Nocturnal insects largely rely on their sense of smell to locate food sources and oviposition sites. However, preferred nectar sources or suitable host plants are often rare, and odors emitted by these essential plants are mixed with bouquets released by neighboring plants (Bruce et al., 2005). Plants that depend on nocturnal pollination, for example, by hawkmoths, advertise their nectar-providing flowers with bright colors, and most notably by a strong scent to attract their nectar-feeding pollinators (Raguso et al., 2003a; Raguso et al., 2003b). Evolution has thus formed a system that greatly facilitates the location of nectar sources by foraging insects. The situation is very different when gravid females search for a suitable host plant for oviposition. Vegetative parts of plants, probably to remain cryptic to herbivores, emit only trace quantities of volatiles that might be difficult to identify against the olfactory background provided by other plants (Turlings et al., 1995). At the same time, leaf damage by insect herbivores leads to an increased emission of volatiles, sometimes attracting parasitoids and predators of these insects (Pare and Tumlinson, 1999). Herbivore-induced plant volatiles are often similar across plant species (Mumm and Dicke, 2010), and herbivores are omnipresent in natural environments. Together, these facts suggest that female moths searching for an oviposition site encounter either undamaged, olfactorily unremarkable plants or damaged plants with a more conspicuous volatile profile, components of which are shared across many non-host plants. In any case, gravid moths have to identify suitable host plants against a vast odor scenery provided by the background vegetation. For this purpose, insects might depend on taxon-specific volatiles released by host plants but not by surrounding plants. An example is the cabbage moth Plutella xylostella that uses host plant-specific isothiocyanates to locate cruciferous hosts (Liu et al., 2020). Most insects, however, seem to identify host plants by blends of ubiquitous components that are present in plant-specific ratios. This has been shown in experiments where small changes in the composition and ratios of crucial odor blends had a huge impact on the behavior of insects (Cha et al., 2008; Kárpáti et al., 2013; Riffell et al., 2014; Visser and Avé, 1978; Webster et al., 2010). Furthermore, the chemical composition of crucial blends and the capability of the insect’s antenna to detect specific components of these blends have been studied in detail (Conchou et al., 2017; Fraser et al., 2003; Tasin et al., 2010). At the level of the first olfactory processing center in the insect brain, the antennal lobe, previous studies have investigated the temporal coding patterns evoked by floral bouquets. By impaling a restricted region of the antennal lobe with a multiunit probe, simultaneous recordings from a mixed population of local interneurons and projection neurons in this area were performed (Riffell et al., 2009a; Riffell et al., 2009b). Using the same approach, inhibitory interactions between these neurons could be studied in addition (Lei et al., 2004). However, this recording technique does not allow assigning functional significance to individual olfactory glomeruli, which are the morphological and functional subunits of the antennal lobe (Gao et al., 2000; Hansson et al., 1992). An analysis of the spatial coding patterns, however, is possible via functional calcium imaging. Although this technique does not inform about temporal coding patterns or inhibitory interactions, it was used in different insect species to provide a detailed insight into the spatial representation of natural odor blends across the glomerular array (Burger et al., 2021; Lahondère et al., 2020; Saveer et al., 2012; Schubert et al., 2014; Zhao et al., 2020). Usually, only odor blends that are known to be essential in the ecology of the insect were tested as the aim of those studies was to reveal how crucial blends are coded in the brain. However, it remains unclear how the olfactory systems of insects can differentiate between crucial and irrelevant blends, that is, how peripheral detection and central representation allow the identification of food sources and oviposition sites within a complex olfactory environment.

In our study, we collected headspaces of focal plants and background vegetation in the habitat of the tobacco hawkmoth Manduca sexta in Southern Arizona. Volatiles of hawkmoth-visited plants, like of most vegetation, differ between day and night both regarding floral (Hoballah et al., 2005; Raguso et al., 2003b) and leaf emissions (De Moraes et al., 2001). We collected plant headspace only during the night as we were interested in how the nocturnal M. sexta would detect and process these olfactory cues.

The primary nectar sources for M. sexta in the Southwestern United States are flowers of Agave palmeri and Datura wrightii. Volatile emissions of these two species are strong but very different from each other (Raguso, 2004; Raguso et al., 2003a; Riffell et al., 2008), and their pollen together account for 90% of the pollen load on the proboscis of M. sexta (Alarcón et al., 2008), a measurement that can be used as a proxy for flower visitation. Presence of pollen from Mirabilis longiflora and Mimosa dysocarpa on the moth’s proboscis and nighttime observations reveal that these plants are additional secondary nectar sources in the same habitat (Alarcón et al., 2008; Grant and Grant, 1983). Datura, in addition to being a valuable nectar source for M. sexta, is one of its two larval host plants in the area. Datura plants thus have to interact with an insect that is at the same time an important pollinator and a damaging herbivore (Bronstein et al., 2009), enabling the moth to find an oviposition site by navigating towards the scent of nectar-providing flowers emitted by the same plant (Reisenman et al., 2010). The other local host plant of M. sexta larvae is Proboscidea spp., the only known host belonging to a non-solanaceous family (Mechaber and Hildebrand, 2000). Flowers of Proboscidea, however, are not visited by foraging hawkmoths, that is, Proboscidea plants are suffering from leaf consumption by M. sexta larvae but do not profit from pollination by ovipositing moths. Furthermore, we sampled odors from another 11 native, frequent plants in the direct neighborhood of M. sexta’s focal plants. These background plants have no documented relevance for M. sexta; they included flowering herbaceous plants, nonflowering woody shrubs or trees and tufts of grass. Three of the background plants, the desert willow Chilopsis linearis, the sunflower Helianthus annuus, and the wild grape Vitis arizonica, are larval hosts of other sympatric hawkmoth species (Table 1).

After collecting all nocturnal plant headspaces in situ in the field, we proceeded to analyze this comprehensive chemical database. We then used the plants’ headspaces as stimuli in physiological experiments with female M. sexta. Specifically, we investigated which components of the volatile blends the moth’s antenna can detect, and how the glomerular array of the antennal lobe is coding these complex odor bouquets. An insect’s reaction to olfactory cues is known to be plastic in relation to its physiological condition and experience (Gadenne et al., 2016). The moths tested in our study were laboratory-reared on artificial diet, naïve to plant odors, not fed, and tested only once, as we were interested in the insects’ innate neuronal responses. However, M. sexta has been demonstrated to differentially respond to plant odors depending on its mating status (Mechaber et al., 2002). Underlying this differential response is a state-dependent modulation of the olfactory system, which may take place at the level of the antenna, the brain, or at both levels (Gadenne et al., 2016; Saveer et al., 2012). Therefore, we investigated the peripheral detection of plant headspace and the central representation of this olfactory information in both virgin and mated M. sexta females.

Our results revealed that the olfactory system of female moths responds strongly to odors related to nectar sources. Suitable oviposition substrates elicited much weaker but specific responses, a specificity that was most pronounced in gravid females. Evolution thus seems to have shaped an olfactory system that allows efficient feeding at all stages and that enables the mated female to pinpoint an optimal home for her offspring.

For a female moth, two plant-based resources are of overriding importance: flowers providing nectar for sustenance of the animal itself and plants providing suitable oviposition sites and thereby food for the offspring. Here, we studied how the olfactory system of the female hawkmoth, M. sexta, has evolved to allow unambiguous identification of these resources based on their emissions of volatile molecules.

As could be expected, plants that predominately (Datura, Mirabilis) or at least partly (Agave) rely on nocturnal pollination by hawkmoths (Alarcón et al., 2008; Emiliano Trejo-Salazar et al., 2015) sent a clear and distinctive chemical signal in the night. Our results regarding the number and identity of compounds emitted by Agave and Datura flowers and the dissimilarity between both floral bouquets confirm earlier studies (Raguso, 2004; Raguso et al., 2003a; Riffell et al., 2008). In addition, the sunflower Helianthus emitted a strong and distinct scent, illustrating that its around-the-clock open flowers depend not only on diurnal but also on nocturnal pollinators. Although M. sexta is not described as a pollinator of Helianthus (Torretta et al., 2009), unspecified pollen from the sunflower family was found on the proboscis of M. sexta and other hawkmoths, indicating that these moths occasionally feed also on sunflowers (Alarcón et al., 2008). Low nighttime emissions observed in the remaining samples might reflect the plants’ independence of nocturnal pollination (in the case of flowering plants) or an avoidance strategy against herbivory (for collections from nonflowering branches).

When we tested the antenna of female M. sexta with plant headspaces using GC-EAD, we found that the moths in most of the cases detect at least some compounds, even in wind-pollinated background vegetation like grass or careless weed, plants that, based on the chemical analysis, had a weak smell consisting of a small number of components. Female moths, both virgin and mated, therefore seem to be equipped with the sensory capability to distinguish not only strong and complex scents emitted by nectar sources but also bouquets of host plants and surrounding background vegetation. However, the highest number of active compounds was present in the floral headspace of Agave and Datura. In particular, the bouquet of Agave contained 9 of the 16 strongest antennal stimulants, 8 of them being aliphatic esters. These esters are signature compounds of Agave flowers (Raguso, 2004) as they are rarely found in other floral headspace investigated in almost 1000 plant species from 90 families (Knudsen et al., 2006). In particular, this chemical class is lacking in typical hawkmoth-pollinated flowers (Raguso et al., 2003a; Raguso et al., 2003b). Two enantiomers of the Agave-characteristic ester ethyl sorbate elicited the strongest antennal response of all active GC-peaks (median EAG amplitudes: 2.6 mV and 2.9 mV, stimulus concentrations: ~0.5 µg and >>0.5 µg, Figure 2D). These responses are higher than the response of a male antenna when stimulated with bombykal, the main component of M. sexta’s sex pheromone (1.9 mV, stimulus concentration: ~100 µg; Fandino et al., 2019). Even if we consider that bombykal has a lower vapor pressure than ethyl sorbate and that less odor might reach the antenna in EAG than in GC-EAD experiments, this comparison indicates that the female antenna is at least as sensitive to promising floral, that is, nectar-indicating volatiles, as the male antenna by the female sex-pheromone.

EAD activity might correlate with behavior (Liu et al., 2020; Zhu et al., 1993), but a strong antennal response towards an odor does not always imply a strong behavioral response to this odor molecule (Honda et al., 1998; Suckling et al., 1996). In M. sexta, a comparison of physiological and behavioral data is possible as almost half of the active and identified GC-peaks in this study were previously tested in a wind tunnel assay (Bisch-Knaden et al., 2018). EAD responses evoked by these 31 shared odors belonging to seven chemical classes are indeed positively correlated with the duration a female moth shows feeding behavior when encountering the same odors (EAD amplitude versus duration of proboscis contacts with a scented filter paper, Pearson correlation coefficient r = 0.41, p=0.023). In contrast, no correlation was found between EAD activity and the duration of abdomen curling behavior, that is, behavior related to oviposition (r = −0.03, p=0.9). Hence, no conclusions from GC-EAD results can be drawn regarding an odor’s relevance in connection with an oviposition site, whereas odors that evoked a strong response at the antenna of female M. sexta often are attractive in the context of feeding.

In previous GC-coupled single-sensillum recordings (GC-SSR), 60% of randomly chosen olfactory sensilla on the antenna of female M. sexta reacted to the aliphatic ester (Z)-3-hexenyl acetate when stimulated with the scent of herbivore-damaged Datura foliage (Spaethe et al., 2013b). If the olfactory sensory neurons housed in these sensilla would not only detect (Z)-3-hexenyl acetate but aliphatic esters in general, this could explain the prominent response towards typical Agave esters in our GC-EAD experiments. In addition, the antenna might harbor narrowly tuned olfactory sensory neurons strongly responding only to Agave esters. Hawkmoth-pollinated flowers like Datura, Nicotiana, and Petunia emit oxygenated aromatics that are especially attractive to foraging hawkmoths and elicit a strong response from the antenna of M. sexta, and in its antennal lobe, respectively (Bisch-Knaden et al., 2018; Hoballah et al., 2005; Kessler et al., 2008; Riffell et al., 2013). This study shows that M. sexta females in addition exhibit a robust physiological response towards the bouquet collected from Agave flowers, reflecting the significant role this copious nectar source — releasing a very different smell than typical hawkmoth flowers — plays in M. sexta’s foraging behavior. Other hawkmoth species feeding on nectar from Agave flowers might share similar olfactory detection and processing abilities (Alarcón et al., 2008; Emiliano Trejo-Salazar et al., 2015).

Three volatiles, α-copaene, (Z)-3-hexenyl acetate, and β-ocimene, stood out as particularly strong activators of the female M. sexta antenna, although they were present in very low concentrations. The high sensitivity towards these odors might indicate that they act as long-distance cues guiding the moth to places with vegetation (Webster and Cardé, 2017). Furthermore, these odors have meanings that are more specific: α-copaene is involved in the oviposition decision process of M. sexta (Zhang et al., 2022) and in addition might indicate rewarding nectar sources as it was functionally present, that is, EAD-active, only in the headspace of Datura flower and Mirabilis. (Z)-3-hexenyl acetate and β-ocimene, on the other hand, are typical herbivore-induced volatiles and are released by herbivore-damaged Datura leaves (Allmann et al., 2013; Hare and Sun, 2011; Zhang et al., 2022). Interestingly, some projection neurons in the female antennal lobe targeting an identified glomerulus were reported to specifically respond to low concentrations of (Z)-3-hexenyl acetate (Reisenman et al., 2005). This odor might thus inform a M. sexta female searching for oviposition sites about the presence of potential larval competitors and predators already at a distance.

An earlier GC-EAD study with female M. sexta reported that Datura and Proboscidea foliage each emit 10 identified EAD-active compounds and share 8 of them (Fraser et al., 2003). Our work, in contrast, shows that both host plants emit only nine and four active compounds, respectively, and have no active compounds in common. In the case of Proboscidea headspace, none of its EAD-active compounds found in our experiments was identified in the former study, and vice versa. Many methodological factors could have contributed to this discrepancy in the results. In detail, Fraser et al. collected headspace from single, potted, undamaged plants with buds, flowers, and seeds removed; and a cultivar of Proboscidea was used, not the wild type. In this study, we collected headspace of local, mostly herbivore-damaged plants growing in a natural plant community and did not remove any parts of the plant. In addition, our odor collection lasted 12 hr during the natural dark phase versus 24 hr of artificially induced scotophase in Fraser et al., 2003. Conditions like growth in mixed plant populations or in monocultures (Kigathi et al., 2019), light deprivation (He et al., 2021), herbivore attack, and other stress factors (Holopainen and Gershenzon, 2010) influence both composition and quantity of plant-emitted volatiles. Therefore, the observed differences between the studies could be expected and emphasize the significance of odor collections in the field.

Bath application of a fluorescent calcium sensor allows monitoring of odor-induced neural activity in the brain. Each neuron type in the treated brain region might take up the marker molecules. However, as each glomerulus in the antennal lobe receives input from 4000 to 5000 olfactory sensory neurons (Oland and Tolbert, 1988), and is targeted by only 4–5 projection, that is, output neurons (Homberg et al., 1988), odor-evoked activation patterns in calcium imaging experiments can be assumed to reflect mainly the activity of input neurons. Additionally, about 360 local interneurons per antennal lobe (Homberg et al., 1988) with inhibitory and/or excitatory functions (Reisenman et al., 2011) might synapse back onto the sensory neurons, thus modulating their activity and accordingly the observed calcium signal. Although most of these interneurons arborize in many, if not all, glomeruli, some interneurons have a more restricted innervation pattern and connect only a few glomeruli (Christensen et al., 1993). This type of interneuron seems predisposed to play a role in the coding of complex odor blends released by plants. Interestingly, patchy interneurons are present mainly in female M. sexta (Matsumoto and Hildebrand, 1981). In the vinegar fly Drosophila melanogaster, patchy interneurons are responsible for nonlinear processing of binary odor mixtures (Mohamed et al., 2019). For some glomeruli in D. melanogaster, this modulation occurred already at the presynaptic level, that is, at the level we monitored in our calcium imaging experiments. To estimate if nonlinear interactions might occur in the antennal lobe of M. sexta, we compared headspace-evoked activation patterns with activation patterns evoked by EAD-active, single compounds that were present in the respective headspace. From the bouquet of Datura foliage, for example, (Z)-3-hexenyl acetate elicited the strongest antennal response (Figure 2C) and activates mainly four glomeruli (glomeruli 6, 13, 16, and 12) when tested on its own (Bisch-Knaden et al., 2018). After stimulation with the complex headspace, however, none of these glomeruli was responding (Figure 3E, Table 2). The second best antennal activator in the headspace of Datura foliage, geraniol, activates mainly three glomeruli (glomeruli 6, 4, and 5, Bisch-Knaden et al., 2018). Of these, glomerulus 4 was the only one responding towards stimulation with the headspace (Figure 3E, Table 2). We thus conclude that there are indications of local inhibition as we otherwise would have expected to observe more activated glomeruli after stimulation with the complex headspace. A similar inhibition of glomeruli in mixtures of odors was reported in a calcium imaging study in honey bees, where the inhibitory effect was stronger in ternary than in binary mixtures (Joerges et al., 1997). As the plant bouquets tested in our study contained up to 20 EAD-active components, and as local interneurons in M. sexta, like in most insects, are mainly inhibitory (Christensen et al., 1993), the observed inhibitory mixture interactions after stimulation with complex blends seem plausible.

However, we also revealed coding characteristics that were similar at the periphery and in the brain, especially after stimulation with feeding-related odor bouquets. Representation of the essential nectar sources Datura and Agave flowers in the antennal lobe was outstanding as in the vast majority of all glomerulus-headspace combinations these two floral scents elicited the highest response. In former studies using a different approach, only a small fraction of the compounds present in the two floral bouquets (Agave: 10%; Datura: 15%) activated neurons in the antennal lobe of male M. sexta (Riffell et al., 2009a; Riffell et al., 2009b). However, the recording technique used by Riffell and colleagues targets about 10 glomeruli and part of the adjacent neuropil in the lateral part of the male antennal lobe, while we recorded from 23 identified glomeruli in the dorsal part of the female lobe. In addition, we used a puff of the floral headspace as stimulus, that is, the antennal lobe was activated by the full floral blend, whereas in previous studies a GC-coupled stimulus was applied, that is, the antennal lobe was activated by temporally separated single compounds present in the floral blend. The differing results might thus be due to these different approaches and potential sex-specific coding differences. However, compounds that were identified to activate neurons in the male antennal lobe, like ethyl sorbate (Agave) and benzyl alcohol (Datura), were also EAD-active in this study (Figure 2C) and evoked responses in some glomeruli of the female antennal lobe in a previous imaging study (Bisch-Knaden et al., 2018). Interestingly, lab experiments in a wind tunnel suggest that even such a strong scent as the one from Datura flowers can become less attractive to male M. sexta when presented in the olfactory background of a selected nonhost plant (Riffell et al., 2014).

Olfactory coding can change depending on the mating status of an insect (Gadenne et al., 2016). However, the neural response of female M. sexta towards volatiles from its main nectar sources was not altered following mating as it was reported for the noctuid moth Spodoptera littoralis (Saveer et al., 2012). Different life history traits of noctuid and sphingid moths might explain this different result: noctuid moths are generalists and lay their eggs in clusters on a wide range of acceptable host plants. Sphingid moths like M. sexta, on the other hand, are usually specialized on a few host plant families and females lay only a few single eggs on a given plant. Thus, hawkmoths need to refill their energy reservoir between oviposition bouts at host plants that are rare in the habitat and therefore require long flights between them (Alarcón et al., 2008; Raguso et al., 2003a). Moreover, female hawkmoths benefit from nectar feeding following mating as they live longer and produce more mature eggs compared to starved females (Sasaki and Riddiford, 1984; von Arx et al., 2013). The energy demand of hawkmoths is in addition especially high as both feeding and oviposition usually occur while the moth is hovering in front of the plant (Stöckl and Kelber, 2019). Taken together, the prominent and mating status-independent representation of floral bouquets at the antenna and in the antennal lobe of female M. sexta is in accordance with the moths’ ecology.

While the coding of flower volatiles in nectar-feeding moths is probably independent of sex, odors indicating oviposition sites should be of special importance for female moths after mating. Two enlarged, female-specific glomeruli that are located at the entrance of the antennal nerve into the female antennal lobe — at the same position as the sex pheromone-processing macroglomerular complex in males (Matsumoto and Hildebrand, 1981; Rössler et al., 1998) — seem predisposed to be involved in oviposition choice. This hypothesis is supported by the fact that output neurons targeting both glomeruli respond to headspace of tomato leaves, another host plant for M. sexta (King et al., 2000; Reisenman et al., 2009). On the other hand, the two host plant bouquets tested in our imaging experiments did not activate these glomeruli (glomeruli 1 and 2, Table 2), confirming results of a study using vegetative headspace from the hosts Datura, Nicotiana, and tomato. These scents failed to evoke a response in sensilla targeting mainly the two female-specific glomeruli (Shields and Hildebrand, 2001). Therefore, the question if these glomeruli might be involved in identifying an oviposition site is still open.

In contrast to the wide and strong activation of antennal lobe glomeruli by flower odors, M. sexta’s host plant bouquets each activated only a single glomerulus of the 23 glomeruli under investigation. While the responding glomerulus towards Datura foliage was independent of the female’s mating status, Proboscidea activated a different glomerulus in virgin than in mated females. This result is in line with the fact that the ecological meaning of Datura foliage does not change after mating as its smell indicates both a suitable host plant and a profitable nectar source (Kárpáti et al., 2013). Proboscidea, on the other hand, does not provide nectar for hawkmoths and is therefore interesting for the female moth only after mating. Many EAD-active compounds were tested in a previous calcium imaging study using monomolecular odorants as stimuli (Bisch-Knaden et al., 2018), allowing a comparison between these data and our imaging results obtained with natural mixtures. Some compounds present in the headspace of Proboscidea and Datura foliage, for example, when tested alone activated most strongly glomerulus 6, a glomerulus that was not activated after stimulation with the complete headspaces, again indicating nonlinear processing and robust presynaptic inhibitory interactions between glomeruli (Joerges et al., 1997; Mohamed et al., 2019). The two host plant-activated glomeruli in mated females were as well responding to nectar sources and hosts of sympatric hawkmoths. However, host plants exclusively activated one of these glomeruli, whereas the other sources activated additional glomeruli. Even if nonhost plants as well as host plants would activate more glomeruli in areas of the antennal lobe that were inaccessible in our imaging study, the resulting neural representation of nonhost plants in the antennal lobe of mated females would remain different from the pattern evoked by host plants.

Interestingly, virgin and mated females differed markedly in their response to the odor of background plants: of the 23 identified glomeruli, these plants activated only a small number in virgin females (range: 0–9) and even less glomeruli (range: 0–2) in mated females. The few background-activated glomeruli did not include the two host plant-activated glomeruli. The moths’ reduced responses to background plants but not to host plants after mating, together with the finding that the host plant Proboscidea activates a different glomerulus in virgin and mated females, indicate that the olfactory system of M. sexta females becomes tuned towards host plants following mating. Mechanisms mediating these post-mating changes in moth olfactory processing seem to be independent of neurotransmitters like octopamine and serotonin (Barrozo et al., 2010) but might include neuropeptides as in the vinegar fly, D. melanogaster (Hussain et al., 2016), and regulation of chemosensory-related genes like in Drosophila suzukii (Crava et al., 2019). Our data suggest that mated females could potentially be able to identify suitable oviposition sites by the relative activity of one or two glomeruli compared with the activity of other glomeruli. A similar sparse coding strategy was recently described for the discrimination of differentially attractive body odors by mosquitoes (Zhao et al., 2020). In this case, the relative activity of a single, human-odor-activated glomerulus versus a broadly tuned glomerulus has been proposed to enable the mosquito to identify its preferred human host.

M. sexta females intersperse feeding and oviposition bouts when visiting a flowering Datura (Raguso et al., 2003a), and lay more eggs on flowering than on nonflowering plants (Reisenman et al., 2010). However, Datura foliage alone attracts egg-laying females in the field (personal observation) and the lab (Nataraj et al., 2021; Spaethe et al., 2013b). We therefore tested leaves of Datura separately and compared their headspace with that of Proboscidea, the only other host plant in our study area. As the single activated glomerulus was different after stimulation with the two host plant bouquets, which also did not share any EAD-active compounds, M. sexta females should be able to distinguish the two plants based on olfaction alone. Field observations and experiments show that females lay more eggs on Proboscidea than on solanaceous hosts, although the plants grow next to each other and have a similar leaf surface (Diamond and Kingsolver, 2010; Mechaber and Hildebrand, 2000). These findings indicate that M. sexta can indeed discriminate between host plants belonging to different plant families, although visual and tactile cues might play a role in combination with olfactory cues. The observed low overall activity across the antennal lobe evoked by host plant odors corresponds to the preference of M. sexta for plants with a faint smell when searching for oviposition sites. Inbred horse nettle (Solanum carolinense) exhibits much lower nocturnal volatile emissions than outbred horse nettle, a solanaceous host plant of M. sexta in the southeastern US. Correspondingly, female moths spend more time hovering near inbred plants and lay more eggs there than on outbred plants. This preference is governed by olfactory cues alone as it persists in the absence of visual and contact cues (Kariyat et al., 2013). Furthermore, when given the choice between headspaces of two solanaceous host plant species with different total volatile concentration, M. sexta clearly prefers the weaker smelling plant. Diluting the headspace of the more intensely smelling plant leads to a reduction in this preference (Spaethe et al., 2013a). These findings show again that female moths consistently favor host plants with low volatile emissions, probably because high emission of specific volatiles are signs of active plant defense mechanisms, indicating the presence of larval competitors (De Moraes et al., 2001), and leading to impaired larval growth (Delphia et al., 2009). High levels of these herbivore-induced volatiles also attract predators and parasitoids (Kessler and Baldwin, 2001; Turlings et al., 1995), and egg-laying moths therefore avoid these sites (De Moraes et al., 2001; Li et al., 2018). Conversely, when M. sexta has to choose between flowering tobacco plants from populations that differ in their flower volatile concentration, the moths clearly prefer to forage at flowers with a stronger smell (Haverkamp et al., 2018). Hence, M. sexta pursues different strategies when searching for oviposition or feeding sites as the moths favor weakly or strongly scented sources, respectively.

In contrast to M. sexta’s host plants, the bouquets of host plants of sympatric hawkmoths activated many glomeruli in virgins, and even more glomeruli in mated females. Two glomeruli contributed mostly to this effect as they were responding to all three nonhost bouquets only after mating (glomeruli 12 and 13; Table 2). Odor-induced activation levels of these two glomeruli were positively correlated to odor-induced behavior in wind tunnel experiments using monomolecular odorants (Bisch-Knaden et al., 2018). However, only virgin females were included in this study, so conclusions regarding the behavior of mated females cannot be drawn.

The strong activation of antennal lobe glomeruli by host plants of other hawkmoths living in the same habitat was in contrast to weak but specific activation of single glomeruli (among those imaged) by host plants of M. sexta. The conspicuous activation patterns evoked by host plants of sympatric hawkmoths might serve as a stop signal for M. sexta during their search for a suitable oviposition site and therefore might help gravid females to avoid inappropriate hosts at a distance. It would be interesting to compare headspace-evoked activation patterns in the antennal lobe of co-occurring hawkmoths upon stimulation with odors of their own and of other species’ host plants to test if this might be a general coding policy. Examples of olfaction-based avoidance of nonhost plants were also reported for example in bark beetles (Huber et al., 2000). Antennae of these insects respond strongly to many volatiles released by nonhost trees. Like in the case of M. sexta, some compounds are present in the bouquet of both host and nonhost plants, corroborating the hypothesis that odor-guided choice of host plants relies on blends of ubiquitous compounds in a specific ratio (Bruce and Pickett, 2011) and concentration (Spaethe et al., 2013a) rather than on the detection of host-exclusive odors.

By using ecologically relevant odors collected in the actual habitat of our model animal, M. sexta, we revealed olfactory coding strategies both for odors emanating from crucial resources but also for those emitted by substrates that should be avoided. We also show how the female mating status affects olfactory processing but, interestingly, in a way well adapted to the specific life history traits of the species under investigation. In a broader perspective, our study contributes to understanding innate neural representation of natural odor mixtures in the brain and coding strategies enabling animals to distinguish crucial resources from background noise.

Figure 1—source data 1, Figure 2—source data 1 and Figure 3—source data 1 contain the numerical data used to generate the figures. Figure 3—source code 1 contains custom written software for processing calcium imaging data.

1. 1. Alarcón R
   2. Davidowitz G
   3. Bronstein JL

   (2008) Nectar usage in a southern Arizona hawkmoth community

   Ecological Entomology 33:503–509.

   https://doi.org/10.1111/j.1365-2311.2008.00996.x

   • Google Scholar
2. 1. Allmann S
   2. Späthe A
   3. Bisch-Knaden S
   4. Kallenbach M
   5. Reinecke A
   6. Sachse S
   7. Baldwin IT
   8. Hansson BS

   (2013) Feeding-induced rearrangement of green leaf volatiles reduces moth oviposition

   eLife 2:e00421.

   https://doi.org/10.7554/eLife.00421

   • PubMed
   • Google Scholar
3. 1. Barrozo RB
   2. Jarriault D
   3. Simeone X
   4. Gaertner C
   5. Gadenne C
   6. Anton S

   (2010) Mating-induced transient inhibition of responses to sex pheromone in a male moth is not mediated by octopamine or serotonin

   The Journal of Experimental Biology 213:1100–1106.

   https://doi.org/10.1242/jeb.040139

   • PubMed
   • Google Scholar
4. 1. Bisch-Knaden S
   2. Dahake A
   3. Sachse S
   4. Knaden M
   5. Hansson BS

   (2018) Spatial Representation of Feeding and Oviposition Odors in the Brain of a Hawkmoth

   Cell Reports 22:2482–2492.

   https://doi.org/10.1016/j.celrep.2018.01.082

   • PubMed
   • Google Scholar
5. 1. Bronstein JL
   2. Huxman T
   3. Horvath B
   4. Farabee M
   5. Davidowitz G

   (2009) Reproductive biology of Datura wrightii: the benefits of a herbivorous pollinator

   Annals of Botany 103:1435–1443.

   https://doi.org/10.1093/aob/mcp053

   • PubMed
   • Google Scholar
6. 1. Bruce TJA
   2. Wadhams LJ
   3. Woodcock CM

   (2005) Insect host location: a volatile situation

   Trends in Plant Science 10:269–274.

   https://doi.org/10.1016/j.tplants.2005.04.003

   • PubMed
   • Google Scholar
7. 1. Bruce TJA
   2. Pickett JA

   (2011) Perception of plant volatile blends by herbivorous insects--finding the right mix

   Phytochemistry 72:1605–1611.

   https://doi.org/10.1016/j.phytochem.2011.04.011

   • PubMed
   • Google Scholar
8. 1. Burger H
   2. Marquardt M
   3. Babucke K
   4. Heuel KC
   5. Ayasse M
   6. Dötterl S
   7. Galizia CG

   (2021) Neural and behavioural responses of the pollen-specialist bee Andrena vaga to Salix odours

   The Journal of Experimental Biology 224:13.

   https://doi.org/10.1242/jeb.242166

   • PubMed
   • Google Scholar
9. 1. Cha DH
   2. Nojima S
   3. Hesler SP
   4. Zhang A
   5. Linn CE
   6. Roelofs WL
   7. Loeb GM

   (2008) Identification and field evaluation of grape shoot volatiles attractive to female grape berry moth (Paralobesia viteana

   Journal of Chemical Ecology 34:1180–1189.

   https://doi.org/10.1007/s10886-008-9517-0

   • PubMed
   • Google Scholar
10. 1. Christensen TA
    2. Hildebrand JG

    (1987) Male-specific, sex pheromone-selective projection neurons in the antennal lobes of the mothManduca sexta

    Journal of Comparative Physiology A 160:553–569.

    https://doi.org/10.1007/BF00611929

    • PubMed
    • Google Scholar
11. 1. Christensen TA
    2. Waldrop BR
    3. Harrow ID
    4. Hildebrand JG

    (1993) Local interneurons and information processing in the olfactory glomeruli of the moth Manduca sexta

    Journal of Comparative Physiology A 173:385–399.

    https://doi.org/10.1007/BF00193512

    • PubMed
    • Google Scholar
12. 1. Conchou L
    2. Anderson P
    3. Birgersson G

    (2017) Host Plant Species Differentiation in a Polyphagous Moth: Olfaction is Enough

    Journal of Chemical Ecology 43:794–805.

    https://doi.org/10.1007/s10886-017-0876-2

    • PubMed
    • Google Scholar
13. 1. Crava CM
    2. Sassù F
    3. Tait G
    4. Becher PG
    5. Anfora G

    (2019) Functional transcriptome analyses of Drosophila suzukii antennae reveal mating-dependent olfaction plasticity in females

    Insect Biochemistry and Molecular Biology 105:51–59.

    https://doi.org/10.1016/j.ibmb.2018.12.012

    • PubMed
    • Google Scholar
14. 1. De Moraes CM
    2. Mescher MC
    3. Tumlinson JH

    (2001) Caterpillar-induced nocturnal plant volatiles repel conspecific females

    Nature 410:577–580.

    https://doi.org/10.1038/35069058

    • PubMed
    • Google Scholar
15. 1. Delphia CM
    2. De Moraes CM
    3. Stephenson AG
    4. Mescher MC

    (2009) Inbreeding in horsenettle influences herbivore resistance

    Ecological Entomology 34:513–519.

    https://doi.org/10.1111/j.1365-2311.2009.01097.x

    • Google Scholar
16. 1. Diamond SE
    2. Kingsolver JG

    (2010) Fitness consequences of host plant choice: a field experiment

    Oikos 119:542–550.

    https://doi.org/10.1111/j.1600-0706.2009.17242.x

    • Google Scholar
17. 1. Emiliano Trejo-Salazar R
    2. Scheinvar E
    3. Eguiarte LE

    (2015) Who really pollinates agaves? Diversity of floral visitors in three species of Agave (Agavoideae: Asparagaceae

    Revista Mexicana de Biodiversidad 86:358–369.

    https://doi.org/10.1016/j.rmb.2015.04.007

    • Google Scholar
18. 1. Fandino RA
    2. Haverkamp A
    3. Bisch-Knaden S
    4. Zhang J
    5. Bucks S
    6. Nguyen TAT
    7. Schröder K
    8. Werckenthin A
    9. Rybak J
    10. Stengl M
    11. Knaden M
    12. Hansson BS
    13. Große-Wilde E

    (2019) Mutagenesis of odorant coreceptor Orco fully disrupts foraging but not oviposition behaviors in the hawkmoth Manduca sexta

    PNAS 116:15677–15685.

    https://doi.org/10.1073/pnas.1902089116

    • PubMed
    • Google Scholar
19. 1. Fraser AM
    2. Mechaber WL
    3. Hildebrand JG

    (2003) Electroantennographic and behavioral responses of the sphinx moth Manduca sexta to host plant headspace volatiles

    Journal of Chemical Ecology 29:1813–1833.

    https://doi.org/10.1023/a:1024898127549

    • PubMed
    • Google Scholar
20. 1. Gadenne C
    2. Barrozo RB
    3. Anton S

    (2016) Plasticity in Insect Olfaction: To Smell or Not to Smell?

    Annual Review of Entomology 61:317–333.

    https://doi.org/10.1146/annurev-ento-010715-023523

    • PubMed
    • Google Scholar
21. 1. Gao Q
    2. Yuan BB
    3. Chess A

    (2000) Convergent projections of Drosophila olfactory neurons to specific glomeruli in the antennal lobe

    Nature Neuroscience 3:780–785.

    https://doi.org/10.1038/77680

    • PubMed
    • Google Scholar
22. 1. Grant V
    2. Grant KA

    (1983) Hawkmoth pollination of Mirabilis longiflora (Nyctaginaceae

    PNAS 80:1298–1299.

    https://doi.org/10.1073/pnas.80.5.1298

    • PubMed
    • Google Scholar
23. 1. Grosse-Wilde E
    2. Kuebler LS
    3. Bucks S
    4. Vogel H
    5. Wicher D
    6. Hansson BS

    (2011) Antennal transcriptome of Manduca sexta

    PNAS 108:7449–7454.

    https://doi.org/10.1073/pnas.1017963108

    • PubMed
    • Google Scholar
24. 1. Hansson BS
    2. Ljungberg H
    3. Hallberg E
    4. Löfstedt C

    (1992) Functional specialization of olfactory glomeruli in a moth

    Science (New York, N.Y.) 256:1313–1315.

    https://doi.org/10.1126/science.1598574

    • PubMed
    • Google Scholar
25. 1. Hansson BS
    2. Carlsson MA
    3. Kalinovà B

    (2003) Olfactory activation patterns in the antennal lobe of the sphinx moth, Manduca sexta

    Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology 189:301–308.

    https://doi.org/10.1007/s00359-003-0403-5

    • PubMed
    • Google Scholar
26. 1. Hare JD
    2. Sun JJ

    (2011) Production of induced volatiles by Datura wrightii in response to damage by insects: effect of herbivore species and time

    Journal of Chemical Ecology 37:751–764.

    https://doi.org/10.1007/s10886-011-9985-5

    • PubMed
    • Google Scholar
27. 1. Haverkamp A
    2. Hansson BS
    3. Baldwin IT
    4. Knaden M
    5. Yon F

    (2018) Floral Trait Variations Among Wild Tobacco Populations Influence the Foraging Behavior of Hawkmoth Pollinators

    Frontiers in Ecology and Evolution 6:19.

    https://doi.org/10.3389/fevo.2018.00019

    • Google Scholar
28. 1. He J
    2. Halitschke R
    3. Schuman MC
    4. Baldwin IT

    (2021) Light dominates the diurnal emissions of herbivore-induced volatiles in wild tobacco

    BMC Plant Biology 21:401.

    https://doi.org/10.1186/s12870-021-03179-z

    • PubMed
    • Google Scholar
29. 1. Hoballah ME
    2. Stuurman J
    3. Turlings TCJ
    4. Guerin PM
    5. Connétable S
    6. Kuhlemeier C

    (2005) The composition and timing of flower odour emission by wild Petunia axillaris coincide with the antennal perception and nocturnal activity of the pollinator Manduca sexta

    Planta 222:141–150.

    https://doi.org/10.1007/s00425-005-1506-8

    • PubMed
    • Google Scholar
30. 1. Holopainen JK
    2. Gershenzon J

    (2010) Multiple stress factors and the emission of plant VOCs

    Trends in Plant Science 15:176–184.

    https://doi.org/10.1016/j.tplants.2010.01.006

    • PubMed
    • Google Scholar
31. 1. Homberg U
    2. Montague RA
    3. Hildebrand JG

    (1988) Anatomy of antenno-cerebral pathways in the brain of the sphinx moth Manduca sexta

    Cell and Tissue Research 254:255–281.

    https://doi.org/10.1007/BF00225800

    • PubMed
    • Google Scholar
32. 1. Honda K
    2. Ômura H
    3. Hayashi N

    (1998) Identification of floral volatiles from Ligustrum japonicum that stimulate flower-visiting by cabbage butterfly, Pieris rapae

    Journal of Chemical Ecology 24:2167–2180.

    https://doi.org/10.1023/A:1020750029362

    • Google Scholar
33. 1. Huber DPW
    2. Gries R
    3. Borden JH
    4. Pierce Jr. HD

    (2000) A survey of antennal responses by five species of coniferophagous bark beetles (Coleoptera: Scolytidae) to bark volatiles of six species of angiosperm trees

    Chemoecology 10:103–113.

    https://doi.org/10.1007/PL00001811

    • Google Scholar
34. 1. Hussain A
    2. Üçpunar HK
    3. Zhang M
    4. Loschek LF
    5. Grunwald Kadow IC

    (2016) Neuropeptides Modulate Female Chemosensory Processing upon Mating in Drosophila

    PLOS Biology 14:e1002455.

    https://doi.org/10.1371/journal.pbio.1002455

    • PubMed
    • Google Scholar
35. 1. Joerges J
    2. Küttner A
    3. Galizia CG
    4. Menzel R

    (1997) Representations of odours and odour mixtures visualized in the honeybee brain

    Nature 387:285–288.

    https://doi.org/10.1038/387285a0

    • Google Scholar
36. 1. Kariyat RR
    2. Mauck KE
    3. Balogh CM
    4. Stephenson AG
    5. Mescher MC
    6. De Moraes CM

    (2013) Inbreeding in horsenettle (Solanum carolinense) alters night-time volatile emissions that guide oviposition by Manduca sexta moths

    Proceedings. Biological Sciences 280:20130020.

    https://doi.org/10.1098/rspb.2013.0020

    • PubMed
    • Google Scholar
37. 1. Kárpáti Z
    2. Knaden M
    3. Reinecke A
    4. Hansson BS

    (2013) Intraspecific combinations of flower and leaf volatiles act together in attracting hawkmoth pollinators

    PLOS ONE 8:e72805.

    https://doi.org/10.1371/journal.pone.0072805

    • PubMed
    • Google Scholar
38. 1. Kessler A
    2. Baldwin IT

    (2001) Defensive function of herbivore-induced plant volatile emissions in nature

    Science (New York, N.Y.) 291:2141–2144.

    https://doi.org/10.1126/science.291.5511.2141

    • PubMed
    • Google Scholar
39. 1. Kessler D
    2. Gase K
    3. Baldwin IT

    (2008) Field experiments with transformed plants reveal the sense of floral scents

    Science (New York, N.Y.) 321:1200–1202.

    https://doi.org/10.1126/science.1160072

    • PubMed
    • Google Scholar
40. 1. Kigathi RN
    2. Weisser WW
    3. Reichelt M
    4. Gershenzon J
    5. Unsicker SB

    (2019) Plant volatile emission depends on the species composition of the neighboring plant community

    BMC Plant Biology 19:58.

    https://doi.org/10.1186/s12870-018-1541-9

    • PubMed
    • Google Scholar
41. 1. King JR
    2. Christensen TA
    3. Hildebrand JG

    (2000)

    Response characteristics of an identified, sexually dimorphic olfactory glomerulus

    The Journal of Neuroscience 20:2391–2399.

    • PubMed
    • Google Scholar
42. 1. Knudsen JT
    2. Eriksson R
    3. Gershenzon J
    4. Ståhl B

    (2006) Diversity and Distribution of Floral Scent

    The Botanical Review 72:1–120.

    https://doi.org/10.1663/0006-8101(2006)72[1:DADOFS]2.0.CO;2

    • Google Scholar
43. 1. Lahondère C
    2. Vinauger C
    3. Okubo RP
    4. Wolff GH
    5. Chan JK
    6. Akbari OS
    7. Riffell JA

    (2020) The olfactory basis of orchid pollination by mosquitoes

    PNAS 117:708–716.

    https://doi.org/10.1073/pnas.1910589117

    • PubMed
    • Google Scholar
44. 1. Lei H
    2. Christensen TA
    3. Hildebrand JG

    (2004) Spatial and temporal organization of ensemble representations for different odor classes in the moth antennal lobe

    The Journal of Neuroscience 24:11108–11119.

    https://doi.org/10.1523/JNEUROSCI.3677-04.2004

    • PubMed
    • Google Scholar
45. 1. Li XH
    2. Garvey M
    3. Kaplan I
    4. Li BP
    5. Carrillo J

    (2018) Domestication of tomato has reduced the attraction of herbivore natural enemies to pest-damaged plants

    Agricultural and Forest Entomology 20:390–401.

    https://doi.org/10.1111/afe.12271

    • PubMed
    • Google Scholar
46. 1. Liu X-L
    2. Zhang J
    3. Yan Q
    4. Miao C-L
    5. Han W-K
    6. Hou W
    7. Yang K
    8. Hansson BS
    9. Peng Y-C
    10. Guo J-M
    11. Xu H
    12. Wang C-Z
    13. Dong S-L
    14. Knaden M

    (2020) The Molecular Basis of Host Selection in a Crucifer-Specialized Moth

    Current Biology 30:4476–4482.

    https://doi.org/10.1016/j.cub.2020.08.047

    • PubMed
    • Google Scholar
47. 1. Matsumoto SG
    2. Hildebrand JG

    (1981) Olfactory interneurons in the moth Manduca sexta: response characteristics and morphology of central neurons in the antennal lobes

    Proceedings of the Royal Society of London. Series B. Biological Sciences 213:249–277.

    https://doi.org/10.1098/rspb.1981.0066

    • Google Scholar
48. 1. Mechaber WL
    2. Hildebrand JG

    (2000) Novel, Non-Solanaceous Hostplant Record for Manduca sexta (Lepidoptera: Sphingidae) in the Southwestern United States

    Annals of the Entomological Society of America 93:447–451.

    https://doi.org/10.1603/0013-8746(2000)093[0447:NNSHRF]2.0.CO;2

    • Google Scholar
49. 1. Mechaber WL
    2. Capaldo CT
    3. Hildebrand JG

    (2002) Behavioral responses of adult female tobacco hornworms, Manduca sexta, to hostplant volatiles change with age and mating status

    Journal of Insect Science 2:1–8.

    https://doi.org/10.1673/031.002.0501

    • Google Scholar
50. Conference

    1. Medina AL

    (2003)

    Historical and recent flora of the Santa Rita Experimental Range

    USDA Forest Service Proceedings, RMRS-P-30. pp. 141–148.

    • Google Scholar
51. 1. Mohamed AAM
    2. Retzke T
    3. Das Chakraborty S
    4. Fabian B
    5. Hansson BS
    6. Knaden M
    7. Sachse S

    (2019) Odor mixtures of opposing valence unveil inter-glomerular crosstalk in the Drosophila antennal lobe

    Nature Communications 10:1201.

    https://doi.org/10.1038/s41467-019-09069-1

    • PubMed
    • Google Scholar
52. 1. Mumm R
    2. Dicke M

    (2010) Variation in natural plant products and the attraction of bodyguards involved in indirect plant defense

    Canadian Journal of Zoology 88:628–667.

    https://doi.org/10.1139/z10-032

    • Google Scholar
53. 1. Nataraj N
    2. Adam E
    3. Hansson BS
    4. Knaden M

    (2021) Host Plant Constancy in Ovipositing Manduca sexta

    Journal of Chemical Ecology 47:1042–1048.

    https://doi.org/10.1007/s10886-021-01309-3

    • PubMed
    • Google Scholar
54. 1. Oland LA
    2. Tolbert LP

    (1988) Effects of hydroxyurea parallel the effects of radiation in developing olfactory glomeruli in insects

    The Journal of Comparative Neurology 278:377–387.

    https://doi.org/10.1002/cne.902780307

    • PubMed
    • Google Scholar
55. 1. Pare P
    2. Tumlinson JH

    (1999) Plant volatiles as a defense against insect herbivores

    Plant Physiology 121:325–332.

    https://doi.org/10.1104/pp.121.2.325

    • PubMed
    • Google Scholar
56. 1. Raguso RA
    2. Henzel C
    3. Buchmann SL
    4. Nabhan GP

    (2003a) Trumpet flowers of the Sonoran Desert: floral biology of Peniocereus cacti and Sacred Datura

    International Journal of Plant Sciences 164:877–892.

    https://doi.org/10.1086/378539

    • Google Scholar
57. 1. Raguso RA
    2. Levin RA
    3. Foose SE
    4. Holmberg MW
    5. McDade LA

    (2003b) Fragrance chemistry, nocturnal rhythms and pollination “syndromes” in Nicotiana

    Phytochemistry 63:265–284.

    https://doi.org/10.1016/s0031-9422(03)00113-4

    • PubMed
    • Google Scholar
58. 1. Raguso RA

    (2004) WHY ARE SOME FLORAL NECTARS SCENTED?

    Ecology 85:1486–1494.

    https://doi.org/10.1890/03-0410

    • Google Scholar
59. 1. Reisenman CE
    2. Christensen TA
    3. Hildebrand JG

    (2005) Chemosensory selectivity of output neurons innervating an identified, sexually isomorphic olfactory glomerulus

    Journal of Neuroscience 25:8017–8026.

    https://doi.org/10.1523/jneusosci.1314-05.2005

    • Google Scholar
60. 1. Reisenman CE
    2. Riffell JA
    3. Hildebrand JG

    (2009) Neuroethology of oviposition behavior in the moth Manduca sexta

    Annals of the New York Academy of Sciences 1170:462–467.

    https://doi.org/10.1111/j.1749-6632.2009.03875.x

    • PubMed
    • Google Scholar
61. 1. Reisenman CE
    2. Riffell JA
    3. Bernays EA
    4. Hildebrand JG

    (2010) Antagonistic effects of floral scent in an insect-plant interaction

    Proceedings. Biological Sciences 277:2371–2379.

    https://doi.org/10.1098/rspb.2010.0163

    • PubMed
    • Google Scholar
62. 1. Reisenman CE
    2. Dacks AM
    3. Hildebrand JG

    (2011) Local interneuron diversity in the primary olfactory center of the moth Manduca sexta

    Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology 197:653–665.

    https://doi.org/10.1007/s00359-011-0625-x

    • PubMed
    • Google Scholar
63. 1. Riffell J
    2. Alarcón R
    3. Abrell L
    4. Davidowitz G
    5. Bronstein JL
    6. Hildebrand JG

    (2008) Behavioral consequences of innate preferences and olfactory learning in hawkmoth-flower interactions

    PNAS 105:3404–3409.

    https://doi.org/10.1073/pnas.0709811105

    • PubMed
    • Google Scholar
64. 1. Riffell JA
    2. Lei H
    3. Christensen TA
    4. Hildebrand JG

    (2009a) Characterization and coding of behaviorally significant odor mixtures

    Current Biology 19:335–340.

    https://doi.org/10.1016/j.cub.2009.01.041

    • PubMed
    • Google Scholar
65. 1. Riffell JA
    2. Lei H
    3. Hildebrand JG

    (2009b) Neural correlates of behavior in the moth Manduca sexta in response to complex odors

    PNAS 106:19219–19226.

    https://doi.org/10.1073/pnas.0910592106

    • PubMed
    • Google Scholar
66. 1. Riffell JA
    2. Lei H
    3. Abrell L
    4. Hildebrand JG

    (2013) Neural basis of a pollinator’s buffet: olfactory specialization and learning in Manduca sexta

    Science (New York, N.Y.) 339:200–204.

    https://doi.org/10.1126/science.1225483

    • PubMed
    • Google Scholar
67. 1. Riffell JA
    2. Shlizerman E
    3. Sanders E
    4. Abrell L
    5. Medina B
    6. Hinterwirth AJ
    7. Kutz JN

    (2014) Sensory biology. Flower discrimination by pollinators in a dynamic chemical environment

    Science (New York, N.Y.) 344:1515–1518.

    https://doi.org/10.1126/science.1251041

    • PubMed
    • Google Scholar
68. 1. Rössler W
    2. Tolbert LP
    3. Hildebrand JG

    (1998) Early formation of sexually dimorphic glomeruli in the developing olfactory lobe of the brain of the moth Manduca sexta

    The Journal of Comparative Neurology 396:415–428.

    https://doi.org/10.1002/(sici)1096-9861(19980713)396:43.0.co;2-4

    • PubMed
    • Google Scholar
69. 1. Sachse S
    2. Rappert A
    3. Galizia CG

    (1999) The spatial representation of chemical structures in the antennal lobe of honeybees: steps towards the olfactory code

    The European Journal of Neuroscience 11:3970–3982.

    https://doi.org/10.1046/j.1460-9568.1999.00826.x

    • PubMed
    • Google Scholar
70. 1. Sasaki M
    2. Riddiford LM

    (1984) Regulation of reproductive behaviour and egg maturation in the tobacco hawk moth, Manduca sexta

    Physiological Entomology 9:315–327.

    https://doi.org/10.1111/j.1365-3032.1984.tb00713.x

    • Google Scholar
71. 1. Saveer AM
    2. Kromann SH
    3. Birgersson G
    4. Bengtsson M
    5. Lindblom T
    6. Balkenius A
    7. Hansson BS
    8. Witzgall P
    9. Becher PG
    10. Ignell R

    (2012) Floral to green: mating switches moth olfactory coding and preference

    Proceedings. Biological Sciences 279:2314–2322.

    https://doi.org/10.1098/rspb.2011.2710

    • PubMed
    • Google Scholar
72. 1. Schubert M
    2. Hansson BS
    3. Sachse S

    (2014) The banana code: natural blend processing in the olfactory circuitry of Drosophila melanogaster

    Frontiers in Physiology 5:59.

    https://doi.org/10.3389/fphys.2014.00059

    • Google Scholar
73. 1. Shields VDC
    2. Hildebrand JG

    (2001) Responses of a population of antennal olfactory receptor cells in the female moth Manduca sext a to plant-associated volatile organic compounds

    Journal of Comparative Physiology A 186:1135–1151.

    https://doi.org/10.1007/s003590000165

    • PubMed
    • Google Scholar
74. 1. Spaethe A
    2. Reinecke A
    3. Haverkamp A
    4. Hansson BS
    5. Knaden M

    (2013a) Host plant odors represent immiscible information entities - blend composition and concentration matter in hawkmoths

    PLOS ONE 8:e77135.

    https://doi.org/10.1371/journal.pone.0077135

    • Google Scholar
75. 1. Spaethe A
    2. Reinecke A
    3. Olsson SB
    4. Kesavan S
    5. Knaden M
    6. Hansson BS

    (2013b) Plant species- and status-specific odorant blends guide oviposition choice in the moth Manduca sexta

    Chemical Senses 38:147–159.

    https://doi.org/10.1093/chemse/bjs089

    • PubMed
    • Google Scholar
76. 1. Stöckl AL
    2. Kelber A

    (2019) Fuelling on the wing: sensory ecology of hawkmoth foraging

    Journal of Comparative Physiology. A, Neuroethology, Sensory, Neural, and Behavioral Physiology 205:399–413.

    https://doi.org/10.1007/s00359-019-01328-2

    • PubMed
    • Google Scholar
77. 1. Suckling DM
    2. Karg G
    3. Gibb AR
    4. Bradley SJ

    (1996) Electroantennogram and oviposition responses of Epiphyas postvittana (Lepidoptera: Tortricidae) to plant volatiles

    New Zealand Journal of Crop and Horticultural Science 24:323–333.

    https://doi.org/10.1080/01140671.1996.9513969

    • Google Scholar
78. 1. Tasin M
    2. Bäckman A-C
    3. Anfora G
    4. Carlin S
    5. Ioriatti C
    6. Witzgall P

    (2010) Attraction of female grapevine moth to common and specific olfactory cues from 2 host plants

    Chemical Senses 35:57–64.

    https://doi.org/10.1093/chemse/bjp082

    • PubMed
    • Google Scholar
79. 1. Tautenhahn R
    2. Patti GJ
    3. Rinehart D
    4. Siuzdak G

    (2012) XCMS Online: a web-based platform to process untargeted metabolomic data

    Analytical Chemistry 84:5035–5039.

    https://doi.org/10.1021/ac300698c

    • PubMed
    • Google Scholar
80. 1. Torretta JP
    2. Navarro F
    3. Medan D

    (2009)

    Nocturnal floral visitors of sunflower (Helianthus annuus, Asterales: Asteraceae) in Argentina

    Revista de La Sociedad Entomologica Argentina 68:339–350.

    • Google Scholar
81. 1. Turlings TCJ
    2. Loughrin JH
    3. McCall PJ
    4. Rose USR
    5. Lewis WJ
    6. Tumlinson JH

    (1995) How caterpillar-damaged plants protect themselves by attracting parasitic wasps

    PNAS 92:4169–4174.

    https://doi.org/10.1073/pnas.92.10.4169

    • Google Scholar
82. 1. Visser JH
    2. Avé DA

    (1978) General green leaf volatiles in the olfactory orientation of the Colorado beetle, Leptinotarsa decemlineata

    Entomologia Experimentalis et Applicata 24:738–749.

    https://doi.org/10.1111/j.1570-7458.1978.tb02838.x

    • Google Scholar
83. 1. von Arx M
    2. Sullivan KA
    3. Raguso RA

    (2013) Dual fitness benefits of post-mating sugar meals for female hawkmoths (Hyles lineata

    Journal of Insect Physiology 59:458–465.

    https://doi.org/10.1016/j.jinsphys.2013.01.006

    • Google Scholar
84. 1. Webster B
    2. Bruce T
    3. Pickett J
    4. Hardie J

    (2010) Volatiles functioning as host cues in a blend become nonhost cues when presented alone to the black bean aphid

    Animal Behaviour 79:451–457.

    https://doi.org/10.1016/j.anbehav.2009.11.028

    • Google Scholar
85. 1. Webster B
    2. Cardé RT

    (2017) Use of habitat odour by host-seeking insects

    Biological Reviews of the Cambridge Philosophical Society 92:1241–1249.

    https://doi.org/10.1111/brv.12281

    • PubMed
    • Google Scholar
86. 1. Zhang J
    2. Komail Raza SA
    3. Wei Z
    4. Keesey IW
    5. Parker AL
    6. Feistel F
    7. Chen J
    8. Cassau S
    9. Fandino RA
    10. Grosse-Wilde E
    11. Dong S
    12. Kingsolver J
    13. Gershenzon J
    14. Knaden M
    15. Hansson BS

    (2022) Competing beetles attract egg laying in a hawkmoth

    Current Biology 32:861–869.

    https://doi.org/10.1016/j.cub.2021.12.021

    • PubMed
    • Google Scholar
87. Preprint

    1. Zhao Z
    2. Zung JL
    3. Kriete AL
    4. Iqbal A
    5. Younger MA
    6. Matthews BJ
    7. Merhof D
    8. Thiberge S
    9. Strauch M
    10. McBride CS

    (2020) Chemical Signatures of Human Odour Generate a Unique Neural Code in the Brain of Aedes Aegypti Mosquitoes

    bioRxiv.

    https://doi.org/10.1101/2020.11.01.363861

    • Google Scholar
88. 1. Zhu YC
    2. Keaster AJ
    3. Gerhardt KO

    (1993) Field Observations on Attractiveness of Selected Blooming Plants to Noctuid Moths and Electroantennogram Responses of Black Cutworm (Lepidoptera: Noctuidae) Moths to Flower Volatiles

    Environmental Entomology 22:162–166.

    https://doi.org/10.1093/ee/22.1.162

    • Google Scholar

Author details

1. Sonja Bisch-Knaden

   Max-Planck-Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Jena, Germany

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing - original draft, Writing - review and editing

   For correspondence

   sbisch-knaden@ice.mpg.de

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3424-8376

2. Michelle A Rafter

   CSIRO Health and Biosecurity, Dutton Park Queensland, Australia

   Contribution

   Formal analysis, Funding acquisition, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5180-0062

3. Markus Knaden

   Max-Planck-Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Jena, Germany

   Contribution

   Conceptualization, Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6710-1071

4. Bill S Hansson

   Max-Planck-Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Jena, Germany

   Contribution

   Conceptualization, Funding acquisition, Supervision, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4811-1223

• 1,119

  views

• 254

  downloads

• 5

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.