Transect sampling to enhance efficiency of corn rootworm (Coleoptera: Chrysomelidae) monitoring in corn.
Crop monitoring for adult corn rootworms, Diabrotica virgifera virgifera LeConte and Diabrotica barberi Smith and Lawrence, remains the best means to assess fields at risk from this pest if replanted to corn, Zea mays (L.). Improvements in sampling methodology, including the development of a sequential sampling plan, have reduced the minimum sampling time required to make a management decision to 20 min or less per field per visit. However, many growers and crop consultants still find this time commitment a constraint to repeated scouting. A common currently used sampling method involves systematically covering most of the field following a "W" pattern. The feasibility of replacing the current sampling pattern with a simpler and less time-consuming transect (straight line) pattern was assessed. When sampling methods were compared, computer simulations demonstrated that treatment decisions based on transect sampling would have an acceptably low error rate averaging 10% over a range of realistic corn rootworm densities (0-2 adults per plant). This error rate represented a decrease in accuracy of <1% compared with systematic sampling. Field trials using transect, systematic, and random sampling in each field were used to compare the categorization of adult corn rootworm densities into "above" or "below" threshold with a sequential sampling plan. Efficiency measured in time to reach a decision, number of corn plants evaluated, and time divided by plants observed were compared between sampling methods. The three methods did not differ significantly in the number of plants evaluated or in the categorization of corn rootworm populations. Transect sampling resulted in a significantly shorter time divided by plants observed (38 s), than either systematic (78 s), or random sampling methods (166 s). Based on these results transect sampling reduces sampling time 51% compared with systematic sampling and thus could be used to reduce total sampling times substantially.
Losey
John E
JE
Department of Entomology, Cornell University, Ithaca, NY 14853, USA.
Allee
Leslie L
LL
Zbarsky
Vladimir
V
Waldron
J Keith
JK
Shields
Elson J
EJ
D000383:Agriculture / Q000379:methods; D000818:Animals; D001517:Coleoptera; D003198:Computer Simulation; D010935:Plant Diseases; D011156:Population Density; D003313:Zea mays