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Recent work on complex odour processing in the moth Manduca sexta reports strikingly similar results [19], [20].
This study investigates learning of complex odour mixtures in honeybees using a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm.
Different mosquito sampling techniques are in use such as human landing catch which is highly facing ethical barriers, complex odour baited traps which needs trained staffs and CDC light traps which needs recharged power system to operate for long ; however most of them have a limited use thus new techniques are needed to complement or replace the existing ones.
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The honeybee has to detect, process and learn numerous complex odours from her natural environment on a daily basis.
Whether a bee generalizes or discriminates between complex odours would of course also depend on the concentration of the odorants in the mixtures, which was not tested here.
We have therefore interpreted our results in line with previous studies, which described the same phenomenon and where the authors came to the conclusion that bees learn "key components" from complex odours [5], [6], [12], [13], [14].
Here, we present a detailed behavioural study on learning of complex odours, using an exquisite olfactory model organism, the honeybee, and a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm.
By contrast, the much more complex social odours of mammals provide a broad range of information about the individual owner and stimulate individual-specific responses that are modulated by learning.
However, the more complex individual-specific odours of mammals, combined with variable responses to scents that often depend on context and learning, have led many to suggest that mammalian scent signals generally do not trigger the specific inherent responses required to fulfil the classical definition of pheromones [ 2, 4, 5].
However, the small number of neurons in the nematode's nervous system cannot support complex combinatorial coding of odours.
A computational fluid dynamics (CFD) model was developed to predict livestock odour dispersion over complex terrain.
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