Improving a Tomato Growth Model to Predict Fresh Weight and Size of Individual Fruits

Abstract

A new version of the CROPGRO-Tomato model was developed to include a subroutine for predicting dry matter concentration, fresh weight and size of fruits over time. This subroutine builds on already existing crop model predictions of dry mass per fruit and fruit thermal age. The model was calibrated with field data obtained on tomato cultivar ‘Florida 47’ in Gainesville Florida during spring 2007 and evaluated with an independent data set obtained during spring 2006. The dynamics of dry weight accumulation, fresh weight, dry matter concentration, and fruit size were simulated by the model and compared with independent data of fruits tagged at anthesis in the field study at three successive weekly dates. These results demonstrated that the model was able to explain and predict the time-series growth and development of individual fruits on a cohort basis, to include delayed growth, slower growth, and smaller size of progressively later-set fruits. Overall, the standard deviation of model error was less than 20 percent of the mean for all the variables evaluated (dry weight, fresh weight, fruit dry matter concentration, and fruit size). In addition, the Willmot index was always above 0.9. The effects of water and N stress on the growth of individual fruits were studied by withholding drip irrigation for three periods and withholding N supply beginning at 14 days after transplanting. The main effects of water stress on the growth of individual fruits were reduced fresh mass and size and an increase in dry matter concentration, while N stress on the other hand, caused a decrease in dry matter concentration of fruits. The existing water and N stress factors in the CROPGRO model were linked to the new equations that affect dry weight growth and dry matter concentration of individual fruits, and were successfully used to predict the stress-induced variations in dry matter concentration, and reductions in dry and fresh weight growth and size of single fruits. The newly-added subroutine for predicting dry matter concentration, fruit fresh weight, and size, along with coupling to water and N stresses make the improved model a valuable risk assessment tool for predicting fresh market production and quality of tomato.