Models for Estimating Morphological Characteristics of Pennisetum giganteum Leaves
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摘要:目的 叶片是植物的重要器官，但巨菌草叶片的形态特征尚缺乏基础的数据支撑。利用巨菌草叶片相关指标构建叶面积和叶鲜重模型可为巨菌草形态特征研究提供便捷方法。方法 采集巨菌草叶片长度、宽度、叶面积和叶鲜重等信息，对巨菌草叶片长度、叶片宽度、叶片鲜重、叶面积指标进行相关性分析，利用叶片长度、叶片宽度、叶片长宽积、叶片长度-叶片宽度、叶片长度+叶片宽度、叶长2、叶宽2等7个指标，采用一元线性回归模型、二元线性回归模型、二次三项式模型对叶面积和叶鲜重进行模型的构建。结果 巨菌草叶片长度、叶片宽度、叶片鲜重、叶面积指标间的相关性较好，指标间相关性系数在0.74～0.91。最适宜巨菌草叶面积的估算模型为：yA=0.72xP（R2=0.99，yA代表叶面积，xP代表叶片长宽积），叶片鲜重最优估算模型为：yF=0.02xP（R2=0.96，其中yF代表叶鲜重，xP代表叶片长宽积）。验证结果表明，实测叶面积与估测叶面积线性回归拟合较好R2均为0.99，叶面积和叶鲜重的RMSE分别为18.67 cm2、0.67 g。结论 本研究得出了巨菌草叶面积和叶鲜重的最优模型，对于菌草研究基础数据的扩充有一定的理论意义。Abstract:Objective Mathematic models for estimating the morphological characteristics of Pennisetum giganteum leaves were constructed to facilitate the utilization of the plant material.Method Measurements on the length, width, area, and fresh weight of P. giganteum leaves were collected. Specifically, 7 parameters including length, width, (length× width), (length – width), (length + width), (length)2, and (width)2 of the leaves were used to construct fresh weight estimation models using univariate linear regression, binary linear regression, and quadratic trinomial analyses.Result The correlations among the various measurements had coefficients ranging from 0.74 to 0.91. The estimation models with the highest R2 = 0.99 was on yA = 0.72xP, where yA = leaf area and xP = (length×width), and R2=0.96 on yF=0.02xP, where yF = fresh weight and xP = (length×width). The verification test on the regression equations between the estimated and actual leaf area showed R2 = 0.99 with an RMSE of 18.67 cm2 for leaf area and an RMSE of 0.67 g for fresh leaf weigh.Conclusion The models for estimating the area and fresh weight of P. giganteum leaves had high degree of validity in providing basic information for Juncao research.
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图 1 用于巨菌草叶面积测量的实例图片
注：A图代表叶片RGB图片；B图代表叶片8-bit；C图代表巨菌草叶面积获取区域
Figure 1. Sample photo for measuring leaf area of P. giganteum
Note: Fig. A: RGB picture of leaf blade; Fig. B: leaf blade 8-bit; Fig. C: acquisition area on leaf.
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图 2 巨菌草叶面积一元函数模型的构建
Figure 2. Construction of univariate function model for P. giganteum leaf area
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图 3 巨菌草叶面积二次三项式拟合图
Figure 3. Quadratic trinomial fitting diagram of P. giganteum leaf area
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图 5 巨菌草叶片鲜重线性模型
Figure 5. Linear model for estimating fresh weight of P. giganteum leaves
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图 6 巨菌草叶片鲜重二次三项式拟合
Figure 6. Quadratic trinomial fitting on estimating fresh weight of P. giganteum leaves
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图 7 巨菌草叶片鲜重拟合模型拟合度检验
Figure 7. Fitting of model for estimating fresh weight of P. giganteum leaves
表 1 巨菌草叶相关指标总体分布特征
Table 1 Overall distribution of related parameters on P. giganteum leaves
统计量 Statistics 指标 Indexes 叶片长度
Leaf length/cm叶片宽度
Leaf width/cm叶片鲜重
Leaf fresh weight/g叶面积
Leaf area/cm2均值 Mean 93.32 3.34 6.07 223.62 标准差 Standard deviation 21.61 1.00 2.86 110.47 标准误 Standard Error 1.96 0.09 0.26 10.04 均值的95%置信区间上限
Lower 95%CI of mean96.81 3.51 6.53 242.35 均值的95%置信区间下限
Upper 95%CI of Mean89.21 3.16 5.55 203.4 偏度 Skewness −0.99 0.54 0.18 0.46 峰度 Kurtosis 0.64 0.16 −0.55 −0.08 变异系数
Coefficient of variation0.23 0.30 0.47 0.49 平均绝对偏差
Mean absolute deviation−0.10 0.00 0.00 −0.49 最小值 Minimum 25 1 1 24 最大值 Maximum 130 6 12 511 
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表 2 巨菌草叶片相关参数的相关性（Pearson）分析
Table 2 Pearson analysis of related parameters on P. giganteum leaves
指标
Indexes叶片长度
Leaf length叶片宽度
Leaf width叶片鲜重
Leaf fresh weight叶面积
Leaf area叶片长度
Leaf length1 叶片宽度
Leaf width0.74** 1 叶片鲜重
Leaf fresh weight0.81** 0.90** 1 叶面积 Leaf area 0.83** 0.91** 0.91** 1 注：**在0.01水平上显著相关。
Note: ** significant correlation at 0.01 level.
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