Transgenic cry1C⁎ gene rough rice line T1C-19 does not change the host preferences of the non-target stored product pest, Rhyzopertha dominica (Fabricius) (Coleoptera: Bostrichidae), and its parasitoid wasp, Anisopteromalus calandrae (Howard) (Hymenoptera: Pteromalidae)

Ecotoxicology and Environmental Safety 120 (2015) 449–456

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Transgenic cry1Cn gene rough rice line T1C-19 does not change the host preferences of the non-target stored product pest, Rhyzopertha dominica (Fabricius) (Coleoptera: Bostrichidae), and its parasitoid wasp, Anisopteromalus calandrae (Howard) (Hymenoptera: Pteromalidae) Xiao Sun a, Miao-Jun Yan a, Aijun Zhang b, Man-Qun Wang a,n a Hubei Insect Resources Utilization and Sustainable Pest Management Key Laboratory, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, PR China b Invasive Insect Biocontrol and Behavior Laboratory, BARC-West, USDA-ARS, Beltsville, MD 20705-2350, United States

art ic l e i nf o

a b s t r a c t

Article history: Received 25 February 2015 Received in revised form 21 June 2015 Accepted 22 June 2015 Available online 3 July 2015

Rough rice grains are often stored for extended periods before they are used or consumed. However, during storage, the rough rice is vulnerable to insect infestation, resulting in significant economic loss. Previous studies have shown that volatiles cues, physical characteristics, and taste chemicals on the grains could be the important key behavior factors for storage insect pests to locate the hosts and select oviposition sites. It is also well known that the transgenic Bt rough rice line T1C-19, which expresses a cry1Cn gene has a high resistance to Lepidoptera pests. However, there were no evidences to show the consequences of host preference for non-target insect pests after growing Bt transgenic rice. In this study, the potential key factors of Bt rough rice were investigated for their impacts on the behaviors of nontarget pest lesser grain borer Rhyzopertha dominica, the main weevil pest of grain and its parasitic wasps Anisopteromalus calandrae, the natural enemy of the beetle. Both electronic nose and electronic tongue analyses showed that the parameters of Bt rough rice were analogous to those of the non-Bt rough rice. The volatile profiles of Bt and non-Bt rough rice examined by gas chromatographic mass spectrometry (GC–MS) were similar. For most volatile compounds, there were no significantly quantitative differences in compound quantities between Bt and non-Bt rough rice. The densities of sclereids and trichomes on the rough rice husk surface were statistically equal in Bt and non-Bt rough rice. The non-target pest, R. dominica, and its parasitoid wasp, A. calandrae, were attracted to both rough rice and could not distinguish the transgenic T1C-19 from the isogenic rough rice. These results demonstrated that Bt rough rice has no negative impacts on the host preference behaviors of non-target stored product pest R. dominica and its parasitoid A. calandrae. & 2015 Elsevier Inc. All rights reserved.

Keywords: Bacillus thuringiensis Rough rice Volatile chemicals Physical character Non-target effect Tritrophic bioassay

1. Introduction Rice (Oryza sativa L.) is one of the most important food crops in the world, however, quantity and quality of the rice were affected and threatened by several insect pests. The difficulty in controlling the stemborers, including yellow stemborer (Tryporyza incertulas) and striped stemborer (Chilo suppressalis), was the incentive to develop transgenic rice lines. They produce different derivatives of an insecticidal crystal protein from the insect pathogen, Bacillus thuringiensis Berliner, such as Bt Shanyou 63 harboring a cry1Ab/ cry1Ac fusion gene and Bt Xiushui 11 containing a synthetic Abbreviations: Bt, Bacillus thuringiensis; PCA, principal component analysis n Corresponding author. Fax: þ 86 27 87280920. E-mail address: [email protected] (M.-Q. Wang). http://dx.doi.org/10.1016/j.ecoenv.2015.06.034 0147-6513/& 2015 Elsevier Inc. All rights reserved.

cry1Ab gene, and encode Bt δ-endotoxin that are known to be effective against these pests (Tu et al., 2000; Ye et al., 2000; Chen et al., 2005; Tang et al., 2006; Wang et al., 2010). However, the commercial release of Bt rice has not been permitted because there are still significant debates over the social, economic and ecological implications of the use of genetic modification in agriculture (Obonyo et al., 2010; Yu et al., 2011), even though laboratory and field tests have confirmed that Bt rice lines are more environmentally friendly than present practices (Chen et al., 2011). Rough rice is often stored for extended periods before it is used or consumed. During the storage period, rough rice is vulnerable to infestation from a variety of stored product insects, such as Rhyzopertha dominica (Coleoptera: Bostrichidae), Sitophilus oryzae (Coleoptera: Dryophthoridae), Plodia interpunctella (Lepidoptera: Pyralidae) and Sitotroga cerealella (Lepidoptera: Gelichiidae)

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(García et al., 2005). Previous studies have shown that emergence and fecundity in two species of stored-product moths, P. interpunctella and S. cerealella, had declined when reared on lepidopteran-specific Bt transgenic maize. In P. interpunctella, this effect can last up to 5 months after harvest (Sedlacek et al., 2001; Giles et al., 2000). In addition, the development time from egg to adult for both sexes had increased when reared on Bt maize (Gryspeirt and Grégoire, 2012). Diets using Bt kernels containing the same concentration of Cry1Ab caused 100% mortality in Ephestia elutella, Cadra cautella and P. interpunctella and 65% mortality in Ephestia kuehniella (Hubert et al., 2008). Furthermore, Bt non-target pests, such as Sitophilus zeamais, were not negatively affected by transgenic Bt maize, with regards to their developmental characteristics (development time, body mass), and females emerging from transgenic maize kernels were larger than from isogenic maize. However, the overall number of the parasitoid Lariophagus distinguendus, emerging from weevils that had developed inside the transgenic kernels, had declined (Hansen et al., 2012). Thus, possible non intentional Bt side-effects are exited and the impact of transgenic rough rice on storage insects needs to be investigated. Previous studies have shown that P. interpunctella was unable to survive in rice semolina obtained from Bt rice and the number of S. oryzae and Liposcelis bostrichophila emerging from Bt rice had declined (Riudavets et al., 2006), whereas no significant differences in developmental duration and the life table of the beetle, Tribolium castaneum, were found among several the Bt and non-Bt rice varieties (Yao et al., 2012). Most insects locate and select their hosts largely based on chemosensory cues. Olfactory cues can mediate long-range attraction (Jyothi et al., 2002; Van Naters and Carlson, 2006; Gallego et al., 2008; Fettig et al., 2009; Hu et al., 2009; Zhuge et al., 2010). For example, the onion fly, Delia antiqua, is attracted to the host volatile dipropyl disulfide from distances of 100 m or more (Judd and Borden, 1989). Volatiles from various stored grains have also been shown to attract certain storage insects toward the food sources and R. dominica has been reported to respond to grainemitted volatiles from food-baited traps (Chambers, 1990). Previous studies have shown that plants are actively involved in the production and release of chemical cues that guide foraging parasitoids (Turlings et al., 1995) and parasitoids can respond to cues coming from their herbivorous host species or from the different plants on which their hosts feed (Steidle and Schöller, 1997; Steiner et al., 2007). Anisopteromalus calandrae is a well-known cosmopolitan parasitoid of Coleoptera that infests stored products (Schöller et al., 2006). The question is whether the volatile compounds could be altered in Bt rice grains, which would influence the behavior of herbivores searching for host location, and that of parasitoids seeking for insect host. It has also been shown that host taste cues can either stimulate or inhibit feeding and also affect egg laying by females. Manduca sexta caterpillars, for example, are stimulated to feed on their host plants by some compounds, including various sugars, and are deterred by others, including caffeine and aristolochic acid, which taste bitter to humans (Glendinning et al., 2002). Studies have also shown that physical characteristics could be the key to oviposition selection. For example, more S. zeamais adults were more attracted to traps containing naturally damaged kernels than to traps with intact or mechanically damaged kernels (Trematerra et al., 2007). McGaughey (1974) found that R. dominica reproduced better in brown rice than that in rough or milled rice. However, it is unknown whether these compounds and the physical characteristics could be altered in transgenic rough rice. In addition, if these are changed, it is not clear whether these changes could influence the behaviors of storage insect pests and their parasitoids for host location. In this study, the volatiles, taste chemicals, and the physical

characteristics of transgenic Bt rough rice line T1C-19, which expresses a cry1Cn gene and has a high resistance to Lepidoptera pests (Tang et al., 2006), were studied in comparison with non-Bt rough rice. The impacts of Bt grains on the behavior of the main beetle pest of rough rice, R. dominica, and its natural enemy, A. calandrae, were also investigated in order to identify possible sideeffects that would interfere with parallel parasitoid-based control methods. Our results revealed that Bt rough rice had no negative impacts on the behaviors of the non-target storage insect species R. dominica and its parasitoid A. calandrae. Therefore, R. dominica beetles are likely to remain under biological control in the Bt rough rice T1C-19 line.

2. Methods and materials 2.1. Insects rearing R. dominica and its parasitoid, A. calandrae, were obtained from stock cultures maintained in the laboratory. The insect and its parasitoid were kept under controlled conditions of 25 72 °C and 70710% RH, with a 16:8 (L:D) photoperiod. R. dominica was reared in rough rice and kept in glass jars (about 500 ml) sealed across the top with black muslin cloth, while A. calandrae was colonized on R. dominica and were kept in nylon cages (30 cm diameter and 50 cm height). Before testing, the trial beetles and the parasitoids were kept separately for 6 h, i.e. without their respective host, in order to prevent oviposition. During this time, R. dominica and its parasitoids were only fed with 5% sucrose solution. All of the insects used in the study were treated according to the International Guiding Principles for Biomedical Research Involving Animals (Council for International Organizations of Medical Sciences, http://www.cioms.ch) and approved by the institution animal care and use committees of the Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. 2.2. Rice cultivars T1C-19 expresses a cry1Cn gene, which encodes B. thuringiensis (Bt) δ-endotoxin with the cry1C concentration about 10.4 ng/g and was synthesized by codon optimization. It was introduced into the elite indica rice restorer line, Minghui 63 (MH63), by Agrobacterium-mediated transformation. All the rice lines were gifted from Lin Yong-Jun, National Key Laboratory of Crop Genetic Improvement, Wuhan, China. T1C-19 and the non-transgenic isoline, MH63 (control), were cultivated in a Xiaogan City suburb (113.54°E, 30.56°N). 2.3. Electronic nose measurement An electronic nose, FOX 4000 (Alpha MOS, France), was used in this study. It was equipped with 18 different thermo-regulated metal oxide semiconductor sensors, which were slightly sensitive to different classes of chemical compounds (Table S1). Clean air (through an activated charcoal filter) was used as a reference gas. For each sample, 5 g of rough rice was placed in a 22 ml Pyrex vial and sealed with a polytetrafluoroethylene/butyl septum and an aluminum crimp cap, and incubated at 37 °C for 1 h for headspace equilibration. Measurements were performed in dynamic headspace mode by extracting the headspaces through the 0.45 μm syringe filter outlets to prevent environmental contamination. Each measurement cycle consisted of (1) exposing the sensors to clean filtered ambient air for 120 s, (2) sensor exposure to the sample headspace for 120 s, and (3) sensor exposure to filtered ambient air over 360 s for baseline recovery before the next analysis. The experimental conditions were adapted from Camurati

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et al. (2006). Ten replicates were conducted for each sample in order to verify the signal stability and to get enough data to reduce sample variations. In order to correlate the statistical data, electronic tongue and gas chromatography/mass spectrometry (GC– MS) samplings were simultaneously taken as e-nose. 2.4. Electronic tongue measurement The samples were analyzed using an Alpha ASTREE II (Alpha MOS, Toulouse, France) potentiometric electronic tongue that was designed to analyze, recognize and identify complex water-dissolved compounds. The instrument was connected to an LS 16 auto sampler unit. The system’s principle is to simulate the human tasting procedure. The electronic tongue has seven ion sensitive field effect transistor (ISFET) potentiometric chemical sensors for food applications (ZZ, BA, BB, CA, GA, HA and JB). The under-lying sensor technology is based on chemically modified field effect transistor technology (ChemFET). These chemical sensors are potentiometric sensors with an organic membrane coating that gives each sensor specific sensitivity and selectivity (Ampuero and Bosset, 2003). They measure organic and inorganic compounds dissolved in water, including taste and flavor compounds. The sensors have cross-sensitivity for the different flavor components. Sensor potential is measured against a standard Ag/AgCl 3 M KCl reference electrode (Metrohm AG). In each case, a sample quantity of 10 g of rough rice was attrited and then soaked in 100 ml ddH2O for 2 h. The conditions were as follows: 100 ml sample volume, 180 s per analysis and 30 s per cleaning. The samples were put into the sample holder glasses 1 h before measurement began in order to release their CO2 content, which helped improving analytical reliability. 2.5. Collection, isolation and identification of volatile compounds 100 g rough rice sample was stored in a 2 L glass container that was covered with glass wool (Fig. S1). Subsamples were then placed separately into four glass containers (20 cm (diam)  50 cm (height)) and connected to Super Q traps (Alltech Associates, Inc. Deerfield, IL, USA; subsample weight, 200 mg; trap size, 15 cm  0.6 cm OD) (Heath and Manukian, 1994). The air was filtered through three adsorbent traps (20 cm  3 cm OD): charcoal (activated carbon, 6–14 mesh, Fisher Scientific), 5 A molecular sieves, (beads, 8–12 mesh, Sigma-Fluka) and silica gel Rubin (a drying agent that is free of metal saltsn, Sigma-Fluka) before being pumped through the apparatus with a vacuum pump. The flow rate was controlled at 0.4 L min  1 and static adsorption was kept at 2571 °C for 24 h. The airborne volatiles were eluted by percolating each Super Q trap with glass-distilled dichloromethane (0.5 ml of each trap) and the resultant dichloromethane solutions were concentrated under a stream of nitrogen to a volume of about 100 ml. 200 ng of nonyl acetate (Sigma, Buchs, Switzerland) in 10 ml of dichloromethane (20 ng/ml) was added to the samples as an internal standard and then the samples were stored at  40 °C. Collections were replicated six times for each variety. GC–MS analyses were performed using a DSQ II instrument (Thermo Fisher Scientific, USA) connected to a mass spectrometer with an automated on-column injection system and a flame ionization detector. From each sample, 1 ml aliquot was injected onto a HP-5 capillary column (30 m, 0.25 mm i.d., 0.25 mm film thickness, Alltech, Deerfield, IL, USA) in splitless mode. Helium (24 cm s  1) was used as the carrier gas. After injection, the oven temperature was maintained at 40 °C for 2 min, increased to 250 °C at 6 °C min  1 and then held at 250 °C for 2 min. The detector signal was processed using Hewlett Packard GC Chemstation software. Initial identification of the volatile compounds was based on

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comparison of mass spectra with Wiley MS library database, and the results were confirmed by the mass spectrometry analysis of authentic samples. For quantitative analysis, 1 ml aliquot was injected in pulsed splitless mode into a HP GC equipped with a flame ionization detector, using the same column and temperature program as above. Total quantities of volatiles were calculated by comparing their peak areas to that produced by the internal standard. 2.6. Trichome and sclereid density The densities of trichome and sclereid measurements at the surface of rough rice were carried out under a scanning electron microscope (SEM) (Tokyo, Japan) (Xue et al., 2008). Thirty samples were examined and the results were calculated as trichome and sclereid density per 1 mm2. 2.7. Olfactometer bioassay The Y-tube olfactometer (12 cm long and 2 cm in diameter) used in this experiment to investigate the orientation response of the adult beetles and parasitoids toward volatiles was placed. The two arms (7 cm long each) were set at an angle of 90°. The air was purified through a charcoal filter before reaching the glass container containing the stimuli being tested. The airflow through each olfactometer arm was 150 ml min  1, which was determined using a flow meter (Zhen Xing, Wuhan, China). Different odor source treatments (CK vs. CK, CK vs. MH63 and MH63 vs. T1C-19) (CK: control (clean air)) were placed inside the glass container for the experiments. The outlet tubes were covered with gauze (0.3 mm mesh size) inside the jar lid to prevent insects from entering the tubes. The empty container was used as control. Beetles and parasitoids were randomly selected. They were checked before each test; and those with damaged antennae or were inactive/immobile within 5 s of being placed on a planed wood (not slippery) or paper were discarded. A single tested insect was released at the downwind entrance of the main tube and allowed to walk and choose either of the arms. The maximum observation duration for each insect was 5 min. The olfactometer was cleaned with alcohol and the arms were switched between the two odor source jars after every five insects to avoid possible environmental factors or location effects. Fifty beetles and fifty parasitoids were tested in each odor trial. 2.8. Roundel behavioral bioassays In order to assess olfaction and gustation preferences, 40 randomly selected R. dominica females and males were released in the center of a culture dish (20 cm diameter) covered with tinfoil. Four piles of rough rice (5 g MH63 or T1C-19/each pile) were diagonally placed in dish (Fig. S2). The assay consisted of 40 replicates, which were carried out in a greenhouse at a temperature of 25 72 °C and 707 10% RH with a 16:8 (L:D) photoperiod. The positions of the Bt and non-Bt piles in the culture dish were randomly chosen in each replicate. The rough rice was exposed to the beetles for 24 h, after which the number of beetles in each pile was recorded.

3. Data analysis The complex data sets created by e-nose and e-tongue analyses were submitted to principal component analysis (PCA) using a projection method that allowed an easy visualization of the information contained in the data sets and also permitted dimensional reduction (Yu and Wang, 2007). The PCA was applied as a

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data visualization tool for sensory analysis. The figures show the analysis results on a two-dimensional plane with a principal component 1 (PC1) and a principal component 2 (PC2). The PCA is viewed using a linear combinatorial method, which can reduce the complexity of the data set. To compare the quantitative differences of volatiles, as well as the trichome/sclereids density and behavior in the roundel behavioral bioassays between MH63 and T1C-19, all data were tested for normal distribution by Shapiro–Wilk test and for homogeneity of variances by Levene’s test. Then t-tests were used to analyze the differences in the quantity of volatiles and trichome/sclereids density between MH63 and T1C-19. The χ2 goodness-of-fit test was used to analyze differences in the olfactometer bioassays, and a paired-sample t-test was used to analyze the differences in the roundel behavioral bioassays between MH63 and T1C-19. Data were statistically analyzed using SPSS 20 for Windows software.

explained (Fig. 2B). The distance indicated a low discrimination power between the components of the non-Bt and Bt samples, indicating that the Bt rough rice was analogous to the non-Bt rough rice. This method was not able to distinguish between sensors at the PC1 level where the contribution rate was 98.7%, but could partially discriminate between some of the sensors for Bt and non-Bt rough rice at the PC2 level where the contribution rate was only 0.9%. 4.3. Volatiles analysis

The response of the radar values from each sensor showed the peak height of each sensor as a radial vector (Fig. 1A). The response of the sensors was highly reproducible. The t-test statistical analysis showed that there were no obvious changes in the relative abundance detected by each sensor between MH63 and T1C-19 rough rice (Table S2). The samples taken from the two varieties could not be clearly distinguished at the PC1 level and had a contribution rate of 91.3%. Nevertheless, the two variety samples were found to be mixed in with each other at the PC2 level and the contribution rate was only 6.8%. The MH63 and T1C-19 rough rice volatile fingerprints were very close and had a distance of only 0.01 (Fig. 1B).

The GC–MS total ion chromatograms between Bt and non-Bt rough rice were very similar (Fig. 3). 27 compounds belonging to different groups of chemicals, including alkanes, aromatic, hydroxyl and carbonyl compounds, terpenoids and heterocyclic compounds were identified (Table 1). The alkanes, such as undecane, dodecane, tridecane, tetradecane, pentadecane, hexadecane, heptadecane, heneicosane, heptacosane and nonacosane, were widespread and constituted one of the most abundant classes of compounds. There was no significant difference in the quantity for each alkane between volatiles from Bt and non-Bt rough rice. For aromatic compound, the naphthalene was predominant in both rice volatiles. Except for the quantity of dibenzofuran in MH63, which was higher than in T1C-19 rough rice, there was no significant difference between volatiles from Bt and non-Bt rough rice. Hydroxyl and carbonyl compounds, such as cedrol, octanal, nonanal, camphor and decanal, were present in smaller quantities than the alkanes. There was no significant difference between volatiles from Bt and non-Bt rough rice. It is same to terpenoid compound, no significant difference was found between volatiles from Bt and non-Bt rough rice. However, the quantity of 2-pentyl-furan, a heterocyclic compound, was significantly higher in the volatiles from Bt rough rice than in the volatiles from non-Bt rough rice.

4.2. Electronic tongue analysis

4.4. Trichome and sclereid density

The results obtained from the radar values for each sensory analysis showed that the fingerprints were so close that the two varieties had overlapped (Fig. 2A). The t-test analysis showed that there were no obvious changes in the relative abundance detected by each sensor between the MH63 and T1C-19 rough rice (Table S3). The PCA analysis was completed, and for the first two PCs, the explained variance accumulated was 99.6%, which means that nearly all the variance contained in the original data can be

Under the SEM, many sclereids, but few trichomes, were present on the rough rice husk surface (Fig. S3). The sclereids were found to widespread across the leaf surface of Bt rough rice and non-Bt rough rice husk, but the trichomes were restricted only to the veins on the husk surfaces. The average numbers of trichomes/mm2 (mean 7SE) on Bt and non-Bt rough rice were 5.1 70.4 and 5.9 7 0.7 (Fig. 4A), and the average numbers of sclereids/mm2 (mean 7SE) on Bt and non-Bt

4. Results 4.1. Electronic nose analysis

Fig. 1. Radar map and scores plot PC1 vs. PC2 of rice by means of the electronic nose. (A) Radar map of Bt and non-Bt rice, and (B) scores plot PC1 vs. PC2, for PCA analysis of Bt and non-Bt rice.

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Fig. 2. Radar map and scores plot PC1 vs. PC2, for PCA analysis of rice by means of the electronic tongue. (A) Radar map of Bt and non-Bt rice, and (B) scores plot PC1 vs. PC2, for PCA analysis of Bt and non-Bt rice.

Fig. 3. Gas chromatography–mass spectrometry (GC–MS) profiles of representative solvent extract of T1C-19 Bt and MH63 non-Bt rice: (1) p-xylene, (2) α-pinene, (3) benzaldehyde, (4) furan, 2-pentyl-, (5) octanal, (6) D-limonene, (7) indane, (8) undecane, (9) nonanal, (10) camphor, (11) naphthalene, (12) dodecane, (13) decanal, (14) thymol, (15) tridecane, (16) biphenyl, (17) tetradecane, (18) heneicosane, (19) heptacosane, (20) acenaphthene, (21) pentadecane, (22) dibenzofuran, (23) fluorene, (24) cedrol, (25) hexadecane, (26) heptadecane, and (27) nonacosane.

rough rice were 135.9 78.7 and 143.2 76.1 (Fig. 4B), respectively. The t-test analysis indicated that trichome (t¼  0.09, df ¼38, p ¼0.93) and sclereid (t¼  0.43, df ¼ 38, p¼ 0.67) densities on the rough rice husk surfaces were not significantly different between Bt and non-Bt rough rice. 4.5. Olfactometer bioassay The bioassay was first validated using control air (blank) on both arms of the olfactometer. In R. dominica, no significant differences were observed in preference (17 vs. 20) and in the time taken to respond to each of these blanks (χ2 ¼ 0.243, df ¼1; p ¼0.62). In a similar manner, A. calandrae showed no significant preference to the blanks (16 vs. 19) (χ2 ¼0.257, df ¼ 1; p¼ 0.612). Comparing with blank controls, the results showed that both the beetles (9 vs. 35) (χ2 ¼15.360, df ¼ 1; p o0.01) and their parasitoids (5 vs. 33) (χ2 ¼ 20.632, df ¼1; p o0.01) were strongly attracted to MH63. There was no significant difference in the beetle's response to T1C-19 and MH63 (28 vs. 19) (χ2 ¼ 1.732, df ¼1; p ¼0.189). A. calandrae also showed no significant preference for

T1C-19 when compared with MH63 (23 vs. 19) (χ2 ¼0.381, df ¼1; p¼ 0.537) (Fig. 5). 4.6. Roundel behavioral bioassays The numbers of R. dominica in the different rough rice piles were measured and the two rough rice lines were compared. The average numbers of beetles (mean 7SE) per Bt and non-Bt rough rice were 16.6 70.8 and 16.3 70.6, respectively. There was no significant difference between the number of beetles observed in the Bt compared to the non-Bt rough rice (t¼0.74, df ¼ 62, p ¼0.46) (t test) (Fig. S4).

5. Discussion Previous studies have shown that many parasitoids locate their host by the volatile cues released by the pest host plants (Romeis et al., 2006; Lundgren et al., 2009). In this context, the aim of this work was to investigate, using diverse approaches, the impact on

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Table 1 Volatiles released by Bt and non-Bt rice (mean7 SE, n¼ 6) (t test). Number

Volatile

MH63

T1C-19

t Value

df

p Value

Alkanes 8 12 15 17 18 19 21 25 26 27

Undecane Dodecane Tridecane Tetradecane Heneicosane Heptacosane Pentadecane Hexadecane Heptadecane Nonacosane

0.36 7 0.09 2.677 0.58 1.56 7 0.05 2.147 0.29 1.077 0.15 0.477 0.08 3.107 0.28 2.117 0.37 0.82 7 0.11 0.50 7 0.12

0.26 7 0.03 1.87 7 0.22 1.717 0.21 3.017 0.43 1.20 7 0.16 0.56 7 0.07 3.417 0.35 1.93 7 0.15 0.767 0.08 0.647 0.08

1.44 1.48  0.59  1.53  0.58  0.87  0.61 0.55 0.41  0.99

9 8 8 9 8 5 8 9 8 6

0.18 0.18 0.57 0.16 0.58 0.42 0.56 0.60 0.69 0.36

Aromatic 1 3 7 11 14 16 20 22 23

compounds p-Xylene Benzaldehyde Indane Naphthalene Thymol Biphenyl Acenaphthene Dibenzofuran Fluorene

1.007 0.20 0.23 7 0.03 0.127 0.02 19.497 0.79 0.197 0.02 0.487 0.12 2.017 0.31 1.05 7 0.13 0.917 0.11

1.177 0.17 0.22 7 0.08 0.127 0.12 22.29 7 1.84 0.22 7 0.04 0.447 0.06 1.93 7 0.52 0.54 7 0.12 1.03 7 0.18

 0.64 0.19  0.29  1.17  0.49 0.37 0.41  3.36  0.56

7 3 4 8 7 7 9 5 6

0.54 0.87 0.79 0.28 0.64 0.72 0.69 0.02 0.60

Hydroxyl 24 5 9 10 13

and carbonyl compounds Cedrol 0.197 0.02 Octanal 0.22 7 0.10 Nonanal 0.95 7 0.08 Camphor 0.187 0.03 Decanal 0.75 7 0.06

0.22 7 0.03 0.217 0.02 0.95 7 0.09 0.217 0.02 0.767 0.09

 0.87 0.32 0.01  0.77  0.10

7 5 11 7 9

0.41 0.76 0.99 0.47 0.93

Terpenoids 6 D-Limonene 2 α-Pinene

1.84 7 0.71 0.23 7 0.06

1.617 0.28 0.197 0.02

0.38 0.74

5 7

0.72 0.48

Heterocyclic compounds 4 Furan, 2-pentyl-

0.08 7 0.01

0.157 0.01

 4.95

2

0.04

the host preferences of non-Bt targeted rice pest and its parasitoid after introduction of Bt toxin in rice. Electronic nose is based on the principal of GC and an array of solid-state sensors that are non-selectively sensitive to a number of relevant chemicals. Their response reflected the chemical information contained in the sample. The electronic noses have been applied in a number of different fields and have provided useful sample identification and classification information (Eifler et al., 2011; Korsching, 2002; Perkowski et al., 2008; Lopez de Lerma et al., 2012). In this study, for the first time, the electronic noses were used to compare Bt line T1C-19 and non-Bt line MH63 rough rice. Both of the radar map analysis and the PCA results showed

that it was hard to discriminate the volatile compounds released from the Bt and the non-Bt rough rice. In previous studies (Peres et al., 2009; Dias et al., 2011), a similar multisensor e-tongue system, made up of cross-sensitivity polymeric membranes, was used as a taste sensor for qualitative, semi-quantitative and quantitative analyses in food matrices. E-tongue devices have been successfully used to classify food matrices based on their physico-chemical and sensorial characteristics (Uyen Tran et al., 2004; Benjamin et al., 2012; Peres et al., 2011). Our PCA results showed that chemical compositions in individual groups of MH63 and T1C-19 were very similar. Both the radar map and PCA analysis results showed that it was hard to discriminate Bt and non-Bt rough rice. A possible explanation for this fact is its “harmonic” taste. Overall, the types of volatiles present in T1C-19 and MH63 rough rice identified by GC–MS were similar and the major compounds produced by all rough rice samples were alkanes and aromatic compounds (Fig. 1). There was no significantly quantitative difference in compounds detected from Bt and non-Bt rough rice, with the exception of the dibenzofuran and 2-pentyl-furan, which had higher amounts in MH63 than in T1C-19, respectively. These two compounds have previously been found in rough rice (Maga, 1984; Widjaja et al., 1996). The relationships between the dibenzofuran and 2-pentylfuran emitted from rough rice and the behavior responses of stored products pests or their natural enemies are still not clear. Certain physiological changes have been found in transgenic cotton plants, such as changes in peroxidase and esterase activities (Ding et al., 2001). The concentration of a secondary chemical, which was believed to be responsible for resistance in a number of host plants to some sucking insects (Lane and Schuster, 1981), was significantly different in Bt plants than in non-Bt plants (Zhang et al., 1999). In addition, differences between Bt and non-Bt plants, including changes in the blend of plant volatiles emitted, have been found and extensively discussed (Yan et al., 2004; Turlings et al., 2005; Dean and De Moraes, 2006; Ibrahim et al., 2008). Undamaged Bt cotton plants emitted unique compounds and different proportions of typical compounds when compared with non-Bt cotton (Yan et al., 2004) and the headspace volatiles of transgenic scab resistant apple plants from two representative cultivars quantitatively differed for four terpenes and an aromatic compound (Vogler et al., 2010). Turlings et al. (2005) observed that a non-Bt maize cultivar released a higher quantity of volatile compounds than a Bt maize and similar changes were also observed by Vogler et al. (Vogler et al., 2010). However, Dean and De Moraes (2006) found that in the Bt maize, genetic modification did not appear to alter the volatile profile of undamaged maize. The data available to date, relating to Bt transgenes and induced

Fig. 4. Density measurements (mean7 SE) per 0.1 mm2 of the trichomes: (A) (t¼  0.09, p¼ 0.93) and the sclereids and (B) (t ¼  0.43, p ¼ 0.67) of MH 63 non-Bt and T1C-19 Bt rice surface (t test).

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455

Fig. 5. Behavior responses of R. dominica and its parasitoid A. calandrae to MH63 non-Bt and T1C-19 Bt rice in Y-tube olfactometer. CK: control (clean air). N ¼50. Statistical analysis CK vs. CK for beetles (χ2 ¼0.243; p ¼ 0.62), CK vs. MH63 for beetles (χ2 ¼ 15.360; p o 0.01), MH63 vs. T1C-19 for beetles (χ2 ¼1.732; p ¼ 0.189), CK vs. CK for parasitoids (χ2 ¼0.257; p ¼ 0.612), CK vs. MH63 for parasitoids (χ2 ¼20.632; p o 0.01) and MH63 vs. T1C-19 for parasitoids (χ2 ¼0.381; p ¼ 0.537). Asterisks indicate significant differences between members of a pair (**po 0.01, χ2 test).

volatile release by plants, implies that many different genetic modification effects can be seen in different plant species. Changes in physical characteristics on the host plant surface could influence the searching behaviors of insects (Kamel and Elkassaby, 1965). Physical factors on the host surface of rough rice are mainly caused by the density of trichomes and sclereids. In this study, the trichome and sclereid densities were similar between Bt and non-Bt rough rice, as observed in the physical profiles of Bt and non-Bt Arabidopsis plants (Aharoni et al., 2003), and cotton plants (Yan et al., 2004). The behavioral bioassays, consisting of both the olfactometer and roundel behavioral bioassays, indicated that the beetles were strongly attracted to the hosts, but could not distinguish between the odor from Bt and non-Bt rough rice. In addition, A. calandrae, one of the most important parasitoids of the R. dominica beetle, showed no behavioral preference to MH63 or T1C-19 rough rice. It is coincidence with the results found in Bt crops and the abundance and activity of parasitoids are similar in Bt and non-Bt crops (Romeis et al., 2006). Cry toxins are specific to the insect order, however, if T1C-19 expresses a cry1Cn gene could have other potentially biological impacts on non-target storage insect R. dominica and their parasitoid A. calandrae should be investigated in the future.

Genetically Modified Organisms Breeding Major Projects of China (No. 2011ZZX08001-001) and Fundamental Research Funds for the Central Universities (2013PY046).

6. Conclusion

References

This study showed that (1) insertion of cry1Cn genes into rough rice produced few grain compounds and physical traits to the rough rice and (2) the tritrophic communication, as reflected in the foraging behaviors of non-target stored product insect pest as well as it parasitoid wasp, was not affected. Therefore, R. dominica beetles are likely to remain under biological control program during the in Bt rough rice storage.

Author contributions M-QW and XS conceived and designed the experiments. XS and M-JY performed the experiments. XS and AZ analyzed the data. XS, AZ and M-QW wrote the manuscript; all authors provided editorial advices.

Funding This study was supported and funded by the National

Acknowledgments The authors thank Zhang Hong-Yan (Key Laboratory of Horticultural Plant Biology, Huazhong Agricultural University, Ministry of Education) for the technical assistance during the GC–MS analysis. We are grateful for the technical assistances by Wang RuFeng during the E-nose analysis and by Qin Li-Hong during SEM analysis. We also appreciatively acknowledge Dr. Emmanuelle Jacquin-Joly (INRA-UPMC PISC, Versailles, France) for helpful suggestions on an earlier version of this manuscript. This work was generously supported by the China Scholarship Council (CSC) of China.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at 10.1016/j.ecoenv.2015.06.034.

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