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1 March 2015 Life History Traits of Three Cryptic Species Asia I, Asia II-1 and Asia II-7 of Bemisia tabaci (Hemiptera: Aleyrodidae) Reconfirm Their Genetic Identities
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The Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a pest of agricultural and horticultural crops. It is a species complex consisting of 34 cryptic species. For the distinction of these cryptic species molecular data is extensively used, but corroboration of these with life history traits has been inadequate. In the present study life history traits of 3 cryptic species Asia I, Asia II-1 and Asia II-7 were compared to verify whether biology data of these coincide with molecular data and genetic identities. The results revealed that developmental periods of Asia I, Asia II-1 and Asia II-7 groups ranged from 23.65 to 25.75 days and these were longer in Asia I than Asia II. Survivorships were nearly equal in all these varying from 68.23 to 69.12% with the variations being statistically insignificant. However, the durations of the preoviposition period, egg stage, fourth instar and longevity were observed to be significantly varying (P ≤ 0.001). Multivariate analysis of the life history parameters through principal component analysis (PCA) revealed that the first 4 principal components (PCs) account for 49.5% of total variation. Separate clusters were observed for the Asia I, Asia II-1 and Asia II-7 with slight overlapping. Overall 70% of the classifications got correctly attributed through canonical discriminant analysis (CDA) and the clustering confirmed the groups revealed by principal component analysis (PCA). These clusterings were reconfirmed in the genetic identity of the 3 cryptic species Asia I, Asia II-1 and Asia II-7 determined through molecular characterization. Thus this study adds to the knowledge on the life history traits of the B. tabaci and its cryptic species complex in India.

Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a haplodiploid, sap-sucking hemipteran pest in field crops of warm to hot climates between 30° N and 30° S of the equator. It is polyphagous and has been reported reproducing on more than 900 host plant species (Hsieh et al. 2006). In the last 2 decades, it has become a serious pest on shortlived herbaceous hosts including numerous dicotyledonous crops of agricultural and horticultural importance (Ahmed et al. 2010). The genetic complexity of B. tabaci was first recognized in the late 1950's (Bird 1957). Several populations were observed to be morphologically indistinguishable but differing in host range, host plant adaptability and their ability to transmit plant viruses (Perring 2001; Boykin et al. 2007). De Barro et al. (2011) stated that B. tabaci is a species complex of 11 well-defined high level groups containing at least 24 morphologically indistinguishable species. These were later concluded to consist of 34 cryptic species with differences in genetic structure, host plant preferences, bacterial symbionts and interbreeding capabilities (Hu et al. 2011; Liu et al. 2012; Boykin et al. 2012; Lee et al. 2013; Boykin, 2013; Boykin et al. 2013; Boykin & De Barro, 2014).

In India B. tabaci was first reported from cotton fields of Punjab in 1905 (Misra & Lambda 1929). Banks et al. (2001) reported the presence of invasive biotype B (now referred as Middle East Asia Minor 1, aka MEAM 1) from the fields of Kolar and Bangalore. Boykin et al. (2007) differentiated the Asian B. tabaci populations into Asia I, Asia II and China groups. Ahmed et al. (2011) reported Asia I, Asia II-1 and MEAM 1 from Punjab and Sindh province of Pakistan. Reddy et al. (2012) further resolved these and showed that Asia I, Asia II-1, Asia II-5, Asia II-7, Asia II-8 and MEAM1 groups are present in the Indian subcontinent and Asia.

Numerous studies elaborate the biology, ecology and developmental characteristics of B. tabaci and its biotypes, i.e., B biotype (Perring 2001; Brown & Czosnek 2002; Jones 2003; Horowitz et al. 2005; Liu et al. 2007), Cv biotype (Qiu et al. 2011), Q biotype (Drost et al. 1998; Muniz & Nombella 2001) and Asia II-1 and MEAM 1 cryptic species (Ahmed et al. 2014). Biological variations of B. tabaci had also been reported according to host plants, viz., cotton (Bethke et al. 1991; Thomas et al. 2011), sweet pepper (Muniz & Nombella 2001), eggplant and tomato (Tsai & Wang 1996), and soybean and garden bean (Mansaray & Sundufu 2009). But corroboration of life history traits with molecular data and genetic grouping had been largely inadequate. In the present study, we compare the life history traits of 3 cryptic species Asia I, Asia II-1 (formally referred to as ZHJ2 biotype) and Asia II-7 (formally referred to as Cv biotype) collected from the agroclimatic zones of India, and reared on cotton under controlled environmental conditions.

Materials and Methods


Populations of B. tabaci were collected from 5 locations (Amravati, N 21°01′604″ E 77°55′004″, 367 m; Kalyani, N 23°37′36.2″ E 87°44′09.4″, 38 m; Ludhiana, N 30° 53′932″ E 75 48′229″, 240 m; Sriganganagar, N 29°45′205 ″ E 74°04′854 ″, 171 m and Delhi, N 28°38′28.1″ E 77°10′12.2″, 213 m asl) in various agroclimatic zones of India from their host plants viz., cotton (Gossypium spp.; Malvales: Malvaceae), brinjal (Solanum melongena L.: Solanales: Solanaceae) and leucaena (Leucaena spp.; Fabales: Fabaceae). These were reared for 6 generations on line ‘RCH138 BGII’ of hybrid cotton in an insect proof climate control chamber at the Indian Agricultural Research Institute, New Delhi, India. The methodology for maintaining pure colonies followed was as described by Luan et al. (2008). Briefly each B. tabaci population was maintained in a separate insect proof climate control chamber in an acrylic cage (61 × 61 cm) on line ‘RCH138 BGII’ of hybrid cotton at 28 ± 2 °C, 60 ± 5% RH and 10:14 h L:D. The purity of each of the 3 cryptic species was monitored every alternate generation using mitochondrial cytochrome oxidase 1 (mtCO1) gene sequence analysis. The samples drawn from these cultures were used for biological studies on the above line of hybrid cotton as well as for molecular confirmation of their genetic identities.


Genomic DNA was extracted from the whole adult female body as described by De Barro & Driver (1997). The PCR primers were employed to amplify a mtCO1 gene fragment (800–820) of B. tabaci (Frohlich et al. 1999) with the following PCR conditions: initial denaturation at 95 °C for 4 min followed by 35 cycles of 94 °C for 30 s, 47 °C for 40 s and 72 °C for 1 min with final extension of 72 °C for 10 min. The PCR products were purified and sequencing was performed by Scigenomics Pvt. Ltd. (Cochin, India).

The mtCO1 sequences obtained here were compared with those of the B. tabaci species complex from GenBank (Dinsdale et al. 2010; Hu et al. 2011). The sequences were aligned with the CLUSTAL W algorithm (Thompson et al. 1994) and distances were calculated with the Kimura 2-parameter model of MEGA5 (Tamura et al. 2013). The NJ (Neighbour-Joining) program available in MEGA6 (Tamura et al. 2013) was used to infer phylogenetic relationships, using B. afer (Priesner & Hosny) as an outgroup. One thousand bootstrap replicates were performed for each analysis.


To determine the duration of the various developmental stages, males and females were confined on the abaxial surface of a fully expanded leaf in micro-cages, as described by Zang et al. (2005) and Xu et al. (2010). The eggs laid were observed at 24 h intervals. Transitions not directly observed were inferred from changes in morphology and size, or from the presence of exuviae. A Leica ES2 stereozoom microscope was used to observe the life cycle stages and observations were replicated 20 times for each genetic group.


To evaluate the sex ratio, the adults emerging from the puparia were collected cage by cage and anaesthetized with carbon dioxide for 15–20 s; and their sexual gender was determined while these were inactive under the Leica ES2 stereozoom microscope taking into account their genitalia (Gill 1990). Twenty pairs of newly emerged adults (< 2 h) from each genetic group were randomly selected and confined in 20 clip cages for periodical observations on the preoviposition period.


To analyse longevity and fecundity, newly emerged males and females were confined in pairs in clip cages having minute holes on both sides (3 × 3 mm), on leaves of 5 to 10 day-old plants. Longevities of males and females, and numbers of eggs laid were recorded daily from 20 such pairs.


Univariate one way single factor ANOVA was performed individually for all the observations on life cycle stages to find out the significant variables (Kalaisekar et al. 2012). After this the pattern of clustering was analyzed using multivariate statistical approaches (Tabachnick & Fidell 2007). The Principal Component Analysis (PCA; SAS procedure; PRINCOMP; SAS version 9.1.3, SAS Institute Inc., Cary, NC, USA) was used without any prior assumption of grouping, and which assesses the components for total variation among the specimens by calculating linear combinations of variables that explain the maximum of the total variation. Canonical Discriminant Analysis (CDA; SAS procedure; CANDISC) was used for calculating the linear combinations of variables that maximize the separation of means of previously defined classes. Contributions of the variables best summarizing the differences between classes are revealed by this technique. Since, Discriminant Function Analysis (DFA; SAS procedure; DISCRIM) maximizes the variation among groups, it was used to separate cryptic species of B. tabaci based on life history data.



The PCR amplification of mtCO1 gene sequence was edited to remove PCR primer sequences, which yielded a ~750-bp fragment for each B. tabaci populations from the Amravati (KF298442), Kalyani (KF298441), Ludhiana (KF298443), Sriganganagar (KF298439) and Delhi (JQ023501) and these were compared with sequences of assigned members of B. tabaci species complex. Analysis of mtCO1 revealed that these were assignable to the Asia I, and Asia II groups namely Asia II-1 (formally referred to as the ZHJ2 biotype) and Asia II-7 (formally referred to as the Cv biotype). The Amravati and Kalyani populations clustered with Asia I, those of Ludhiana and Sriganganagar with Asia II-1, while the Delhi populations clustered with Asia II-7 cryptic species complex. All these populations showed 100% similarity with their respective sequences of assigned members of B. tabaci species complex.


The developmental periods of the 3 cryptic species of B. tabaci are shown in Table 1. The total developmental periods of Asia I, Asia II-1 and Asia II-7 ranged from 23.80 to 25.75 days. This period was slightly longer in Asia I than in the Asia II. Statistical analysis showed a significant difference in the total developmental period (F = 6.6246, df = 4, P < 0.001). The developmental periods of the egg, and the first, second, third and fourth instars were longer in Asia I than in Asia II, among which the durations of the egg and the fourth instar periods were significantly varying (F = 14.6818, df = 4, P < 0.001; F = 4.8298, df = 4, P < 0.001 respectively).


Results given in Table 1 indicate that females are always more numerous than males regardless of cryptic species. The highest sex ratio was recorded in Asia II-7 followed by Asia II-1 and lastly by Asia I, however the differences were not significant (F = 1.8496, df = 4, P = 0.05423). The preoviposition period, i.e., the period between adult emergence and egg deposition was the longest in Asia II-7 followed by Asia II-1 and shortest in Asia I, and these differences were statistically significant (F = 3.8298, df = 4, P < 0.001).

Table 1.

Development parameters of the genetic groups of Bemisia tabaci (mean ± SE in days, n = 20).



The longevity and fecundity data of the cryptic species are shown in Table 1. Male longevity was in the following declining order: Asia II-7 > Asia I > Asia II-1, and the differences were statistically significant (F = 8.4029, df = 4, P < 0.001). The female longevity was in the following declining order: Asia I > Asia II-1 > Asia II-7, and these differences too were statistically significant (F = 5.7036, df = 4, P < 0.001). Mean fecundity was in the following declining order: Asia II-7 > Asia II-1 > Asia I. However, variations in fecundity among the 3 cryptic species were statistically insignificant (F = 1.8496, df = 4, P = 0.1257). The mean percentage of survivorship was found nearly equal in all the 3 cryptic species, and these ranged from 68.49 to 69.12% and the variations were statistically insignificant (F = 2.4651, df = 4, P = 0.1638).


Life history data such as developmental periods of eggs and instars, longevity, fecundity, preoviposition period and sex ratio were subjected to PCA, which resulted in a reduction of dimensions and in the identification of the sources of variation. The first 4 principal components (PCs) each with an eigenvalue >1 were observed to account for 49.5% of total variation (Table 2). PC1 explained about 25% of the total variation and had a positive loading for 3 variables, i.e., egg, and first and third instars. PC2 explained about 19% of total variation having positive loading for 2 variables, i.e., second instar and the longevity of the male. The plot for first 2 PCs i.e., PC1 and PC2 shown in Fig. 1 brings out the grouping of the cryptic species. These reveal that separate clustering was observed for Asia I, Asia II-1 and Asia II-7 with slight overlap.

Canonical discriminant analysis (CDA) was carried out with prior grouping and use of the life history data as classification variables. The statistics namely Wilks' λ, Pillai's trace, Hotelling-Lawley Trace and Roy's greatest root (Table 3) were found to be significant at P < 0.0001. These statistics clearly depict the significant contribution towards the model with a lower Wilks' λ (0.2900), and which held true for all of the other statistics. The projection of biological data onto the first 2 canonical discriminant axes is shown in Fig. 2. The analysis was able to extract differences between the 3 cryptic species with slight overlap among them. The first canonical root clearly discriminates the cryptic species with the main contributions from the egg stage duration and the longevity of the female, while second canonical root was able to discriminate from the fourth instar and the longevity of the male (Table 2). This clustering obtained from CDA confirmed the grouping brought out by PCA. A cross validation of group membership was performed identifying the misclassification of specimens and assessing the utility of selected observations. Overall 70% of the classifications were correctly attributed with a relatively less misclassification. The result of cross validation accurately classified 85% of Asia II-1 populations followed by 75% of those of Asia I and 50% of Asia II-7 (Table 4).


The range of host plants and host plant suitability are considered as 2 major factors affecting the spread and damage of B. tabaci. Host plant suitability and biology had been earlier studied in detail (Bethke et al. 1991; Lin & Ren 2005; Lida et al. 2009; Oriani et al. 2011). The life history traits of Asia I, Asia II-1 and Asia II-7 reported herein add to the existing knowledge on the variations in B. tabaci species complex. In the present study, we found significant variations in the total developmental time, egg period and duration of the fourth instar. These are similar to the results obtained on cotton earlier (Bethke et al. 1991; Thomas et al. 2011). The developmental time from egg to adult of the 3 cryptic species ranged from 23.80 to 25.75 days when these were reared on cotton, which was longer than those reported for Asia II-1 from Pakistan (Ahmed et al. 2014) and for B biotype (now referred as MEAM1) (Lida et al. 2009) on different hosts, but nearly similar to the Cv biotype (now referred as Asia II-7) on cucumber and tomato (Qiu et al. 2011). This variation might be due to host plant because time required for B. tabaci to complete development from egg to adult was influenced by the host plant on which it fed (Coudriet et al. 1985; Mansary & Sundufu 2009).

Table 2.

Proportion of variation and variable coefficients for the life history data of B. tabaci species complex PC1, PC2, PC3 of PCA and standardized canonical coefficients (CDA)


Fig. 1.

Component analysis (PCA) showing the clustering of genetic groups of Bemisia tabaci species complex.


The largest sex ratio was recorded in Asia II-7 followed by Asia I and Asia II-1. The host plant was demonstrated to have a significant effect on the longevity and fecundity of B. tabaci (Qiu et al. 2003; Lin & Ren 2005; Qiu et al. 2011; Ahmed et al. 2014). Herein, we found that the longevity of both the male and the female varied significantly, ranging from 12.3 to 17.6 days despite being on the same host plant, i.e., cotton. The longevities of Asia I and Asia II-7 were similar to that of the Cv biotype on tomato, but differed from that of the B biotype (Qiu et al. 2011), which was in the range (10–15 days) reported by Gerling et al. (2001) for B. tabaci in the field at temperatures in the higher 20 °C. However the longevity of Asia II-1 was lesser than that reported by Ahmed et al. (2014), which was 28.8 ± 0.5 days. The fecundity variations were statistically insignificant, and fecundity was less than the reported fecundity of B biotype and Cv biotype on other hosts (Qiu et al. 2011) and of Asia II-1 on cotton (Ahmed et al. 2014), but nearly similar to the fecundity of B biotype on laurel and Cv biotype on poinsettia (Qiu et al. 2011).

Table 3.

Multivariate statistics and F approximations for the life history data of the Bemisia tabaci species complex.


Fig. 2.

Canonical discriminant functional analyses showing 3 genetic groups of Bemisia tabaci species complex.


The clustering of populations revealed through the results of the PCA and CDA of the life history data was identical to the genetic identity of the 3 cryptic species Asia I, Asia II-1 and Asia II-7 determined by molecular characterization. The genetic diversities of B. tabaci populations shown through various molecular studies (Dinsdale et al. 2010; De Barro et al. 2011; Reddy et al. 2012; Lee et al. 2013) were found to be in agreement with the present study. DFA with a higher classification (85%, 75% and 50%) values helps to establish the probable validity of these life history traits variations. Thus the biological data with the help of PCA and CDA might provide additional knowledge on the B. tabaci cryptic species complex known from India.

Table 4.

Cross validation matrix of the Discriminant Function Analysis (DFA) for life history data of the Bemisia tabaci species complex.



Support of the National Agricultural Innovation Project (NAIP) of the Indian Council for Agricultural Research (ICAR), India for funding this programme is acknowledged. The authors thank Dr. Pathania PC (Punjab Agricultural University, Ludhiana) and Dr. Nehra PL (S. K. Rajasthan Agricultural University, ARS, Sriganganagar, Rajasthan) for their help in field collections.

References Cited

  1. MZ Ahmed , PJ De Barro , JM Greeff , SX Ren , M Naveed , BL Qiu. 2011. Genetic identity of the Bemisia tabaci species complex and association with high cotton leaf curl disease (CLCuD) incidence in Pakistan. Pest Management Science 67: 307–317. Google Scholar

  2. MZ Ahmed , M Naveed , MN Ane , SX Ren , PJ De Barro , B Qiu. 2014. Host suitability comparison between the MEAM1 and Asia II1 cryptic species of Bemisia tabaci in cotton-growing zones of Pakistan. Pest Management Science 70: 1531–1537. Google Scholar

  3. MZ Ahmed , SX Ren , NS Mandour , MN Marathi , M Naveed , BL Qiu. 2010. Phylogenetic analysis of Bemisia tabaci (Hemiptera: Aleyrodidae) populations from cotton plants in Pakistan, China and Egypt. Journal of Pest Science 83: 135–141. Google Scholar

  4. GK Banks , J Colvin , RV Chowda , MN Maruthi , V Muniyappa , HM Venkatesh , KM Kiran , AS Padmaja , FJ Beitia , SE Seal. 2001. First report of the Bemisia tabaci B biotype in India and an associated tomato leaf curl virus disease epidemic. Plant Diseases 85: 231. Google Scholar

  5. JA Bethke , TD Paine , GS Nuessly. 1991. Comparative biology, morphometrics, and development of 2 populations of Bemisia tabaci (Homoptera: Aleyrodidae) on cotton and poinsettia. Annals of the Entomological Society of America 84: 407–411. Google Scholar

  6. J Bird. 1957. A whitefly transmitted mosaic of Jatropha gossypifolia. Technical Paper, University of Puerto Rico, Agricultural Experiment Station 22: 1–35. Google Scholar

  7. LM Boykin , P De Barro. 2014. A practical guide to identifying members of the Bemisia tabaci species complex: and other morphologically identical species. Frontiers in Ecology and Evolution 2: 45. doi: 10.3389/fevo.2014.00045Google Scholar

  8. LM Boykin , RG Shatters Jr , RC Rosell , CL Mckenzie , RA Bagnall , P De Barro , DR Frohlich. 2007. Global relationships of Bemisia tabaci (Hemiptera: Aleyrodidae) revealed using Bayesian analysis of mitochondrial COI DNA sequences. Molecular Phylogenetics and Evolution 44: 1306–1319. Google Scholar

  9. LM Boykin. 2013. Bemisia tabaci nomenclature: lessons learned. Pest Management Science doi:  10.1002/ps.3709Google Scholar

  10. LM Boykin , KF Armstrong , L Kubatko , PJ De Barro. 2012. Species delimitation and global biosecurity. Evolutionary Bioinformatics 8: 1–37. doi:  10.4137/EBO.S8532Google Scholar

  11. LM Boykin , CD Bell , G Evans , I Small , PJ De Barro. 2013. Is agriculture driving the diversification of the Bemisia tabaci species complex (Hemiptera: Sternorrhyncha: Aleyrodidae): Dating, diversification and biogeographic evidence revealed. BMC Evolutionary Biology 13: 228. doi:  10.1186/1471-2148-13-228Google Scholar

  12. JK Brown , H Czosnek. 2002. Whitefly transmission of plant viruses. Advances in Botanical Research 36: 65–100. Google Scholar

  13. DL Coudriet , N Prabhaker , AN Kishara , DE Meyerdirk. 1985. Variation in development rate on different hosts and overwintering of the sweetpotato whitefly Bemisia tabaci (Homoptera: Aleyrodidae). Environmental Entomology 17: 516–519. Google Scholar

  14. PJ De Barro , F Driver. 1997. Use of RAPD PCR to distinguish the B biotype from other biotypes of Bemisia tabaci (Gennadius) (Hemiptera, Aleyrodidae). Australian Journal of Entomology 36: 149–152. Google Scholar

  15. PJ De Barro , SS Liu , LM Boykin , AB Dinsdale. 2011. Bemisia tabaci: a statement of species status. Annual Review of Entomology 56: 1–19. Google Scholar

  16. A Dinsdale , L Cook , C Riginos , YM Buckley , PJ De Barro. 2010. Refined global analysis of Bemisia tabaci (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae) mitochondrial cytochrome oxidase 1 to identify species level genetic boundaries. Annals of the Entomological Society of America 101: 196–208. Google Scholar

  17. YC Drost , JC van Lenteren , HJW van Roermund. 1998. Life-history parameters of different biotypes of Bemisia tabaci (Hemiptera: Aleyrodidae) in relation to temperature and host plant: A selective review. Bulletin of Entomological Research 88: 219–229. Google Scholar

  18. DR Frohlich , JI Torres , ID Bedford , PG Markham , JK Brown. 1999. A phylogeographical analysis of the Bemisia tabaci species complex based on mitochondrial DNA markers. Molecular Ecology 8: 1683–1691. Google Scholar

  19. D Gerling , S Alomar , J Arno. 2001. Biological control of Bemisia tabaci using predators and parasitoids. Crop Protection 20: 779–799. Google Scholar

  20. RJ Gill. 1990. The morphology of whiteflies. Whiteflies: Their Bionomics, Pest Status and Management. Intercept, Andover. 1346 pp. Google Scholar

  21. AR Horowitz , S Kontsedalov , V Khasdan , I Ishaaya. 2005. Biotypes B and Q of Bemisia tabaci and their relevance to neonicotinoid and pyriproxyfen resistance. Archives of Insect Biochemistry and Physiology 58: 216–225. Google Scholar

  22. CH Hsieh , CH Wang , CC Ko. 2006. Analysis of Bemisia tabaci (Hemiptera: Aleyrodidae) species complex and distribution in Eastern Asia based on mitochondrial DNA markers. Annals of the Entomological Society of America 99: 768–75. Google Scholar

  23. J Hu , PJ De Barro , H Zhao , J Wang , F Nardi , SS Liu . 2011. An extensive field survey combined with a phylogenetic analysis reveals rapid and widespread invasion of two alien whiteflies in China. PLoS One, 6 (1): e16061. doi: 10.1371/journal.pone.0016061Google Scholar

  24. DR Jones. 2003. Plant viruses transmitted by whitefly. European Journal of Plant Pathology 109: 195–219. Google Scholar

  25. A Kalaisekar , VV Ramamurthy , JV Patil , A Dhandapani , Thakur NS Azad. 2012. Multivariate morphometrics of elytral colour polymorphism in seven-spotted ladybird beetle, Coccinella septempunctata L. (Coleoptera: Coccinellidae). Current Science 102(10): 1418–1425. Google Scholar

  26. W Lee , J Park , GS Lee , S Lee , S Akimoto . 2013. Taxonomic status of the Bemisia tabaci complex (Hemiptera: Aleyrodidae) and reassessment of the number of its constituent species. PLoS ONE 8(5): e63817. doi: 10.1371/journal.pone.0063817Google Scholar

  27. H Lida , T Kitamura , K Honda. 2009. Comparison of egg-hatching rate, survival rate and development time of the immature stage between B- and Q-biotypes of Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae) on various agricultural crops. Applied Entomology and Zoology 44: 267–273. Google Scholar

  28. L Lin , SX Ren. 2005. Development and reproduction of ‘B’ biotype Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae) on four ornamentals. Insect Science 12: 1–9. Google Scholar

  29. SS Liu , J Colvin , PJ De Barro. 2012. Species concepts as applied to the whitefly Bemisia tabaci systematics: how many species are there? Journal of Integrative Agriculture 11: 176–186. Google Scholar

  30. SS Liu , PJ De Barro , J Xu , JB Luan , LS Zang , YM Ruan , FH Wan. 2007. Asymmetric mating interactions drive widespread invasion and displacement in a whitefly. Science 318: 1769–1772. Google Scholar

  31. JB Luan , YM Ruan , L Zang , SS Liu. 2008. Pre-copulation intervals, copulation frequencies, and initial progeny sex ratios in two biotypes of whitefly, Bemisia tabaci. Entomologia Experimentalis et Applicata 129: 316–324. Google Scholar

  32. A Mansaray , AJ Sundufu. 2009. Oviposition, development and survivorship of the sweetpotato whitefly Bemisia tabaci on soybean, Glycine max, and the garden bean, phaseolus vulgaris. Journal of Insect Science 9: 1–6. Google Scholar

  33. CS Misra , SK Lambda. 1929. The cotton whitefly (Bemisia gossypiperda sp.). Bulletin of Agricultural Research Institute Pusa 196: 1–7. Google Scholar

  34. M Muniz , G Nombella. 2001. Differential variation in development of the B and Q biotypes of Bemisia tabaci (Homoptera: Aleyrodidae) on sweet pepper at constant temperature. Environmental Entomology 30: 720–727. Google Scholar

  35. MAG Oriani , JD Vendramim , CJ Vasconcelos. 2011. Biology of Bemisia tabaci (Genn.) B biotype (Hemiptera, Aleyrodidae) on tomato genotypes. Scientia Agriculturae 68(1): 37–41. Google Scholar

  36. TM Perring. 2001. The Bemisia tabaci species complex. Crop Protection 20: 725–737. Google Scholar

  37. BL Qiu , F Dang , SJ Li , MZ Ahmed , FL Jin , SX Ren , AGS Cuthbertson. 2011. Comparison of biological parameters between the invasive B biotype and a new defined Cv biotype of Bemisia tabaci (Hemiptera: Aleyradidae) in China. Journal of Pest Science 84: 419–427. Google Scholar

  38. BL Qiu , SX Ren , L Lin , PD Musa. 2003. Effect of host plants on the development and reproduction of Bemisia tabaci (Hemiptera: Aleyrodidae). Acta Ecologica Sinica 23: 1206–1211. Google Scholar

  39. RVC Reddy , M Kirankumar , ES Susan , V Muniyappa , GB Valand , MR Govindappa , J Colvin. 2012. Bemisia tabaci phylogenetic groups in India and the relative transmission efficacy of tomato leaf curl Bangalore virus by an indigenous and an exotic population. Journal of Integrative Agriculture 11(2): 235–248. Google Scholar

  40. BG Tabachnick , LS Fidell. 2007. Using multivariate statistics, 2nd Edition. Allyn and Bacon, Boston, MA, USA. Google Scholar

  41. K Tamura , G Stecher , D Peterson , A Filipski , S Kumar . 2013. MEGA6: Molecular Evolutionary Genetics Analysis version 6.0. Molecular Biology and Evolution 30: 2725–2729. Google Scholar

  42. A Thomas , R Chaubey , A Kar , NC Naveen , VV Ramamurthy. 2011. Bemisia tabaci (Gennadius) on Leucaena leucocephala: new host record from India and a comparative study with cotton populations. International Journal of Tropical Insect Science 31: 235–241. Google Scholar

  43. JD Thompson , DG Higgins , TJ Gibson. 1994. Clustal W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting position-specific gap penalties and weight matrix choice. Nucleic Acids Research 22: 4673–4680. Google Scholar

  44. JG Tsai , KH Wang. 1996. Development and reproduction of Bemisia argentifolii (Homoptera: Aleyrodidae) on 5 host plants. Environmental Entomology 25: 810–816. Google Scholar

  45. J Xu , PJ De Barro , SS Liu. 2010. Reproductive incompatibility among genetic groups of Bemisia tabaci supports the proposition that the whitefly is a cryptic species complex. Bulletin of Entomological Research 100: 359–366. Google Scholar

  46. LS Zang , YQ Liu , SS Liu. 2005. A new clip cage for whitefly experimental studies. Chinese Bulletin of Entomology 42: 329–331. Google Scholar

Rahul Chaubey, R .J. Andrew, N. C. Naveen, R. Rajagopal, and V. V. Ramamurthy "Life History Traits of Three Cryptic Species Asia I, Asia II-1 and Asia II-7 of Bemisia tabaci (Hemiptera: Aleyrodidae) Reconfirm Their Genetic Identities," Florida Entomologist 98(1), (1 March 2015).
Published: 1 March 2015

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