Leucoptera coffeella (Lepidoptera: Lyonetiidae) is one of the main pests in coffee crops. The economic injury level (EIL) is the lowest density of the pest at which economic damages match the costs of control measures. The economic threshold (ET) is the density of the pest at which control measures must be taken so that this population does not reach the EIL. These are the main indices used for pest control decision-making. Control of L. coffeella is carried out by manual, tractor, airplane or drone applications. This work aimed to determine EILs and ETs for L. coffeella as a function of insecticide application technology in conventional and organic Coffea arabica crops. Data were collected over five years in commercial C. arabica crops on seven 100 ha central pivots. The cost of control in organic crops was 16.98% higher than conventional. The decreasing order of control cost was manual > drone > airplane > tractor application. Coffee plants were tolerant to low densities (up to 15% mined leaves) of the pest that caused losses of up to 6.56%. At high pest densities (54.20% mined leaves), losses were high (85.62%). In organic and conventional crops and with the use of different insecticide application technologies, EIL and ET were similar. The EIL and ET were 14% and 11% of mined leaves, respectively. Therefore, these indices can be incorporated in integrated pest management programs in C. arabica crops. The indices determined as a function of insecticide application technology in organic and conventional coffee are important as they serve producers with different technological levels. Additionally, EILs and ETs can contribute to more sustainable production, as control methods will only be employed when the pest density reaches these indices.

Blaptostethus pallescens Poppius is an important predator of vegetable pests in tropical regions. The correct identification of the stages of the life cycle of predatory species is crucial, since different stages may present different rates of pest consumption. Artificial neural networks (ANNs) are computational tools with a structure based on the human brain. With applications in several fields, ANNs have been applied in pest management for identification of pest species, spatial distribution modeling, and insect forecasting. The objective of this study was to apply ANNs as a method for the instar determination of B. pallescens using three morphometric measures (head width, body width, and body length). Cluster analysis was performed to categorize the insects in instars according to the morphometric variables. Subsequently, the ANNs were trained for instar determination using the morphometric measures as input variables. The ANNs tested (with 2, 4, 6, 8, 10, and 12 hidden neurons) provided proper data fitting (R2 > 98%). However, due to the parsimony principle, the network with hidden layer size 6 was selected. This study shows the successful application of ANNs in the instar determination of B. pallescens, which would not be possible using classical methods.

We evaluated the efficacy and residual toxicity of nine commercial insecticides on Plutella xylostella and their selectivity to the predator ant Solenopsis saevissima under laboratory and field conditions. First, to test the insecticides’ effectiveness and selectivity, we conducted concentration-response bioassays on both species and the mortalities were recorded 48 h after exposure. Next, rapeseed plants were sprayed following label rate recommendations in the field. Finally, insecticide-treated leaves were removed from the field up to 20 days after application and both organisms were exposed to them as in the first experiment. Our concentration-response bioassay indicated that seven insecticides caused mortality ≥80% of P. xylostella: bifenthrin, chlorfenapyr, chlorantraniliprole, cyantraniliprole, indoxacarb, spinetoram, and spinosad. However, only chlorantraniliprole and cyantraniliprole caused mortality ≤30% of S. saevissima. The residual bioassay indicated that four insecticides had a long-lasting effect, causing mortality of 100% to P. xylostella 20 days after application: chlorantraniliprole, cyantraniliprole, spinetoram, and spinosad. For S. saevissima, bifenthrin caused mortality of 100% during the evaluated period. Additionally, mortality rates below 30% occurred four days after the application of spinetoram and spinosad. Thus, chlorantraniliprole and cyantraniliprole are safe options for P. xylostella management since their efficacy favor S. saevissima.