Development of Binomial Sequential Sampling Plans for Sugarcane Aphid (Hemiptera: Aphididae) in Commercial Grain Sorghum
| Autor: | Nicholas J Seiter, Norman C. Elliott, Jessica C Lindenmayer, Kristopher L. Giles, Tom A. Royer, Michael J. Brewer, Robert D. Bowling, Sebe A Brown, Allen E. Knutson, Angus L. Catchot, Brian P. McCornack |
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| Rok vydání: | 2020 |
| Předmět: |
0106 biological sciences
01 natural sciences Mississippi Statistics Animals Sorghum Aphid Arkansas Ecology biology Melanaphis sacchari Economic threshold Sampling (statistics) Oklahoma Aphididae Regression analysis General Medicine Kansas Louisiana biology.organism_classification Texas 010602 entomology Aphids Insect Science PEST analysis 010606 plant biology & botany |
| Zdroj: | Journal of Economic Entomology. 113:1990-1998 |
| ISSN: | 1938-291X 0022-0493 |
| Popis: | The sugarcane aphid (Melanaphis sacchari Zehntner) is a significant economic pest of grain sorghum (Sorghum bicolor (L.) Moench) in the Southern United States. Current nominal and research-based economic thresholds are based on estimates of mean aphids per leaf. Because enumerating aphids per leaf is potentially time consuming, binomial sequential sampling plans for M. sacchari were developed that allow users to quickly classify the economic status of field populations and determine when an economic threshold has been exceeded. During 2016 and 2017, counts of M. sacchari were recorded from 281 sampling events in 140 sorghum fields located in six states (Oklahoma, Kansas, Texas, Arkansas, Louisiana, Mississippi) . Regression analysis was used to describe the relationships between the mean M. sacchari density per two-leaf sample and proportion of plants infested with one or more aphids. Tally thresholds of T50 and T100 aphids per two-leaf sample were selected based on goodness of fit and practicality. Stop lines for both tally thresholds were developed for selected economic thresholds using Wald’s sequential probability ratio test. Model validations using an additional 48 fields demonstrated that reliable classification decisions could be made with an average of 11 samples regardless of location. This sampling system, when adopted, can allow users to easily and rapidly determine when M. sacchari infestations need to be treated. |
| Databáze: | OpenAIRE |
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