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.

For pest control to be sustainable, the methods applied must be efficient and have a low environmental impact. Pest control failures bring economic and environmental problems. Phthorimaea absoluta is the main pest in tomato crops worldwide. Benzoylureas, diamides, and pyrethroids are among the insecticides with the highest reports of pest control failures, and Brazil is the country where this has been most observed. Machine learning models are suitable for predicting biological events. Thus, this study aimed to determine the risks of failures in the control of P. absoluta by insecticides in Brazilian biomes using the MaxEnt machine learning algorithm. The risks of pest control failures by benzoylureas and pyrethroids were higher in tomato crops located in the Cerrado and Atlantic Forest biomes, and annual precipitation was the critical variable associated with these failures. The risks of control failures by diamides were higher in crops located in the Caatinga, Cerrado, and Atlantic Forest, and temperature seasonality was the critical variable associated with these failures. In conclusion, the models determined in the study are robust to predict the regions with higher risks of P. absoluta control failures by insecticides, and they indicated the environmental variables associated with these risks.

Biological control is a growing branch in Brazil, and with it comes the need to obtain efficient enemies in the control of pests. The use of entomopathogens has expanded and with it comes the need to investigate their selectivity to non-target organisms. The present work was conducted in a pinecone (Annona squamosa L.) orchard with the objective of evaluating in which locations of the plant (lower, middle or upper third) and the effects of the entomopathogens: Beauveria bassiana, Metharhizium anisoplie and Bacillus thuringiensis on the predatory mite. Sixteen weekly applications were made between March and August 2017 with a constant pressure knapsack sprayer, nozzle type JA-2 with the jet directed at the entire plant. The treatments consisted of the use of three entomopathogenic biological products: Dipel, Beuaveria bassiana JCO and Metarhizium anisopliae JCO applied alone and in combination. Eight treatments were performed, as follows: T1-Spraying with M. anisopliae + phfos (Quimifol) + adhesive spreader (Agral), T2-Spraying with B. bassiana + phfos (Quimifol) + adhesive spreader (Agral), T3-Spraying with B. thruringiensis + phfos (Quimifol) + adhesive spreader (Agral), T4-Spraying with M. anisopliae + B. basisiana + phfos (Quimifol) + adhesive spreader (Agral), T5- Spraying with M. anisopliae + B. thruringiensis + phfos (Quimifol) + adhesive spreader (Agral), T6- Spraying with B. bassiana + B. thruringiensis + phfos (Quimifol) + adhesive spreader (Agral); T7- Spraying with M. anisopliae + B. bassiana + B. thruringiensis + phfos (Quimifol) + adhesive spreader (Agral) e T8-Testify, spraying with phfos (Quimifol) + adhesive spreader (Agral). The results indicate a preference of the Neoseiulus sp. mite for the middle third of the plant canopy. The results obtained indicated that the entomopathogens influenced the population of the Neoseiulus sp. mite until the sixth week after treatment, where the combination of Metarhizium anisopliae + Beauveria bassiana + Bacillus thuringiensis was the one that most negatively affected the population of the predatory mite Neoseiulus sp.