Fipronil exposure compromises respiration and damages the Malpighian tubules of the stingless bee Partamona helleri Friese (Hymenoptera: Apidae).

Fipronil has been widely used in agriculture and forestry in Brazil to control several pests. However, this insecticide may be hazardous to non-target organisms, including stingless bees, which are essential pollinators of crops and natural environments. Here, we investigated the effect of 24-h acute oral exposure to LC50 of fipronil on the Malpighian tubules of the stingless bee Partamona helleri (Friese). Insecticide exposure decreases the respiration rate of forager bees, and the Malpighian tubules are severely affected, as shown by the epithelial architecture disorganization, loss of cytoplasmic content, degradation of the brush border, and nuclear pyknosis. In addition, fipronil ingestion increases the number of Malpighian cells positive for peroxidase, LC3, cleaved caspase-3, and JNK. However, Notch and ERK1/2-positive cells decrease in the exposed bees. These changes in the signaling proteins indicate an increase in oxidative stress, autophagy and apoptosis, and impairment of cell recovery. Overall, our results demonstrate the toxicological effects of fipronil on a stingless bee, which compromises the physiology of this important pollinator.

Lethal and sublethal effects of an emulsion based on Pogostemon cablin (Lamiaceae) essential oil on the coffee berry borer, Hypothenemus hampei.

The global search for eco-friendly and human-safe pesticides has intensified, and research on essential oils (EOs) has expanded due to their remarkable insecticidal activities and apparent human-safe. Despite this, most of the literature focuses on short-term and simplified efforts to understand lethal effects, with only a few comprehensive studies addressing sublethal exposures. To fill this shortcoming, we explore the lethal and sublethal effects of Pogostemon cablin (Lamiaceae) EO and an EO-based emulsion (18%) using the coffee berry borer Hypothenemus hampei Ferrari (Coleoptera: Curculionidae: Scolytinae) as a model. First, we determine the toxicity of EO and EO-based emulsion using dose-mortality curves and lethal times. Second, we subjected adult females of H. hampei to sublethal doses to assess whether they affected their behavior, reproductive output, and histological features. Our findings reveal that patchoulol (43.05%), α-Guaiene (16.06%), and α-Bulnesene (13.69%) were the main components of the EO. Furthermore, the EO and its emulsion had similar toxicity, with dose-mortality curves and lethal times overlapping 95% confidence intervals. We also observed that sublethal exposure of females of H. hampei reduces reproduction and feeding, increases walking activity, and causes histopathological changes in the midgut. This study advances the knowledge of the lethal and sublethal effects of an eco-friendly substance on insects.Responsible Editor: Giovanni Benelli.

Wet and warm conditions contribute to the occurrence of the neotropical butterfly Ascia monuste orseis Godart (Lepidoptera: Pieridae) on Brassica crops.

Ascia monuste orseis Godart (Lepidoptera: Pieridae) is a neotropical butterfly distributed in South America. During the larval stage, this insect causes economic losses on Brassica crops. Wet and warm conditions are known to increase subspecies occurrence, but it remains unclear why these conditions are more suitable. In this study, we have shown that both conditions are highly favourable for A. monuste orseis. We determined the thermal requirements for immature development and then created models for A. monuste orseis occurrence using Climex algorithm. Two models were built: one for the year-round presence and other for seasonal suitability. We validated the models using subspecies occurrence records and monitoring in two Brazilian regions (Northeast and Southeast). The minimum, optimum and maximum temperature for immature development were estimated at 16.37, 29.16 and 34.95 °C, respectively. The model for year-round presence indicated tropical areas as highly suitable for A. monuste orseis occurrence (with 88% of accuracy) and the seasonal models showed unsuitable areas in some parts of South America during cold and dry periods. Such predictions were observed in the monitored areas where A. monuste orseis was not found. These results can be associated with the mortality caused by low temperature to immature stages and drought conditions that may induce adult migration to moist habitats. Thus, we suggest that A. monuste orseis occurs mainly during wet and warm seasons on Brassica crops due to deleterious effects caused by cold and dry conditions. This information can be used to improve A. monuste orseis management in Brassica crops.

Machine Learning for Seed Quality Classification: An Advanced Approach Using Merger Data from FT-NIR Spectroscopy and X-ray Imaging.

Optical sensors combined with machine learning algorithms have led to significant advances in seed science. These advances have facilitated the development of robust approaches, providing decision-making support in the seed industry related to the marketing of seed lots. In this study, a novel approach for seed quality classification is presented. We developed classifier models using Fourier transform near-infrared (FT-NIR) spectroscopy and X-ray imaging techniques to predict seed germination and vigor. A forage grass (Urochloa brizantha) was used as a model species. FT-NIR spectroscopy data and radiographic images were obtained from individual seeds, and the models were created based on the following algorithms: linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), random forest (RF), naive Bayes (NB), and support vector machine with radial basis (SVM-r) kernel. In the germination prediction, the models individually reached an accuracy of 82% using FT-NIR data, and 90% using X-ray data. For seed vigor, the models achieved 61% and 68% accuracy using FT-NIR and X-ray data, respectively. Combining the FT-NIR and X-ray data, the performance of the classification model reached an accuracy of 85% to predict germination, and 62% for seed vigor. Overall, the models developed using both NIR spectra and X-ray imaging data in machine learning algorithms are efficient in quickly, non-destructively, and accurately identifying the capacity of seed to germinate. The use of X-ray data and the LDA algorithm showed great potential to be used as a viable alternative to assist in the quality classification of U. brizantha seeds.

Sub-lethal effects of essential oil of Lippia sidoides on drywood termite Cryptotermes brevis (Blattodea: Termitoidea).

The drywood termite Cryptotermes brevis (Walker, 1853) (Kalotermitidae) is one of the most important wood structural pest in the world. Substances from the secondary metabolism of plants (e.g., essential oils) have been considered an environmentally safer form of control for urban pests, such as termites. In the present study, we analyzed the lethal and sub-lethal effects of essential oil of Lippia sidoides and its major components on C. brevis pseudergates in two routes of exposure (contact and fumigation). The essential oil of L. sidoides and thymol were more toxic to C. brevis pseudergates when applied by contact (LD50 = 9.33 and 8.20µgmg-1, respectively) and by fumigation (LC50 = 9.10 and 23.6µLL-1, respectively). In general, treatments changed the individual and collective behaviors of C. brevis pseudergates, as well as the displacement and walking speed. The essential oil of L. sidoides and its major components showed a high potential to control C. brevis pseudergates, due to the bioactivity in the two routes of exposure and the sub-lethal effects on the behavior and walking, important activities for the cohesion of C. brevis colonies.