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Wednesday, January 7, 2009: 3:40 PM
Salon I (Marriott Rivercenter Hotel)
A physiologically based model has been developed for use in addressing crop and pest management decisions in processing cotton (COTTAMIN Model) .
Field studies conducted during 2004-2006 cotton growing seasons in Fayum Governorate, to detect the adult population of the pink bollworm, Pectinophora gossypiella, cotton leaf worm, Spodoptera littoralis, cotton aphis, Aphis gossypii, white fly, Bemisia Tabaci and red mite, Tetranychus Urticae. Field generation numbers, life table parameters for field, thermal requirements and heat unit's accumulation was used. Cotton plant phonology was recorded as well as weather factors. The relationships in cotton complex were detected.
The interaction of pest (5 pests), plant (phenology) and weather (four Factors) were tested in COTTAMIN Model, on two cotton varieties (Giza83 and Giza 90) .
A comparison was made between the expected and observed data. Most of the validations produced results that were in reasonable agreement with the observed data. The forecasts were more accurate, when the phenology of the population peaks was compared than when actual population densities were compared.
In general, no computer model can make perfect forecasts, however, we can use COTTAMIN Model successfully to help to take the decisions in cotton fields.
Field studies conducted during 2004-2006 cotton growing seasons in Fayum Governorate, to detect the adult population of the pink bollworm, Pectinophora gossypiella, cotton leaf worm, Spodoptera littoralis, cotton aphis, Aphis gossypii, white fly, Bemisia Tabaci and red mite, Tetranychus Urticae. Field generation numbers, life table parameters for field, thermal requirements and heat unit's accumulation was used. Cotton plant phonology was recorded as well as weather factors. The relationships in cotton complex were detected.
The interaction of pest (5 pests), plant (phenology) and weather (four Factors) were tested in COTTAMIN Model, on two cotton varieties (Giza83 and Giza 90) .
A comparison was made between the expected and observed data. Most of the validations produced results that were in reasonable agreement with the observed data. The forecasts were more accurate, when the phenology of the population peaks was compared than when actual population densities were compared.
In general, no computer model can make perfect forecasts, however, we can use COTTAMIN Model successfully to help to take the decisions in cotton fields.