Growth equations may be relatively general and describe plant dry mass accumulations based on data representing wide ranges of environment parameter values or they may be narrow and apply only to limited ranges. This paper proposes an empirical approach of the second type, a method to derive, by regression growth functions that can be readily implemented on control computers to improve (or attempt to optimize) growth within a narrow range of growing conditions. The method assumes plant vegetative growth may be predicted by two separable functions which combine by multiplication. One function is based on environmental conditions (air temperature, CO2 concentration, light integral and nutrient solution nitrate concentration, but not root zone temperature). The other function has two parameters, root zone temperature and time. Three data sets of hydroponic lettuce vegetative growth data are analyzed using the method. In each case, converting the original data to dimensionless form permitted the data to be expressed using a single, simple equation that described the original data relatively well.