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光核桃(Amygdalus mira)是蔷薇科(Rosaceae)、桃属(Amygdalus)的西藏野生桃种,抗旱、抗寒、结果力强,年产量约500万kg[1],是西藏分布最广的野生果树之一。光核桃的分布覆盖20多个县,生长环境变化大,适应性强,主要集中分布在海拔为2 000 ~ 4 000 m雅鲁藏布江河谷、帕隆藏布和尼洋河流域[2]。
目前,对光核桃的研究多集中在生理特征[3-4]、生物遗传多样性[2,5-7]及加工利用 [1,8-9]等方面。光核桃抗旱[3]、抗寒[10],遗传多样性高且与其他桃种遗传关系较远[6-7],是筛选抗旱、抗寒等性状的优良桃树种质资源。光核桃果肉(外果皮和中果皮)研究开发出果酒、果醋等产品[1,9];种仁作中药[11],且含油量高[12];桃核可做活性炭、生物吸附剂[13]等,因此,光核桃的果实具有综合开发利用的价值。根据前人的研究结果,对光核桃果实的开发主要分为果肉和果核两个部分,但目前未形成大规模的综合开发利用,主要原因是野生的光核桃多分布在山地、沟壑中,采集果实较为困难,且育种技术薄弱,到目前为止没有真正意义上的栽培新品种。此外,由于生境片段化的形成,光核桃资源及更新苗均受到破坏,不利于种质资源的保存。依据果肉厚度及果核的大小选育不同利用目的的优良种质资源,对光核桃资源的保护及开发利用等方面尤为重要。在优良种质资源选育过程中,对光核桃种群果实表型性状的系统研究是必不可少的。
包文泉等[14]对光核桃表型性状做了初步的研究,但采样的地理范围未能覆盖全分布区。光核桃果实表型差异是筛选种质资源的主要根据,表型差异是通过基因与环境相互作用实现的,也是其对环境条件适应性的表现[15],而研究生态因子对表型的影响规律是种植、推广优良种质的主要依据。因此,本文对18个种群光核桃果实表型性状进行研究,分析种群间与种群内的变异,根据利用部位筛选优良果实性状及其主要分布区,为光核桃优良种质的选择和良种选育提供依据;研究生态因子对果实表型性状及特征性状的影响规律,为光核桃良种推广提供参考。
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根据西藏野生光核桃的自然集中分布区,兼顾其生长的海拔、气候和成熟期的差异性,对西藏光核桃的5个地级市18个种群进行实地调查采样,调查采样点覆盖了光核桃的主要分布区。通过实地调查,采用GPS定位记录采样地的经纬度和海拔,根据光核桃褪去绿色,着黄、粉红色和形态判断成熟,并根据开始成熟时间记录各种群光核桃的成熟期。从每个种群中选取13株长势良好的光核桃,各单株间距大于50 m,种群间距离大于3 km[16]。分别从每个植株的阴面上、阴面下、阳面上和阳面下4方位采集成熟果实,从每个方位采集的成熟果实中随机选择5枚,共20枚,测量其表型性状。18个种群的位置及概况信息见图1和表1,其中年降雨量和年均温数据来自中国气象网及当地的气象局。
表 1 光核桃18个种群的基本信息及成熟期
Table 1. Basic information and maturity stage of the 18 A. mira populations investigated in this study
种群及代码
Population and code经度
Longitude纬度
Latitude海拔
Elevation
(H)/m年均降水量
Average annual
rainfall(R)/mm年均温
Mean temperature
(T)/℃成熟期
Maturity stage日喀则亚东县上亚东乡
Shangyadong Township, Shigatse City(SYD)88°57′17″E 27°30′40″N 3 218 873.0 8.5 9月下旬
Late September山南加查县安绕镇
Anrao Township, Lhoka(AR)92°33′59″E 29°09′00″N 3 265 492.7 8.9 8月中下旬
Mid-late August山南加查县冷达乡
Lengda Township, Lhoka(LD)92°43′19″E 29°04′38″N 3 168 492.7 8.9 8月中下旬
Mid-late August山南贡嘎县江塘镇
Jiangtang Township, Lhoka(JT)90°41′42″E 29°15′43″N 3 770 356.6 9.2 9月中下旬
Mid-late September昌都左贡县东坝乡
Dongba Township, Qamdo City(DB)97°26′35″E 29°52′40″N 3 153 405.0 4.2 9月上旬
Early September昌都芒康县曲登乡
Qudeng Township, Qamdo City(QD)98°12′18″E 29°33′23″N 3 654 350.0 10.0 9月上旬
Early September昌都芒康县木许乡
Muxu Township, Qamdo City(MX)98°37′02″E 28°54′27″N 2 280 450.0 10.5 8月中下旬
Mid-late August昌都八宿县林卡乡
Linka Township, Qamdo City(LK)97°10′04″E 30°00′39″N 2 984 233.3 10.4 8月中下旬
Mid-late August昌都八宿县白马镇
Baima Township, Qamdo City(BM)96°55′56″E 30°03′47″N 3 240 233.3 10.4 9月上旬
Early September林芝察隅县古玉乡
Guyu Township, Nyingchi(GY)97°10′44″E 29°16′31″N 3 310 793.9 13.3 9月中下旬
Mid-late September林芝波密县松宗镇
Songzong Township, Nyingchi(SZ)96°16′20″E 29°37′49″N 3 230 900.0 8.5 8月下旬
Late August林芝林芝县布久乡
Bujiu Township, Nyingchi(BJ)94°23′30″E 29°35′24″N 2 927 654.0 8.5 9月中下旬
Mid-late September林芝米林县扎绕乡
Zharao Township, Nyingchi(ZR)94°21′17″E 29°19′28″N 2 912 641.0 8.2 9月中下旬
Mid-late September林芝米林县派镇
Paizhen Township, Nyingchi(PZ)94°52′26″E 29°30′54″N 2 864 641.0 8.2 9月中下旬
Mid-late September林芝米林县羌纳乡
Qiangna Township, Nyingchi(QN)94°30′17″E 29°25′34″N 2 881 641.0 8.2 9月中下旬
Mid-late September林芝工布江达县巴河镇
Bahe Township, Nyingchi(BH)93°39′47″E 29°51′35″N 3 125 808.0 8.3 9月中下旬
Mid-late September林芝朗县朗镇
Lang Township, Nyingchi(LZ)92°55′44″E 29°04′08″N 3 118 600.0 8.2 8月中旬
Mid August拉萨曲水县才纳乡
Caina Township, Lhasa City(CN)90°59′44″E 29°26′07″N 3 740 440.0 7.4 9月中下旬
Mid-late September -
光核桃果实表型性状中果实质量(FWT)和果核质量(NWT)用电子天平(精度0.01 g)测得,果实的纵径(FL)、横径(FWH)、侧径(FT)及果核的长(NL)、宽(NWH)、厚(NT)用电子游标卡尺(精度0.01 mm)测得。纵径为果实基部到顶部的距离;横径为果实腹缝线到果实边缘最大宽度;侧径为垂直于纵径、横径处的最厚距离,果核的长、宽、厚取值方式同果实纵径、横径和侧径。果实的果肉厚(PT)= FT-NT,出核率(NR)= NWT/FWT × 100%。
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通过巢式方差分析、方差分量及种群间表型分化系数(VST)的计算[17],研究18个种群光核桃果实表型性状种群间与种群内变异;使用均值、变异系数(coefficient of variation,CV)分析光核桃种群间与种群内表型性状的离散程度。
$$ {V_{{\rm{ST}}}} = \sigma _{\frac{t}{s}}^2/\left( {\sigma _{\frac{t}{s}}^2 + \sigma _s^2} \right) \times 100\% $$ 式中:s为种群数目;t为种群内的株数;
$ {\sigma }_{\frac{t}{s}}^{2} $ 为种群间方差分量;$ {\sigma }_{s}^{2} $ 为种群内方差分量。$$ {\rm{CV}} = S/X $$ 式中:S为标准差,X为平均值。
采用Pearson相关系数分析果实性状间的相关性。采用主成分分析(principal component analysis,PCA)果实表型性状与种群的相对关系,根据排序图筛选优良性状的主要代表种群。冗余分析(redundancy analysis,RDA)生态因子对果实表型性状总体变异的影响,并采用多元回归分析生态因子对特征性状的影响规律。PCA、RDA使用R语言vegan软件包分析,其它使用SAS及EXCEL软件分析。
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实地调查18个种群光核桃的成熟期,发现种群间有明显差异(表1)。光核桃的成熟期主要从8月中旬到9月下旬,林芝市朗县朗镇(海拔3 118 m)光核桃成熟最早,日喀则亚东县上亚东乡(海拔3 218 m)成熟较晚。即使在同一地区不同的种群间也存在差异,如山南市贡嘎县江塘镇(海拔3 770 m)光核桃的成熟期比山南市其他种群的成熟期晚;昌都市芒康县木许乡(海拔2 280 m)和八宿县林卡乡(海拔2 984 m)与山南市加查县的安绕镇(海拔3 265 m)和冷达乡(海拔3 168 m)属于不同地区,海拔相差也较大,但却有相近的成熟期。
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对18个种群的光核桃果实表型性状进行了巢式方差分析、方差分量及VST的计算(表2、3),结果显示10个果实表型性状在种群间和种群内均是极显著差异(P < 0.01);种群间的表型变异占总体变异的60.98%,种群内的占28.09%;表型分化系数为40.48% ~ 87.46%,果核厚表型分化系数最大,果核质量表型分化系数最小。表型分化系数的平均值为67.99%,表明光核桃果实表型变异主要来源于种群间。
表 2 18个种群光核桃果实表型性状方差分析
Table 2. ANOVA results of fruit phenotypic characters of A. mira from 18 populations
表型性状
Phenotypic trait均方 Mean square F 种群间
Between populations种群内
Within population随机误差
Random error种群间
Between populations种群内
Within population果实质量 Fruit mass(FWT) 5301.46 247.52 6.94 21.42** 35.66** 纵径 Fruit length(FL) 1273.28 65.70 2.68 19.38** 24.50** 横径 Fruit width(FWH) 2245.02 87.78 2.53 25.58** 34.70** 侧径 Fruit thickness(FT) 2642.09 89.83 2.77 29.41** 32.47** 果核质量 Nut mass(NWT) 10.48 1.10 0.04 9.50** 26.06** 果核长 Nut length(NL) 728.61 27.23 1.32 26.76** 20.70** 果核宽 Nut width(NWH) 518.54 17.72 0.79 29.26** 22.43** 果核厚 Nut thickness(NT) 527.29 6.07 0.32 86.92** 19.24** 果肉厚 Pulp thickness(PT) 3237.64 68.85 2.38 47.03** 28.89** 出核率 Nuclear rate(NR) 1 935.73 38.61 1.46 50.14** 26.39** 注:种群间自由度(df)为17;种群内的自由度(df)为216;随机误差的自由度(df)为4 446。**代表差异极显著,P < 0.01;*代表差异显著,P < 0.05。Notes:the degree of freedom (df) among populations is 17, the degree of freedom (df) within population is 216, the degree of freedom (df) of the random error is 4 446. ** represents very significant difference, P < 0.01; * represents significant difference, P < 0.05. 表 3 光核桃果实表型性状种群间和种群内方差分量与种群间表型分化系数(VST)
Table 3. Variance components and phenotypic differentiation coefficients(VST)of fruit phenotypic traits among A. mira populations and within population
表型性状
Phenotypic trait方差分量
Variance component方差分量百分比
Percentage of variance component/%VST/% 种群间
Between populations种群内
Within population随机误差
Random error种群间
Between populations种群内
Within populationFWT 38.88 24.06 6.94 55.64 34.43 61.77 FL 9.29 6.30 2.68 50.84 34.49 59.58 FWH 16.59 8.53 2.53 60.02 30.83 66.06 FT 19.63 8.71 2.77 63.12 27.99 69.28 NWT 0.07 0.11 0.04 32.71 48.10 40.48 NL 5.40 2.59 1.32 58.00 27.86 67.55 NWH 3.85 1.69 0.79 60.81 26.72 69.47 NT 4.01 0.58 0.32 81.83 11.74 87.46 PT 24.38 6.65 2.38 72.97 19.90 78.58 NR 14.59 3.71 1.46 73.81 18.79 79.71 平均 Mean — — — 60.98 28.09 67.99 -
对18个种群光核桃的果实表型性状进行相关性分析(表4),结果显示果实质量、纵径、横径、侧径、果肉厚相互之间存在显著性正相关;果实质量、纵径、横径、侧径、果肉厚与出核率呈显著负相关,果实的大小与果核的大小相关性不显著(r = − 0.13 ~ 0.20),表明果核的大小受果实大小的影响较小。
表 4 光核桃果实表型性状的相关系数
Table 4. Correlation coefficients between fruit phenotypic traits of A. mira
表型性状
Phenotypic traitFWT FL FWH FT NWT NL NWH NT PT NR FWT 1 0.94** 0.99** 0.99** 0.54* − 0.07 0.12 − 0.06 0.91** − 0.87** FL 1 0.94** 0.94** 0.54* 0.10 0.20 0.06 0.83** − 0.78** FWH 1 0.99** 0.51* − 0.13 0.08 − 0.09 0.93** − 0.89** FT 1 0.48* − 0.08 0.11 − 0.03 0.92** − 0.90** NWT 1 0.40 0.47* 0.23 0.34 − 0.15 NL 1 0.90** 0.90** − 0.44 0.35 NWH 1 0.94** − 0.28 0.16 NT 1 − 0.43 0.26 PT 1 − 0.92** NR 1 注:**表示在0.01水平下显著相关;*代表在0.05水平下显著相关。Notes: ** means the correlation is significant at 0.01 level; * means the correlation is significant at 0.05 level. -
变异系数(CV)反映了果实表型性状种群内与种群间的离散程度[18],结果种群内各果实表型性状变异系数的平均值DB最大,为18.53%;BM最小,为8.43%。果实表型性状种群间平均变异系数为7.86% ~ 25.25%,果实质量最大,果实纵径最小(表5)。
表 5 18个种群光核桃果实表型性状的均值和变异系数
Table 5. Means and CV (coefficient of variation) values of 10 phenotypic traits within 18 A. mira populations
表型性状
Phenotypic traitSYD AR LD LZ DB QD MX LK BM GY SZ BJ ZR JT CN PZ QN BH 均值
MeanFWT $ \bar X/\mathrm{g} $ 8.90 22.44 16.25 24.43 9.68 9.30 19.21 21.48 15.91 8.37 12.70 20.70 23.94 28.48 22.63 20.31 26.90 20.86 18.47 CV/% 34.16 27.64 17.19 30.77 43.92 21.00 22.38 21.31 16.20 29.60 25.49 19.03 22.26 31.49 22.79 26.61 28.97 13.72 25.25 FL $ \bar X/\mathrm{m}\mathrm{m} $ 27.40 33.48 30.35 33.14 25.49 28.24 32.58 33.59 29.87 27.39 30.53 33.14 34.69 36.56 31.28 32.89 36.36 33.91 31.72 CV/% 10.05 9.39 6.57 10.99 11.28 5.98 8.39 7.87 6.14 6.76 7.26 6.06 6.21 9.73 6.00 8.83 8.39 5.66 7.86 FWH $ \bar X/\mathrm{m}\mathrm{m} $ 24.97 33.64 30.48 34.55 24.95 25.54 30.80 32.86 28.59 23.25 27.41 32.68 34.41 36.76 33.62 32.98 36.07 33.09 30.92 CV/% 12.65 9.87 7.13 11.30 14.52 7.36 9.60 8.31 6.76 8.82 8.02 7.31 8.58 12.38 7.69 10.11 10.79 5.53 9.26 FT $ \bar X/\mathrm{m}\mathrm{m} $ 23.63 33.34 29.15 33.34 23.74 23.99 30.71 31.82 28.87 22.84 26.29 33.26 34.71 36.02 33.53 32.85 36.17 33.49 30.43 CV/% 13.09 10.60 6.97 10.16 14.46 8.69 10.30 14.15 6.80 10.84 8.89 5.16 8.31 11.68 8.06 10.02 9.67 4.99 9.60 NWT $ \bar X/\mathrm{g} $ 1.31 1.90 1.43 1.77 1.06 1.57 1.61 2.37 1.80 1.55 1.54 1.56 1.49 1.88 1.79 1.48 1.77 1.39 1.63 CV/% 18.96 25.80 19.51 22.61 35.88 13.47 21.08 15.06 12.76 16.65 24.53 15.87 20.03 19.00 18.88 23.57 18.69 23.58 20.33 NL $ \bar X/\mathrm{m}\mathrm{m} $ 19.99 22.12 13.83 14.94 17.66 21.30 21.09 22.46 21.55 22.11 21.37 19.24 19.93 20.93 18.82 18.93 20.72 19.60 19.81 CV/% 9.39 8.96 11.94 10.04 10.10 7.18 9.37 5.70 6.69 7.29 6.84 7.34 8.74 10.59 7.42 7.99 6.43 8.47 8.36 NWH $ \bar X/\mathrm{m}\mathrm{m} $ 15.77 17.83 9.99 11.19 13.93 15.93 14.43 17.68 16.11 15.68 16.08 15.14 15.26 17.05 16.52 15.11 16.40 14.88 15.28 CV/% 7.49 11.19 8.24 13.81 8.29 5.22 6.74 5.79 6.20 6.12 9.60 8.52 8.95 9.08 8.69 10.03 9.13 9.04 8.45 NT $ \bar X/\mathrm{m}\mathrm{m} $ 11.37 11.38 4.48 5.24 9.16 11.10 10.18 11.61 10.78 11.43 10.67 10.81 10.46 10.92 11.22 10.60 11.07 10.28 10.15 CV/% 5.18 10.08 17.59 16.53 11.11 5.53 7.93 6.03 5.70 4.28 7.83 7.06 5.63 5.90 6.71 7.77 7.56 8.30 8.15 PT $ \bar X/\mathrm{m}\mathrm{m} $ 12.26 21.96 24.68 28.10 14.58 12.89 20.52 20.22 18.09 11.41 15.63 22.45 24.25 25.10 22.31 22.25 25.10 23.21 20.28 CV/% 21.72 12.87 5.61 10.06 18.37 15.00 16.06 22.15 8.72 19.24 13.87 5.43 10.04 15.25 10.40 12.22 11.47 6.01 13.03 NR/% $ \bar X $ 15.60 8.67 8.83 7.56 11.55 17.29 8.95 11.44 11.52 19.33 12.55 7.64 6.33 7.07 8.09 7.43 6.87 6.67 10.19 CV 19.93 16.93 10.83 19.11 17.33 15.69 35.33 20.23 8.28 17.91 20.36 8.05 13.87 23.97 12.33 11.41 19.86 14.46 16.99 ${\overline {\rm{CV}} }$/% 15.26 14.33 11.16 15.54 18.53 10.51 14.72 12.66 8.43 12.75 13.27 8.98 11.26 14.91 10.90 12.86 13.10 9.98 注:$\bar X$为平均值;CV为变异系数;$\overline{\mathrm{C}\mathrm{V} }$为种群内各表型性状变异系数平均值。Notes: $\bar X$ is mean value; CV is coefficient of variation;$\overline {{\rm{CV}}} $ is the average variation coefficient of phenotypic traits in the population. -
PCA分析通过降维形式直观的表现光核桃果实表型性状与种群的相对关系[19],结果显示PC1、PC2共解释了90.81%观测到的果实表型性状变异,PC1和PC2分别解释58.54%和32.27%(表6)。PC1主要解释果实质量、纵径、横径、侧径、果肉厚和出核率;PC2主要解释果核长、果核宽和果核厚。根据主成分PC1和PC2绘制线性排序图,结合利用部位果肉和果核,可以看出果实大、果核小、果肉厚、出核率低的代表种群为JT、QN、LZ,其表型性状果实质量24.43 ~ 28.48 g,纵径33.14 ~ 36.56 mm,横径34.55 ~ 36.76 mm,侧径33.34 ~ 36.17 mm,果核质量1.77 ~ 1.88 g,果核长14.94 ~ 20.93 mm,果核宽11.19 ~ 17.05 mm,果核厚5.24 ~ 11.07 mm,果肉厚25.10 ~ 28.10 mm,出核率6.87% ~ 7.56%;果实小、果核大、果肉薄、高出核率代表种群有GY、SYD、QD,其表型性状果实质量8.37 ~ 9.30 g,纵径27.39 ~ 28.24 mm,横径23.25 ~ 25.54 mm,侧径22.84 ~ 23.99 mm,果核质量1.31 ~ 1.57 g,果核长19.99 ~ 22.11 mm,果核宽15.68 ~ 15.93 mm,果核厚11.10 ~ 11.43 mm,果肉厚11.41 ~ 12.89 mm,出核率15.60% ~ 19.33%(图2,表5)。
图 2 18个种群光核桃果实表型性状PCA分析
Figure 2. Segregation of the 18 populations according to fruit phenotypic traits determined by PCA analysis
表 6 PC1、PC2主成分的载荷
Table 6. Main components of load PC1 and PC2
表型性状
Phenotypic trait载荷系数 Load coefficient PC1(λ=58.54%) PC2(λ=32.27%) FWT 1.126 2 0.134 2 FL 1.068 1 0.271 7 FWH 1.134 9 0.079 8 FT 1.126 0 0.125 3 NWT 0.556 2 0.621 5 NL − 0.207 7 1.088 6 NWH − 0.002 7 1.114 9 NT − 0.193 1 1.061 5 PT 1.095 1 − 0.315 2 NR − 1.038 6 0.230 5 -
RDA分析结果显示,5个生态因子共解释56.00%的果实表型性状变异,RDA1、RDA2分别解释44.82%和9.20%,共54.02%(表7,图3)。生态因子与主成分的相关性分析结果显示只有年均温对10个表型性状的总体变异有显著影响,年均温对果实性状的影响大小顺序为NR > NL > NWT > NWH > NT > FL > FWT > FT > FWH > PT(表8,图3)。
图 3 5个生态因子与18个种群光核桃果实表型性状RDA分析
Figure 3. RDA analysis of 18 populations phenotypic traits with 5 ecological factors
表 7 RDA主成分的贡献率
Table 7. Contribution rates of RDA principal components
项目 Item RDA1 RDA2 RDA3 RDA4 RDA5 特征值
Eigenvalue4.482 4 0.919 9 0.117 9 0.056 1 0.024 3 贡献率
Contribution rate/%44.82 9.20 1.18 0.56 0.24 累计贡献率
Cumulative contribution rate/%44.82 54.02 55.20 55.76 56.00 表 8 生态因子与主成分RDA1、RDA2的相关性分析
Table 8. Correlation analysis of ecological factors and principal components of RDA1 and RDA2
生态因子Ecological factor RDA1 RDA2 R2 P E − 0.936 38 0.350 99 0.159 8 0.254 N 0.832 07 0.554 67 0.093 9 0.487 H − 0.847 67 0.530 52 0.056 3 0.653 R − 0.713 40 − 0.700 76 0.089 5 0.482 T − 0.481 89 0.876 23 0.302 3 0.049 * -
根据光核桃果实质量、纵径、横径、侧径与果肉厚存在显著性正相关,果实的大小与果核的大小相关性不显著,并结合利用部位果肉和果核,筛选出果肉厚和出核率两个特征性状。果肉厚和出核率与生态因子进行多元回归分析(表9),结果显示两方程调整后判定系数分别为0.599 3,0.798 1,F检验P值均小于0.01,表明两个方程均回归显著。果肉厚与经度、海拔、年均降雨量呈负相关,与纬度和年均温呈正相关;出核率与经度、海拔、年均降雨量和年均温呈正相关,与纬度呈负相关。两个回归方程中自变量的决定系数通过t检验显示5个生态因子中经度、纬度、海拔对果肉厚和出核率的影响极显著。
表 9 果肉厚、出核率与生态因子的多元回归方程
Table 9. Multiple regression equations of pulp thickness, nut rate and geographical meteorological factors
表型性状
Phenotypic trait回归方程
Regression equation调整后判定系数
Adjusted R2P值
P valuePT Y = 58.104 9 − 2.139 4x1 + 6.783 5x2 − 0.010 8x3 − 0.006 2x4 + 0.310 5x5 0.599 3 0.004 9 NR Y = − 8.888 7 + 1.534 8x1 − 5.421 8x2 + 0.009 1x3 + 0.003 5x4 + 0.302 9x5 0.798 1 0.000 1 注:x1.经度;x2. 纬度;x3. 海拔;x4. 年均降雨量;x5. 年均温。Notes: x1 is longitude; x2 is latitude; x3 is elevation; x4 is annual mean rainfall; x5 is annual mean temperature. -
不同种群光核桃的成熟期存在明显差异,主要从8月中旬到9月下旬。植物果实成熟期受环境条件和遗传特性的影响,经过长期的自然适应每个种群形成相对稳定的成熟期。Dicenta等人研究表明成熟期是可以遗传的[20]。因此,对于成熟期的调查为早熟或晚熟品种选育提供数据支持,成熟期的差异有助于满足不同时期桃子的市场需求。
光核桃表型性状在种群间和种群内存在显著差异,表明光核桃表型多样性丰富。表型分化系数平均为67.99%,种群间的变异大于种群内的变异,光核桃的表型变异主要来源于种群间,这与包文泉在林芝、山南范围内分析光核桃表型变异的研究结论相一致[14]。光核桃在西藏分布广泛,生境多样,各种群间有山地阻隔或距离较远,限制了花粉的传播和基因交流,也反映了地理和生殖隔离对表型变异的影响[17,21];另一方面,由于种群生境的差异造成了局部适应,致使不同生境下种群间有效基因流的降低,从而形成了适应性隔离[22-24]。种群变异包括表型变异与遗传变异,表型变异又与遗传变异密切相关,植物表型变异大表明其具有遗传多样性潜力[25]。因此,光核桃果实表型变异大,可以选育具有特征性状的光核桃。
表型变异系数越小离散程度越小,性状稳定性越好[26],种群内各果实表型性状变异系数的平均值DB最大为18.53%,BM最小为8.43%。种群内部环境差异大造成表型变异大,DB处在海拔变化较大的山谷,光照、水分等差异明显。种群间10个果实表型性状变异系数平均值为7.86% ~ 25.25%,果实质量最大,果实纵径最小,说明果实纵径较为稳定。
结合光核桃利用部位果肉和果核,筛选出果实大、果核小、果肉厚、出核率低的果用型和果实小、果核大、果肉薄、高出核率的核用型两种光核桃种质资源。果用型光核桃可用于加工果酒、果醋、果脯等,或作为水果食用[1,9],代表性种群有JT、QN、LZ;核用型光核桃桃核可做活性炭、生物吸附剂外;桃仁有炒制食用和浸泡榨油食用的历史,其种子可加工或做坚果[12],代表种群有GY、SYD、QD。
表型差异是通过基因与环境的相互作用实现的,生态因子对植物表型的塑造起着重要的作用[27]。结合RDA分析,经度、纬度、海拔、年均降雨量、年均温5个生态因子解释56.00%的表型性状变异,其他44.00%的表型变异可能来自于生物遗传特性[28]、土壤养分[29]、光[30]、昼夜温差[31]等条件。5个因子中只有年均温对光核桃的10个表型性状影响显著,这与李洪果研究的温度因子在气候因子中对种群表型性状的影响起主导作用的结论相一致[32],也同时说明了局部环境的温度受地形、海拔、降雨和光照等因素的影响,是环境变化的集中表现。
特征性状果肉厚与经度、海拔、年均降雨量呈负相关,可能与西藏降雨规律有关。光核桃分布区随着经度的增加,降雨量有所增加,且降雨集中在5—10月[33],通过影响温度、光照等进一步影响果实有机物质的积累与生长[34-35]。此外,随着海拔的增加,温度降低,植物生长缓慢,从而影响果实的生长。果肉厚与纬度和年均温呈正相关,随着纬度的升高,降雨量相对较少[33],白天阳光充足,夜晚温度低,有利于有机物质的积累[34];年均温的增加也有利于果实有机物质的积累[35]。出核率与经度、海拔、年均降雨量和年均温呈正相关,与纬度呈负相关。随着经度、海拔、年均降雨量的增加,果实果肉厚的减小,出核率增加;同时年均温的增加,果核也增大,与出核率呈现出正相关;随着纬度的升高,果肉厚增加,出核率降低。生态因子对特征性状的影响规律对光核桃优良种质资源推广种植具有指导意义。
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根据西藏野生光核桃的集中分布区,兼顾其生长的海拔、气候和成熟期的差异性,对5个地级市18个种群进行实地调查采样,研究光核桃果实表型性状种群变异规律,根据利用部位对光核桃种质资源进行筛选,得出如下结论:光核桃果实种群间表型性状多样,存在丰富的遗传变异潜力。依据光核桃果实利用部位及种群间果实表型性状筛选出果用型和核用型两类种质资源,山南贡嘎县江塘镇、林芝米林县羌纳乡、林芝朗县朗镇为果用型光核桃的代表种群,林芝察隅县古玉乡、日喀则亚东县上亚东乡、昌都芒康县曲登乡为核用型光核桃的代表种群。经度、纬度、海拔、年均降雨量、年均温5个生态因子中年均温对10个果实表型性状的总体影响显著,其中经度、纬度、海拔对特征性状果肉厚和出核率的影响极显著。研究光核桃果实表型种群变异,筛选优良种质资源,为光核桃果实的开发利用提供思路,也为光核桃的良种选育和推广提供参考。
Analysis on phenotypic variation and germplasm resource selection of wild Amygdalus mira in Tibet of southwestern China
-
摘要:
目的 本研究是探究西藏野生光核桃果实表型性状种群变异规律,结合主成分分析筛选优良种质资源,探明生态因子对果实表型性状的影响,为光核桃良种选育和推广提供参考。 方法 根据西藏野生光核桃的集中分布区,兼顾种群生长海拔、气候和成熟期的差异,对5个地级市18个种群(SYD、AR、LD、JT、DB、QD、MX、LK、BM、GY、SZ、BJ、ZR、PZ、QN、BH、LZ、CN)进行实地调查采样,每个种群选取13株长势良好的光核桃,各单株间距大于50 m,每株分阴面、阳面和上、下4个方位采集成熟果实,从每方位的果实中随机选择5枚,共20枚,测量其表型性状。 结果 光核桃果实表型性状种群间和种群内均存在极显著差异;种群间表型分化系数均值为67.99%,表型变异主要来源于种群间;根据PCA分析结合利用部位果肉和果核,筛选出果实大、果核小、果肉厚、出核率低的果用型光核桃,代表种群为山南贡嘎县江塘镇、林芝米林县羌纳乡、林芝朗县朗镇;果实小、果核大、果肉薄、高出核率的核用型光核桃,代表种群有林芝察隅县古玉乡、日喀则亚东县上亚东乡、昌都芒康县曲登乡。RDA分析5个生态因子共解释56.00%的果实性状变异,仅年均温对果实性状的总体变异影响显著(P = 0.049);两个特征性状果肉厚和出核率与生态因子的多元回归方程均回归显著(P < 0.01),调整后判定系数分别为0.599 3、0.798 1。果肉厚与经度、海拔、年均降雨量呈负相关,与纬度和年均温呈正相关;出核率与经度、海拔、年均降雨量和年均温呈正相关,与纬度呈负相关;5个生态因子中经度、纬度、海拔对果肉厚和出核率的影响极显著。 结论 光核桃果实表型性状变异主要来源于种群间;根据表型性状筛选出了果用型和核用型光核桃及其代表种群,其特征性状主要受经纬度、海拔的影响。 Abstract:Objective This study aims to explore the variation of fruit phenotypic traits of the wild Amygdalus mira populations in Tibet of southwestern China and to screen the good germplasm resources by the principal component analysis, and also to ascertain the effects of ecological factors on phenotypic traits of fruits for fine breeding and generalizing of Amygdalus mira. Method The 18 populations (SYD, AR, LD, JT, DB, QD, MX, LK, BM, GY, SZ, BJ, ZR, PZ, QN, BH, LZ, CN) in 5 regions were surveyed and sampled according to the concentration distribution area combined with the differences in altitude, climate and maturity of wild A. mira in Tibet. In each population, 13 trees with good growth potential were selected, and the spacing of each individual plant was greater than 50 m. The ripe fruits were collected from the dark, sunny and the upper, lower four directions of each plant, 5 fruits were randomly selected from each direction, 20 in total, and then the phenotypic traits were measured. Result The fruit phenotypic traits were highly significantly different in population and among populations of A. mira. The mean of phenotypic differentiation coefficient was 67.99%, and the fruit phenotypic variations were mainly derived from populations. According to the results of PCA analysis and the use of pulp and core, the representative populations with large fruit, small nut, thick pulp and low nuclear rate were selected, and they were the Jiangtang Township, Qiangna Township and Lang Township. While the representative populations with small fruit, large nut, thin pulp and high nuclear rate were the Guyu Township, Shangyadong Township and Qudeng Township. The 5 ecological factors explained 56.00% of the fruit character variation through RDA analysis, and only the annual average temperature had a significant effect on the overall variation of fruit traits (P = 0.049). The multiple regression equation of the two characteristics of the pulp thickness and the nuclear rate with the ecological factors were all significant (P < 0.01), and the adjusted R2 was 0.5993 and 0.7981, respectively. The thickness of pulp was negatively correlated with longitude, altitude and average annual rainfall, and was positively correlated with latitude and average annual temperature. The nuclear rate was positively correlated with longitude, altitude, average annual rainfall and annual temperature, and was negatively correlated with latitude. The effects of longitude, latitude and altitude on the thickness of pulp and the nuclear rate were highly significant. Conclusion The phenotypic variation of A. mira mainly comes from populations. According to the phenotypic traits, fruit type and nut type of A. mira and its representative populations were screened. The effects of longitude, latitude and altitude of 5 ecological factors on the thickness of pulp and the nuclear rate were the most significant. -
Key words:
- Amygdalus mira /
- phenotypic character /
- population /
- variation /
- germplasm resource
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图 2 18个种群光核桃果实表型性状PCA分析
FWT、FL、FWH、FT、NWT、NL、NWH、NT、PT、NR为表型性状;SYD、AR、LD、LZ、DB、QD、MX、LK、BM、GY、SZ、BJ、ZR、JT、CN、PZ、QN、BH为种群代码。下同。FWT, FL, FWH, FT, NWT, NL, NWH, NT, PT, NR are phenotypic traits; SYD, AR, LD, LZ, DB, QD, MX, LK, BM, GY, SZ, BJ, ZR, JT, CN, PZ, QN, BH are population codes. The same below.
Figure 2. Segregation of the 18 populations according to fruit phenotypic traits determined by PCA analysis
表 1 光核桃18个种群的基本信息及成熟期
Table 1. Basic information and maturity stage of the 18 A. mira populations investigated in this study
种群及代码
Population and code经度
Longitude纬度
Latitude海拔
Elevation
(H)/m年均降水量
Average annual
rainfall(R)/mm年均温
Mean temperature
(T)/℃成熟期
Maturity stage日喀则亚东县上亚东乡
Shangyadong Township, Shigatse City(SYD)88°57′17″E 27°30′40″N 3 218 873.0 8.5 9月下旬
Late September山南加查县安绕镇
Anrao Township, Lhoka(AR)92°33′59″E 29°09′00″N 3 265 492.7 8.9 8月中下旬
Mid-late August山南加查县冷达乡
Lengda Township, Lhoka(LD)92°43′19″E 29°04′38″N 3 168 492.7 8.9 8月中下旬
Mid-late August山南贡嘎县江塘镇
Jiangtang Township, Lhoka(JT)90°41′42″E 29°15′43″N 3 770 356.6 9.2 9月中下旬
Mid-late September昌都左贡县东坝乡
Dongba Township, Qamdo City(DB)97°26′35″E 29°52′40″N 3 153 405.0 4.2 9月上旬
Early September昌都芒康县曲登乡
Qudeng Township, Qamdo City(QD)98°12′18″E 29°33′23″N 3 654 350.0 10.0 9月上旬
Early September昌都芒康县木许乡
Muxu Township, Qamdo City(MX)98°37′02″E 28°54′27″N 2 280 450.0 10.5 8月中下旬
Mid-late August昌都八宿县林卡乡
Linka Township, Qamdo City(LK)97°10′04″E 30°00′39″N 2 984 233.3 10.4 8月中下旬
Mid-late August昌都八宿县白马镇
Baima Township, Qamdo City(BM)96°55′56″E 30°03′47″N 3 240 233.3 10.4 9月上旬
Early September林芝察隅县古玉乡
Guyu Township, Nyingchi(GY)97°10′44″E 29°16′31″N 3 310 793.9 13.3 9月中下旬
Mid-late September林芝波密县松宗镇
Songzong Township, Nyingchi(SZ)96°16′20″E 29°37′49″N 3 230 900.0 8.5 8月下旬
Late August林芝林芝县布久乡
Bujiu Township, Nyingchi(BJ)94°23′30″E 29°35′24″N 2 927 654.0 8.5 9月中下旬
Mid-late September林芝米林县扎绕乡
Zharao Township, Nyingchi(ZR)94°21′17″E 29°19′28″N 2 912 641.0 8.2 9月中下旬
Mid-late September林芝米林县派镇
Paizhen Township, Nyingchi(PZ)94°52′26″E 29°30′54″N 2 864 641.0 8.2 9月中下旬
Mid-late September林芝米林县羌纳乡
Qiangna Township, Nyingchi(QN)94°30′17″E 29°25′34″N 2 881 641.0 8.2 9月中下旬
Mid-late September林芝工布江达县巴河镇
Bahe Township, Nyingchi(BH)93°39′47″E 29°51′35″N 3 125 808.0 8.3 9月中下旬
Mid-late September林芝朗县朗镇
Lang Township, Nyingchi(LZ)92°55′44″E 29°04′08″N 3 118 600.0 8.2 8月中旬
Mid August拉萨曲水县才纳乡
Caina Township, Lhasa City(CN)90°59′44″E 29°26′07″N 3 740 440.0 7.4 9月中下旬
Mid-late September表 2 18个种群光核桃果实表型性状方差分析
Table 2. ANOVA results of fruit phenotypic characters of A. mira from 18 populations
表型性状
Phenotypic trait均方 Mean square F 种群间
Between populations种群内
Within population随机误差
Random error种群间
Between populations种群内
Within population果实质量 Fruit mass(FWT) 5301.46 247.52 6.94 21.42** 35.66** 纵径 Fruit length(FL) 1273.28 65.70 2.68 19.38** 24.50** 横径 Fruit width(FWH) 2245.02 87.78 2.53 25.58** 34.70** 侧径 Fruit thickness(FT) 2642.09 89.83 2.77 29.41** 32.47** 果核质量 Nut mass(NWT) 10.48 1.10 0.04 9.50** 26.06** 果核长 Nut length(NL) 728.61 27.23 1.32 26.76** 20.70** 果核宽 Nut width(NWH) 518.54 17.72 0.79 29.26** 22.43** 果核厚 Nut thickness(NT) 527.29 6.07 0.32 86.92** 19.24** 果肉厚 Pulp thickness(PT) 3237.64 68.85 2.38 47.03** 28.89** 出核率 Nuclear rate(NR) 1 935.73 38.61 1.46 50.14** 26.39** 注:种群间自由度(df)为17;种群内的自由度(df)为216;随机误差的自由度(df)为4 446。**代表差异极显著,P < 0.01;*代表差异显著,P < 0.05。Notes:the degree of freedom (df) among populations is 17, the degree of freedom (df) within population is 216, the degree of freedom (df) of the random error is 4 446. ** represents very significant difference, P < 0.01; * represents significant difference, P < 0.05. 表 3 光核桃果实表型性状种群间和种群内方差分量与种群间表型分化系数(VST)
Table 3. Variance components and phenotypic differentiation coefficients(VST)of fruit phenotypic traits among A. mira populations and within population
表型性状
Phenotypic trait方差分量
Variance component方差分量百分比
Percentage of variance component/%VST/% 种群间
Between populations种群内
Within population随机误差
Random error种群间
Between populations种群内
Within populationFWT 38.88 24.06 6.94 55.64 34.43 61.77 FL 9.29 6.30 2.68 50.84 34.49 59.58 FWH 16.59 8.53 2.53 60.02 30.83 66.06 FT 19.63 8.71 2.77 63.12 27.99 69.28 NWT 0.07 0.11 0.04 32.71 48.10 40.48 NL 5.40 2.59 1.32 58.00 27.86 67.55 NWH 3.85 1.69 0.79 60.81 26.72 69.47 NT 4.01 0.58 0.32 81.83 11.74 87.46 PT 24.38 6.65 2.38 72.97 19.90 78.58 NR 14.59 3.71 1.46 73.81 18.79 79.71 平均 Mean — — — 60.98 28.09 67.99 表 4 光核桃果实表型性状的相关系数
Table 4. Correlation coefficients between fruit phenotypic traits of A. mira
表型性状
Phenotypic traitFWT FL FWH FT NWT NL NWH NT PT NR FWT 1 0.94** 0.99** 0.99** 0.54* − 0.07 0.12 − 0.06 0.91** − 0.87** FL 1 0.94** 0.94** 0.54* 0.10 0.20 0.06 0.83** − 0.78** FWH 1 0.99** 0.51* − 0.13 0.08 − 0.09 0.93** − 0.89** FT 1 0.48* − 0.08 0.11 − 0.03 0.92** − 0.90** NWT 1 0.40 0.47* 0.23 0.34 − 0.15 NL 1 0.90** 0.90** − 0.44 0.35 NWH 1 0.94** − 0.28 0.16 NT 1 − 0.43 0.26 PT 1 − 0.92** NR 1 注:**表示在0.01水平下显著相关;*代表在0.05水平下显著相关。Notes: ** means the correlation is significant at 0.01 level; * means the correlation is significant at 0.05 level. 表 5 18个种群光核桃果实表型性状的均值和变异系数
Table 5. Means and CV (coefficient of variation) values of 10 phenotypic traits within 18 A. mira populations
表型性状
Phenotypic traitSYD AR LD LZ DB QD MX LK BM GY SZ BJ ZR JT CN PZ QN BH 均值
MeanFWT $ \bar X/\mathrm{g} $ 8.90 22.44 16.25 24.43 9.68 9.30 19.21 21.48 15.91 8.37 12.70 20.70 23.94 28.48 22.63 20.31 26.90 20.86 18.47 CV/% 34.16 27.64 17.19 30.77 43.92 21.00 22.38 21.31 16.20 29.60 25.49 19.03 22.26 31.49 22.79 26.61 28.97 13.72 25.25 FL $ \bar X/\mathrm{m}\mathrm{m} $ 27.40 33.48 30.35 33.14 25.49 28.24 32.58 33.59 29.87 27.39 30.53 33.14 34.69 36.56 31.28 32.89 36.36 33.91 31.72 CV/% 10.05 9.39 6.57 10.99 11.28 5.98 8.39 7.87 6.14 6.76 7.26 6.06 6.21 9.73 6.00 8.83 8.39 5.66 7.86 FWH $ \bar X/\mathrm{m}\mathrm{m} $ 24.97 33.64 30.48 34.55 24.95 25.54 30.80 32.86 28.59 23.25 27.41 32.68 34.41 36.76 33.62 32.98 36.07 33.09 30.92 CV/% 12.65 9.87 7.13 11.30 14.52 7.36 9.60 8.31 6.76 8.82 8.02 7.31 8.58 12.38 7.69 10.11 10.79 5.53 9.26 FT $ \bar X/\mathrm{m}\mathrm{m} $ 23.63 33.34 29.15 33.34 23.74 23.99 30.71 31.82 28.87 22.84 26.29 33.26 34.71 36.02 33.53 32.85 36.17 33.49 30.43 CV/% 13.09 10.60 6.97 10.16 14.46 8.69 10.30 14.15 6.80 10.84 8.89 5.16 8.31 11.68 8.06 10.02 9.67 4.99 9.60 NWT $ \bar X/\mathrm{g} $ 1.31 1.90 1.43 1.77 1.06 1.57 1.61 2.37 1.80 1.55 1.54 1.56 1.49 1.88 1.79 1.48 1.77 1.39 1.63 CV/% 18.96 25.80 19.51 22.61 35.88 13.47 21.08 15.06 12.76 16.65 24.53 15.87 20.03 19.00 18.88 23.57 18.69 23.58 20.33 NL $ \bar X/\mathrm{m}\mathrm{m} $ 19.99 22.12 13.83 14.94 17.66 21.30 21.09 22.46 21.55 22.11 21.37 19.24 19.93 20.93 18.82 18.93 20.72 19.60 19.81 CV/% 9.39 8.96 11.94 10.04 10.10 7.18 9.37 5.70 6.69 7.29 6.84 7.34 8.74 10.59 7.42 7.99 6.43 8.47 8.36 NWH $ \bar X/\mathrm{m}\mathrm{m} $ 15.77 17.83 9.99 11.19 13.93 15.93 14.43 17.68 16.11 15.68 16.08 15.14 15.26 17.05 16.52 15.11 16.40 14.88 15.28 CV/% 7.49 11.19 8.24 13.81 8.29 5.22 6.74 5.79 6.20 6.12 9.60 8.52 8.95 9.08 8.69 10.03 9.13 9.04 8.45 NT $ \bar X/\mathrm{m}\mathrm{m} $ 11.37 11.38 4.48 5.24 9.16 11.10 10.18 11.61 10.78 11.43 10.67 10.81 10.46 10.92 11.22 10.60 11.07 10.28 10.15 CV/% 5.18 10.08 17.59 16.53 11.11 5.53 7.93 6.03 5.70 4.28 7.83 7.06 5.63 5.90 6.71 7.77 7.56 8.30 8.15 PT $ \bar X/\mathrm{m}\mathrm{m} $ 12.26 21.96 24.68 28.10 14.58 12.89 20.52 20.22 18.09 11.41 15.63 22.45 24.25 25.10 22.31 22.25 25.10 23.21 20.28 CV/% 21.72 12.87 5.61 10.06 18.37 15.00 16.06 22.15 8.72 19.24 13.87 5.43 10.04 15.25 10.40 12.22 11.47 6.01 13.03 NR/% $ \bar X $ 15.60 8.67 8.83 7.56 11.55 17.29 8.95 11.44 11.52 19.33 12.55 7.64 6.33 7.07 8.09 7.43 6.87 6.67 10.19 CV 19.93 16.93 10.83 19.11 17.33 15.69 35.33 20.23 8.28 17.91 20.36 8.05 13.87 23.97 12.33 11.41 19.86 14.46 16.99 ${\overline {\rm{CV}} }$ /%15.26 14.33 11.16 15.54 18.53 10.51 14.72 12.66 8.43 12.75 13.27 8.98 11.26 14.91 10.90 12.86 13.10 9.98 注: $\bar X$ 为平均值;CV为变异系数;$\overline{\mathrm{C}\mathrm{V} }$ 为种群内各表型性状变异系数平均值。Notes:$\bar X$ is mean value; CV is coefficient of variation;$\overline {{\rm{CV}}} $ is the average variation coefficient of phenotypic traits in the population.表 6 PC1、PC2主成分的载荷
Table 6. Main components of load PC1 and PC2
表型性状
Phenotypic trait载荷系数 Load coefficient PC1(λ=58.54%) PC2(λ=32.27%) FWT 1.126 2 0.134 2 FL 1.068 1 0.271 7 FWH 1.134 9 0.079 8 FT 1.126 0 0.125 3 NWT 0.556 2 0.621 5 NL − 0.207 7 1.088 6 NWH − 0.002 7 1.114 9 NT − 0.193 1 1.061 5 PT 1.095 1 − 0.315 2 NR − 1.038 6 0.230 5 表 7 RDA主成分的贡献率
Table 7. Contribution rates of RDA principal components
项目 Item RDA1 RDA2 RDA3 RDA4 RDA5 特征值
Eigenvalue4.482 4 0.919 9 0.117 9 0.056 1 0.024 3 贡献率
Contribution rate/%44.82 9.20 1.18 0.56 0.24 累计贡献率
Cumulative contribution rate/%44.82 54.02 55.20 55.76 56.00 表 8 生态因子与主成分RDA1、RDA2的相关性分析
Table 8. Correlation analysis of ecological factors and principal components of RDA1 and RDA2
生态因子Ecological factor RDA1 RDA2 R2 P E − 0.936 38 0.350 99 0.159 8 0.254 N 0.832 07 0.554 67 0.093 9 0.487 H − 0.847 67 0.530 52 0.056 3 0.653 R − 0.713 40 − 0.700 76 0.089 5 0.482 T − 0.481 89 0.876 23 0.302 3 0.049 * 表 9 果肉厚、出核率与生态因子的多元回归方程
Table 9. Multiple regression equations of pulp thickness, nut rate and geographical meteorological factors
表型性状
Phenotypic trait回归方程
Regression equation调整后判定系数
Adjusted R2P值
P valuePT Y = 58.104 9 − 2.139 4x1 + 6.783 5x2 − 0.010 8x3 − 0.006 2x4 + 0.310 5x5 0.599 3 0.004 9 NR Y = − 8.888 7 + 1.534 8x1 − 5.421 8x2 + 0.009 1x3 + 0.003 5x4 + 0.302 9x5 0.798 1 0.000 1 注:x1.经度;x2. 纬度;x3. 海拔;x4. 年均降雨量;x5. 年均温。Notes: x1 is longitude; x2 is latitude; x3 is elevation; x4 is annual mean rainfall; x5 is annual mean temperature. -
[1] 钟政昌, 王婷, 高根升, 等. 自然温度下光核桃果酒主发酵工艺优化[J]. 食品科学, 2012, 33(13):197−201. Zhong Z C, Wang T, Gao G S, et al. Optimization of fermentation process for Prunus mira Koehne wine at natural temperature by response surface methodology[J]. Food Science, 2012, 33(13): 197−201. [2] 谭江平, 曾秀丽, 廖明安. 西藏光核桃自然居群遗传多样性的SRAP分析[J]. 草业学报, 2012, 21(6):213−220. doi: 10.11686/cyxb20120628 Tan J P, Zeng X L, Liao M A. Genetic diversity of natural Prunus mira populations detected by SRAP[J]. Acta Prataculturae Sinica, 2012, 21(6): 213−220. doi: 10.11686/cyxb20120628 [3] 郭其强, 罗大庆, 王贞红, 等. 光核桃幼苗光合特性和保护酶对干旱胁迫的响应[J]. 西北农林科技大学学报(自然科学版), 2010, 38(6):138−144. Guo Q Q, Luo D Q, Wang Z H, et al. Photosynthetic characteristics and protective enzyme activities of Prunus mira seedlings to drought stress[J]. Journal of Northwest A&F University (Natural Science Edition), 2010, 38(6): 138−144. [4] 侯常伟, 白涛, 王忆, 等. Uv-b辐射对光核桃光合作用和内源激素水平的影响[J]. 中国农学通报, 2012, 28(22):184−189. doi: 10.11924/j.issn.1000-6850.2012-1872 Hou C W, Bai T, Wang Y, et al. Influence of ultraviolet radiation on photosynthesis and hormone levels in Prunus mira Koehne[J]. Chinese Agricultural Science Bulletin, 2012, 28(22): 184−189. doi: 10.11924/j.issn.1000-6850.2012-1872 [5] 包文泉, 乌云塔娜, 杜红岩, 等. 基于SSR标记的西藏光核桃群体遗传多样性和遗传结构分析[J]. 林业科学, 2018, 54(2):30−41. doi: 10.11707/j.1001-7488.20180204 Bao W Q, Wuyuntana, Du H Y, et al. Genetic diversity and population structure of Amygdalus mira in the Tibet Plateau in China based on SSR markers[J]. Scientia Silvae Sinicae, 2018, 54(2): 30−41. doi: 10.11707/j.1001-7488.20180204 [6] Guan F, Wang S, Li R, et al. Genetic diversity of wild peach (Prunus mira Koehne kov et. kpst) from different altitudes in the Tibetan Plateau by pollen morphous and rapd markers[J]. Hortscience, 2014, 49(8): 1017−1022. doi: 10.21273/HORTSCI.49.8.1017 [7] Peng M, Guan F, Tao L, et al. Analysis of genetic relationship on Amygdalus mira (Koehne) ricker with other peach species using simple sequence repeat (SSR)[J]. Biochemical Systematics & Ecology, 2015, 62: 98−105. [8] 钟政昌, 方江平, 钟国辉. 土壤因子与西藏光核桃果实品质的关系[J]. 林业科技开发, 2009, 23(5):44−47. doi: 10.3969/j.issn.1000-8101.2009.05.011 Zhong Z C, Fang J P, Zhong G H. Relationship between soil nutrient and Prunus mira Koehne fruit quality[J]. China Forestry Science and Technology, 2009, 23(5): 44−47. doi: 10.3969/j.issn.1000-8101.2009.05.011 [9] 钟政昌, 方江平. 液固串淋法生产光核桃果醋的工艺[J]. 食品研究与开发, 2011, 32(3):94−96. doi: 10.3969/j.issn.1005-6521.2011.03.026 Zhong Z C, Fang J P. Liquid & solid cross-sprinkling fermentation in producing Prunus mira Koehne vinegar[J]. Food Research and Development, 2011, 32(3): 94−96. doi: 10.3969/j.issn.1005-6521.2011.03.026 [10] 郝海平, 姜闯道, 石雷, 等. 根系温度对光核桃幼苗光合机构热稳定性的影响[J]. 植物生态学报, 2009, 33(5):984−992. doi: 10.3773/j.issn.1005-264x.2009.05.018 Hao H P, Jiang C D, Shi L, et al. Effects of root temperature on thermostability of photosynthetic apparatus in Prunus mira seedlings[J]. Chinese Journal of Plant Ecology, 2009, 33(5): 984−992. doi: 10.3773/j.issn.1005-264x.2009.05.018 [11] 罗达尚.中华藏本草[M]. 北京: 民族出版社, 1997: 122−123. Luo D S. Chinese Tibetan materia medica[M]. Beijing:The Ethnic Publishing House, 1997:122−123. [12] 魏丽萍, 钟政昌, 李明. 光核桃仁脂肪油的提取与其理化性质分析[J]. 经济林研究, 2013, 31(3):136−139. doi: 10.3969/j.issn.1003-8981.2013.03.027 Wei L P, Zhong Z C, Li M. Extraction and physicochemical properties of fatty oil in Prunus mira kernel[J]. Nonwood Forest Research, 2013, 31(3): 136−139. doi: 10.3969/j.issn.1003-8981.2013.03.027 [13] 刘侠, 陈碧, 白艳霞. 桃核直接作为生物吸附材料对水中亚甲基蓝的吸附研究[J]. 科学技术与工程, 2015, 15(12):118−122. doi: 10.3969/j.issn.1671-1815.2015.12.020 Liu X, Chen B, Bai Y X. Study on adsorption of peach core directly as a biological adsorption material on methylene blue in aqueous solution[J]. Science Technology and Engineering, 2015, 15(12): 118−122. doi: 10.3969/j.issn.1671-1815.2015.12.020 [14] 包文泉, 乌云塔娜, 杜红岩, 等. 西藏光核桃表型性状遗传多样性分析[J]. 分子植物育种, 2018, 16(16):5463−5473. Bao W Q, Wuyuntana, Du H Y, et al. Genetic diversity analysis of Amygdalus mira from the Tibet Plateau in China based on phenotypic traits[J]. Molecular Plant Breeding, 2018, 16(16): 5463−5473. [15] Pigliucci M, Murren C J, Schlichting C D. Phenotypic plasticity and evolution by genetic assimilation[J]. Journal of Experimental Biology, 2006, 209(12): 2362−2367. doi: 10.1242/jeb.02070 [16] Li M, Zhao Z, Miao X J, et al. Genetic diversity and population structure of Siberian apricot (Prunus sibirical) in China[J/OL]. International Journal of Molecular Sciences, 2014, 15(1), 377. [2019−10−25]. https://www.mdpi.com/1422-0067/15/1/377/pdf. [17] 张彩霞, 明军, 刘春, 等. 岷江百合天然群体的表型多样性[J]. 园艺学报, 2008, 35(8):1183−1188. doi: 10.3321/j.issn:0513-353X.2008.08.013 Zhang C X, Ming J, Liu C, et al. Phenotypic variation of natural populations in Lilium regale Wilson[J]. Acta Horticulturae Sinica, 2008, 35(8): 1183−1188. doi: 10.3321/j.issn:0513-353X.2008.08.013 [18] Jie Z, Zheng H, Gan S, et al. Phenotypic variation in natural populations of Betula alnoides in Guangxi, China[J]. Scientia Silvae Sinicae, 2005, 41(2): 59−65. [19] Cantin C M, Gogorcena Y, Moreno M A. Phenotypic diversity and relationships of fruit quality traits in peach and nectarine (Prunus persica (L.) Batsch) breeding progenies[J]. Euphytica, 2010, 171(2): 211−226. doi: 10.1007/s10681-009-0023-4 [20] Dicenta F, Garcia J E, Carbonell E A. Heritability of fruit characters in almond[J]. Journal of Horticultural Science, 1993, 68(1): 121−126. doi: 10.1080/00221589.1993.11516335 [21] 冯秋红, 史作民, 徐静茹, 等. 岷江柏天然种群种实表型变异特征[J]. 应用生态学报, 2017, 28(3):748−756. Feng Q H, Shi Z M, Xu J R, et al. Phenotypic variations in cones and seeds of natural Cupressus chengiana populations in China[J]. Chinese Journal of Applied Ecology, 2017, 28(3): 748−756. [22] Shih K M, Chang C T, Chung J D, et al. Adaptive genetic divergence despite significant isolation-by-distance in populations of Taiwan cow-tail fir (Keteleeria davidiana var. formosana) [J/OL]. Frontiers in Plant Science, 2018, 9: 92 [2019−09−20]. https://sci-hub.tw/10.3389/fpls.2018.00092#. [23] Zhao Y, Vrieling K, Liao H, et al. Are habitat fragmentation, local adaptation and isolation-by-distance driving population divergence in wild rice Oryza rufipogon?[J]. Molecular Ecology, 2013, 22(22): 5531−5547. doi: 10.1111/mec.12517 [24] Ruan Y, Huang B H, Lai S J, et al. Population genetic structure, local adaptation, and conservation genetics of Kandelia obovata[J]. Tree Genetics & Genomes, 2013, 9(4): 913−925. [25] Khadivi-Khub A, Etemadi-Khah A. Phenotypic diversity and relationships between morphological traits in selected almond (Prunus amygdalus) germplasm[J]. Agroforest Syst, 2015, 89: 205−216. doi: 10.1007/s10457-014-9754-x [26] 林玲, 王军辉, 罗建, 等. 砂生槐天然群体种实性状的表型多样性[J]. 林业科学, 2014, 50(4):137−143. Lin L, Wang J H, Luo J, et al. Phenotypic diversity of seed and fruit traits in natural populations of Sophora moorcroftiana[J]. Scientia Silvae Sinicae, 2014, 50(4): 137−143. [27] Bonser S P. Plant phenotypic plasticity in a changing climate[J]. Trends in Plant Science, 2010, 15(12): 684−692. doi: 10.1016/j.tplants.2010.09.008 [28] 张永兵, 李寐华, 吴海波, 等. 新疆甜瓜地方品种资源的表型遗传多样性[J]. 园艺学报, 2012, 39(2):305−314. Zhang Y B, Li M H, Wu H B, et al. Genetic diversity of melon landraces (Cucumis melo L.) in Xinjiang based on phenotypic characters[J]. Acta Horticulturae Sinica, 2012, 39(2): 305−314. [29] 杜会聪, 蒋雅婷, 田敏, 等. 浙江省野生蜡梅花部形态变异及其与环境因子的相关性[J]. 生态学报, 2018, 38(16):5800−5809. Du H C, Jiang Y T, Tian M, et al. Morphological variation in flowers of wild populations of Chimonanthus praecox in Zhejiang Province and its correlation with environment factors[J]. Acta Ecologica Sinica, 2018, 38(16): 5800−5809. [30] 杜宁, 张秀茹, 王炜, 等. 荆条叶性状对野外不同光环境的表型可塑性[J]. 生态学报, 2011, 31(20):6049−6059. Du N, Zhang X R, Wang W, et al. Foliar phenotypic plasticity of a warm-temperate shrub, Vitex negundo var.heterophylla, to different light environments in the field[J]. Acta Ecologica Sinica, 2011, 31(20): 6049−6059. [31] 沈涛, 申仕康, 张霁, 等. 三七表型变异及其对气候因子的响应[J]. 热带亚热带植物学报, 2017, 25(5):445−455. doi: 10.11926/jtsb.3724 Shen T, Shen S K, Zhang J, et al. Phenotypic variation of Panax notoginseng and response to climatic factors[J]. Journal of Tropical and Subtropical Botany, 2017, 25(5): 445−455. doi: 10.11926/jtsb.3724 [32] 李洪果, 陈达镇, 许靖诗, 等. 濒危植物格木天然种群的表型多样性及变异[J]. 林业科学, 2019, 55(4):72−86. Li H G, Chen D Z, Xu J S, et al. Phenotypic diversity and variation in natural populations of Erythrophleum fordii, an endangered plant species[J]. Scientia Silvae Sinicae, 2019, 55(4): 72−86. [33] 王晓军, 程绍敏. 西藏主要气候特征分析[J]. 高原山地气象研究, 2009, 29(4):81−84. doi: 10.3969/j.issn.1674-2184.2009.04.014 Wang X J, Cheng S M. Analysis of major climatic features in Tibet[J]. Plateau and Mountain Meteorology Research, 2009, 29(4): 81−84. doi: 10.3969/j.issn.1674-2184.2009.04.014 [34] 赵玉萍, 邹志荣, 杨振超, 等. 不同温度和光照对温室番茄光合作用及果实品质的影响[J]. 西北农林科技大学学报(自然科学版), 2010, 38(5):125−130. Zhao Y P, Zou Z R, Yang Z C, et al. Effect of temperature and light to tomato photosynthesis and quality in greenhouse[J]. Journal of Northwest A&F University (Natural Science Edition), 2010, 38(5): 125−130. [35] 齐国亮, 苏雪玲, 郑国琦, 等. 气象因子对宁夏枸杞果实生长及多糖含量的影响[J]. 植物学报, 2016, 51(3):311−321. doi: 10.11983/CBB15041 Qi G L, Su X L, Zheng G Q, et al. Effect of meteorological factor on fruit growth and accumulation of polysaccharides in Lycium barbarum[J]. Chinese Bulletin of Botany, 2016, 51(3): 311−321. doi: 10.11983/CBB15041 -