Morphometric study using wing image analysis for identification of the Bactrocera dorsalis complex (Diptera : Tephritidae)

Suwannee Adsavakulchai1, Visut Baimai1, Wudhibhan Prachyabrued2,

Paul J.Grote3 and Surat Lertlum4

1 Department of Biology and 2Department of Physics,

Faculty of Science, Mahidol University, Rama VI Road, Bangkok, 10400

3 School of Biology, Suranaree University of Technology

4 Faculty of Computer Science Program, Chulachomklao Military Academy

Correspondence should be addressed to Suwannee Adsavakulchai

Email : std77189@ait.ac.th

Submitted for publication: April 1998


Keywords: Bactrocera dorsalis complex, wing image processing, morphometric, discriminant and cluster analyses


  

ABSTRACT

Eight species of the Bactrocera dorsalis complex ( Diptera : Tephritidae ) used in this study included B. dorsalis,B. arecae, B. carambolae, B. payena, B. propinqua, B. pyrifoliae, B. verbascifoliae, and three new species complexes are Species E, Species K and Species P. Bactrocera tau was used as an out-group. A total of 424 wings of the adults emerged from pupae collected from natural populations in Thailand were prepared for measurements. Morphometric analysis was made from measuring wing vein characters. The wing image is captured in digital format and go through digital image processing to calculate Euclidean distance of each wing vein. Discriminant and cluster analyses were used for dichotomy of classification processes. All 424 wing specimens were classified to species in terms of the percentage of "grouped" cases which yielded about 89.6% accurate identification compared with the formal description of these species. After clustering, the percentage of "grouped" cases yielded about 100.0%, 98.9%, 98.1%, 95.2 and 84.6% accurate identification between the B. dorsalis complex and B. tau; B. arecae and Species E; B. dorsalis and B. verbascifoliae; B. propinqua and B. pyrifoliae; and Species K and Species P, respectively. This method of numerical taxonomy may be useful for practical identification of other groups of agricultural pests.


 

INTRODUCTION

The Oriental fruit fly, the Bactrocera dorsalis (Diptera : Tephritidae) group of the subgenus Bactrocera, has been considered one of the most important groups of agricultural pest in Southeast Asia because some of these species attack seed bearing organs of plants, including soft fruits and flowers (1). The B. dorsalis group comprises about 43 closely related species (2). Some of these species are morphologically similar. Drew (3). postulated that the Dacinae fruit flies originated in the Papua New Guinea area and speciated prolifically throughout the region. Drew and Hancock (2). listed fourteen closely related species of the B. dorsalis complex from Thailand on the basis of morphological characters. These species are B. arecae, B. carambolae, B. dorsalis, B. irvingiae, B. kanchanaburi, B. melastomatos, B. osbeckiae, B. papayae, B. propinqua, B. pyrifoliae, B. raiensis, B. thailandica, B. unimaculata and B. verbascifoliae. Recently, we provide population genetic data of some members of the B. dorsalis complex (4,5). Nonetheless, most species of the B. dorsalis complex have limited distribution within the tropical and subtropical regions (3). The limitation of the distribution range of these species is due in part to physical, climatic and gross vegetation factors. However, it is more likely that the distribution range correlated with the specificity on fruits of particular host plants. Yet little information is available on the range of host plants of these species.

The B. dorsalis complex is systematically one of the most interesting groups of insect pest (6). Because of similarity in external morphology among the members of the B. dorsalis complex and the geographic variation in morphology within each species, it has been very difficult to separate these species. Consequently, such morphological variation causes taxonomic problems (7). Thus, the most common errors are synonyms, homonyms, misidentifications and establishment of supra-specific groups based on questionable morphological characters (8). There is still a major need for more taxonomic study in correlation with population genetic investigations of the B. dorsalis complex to elucidate some sibling species problems. In most countries, there is a complete list of reference collections for identification purposes. For such research efforts, well trained taxonomists are required. In the history of the family Dacinae taxonomy, it is obvious that fruit flies caused major economic impacts on society, and there was a need to identify the species involved by the economic entomologists of the day. They worked tirelessly but left a legacy of taxonomic problems and misidentifications. Some of these systematic problems can be elucidated with the aid of recent development of taxonomic techniques such as cytotaxonomy and molecular biology as well as improved numerical taxonomy (9).

In our on-going research project in the biology of fruit flies in Thailand, we attempt to employ ecological observations in the fields and genetic investigations in laboratory coupled with morphological examination of larvae, pupae and adults to help solving the problems of some cryptic or isomorphic species. Thus some new sibling species of the B. dorsalis complex have been found through allozyme electrophoresis (5) and cytogenetic studies (4).

In this paper we describes the methodology of image analysis to acquire and quantify morphological characters of the wing veins of eight species of the B. dorsalis complex to a computer compatible form for practical and suitable identification of these species.


  

MATERIALS AND METHODS

Specimen collection. Eight species of the B. dorsalis complex used in this study include B. dorsalis (Hendel), B. arecae (Hardy & Adachi), B. propinqua (Hardy & Adachi), B. pyrifoliae (Drew and Hancock), B. verbascifoliae (Drew and Hancock), and three new species complexes are species E, species K and species P that morphological characters differ from the record of Drew and Hancock (4). In addition, Bactrocera tau (Walker) was used as the out-group. Larval specimens of these members of the B. dorsalis complex were obtained from a wide variety of infested fruits from various parts of Thailand (Table 1) . Some larvae were processed for mitotic karyotype study which provided a useful information for species identification. Most of larvae were reared either in the fields or in the laboratory allowing them to pupate and finally emerged as young adults. Some adults were processed for electrophoretic study to confirm the genetic species as determined by mitotic chromosome markers. Adults from each collection were examined morphologically for species identification in correlation with chromosomal evidence and electromorphic patterns of allozyme. Some adults were kept for wing specimens.The framework of the research as shown in figure 1.

Wing preparation. Wings of individual adults were detached from the thorax and they were placed on a cleaned microscopic slide. The wings were secured with Canada Balsam under a coverslip.

Image processing. Wing image processing procedure as shown in figure 2. The microscopic slide with wing samples was positioned on a Nikon SMZ-2T stereomicroscope with a low objective lens (1x). The vertical tube has a control light path switchover which allows the diversion of the right eye image to the camera. The Nikon E2s Digital Still Cameras was attached with CF projection lens (4x) that captured the wing image on the memory card. Digital imaging with high-resolution of 1.3 million pixels was then transferred to application handling JPEG (Joint Photographic Experts Group) files (see figure 3).

The original color image (JPEG : raster format) was transformed into gray scale in the form of BMP (BitMaP) raster file format that allows efficient localized image processing. From BMP, image was pre-processed by low-pass filtering with average of 3x3 to create smooth image (10), and then transformed the image by applying a linear function to enhance image by calculating the ratios from pixel values of the original image divided by pixel values of the smooth image. Then, the image was vectorized to create vector file format in DXF (Drawing eXchange File) file format, and manually adjusted it suitable for measuring the 30 wing veins (see figure 4). The vector file was used to create automatically the coverage that contained 30 data sets of each sample in terms of Euclidean distances. Euclidean distance is the measurement between the 2 co-ordinates and is computed as the square root of the sum of the squared differences as shown in the following formula : 

Euclidean distance (D) = [ (x-s)2 + (y-t)2] 1/2

 where Euclidean distance is the distance between two points : (x,y) is co-ordinate of p; (s,t) is co-ordinate of q

Statistical methods. The value in the results section is based on the discriminant and cluster analysis that equipped with the statistical software package, SPSS for window.


  
 

RESULTS

Our data showed that the length of a vein is correlated with the size of the wing. Ratios of the vein lengths provide a very effective means for recognizing trends in variation and for a quick diagnostic character. Discriminant function analysis was used to derive a function to provide a criteria for separation of the eight species used in this study. The percentage of "grouped" cases correctly classified with the accuracy of 89.6% as shown in (Table 2) . The linear discriminant function can completely discriminate members of the B. dorsalis complex from B. tau as following:

Y = 2.76 x1 + 9.85 x2 -16.74

where x1 = vein2/vein22, and x2 = vein3/vein8. Specimens are identified by the following rule :

If Y < 0 then species is Bactrocera dorsalis complex

If Y > 0 then species is Bactrocera tau

The eight species of the B. dorsalis complex can also be separated by using cluster analysis (see figure 5) . The results from cluster analysis show that the eight members of the B. dorsalis complex can be classified into 4 classes : (1) B. arecae and Species E; (2) B. verbascifoliae and B. dorsalis; (3) B. propinqua and B. pyrifoliae; and (4) Species K and Species P. Bactrocera tau was used as the out-group. Discriminant function analysis was used to derive a function to provide maximum values for separation of these 4 classes. The percentage of cases correctly classified "grouped" with confidence of 98.9%, 98.1%, 95.2% and 84.6%, respectively (Table 3) . The stepwise discriminant analysis procedure has certain advantages in reducing the use of a large number of variates to a small number of canonical variables. These selected variables are calculated as a ratio between each variables, which were then using discriminant analysis for classification in each group afterward. The stepwise discriminant analysis procedure was performed to take data correlation and to select variables for transformation in the next step. Finally, the best ratio was selected as an index for each species as shown in (Table 4) .

The results appears to be satisfactory in separation of these species of the B. dorsalis complex compared with the genetic data (4)and classical taxonomy (2).In addition, "Cluster Membership of Cases using Average Linkage (Between Groups)" among the eight species of the B. dorsalis complex and B. tau showed some overlapping characters since they are mixed characteristics which lead to difficulty in classification (see figure 5) . Moreover, dendrogram shows how the species could be overlapped as a result of genetic differentiation during the speciation processes (11).


  

DISCUSSION AND CONCLUSION

Yu, et al. (12) studied on morphometric analysis of linear wing measurements for identification of ichneumonid wasps using image analysis of wings. The authors outlined the procedure to digitize and to measure various elements of the wings with an image analyzer and the wing specimens were assigned to species by discriminant analysis and independent univariate. Recently, Weeks (13)developed Daisy (Digital Automated Identification System) that the pattern of veins and pigments on insects' wings are different and rather like fingerprints. They can screen five species of parasitic wasps from Central America. Recent advances in computer technology dealing with computerized acquisition of morphological characters of insects (14) has concentrated mainly on measuring projected image on digitizing tablets (15). Therefore linear measurements were taken by using a digitizing tablet connected to a computer. These technologies efficiently provide accurate measurement, and save development time. In addition, these methods can be easily repeated and can be made available to any user and to rework with minimum of effort. However, these methods have high cost of investment, software development and maintenance of equipment. It is the first step towards a completely automated insect identification technique.

The methodology used for discrimination of members of the B. dorsalis complex proposed in this study has some advantages over other tedious taxonomic techniques (e.g. cytotaxonomy and electrophoresis) for separation of closely related species of insect. First, this method does not required fresh specimens. Second, it can be operated by a person who has a minimal knowledge of taxonomy or for a non-taxonomists. Finally, this methodology described in this study seems to be promising for further development of on-line identification systems. It is clear that the data in the form of numerical tables can be easily stored and the computations can be swiftly made (16). The methodology of morphometric analysis described here also illustrates the rapid advance in automated methods of on-line biological classification scheme which may have implications in the field of agricultural entomology particularly in the tropical regions.


  

ACKNOWLEDGEMENTS

We wish to thank S. Tigvatananont for providing most of the dried specimens of the fruit flies used in this study. We are grateful to Hollywood International Ltd. for providing access to use Nikon E2 Series (Nikon Digital Still Camaras). This work was supported by the Thailand Research Fund (RTA 3880008).


  

REFERENCES

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