Date of Award
Summer 2004
Document Type
Thesis - Restricted
Degree Name
Master of Science (MS)
Department
Electrical and Computer Engineering
First Advisor
Brown, Ronald H.
Second Advisor
Merrill, Stephen J.
Third Advisor
Corliss, George F.
Abstract
We developed a daily forecasting model for processing tomato harvest tonnage deliveries in California. This thesis introduces an initial daily forecasting model of daily processing tomato harvest tonnages. The effects of weather on the processing tomato harvest are examined. This model is based on first principle research and is capable of generating a daily forecast for the remainder of the harvest season. As actual harvest tonnage data becomes available, a system of mid-harvest forecast adjustments is applied for the purpose of reducing short term error. This agricultural forecasting model could be used as an input to a natural gas forecasting system. Some natural gas is used for agricultural processes related to crop harvest, such as the processing of tomatoes. More accurate prediction of natural gas demand for agricultural purposes can produce cost savings for natural gas utilities. This model could also be used in the commodity trading industry as harvest tonnage forecasts may provide information useful in futures market trading.
Recommended Citation
Marx, Brian, "Forecasting Daily Processing Tomato Harvest Tonnage in California" (2004). Master's Theses (1922-2009) Access restricted to Marquette Campus. 4758.
https://epublications.marquette.edu/theses/4758