Abstract
Measurements of chlorothalonil residue on tomato foliage are expensive and time consuming, yet knowledge of chlorothalonil persistence would assist in fungicide application scheduling. The objective of this study was to calibrate an existing chlorothalonil persistence model for processing tomatoes, and to incorporate the predictions of chlorothalonil residue into TOM-CAST. The Bruhn and Fry (1982b. A mathematical model of the spatial and temporal dynamics of chlorothalonil residues in a potato canopy. Phytopathology 72, 1306-1312) model for chlorothalonil persistence on potato foliage was calibrated for tomatoes using data from controlled rainfall experiments with a rainfall simulator. Field data consisting of chlorothalonil residue data and weather data from 1993 and 1995 field trials in Columbus, OH, was also used. Model evaluation was conducted using two data sets of chlorothalonil residue data and weather data from 1998 field trials in Columbus, OH. The chlorothalonil persistence predictions were within the 90% confidence interval of the observed chlorothalonil residues on upper canopy foliage for 11 of the 13 data points and nine of the 13 data points for the lower canopy foliage. The chlorothalonil persistence model and the TOM-CAST disease-forecasting algorithm were combined into an integrated fungicide application decision aid. The linked model predicted three spray applications were necessary compared to five predicted with the TOM-CAST-only program for the 1998 season in Columbus, OH. (C) 2000 Elsevier Science Ltd.
Original language | English |
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Pages (from-to) | 171-187 |
Number of pages | 17 |
Journal | Agricultural Systems |
Volume | 64 |
Issue number | 3 |
DOIs | |
State | Published - Jun 2000 |
Bibliographical note
Funding Information:This material is based upon work supported under a National Science Foundation Graduate Fellowship. This research was in part supported by the North Central Region Pesticide Impact Assessment Program (NCRPIAP), and the United States Department of Agriculture National Research Initiative Grant Program (USDA-NRI). The investigation reported in this paper (No. 99-05-138) is part of a project of the Kentucky Agricultural Experiment Station and is published with the approval of the director.
Funding
This material is based upon work supported under a National Science Foundation Graduate Fellowship. This research was in part supported by the North Central Region Pesticide Impact Assessment Program (NCRPIAP), and the United States Department of Agriculture National Research Initiative Grant Program (USDA-NRI). The investigation reported in this paper (No. 99-05-138) is part of a project of the Kentucky Agricultural Experiment Station and is published with the approval of the director.
Funders | Funder number |
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North Central Region Sustainable Research and Education | |
NRI/CSREES/USDA | |
United States Department of Agriculture CSREES National Research Initiative | |
National Science Foundation Arctic Social Science Program |
Keywords
- Chlorothalonil
- Computer decision aid
- Fungicide
- Persistence model
- Processing tomatoes
- TOM-CAST
ASJC Scopus subject areas
- Animal Science and Zoology
- Agronomy and Crop Science