Planting and first harvest dates of tomato (Lycopersicon esculentum Mill.) from 2 seasons in 3 years at eight locations in Georgia, North Carolina and South Carolina formed 38 environments which were used to determine the most reliable method to predict first harvest date of tomato based on daily maximum and minimum air temperature. Eleven methods of calculating heat units were chosen for comparison based on their performance as described in the literature. The most reliable method was defined as the one with the smallest coefficient of variation (CV). CVs were calculated for each method over both seasons and locations, for each season over all locations, each location over all seasons, and for each season at each location. All heat unit summation methods had smaller coefficients of variation (CV) than the standard method of counting days from planting to first harvest. Heat unit summation methods improved harvest date prediction accuracy compared with the counting day method for tomatoes in the South Atlantic Coast (SAC) region. Prediction using location/season specific models were less variable than the models over all seasons and locations. Incorporating daylength improved model prediction accuracy when applied over all locations and seasons, all locations by season, and all seasons by location. Based on the results of this study, the heat unit summation technique recommended for this region (where the location and season specific models are not available) is the reduced ceiling method multiplied by daylength.
All Science Journal Classification (ASJC) codes
- Global and Planetary Change
- Agronomy and Crop Science
- Atmospheric Science