枣树叶面积估算模型构建

Establishment of leaf area estimation model for jujube trees

【目的】构建并评估多个枣树叶面积估算模型,筛选出适宜的枣树叶面积无损测量模型。【方法】以叶片形态差异显著的8个枣树品种为试材,通过数字扫描仪获取叶片长度(LL)、宽度(LW)、叶面积(LA)等形态参数,基于决定系数(R^2)、均方根误差(RMSE)、AIC(Akaike Information Criterion,赤池信息量准则,)对建立的17个线性及非线性叶面积模型进行筛选及适宜性评价。【结果】共获得3287枚叶片形态参数,各叶片形态参数间差异显著,尤其LA变异系数最大,达64.44%。以LL和LW复合变量为自变量的线性模型5 LA=a(LL×LW)、模型6 LA=a(LL+LW)^2,模型9 LA=a LL^2+b LW^2和非线性模型17 LA=(LL×LW)^b的精度可满足各个品种叶面积的估算,但需要根据品种拟合模型系数。基于全部数据的总体模型5和6的精度可用于各个枣品种叶面积估算,模型系数分别为0.7035和0.1646,确定系数分别为99.40%和98.84%,RMSE分别为0.46 cm^2和0.64 cm^2,两模型参数的准确估计需要的样本数量应大于250。【结论】筛选出的枣树单叶面积模型精度可满足供试各品种叶片面积估算的要求,无需针对单个品种独立建模。

【Objective】The study aims to establish a reliable and accurate leaf area(LA)estimation model based on leaf length(LL)and leaf width(LW)which can be measured non-destructively.Leaf area is usually determined by destructive methods,which are time-consuming and impossible to make successive measurements on the same leaf samples.Non-destructive portable leaf area laser scanners are expensive and complex.The model-based leaf area estimation overcomes the above defects.However,the optimal model needs to be selected from candidate models for jujube trees.【Methods】Eight jujube cultivars with significant differences in leaf morphology,including‘Junzao’‘Lizao’‘Qiyuexian’‘Suanzao’‘Zanhuangdazao’‘Fengmiguan’‘Gagazao’and‘Jinsixiaozao’,were used as the materials.Leaves were sampled and then scanned with a laser scanner to obtain digital images.Leaf morphological parameters,such as LL,LW,LA and petiole length(PL),were extracted using ImageJ software.There were 17 candidate models established and compared.Each model was established and validated using pooled data from all cultivars and separately for each cultivar.A further validation was conducted for the general models constructed with pooled data to evaluated their applicability to different individual cultivars.The root mean square error(RMSE),determination coefficient(R2)and Akaike information criterion(AIC)were used to evaluate the accuracy of the established models for leaf area through the comparisons between predicted values and actually measured values of leaf area.Each dataset was separated randomly into training dataset(75% of the data)and testing dataset(25% of the data)to fit and validate models by using R software.【Results】3287 leaves were sampled and significant differences were found among the cultivars in LL,LW,LA,PL,LL/LW ratio,PL/(PL+LL)ratio and roundness.The coefficient of variation(CV)in leaf area(LA)was the largest(64.44%),and followed by PL(43.41%),LW(37.24%)and LL(32.20%).LL,LW and their integrated variables,such as LL+LW,LL×LW,LL^2 and LW^2 etc.,could be used as the independent variables to predict the LA for all cultivars.By using all data together,the 17 models showed varied predictivity(71.66≤R^2≤99.52%,0.51≤RMSE≤3.09 cm^2 and 3769.08≤AIC≤16947.72).Among those models,model 16 LA=a(LL×LW)b had the highest accuracy(R^2=99.52%,RMSE=0.44 cm^2,AIC=3769.08),followed in descending order by model 5 LA=a(LL×LW)(R^2=99.40%,RMSE=0.46 cm^2,AIC=4076.65),model 9 LA=a LL^2+b LW^2(R^2=99.34%,RMSE=0.51 cm^2,AIC=4487.99),model 14 LA=a(LL+LW)b(R^2=98.87%,RMSE=0.65 cm^2,AIC=6469.08),model 6 LA=a(LL+LW)^2(R^2=98.84%,RMSE=0.64 cm^2,AIC=6563.66),and model 17 LA=(LL×LW)b(R^2=98.72%,RMSE=0.70 cm^2,AIC=6627.65).Estimation with all the models for each cultivar showed that models 5,6,9 and 17 met the requirements of accuracy to predict the leaf area for all the cultivars.The coefficient of models 5,6 and 17,had smallest CV among cultivars(2.71%,2.91% and 3.41%,respectively)as compared to the other models.When the all-data models were validated by individual cultivars,models 5 and 6 still had a high accuracy of leaf area estimation,with the lowest R^2 appearing in‘Suanzao’in model 6,which was 96.80%,and the largest decrease in RMSE appearing in‘Lizao’in the same model,which was 0.1451 cm^2.Yet,when compared the R^2 between cultivar specified and all-data based model 17,the R^2 in cultivar specified model 17 for‘Suanzao’and‘Jinsixiaozao’decreased from 97.27% and 94.22% to 84.16% and 83.51% in alldata model,respectively.The model coefficients for model 5 and 6 were 0.7035 and 0.1646,respectively.LA was estimated with a higher accuracy by employing LW alone compared to LL alone,irrespective of cultivars.LA estimation was not always improved by employing both LL and LW as compared to employing single variable.LA can be estimated by employing LW alone with model LA=a LWb,but the model coefficients need to be ajusted acccording cultivar.The minimum number of leaves was 250 to estimate the model coefficients for models 5 and 6 with relative lower errors.【Conclusion】For a specific cultivar,models 5,6,9 and 17 can meet the requirements of accuracy to predict the leaf area without the use of any expensive instruments but need to be fitted to obtain specific model coefficients for individual cultivars.Among the above 4 models,models 5 and 6 can be used to estimate leaf area accurately using the same model coefficients,irrespective of cultivar.The minimum sample size of 250 is required for models 5 and 6 to obtain reliable model coefficients.The accuracy leaf area model will be helpful to develop three-dimensional virtual jujube trees with accurate leaf dimensions.