In order to establish sweetpotato whitefly, Bemisia tabaci, control in paprika greenhouses a fixed-precision-level sampling plan and binomial sampling plan were developed. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 co...
In order to establish sweetpotato whitefly, Bemisia tabaci, control in paprika greenhouses a fixed-precision-level sampling plan and binomial sampling plan were developed. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 consecutive weeks, using 19 sampling locations in GH 1 and 9 sampling locations in GH 2. The plant in both greenhouses were divided into top (180-220 cm from the ground), middle (80-120 cm from the ground) and bottom (30-70 cm from the ground) sections and B. tabaci adults and pupae were observed on three paprika leaves at each position and recorded separately. GH 2 data were used to validate the fixed-precision sampling plan and binomial sampling plan, which was developed using GH 1 data. The fixed-precision-level sampling plan consisted of spatial distribution analysis, a sampling stop line, and decision making. In this study, spatial distribution analysis was performed using Taylor’s power law with the pooled data of the top and bottom position (B. tabaci adults), and the middle and bottom positions (B. tabaci pupae), based on a 1-leaf sampling unit. Decision making was undertaken using the maximum of action threshold in accordance with previously published method, and the value was decided by the price of the plants. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated a reasonable level of precision.
Binomial sampling plans were developed based on the relationship between the mean density per leaf (m) and the proportion of leaf infested with less than T B. tabaci per leaf (PT), according to empirical model (). T was defined as tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaf in this study. Increasing sample size, regardless of tally threshold, had little effects on the precision of the binomial sampling plan. Increasing sample size had little effect on the precision of the estimated mean regardless of tally threshold. T=1 was chosen as the best tally threshold for estimating densities of B. tabaci adults based on the precision on the model and T=3 was best tally threshold in B. tabaci pupae. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated the suitable results.
In order to establish sweetpotato whitefly, Bemisia tabaci, control in paprika greenhouses a fixed-precision-level sampling plan and binomial sampling plan were developed. Sampling was conducted simultaneously in two independent greenhouses (GH 1, GH 2). GH 1 and 2 were surveyed every week for 22 consecutive weeks, using 19 sampling locations in GH 1 and 9 sampling locations in GH 2. The plant in both greenhouses were divided into top (180-220 cm from the ground), middle (80-120 cm from the ground) and bottom (30-70 cm from the ground) sections and B. tabaci adults and pupae were observed on three paprika leaves at each position and recorded separately. GH 2 data were used to validate the fixed-precision sampling plan and binomial sampling plan, which was developed using GH 1 data. The fixed-precision-level sampling plan consisted of spatial distribution analysis, a sampling stop line, and decision making. In this study, spatial distribution analysis was performed using Taylor’s power law with the pooled data of the top and bottom position (B. tabaci adults), and the middle and bottom positions (B. tabaci pupae), based on a 1-leaf sampling unit. Decision making was undertaken using the maximum of action threshold in accordance with previously published method, and the value was decided by the price of the plants. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated a reasonable level of precision.
Binomial sampling plans were developed based on the relationship between the mean density per leaf (m) and the proportion of leaf infested with less than T B. tabaci per leaf (PT), according to empirical model (). T was defined as tally threshold, and set to 1, 2, 3, 4, 5 (adults) and 1, 3, 5, 7 (pupae) per leaf in this study. Increasing sample size, regardless of tally threshold, had little effects on the precision of the binomial sampling plan. Increasing sample size had little effect on the precision of the estimated mean regardless of tally threshold. T=1 was chosen as the best tally threshold for estimating densities of B. tabaci adults based on the precision on the model and T=3 was best tally threshold in B. tabaci pupae. Using the results obtained in the greenhouse, simulated validation of the developed sampling plan by RVSP (Resampling Validation for Sampling Plan) indicated the suitable results.
주제어
#Paprika
#Bemisia tabaci
#Fixed precision level sampling plan stop line
#Control decision making
#Binomial sampling plan
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