Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: June 19, 2001
Publication Date: N/A
Technical Abstract: South Texas vegetable producers have requested assistance in developing methodologies to predict harvest dates for commercially grown muskmelon (cantaloupe). Harvest times play a major role in determining produce prices at the marketplace. They also determine how commercial growers schedule labor for harvest and arrange transportation of the produce to market. Harvest date predictions based on chronological time often fail, due to unseasonable weather. Our goal was to construct a simple muskmelon phenology model which could be run with easily obtainable weather station data and used by growers to quantify phenological development and aid in projecting harvest dates. The model quantifies vegetative development in terms of main vine node numbers which allows the model to simulate either a direct seeded or a transplanted crop. The model operates on an hourly time-step but requires only daily weather data and a few cultivar specific parameters. The model was tested against independent data sets and was able to predict main vine node numbers within one to two nodes of observed values, with an average model accuracy of one to three days in harvest date prediction. The model is currently being evaluated as a crop management decision-aid by commercial growers in Texas and seed company plant breeders in Florida.