番薯叶片性状关系模型的建立与验证

Establishment and Validation of the Model of Ipomoea batatas Leaf Traits

建立植物叶片生长预测模型是林学、生态学和植物学的热点与难点。以番薯(Ipomoea batatas)叶为研究对象,利用易测的叶长(L)、叶宽(W)和叶绿素含量(S)及其不同的组合作为模型拟合参数,建立了10个关于叶面积(LA)、叶饱和鲜重(SFW)和叶干重(DW)的预测模型,选择拟合度最好的3个模型作为LA、SFW和DW的预测模型,这3个模型分别为:LA=–22.995+5.322W+0.322L2(R=0.972)、SFW=0.459+0.000 034 1LWS(R=0.964)和DW=–0.064+0.016W+0.000 048 4LS(R=0.955);并用实测值对模型进行了验证。结果表明,LA、SFW和DW的预测值与实测值均高度一致(R2>0.9,P<0.001),故可用于对实际未知叶片LA、SFW和DW的预测。该研究可为简化植物性状测定提供参考。

The establishment of a leaf growth prediction model in forestry, ecology and botany has been the focus of attention and difficulty. We measured leaf length, leaf width, SPAD （S） value of Ipomoea batatas and used their combination to develop 10 regression models to predict individual leaf area （LA）, saturated fresh weight （SFW）, and dry weight （DIN） of I. batatas. We selected the best-fit model as a predictive model for LA, SFW and DW. Three models were LA=-22.995＋5.322W＋0.322L2 （R=0.972）, SFW=0.459＋0.000 034 1LWS （LWS： Leaf lengthxLeaf widthxSPAD）（R= 0.964）, and DW=-0.064＋0.016W＋0.000 048 4LS （LS： Leaf lengthxSPAD）（R=-O.955）. We validated the best prediction models with the measured value. The predicted and measured values were highly consistent （R2〉0.9, P〈0.001）. The models could be used to predict LA, SEW and DW of actual unknown leaves. We therefore provide model for simplifying the determination of plant leaf traits.