Abdominal contact of fluvalinate induces olfactory deficit in Apis mellifera.

τ-Fluvalinate (fluvalinate) is a highly selective pyrethroid insecticide compound used for controlling ectoparasitic mites that cause major damages in honey bee colonies. Although honey bees have resistance and low toxicity to this xenobiotic chemical, little is known about the effects of this chemical on sensory modulation and behaviors in honey bees. Here we addressed the effect on olfactory cognition at the behavioral, molecular, and neurophysiological levels. First, we found that topical application of fluvalinate to honeybee abdomen elicited somewhat severe toxicity to honey bees. Furthermore, honeybees treated with sublethal doses of fluvalinate showed a significant decrease in olfactory responses. At the molecular level, there was no change in gene expression levels of odorant receptor co-receptor (Orco), which is important for electrical conductivity induced by odorant binding in insects. Rather, small neuropeptide F (sNPF) signaling pathway was involved in olfactory fluctuation after treatment of fluvalinate. This indicates that olfactory deficits by abdominal contact of fluvalinate may stem from various internal molecular pathways in honey bees.

Odor descriptive ratings can predict some odor-color associations in different color features of hue or lightness.

Background: Olfactory information can be associated with color information. Researchers have investigated the role of descriptive ratings of odors on odor-color associations. Research into these associations should also focus on the differences in odor types. We aimed to identify the odor descriptive ratings that can predict odor-color corresponding formation, and predict features of the associated colors from the ratings taking into consideration the differences in the odor types. Methods: We assessed 13 types of odors and their associated colors in participants with a Japanese cultural background. The associated colors from odors in the CIE L*a*b* space were subjectively evaluated to prevent the priming effect from selecting color patches. We analyzed the data using Bayesian multilevel modeling, which included the random effects of each odor, for investigating the effect of descriptive ratings on associated colors. We investigated the effects of five descriptive ratings, namely Edibility, Arousal, Familiarity, Pleasantness, and Strength on the associated colors. Results: The Bayesian multilevel model indicated that the odor description of Edibility was related to the reddish hues of associated colors in three odors. Edibility was related to the yellow hues of colors in the remaining five odors. The Arousal description was related to the yellowish hues in two odors. The Strength of the tested odors was generally related to the color lightness. The present analysis could contribute in investigating the influence of the olfactory descriptive rating that anticipates the associated color for each odor.