Electrophysiological and behavioral responses of cabbage aphid (Brevicoryne brassicae) to rosemary (Rosmarinus officinalis) volatiles, a potential push plant for vegetable push-pull cropping system

Electrophysiological and behavioral responses of cabbage aphid (Brevicoryne brassicae) to rosemary (Rosmarinus officinalis) volatiles, a potential push plant for vegetable push-pull cropping system | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Electrophysiological and behavioral responses of cabbage aphid (Brevicoryne brassicae) to rosemary (Rosmarinus officinalis) volatiles, a potential push plant for vegetable push-pull cropping system Bretor Katuku Mutua, Thomas Dubois, Komivi Senyo Akutse, Benjamin Muli, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3815776/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Mar, 2024 Read the published version in Journal of Chemical Ecology → Version 1 posted 7 You are reading this latest preprint version Abstract The cabbage aphid ( Brevicoryne brassicae ) is a major pest of kale ( Brassica oleraceae var. acephala ), an important vegetable that is grown worldwide due to its high nutritional and economic value. Brevicoryne brassicae poses a great challenge to B. oleraceae var. acephala production, causing significant direct and indirect yield losses. Farmers overly rely on synthetic insecticides to manage the pest with limited success owing to its high reproductive behavior and development of resistance. This necessitates search for sustainable alternatives to mitigate these challenges. This study assessed behavioral responses of B. brassicae to odors from rosemary ( Rosmarinus officinalis ) and B. oleraceae var. acephala headspace volatiles in a Perspex four-arm olfactometer. We identified and quantified volatiles emitted by each of the two plants and those eliciting behavioral response using coupled gas chromatography-mass spectrometry (GC-MS) and gas chromatography-electroantennogram (GC-EAG), respectively. Our findings revealed that B. brassicae spent more time in the arms of the olfactometer that contained B. oleraceae var. acephala volatiles compared to the arm that held R. officinalis volatiles. GC-MS analysis revealed diverse and higher quantities of volatile compounds in R. officinalis compared to B. oleraceae var. acephala . GC-EAG showed that B. brassicae was responsive to linalool, camphor, borneol, α-terpineol, verbenone, geraniol and bornyl acetate from R. officinalis and sabinene, γ-terpinene, and β-caryophyllene from B. oleraceae var. acephala . Our findings demonstrate that R. officinalis is repellent against B. brassicae and could be utilized as a ‘push’ plant in an intercropping strategy against this pest. Agroecology Cabbage aphid Integrated pest management Kale Rosemary Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Kale ( Brassica oleracea L. var. acephala ) is a leafy vegetable of global importance, primarily cultivated by small-scale farmers for both subsistence and income generation, particularly in tropical and subtropical regions (Mutiga et al. 2011 ; Peris and Kiptoo, 2017 ; Šamec et al. 2019 ). According to the Center for Disease Control (CDC), B. oleracea var. acephala was ranked 15th of the 47 powerhouse fruits and vegetables, producing more than 17 essential nutrients (CDC, 2014 ). Brassica oleracea var. acephala has garnered significant attention recently owing to its notable health advantages. It contains phytochemicals that have been linked to reduced risk of cancer and other chronic diseases, due to antioxidant properties and high dietary fiber content (Šamec et al. 2019 ). Additionally, B. oleracea var. acephala is known for its resilience to adverse effects of climate change, rendering it adaptable to extreme climatic conditions (Lagerkvist et al. 2012 ). In Kenya, B. oleracea var. acephala has become increasingly popular due to its ability to maximize land use and address food security and nutrition concerns amidst challenges such as land degradation and population pressure (Mutiga et al. 2011 ; Olwande et al. 2015 ; HCD 2019 ). Due to the low input and labour requirements for B. oleracea var. acephala production, the crop stands out as one of the most accessible vegetables to cultivate (Lans et al. 2012 ; Canwat et al. 2021 ). Its cost-effective production methods contribute to relatively low market prices, ensuring affordability for consumers. Consequently, it is widely consumed in households and extensively sold in urban areas (Ngolo Otieno, 2019 ). Despite these benefits, the successful production and productivity of B. oleracea var. acephala face various constraints such as pests and disease pressures, poor soils, limited market access, climate change and inadequate production techniques (Mutiga et al. 2010 ). The cabbage aphid, Brevicoryne brassicae (L.) (Hemiptera: Aphididae) is one of the most destructive insect pest that affects production of B. oleracea var. acephala and other Brassica sp. crops worldwide (Cole 1994 ; Gill et al. 2013 ). The pest is native to Europe but has been reported in many parts of the world (Gill et al. 2013 ; Munthali and Tshegofatso, 2014 ). The adults feed on the sap of plant tissues using their piercing-sucking mouthparts, causing direct crop damage through wilting, stunted growth and deformation, and transmits diseases such as mosaic virus and ring necrosis, which eventually result in plant death (Powell et al. 2006 ; Mutiga et al. 2010 ; Chalise and Dawadi, 2019 ). Brevicoryne brassicae has a wide host range of crops belonging to Brassicaceae family such as kale ( Brassica oleracea var. acephala) , cabbage ( Brassica oleracea var. capitata) , Brussels sprout (Brassica oleracea var. gemmifera) and Broccoli ( Brassica oleracea var. italica ) (Douloumpaka and Van Emden, 2003 ; Van Emden and Harrington, 2007 ; Döring, 2014 ). Smallholder farmers with limited resources have resorted to indiscriminate use of synthetic insecticides to control the pest (Badenes-Perez and Shelton, 2006 ; Ngolo Otieno, 2019 ). The repeated use of these chemical insecticides has resulted in additional economic costs to farmers, insecticide resistance and pests resurgences, and has proven detrimental to agrobiodiversity, human and environmental health (Kianmatee and Ranamukhaarachchi, 2007 ; Macharia and Afr, 2009 ; Ngolo et al. 2019 ; Ricupero et al. 2020 ). There is therefore an urgent need to develop alternative control options which will be ecologically friendly, cost-effective, sustainable and suitable for resource-limited vegetable farmers in Africa. The push pull cropping system is one of such sustainable management options that has been successfully used in cereal pests control (Khan et al. 2001 ). This is a habitat management strategy that uses plant semiochemicals to manipulate the distribution of pests and their natural enemies through production of volatile organic compounds (VOCs) in the natural ecosystem, which play an important role in communication, defense and response to abiotic stresses (Khan et al. 2001 ). The push/repellent plant produces VOCs that have the ability to mask the host plant volatiles, attract natural enemies or deter the pest from landing on the host plant (Cook et al. 2007 ). Host location involves perception of specific or a blend of VOCs naturally emitted into the ecosystem which determine attraction or avoidance (Zhang and Chen, 2015 ). As such, non-host plant volatiles can be used to modify the behavior of pests by interfering with their host selection and orientation. Previous studies have demonstrated the potential of rosemary ( Rosmarinus officinalis ), an aromatic perennial herb of Lamiaceae family, as an insect repellent plant, showcasing its effectiveness against a wide range of insects pests ( Cloyd et al. 2009 ; Cook et al. 2007 ; Dardouri et al. 2019 ; Elhalawany et al. 2019 ; Li et al. 2021 ; Waithaka et al. 2017 ; Zhang and Chen, 2015 ). For example, applications of different doses of R. officinalis leaf extracts and essential oils have demonstrated their efficacy as repellents against two-spotted spider mite ( Tetranychus urticae Koch (Trombidiformes: Tetranychidae)) and citrus brown mite ( Eutetranychus orientalis Klein (Trombidiformes: Tetranychidae)) (Elhalawany et al. 2019 ). Similarly, laboratory bioassays with different R. officinalis species have demonstrated their ability to exhibit repellent properties towards green peach aphid ( Myzus persicae Sulzer (Hemiptera: Aphididae)) through the production of different VOCs (Dardouri et al. 2019 ). Moreover, intercropping R. officinalis with sweet pepper ( Capsicum annuum L. Solanaceae) in a greenhouse experiment in China was found to suppress the population of M. persicae , thrips ( Frankliniella intonsa Trybom (Thysanoptera: Thripidae)), and silverleaf whitefly ( Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae)) without affecting the population dynamics of natural enemies (Li et al. 2021 ). The repulsive effect of R. officinalis in these studies have been attributed to emission of VOCs which are repellent to the pests. Despite these studies demonstrating the repellence ability of R. officinalis , its activity against B. brassicae has not been investigated. Therefore, in this study, we (1) investigated the behavioral response of B. brassicae to R. officinalis and B. oleracea var. acephala headspace volatiles; (2) identified and compared the discriminant VOCs in the two plants; and (3) used Gas chromatography- electroantennography to determine the responses of B. brassicae antenna to R. officinalis and B. oleracea var. acephala headspace volatiles. MATERIALS AND METHODS Plants Brassica oleracea var. acephala (var. simlaw select) seeds were purchased from Simlaw Seeds Company Limited, Nairobi, Kenya. The seeds were sown in a 2 × 1 m nursery bed at the International Centre of Insect Physiology and Ecology ( icipe ), Nairobi, Kenya (01º 13’ 25.6” S 036º 53’ 49.1” E, 1616 m above sea level) and allowed to grow for three weeks, after which the seedlings were transplanted individually into 5 L plastic pots. The pots were filled with soil and organic manure mixed in a ratio of 2:1 and were maintained in an insect-proof screenhouse in the same location. Irrigation was done manually once a day. Plants did not receive any synthetic insecticides or fertilizer inputs. Rosmarinus officinalis (var. Tuscan Blue) was propagated vegetatively through stem cuttings obtained from Kimplanter Seedlings and Nurseries located at Thika, Kenya and received the same treatment as B. oleracea var. acephala . Six weeks old B. oleracea var. acephala and eight weeks old R. officinalis plants were used for experiments. Insects An initial colony of the B. brassicae was established with insects obtained from smallholder B. oleracea var. acephala farms in Limuru, Kenya (1° 10' 9.13" S, 36° 41' 25.18" E, 2500 m above sea level). Adult B. brassicae were reared on B. oleracea var. acephala plants in 50 × 80 x 40 cm Perspex rearing cages in the laboratory and maintained at the temperature of 25 ± 1 ºC, 65 ± 5% relative humidity (RH) and 12L: 12D hrs photoperiod as a modification of Chalise and Dawadi ( 2019 ) who reared the aphids at 25 ± 2°C and 55 ± 5% Relative Humidity. Freshly potted B. oleracea var. acephala plants were provided after every three days for feeding and reproduction. After 10 days, the newly emerged adults were transferred to a separate rearing cage, fed with B. oleracea var. acephala plants and later used for bioassays. After every two weeks, field collected insects were infused into the laboratory colony to maintain behavioral characteristics and avoid genetic decay. Insects were reared on B. oleracea var. acephala for 10 generations prior to the bioassays. All the aphids used for bioassays were fourteen days old. Collection of volatiles using headspace technique Headspace sampling technique was used to collect volatiles from experimental plants ( B. oleracea var. acephala and R. officinalis ) and a control (empty polyethylene terephthalate bag) for 24 h, starting at the first two hours of the photo phase as described by Mutyambai et al. ( 2015 ). The aerial parts of the plants were gently enclosed inside polyethylene terephthalate (PET) bags ( ̴ 12.5 mm thickness, volume 3.2 L), heated to 150°C for 30 min before use, and fitted with Swagelok inlet and outlet ports (Mutyambai et al. 2015 ). Charcoal-filtered air was passed through the inlet port at a flow rate of 600 mL min −1 . VOCs were collected on Charcoal filters (0.05 g, 60/80 mesh, Supelco, USA) inserted into the outlet through which air was drawn at 400 mL min −1 . After trapping, the entrained volatiles were eluted using 250 µL dichloromethane (analytical grade, Sigma-Aldrich, USA) in 2 mL micro vials (Agilent Technologies, Warsaw, Poland) and stored in a -40°C freezer before further chemical analysis and bioassays. Entrainments from each host plant were replicated four times and each plant was used only once. Olfactometer bioassay Two separate sets of experiments were carried out to evaluate the olfactory response of B. brassicae using a Perspex four-arm olfactometer as described by Mutyambai et al. ( 2015 ). In the first experiment, the two opposite arms of the olfactometer were directly connected to B. oleracea var. acephala and R. officinalis plants respectively, while the remaining two arms were connected to empty bags (control arms). Charcoal-filtered air at a rate of 300 mL min − 1 was pumped into the headspace of the test plants enclosed in heat-sterilized PET bags (control), positioned away from the olfactometer arena to prevent any visual cues. In order not to contaminate the headspace plant volatiles, the pots were wrapped with aluminum foil leaving only the aerial part exposed. A suction tube was used to simultaneously draw air from the plants to the olfactometer at a rate of 100 mL min − 1 to enable the movement of the plant volatiles (25 mL min − 1 per arm), and air was then exhausted from the laboratory (Lohonyai et al. 2019 ). Fourteen-day-old B. brassicae were individually placed in Petri dish (90 × 20 mm) and kept in the laboratory for 1 h to acclimatize prior to the bioassay. They were then introduced individually at the center of the olfactometer and allowed to make choice. In the second experiment, a choice test was conducted to determine the response of B. brassicae to constitutive test plant-derived volatiles and solvent (DCM) control. The two opposite arms held 10 µl aliquots of each of the plants’ headspace samples while the other two opposing arms held 10 µl of solvent as controls. The headspace samples were applied to a filter paper (4 × 25 mm) using a micropipette (Drummond Scientific, Broomall, USA) and placed at the inlet of the olfactometer arms. Brevicoryne brassicae were then introduced at the center of the olfactometer with a fine camel hairbrush and allowed to make a choice. To enable the insect to detect the volatiles, a suction pump was connected to the olfactometer, facilitating the suction of air containing the volatiles from the arms to the center of the olfactometer at a rate of 25 mL min − 1 . In both experiments, the duration of time spent by the insect in each arm of the olfactometer was recorded using Olfa- (F. Nazzi, Udine, Italy) (Mutyambai et al. 2015 ). Twelve aphids were tested and each insect was used only once. The olfactometer was rotated every 4 min to avoid positional and directional bias. The insects were observed for 20 min and each olfactometer was used only once. In the event that an aphid remained stationary for a consecutive duration of 2 min at the center of the olfactometer, it was regarded as inactive, leading to the rejection of that particular replicate. Analyses of volatiles The headspace volatiles from B. oleracea var. acephala and R. officinalis were analyzed using gas chromatograph-mass spectrometry (GC-MS; 7890A GC and MSD 5975C triple-axis; Agilent Technologies, Palo Alto, USA). The GC-MS was configured to operate in an electron impact ionization mode of 70 eV. A HP5-MSI low-bleed capillary column with dimensions of 30 m length × 0.25 mm inner diameter × 0.25 µm film thickness (J & W Scientific, Folsom, USA). A flow rate of 1.2 mL min − 1 of helium gas was employed as the carrier gas. The oven temperature was initially set at 35°C for 5 min and then increased at a rate of 10°C min − 1 until reaching a final temperature of 280°C and held for 10.5 min. The headspace samples were injected into the GC-MS using an autosampler in measured aliquots (1 µL). The identification of compounds was accomplished by comparing their mass spectra with those obtained from authentic standards, as well as utilizing mass spectra databases of the National Institute of Standards and Technology chemistry webbook (NIST11, Gaithersburg, Maryland). Additionally, retention indices were determined by comparing the retention times of a mixture of n-alkanes ranging from C8 to C23. To ensure further confirmation, a co-injection with available authentic standards was performed under the same experimental conditions. For quantification of the amount (in ng) of identified VOCs, the peak areas were divided by the known quantities of external standards. The emission rate, expressed as ng − 1 plant − 1 h − 1 , was determined by multiplying the reciprocal of the proportion of the total headspace utilized and subsequently dividing it by the number of hours in the sampling period. All compounds detected in the control group were deemed contaminants and subsequently disregarded during the identification process. The MSD Chemstation software (v F.01.00.1903; Agilent Technologies, Palo Alto, USA) was employed to analyze the data. Coupled gas chromatography-electroantennography Adult B. brassicae were individually collected from the Perspex rearing cage into a 100 mm x 15mm plastic petri dish. Antennae were prepared by separating the head of ice-chilled B. brassicae from the rest of the body using a scalpel. Two silver-silver chloride (Ag-AgCl) borosilicate glass micro electrodes, 2 mm o.d. X 1.16 mm i.d. with an inner filament (INR-II, Syntech, Hilversum, the Netherlands) filled with Ringer saline solution (7.5 gl-1 sodium chloride, 0.7 gl-1 potassium chloride, 0.2 gl-1 calcium chloride, 0.2 gl-1 magnesium chloride) as in Maddrell ( 1969 ) but without glucose were used for electroantennogram recordings. With the help of an electrode holder, the head was placed at the indifferent electrode with the tip of the antenna touching the recording electrode. The glass tube featured a side hole through which the column effluent was introduced. The splitter used in this setup was made of glass-lined stainless-steel tubing and deactivated fused silica tubing. VOCs to which B. brassicae antenna responded to were identified on GC. One µl of the concentrated entrainment sample was injected onto a nonpolar column (HP-1, 50 m × 0.32 mm i.d.× 0.52 µm film thickness, (Agilent Technologies, California, USA) in a HP5890 GC (Agilent Technologies, Palo Alto, USA) equipped with a cool on-column injector and a flame ionization detector (FID). The oven temperature was programmed at 35°C for 2 min and then programmed at 10°C min − 1 to 280°C. Hydrogen was used as the carrier gas. Simultaneous recordings of the EAG and FID responses were obtained with specialized software (Electro Antenno Detection 2015 version 1.2.6, Syntech, Hilversum, The Netherlands). The EAD outlet contained an uninterrupted airflow filtered through charcoal at a rate of 400 mL min − 1 directed to the B. brassicae antenna. A total of six coupled runs were completed. Only FID peaks which corresponded to an EAG peak in 3 or more replicates were considered electro-physiologically active. Statistical analyses Data was analyzed using R statistical software version 4.2.3 (R Core Team, 2022 ). The duration of time spent by B. brassicae in each arm of the olfactometer was first converted into proportions to address dependence of visiting time and log 10 -ratio transformations to allow for analysis of compositional data (Mutyambai et al. 2015 ; Piepel and Aitchison, 1988 ). For the normal distribution of the data, Shapiro-Wilk test (Shapiro and Wilk, 1965 ) was performed before being subjected to analysis of variance (ANOVA), followed by the Student-Newman-Keuls (SNK) test for mean separation whenever treatments were found to be significantly different at P < 0.05. All P values ≤ 0.05 were considered statistically significant. The emission of compounds from all test plants underwent non-parametric statistical test, the Kruskal Wallis test following the abnormal distribution of the data as determined by the Shapiro-Wilk test ( P < 0.05). Subsequently, Dunn’s multiple pairwise comparison of the means was utilized to differentiate means between the two groups. Furthermore, to assess the contribution of various VOCs to dissimilarities among the test plants, their abundance was compared using a heatmap. RESULTS Olfactory response of Brevicoryne brassicae to Brassica oleracea var. acephala and Rosmarinus officinalis plants and their headspace volatiles In the first experiment with individual plant odors from B. oleracea var. acephala and R. officinalis plants, or clean air, B. brassicae showed more preference to the arm containing B. oleracea var. acephala over the arms with R. officinalis or clean air ( P < 0.001) (Fig. 1 A). In the second experiment with odour sources from B. oleracea var. acephala and R. officinalis headspace volatiles, or clean air, B. brassicae showed less preference to the arm containing R. officinalis volatiles than the arms containing B. oleracea var. acephala volatiles or clean air ( P < 0.001) (Fig. 1 B). Volatile profiles GC-MS analysis detected 22 major compounds from the plant headspace samples belonging to three chemical classes: monoterpenes (17), ketones (1) and sesquiterpenes (4) (Table 1 and Fig. 2 A, B). Of the identified compounds, nine were detected from B. oleracea var. acephala (Fig. 2 B) and 19 from R. officinalis (Fig. 2 A). Common volatiles between the two plants included α-pinene, β-pinene, myrcene, 1,8-cineole, γ-terpinene, camphor and β-caryophyllene with R. officinalis producing 57, 61, 6, 36, 10, 106 and 274 times more the amount produced by B. oleracea var. acephala respectively ( P < 0.001) (Table 1 ). VOCs that were detected in R. officinalis but not detected in B. oleracea var. acephala included camphene, α-phellandrene, δ-2- carene, (Z)-sabinene hydrate, linalool, borneol, α-terpineol, verbenone, citronellol, geraniol, bornyl acetate, α-humulene and caryophyllene oxide. Those detected in B. oleracea var. acephala but not in R. officinalis included sabinene and limonene (Table 1 ). Heatmap clustering showed volatiles obtained from R. officinalis were more concentrated than those obtained from B. oleracea var. acephala (Fig. 3 ). It also showed that 1,8-cineole, β-pinene, myrcene and sabinene were the most abundant volatiles in B. oleracea var. acephala whereas γ-terpinene, camphor, limonene, α-pinene were the least abundant in that order. Additionally, 1,8-cineole was the most abundant volatile in both B. oleracea var. acephala and R. officinalis , while 1,8-cineole, α-pinene, β-caryophyllene, camphor, bornyl acetate and verbenone were the most abundant VOCs in R. officinalis . Table 1 Mean amount (ng/plant/h) of volatile organic compounds (VOCs) identified in headspace collection of Brassica oleracea var. acephala and Rosmarinus officinalis plants (n = 4). No RT (min) Compound Name 1 RI alk 2 RI L 3 Brassica oleracea var. acephala Rosmarinus officinalis P -value 4 1 9.74 α -pinene* 931 934 410.54 ± 159.48 b 23,465.15 ± 4393.73 a 0.002 2 10.03 Camphene 945 944 nd 5,914.963 ± 607.05 - 3 10.55 Sabinene 969 974 1,274.64 ± 746.55 nd - 4 10.61 β -pinene* 972 978 87.00 ± 50.44 b 5,379.80 ± 496.49 a < 0.001 5 10.93 myrcene* 987 981 953.28 ± 527.07 b 5,983.69 ± 831.85 a 0.002 6 11.17 α -phellandrene 998 1005 nd 1,429.39 ± 253.42 - 7 11.39 δ -2-carene 1011 1011 nd 1,555.28 ± 289.47 - 8 11.65 Limonene* 1026 1030 1,457.36 ± 854.58 nd - 9 11.79 1,8-cineole 1032 1036 1,232.56 ± 622.18 b 40,197.45 ± 14,913.86 a 0.009 10 12.29 γ -terpinene* 1061 1060 381.39 ± 359.18 b 3,907.73 ± 632.33 a < 0.001 11 12.44 (Z) -sabinene hydrate 1069 1092 nd 3,955.11 ± 1072.60 - 12 12.92 Linalool* 1096 1101 nd 7,470.31 ± 2507.75 - 13 13.73 Camphor 1146 1146 118.25 ± 53.30 b 12,642.43 ± 3081.30 a 0.007 14 14.11 Borneol 1167 1167 nd 9,645.39 ± 1169.14 - 15 14.66 α -terpineol* 1204 1189 nd 3,666.03 ± 1261.86 - 16 14.85 Verbenone* 1218 1209 nd 11,939.37 ± 2333.98 - 17 15.00 Citronellol* 1228 1230 nd 1,143.08 ± 347.97 - 18 15.45 Geraniol* 1259 1253 nd 4,401.97 ± 1092.20 - 19 15.90 Bornyl acetate 1290 1295 nd 12,775.81 ± 2801.34 - 20 17.79 β- caryophyllene 1428 1430 69.90 ± 26.39 b 19,141.41 ± 3947.36 a < 0.001 21 18.17 α -humulene 1462 1465 nd 4,706.05 ± 1147.31 - 22 19.77 Caryophyllene oxide* 1593 1588 nd 2,971.13 ± 491.12 - * Indicates compounds confirmed with authentic standards. Means (± SE) with different superscript letter(s) within the rows are significantly different at the P < 0.05 level. "nd" indicates not detected. Gas chromatography-electroantennography responses of Brevicoryne brassicae to Rosmarinus officinalis and Brassica oleracea var. acephala headspace volatiles The flame ionization detector (FID) and electroantennographic detector (EAD) were used to detect volatile compounds from R. officinalis and B. oleracea va r. acephala plants by B. brassicae antennae. The GC-EAD recordings showed that B. brassicae elicited antennal response to three compounds from B. oleracea va r. acephala namely sabinene, γ-terpinene and β-caryophyllene (Fig. 4 A) and seven active compounds from R. officinalis namely linalool (12), camphor (13), borneol (14), α-terpineol (15), verbenone (16), geraniol (18) and bornyl acetate (19) (Fig. 4 B) DISCUSSION Our findings from the current study revealed that B. brassicae were more attracted to constitutive and headspace volatiles of B. oleracea var. acephala (their main host) and were repelled by R. officinalis as a whole plant and its headspace volatiles. These observations align with the results reported by Cai et al. ( 2018 ) where M. persicae were found to be attracted by cabbage ( Brassica oleracea var. capitata) volatiles, one of their major host. The reduced attraction of B. brassicae to R. officinalis plant volatiles as demonstrated in the current study is in agreement with the results reported by Cai et al. ( 2018 ) and Dardouri et al. ( 2019 ), where the authors demonstrated that M. persicae preferred a blank chamber over the ones containing R. officinalis , which emitted VOCs in relatively higher amounts. Non-host plant odors contribute to the repellent and deterrent effects observed in push plants such as the Greenleaf desmodium ( Desmodium uncinatum ) and molasses grass ( Melinis minutiflora) used in cereal push pull cropping systems leading to reduced pest infestation and plant damage (Khan et al. 2001 ). Similarly, R. officinalis volatiles could mask the host plant attractive VOCs from B. oleracea var. acephala given its higher emission of some of the repellent volatile compounds making it difficult for B. brassicae to perceive its host in presence of the repellent R. officinalis volatiles. Chemical analysis of headspace volatiles showed that R. officinalis produced more terpenes as compared to B. oleracea var. acephala (Table 1 ). The most abundant VOCs in R. officinalis included 1,8-cineole, camphor, verbenone, bornyl acetate, linalool and citronellol. Majority of these compounds have been associated with repellence properties against different insects species when used as plant extracts and essential oils (Miresmailli and Isman, 2006 ; Cloyd et al. 2009 ; Webster, 2009 ; Dayaram and Khan, 2016 ). Comparable results on R. officinalis essential oils were reported by Elhalawany et al. ( 2019 ), who observed that the major constituents of R. officinalis oil was mostly made of linalool, α -pinene, limonene, bornyl acetate and β-caryophyllene. Rosmarinus officinalis produced 1,8-cineole 36-fold the amount produced by B. oleracea var. acephala . Additionally, verbenone, linalool and β-caryophyllene were found to be the other two most abundant VOCs. This is in tandem with previous studies that reported verbenone, 1–8 cineole and linalool as the major constituents of R. officinalis volatiles and its oil extracts (Hori, 1998 ). Rosmarinus officinalis emitted a higher quantity of volatiles as compared to B. oleracea var. acephala , which are responsible for its characteristic aroma. The high abundance of these major compounds is evidence that R. officinalis , being an aromatic herb produces such compounds in very high amounts, which the insect can perceive from a far and avoid them, while masking the host plant volatiles. Host location by B. brassicae involves the perception of the volatiles by the sensilla of the insect’s antenna. The GC-EAD gives an opportunity to utilize these antennae and under controlled volumes, determine which among the volumes of the volatiles are responsible for the behavior of the insect. The findings of this study indicate that B. brassicae ’s antenna responded to sabinene, γ-terpinene and β-caryophyllene from B. oleracea var. acephala (Fig. 4 A). Sabinene was one of the major constituent volatiles in B. oleracea var. acephala but was not observed in R. officinalis . Additionally, despite γ-terpinene and β-caryophyllene being found in both plants, B. brassicae antenna didn’t show any antennal response when R. officinalis volatiles were used. However, B. brassicae antenna showed antennal response to linalool, camphor, borneol, α-terpineol, verbenone, geraniol and bornyl acetate from R. officinalis (Fig. 4 B). Among the R. officinalis compounds that caused antennal response, bornyl acetate, camphor and α-terpineol have been reported to reduce the activities of M. persicae and other insects such as mosquitoes (Dardouri et al. 2019 ). The insect’s antenna did not show any response to 1,8-cineole despite it being a major constituent of R. officinalis oil. However, some studies have reported its insecticidal activity against onion aphid, Neotoxoptera formosana Takahashi (Hemiptera: Aphididae) (Hori, 1998 ; Elhalawany et al. 2019 ). Camphor, citronellal and geraniol, have also been reported to have high insecticidal activity against aphids by disrupting their digestive and neurological enzymes hence leading to death (Chalise & Dawadi, 2019 ); therefore, their presence in the volatiles emitted by R. officinalis could have contributed to the observed repellence behavior exhibited by B. brassicae . Our electrophysiological study confirms the results of laboratory bioassays with R. officinalis volatiles which showed that linalool, camphor, and α-terpineol were repellent to B. brassicae as opposed to other compounds in R. officinalis bouquet. Similar results were obtained with M. persicae (Hori, 1998 ). Li et al. ( 2021 ) reported the presence of monoterpenes such as α-pinene, 1,8-cineole, camphor, camphene, and verbenone as the most abundant repellent compounds in R. officinalis. Conflictingly, B. brassicae did not show any electrophysiological response to 1,8-cineole and camphene. Bruce et al. ( 2005 ) and Dardouri et al. ( 2019 ) documented that α-pinene, camphene, limonene, γ-terpinene, linalool, borneol, and verbenone lack repellent properties against M. persicae . Our study contradicts this as we observed that B. brassicae antennae detected linalool, borneol, and verbenone, an indication that these VOCs might elicit species specific response among different species of aphids. Camphor, verbenone and linalool have been found to be the major constituents of R. officinalis volatiles and its oil extracts, responsible for repellence properties against different pests. For instance, they were found to not only repel and induce an anti-appetizing effect on M. persicae but also on the onion aphid N. formosana , mosquitoes and lesser grain borer Rhyzopertha dominica Fabricius (Coleoptera: Bostrichidae) (Hori, 1998 ; Dardouri et al. 2019 ). In conclusion, this study demonstrates that R. officinalis emits VOCs which are repellent to B. brassicae . It therefore provides insights on the use of R. officinalis as a potential repellent plant in the management of B. brassicae through an intercropping strategy. Such an approach would be a promising strategy towards the reduction of synthetic pesticides in management of B. brassicae in smallholder B. oleracea var. acephala production systems. However, field evaluation trials are warranted to validate these findings using B. olearacea var. acephala and R. officinalis intercropping on the B. brassicae infestation, damage, reproduction rate, interactions with its associated natural enemies and yield. Declarations Institutional Review Board Statement No institutional approval was required to conduct the study. Informed Consent Statement No Informed consent was required to conduct this study. Conflicts of Interest The authors declare no conflict of interest. Author Contribution DMM and TD conceived the idea, BKM, DMM, KSA, and ENK designed the study; BKM collected data; BKM, DMM, and BM analysed data; BKM and DMM led the drafting of the manuscript; TD supervised the work and DMM provided resources. All authors critically reviewed and approved the final version. Acknowledgement This research was funded by the Biovision Foundation project “Intensified agroecological based cropping systems to enhance food security, environmental safety, and income of smallholder producers of crucifers and traditional African vegetables in East Africa—AGROVEG” (DPP-020/2022–2024) through the International Centre of Insect Physiology and Ecology ( icipe ). The authors gratefully acknowledge the icipe core funding provided by the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Norwegian Agency for Development Cooperation (Norad); the Federal Democratic Republic of Ethiopia; and the Government of the Republic of Kenya. The views expressed herein do not necessarily reflect the official opinion of the donors. Data Availability Statement The derived data that support the findings of this study will be made available without undue reservation upon request. References Badenes-Perez FR, Shelton AM (2006) Pest management and other agricultural practices among farmers growing cruciferous vegetables in the Central and Western highlands of Kenya and the Western Himalayas of India. 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Entomol Exp Appl 156(1):77–87. https://doi.org/10.1111/eea.12310 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Mar, 2024 Read the published version in Journal of Chemical Ecology → Version 1 posted Editorial decision: Revision requested 13 Jan, 2024 Reviews received at journal 03 Jan, 2024 Reviewers agreed at journal 02 Jan, 2024 Reviewers invited by journal 02 Jan, 2024 Editor assigned by journal 31 Dec, 2023 Submission checks completed at journal 29 Dec, 2023 First submitted to journal 28 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3815776","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264562475,"identity":"9cc5e649-2d60-4d6e-b288-845b2fd2f2b4","order_by":0,"name":"Bretor Katuku Mutua","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Bretor","middleName":"Katuku","lastName":"Mutua","suffix":""},{"id":264562476,"identity":"f2ee414a-0059-4b4b-bdd4-8d4b49839d89","order_by":1,"name":"Thomas Dubois","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Dubois","suffix":""},{"id":264562477,"identity":"b57fbe2f-f470-4996-ad0e-59ce8d1ed233","order_by":2,"name":"Komivi Senyo Akutse","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Komivi","middleName":"Senyo","lastName":"Akutse","suffix":""},{"id":264562478,"identity":"92dd9c44-b57b-4d52-9dd7-c2ab75181837","order_by":3,"name":"Benjamin Muli","email":"","orcid":"","institution":"South Eastern Kenya University","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"","lastName":"Muli","suffix":""},{"id":264562479,"identity":"cbcc74f1-06ab-4cf0-a4d8-abd072fceb8b","order_by":4,"name":"Edward Nderitu Karanja","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Edward","middleName":"Nderitu","lastName":"Karanja","suffix":""},{"id":264562480,"identity":"36dc5f32-1476-45b1-900f-9086328d99f5","order_by":5,"name":"Daniel Munyao Mutyambai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDCCAxAqgYGZ+cABBgPitDA2QLSwJZCqhYGHKPUMDHzXzpg/5qnZlsffzvPxwI+CO3IM7L2PX+DTInk7x7CZ59jtYonDvBsO9hg8M2bgOW5mgU+LAVgL2+3EBqCWwwwGhxMbJNLY8DoRouXf7cT5h3kegLTUE6eFt+124obDPAwgLQkMEmnMD/D7Ja1w5ty+28WGh9kMQH4xbOM5xoZPBwPf7eQNH958u50nd/7w4w8//tyR52dvY/6AVw8QMPEg2AcYgFawSRDSwvgDWQsQELZlFIyCUTAKRhQAAA1aVGbrKPILAAAAAElFTkSuQmCC","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"Munyao","lastName":"Mutyambai","suffix":""}],"badges":[],"createdAt":"2023-12-28 09:01:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3815776/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3815776/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10886-024-01485-y","type":"published","date":"2024-03-12T15:00:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49042003,"identity":"bfdb7dba-6fc1-4634-8977-1612f0dea73c","added_by":"auto","created_at":"2024-01-02 05:42:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34698,"visible":true,"origin":"","legend":"\u003cp\u003eBehavioral response of \u003cem\u003eBrevicoryne brassicae\u003c/em\u003eto naturally emitted constitutive volatiles from \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003eand \u003cem\u003eRosmarinus officinalis\u003c/em\u003e plants (A) and their headspace volatiles (B) in a four-arm olfactometer. Time spent by \u003cem\u003eBrevicoryne brassicae\u003c/em\u003e was observed for 20 min (N=12). Means (± SE) with different letter above the bars are significantly different.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3815776/v1/b2cdc07b4b004df9fb628eac.png"},{"id":49041805,"identity":"8d7ec956-9803-463b-b75d-4942ba7ab786","added_by":"auto","created_at":"2024-01-02 05:34:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180022,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative gas chromatography-mass spectroscopy chromatogram of \u003cem\u003eRosmarinus officinalis\u003c/em\u003e(A) and \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (B) plants. Identities of labelled peaks are represented in Table 1 below.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3815776/v1/ca3795b431184d7a15d39ddb.png"},{"id":49041804,"identity":"585b45eb-da03-4ac5-92b4-2060a782e366","added_by":"auto","created_at":"2024-01-02 05:34:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":84644,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap clustering showing the abundance (in decreasing color intensity) of volatile organic compounds across replicates of \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eRosmarinus officinalis \u003c/em\u003eplants.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3815776/v1/3bf213f428680a245ed58dc4.png"},{"id":49041802,"identity":"e00380b1-f2c6-47ac-a5a0-36f950881de6","added_by":"auto","created_at":"2024-01-02 05:34:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":127585,"visible":true,"origin":"","legend":"\u003cp\u003eGas chromatography-electroantennography active compounds from \u003cem\u003eBrassica oleracea \u003c/em\u003evar.\u003cem\u003e acephala \u003c/em\u003e\u003cstrong\u003e(A)\u003c/strong\u003eand\u003cem\u003e Rosmarinus officinalis \u003c/em\u003e\u003cstrong\u003e(B)\u003c/strong\u003e plant volatiles.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3815776/v1/1f435bc0890c84dc6eed7082.png"},{"id":52908189,"identity":"59f4ef5d-edac-467a-9680-0de5f31bf9b8","added_by":"auto","created_at":"2024-03-18 15:14:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":933765,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3815776/v1/c423bff1-a8ac-4d39-a77a-24fa89d5aaad.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electrophysiological and behavioral responses of cabbage aphid (Brevicoryne brassicae) to rosemary (Rosmarinus officinalis) volatiles, a potential push plant for vegetable push-pull cropping system","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eKale (\u003cem\u003eBrassica oleracea\u003c/em\u003e L. var. \u003cem\u003eacephala\u003c/em\u003e) is a leafy vegetable of global importance, primarily cultivated by small-scale farmers for both subsistence and income generation, particularly in tropical and subtropical regions (Mutiga et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Peris and Kiptoo, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Šamec et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). According to the Center for Disease Control (CDC), \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e was ranked 15th of the 47 powerhouse fruits and vegetables, producing more than 17 essential nutrients (CDC, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e has garnered significant attention recently owing to its notable health advantages. It contains phytochemicals that have been linked to reduced risk of cancer and other chronic diseases, due to antioxidant properties and high dietary fiber content (Šamec et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e is known for its resilience to adverse effects of climate change, rendering it adaptable to extreme climatic conditions (Lagerkvist et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In Kenya, \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e has become increasingly popular due to its ability to maximize land use and address food security and nutrition concerns amidst challenges such as land degradation and population pressure (Mutiga et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Olwande et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; HCD \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Due to the low input and labour requirements for \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e production, the crop stands out as one of the most accessible vegetables to cultivate (Lans et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Canwat et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Its cost-effective production methods contribute to relatively low market prices, ensuring affordability for consumers. Consequently, it is widely consumed in households and extensively sold in urban areas (Ngolo Otieno, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite these benefits, the successful production and productivity of \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e face various constraints such as pests and disease pressures, poor soils, limited market access, climate change and inadequate production techniques (Mutiga et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The cabbage aphid, \u003cem\u003eBrevicoryne brassicae\u003c/em\u003e (L.) (Hemiptera: Aphididae) is one of the most destructive insect pest that affects production of \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and other \u003cem\u003eBrassica\u003c/em\u003e sp. crops worldwide (Cole \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Gill et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The pest is native to Europe but has been reported in many parts of the world (Gill et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Munthali and Tshegofatso, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The adults feed on the sap of plant tissues using their piercing-sucking mouthparts, causing direct crop damage through wilting, stunted growth and deformation, and transmits diseases such as mosaic virus and ring necrosis, which eventually result in plant death (Powell et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Mutiga et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Chalise and Dawadi, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). \u003cem\u003eBrevicoryne brassicae\u003c/em\u003e has a wide host range of crops belonging to Brassicaceae family such as kale (\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala)\u003c/em\u003e, cabbage (\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003ecapitata)\u003c/em\u003e, Brussels sprout \u003cem\u003e(Brassica oleracea var. gemmifera)\u003c/em\u003e and Broccoli (\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eitalica\u003c/em\u003e) (Douloumpaka and Van Emden, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Van Emden and Harrington, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; D\u0026ouml;ring, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSmallholder farmers with limited resources have resorted to indiscriminate use of synthetic insecticides to control the pest (Badenes-Perez and Shelton, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Ngolo Otieno, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The repeated use of these chemical insecticides has resulted in additional economic costs to farmers, insecticide resistance and pests resurgences, and has proven detrimental to agrobiodiversity, human and environmental health (Kianmatee and Ranamukhaarachchi, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Macharia and Afr, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ngolo et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ricupero et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). There is therefore an urgent need to develop alternative control options which will be ecologically friendly, cost-effective, sustainable and suitable for resource-limited vegetable farmers in Africa.\u003c/p\u003e \u003cp\u003eThe push pull cropping system is one of such sustainable management options that has been successfully used in cereal pests control (Khan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This is a habitat management strategy that uses plant semiochemicals to manipulate the distribution of pests and their natural enemies through production of volatile organic compounds (VOCs) in the natural ecosystem, which play an important role in communication, defense and response to abiotic stresses (Khan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The push/repellent plant produces VOCs that have the ability to mask the host plant volatiles, attract natural enemies or deter the pest from landing on the host plant (Cook et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Host location involves perception of specific or a blend of VOCs naturally emitted into the ecosystem which determine attraction or avoidance (Zhang and Chen, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As such, non-host plant volatiles can be used to modify the behavior of pests by interfering with their host selection and orientation. Previous studies have demonstrated the potential of rosemary (\u003cem\u003eRosmarinus officinalis\u003c/em\u003e), an aromatic perennial herb of Lamiaceae family, as an insect repellent plant, showcasing its effectiveness against a wide range of insects pests \u003cem\u003e(\u003c/em\u003eCloyd et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Cook et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Dardouri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Elhalawany et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Waithaka et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhang and Chen, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). For example, applications of different doses of \u003cem\u003eR. officinalis\u003c/em\u003e leaf extracts and essential oils have demonstrated their efficacy as repellents against two-spotted spider mite (\u003cem\u003eTetranychus urticae\u003c/em\u003e Koch (Trombidiformes: Tetranychidae)) and citrus brown mite (\u003cem\u003eEutetranychus orientalis\u003c/em\u003e Klein (Trombidiformes: Tetranychidae)) (Elhalawany et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, laboratory bioassays with different \u003cem\u003eR. officinalis\u003c/em\u003e species have demonstrated their ability to exhibit repellent properties towards green peach aphid (\u003cem\u003eMyzus persicae\u003c/em\u003e Sulzer (Hemiptera: Aphididae)) through the production of different VOCs (Dardouri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, intercropping \u003cem\u003eR. officinalis\u003c/em\u003e with sweet pepper (\u003cem\u003eCapsicum annuum\u003c/em\u003e L. Solanaceae) in a greenhouse experiment in China was found to suppress the population of \u003cem\u003eM. persicae\u003c/em\u003e, thrips (\u003cem\u003eFrankliniella intonsa\u003c/em\u003e Trybom (Thysanoptera: Thripidae)), and silverleaf whitefly (\u003cem\u003eBemisia tabaci\u003c/em\u003e Gennadius (Hemiptera: Aleyrodidae)) without affecting the population dynamics of natural enemies (Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The repulsive effect of \u003cem\u003eR. officinalis\u003c/em\u003e in these studies have been attributed to emission of VOCs which are repellent to the pests. Despite these studies demonstrating the repellence ability of \u003cem\u003eR. officinalis\u003c/em\u003e, its activity against \u003cem\u003eB. brassicae\u003c/em\u003e has not been investigated.\u003c/p\u003e \u003cp\u003eTherefore, in this study, we (1) investigated the behavioral response of \u003cem\u003eB. brassicae\u003c/em\u003e to \u003cem\u003eR. officinalis\u003c/em\u003e and \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e headspace volatiles; (2) identified and compared the discriminant VOCs in the two plants; and (3) used Gas chromatography- electroantennography to determine the responses of \u003cem\u003eB. brassicae\u003c/em\u003e antenna to \u003cem\u003eR. officinalis\u003c/em\u003e and \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e headspace volatiles.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePlants\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (var. simlaw select) seeds were purchased from Simlaw Seeds Company Limited, Nairobi, Kenya. The seeds were sown in a 2 \u0026times; 1 m nursery bed at the International Centre of Insect Physiology and Ecology (\u003cem\u003eicipe\u003c/em\u003e), Nairobi, Kenya (01\u0026ordm; 13\u0026rsquo; 25.6\u0026rdquo; S 036\u0026ordm; 53\u0026rsquo; 49.1\u0026rdquo; E, 1616 m above sea level) and allowed to grow for three weeks, after which the seedlings were transplanted individually into 5 L plastic pots. The pots were filled with soil and organic manure mixed in a ratio of 2:1 and were maintained in an insect-proof screenhouse in the same location. Irrigation was done manually once a day. Plants did not receive any synthetic insecticides or fertilizer inputs. \u003cem\u003eRosmarinus officinalis\u003c/em\u003e (var. Tuscan Blue) was propagated vegetatively through stem cuttings obtained from Kimplanter Seedlings and Nurseries located at Thika, Kenya and received the same treatment as \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e. Six weeks old \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and eight weeks old \u003cem\u003eR. officinalis\u003c/em\u003e plants were used for experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInsects\u003c/h2\u003e \u003cp\u003eAn initial colony of the \u003cem\u003eB. brassicae\u003c/em\u003e was established with insects obtained from smallholder \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e farms in Limuru, Kenya (1\u0026deg; 10' 9.13\" S, 36\u0026deg; 41' 25.18\" E, 2500 m above sea level). Adult \u003cem\u003eB. brassicae\u003c/em\u003e were reared on \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e plants in 50 \u0026times; 80 x 40 cm Perspex rearing cages in the laboratory and maintained at the temperature of 25\u0026thinsp;\u0026plusmn;\u0026thinsp;1 \u0026ordm;C, 65\u0026thinsp;\u0026plusmn;\u0026thinsp;5% relative humidity (RH) and 12L: 12D hrs photoperiod as a modification of Chalise and Dawadi (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) who reared the aphids at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 55\u0026thinsp;\u0026plusmn;\u0026thinsp;5% Relative Humidity. Freshly potted \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e plants were provided after every three days for feeding and reproduction. After 10 days, the newly emerged adults were transferred to a separate rearing cage, fed with \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e plants and later used for bioassays. After every two weeks, field collected insects were infused into the laboratory colony to maintain behavioral characteristics and avoid genetic decay. Insects were reared on \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e for 10 generations prior to the bioassays. All the aphids used for bioassays were fourteen days old.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCollection of volatiles using headspace technique\u003c/h2\u003e \u003cp\u003eHeadspace sampling technique was used to collect volatiles from experimental plants (\u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e) and a control (empty polyethylene terephthalate bag) for 24 h, starting at the first two hours of the photo phase as described by Mutyambai et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The aerial parts of the plants were gently enclosed inside polyethylene terephthalate (PET) bags ( ̴ 12.5 mm thickness, volume 3.2 L), heated to 150\u0026deg;C for 30 min before use, and fitted with Swagelok inlet and outlet ports (Mutyambai et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Charcoal-filtered air was passed through the inlet port at a flow rate of 600 mL min\u003csup\u003e\u0026minus;1\u003c/sup\u003e. VOCs were collected on Charcoal filters (0.05 g, 60/80 mesh, Supelco, USA) inserted into the outlet through which air was drawn at 400 mL min\u003csup\u003e\u0026minus;1\u003c/sup\u003e. After trapping, the entrained volatiles were eluted using 250 \u0026micro;L dichloromethane (analytical grade, Sigma-Aldrich, USA) in 2 mL micro vials (Agilent Technologies, Warsaw, Poland) and stored in a -40\u0026deg;C freezer before further chemical analysis and bioassays. Entrainments from each host plant were replicated four times and each plant was used only once.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOlfactometer bioassay\u003c/h2\u003e \u003cp\u003eTwo separate sets of experiments were carried out to evaluate the olfactory response of \u003cem\u003eB. brassicae\u003c/em\u003e using a Perspex four-arm olfactometer as described by Mutyambai et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In the first experiment, the two opposite arms of the olfactometer were directly connected to \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e plants respectively, while the remaining two arms were connected to empty bags (control arms). Charcoal-filtered air at a rate of 300 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was pumped into the headspace of the test plants enclosed in heat-sterilized PET bags (control), positioned away from the olfactometer arena to prevent any visual cues. In order not to contaminate the headspace plant volatiles, the pots were wrapped with aluminum foil leaving only the aerial part exposed. A suction tube was used to simultaneously draw air from the plants to the olfactometer at a rate of 100 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to enable the movement of the plant volatiles (25 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eper arm), and air was then exhausted from the laboratory (Lohonyai et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Fourteen-day-old \u003cem\u003eB. brassicae\u003c/em\u003e were individually placed in Petri dish (90 \u0026times; 20 mm) and kept in the laboratory for 1 h to acclimatize prior to the bioassay. They were then introduced individually at the center of the olfactometer and allowed to make choice.\u003c/p\u003e \u003cp\u003eIn the second experiment, a choice test was conducted to determine the response of \u003cem\u003eB. brassicae\u003c/em\u003e to constitutive test plant-derived volatiles and solvent (DCM) control. The two opposite arms held 10 \u0026micro;l aliquots of each of the plants\u0026rsquo; headspace samples while the other two opposing arms held 10 \u0026micro;l of solvent as controls. The headspace samples were applied to a filter paper (4 \u0026times; 25 mm) using a micropipette (Drummond Scientific, Broomall, USA) and placed at the inlet of the olfactometer arms. \u003cem\u003eBrevicoryne brassicae\u003c/em\u003e were then introduced at the center of the olfactometer with a fine camel hairbrush and allowed to make a choice. To enable the insect to detect the volatiles, a suction pump was connected to the olfactometer, facilitating the suction of air containing the volatiles from the arms to the center of the olfactometer at a rate of 25 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. In both experiments, the duration of time spent by the insect in each arm of the olfactometer was recorded using Olfa- (F. Nazzi, Udine, Italy) (Mutyambai et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Twelve aphids were tested and each insect was used only once. The olfactometer was rotated every 4 min to avoid positional and directional bias. The insects were observed for 20 min and each olfactometer was used only once. In the event that an aphid remained stationary for a consecutive duration of 2 min at the center of the olfactometer, it was regarded as inactive, leading to the rejection of that particular replicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAnalyses of volatiles\u003c/h2\u003e \u003cp\u003eThe headspace volatiles from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e were analyzed using gas chromatograph-mass spectrometry (GC-MS; 7890A GC and MSD 5975C triple-axis; Agilent Technologies, Palo Alto, USA). The GC-MS was configured to operate in an electron impact ionization mode of 70 eV. A HP5-MSI low-bleed capillary column with dimensions of 30 m length \u0026times; 0.25 mm inner diameter \u0026times; 0.25 \u0026micro;m film thickness (J \u0026amp; W Scientific, Folsom, USA). A flow rate of 1.2 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of helium gas was employed as the carrier gas. The oven temperature was initially set at 35\u0026deg;C for 5 min and then increased at a rate of 10\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e until reaching a final temperature of 280\u0026deg;C and held for 10.5 min. The headspace samples were injected into the GC-MS using an autosampler in measured aliquots (1 \u0026micro;L). The identification of compounds was accomplished by comparing their mass spectra with those obtained from authentic standards, as well as utilizing mass spectra databases of the National Institute of Standards and Technology chemistry webbook (NIST11, Gaithersburg, Maryland). Additionally, retention indices were determined by comparing the retention times of a mixture of n-alkanes ranging from C8 to C23. To ensure further confirmation, a co-injection with available authentic standards was performed under the same experimental conditions. For quantification of the amount (in ng) of identified VOCs, the peak areas were divided by the known quantities of external standards. The emission rate, expressed as ng\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eplant\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eh\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, was determined by multiplying the reciprocal of the proportion of the total headspace utilized and subsequently dividing it by the number of hours in the sampling period. All compounds detected in the control group were deemed contaminants and subsequently disregarded during the identification process. The MSD Chemstation software (v F.01.00.1903; Agilent Technologies, Palo Alto, USA) was employed to analyze the data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCoupled gas chromatography-electroantennography\u003c/h2\u003e \u003cp\u003eAdult \u003cem\u003eB. brassicae\u003c/em\u003e were individually collected from the Perspex rearing cage into a 100 mm x 15mm plastic petri dish. Antennae were prepared by separating the head of ice-chilled \u003cem\u003eB. brassicae\u003c/em\u003e from the rest of the body using a scalpel. Two silver-silver chloride (Ag-AgCl) borosilicate glass micro electrodes, 2 mm o.d. X 1.16 mm i.d. with an inner filament (INR-II, Syntech, Hilversum, the Netherlands) filled with Ringer saline solution (7.5 gl-1 sodium chloride, 0.7 gl-1 potassium chloride, 0.2 gl-1 calcium chloride, 0.2 gl-1 magnesium chloride) as in Maddrell (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1969\u003c/span\u003e) but without glucose were used for electroantennogram recordings. With the help of an electrode holder, the head was placed at the indifferent electrode with the tip of the antenna touching the recording electrode.\u003c/p\u003e \u003cp\u003eThe glass tube featured a side hole through which the column effluent was introduced. The splitter used in this setup was made of glass-lined stainless-steel tubing and deactivated fused silica tubing. VOCs to which \u003cem\u003eB. brassicae\u003c/em\u003e antenna responded to were identified on GC. One \u0026micro;l of the concentrated entrainment sample was injected onto a nonpolar column (HP-1, 50 m \u0026times; 0.32 mm i.d.\u0026times; 0.52 \u0026micro;m film thickness, (Agilent Technologies, California, USA) in a HP5890 GC (Agilent Technologies, Palo Alto, USA) equipped with a cool on-column injector and a flame ionization detector (FID). The oven temperature was programmed at 35\u0026deg;C for 2 min and then programmed at 10\u0026deg;C min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 280\u0026deg;C. Hydrogen was used as the carrier gas. Simultaneous recordings of the EAG and FID responses were obtained with specialized software (Electro Antenno Detection 2015 version 1.2.6, Syntech, Hilversum, The Netherlands). The EAD outlet contained an uninterrupted airflow filtered through charcoal at a rate of 400 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e directed to the \u003cem\u003eB. brassicae\u003c/em\u003e antenna. A total of six coupled runs were completed. Only FID peaks which corresponded to an EAG peak in 3 or more replicates were considered electro-physiologically active.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eData was analyzed using R statistical software version 4.2.3 (R Core Team, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The duration of time spent by \u003cem\u003eB. brassicae\u003c/em\u003e in each arm of the olfactometer was first converted into proportions to address dependence of visiting time and log\u003csub\u003e10\u003c/sub\u003e-ratio transformations to allow for analysis of compositional data (Mutyambai et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Piepel and Aitchison, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). For the normal distribution of the data, Shapiro-Wilk test (Shapiro and Wilk, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1965\u003c/span\u003e) was performed before being subjected to analysis of variance (ANOVA), followed by the Student-Newman-Keuls (SNK) test for mean separation whenever treatments were found to be significantly different at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026le;\u0026thinsp;0.05 were considered statistically significant. The emission of compounds from all test plants underwent non-parametric statistical test, the Kruskal Wallis test following the abnormal distribution of the data as determined by the Shapiro-Wilk test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Subsequently, Dunn\u0026rsquo;s multiple pairwise comparison of the means was utilized to differentiate means between the two groups. Furthermore, to assess the contribution of various VOCs to dissimilarities among the test plants, their abundance was compared using a heatmap.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cb\u003eOlfactory response of\u003c/b\u003e \u003cb\u003eBrevicoryne brassicae\u003c/b\u003e \u003cb\u003eto\u003c/b\u003e \u003cb\u003eBrassica oleracea\u003c/b\u003e \u003cb\u003evar.\u003c/b\u003e \u003cb\u003eacephala\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eRosmarinus officinalis\u003c/b\u003e \u003cb\u003eplants and their headspace volatiles\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn the first experiment with individual plant odors from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e plants, or clean air, \u003cem\u003eB. brassicae\u003c/em\u003e showed more preference to the arm containing \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e over the arms with \u003cem\u003eR. officinalis\u003c/em\u003e or clean air (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In the second experiment with odour sources from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e headspace volatiles, or clean air, \u003cem\u003eB. brassicae\u003c/em\u003e showed less preference to the arm containing \u003cem\u003eR. officinalis\u003c/em\u003e volatiles than the arms containing \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e volatiles or clean air (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eVolatile profiles\u003c/h2\u003e \u003cp\u003eGC-MS analysis detected 22 major compounds from the plant headspace samples belonging to three chemical classes: monoterpenes (17), ketones (1) and sesquiterpenes (4) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). Of the identified compounds, nine were detected from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) and 19 from \u003cem\u003eR. officinalis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Common volatiles between the two plants included α-pinene, β-pinene, myrcene, 1,8-cineole, γ-terpinene, camphor and β-caryophyllene with \u003cem\u003eR. officinalis\u003c/em\u003e producing 57, 61, 6, 36, 10, 106 and 274 times more the amount produced by \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e respectively (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). VOCs that were detected in \u003cem\u003eR. officinalis\u003c/em\u003e but not detected in \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e included camphene, α-phellandrene, δ-2- carene, (Z)-sabinene hydrate, linalool, borneol, α-terpineol, verbenone, citronellol, geraniol, bornyl acetate, α-humulene and caryophyllene oxide. Those detected in \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e but not in \u003cem\u003eR. officinalis\u003c/em\u003e included sabinene and limonene (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeatmap clustering showed volatiles obtained from \u003cem\u003eR. officinalis\u003c/em\u003e were more concentrated than those obtained from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It also showed that 1,8-cineole, β-pinene, myrcene and sabinene were the most abundant volatiles in \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e whereas γ-terpinene, camphor, limonene, α-pinene were the least abundant in that order. Additionally, 1,8-cineole was the most abundant volatile in both \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e, while 1,8-cineole, α-pinene, β-caryophyllene, camphor, bornyl acetate and verbenone were the most abundant VOCs in \u003cem\u003eR. officinalis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean amount (ng/plant/h) of volatile organic compounds (VOCs) identified in headspace collection of \u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eRosmarinus officinalis\u003c/em\u003e plants (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRT (min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompound Name\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRI\u003csub\u003ealk\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRI\u003csub\u003eL\u003c/sub\u003e\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eRosmarinus officinalis\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e-pinene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e934\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e410.54\u0026thinsp;\u0026plusmn;\u0026thinsp;159.48\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23,465.15\u0026thinsp;\u0026plusmn;\u0026thinsp;4393.73\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamphene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,914.963\u003c/p\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;607.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSabinene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,274.64\u0026thinsp;\u0026plusmn;\u0026thinsp;746.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ\u003c/em\u003e-pinene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87.00\u0026thinsp;\u0026plusmn;\u0026thinsp;50.44\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,379.80\u0026thinsp;\u0026plusmn;\u0026thinsp;496.49\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emyrcene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e953.28\u0026thinsp;\u0026plusmn;\u0026thinsp;527.07\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,983.69\u0026thinsp;\u0026plusmn;\u0026thinsp;831.85\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e-phellandrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,429.39\u0026thinsp;\u0026plusmn;\u0026thinsp;253.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eδ\u003c/em\u003e-2-carene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,555.28\u0026thinsp;\u0026plusmn;\u0026thinsp;289.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLimonene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,457.36\u0026thinsp;\u0026plusmn;\u0026thinsp;854.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,8-cineole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,232.56\u0026thinsp;\u0026plusmn;\u0026thinsp;622.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40,197.45\u0026thinsp;\u0026plusmn;\u0026thinsp;14,913.86\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eγ\u003c/em\u003e-terpinene*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e381.39\u0026thinsp;\u0026plusmn;\u0026thinsp;359.18\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,907.73\u0026thinsp;\u0026plusmn;\u0026thinsp;632.33\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e(Z)\u003c/em\u003e-sabinene hydrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,955.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1072.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLinalool*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,470.31\u0026thinsp;\u0026plusmn;\u0026thinsp;2507.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCamphor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e118.25\u0026thinsp;\u0026plusmn;\u0026thinsp;53.30\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12,642.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3081.30\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBorneol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,645.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1169.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e-terpineol*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,666.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1261.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVerbenone*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,939.37\u0026thinsp;\u0026plusmn;\u0026thinsp;2333.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCitronellol*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,143.08\u0026thinsp;\u0026plusmn;\u0026thinsp;347.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGeraniol*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,401.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1092.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBornyl acetate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12,775.81\u0026thinsp;\u0026plusmn;\u0026thinsp;2801.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eβ-\u003c/em\u003ecaryophyllene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1430\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.90\u0026thinsp;\u0026plusmn;\u0026thinsp;26.39 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19,141.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3947.36 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e-humulene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,706.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1147.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaryophyllene oxide*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2,971.13\u0026thinsp;\u0026plusmn;\u0026thinsp;491.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* Indicates compounds confirmed with authentic standards. Means (\u0026plusmn;\u0026thinsp;SE) with different superscript letter(s) within the rows are significantly different at the \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level. \"nd\" indicates not detected.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGas chromatography-electroantennography responses of\u003c/b\u003e \u003cb\u003eBrevicoryne brassicae\u003c/b\u003e \u003cb\u003eto\u003c/b\u003e \u003cb\u003eRosmarinus officinalis\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eBrassica oleracea\u003c/b\u003e \u003cb\u003evar.\u003c/b\u003e \u003cb\u003eacephala\u003c/b\u003e \u003cb\u003eheadspace volatiles\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe flame ionization detector (FID) and electroantennographic detector (EAD) were used to detect volatile compounds from \u003cem\u003eR. officinalis\u003c/em\u003e and \u003cem\u003eB. oleracea\u003c/em\u003e va\u003cem\u003er. acephala\u003c/em\u003e plants by \u003cem\u003eB. brassicae\u003c/em\u003e antennae. The GC-EAD recordings showed that \u003cem\u003eB. brassicae\u003c/em\u003e elicited antennal response to three compounds from \u003cem\u003eB. oleracea\u003c/em\u003e va\u003cem\u003er. acephala\u003c/em\u003e namely sabinene, γ-terpinene and β-caryophyllene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) and seven active compounds from \u003cem\u003eR. officinalis\u003c/em\u003e namely linalool (12), camphor (13), borneol (14), α-terpineol (15), verbenone (16), geraniol (18) and bornyl acetate (19) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur findings from the current study revealed that \u003cem\u003eB. brassicae\u003c/em\u003e were more attracted to constitutive and headspace volatiles of \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (their main host) and were repelled by \u003cem\u003eR. officinalis\u003c/em\u003e as a whole plant and its headspace volatiles. These observations align with the results reported by Cai et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) where \u003cem\u003eM. persicae\u003c/em\u003e were found to be attracted by cabbage (\u003cem\u003eBrassica oleracea\u003c/em\u003e var. \u003cem\u003ecapitata)\u003c/em\u003e volatiles, one of their major host. The reduced attraction of \u003cem\u003eB. brassicae\u003c/em\u003e to \u003cem\u003eR. officinalis\u003c/em\u003e plant volatiles as demonstrated in the current study is in agreement with the results reported by Cai et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Dardouri et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), where the authors demonstrated that \u003cem\u003eM. persicae\u003c/em\u003e preferred a blank chamber over the ones containing \u003cem\u003eR. officinalis\u003c/em\u003e, which emitted VOCs in relatively higher amounts. Non-host plant odors contribute to the repellent and deterrent effects observed in push plants such as the Greenleaf desmodium (\u003cem\u003eDesmodium uncinatum\u003c/em\u003e) and molasses grass (\u003cem\u003eMelinis minutiflora)\u003c/em\u003e used in cereal push pull cropping systems leading to reduced pest infestation and plant damage (Khan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Similarly, \u003cem\u003eR. officinalis\u003c/em\u003e volatiles could mask the host plant attractive VOCs from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e given its higher emission of some of the repellent volatile compounds making it difficult for \u003cem\u003eB. brassicae\u003c/em\u003e to perceive its host in presence of the repellent \u003cem\u003eR. officinalis\u003c/em\u003e volatiles.\u003c/p\u003e \u003cp\u003eChemical analysis of headspace volatiles showed that \u003cem\u003eR. officinalis\u003c/em\u003e produced more terpenes as compared to \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The most abundant VOCs in \u003cem\u003eR. officinalis\u003c/em\u003e included 1,8-cineole, camphor, verbenone, bornyl acetate, linalool and citronellol. Majority of these compounds have been associated with repellence properties against different insects species when used as plant extracts and essential oils (Miresmailli and Isman, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Cloyd et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Webster, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Dayaram and Khan, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Comparable results on \u003cem\u003eR. officinalis\u003c/em\u003e essential oils were reported by Elhalawany et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), who observed that the major constituents of \u003cem\u003eR. officinalis\u003c/em\u003e oil was mostly made of linalool, \u003cem\u003eα\u003c/em\u003e-pinene, limonene, bornyl acetate and β-caryophyllene. \u003cem\u003eRosmarinus officinalis\u003c/em\u003e produced 1,8-cineole 36-fold the amount produced by \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e. Additionally, verbenone, linalool and β-caryophyllene were found to be the other two most abundant VOCs. This is in tandem with previous studies that reported verbenone, 1\u0026ndash;8 cineole and linalool as the major constituents of \u003cem\u003eR. officinalis\u003c/em\u003e volatiles and its oil extracts (Hori, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). \u003cem\u003eRosmarinus officinalis\u003c/em\u003e emitted a higher quantity of volatiles as compared to \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e, which are responsible for its characteristic aroma. The high abundance of these major compounds is evidence that \u003cem\u003eR. officinalis\u003c/em\u003e, being an aromatic herb produces such compounds in very high amounts, which the insect can perceive from a far and avoid them, while masking the host plant volatiles.\u003c/p\u003e \u003cp\u003eHost location by \u003cem\u003eB. brassicae\u003c/em\u003e involves the perception of the volatiles by the sensilla of the insect\u0026rsquo;s antenna. The GC-EAD gives an opportunity to utilize these antennae and under controlled volumes, determine which among the volumes of the volatiles are responsible for the behavior of the insect. The findings of this study indicate that \u003cem\u003eB. brassicae\u003c/em\u003e\u0026rsquo;s antenna responded to sabinene, γ-terpinene and β-caryophyllene from \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Sabinene was one of the major constituent volatiles in \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e but was not observed in \u003cem\u003eR. officinalis\u003c/em\u003e. Additionally, despite γ-terpinene and β-caryophyllene being found in both plants, \u003cem\u003eB. brassicae\u003c/em\u003e antenna didn\u0026rsquo;t show any antennal response when \u003cem\u003eR. officinalis\u003c/em\u003e volatiles were used. However, \u003cem\u003eB. brassicae\u003c/em\u003e antenna showed antennal response to linalool, camphor, borneol, α-terpineol, verbenone, geraniol and bornyl acetate from \u003cem\u003eR. officinalis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Among the \u003cem\u003eR. officinalis\u003c/em\u003e compounds that caused antennal response, bornyl acetate, camphor and α-terpineol have been reported to reduce the activities of \u003cem\u003eM. persicae\u003c/em\u003e and other insects such as mosquitoes (Dardouri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The insect\u0026rsquo;s antenna did not show any response to 1,8-cineole despite it being a major constituent of \u003cem\u003eR. officinalis\u003c/em\u003e oil. However, some studies have reported its insecticidal activity against onion aphid, \u003cem\u003eNeotoxoptera formosana\u003c/em\u003e Takahashi (Hemiptera: Aphididae) (Hori, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Elhalawany et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Camphor, citronellal and geraniol, have also been reported to have high insecticidal activity against aphids by disrupting their digestive and neurological enzymes hence leading to death (Chalise \u0026amp; Dawadi, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); therefore, their presence in the volatiles emitted by \u003cem\u003eR.\u003c/em\u003e officinalis could have contributed to the observed repellence behavior exhibited by \u003cem\u003eB. brassicae\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eOur electrophysiological study confirms the results of laboratory bioassays with \u003cem\u003eR. officinalis\u003c/em\u003e volatiles which showed that linalool, camphor, and α-terpineol were repellent to \u003cem\u003eB. brassicae\u003c/em\u003e as opposed to other compounds in \u003cem\u003eR. officinalis\u003c/em\u003e bouquet. Similar results were obtained with \u003cem\u003eM. persicae\u003c/em\u003e (Hori, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Li et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) reported the presence of monoterpenes such as α-pinene, 1,8-cineole, camphor, camphene, and verbenone as the most abundant repellent compounds in \u003cem\u003eR. officinalis.\u003c/em\u003e Conflictingly, \u003cem\u003eB. brassicae\u003c/em\u003e did not show any electrophysiological response to 1,8-cineole and camphene. Bruce et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and Dardouri et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) documented that α-pinene, camphene, limonene, γ-terpinene, linalool, borneol, and verbenone lack repellent properties against \u003cem\u003eM. persicae\u003c/em\u003e. Our study contradicts this as we observed that \u003cem\u003eB. brassicae\u003c/em\u003e antennae detected linalool, borneol, and verbenone, an indication that these VOCs might elicit species specific response among different species of aphids. Camphor, verbenone and linalool have been found to be the major constituents of \u003cem\u003eR. officinalis\u003c/em\u003e volatiles and its oil extracts, responsible for repellence properties against different pests. For instance, they were found to not only repel and induce an anti-appetizing effect on \u003cem\u003eM. persicae\u003c/em\u003e but also on the onion aphid \u003cem\u003eN. formosana\u003c/em\u003e, mosquitoes and lesser grain borer \u003cem\u003eRhyzopertha dominica\u003c/em\u003e Fabricius (Coleoptera: Bostrichidae) (Hori, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Dardouri et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, this study demonstrates that \u003cem\u003eR. officinalis\u003c/em\u003e emits VOCs which are repellent to \u003cem\u003eB. brassicae\u003c/em\u003e. It therefore provides insights on the use of \u003cem\u003eR. officinalis\u003c/em\u003e as a potential repellent plant in the management of \u003cem\u003eB. brassicae\u003c/em\u003e through an intercropping strategy. Such an approach would be a promising strategy towards the reduction of synthetic pesticides in management of \u003cem\u003eB. brassicae\u003c/em\u003e in smallholder \u003cem\u003eB. oleracea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e production systems. However, field evaluation trials are warranted to validate these findings using \u003cem\u003eB. olearacea\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e and \u003cem\u003eR. officinalis\u003c/em\u003e intercropping on the \u003cem\u003eB. brassicae\u003c/em\u003e infestation, damage, reproduction rate, interactions with its associated natural enemies and yield.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eInstitutional Review Board Statement\u003c/h2\u003e\n\u003cp\u003eNo institutional approval was required to conduct the study.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eNo Informed consent was required to conduct this study.\u003c/p\u003e\n\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eDMM and TD conceived the idea, BKM, DMM, KSA, and ENK designed the study; BKM collected data; BKM, DMM, and BM analysed data; BKM and DMM led the drafting of the manuscript; TD supervised the work and DMM provided resources. All authors critically reviewed and approved the final version.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThis research was funded by the Biovision Foundation project \u0026ldquo;Intensified agroecological based cropping systems to enhance food security, environmental safety, and income of smallholder producers of crucifers and traditional African vegetables in East Africa\u0026mdash;AGROVEG\u0026rdquo; (DPP-020/2022\u0026ndash;2024) through the International Centre of Insect Physiology and Ecology (\u003cem\u003eicipe\u003c/em\u003e). The authors gratefully acknowledge the \u003cem\u003eicipe\u003c/em\u003e core funding provided by the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Norwegian Agency for Development Cooperation (Norad); the Federal Democratic Republic of Ethiopia; and the Government of the Republic of Kenya. The views expressed herein do not necessarily reflect the official opinion of the donors.\u003c/p\u003e\n\u003ch2\u003eData Availability Statement\u003c/h2\u003e\n\u003cp\u003eThe derived data that support the findings of this study will be made available without undue reservation upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBadenes-Perez FR, Shelton AM (2006) Pest management and other agricultural practices among farmers growing cruciferous vegetables in the Central and Western highlands of Kenya and the Western Himalayas of India. 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Imperial College London\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Z, Chen Z (2015) Non-host plant essential oil volatiles with potential for a push-pull strategy to control the tea green leafhopper, \u003cem\u003eEmpoasca vitis\u003c/em\u003e. Entomol Exp Appl 156(1):77\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/eea.12310\u003c/span\u003e\u003cspan address=\"10.1111/eea.12310\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Agroecology, Cabbage aphid, Integrated pest management, Kale, Rosemary","lastPublishedDoi":"10.21203/rs.3.rs-3815776/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3815776/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe cabbage aphid (\u003cem\u003eBrevicoryne brassicae\u003c/em\u003e) is a major pest of kale (\u003cem\u003eBrassica oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e), an important vegetable that is grown worldwide due to its high nutritional and economic value. \u003cem\u003eBrevicoryne brassicae\u003c/em\u003e poses a great challenge to \u003cem\u003eB. oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e production, causing significant direct and indirect yield losses. Farmers overly rely on synthetic insecticides to manage the pest with limited success owing to its high reproductive behavior and development of resistance. This necessitates search for sustainable alternatives to mitigate these challenges. This study assessed behavioral responses of \u003cem\u003eB. brassicae\u003c/em\u003e to odors from rosemary (\u003cem\u003eRosmarinus officinalis\u003c/em\u003e) and \u003cem\u003eB. oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e headspace volatiles in a Perspex four-arm olfactometer. We identified and quantified volatiles emitted by each of the two plants and those eliciting behavioral response using coupled gas chromatography-mass spectrometry (GC-MS) and gas chromatography-electroantennogram (GC-EAG), respectively. Our findings revealed that \u003cem\u003eB. brassicae\u003c/em\u003e spent more time in the arms of the olfactometer that contained \u003cem\u003eB. oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e volatiles compared to the arm that held \u003cem\u003eR. officinalis\u003c/em\u003e volatiles. GC-MS analysis revealed diverse and higher quantities of volatile compounds in \u003cem\u003eR. officinalis\u003c/em\u003e compared to \u003cem\u003eB. oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e. GC-EAG showed that \u003cem\u003eB. brassicae\u003c/em\u003e was responsive to linalool, camphor, borneol, α-terpineol, verbenone, geraniol and bornyl acetate from \u003cem\u003eR. officinalis\u003c/em\u003e and sabinene, γ-terpinene, and β-caryophyllene from \u003cem\u003eB. oleraceae\u003c/em\u003e var. \u003cem\u003eacephala\u003c/em\u003e. Our findings demonstrate that \u003cem\u003eR. officinalis\u003c/em\u003e is repellent against \u003cem\u003eB. brassicae\u003c/em\u003e and could be utilized as a \u0026lsquo;push\u0026rsquo; plant in an intercropping strategy against this pest.\u003c/p\u003e","manuscriptTitle":"Electrophysiological and behavioral responses of cabbage aphid (Brevicoryne brassicae) to rosemary (Rosmarinus officinalis) volatiles, a potential push plant for vegetable push-pull cropping system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 05:34:55","doi":"10.21203/rs.3.rs-3815776/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-13T09:10:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-03T08:13:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c11f6a17-971f-4642-adf2-451d844f08b5","date":"2024-01-02T16:05:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-02T13:58:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-31T16:15:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-29T11:52:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Chemical Ecology","date":"2023-12-28T08:58:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7ad3b9ca-16a3-4905-802e-51fd38353344","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-18T15:13:10+00:00","versionOfRecord":{"articleIdentity":"rs-3815776","link":"https://doi.org/10.1007/s10886-024-01485-y","journal":{"identity":"journal-of-chemical-ecology","isVorOnly":false,"title":"Journal of Chemical Ecology"},"publishedOn":"2024-03-12 15:00:55","publishedOnDateReadable":"March 12th, 2024"},"versionCreatedAt":"2024-01-02 05:34:55","video":"","vorDoi":"10.1007/s10886-024-01485-y","vorDoiUrl":"https://doi.org/10.1007/s10886-024-01485-y","workflowStages":[]},"version":"v1","identity":"rs-3815776","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3815776","identity":"rs-3815776","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}