Biochemical Systematics and Ecology 34 (2006) 609e616 www.elsevier.com/locate/biochemsyseco

Antifeedant effects and chemical composition of essential oils from different populations of Lavandula luisieri L. Azucena Gonza´lez-Coloma a,*, Darı´o Martı´n-Benito a, Nagla Mohamed a, Ma Concepcio´n Garcı´a-Vallejo b, Ana Cristina Soria c b

a Instituto de Ciencias Agrarias, CSIC, Serrano 115-dpdo, 28006 Madrid, Spain Centro de Investigacio´n Forestal, Instituto Nacional de Investigacio´n y Tecnologı´a Agraria y Alimentaria, Ctra. La Corun˜a Km 7.5, 28040 Madrid, Spain c Instituto de Quı´mica Orga´nica General, CSIC, Juan de la Cierva 3, 28006 Madrid, Spain

Received 15 September 2005; accepted 25 February 2006

Abstract Forty-seven individual Lavandula luisieri (Rozeira) Riv.-Mart. plants were grouped into six categories according to their volatile composition using Principal Component Analysis. The essential oils from flowers and leaves from these six groups were analyzed by GCeMS and their antifeedant effects tested against the insect species Spodoptera littoralis, Leptinotarsa decemlineata and Myzus persicae; L. decemlineata and M. persicae being the most sensitive species. The antifeedant effects of these oils could not be justified by the activity of their major components considered individually thus pointing to synergistic effects among the oil components as suggested by a stepwise linear regression of compound concentrations on antifeedant effects for these groups. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Lavandula luisieri; Volatiles; Principal Component Analysis; Antifeedant

1. Introduction Desertification is a land degradation problem of major importance in the world’s arid regions. Approximately 50% of Spain is arid. Virtually all of the rangeland has suffered severe land degradation. Erosion continues on the extensive dry farm lands and desertification effects are evident in the form of soil fertility, soil compaction, and soil crusting (Dregne, 1986). Plants producing significant yields of relatively high valued products such as pharmaceuticals and biologically active materials such as essential oils which have low water requirements that are likely new crop candidates for arid lands (Thompson, 1990). Labiatae species are a source of bioactive essential oils. Some of these oils are efficient insecticides against a wide range of insect pests (Regnault-Roger et al., 1993).

* Corresponding author. Tel.: þ34 917452500; fax: þ34 915640800. E-mail address: [email protected] (A. Gonza´lez-Coloma). 0305-1978/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.bse.2006.02.006

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Lavandula luisieri (Rozeira) Riv.-Mart. is an aromatic Labiatae endemic to the Iberian Peninsula, common in the semi-arid regions of Southern Portugal and Southwest Spain. Essential oils of Lavandula species are of economic value for the fragrance industry. A previous study showed that L. luisieri oil contained several compounds such as 1,8-cineole, lavandulol, linalool and their acetates, also present in other Lavandula species, in addition to a series of compounds with a 1,2,2,3,4-pentamethylcyclopentane (necrodane) structure (Garcı´a-Vallejo, 1992; Garcı´a-Vallejo et al., 1994; Lavoine-Hanneguelle and Casabianca, 2004; Baldovini et al., 2005). These necrodane derivatives have only previously been found in the defensive secretion of a beetle (Necrodes surinamensis) (Roach et al., 1990), suggesting a potential plant defensive role for these compounds. As part of our ongoing search for potential value-added crops to combat soil erosion on semi-arid and arid land, we are assessing the chemotype distribution and bioactive potential of L. luisieri oil. We have previously reported on the distribution of its volatile components obtained by means of direct thermal desorption coupled with gas chromatography and mass spectrometry (Sanz et al., 2004). Quantitative results were obtained for flowers and leaves of 47 individual plants. Samples presented a wide variation in their yield and composition. Major components were camphor and 1,8-cineole (up to 80.9% and 76.7% in leaves, and 87.8% and 85.2% in flowers, respectively). Another major component (up to 60% in flowers and leaves) was 5-methylene-2,3,4,4-tetramethylcyclopent-2-enone. In this work, L. luisieri samples from two locations were grouped according to their volatile composition subsequent to Principal Component Analysis of quantitative data from nine selected volatile compounds. The essential oils extracted from the grouped plants were analyzed by GCeMS and their insecticidal properties (insect antifeedant and toxic effects) were tested against Spodoptera littoralis, Leptinotarsa decemlineata (Colorado potato beetle, CPB) and the aphid Myzus persicae to assess its potential as a natural biopesticide. 2. Materials and methods 2.1. Chemicals Fenchone, 1,8-cineole (eucalyptol) and camphor were purchased from Fluka, Buchs, Switzerland. a-Necrodyl acetate and 5-methylene-2,3,4,4-tetramethylcyclopent-2-enone were kindly donated by Dr. S. Lavoine-Hanneguelle and a-necrodol was obtained from Drs. Schulte-Elte and Pamingle (Firmenich, Switzerland). 2.2. Plant material L. luisieri (Rozeira) Riv.-Mart. flowers and leaves from 47 individual plant samples were collected from two locations (South of Toledo and North of Seville, Spain) as described in Sanz et al. (2004). 2.3. Direct thermal desorptionegas chromatographyemass spectrometry (DTDeGCeMS) Volatile fractionation was carried out by means of an ATD 400 thermal desorber (PerkineElmer, Norwalk, CT, USA). Cuttings of dry plant samples (10e20 mg) were inserted into a PTFE tube which was then placed into a stainless steel desorption cartridge. Volatile compounds were desorbed under helium flow at 180
C for 15 min and then cryofocused on a Tenax TA trap at 30
C. This trap was heated to 320
C at w40
C s1; and the desorbed volatiles were transferred to the GC column through a fused-silica line heated to 225
C. The ATD 400 was connected to a GC 8000 gas chromatograph (Fisons, Milan, Italy) coupled to an MD 800 mass detector (Fisons, Manchester, UK). A methyl silicone SPB-1 column (27 m  0.25 mm i.d.  0.25 mm film thickness) was temperature programmed from 60 to 180
C (at 3
C min1) and then to 250
C (at 8
C min1) for 5 min. Helium was used as the carrier gas. Mass spectra were recorded in the electron impact (EI) mode at 70 eV, scanning the 38e350 m/z range. Source temperature was 200
C, and the transfer line was heated to 250
C. Other conditions are detailed elsewhere (Esteban et al., 1993, 1996). Peaks in the TIC (total ion current) profile were identified from their chromatographic retention and their mass spectra by using the NIST and Wiley mass spectral libraries (NIST/EPA/NIH Version 2.0; Wiley, 1989). Percent concentration values were directly calculated from TIC peak areas. Semiquantitative values were obtained by using 2-dodecanone (Fluka Chemie, Buchs, Switzerland) as an internal standard.

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2.4. Data processing Quantitative data were processed by using the BMDP statistical package for PC (BMDP Statistical Software Release 7, 1992). Factor Analysis was carried out in the Principal Component Analysis (PCA) mode using the covariance matrix about the mean without factor rotation (program 4M). The stepwise program was used for the regression analyses (2R). ANOVA and ANCOVA analyses were performed with the Stagraphics statistical package. 2.5. Essential oil distillation Plants showing a volatile composition similar to the DTDeGCeMS results were pooled (groups 1e6). Flowers were manually separated from the twigs and leaves and then distilled separately in a Clevenger-type apparatus according to the method recommended by the European Pharmacopoeia. The flower and leaf essential oils obtained were used in the insect bioassays. 2.6. Essential oil analysis Flower and leaf essential oils were analyzed by GCeMS using an Agilent 6890N gas chromatograph (Agilent Technologies, Palo Alto, California, USA) connected to an Agilent 5973N mass detector (electron ionization, 70 eV) (Agilent Technologies, Palo Alto, California, USA) and equipped with a 30 m  0.25 mm i.d. DB-5MS capillary column (0.25 mm film thickness) (J&W Scientific, Folsom, California, USA). Working conditions were as follows: split (1:20), injector temperature, 260
C; temperature of the transfer line connected to the mass spectrometer, 300
C; column temperature 60
C for 5 min, then heated to 270
C at 4
C min1. Electron ionization (EI) mass spectra and retention times were used to assess the identity of compounds by comparing them with those of standards or found in the database (Wiley 275 Mass Spectra Database, 2001). Quantitative data were obtained from the TIC peak area percentages without the use of response factors. 2.7. Insect bioassays S. littoralis, L. decemlineata and M. persicae colonies were reared on artificial diet, potato foliage (Solanum tuberosum) and bell pepper (Capsicum annuum) plants, respectively, and maintained at 22  1
C, >70% relative humidity with a photoperiod of 16:8 h (L:D) in a growth chamber. 2.7.1. Choice feeding assay These experiments were conducted with adult L. decemlineata, sixth-instar S. littoralis larvae and M. persicae apterous adults. Percent feeding inhibition (%FI) and percent settling inhibition (%SI) were calculated as described by Reina et al. (2001). 2.7.2. Oral cannulation This experiment was performed with pre-weighed newly molted S. littoralis L6-larvae. Each experiment consisted of 20 larvae orally dosed with 40 mg of the test compound in 4 ml of DMSO (treatment) or solvent alone (control) as described in Reina et al. (2001). At the end of the experiments (72 h), larval consumption and growth were calculated on a dry weight basis. An analysis of covariance (ANCOVA1) on biomass gains with initial biomass as covariate (covariate p > 0.05) showed that initial insect weights were similar for all treatments. A second analysis (ANCOVA2) was performed on biomass gains with food consumption as covariate to test for postingestive effects. 3. Results and discussion Flowers and leaves from the 47 individual plants of L. luisieri collected were subjected to DTDeGCeMS analysis; their qualitative and quantitative results having been previously reported by Sanz et al. (2004). The most important volatile compounds found were 1,8-cineole, fenchone, camphor, 5-methylene-2,3,4,4-tetramethylcyclopent-2enone (Baldovini et al., 2005), previously identified as 2,3,5,5-tetramethyl-4-methylen-2-cyclopenten-1-one

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(Lavoine-Hanneguelle and Casabianca, 2004), and a sesquiterpene with a hydroxycadinenone structure. Two compounds structurally related to the ketone (one having an additional hydroxyl group and another one being its acetyl derivative) were also found in relatively high quantities in the chromatograms obtained by DTDeGCeMS, while trans-a-necrodyl acetate and cis-a-necrodyl acetate were present as minor compounds. The distribution of these nine compounds in the 47 samples was then used to pool the plant samples with a similar composition to extract their essential oil. The percent concentration data from leaf volatiles were subjected to Principal Component Analysis. Loadings obtained for the principal components are listed in Table 1. The first principal component, positively related to camphor and negatively to 1,8-cineole and the ketone compounds, accounted for the 63.8% total variance. Camphor and 1,8-cineole were the main positive contributors to the second component (29.6% of variance), while the ketone compounds had negative coefficients. Leaf sample scores were plotted using the first and second components as coordinate axes in PCA analysis (Fig. 1). Samples appear to form two elongated groups which mainly differ in their first component scores. The samples grouped to the right of the plot (high PC1 scores) presented high camphor content (27e80%), while for samples to the left of the plot camphor amount is lower than 8%. The trend exhibited by samples belonging to the left group corresponds to the continuously variable concentration of 1,8-cineole, which ranges from 77% for samples at the top left of the plot, to 0% for the bottom samples, rich in ketones. PCA analysis was also applied to the flower volatile composition (see Table 2). Both the importance and the significance of the first and second principal components were similar to those described for leaf volatile data. First factor (62.5% of variance) was mainly dominated by camphor, while 1,8-cineole and the three ketones presented negative contributions. The second factor (23.8% of variance) was positively related to 1,8-cineole and camphor and negatively to the ketone compounds. Fig. 2 shows the same trends appearing in Fig. 1 but without a gap between groups since camphor concentration varied continuously from 0% (several left plot samples) to 88% (right plot samples). Taking into account the PCA results for both leaves and flowers and likewise plant location (Seville or Toledo), samples were grouped into six types, numbers 1e6 being used as sample labels in Figs. 1 and 2. Flower and leaf samples belonging to a single plant are usually plotted in the same areas of Figs. 1 and 2, although considerable differences in their volatile composition could be observed in some cases. Labels 1 and 2 correspond to Seville samples. Group 1 includes samples rich in 1,8-cineole (Figs. 1 and 2, left), while group 2 at the bottom of the plots is formed by four samples with low 1,8-cineole content. Toledo samples were divided into four groups (labels 3e6). Group 3 samples, with 1,8-cineole as the main component, had composition similar to that of most of the Seville group 1 samples. Toledo samples labeled as 6 were also rich in 1,8-cineole but contained fenchone as well. Samples in group 4 had fenchone as a major component while group 5 (Figs. 1 and 2, right) included most of the camphor-rich Toledo samples. Fenchone concentration did not seem to be related to those of other volatile compounds; it only appeared as a significant loading in the fourth component for leaves and in the third component for flowers. Direct thermal desorptioneGCeMS is a technique well suited for on-line plant volatile analyses using small amounts, while the isolation of a representative volatile fraction for further tests requires a preparative technique such as hydrodistillation. Both techniques yielded volatile fractions with different compositions in labile components. Although the presence of 1,8-cineole, fenchone, camphor and 5-methylene-2,3,4,4-tetramethylcyclopent-2-enone in the essential oils from leaves and flowers of plants from groups 1 to 6 was similar to that obtained by DTDeGCeMS, the ketone derivatives and the hydroxycadinenone sesquiterpene are not present in the essential oils obtained which instead present a hydroxyketone (C10H14O2) and two hydroxyketone acetates (C12H18O3) probably structurally

Table 1 Principal Component Analysis results for leaf volatiles data (see Section 3 for component code numbers) Explained variance (%)

PC1 PC2 PC3 PC4

63.8 29.6 4.4 1.7

Principal component loadings for leaf samples 1

2

3

4

5

6

7

8

9

16.80 14.91 0.09 1.11

0.42 0.74 0.99 3.94

25.26 7.14 0.09 1.16

4.00 8.81 5.71 1.99

0.00 0.15 0.19 0.13

0.01 0.32 0.12 0.15

1.40 3.16 0.58 0.85

3.36 8.92 5.58 1.46

0.71 0.04 0.23 0.66

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Leaf volatiles 2

PC axis 2

1

0

-1

-2 -1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

PC axis 1 Fig. 1. Plot of the scores of leaf samples using as coordinate axes the first and second components in PCA analysis.

related to the former compounds. The marked differences in composition obtained for groups 1e6 indicate that the pooling process from thermal desorption data was properly performed. Table 3 shows the yields of the leaf and flower essential oils from groups 1 to 6 and the concentration of the main components of each essential oil. In general, leaves were richer in essential oil than flowers. Plants from group 1 (rich in 1,8-cineole, from Seville), group 5 (rich in camphor, from Toledo) and group 6 (rich in fenchone and 1,8-cineole, from Toledo) gave the highest yields. Leaf essential oils were richer in 1,8-cineole, 5-methylene-2,3,4,4-tetramethylcyclopent-2-enone, 2,3,4,5tetramethyl-2-cyclopenten-1-one and hydroxyketone C10H14O2, while the essential oil from flowers showed higher concentrations of sesquiterpenes. Table 4 shows the antifeedant effects of the essential oils extracted from leaves (l) and flowers (f) of groups 1e6. L. decemlineata responded to 42% of the extracts tested and was sensitive to both oils from group 3, followed by 6-f, 2-l and 5-l. S. littoralis responded to 33% of the extracts tested, specifically to both oils from group 6, 4-l and 3-l. M. persicae responded to most of the oils tested (66%). These results support the insect defensive role proposed for L. luisieri oil. Stepwise linear regression was used to estimate the contribution of the oil’s different components to essential oil antifeedant effects. When considered individually, trans-linalool oxide (furanyl ring) presented a moderate correlation with antifeedant effects against L. decemlineata (r ¼ 0.55, p ¼ 0.06) and S. littoralis (r ¼ 0.58, p ¼ 0.05), the same being true for 14-norcadin-5-en-4-one (r ¼ 0.76), hydroxyketone acetate C12H18O3 (r ¼ 0.72), 1,8-cineole (r ¼ 0.71), alcohol C10H16O (r ¼ 0.66), trans-linalool oxide (furanyl ring) (r ¼ 0.51), cis-a-necrodol (r ¼ 0.44) and hydroxyketone acetate C12H18O3 (r ¼ 0.41) in the case of M. persicae. When two compounds were considered in the regression, the best results (multiple r ¼ 0.80) were found for L. decemlineata using a combination of camphor and the hydroxyketone C10H14O2. The correlation with the antifeedant effects on S. littoralis and M. persicae did not improve significantly with other compounds.

Table 2 Principal Component Analysis results for flower volatiles data (see Section 3 for component codes) Explained variance (%)

PC1 PC2 PC3 PC4

62.5 23.8 9.7 2.8

Principal component loadings for flower samples 1

2

3

4

5

6

7

8

9

18.29 17.73 0.84 0.53

0.63 4.21 12.45 2.72

31.81 6.61 2.49 1.11

6.38 9.13 3.69 1.63

0.02 0.01 0.03 0.01

0.05 0.13 0.05 0.07

1.23 1.52 0.73 0.34

6.73 7.90 6.54 3.59

1.57 1.29 2.05 6.41

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Flower volatiles

3

PC axis 2

2

1

0

-1

-2 -1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

PC axis 1 Fig. 2. Plot of the scores of flower samples using as coordinate axes the first and second components in PCA analysis.

Table 3 Yields of the essential oils of leaves (l) and flowers (f) from groups 1 to 6 and concentration (%) of their main components Compound

Group Seville

Toledo

1

1,8-Cineole (1) cis-Linalool oxide (furanyl ring) Fenchone (2) trans-Linalool oxide (furanyl ring) 2,3,4,5-Tetramethyl-2-cyclopenten-1-one Ketone C9H14O Camphor (3) trans-a-Necrodol þ ketone C10H14O Alcohol C10H16O cis-a-Necrodol 5-Methylene-2,3,4,4-tetramethylcyclopent2-enone (4) Ester C12H20O2 trans-a-Necrodyl acetate (5) þ bornyl acetate Lyratyl acetate þ lavandulyl acetate cis-a-Necrodyl acetate (6) Acetate C12H20O2 Acetate C12H20O2 Hydroxyketone C10H14O2 Hydroxyketone acetate C12H18O3 Hydroxyketone acetate C12H18O3 Viridiflorol Sesquiterpenic alcohol C15H26O T-muurolol Cadalene 14-Norcadin-5-en-4-one a-Cyperone Yield (% V/W)

2

3

4

5

6

f

l

f

l

f

l

f

l

f

l

f

l

18.3 0.3 e 0.4 0.2 0.3 4.5 0.7 1.5 1.1 14.6

20.0 0.7 e 0.5 1.1 0.9 1.8 1.1 1.5 0.9 38.3

0.4 0.2 e 0.1 0.1 0.1 1.8 0.3 0.3 0.4 5.8

6.0 0.4 e 0.2 0.6 0.4 2.0 1.3 0.9 0.7 28.1

11.8 0.4 e 0.7 0.3 0.2 9.8 0.7 1.3 1.1 10.1

17.6 0.9 e 0.8 0.4 0.6 3.8 1.3 1.7 1.8 24.1

0.4 0.1 20.7 e 0.1 0.3 7.8 0.6 0.7 1.2 12.2

3.2 0.4 14.7 e 0.5 0.6 3.0 1.0 1.1 1.5 28.8

1.2 0.2 4.2 e 0.3 0.2 51.8 0.8 1.0 0.7 10.2

3.8 0.4 1.4 e 0.5 0.4 53.7 0.9 0.5 0.6 14.7

10.5 0.2 22.0 e 0.4 0.5 9.1 0.6 1.5 1.1 13.0

20.6 0.9 7.8 e 0.5 0.6 2.5 1.1 1.5 1.5 20.5

0.9 1.1 2.5 1.8 0.8 0.2 1.0 0.9 0.5 2.5 1.4 0.2 0.2 e e 0.86

2.0 1.6 2.5 3.5 1.6 0.3 0.4 0.3 0.4 12.1 9.0 5.4 2.2 0.5 0.7 0.14

2.5 2.4 5.1 4.1 2.0 0.4 1.3 1.3 0.8 4.0 2.9 0.3 0.6 e e 0.44

3.9 2.9 4.2 4.4 1.7 0.5 0.7 0.9 0.5 1.1 0.2 3.2 0.8 e 1.0 0.27

1.0 3.7 1.9 1.6 0.6 0.1 0.5 0.7 0.6 0.7 0.3 3.9 0.5 1.8 e 0.46

0.7 2.6 1.8 1.3 0.6 0.2 0.6 0.7 0.6 0.3 e 1.9 0.3 0.6 e 0.72

1.7 1.7 3.4 3.3 1.1 0.3 0.7 1.0 0.5 5.5 3.9 0.9 1.1 0.2 0.3 0.31

2.8 2.2 5.5 3.7 1.9 0.5 1.4 1.2 0.9 1.1 0.2 1.9 0.7 1.8 0.3 0.23

2.7 2.9 3.2 4.2 1.8 0.4 0.8 0.8 0.6 3.3 2.7 4.1 0.6 2.8 0.9 0.12

2.6 2.4 4.3 4.6 1.9 0.4 1.6 0.7 0.6 1.3 0.4 1.6 0.5 1.2 0.3 0.33

1.6 1.8 2.6 2.2 1.3 0.2 0.6 0.7 0.4 0.8 0.2 5.3 0.8 2.8 0.5 0.53

1.9 2.2 4.0 2.7 1.1 0.4 0.9 1.5 0.7 0.6 e 3.6 0.6 1.8 0.2 0.79

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Table 4 Antifeedant effects of L. luisieri essential oils (100 mg/cm2) from leaves (l) and flowers (f) obtained from groups 1 to 6 Group

Plant part

L. decemlineata

S. littoralis

M persicae

%FIa 1

l f l f l f l f l f l f

2 3 4 5 6

30  10 26  12 58  15 43  7 76  16c 60  8c 29  16 39  11 53  17 19  09 20  3 64 þ 12c

29  10 32  11 47  12 17  9 69  10c 0 77  8c 3912 23  7 31  9 57  15 73  8c

%Cb

%Tb

77  23 na 71  37 na na 88  13 83  15 58  16 63  15 na na na

23  23d na 29  35d na na 12  13 17  15d 42  16 37  15 na na na

na, not enough compound available. a %FI ¼ 1  (T/C)  100, where T and C are the consumption of treated and control leaf disks respectively. Represented are mean values  standard deviation (n ¼ 10). b %T and %C are percent aphids settled on treated and control leaf disks. Represented are mean values  standard deviation (n ¼ 20). c p < 0.05, ManneWhitney Test. d p < 0.05, Wilcoxon Signed Rank Paired Test.

The antifeedant and postingestive effects of the major and selected oil components are shown in Table 5. M. persicae showed a significant response to trans- þ cis-a-necrodyl acetate and fenchone, while S. littoralis and L. decemlineata were not affected by these compounds. Additionally, these terpenes were not postingestive antifeedants when orally injected to S. littoralis L6 larvae. Fenchone has acaricidal effects (Lee, 2004), it is a moderate repellent to Aedes aegypti and a toxicant to coleopteran stored-product insects (Kim and Ahn, 2001; Kim et al., 2002). Fenchone and 1,8-cineole are effective toxicants against stored-product insect pests (Lee et al., 2003). However, the antifeedant effects observed for L. luisieri oils are not accounted for by these components individually in line with the results of the stepwise linear regression, suggesting a synergistic antifeedant effect for L. luisieri oils. Similarly, Salvia lavandulifolia oil inhibits the enzyme acetylcholinesterase, through a complex interaction between its constituents, including both synergistic and antagonistic interactions between the terpenes, with 1,8-cineole and camphor being very active components. However, a combination of camphor and cineol was antagonistic (Savelev et al., 2003). In summary, 47 individual L. luisieri plants were grouped into six categories according to their volatile composition by Principal Component Analysis. The antifeedant effects of the essential oils from the flowers and leaves from these six groups cannot be accounted for by the activity of their major components considered individually, supporting the existence of synergistic effects among the oil components. Table 5 Antifeedant and postingestive effects of L. luisieri essential oil selected components Compound

1,8-Cineole Fenchone Camphor 5-Methylene-2,3,4,4-tetramethylcyclopent-2-enone trans-a-Necrodyl acetate þ cis-a-Necrodyl acetate a b c d

L. decemlineata

M. persicae b

EC50a

%C

>50 >50 >50 >50 >50

63  19 70  17 60  24 52  20 67  16

S. littoralis %T

b

37  19 30  17d 40  24 48  20 33  16d

EC50a

DBc

DIc

>50 >50 >50 >50 >50

96  36 100  31 97  35 87  37 103  34

95  33 91  25 83  33 88  33 92  33

EC50, effective dose (mg/cm2) to give a 50% feeding inhibition. As in Table 4. Expressed as percent control, DB ¼ larval weight gain, DI ¼ food ingested (mg dry weight, n ¼ 20 larvae). p < 0.05, Wilcoxon Signed Rank Paired Test.

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