The invention discloses a whole
genome selection model for predicting the
nicotine content of tobacco and application thereof, and the whole
genome selection model for predicting the
nicotine contentof the tobacco is Bayes BNIC; in order that the prediction precision of the model on the phenotypic value of the
nicotine content of the tobacco is optimal, core parameter values such as the number (n1) of molecular markers of the candidate prediction model Bayes B, the scale (n2) of a training group, the ratio (n3) of the training group to a
test group and a
model prediction precision value (n4)are clearly stipulated. The application refers to the application of the whole
genome selection model Bayes BNIC to analyze the
genotype data of a tobacco group so as to predict the nicotine content of the tobacco group. The
tobacco nicotine content whole genome selection model Bayes BNIC provided by the invention can accurately predict the nicotine content value of each
plant in a tobacco group according to the
genotype of the tobacco group, so as to realize the cultivation of excellent tobacco varieties (lines) with different nicotine content levels in tobacco quality breeding.