Abstract
The pistachio psylla, Agonoscena pistaciae Burckhardt & Lauterer (Hemiptera: Psyllidae), is a major pest of pistachio trees throughout the pistachio producing regions in Iran. The effect of temperature on the developmental rates of eggs and nymphs of A. pistaciae was determined at different constant temperatures, i.e. 15, 20, 25, 30, 32.5 and 35 ± 0.5°C. The relationships between temperature and developmental rates were described by linear and the non-linear Lactin models. These models were evaluated based on R2, RSS, AIC and R2adj. The estimated value of the lower temperature threshold for egg, nymph and egg to adult development based on the linear model was 8.06, 10.38 and 9.97°C, respectively, and based on the Lactin model was 8, 11.55 and 11.2°C, respectively. Thermal constants estimated using the linear model, were 88.5, 243.90 and 333.33 DD, respectively, for egg, nymph and egg to adult development. These results indicate that the linear model gives a better description of the relationship between developmental rate and temperature for A. pistaciae than the non-linear model. These results could be incorporated into forecasting models used in the integrated pest management of this pest.
Highlights
Pistachio, Pistacia vera L., is one of the most important horticultural products in Iran
Temperature is an important factor influencing the dynamics of arthropod pests and their natural enemies (Pedigo, 2002; Gullan & Cranston, 2005)
The lower temperature threshold for egg development predicted by the Lactin model is 8°C, which is similar to the value predicted by the linear model (8.06°C)
Summary
Pistacia vera L., is one of the most important horticultural products in Iran. The pistachio psyllid, Agonoscena pistaciae Burckhardt & Lauterer (Hemiptera: Psyllidae), is a major pest of pistachio trees in all the areas of Iran where this plant is grown This pest sucks sap from the leaves, which damages the plant and reduces yield. The lack of linearity in the developmental rate at low and high temperatures indicates that this model is unlikely to provide accurate predictions of the temperature thresholds. This has led to the development of several non-linear phenological models for use in integrated pest management programs (Wagner et al, 1984; Worner, 1992). Whereas linear regression is often used in empirical models, non-linear regressions are used when there are reasons for believing that the relationships between the response and the predictor has a particular functional form (Smyth, 2002)
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