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Weed Models for Integrated Pest Management of Lettuce

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Title:Weed Models for Integrated Pest Management of Lettuce
Authors:Sako, Glenn T.
Date Issued:1988
Abstract:Spanish needle {Bidens pilosa L.) and cheeseweed {Malva parviflora L.) are reservoir hosts of tomato spotted wilt virus (TSWV). Thrips are attracted to their flowers, and the larvae acquire the virus whiie feeding on them. Massive migrations of infected thrips from the reservoir hosts into the lettuce fields have resulted in severe crop losses. In an integrated pest management program, knowing the flowering patterns of Spanish needle and cheeseweed will aid in the prediction of thrips migrations and control the incidence of disease by TSWV. The objective of this study was to deveiop statistical models to predict the time to first flower (T50) and the time to the flower peak of these 2 weed species.
Spanish needle plants were observed from the 5-node stage for the opening of the first flower and until the flower peak occurred. Increasing temperature and rainfall shortened the T50 and the time to the flower peak. Weather data were used to develop models to predict T50 and peak flowering time. Growing degree days was included in the analysis using a base temperature of 5 °C. The model to predict T50 was T50 = -0.57(MAXT) - 0.31 (MINT) + 0.05(GDD) + 21.61 where T50 is the time to 50% of the plants flowered (days), MAXT is the average maximum air temperature (°C) from the 5-node stage to T50, MINT is the average minimum air temperature (°C) from the 5-node stage to T50, and GDD is the sum of growing degree days from the 5-node stage to T50. The coefficient of multiple determination (R2) was 0.99 ***. Validation of the model resulted in predicted values that were within 1 day for 2 of 3 locations. The model to predict peak flowering was WKS = -0.46(MAXT) - 0.32(EVAP) + 13.33 where WKS is the number of weeks from the 5-node stage to the flowering peak and EVAP is the summation of evaporation (cm) from the 5-node stage to peak flower. The R2 was 0.82 **. Validation of the model indicated that the model predicted peak flowering to within 1 week of the actual peak time.
Cheeseweed plants were observed from the 4-leaf stage for the opening of the first flower and until peak flower. Increasing temperature and rainfall shortened the T50 and time to peak flower. Weather data were used to develop models to predict T50 and peak flowering time. Growing degree days was included in the analysis using a base temperature of 6 °C. The model to predict T50 was T50 = 0.05(GDD) + 7.3 where T50 is the time to 50% of the plants flowered (days), and GDD is the sum of growing degree days from the 4-leaf stage to T50. The R2 was 0.86 ***. Validation of the model showed that it predicted T50 values that were within an average of 4 days from the actual values. The model to predict the time to the flower peak was WKS = -0.5(MAXT) + 0.007(GDD) + 15.6 where WKS is the number of weeks from the 4-leaf stage to the flowering peak, and MAXT is the average air maximum temperature (°C) from the 4-leaf stage to peak flower. The R2 was 0.96 ***. Validation of the model indicated that it predicted the observed peak flowering time. These models can be used to help time control measures to control thrips and TSWV.
URI:http://hdl.handle.net/10125/56208
Appears in Collections: M.S. - Horticulture


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