基于机器视觉的稻茬麦单茎穗高通量表型分析

丁启朔,李海康,孙克润,何瑞银,汪小旵,刘富玺,厉翔

High-Throughput Phenotyping of Individual Wheat Stem and Ear Traits with Machine Vision

QiShuo DING,HaiKang LI,KeRun SUN,RuiYin HE,XiaoChan WANG,FuXi LIU,Xiang LI

表1 小麦单茎穗地上部生物量与单穗籽粒产量回归模型

Table 1 The regression model between aboveground biomass per stem-panicle and ear-derived grain yield of wheat

拟合模型 Fitting model 模型类型 Model type 模型方程 Model equation 单穗质量与单穗籽粒产量 Ear-derived weight and grain yield 线性Linear SEY=a0+a1×SEW 二次Quadratic SEY=a0+a1×SEW2 指数Exponential ln(SEY)=a0+a1×ln(SEW)2 地上部各器官生物量与单穗 籽粒产量 Biomass of different organs and ear-derived grain yield 线性Linear SEY=a0+a1×SLW+a2×SSW+a3×SEW 二次Quadratic SEY=a0+a1×SLW2+a2×SSW2+a3×SEW2 拓展Extended SEY=a0+a1×SLW2+a2×SSW2+a3×SEW2+a4×SLW×SSW+a5×SLW×SEW+a6×SSW×SEW 指数Exponential ln(SEY)=a0+a1×ln(SLW)2+a2×ln(SSW)2+a3×ln(SEW)2