Insecticidal activities of garlic substances against adults of grain moth, Sitotroga cerealella （Lepidoptera： Gelechiidae）

The angoumois grain moth, Sitotroga cerealella （Olivier）, is one of the most serious stored grain pests around the world. In attempts to reduce the losses caused by the moth and to suppress its populations, the fumigant activities, behavioral influence and ovipositional inhibition of garlic （Allium sativum） essential oil and its two major components, diallyl disulfide and diallyl trisulfide, were investigated against the adult grain moth. Their effects on reduction in survival of first instar larvae to adult emergence were also evaluated. Results showed that these three materials （garlic essential oil, diallyl disulfide and diallyl trisulfide） had significant fumigant activity with 50% lethal concentration values at 1.33, 0.99, and 1.02/zL/L air space, respectively; meanwhile, the three materials possessed high behavioral deterrent activities against adults in the Y-tube olfactometer. When applied to rice grains, these materials reduced adult longevity and inhibited oviposition, with ovipositional inhibition above 70% at a concentration of 1.5uL/25 g in either no-choice or two-choice tests. In short, the study showed that both diallyl disulfide and diallyl trisulfide, like garlic essential oil, acted as fitrnigants, produced behavioral deter- rence and inhibited oviposition against angoumois grain moth. Our work here indicates that diallyl disulfide and diallyl trisulfide may serve as potential alternatives for grain protectants since both of them can be prepared easily from readily available chemicals.

A Non-Intrusive Reduced Basis EKI for Time Fractional Diffusion Inverse Problems

In this study,we consider an ensemble Kalman inversion(EKI)for the numerical solution of time fractional diffusion inverse problems(TFDIPs).Computational challenges in the EKI arise from the need for repeated evaluations of the forward model.We address this challenge by introducing a non-intrusive reduced basis(RB)method for constructing surrogate models to reduce computational cost.In this method,a reduced basis is extracted from a set of full-order snapshots by the proper orthogonal decomposition(POD),and a doubly stochastic radial basis function(DSRBF)is used to learn the projection coefficients.The DSRBF is carried out in the offline stage with a stochastic leave-one-out cross-validation algorithm to select the shape parameter,and the outputs for new parameter values can be obtained rapidly during the online stage.Due to the complete decoupling of the offline and online stages,the proposed non-intrusive RB method–referred to as POD-DSRBF–provides a powerful tool to accelerate the EKI approach for TFDIPs.We demonstrate the practical performance of the proposed strategies through two nonlinear time-fractional diffusion inverse problems.The numerical results indicate that the new algorithm can achieve significant computational gains without sacrificing accuracy.