Economic thresholds of Thrips palmi (Thysanoptera: Thripidae) for eggplants in a greenhouse
Thrips palmi Karny has recently been implicated in damage to eggplant fruits. This thrips causes cosmetic scars on and deforms fruits, thus lowering their market value. To investigate the relationship between the density of thrips and the resulting damage, experimental plots with initial release densities of 0, 20, 40, 70, and 100 adults thrips per plot were established under greenhouse conditions. Thrips density (for flower sampling = x1; for sticky trap = x2) was monitored using flower sampling and blue sticky trap counts, and was found to be directly related to the proportion of damaged-fruits (y) and the reduction in fruit yield: significant relationships were found for the flower samples (y = 1.2261x1 − 0.6232, r2 = 0.8582) and for the trap catches (y = 11.667 ln(x2) − 9.5, r2 = 0.8896). The proportion of damaged fruits that could be tolerated from an economic perspective, based on the cost of controlling the thrips population chemically and the market value of the fruit, was 6.67–11.76 %; this translated into economic thresholds of 1.05–1.5 adults and/or larvae of T. palmi per flower or 4.91–10.17 adults T. palmi per four-day sticky card count.
Economic Injury Levels and Sequential Sampling Plans for Mexican Bean Beetle (Coleoptera: Coccinellidae) on Dry Beans
Field studies were conducted during the growing seasons of 1995 and 1996, in Scottsbluff, Nebraska, to determine yield-loss relationships for Mexican bean beetle (Epilachna varivestis Mulsant) on dry bean (Phaseolus vulgaris L.). Results of those experiments were combined with data from other studies previously conducted to develop economic injury levels (EILs), economic thresholds (ETs), and a sequential sampling program for Mexican bean beetle. Yield loss was regressed against larvae/row-m, and the slope of the linear regression (113 kg/ha per larvae/row-m) was used as theDI (yield loss/insect density) variable in EIL calculations. The EILs calculated in larvae/row-m were converted to egg masses/row-m and adjusted to reßect average survivorship to the adult stage. An example EIL for esfenvalerate at 0.509 (formulation) liter/ha (0.0453 gal/a) and crop value of $0.44/kg ($20/100 lbs) was 17.78 larvae/row-m. The corresponding ET is 1.04 egg masses/row-m, which reßects an average of 54.6 eggs/egg mass and 33% survival rate from egg to injurious stages. Sequential sampling plans were calculated based on a negative binomial distribution using parameter k estimated from previous research. Because sampling is based on egg masses, growers can make management decisions and take management actions before signiÞcant injury occurs. Also, ETs can be adjusted to include the occurrence of natural mortality in the egg and early instars. Analyses demonstrated that relatively minor variation in ETs has substantial impact on sequential sampling plans, includingparameters suchas average samplenumber.An interactive spreadsheetwasdeveloped that allows users to input economic and other data speciÞc to their situation to calculateMexican bean beetle EILs, ETs, and sequential sampling plans.
Spatial distribution of root lesion nematodes (Pratylenchus spp.) in a long-term no-till cropping system and their relationship with soil and landscape properties
The Cook Agronomy Farm of Washington State University is a long-term precision agriculture study site. Since 2000, the farm has been in various three-year no-till rotations with winter wheat, spring wheat, and various rotation crops such as barley, canola, peas, lentils, and chickpea. The spatial distribution of root lesion nematodes (Pratylenchus spp.) and their relationships with soil and terrain variables were studied by collecting soil samples at 127 and 124 geo-referenced points in two 12-ha fields during the spring of 2010 and 2011, respectively. Pratylenchus spp. were detected in more than 85% of the sampled locations in both fields. Nematode densities spatially mapped using ArcGIS software occurred in an aggregated pattern. Previous rotation crops had no effect on the spatial distribution. Classification and regression tree analysis (CART) using soil and terrain variables, and nematode density, explained 61 and 34% of the variability associated with nematode density in 2010 and 2011, respectively. Soil edaphic factors, such as organic matter, were stronger predictors of nematode populations than rotation effects.