The aim of the research, which was carried out in the years 2003-2005, was to assess the possibility of creating regression models for the earliness of Chinese cabbage (Brassica rapa var. chinensis, pak choy) plants cultivated under field conditions during the summer-autumn months. Four variables were chosen for developing the prediction model: the minimum, mean and maximum air temperatures and sunshine hours. After stepwise regression analysis, it was noted that crop earliness could be described as a function of mean air temperature and sunshine hours. For this model, the coefficient of determination R2 was equal to 0.962. Additional models based on various thermal indices - growing degree days (GDD), heliothermal units (HTU) and photothermal units (PTU) - were also constructed and taken into consideration. The linear regression equation that includes GDD could only simulate the earliness of the plants with a precision below 14%. The model built on the basis of PTU showed a better fit of the predicted data to the observed data (around 49%), while the last model, which incorporated HTU, was the most accurate (R2 was equal to 0.843). Models for the growth of pak choy plants in the field based on a time variable are also presented in this paper.
