不同基因型花生耐荫性评价及其鉴定指标的筛选

【目的】分析不同基因型花生耐荫性,筛选耐荫鉴定指标,建立耐荫评价模型,为花生耐荫资源筛选和品种选育提供理论支撑。【方法】采用田间试验,以30个花生品种（系）和1个玉米品种为试验材料,设计玉米间作花生和净作花生,在花生结荚期测定花生叶片净光合速率（X₁₃）、气孔导度（X₁₄）、胞间CO₂浓度（X₁₅）和蒸腾速率（X₁₆）;成熟期测定主茎高（X₁）、侧枝长（X₂）、总分枝数（X₃）、有效分枝数（X₄）,单株结果数（X₅）、单株饱果数（X₆）和单株产量（X₁₁）;收获晾晒干后测定其百果重（X₇）、百果仁重（X₈）、百仁重（X₉）、出仁率（X₁₀）和小区产量（X₁₂）。根据间作遮荫和净作条件下的各单项指标的耐荫系数,采用主成分分析、聚类分析、逐步回归分析和隶属函数法等多元统计分析法,对花生耐荫性进行综合评价。【结果】不同花生品种（系）各单项指标的耐荫系数变异幅度不同,除出仁率外各个单项指标间存在显著或极显著的相关性。通过主成分分析将16个单项指标转换为5个相互独立的综合指标,其贡献率分别为33.860%、26.666%、11.176%、8.471%和6.954%,代表了全部数据87.127%的信息量。通过隶属函数分析,对于综合指标CI₁—CI₅,其隶属函数值最大的分别是6-2、天府29号、201150118A、201240413和闽花6号。对耐荫综合评价值（D）进行聚类分析,将30个花生品种（系）划分为3类,第一类属于耐荫型,包含11个品种（系）,第二类属于中度耐荫型,包含18个品种（系）,第三类属于敏感型,包含1个品种（系）。通过逐步回归分析建立花生耐荫性评价最优数学模型,D=-0.741+0.576X₉+0.507X₁₁+0.298X₁₃+0.272X₁₂+0.406X₁₀（R²=0.990）,估计精度在93.18%以上,筛选出5个鉴定花生耐荫性指标,分别为百仁重、出仁率、单株产量、小区产量和净光合速率。对参试材料耐荫类别特征分析可知,耐荫型花生净光合速率较高,百仁重、单株产量、小区产量和出仁率高,而敏感型百仁重、单株产量、净光合速率、小区产量和出仁率均最低。【结论】采用多元统计分析法对花生耐荫性进行评价分析是较为科学的,30个花生品种（系）被分成3类（耐荫型、中度耐荫型和敏感型）;百仁重、出仁率、单株产量、小区产量和净光合速率可作为鉴定花生耐荫性的指标,可在相同条件下测定这5个指标,计算耐荫综合评价值预测花生耐荫性。

Evaluation of Shade Tolerance of Peanut with Different Genotypes and Screening of Identification Indexes

【Objective】 The main aim of this study was to explore the methods of evaluating shade-tolerance, analyze the shade-tolerance of peanut in different genotypes, screen suitable identification indexes of shade tolerance, and establish an evaluation model of shade tolerance, so as to provide some theoretical support for screening of shade-tolerance resources and variety breeding of peanut. 【Method】 Qiannuo 868 was selected as the corn variety, and under the conditions of corn-peanut intercropping system and net cropping peanut, thirty peanut cultivars (lines) were treated in the field experiment. Net photosynthetic rate (X₁₃), stomatal conductance (X₁₄), intercellular CO₂ concentration (X₁₅) and transpiration rate (X₁₆) of peanut leaves were measured at the pod stage of peanut. The main stem height (X₁), side branch length (X₂), total branch number (X₃), effective branch number (X₄), plant pod number (X₅), mature pods per plant number (X₆) and yield per plant (X₁₁) were measured in the peanut mature stage. The 100-pod weight (X₇), kernel weight of 100 fruiting (X₈), 100-kernel weight (X₉), shelling percentage (X₁₀) and plot yield (X₁₂) were measured after harvesting and drying of peanut seed. 【Result】 The variation range of shade tolerance coefficient of each single index was different in different peanut varieties (lines). The 16 single indicators were converted into 5 independent comprehensive indicators through principal component analysis, and their contribution rates respectively were 33.860%, 26.666%, 11.176%, 8.471% and 6.954%, representing the information of 87.127% of all data. Through membership function, the largest membership function values of comprehensive indexes CI₁-CI₅ respectively were 6-2, Tianfu 29, 201150118A, 201240413 and Minhua 6. The thirty peanut varieties (lines) were divided into 3 categories: the first category was shade tolerance type, including 11 varieties (lines); the second category was moderate shade tolerance type, including 18 varieties (lines); the third category was sensitive type, including 1 variety (line). The optimal mathematical model of peanut shade tolerance evaluation was established, namely D=0.741+0.576X₉+0.507X₁₁+ 0.298X₁₃+0.272X₁₂+0.406X₁₀ (R²=0.990), and its accuracy was higher than 93.18%. Then, 5 indexes for peanut shade tolerance identification were selected: 100-kernel weight, yield per plant, net photosynthetic rate, plot yield and the ratio of shelled. The shade tolerance type peanut had a higher net photosynthetic rate, higher 100-kernel weight, yield per plant, plot yield and shelling percentage, while the sensitive type peanut were the opposite. 【Conclusion】 It was relatively scientific to evaluate and analyze the shade tolerance of peanut by multivariate statistical analysis. 30 peanut varieties (lines) were divided into three categories: shade tolerance type, moderate shade tolerance type, and sensitive type. 100-kernel weight, shelling percentage, yield per plant, plot yield and net photosynthetic rate could be used as the indexes to identify the shade tolerance of peanut. The comprehensive evaluation value of shade tolerance could be calculated to predict peanut shade tolerance by measuring the five indexes under the same conditions.