; 地上部磷含量、地上部干重和地下部干重3个指标之间的耐低磷系数均为极显著正相关(表2)。可见, 部分指标间存在一定相关关系, 不同指标间可能存在信息重叠, 单靠单项指标难以对表现复杂的耐低磷性综合评价, 综合各项指标能更有效地筛选低磷耐性种质资源。

Table 2
表2
表2谷子各性状耐低磷系数(LP/NP)的相关性分析
Table 2Correlation analysis of coefficient for tolerance to low-phosphorus during different varieties of foxtail millet

性状 Trait	株高 PH	根长 RL	地上部 鲜重 AFW	地下部 鲜重 UFW	叶长 LL	叶宽 LW	茎粗 DMS	地上部 磷含量 APC	地下部 磷含量 SPC	地上部 干重 ADW	地下部 干重 UDW
PH	1
RL	0.036	1
AFW	0.442**	0.172*	1
UFW	-0.531**	0.821**	-0.103	1
LL	0.648**	-0.542**	0.603**	-0.808**	1
LW	0.343**	-0.200*	0.066	-0.361**	0.334**	1
DMS	0.249**	-0.044	0.357**	-0.179*	0.300**	0.109	1
APC	0.268**	-0.121	0.190*	-0.233**	0.303**	0.225**	0.011	1
SPC	0.019	0.104	0.269**	0.075	0.066	-0.153	-0.024	0.573**	1
ADW	0.187*	0.054	0.494**	-0.069	0.290**	0.0177	0.128	0.477**	0.557**	1
UDW	0.222**	-0.073	0.100	-0.179*	0.196*	0.318**	-0.084	0.365**	0.115	0.352**	1

^**代表显著差异P < 0.01; ^*代表显著差异P < 0.05。 PH: plant height; RL: root length; AFW: aboveground fresh weight; UFW: underground fresh weight; LL: leaf length; LW: leaf width; DMS: diameter of main stem; APC: aboveground phosphorus content; SPC: subsurface phosphorus content; ADW: aboveground dry weight; UDW: underground dry weight. ^* represents significant correlation at P < 0.05; ^** represents significant correlation at P < 0.01.

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2.3 主成分分析

为达到简化指标及浓缩数据的目的, 将上述单项指标转化为有效的少量指标^[21], 以160份核心谷子种质各单项指标的耐低磷系数为基础进行主成分分析。从11个主要耐低磷特征指标在各个主成分上的权重系数即特征向量看, 可以发现, 第1主成分贡献率最大 , 主要特征向量包括株高、地上部鲜重、叶长、叶宽、茎粗、地上部磷含量和地上部干重7个单项指标, 特征值为4.657, 反映了地上因子, 可说明原始指标信息量的42.334%; 第2主成分载荷较高的是根长和地下部鲜重, 反映了根系因子, 可说明原始指标信息量的20.793%; 第3主成分载荷较高的是地下部磷含量, 可反映总信息量的11.206%; 第4主成分载荷较高的是地下部干重, 可反映总信息量的8.719%。前4个主成分累积贡献率达83.049%, 足以代表原指标的极大部分信息, 其余贡献率可忽略不计(表3和表4)。因此, 利用4个相互独立的综合指标可以对不同谷子的耐低磷特性进行客观的分析。

Table 3
表3
表3各综合指标特征值及贡献率
Table 3Eigenvalue and contribution of each comprehensive index

主成分 Principal component	特征值 Eigenvalue	贡献率 Contributive ratio (%)	累积贡献率 Cumulative contributive ratio (%)
1	4.657	42.334	42.334
2	2.287	20.793	63.127
3	1.233	11.206	74.333
4	0.959	8.716	83.049

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Table 4
表4
表4各因子载荷矩阵
Table 4Matrix of factor loading

耐低磷指标 Low-P tolerant index	主成分 Principal component
	1	2	3	4
株高PH	0.814	-0.180	0.319	0.007
根长RL	0.421	0.827	0.260	-0.019
地上部鲜重AFW	0.810	0.005	0.156	-0.412
地下部鲜重UFW	0.164	0.957	0.114	0.031
叶长LL	0.580	-0.744	0.074	-0.233
叶宽LW	0.647	-0.172	0.336	0.479
茎粗DMS	0.673	0.027	0.408	-0.234
地上部磷含量APC	0.748	-0.043	-0.432	0.193
地下部磷含量SPC	0.584	0.236	0.649	-0.202
地上部干重ADW	0.793	0.106	-0.344	-0.113
地下部干重UDW	0.529	-0.044	-0.119	0.599

PH: plant height; RL: root length; AFW: aboveground fresh weight; UFW: underground fresh weight; LL: leaf length; LW: leaf width; DMS: diameter of main stem; APC: aboveground phosphorus content; SPC: subsurface phosphorus content; ADW: aboveground dry weight; UDW: underground dry weight.

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2.4 品种耐低磷能力的综合分析

2.4.1 隶属函数鉴定品种耐低磷能力 根据主成分分析结果, 利用公式(2)计算每个综合指标的隶属函数值μ(X_j)。从表5可以看出, 低磷胁迫下, 综合指标Z1中69号品种μ(X₁)最小, 为0, 表明其在Z1中耐低磷能力最弱; V147号品种μ(X₁)最大, 为1.0000, 表明其在Z1中耐低磷能力最强; 综合指标Z2、Z3和Z4中μ(X)最小的品种分别为V151、V19、V81号, μ(X)最大的品种分别V72、V35、V69。可见4个综合指标鉴定的结果各不相同, 因此, 为对谷子耐低磷性进行全面充实的分析, 通过公式(3), 结合各综合指标的贡献率, 得出4个综合指标的权重W_j分别为50.97%、25.04%、13.49%和10.05%, 进一步根据公式(4)计算4个综合指标的综合评价值D, 并根据D值大小对其耐低磷能力的强弱进行排序。结果见表5, 排名较前的品种D值较小, 表明耐低磷能力弱, 称之为磷敏感品种, 排名较后的品种D值较大, 说明耐低磷力强, 称之为磷耐性品种。

Table 5
表5
表5各品种的综合性状指标值、权重、μ(X)及综合评价值(D)
Table 5Value of each comprehensive index (CI), index weight, μ(X), and comprehensive evaluation value (D)

品种 Variety	Z1	Z2	Z3	Z4	μ(X1)	μ(X2)	μ(X3)	μ(X4)	综合评价值 Comprehensive assessment value (D)	排名 Order
V1	-1.6323	0.3830	1.7162	-0.3955	0.2264	0.6479	0.7765	0.3123	0.4152	27
V2	-1.4500	-2.1682	1.3999	-0.5085	0.2539	0.3513	0.7244	0.2908	0.3456	7
V3	-1.2102	-0.6284	-0.2063	1.0063	0.2901	0.5303	0.4597	0.5793	0.4035	20
V4	1.6335	0.7376	-2.4004	1.1895	0.7197	0.6891	0.0981	0.6142	0.6171	134
V5	2.1822	-0.2511	-2.4419	0.4781	0.8026	0.5742	0.0913	0.4787	0.6154	132
V6	0.0319	0.6162	0.2194	-0.2165	0.4778	0.6750	0.5298	0.3464	0.5204	79
V7	-0.0242	-1.3712	-0.1959	0.1746	0.4693	0.4440	0.4614	0.4209	0.4568	49
V8	0.1818	0.6668	-0.6091	-1.6641	0.5004	0.6809	0.3933	0.0707	0.4860	67
V9	3.0438	-2.0966	1.9004	0.6023	0.9327	0.3596	0.8069	0.5024	0.7270	158
V10	0.3314	1.3360	-1.2708	0.1252	0.5230	0.7587	0.2842	0.4115	0.5381	95
V11	-1.3979	-0.0456	0.3979	-0.1125	0.2618	0.5981	0.5593	0.3662	0.3971	17
V12	-1.1021	1.0375	0.4391	0.0901	0.3065	0.7240	0.5660	0.4048	0.4564	47
V13	0.7983	1.0699	-1.3880	-0.9506	0.5935	0.7278	0.2649	0.2066	0.5422	97
V14	-1.6737	2.0691	-0.2322	1.2051	0.2201	0.8439	0.4554	0.6172	0.4498	42
V15	1.0917	-0.5273	-1.6633	0.7557	0.6378	0.5421	0.2196	0.5316	0.5463	99
V16	-0.5638	-0.1478	0.0901	-1.2853	0.3878	0.5862	0.5085	0.1428	0.4280	30
V17	-1.8131	-0.7841	-0.2550	1.8789	0.1991	0.5122	0.4517	0.7455	0.3689	12
V18	-2.9829	-0.8147	0.6199	-0.8614	0.0224	0.5087	0.5958	0.2236	0.2426	1
V19	0.0209	2.1536	-2.9956	1.1885	0.4761	0.8537	0.0000	0.6140	0.5209	81
V20	-1.7178	0.1697	-1.5586	0.5914	0.2135	0.6231	0.2368	0.5003	0.3493	9
V21	0.2587	0.1713	0.1004	1.0974	0.5120	0.6233	0.5102	0.5967	0.5485	102
V22	-0.3407	-1.1073	1.5481	-0.6580	0.4215	0.4747	0.7488	0.2623	0.4622	52
V23	-2.7587	3.3932	-0.1598	1.4613	0.0563	0.9979	0.4673	0.6660	0.4115	24
V24	2.3725	0.2468	-1.4864	0.5768	0.8313	0.6321	0.2487	0.4975	0.6678	149
V25	2.8794	0.2426	-1.2286	1.4558	0.9079	0.6316	0.2912	0.6649	0.7300	159
V26	1.9496	0.0191	-2.3027	0.9441	0.7674	0.6056	0.1142	0.5675	0.6178	135
品种 Variety	Z1	Z2	Z3	Z4	μ(X1)	μ(X2)	μ(X3)	μ(X4)	综合评价值 Comprehensive assessment value (D)	排名 Order
V27	-0.0735	1.0066	-0.2675	0.0285	0.4618	0.7204	0.4496	0.3931	0.5177	76
V28	-1.4796	-2.7691	-1.5485	0.4326	0.2495	0.2815	0.2385	0.4700	0.2791	2
V29	-0.3805	-1.4994	0.0644	-0.8302	0.4155	0.4291	0.5043	0.2295	0.4113	23
V30	-2.3010	0.5568	0.8604	-0.4532	0.1254	0.6681	0.6355	0.3013	0.3486	8
V31	-0.3831	-0.6384	0.3210	-0.2612	0.4151	0.5292	0.5466	0.3379	0.4533	45
V32	-0.3526	-0.8341	0.2491	0.3958	0.4197	0.5064	0.5347	0.4630	0.4615	51
V33	-1.2572	2.0635	0.1175	-0.6559	0.2830	0.8433	0.5130	0.2627	0.4522	44
V34	-2.0066	-0.0741	1.2416	-0.0945	0.1699	0.5948	0.6983	0.3696	0.3685	11
V35	-2.9688	1.9081	3.0723	0.2469	0.0245	0.8252	1.0000	0.4347	0.3997	18
V36	-1.1128	2.6623	1.4580	0.2940	0.3049	0.9129	0.7340	0.4436	0.5296	89
V37	-1.0320	0.6961	-0.0191	0.7611	0.3171	0.6843	0.4905	0.5326	0.4551	46
V38	2.3586	-0.0702	-0.7951	-0.5512	0.8292	0.5952	0.3626	0.2827	0.6503	146
V39	1.3125	-0.1426	0.7184	0.8312	0.6712	0.5868	0.6121	0.5459	0.6289	142
V40	1.7558	-1.0203	-1.9245	1.5502	0.7382	0.4848	0.1765	0.6829	0.5931	123
V41	-0.4456	-0.3004	0.9464	-0.0120	0.4056	0.5685	0.6496	0.3853	0.4772	63
V42	-1.8962	-2.1770	0.8829	0.1763	0.1865	0.3503	0.6392	0.4212	0.3132	4
V43	-0.8274	0.2928	-1.8849	-0.7725	0.3480	0.6374	0.1830	0.2405	0.3869	14
V44	-1.3986	0.4234	-0.7386	-1.0700	0.2617	0.6526	0.3720	0.1838	0.3663	10
V45	0.0631	-0.2475	0.0927	-0.7990	0.4825	0.5746	0.5090	0.2355	0.4832	64
V46	-0.0955	1.4289	-0.2399	0.3159	0.4585	0.7695	0.4541	0.4478	0.5347	91
V47	1.7838	1.5395	-2.2310	1.2522	0.7424	0.7824	0.1260	0.6261	0.6570	147
V48	0.3831	1.5463	-1.2741	-0.8337	0.5308	0.7831	0.2837	0.2288	0.5290	88
V49	-0.5436	0.5557	1.0839	1.1437	0.3908	0.6680	0.6723	0.6055	0.5207	80
V50	-1.3887	0.8153	1.0506	0.8640	0.2632	0.6982	0.6668	0.5522	0.4569	50
V51	2.1270	-1.1928	-0.1009	-0.0165	0.7942	0.4647	0.4771	0.3845	0.6259	140
V52	0.3242	0.7315	-0.8191	-0.0001	0.5219	0.6884	0.3587	0.3876	0.5275	87
V53	0.2900	-0.6707	-1.9185	-1.2474	0.5168	0.5254	0.1775	0.1500	0.4347	32
V54	-0.6756	0.2877	-0.4629	-0.1039	0.3709	0.6368	0.4174	0.3678	0.4434	37
V55	3.0862	-0.8419	0.2682	0.2587	0.9391	0.5055	0.5379	0.4369	0.7237	156
V56	-0.1720	1.2193	-1.3032	-0.0738	0.4470	0.7451	0.2789	0.3736	0.4913	68
V57	-0.6719	0.9067	-1.0655	-0.6782	0.3715	0.7088	0.3181	0.2585	0.4369	33
V58	2.8844	0.6624	-0.2868	1.0581	0.9086	0.6804	0.4464	0.5892	0.7556	160
V59	1.3463	2.2963	0.1229	0.2876	0.6763	0.8703	0.5139	0.4424	0.6784	151
V60	-1.5799	2.0050	0.9341	-0.0246	0.2343	0.8365	0.6476	0.3829	0.4565	48
V61	-1.2737	1.9840	-0.6119	1.3180	0.2806	0.8340	0.3928	0.6387	0.4719	60
V62	-1.9948	2.2161	0.1507	0.5801	0.1716	0.8610	0.5185	0.4981	0.4253	29
V63	0.7281	1.9543	0.0045	0.4504	0.5829	0.8306	0.4944	0.4734	0.6215	137
V64	-1.9503	-0.9239	-0.0778	-0.5369	0.1784	0.4960	0.4809	0.2854	0.3099	3
V65	-0.4570	1.5584	1.3589	0.4630	0.4039	0.7846	0.7176	0.4758	0.5491	103
V66	-0.1959	-0.8819	-0.1243	0.5303	0.4434	0.5009	0.4732	0.4886	0.4665	55
V67	-1.4532	-1.5355	1.5459	1.4533	0.2534	0.4249	0.7484	0.6644	0.4063	22
V68	-0.0935	1.1747	-1.0937	0.9499	0.4588	0.7399	0.3134	0.5686	0.5211	82
V69	-3.1311	0.7949	-1.4602	3.2151	0.0000	0.6958	0.2530	1.0000	0.3134	5
V70	-0.8250	-0.4004	-0.0584	-0.2687	0.3483	0.5568	0.4841	0.3365	0.4176	28
品种 Variety	Z1	Z2	Z3	Z4	μ(X1)	μ(X2)	μ(X3)	μ(X4)	综合评价值 Comprehensive assessment value (D)	排名 Order
V71	-1.4984	2.0480	1.6374	-0.5784	0.2466	0.8415	0.7635	0.2775	0.4685	57
V72	0.3822	3.4116	0.4863	-0.6490	0.5307	1.0000	0.5738	0.2640	0.6260	141
V73	-1.3044	1.9319	1.5631	-0.2074	0.2759	0.8280	0.7513	0.3481	0.4859	66
V74	0.3536	0.6448	-0.2815	-1.0117	0.5264	0.6783	0.4473	0.1949	0.5189	77
V75	-0.4450	1.4046	-0.1209	-0.5443	0.4057	0.7667	0.4738	0.2840	0.4925	69
V76	-1.4930	1.5681	0.4010	-0.4236	0.2474	0.7857	0.5598	0.3070	0.4306	31
V77	0.2232	-1.9715	-0.2916	0.9274	0.5067	0.3742	0.4456	0.5643	0.4713	59
V78	-0.9094	1.0281	0.1685	0.0851	0.3356	0.7229	0.5214	0.4038	0.4648	53
V79	-0.0005	0.7317	1.1602	-0.9947	0.4729	0.6884	0.6849	0.1982	0.5266	86
V80	0.8224	2.6255	-0.6271	-0.7117	0.5972	0.9086	0.3903	0.2521	0.6110	130
V81	1.2214	-2.9115	-0.8400	-2.0352	0.6574	0.2649	0.3552	0.0000	0.4493	40
V82	0.8209	0.5664	-0.5639	-0.7469	0.5969	0.6692	0.4007	0.2454	0.5517	107
V83	-0.4357	-1.2831	0.8076	1.5209	0.4071	0.4542	0.6268	0.6773	0.4769	62
V84	-0.5671	-0.8329	0.4943	-0.1860	0.3873	0.5066	0.5751	0.3522	0.4388	34
V85	1.2493	1.3814	0.0058	-0.8098	0.6617	0.7640	0.4946	0.2334	0.6198	136
V86	0.3429	1.1338	-0.7069	-1.0188	0.5247	0.7352	0.3772	0.1936	0.5228	83
V87	0.1775	0.9740	-0.4391	0.4596	0.4998	0.7166	0.4213	0.4752	0.5409	96
V88	0.8198	-0.3046	-0.1972	0.4407	0.5968	0.5680	0.4612	0.4716	0.5581	109
V89	-1.2621	0.1656	0.4366	-1.3000	0.2823	0.6226	0.5656	0.1400	0.3908	16
V90	0.3801	-0.0729	1.1570	-0.2461	0.5304	0.5949	0.6844	0.3408	0.5474	100
V91	0.7566	1.3846	0.2228	-0.2748	0.5872	0.7643	0.5304	0.3353	0.5975	125
V92	0.9868	0.3051	0.5359	-0.3856	0.6220	0.6389	0.5820	0.3142	0.5885	119
V93	-0.6307	0.0425	1.6762	-1.1183	0.3777	0.6083	0.7699	0.1746	0.4670	56
V94	1.7287	-0.0029	-0.6032	-0.9731	0.7341	0.6030	0.3943	0.2023	0.5996	128
V95	0.7446	1.2538	-0.3449	-0.7549	0.5854	0.7491	0.4368	0.2439	0.5705	115
V96	0.8910	-0.6957	-1.4774	-0.7926	0.6075	0.5225	0.2502	0.2367	0.4991	71
V97	1.0161	1.5727	-0.8139	-0.4504	0.6264	0.7862	0.3595	0.3018	0.5964	124
V98	-2.4021	1.1652	1.6025	0.2695	0.1101	0.7388	0.7578	0.4390	0.3894	15
V99	0.8537	0.3506	-0.3481	0.1239	0.6019	0.6441	0.4363	0.4112	0.5701	114
V100	0.2219	1.2902	-1.8862	1.0882	0.5065	0.7534	0.1828	0.5949	0.5339	90
V101	2.1516	-0.8218	0.6916	1.4801	0.7979	0.5078	0.6077	0.6695	0.6861	153
V102	0.2359	0.3941	1.0508	1.9153	0.5086	0.6492	0.6669	0.7524	0.5907	121
V103	1.5819	-1.5365	-0.2466	1.0536	0.7119	0.4248	0.4530	0.5883	0.5921	122
V104	-0.9350	-0.7984	1.6214	1.7402	0.3317	0.5106	0.7609	0.7191	0.4751	61
V105	-0.9468	-0.8273	0.4000	-0.4906	0.3299	0.5072	0.5596	0.2942	0.4016	19
V106	1.2936	-0.4993	1.2425	0.8576	0.6683	0.5453	0.6984	0.5510	0.6293	143
V107	0.8802	-3.0949	0.1413	1.0083	0.6059	0.2436	0.5170	0.5797	0.5004	72
V108	1.7261	2.4421	-0.6870	-1.1093	0.7337	0.8873	0.3805	0.1764	0.6660	148
V109	0.0716	-0.8917	1.1465	-1.0074	0.4838	0.4997	0.6826	0.1958	0.4843	65
V110	1.1676	-0.6450	0.4010	-1.4996	0.6493	0.5284	0.5598	0.1020	0.5495	105
V111	2.2048	-2.3144	0.4298	0.5973	0.8060	0.3343	0.5645	0.5014	0.6233	138
V112	1.6566	0.4933	-0.7047	-1.3796	0.7232	0.6607	0.3775	0.1249	0.5981	126
V113	1.0447	-1.7958	-1.3696	-1.3406	0.6307	0.3946	0.2680	0.1323	0.4703	58
V114	2.5698	-1.6432	-0.9985	-1.3906	0.8611	0.4123	0.3291	0.1228	0.5995	127
品种 Variety	Z1	Z2	Z3	Z4	μ(X1)	μ(X2)	μ(X3)	μ(X4)	综合评价值 Comprehensive assessment value (D)	排名 Order
V115	0.7084	-0.2833	-0.6263	1.3865	0.5799	0.5704	0.3905	0.6517	0.5595	111
V116	0.2016	-0.9832	-0.6574	-1.4154	0.5034	0.4891	0.3853	0.1181	0.4434	38
V117	0.3319	0.5234	1.0628	-0.7934	0.5231	0.6642	0.6688	0.2365	0.5480	101
V118	-0.0904	1.9288	-0.2509	-1.7092	0.4593	0.8276	0.4523	0.0621	0.5089	74
V119	-0.6536	-0.4628	1.4120	-1.3866	0.3742	0.5496	0.7264	0.1235	0.4393	35
V120	0.2346	1.2992	-0.3514	-1.0919	0.5084	0.7544	0.4358	0.1797	0.5257	85
V121	0.1400	0.3997	-0.1264	-0.8832	0.4941	0.6498	0.4728	0.2194	0.5014	73
V122	-1.0625	1.0788	0.6917	-0.7088	0.3125	0.7288	0.6077	0.2526	0.4503	43
V123	0.2827	0.6421	-0.1297	-0.5724	0.5156	0.6780	0.4723	0.2786	0.5256	84
V124	1.3192	0.3550	2.7395	1.6487	0.6722	0.6447	0.9452	0.7017	0.7052	155
V125	1.0251	-1.4867	2.1165	-0.5607	0.6278	0.4305	0.8425	0.2808	0.5709	116
V126	-0.7859	-0.5590	-0.5303	2.7169	0.3542	0.5384	0.4063	0.9051	0.4652	54
V127	0.6901	-0.7110	-0.2695	0.5643	0.5772	0.5207	0.4493	0.4951	0.5372	93
V128	-0.1924	-2.1455	0.8792	0.0768	0.4439	0.3540	0.6386	0.4023	0.4433	36
V129	2.0218	-3.0902	0.8532	0.0116	0.7783	0.2441	0.6343	0.3898	0.5843	118
V130	2.3030	0.6975	0.1622	-0.7651	0.8208	0.6845	0.5204	0.2419	0.6854	152
V131	1.1158	1.6194	0.8286	-0.8007	0.6415	0.7916	0.6302	0.2351	0.6349	144
V132	-1.3467	0.5684	-0.7876	0.9307	0.2695	0.6695	0.3639	0.5649	0.4134	25
V133	-0.8406	-0.8182	-0.4682	0.1958	0.3460	0.5083	0.4165	0.4249	0.4044	21
V134	2.0695	-4.6858	0.4021	0.8945	0.7855	0.0586	0.5599	0.5580	0.5492	104
V135	0.6691	0.4128	0.1090	-0.2092	0.5740	0.6514	0.5116	0.3478	0.5612	112
V136	-0.3019	1.5029	1.1814	-0.1033	0.4273	0.7781	0.6884	0.3680	0.5442	98
V137	1.0540	1.4276	1.2276	1.1156	0.6322	0.7693	0.6960	0.6001	0.6718	150
V138	1.7374	0.5377	-0.0778	-1.1412	0.7354	0.6659	0.4809	0.1703	0.6243	139
V139	-0.0621	-2.0903	0.5436	-1.5520	0.4636	0.3604	0.5833	0.0920	0.4149	26
V140	1.6572	-1.9967	-0.2135	-0.3041	0.7233	0.3713	0.4585	0.3297	0.5581	110
V141	-1.2772	0.9526	1.0633	-0.1421	0.2800	0.7141	0.6689	0.3606	0.4496	41
V142	0.8626	-0.1704	-0.9908	0.6097	0.6032	0.5836	0.3304	0.5038	0.5511	106
V143	-0.4207	1.6479	-0.2193	-0.6341	0.4094	0.7950	0.4575	0.2669	0.4975	70
V144	-0.0266	-0.0241	0.5838	1.4158	0.4689	0.6006	0.5899	0.6573	0.5380	94
V145	0.0194	1.1904	-0.9115	0.1998	0.4759	0.7418	0.3435	0.4257	0.5193	78
V146	1.4047	0.5100	-0.6107	-0.9683	0.6851	0.6627	0.3930	0.2032	0.5895	120
V147	3.4893	-3.9982	-0.5485	-0.2163	1.0000	0.1386	0.4033	0.3464	0.6352	145
V148	1.2168	-0.6707	2.6366	-0.8229	0.6567	0.5254	0.9282	0.2309	0.6158	133
V149	3.4272	-1.4023	-0.4987	0.6199	0.9906	0.4404	0.4115	0.5057	0.7238	157
V150	1.2416	-0.0553	-0.4547	-1.4753	0.6605	0.5970	0.4187	0.1066	0.5538	108
V151	1.2981	-5.1901	-0.5088	0.5695	0.6690	0.0000	0.4098	0.4961	0.4484	39
V152	0.6812	-0.4861	0.0443	-1.3083	0.5758	0.5469	0.5010	0.1384	0.5126	75
V153	1.7589	-0.4240	-1.2320	-1.3231	0.7386	0.5541	0.2906	0.1356	0.5687	113
V154	1.8504	-0.3416	0.5364	-1.5895	0.7524	0.5637	0.5821	0.0849	0.6121	131
V155	-3.0664	0.5577	2.7888	1.8880	0.0098	0.6682	0.9533	0.7472	0.3794	13
V156	-2.4860	-0.5374	-0.1214	2.2582	0.0974	0.5409	0.4737	0.8177	0.3349	6
V157	2.9685	-1.3375	-0.4448	0.8433	0.9213	0.4479	0.4204	0.5483	0.6960	154
V158	2.0892	-2.2147	0.5843	0.0875	0.7885	0.3459	0.5900	0.4043	0.6106	129
V159	1.5189	-2.8861	1.9919	-0.2344	0.7024	0.2679	0.8219	0.3430	0.5720	117
V160	0.5692	-0.6643	0.8973	-0.3538	0.5589	0.5262	0.6416	0.3202	0.5368	92
Weights	0.5097	0.2504	0.1349	0.1050

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2.4.2 各品种耐低磷能力的聚类分析 为使本试验结果更加客观, 使用最大距离法对4个耐低磷综合指标的综合评价值D进行聚类(图1)。结果将实验中谷子种质分为4类。第I类为低磷敏感型品种, 耐低磷D值范围为0.2426~0.3493, 耐低磷能力最弱, 共9份; 第II类为低磷较敏感型品种, 耐低磷能力中等偏弱, 耐低磷D值范围为0.3663~0.5126, 共66份; 第III类为较耐低磷品种, 耐低磷能力中等偏强, 耐低磷D值范围为0.5177~ 0.6352, 共70份; 第IV类为耐低磷品种, 耐低磷能力最强, 耐低磷D值范围为0.6503~0.7556, 共15份。

图1

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图1160个谷子品种的耐低磷性聚类图

Fig. 1Cluster of low-phosphorus tolerance in 160 foxtail millet varieties

2.5 不同品种在磷胁迫下的根系保护酶活性差异

逆境下, 植物会产生破坏细胞膜结构的超氧自由基。SOD是植物体内天然存在的自由基清除因子, 与POD和CAT结合把毒害的H₂O₂转换分解为完全无害的水, 保持植物正常的生长发育。这3种酶被认为是植物胁迫评估的重要生理指标。由于在LP环境下, 植物会优先将光合产物分配到地下部分, 地上部分生长受到抑制的同时地下部分促进根系发育^[23]。因此, 我们根据筛选结果选择具有代表性的耐低磷品种(V47、V124、V130)与低磷敏感品种(V18、V69、V156)各3份进行水培, 测定其苗期根系SOD、POD、CAT活性。在NP环境下, SOD、POD和CAT根系酶活力平均值分别为282.83 U g^-1 FW、914.80 U g^-1 min^-1 FW和3.51 U g^-1 min^-1 FW; LP环境下, 3种酶活力平均值分别为297.83 U g^-1, FW、998.46 U g^-1 min^-1 FW和3.81 U g^-1 min^-1 FW。低磷胁迫促使6个谷子根系酶活力平均增加了5.30%、9.14%和8.54%。可见, 不同谷子根系在LP环境下相对于NP环境的SOD、POD、CAT活力均增大。与NP环境下相比, 低磷胁迫使V47、V124、V136、V18、V69和V156的SOD活力分别升高8.67%、6.20%、5.07%、4.42%、1.96%和5.74%。其中耐低磷品种V47增长幅度最大, 低磷敏感品种V69增长幅度最小, 6个谷子根系酶活力NP与LP处理间均达到显著差异。V47、V124、V136、V18、V69和V156在LP条件下的POD活力与NP条件下相比, 分别升高7.23%、14.61%、19.74%、5.02%、3.96%和3.29%。其中耐低磷品种V124和V136根系酶活力显著高于其余4个谷子品种。与NP环境下相比, 低磷胁迫使V47、V124、V136、V18、V69和V156的CAT活力分别升高5.41%、12.82%、7.91%、6.00%、1.05%和5.00%, 其中耐低磷品种V124增长幅度最大, 显著高于其余5个谷子根系酶活力, 低磷敏感品种V156增长幅度最小(图2)。

图2

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图2不同供磷强度下谷子SOD、POD、CAT活性的比较

图柱上不同的字母表示5%水平下差异的显著性。
Fig. 2Comparison of SOD, POD, CAT activities of foxtail millet under different phosphate conditions

Bars superscripted by different letters are significantly different at the 5% probability level.

3 讨论

3.1 筛选耐低磷种质资源的方法

苗期是谷子需磷量的瓶颈期和筛选低磷耐性指标的关键时期^[24]。苗期筛选不仅能快速、准确地鉴定和筛选品种, 还可以显著减少田间筛选的工作量与成本^[25]。而盆栽和水培是实施苗期试验简便有效的方法, 且精确度较高。因此本试验采取盆栽方法对160份谷子苗期耐低磷性进行种质筛选, 进一步采用水培方法对耐低磷和低磷敏感品种进行根系酶活性分析。

3.2 苗期耐低磷综合指标的确定

谷子的耐低磷表现是一个复杂的过程, 缺磷会抑制植株某些生理特性, LP环境下地上部指标株高、地上部鲜重、叶长、地上部磷含量和地上部干重均小于NP环境下的各对应指标, 同时缺磷也会促进根系生长, 引起地下部鲜重增大。本试验通过主成分分析, 将所有单项指标划分为具有代表性的综合指标, 对160份核心谷子种质进行耐低磷能力的区分。结果表明, 缺磷对低磷敏感品种的影响要远远高于耐低磷品种, 由于部分耐低磷品种本身含有少量可用于谷物吸收的磷元素, 因而出现部分品种在LP环境下的茎粗、叶长等性状没有受到抑制反而促进生长的趋势, 表明磷元素的缺乏对不同基因型谷子苗期的单项指标有不同的推动作用, 为避免利用单个指标描述耐低磷的局限性, 最终采用4个综合指标分析不同品种的耐低磷特性。采用综合指标对作物的抗逆能力进行评价已在苜蓿^[22]、花生^[26]、水稻^[27]等中取得了一定的成果。

3.3 根系保护酶系统对低磷胁迫的响应

许多研究发现SOD、POD、CAT等酶类是植物抗逆的重要酶保护系统, 这3种酶在低磷胁迫下可以反映植物的逆境胁迫效应^[28]。万美亮等^[29]研究认为, 低磷胁迫诱导甘蔗体内保护酶系统活性升高, 是植物耐低磷的生理机制之一。本研究发现, 低磷环境诱导SOD、POD和CAT 3种酶活性增加以清除谷子幼苗根系内的H₂O₂, 但不同谷子根系酶活性的变化幅度存在一定差异, 与NP环境相比, LP环境中3种酶活性增幅最大的均为耐低磷品种, 增幅最小的均为低磷敏感性品种。表明低磷胁迫对不同基因型谷子根系酶活性具有不同的调控作用, 耐低磷品种和低磷敏感性品种在逆境下的胁迫响应存在差异, 因而清除植物体内产生的自由基的能力也不同。本研究结果与李俊等^[17,30-32]对油菜、大豆、玉米等研究结果类似。

4 结论

本研究对160份核心谷子种质的苗期耐低磷特性进行研究, 根据耐低磷能力强弱可分为低磷敏感型、低磷较敏感型、较耐低磷型和耐低磷型4种不同类型。低磷胁迫下, 本研究所测得的11个指标均可作为鉴定谷子苗期耐低磷能力和品种选育的参考指标。其中低磷耐性品种和低磷敏感品种根系保护酶系统对低磷胁迫响应能力的不同, 是谷子磷胁迫可能的重要逆境胁迫效应。

The authors have declared that no competing interests exist.

作者已声明无竞争性利益关系。

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