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. 2026 Apr 3;16:103900. doi: 10.1016/j.mex.2026.103900

Simple, rapid and cost-effective DNA extraction techniques for detection of economically important fruit flies in India

Suman Barman a, Shashank Pathour Rajendra a,, Damini Diksha b, Susheel Kumar Sharma b, Nitika Gupta b, Godavari Hadpad a, Mukesh Kumar Dhillon a, Soham Ray c
PMCID: PMC13100293  PMID: 42027885

Abstract

Fruit flies (Diptera: Tephritidae) include nearly 200 economically important species, many of which are quarantine pests. Accurate identification is vital for pest management, but morphological diagnosis is often difficult for non-specialists due to similarities in diagnostic traits. DNA barcoding has become the gold standard, providing precise species identification using molecular markers. However, conventional DNA extraction methods, though reliable, are time-consuming and require advanced laboratory facilities, while commercial kits are costly and unsuitable for large-scale use and resource-limited settings. To address this, we established four new rapid and inexpensive DNA extraction methods using Tween 20 + NaOH solution (RDI) buffer, Phosphate Buffer Saline (PBS), Tris-EDTA (TE) buffer and Chelex + Proteinase K solution (Chelex buffer). These methods consistently yielded DNA of sufficient quality and concentration across five major tephritid pests: Zeugodacus cucurbitae, Z. tau, Bactrocera dorsalis, B. divenderi and B. zonata. DNA integrity was confirmed through fluorometric and spectrophotometric analysis and successful amplification of the mitochondrial COI gene.

  • Here, we developed rapid and inexpensive DNA extraction protocols capable of producing DNA from five major fruit fly pests..

  • Requires only 20–45 min, without special equipment and produces DNA of sufficient quality for PCR-based barcoding.

  • Provides a practical alternative for resource-poor laboratories.

Keywords: Barcoding, Detection, Fruit flies, India, Low-cost, COI, PCR, Rapid-extraction

Graphical abstract

Image, graphical abstract

Figure generated using Biorender software.


Specifications table

Subject area Agricultural and Biological Sciences
More specific subject area DNA extraction of fruit flies
Name of your method Rapid DNA extraction and PCR amplification of mtCOI
Name and reference of original method NA
Resource availability All the resources used for this study are mentioned in this article and the supplementary material

Background

In recent years, molecular biology-based approaches in entomology, particularly in systematics, invasion biology, evolutionary ecology and biodiversity, have rapidly advanced, leading to deeper insights into insect behaviour and biology for effective management strategies [[1], [2], [3]]. Timely and accurate surveillance methods are crucial for monitoring of pest abundance and distribution, a vital component of pest management and decision-making programs, especially for pests with quarantine significance and invasion risk. Among the various available molecular tools, DNA barcoding has emerged as a cornerstone for precise and effective pest identification [3,4]. Extracting DNA of high yield and good quality from test specimens is a fundamental prerequisite for all molecular assays. Till date, numerous methods and commercially available kits have been developed and standardized for insect DNA isolation [5]. Most of these are time and labour intensive, require sophisticated laboratory setup and also challenging when processing large batches of samples within limited timeframes. The commercial DNA extraction kits are often feasible but are not so economical particularly for researchers in low- and middle-income countries worldwide. Current research efforts aim to reduce processing time, manual effort and expenses without compromising DNA yield quality. Rapid, straightforward and cost-effective extraction methods providing sufficient DNA purity and quantity would significantly enhance the efficiency of molecular analysis [6]. Among insect pests, fruit flies (Diptera: Tephritidae) are globally recognized as serious threats to horticultural crop production and trade, posing major challenges for policymakers, quarantine authorities and traders [7]. The worldwide trading of fresh fruit and vegetable and increase in human movement, has significantly raises the risk of biological invasions [8]. Among the major tephritid pests, Zeugodacus cucurbitae (Coquillett, 1899), Z. tau Walker, 1849, Bactrocera dorsalis (Hendel, 1912), B. zonata (Saunders, 1842) and B. divenderi Maneesh, Hancock and Prabhakar, 2022 are economically important and listed as quarantine pest [[9], [10], [11], [12], [13], [14]]. Diagnosis of fruit flies mainly relies on microscopic inspection of key phenotypic characteristics of adults, whereas identifying immature stages like larvae is often more challenging [15]. A range of molecular techniques are available for fruit fly diagnostics which comprises analysis of protein or allozyme variation and DNA sequence diversity [16]. DNA-based methods commonly include RAPD [17], AFLP [18], RFLP [19], DNA barcoding [[20], [21], [22]] and species-specific marker based-PCR and qPCR assays [[21], [22], [23], [24]]. Among these, DNA barcoding, involving direct sequencing of a mitochondrial gene region, offers higher resolution for species identification and is increasingly becoming the preferred molecular method for diagnostics [17,25]. In the present study, four new rapid, simple and cost-effective DNA extraction methods were established for five major economically important tephritid pests. These methods yielded DNA of adequate quality and quantity suitable for downstream molecular applications like barcoding and the methods can also be used for on-site diagnostics such as Loop-mediated isothermal amplification (LAMP) [26] and Recombinase polymerase amplification (RPA) [27]. Recent advances in smart pest surveillance systems integrate molecular diagnostics with Internet of Things (IoT) platforms and machine learning-based data analytics to process heterogeneous and dynamic datasets for real-time monitoring and decision making in agriculture [28]. In such frameworks, rapid DNA extraction methods can serve as the front-end step for molecular detection, enabling faster data acquisition in biosecurity and pest surveillance networks. The optimized methods are anticipated to improve diagnostic efficiency and facilitate a broad range of molecular analysis.

Method details

Insect specimens

In this study, five economically important tephritids, Z. cucurbitae, Z. tau, B. dorsalis, B. zonata and B. divenderi were used for the establishment and validation of rapid DNA extraction methods (Supplementary fig. 1–2). DNA was extracted using 10 individuals each from larval, pupal and adult stages of Z. cucurbitae for standardization of the methods and 5–6 mg larval and pupal samples and 3 legs from adults were taken for DNA extraction following new methods.

Materials

DNA extraction protocols

Method 01: RDI buffer

Samples were placed in 50 μl of RDI buffer (Table 1) and homogenized using a micro-pestle followed by incubation at 95 °C for 15 mins. Following incubation, the tubes were centrifuged at 10,000 rpm for 2 mins to bring tissue debris to bottom of the tubes, the tissue free aqueous layer was collected for downstream applications (Fig. 1).

Table 1.

Composition of the lysis buffers used for rapid, simple and cost-effective DNA extraction.

Sl. No. Lysis Solution Composition
1. Rapid DNA isolation (RDI) buffer 20 μl 0.2% NaOH, 5 μl 4.5% Tween 20 and 25 μl of nuclease free water
2. Phosphate buffer saline (PBS) 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4 and 1.8 mM KH2PO4
3. Tris EDTA (TE) buffer
  • 0.01 M Tris–HCl pH 8.0, 0.001 M EDTA pH 8.0

4. Chelex buffer 5% Chelex 100 resin (w/v) and 70 μg/ml Proteinase K
Fig. 1.

Fig 1 dummy alt text

Procedure of DNA extraction from fruit flies.

Method 02: PBS

Specimens were taken in 50 μl of 1X PBS (Table 1) and crushed through micro pestle and incubated for 15 min at 95 °C. The mixture then cooled down to room temperature and stored for further use. The tubes were centrifuged at 12,000 rpm for 3 min before and after incubation (Fig. 1).

Method 03: TE buffer

Insect tissues were homogenized in 50 μl of TE buffer (Table 1) and incubated at 95 °C for 15 min followed by centrifugation @10,000 rpm for two min. The upper aqueous layer containing DNA was used for further downstream applications (Fig. 1).

Method 04: Chelex buffer

Tissue samples were crushed in 50 μl of Chelex buffer (Table 1) and incubated for at 55 °C for 30 min following heat inactivation of the enzyme Proteinase K at 95 °C for 10 min. The tubes were then either centrifuged @10,000 rpm for 2 min or left undisturbed at room temperature for 3–5 min to allow the Chelex to settle (Fig. 1).

Method validation

A total of 144 specimens, including larvae, pupae and adults of four economically important tephritids, Z. tau, B. dorsalis, B. zonata and B. divenderi were used to validate the four DNA extraction methods and assess the PCR suitability of extracted DNA using barcoding (Fig. 2). Three samples each of larvae, pupae, and adults were taken for each species. Some specimens were freshly collected using pheromone traps, while others had been preserved in ethanol for up to one year prior to use in this validation (Supplementary Table 1).

Fig. 2.

Fig 2 dummy alt text

Workflow of Barcoding of economically important fruit flies using simple, cost-effective and rapid methods of DNA extraction (Figure generated using Biorender software).

Spectrophotometric assessment

The yield and quality of DNA obtained through the various extraction methods described above were assessed with a spectrophotometer (NanoDropTM One, Thermo-Fisher Scientific). For Z. cucurbitae DNA, extracted from larval stage, the highest concentration was found using chelex buffer (629.9 ± 66.58 ng/μl), followed by PBS (563.7 ± 35.59 ng/μl) and RDI buffer (541.1 ± 31.53 ng/μl) and the lowest concentration was found using TE buffer (528.40 ± 70.58 ng/μl). When DNA extracted from pupal stage, method using the RDI buffer has given the highest concentration i.e. 1440 ± 56.23 ng/μl followed by TE buffer (1337.9 ± 41.20 ng/μl) and chelex buffer (1184 ± 63.68 ng/μl). The lowest concentration of the DNA extracted from pupal stage is observed in case of PBS (1082.20 ± 108.65 ng/μl). For DNA extracted from the adult stage, the highest concentration is observed using RDI buffer (596.2 ± 32.71 ng/μl) followed by chelex buffer (501.2 ± 88.95 ng/μl) and TE buffer (355.6 ± 43.46 ng/μl) whereas the lowest concentration observed in case of PBS (283.10 ± 65.42) (mean ± SD, n = 10 samples for each method).

Purity (A280/260) of DNA extracted from Z. cucurbitae using rapid methods using RDI buffer, PBS, TE buffer and Chelex buffer, ranged from 1.91 ± 0.01 – 1.95 ± 0.01, 1.76 ± 0.009 – 1.77 ± 0.01, 1.95 ± 0.02 – 2.00 ± 0.01 and 1.74 ± 0.03 – 1.84 ± 0.02 respectively, across larval, pupal adult stages (mean ± SD, n = 10 samples for each method). The spectrophotometric yield and purity of extracted DNA from Z. tau, B. dorsalis, B. zonata and B. divenderi were provided in the supplementary Table 2–6.

Fluorometric assessment

In fluorometric assessment, the highest larval DNA concentration is observed using Chelex buffer (30.41 ± 1.87 ng/μl) followed by PBS (24.88 ± 1.03 ng/μl) and TE buffer (23.48 ± 0.53 ng/μl), whereas the lowest concentration was found using RDI buffer (23.00 ± 0.09 ng/μl). For pupal DNA, the highest concentration was observed using the RDI buffer (58.92 ± 3.76 ng/μl) followed by PBS (50.56 ± 2.59 ng/μl) and TE buffer (48.92 ± 4.32 ng/μl), while the lowest concentration was encountered by using Chelex buffer (28.45 ± 1.22 ng/μl). The maximum adult DNA concentration was achieved using Chelex buffer (19.7 ± 1.95 ng/μl), followed by RDI buffer (15.9 ± 0.77 ng/μl) and TE buffer (13.64 ± 2.56 ng/μl) while the lowest concentration was observed using PBS (12.04 ± 1.24 ng/μl) (mean ± SD, n = 10 samples for each method). The fluorometric concentration of DNA extracted from Z. tau, B. dorsalis, B. zonata and B. divenderi were provided in the supplementary Table 2–6).

PCR validation and PCR product analysis

The standard barcoding gene of mitochondria i.e. COI was amplified using the widely used primer pair, LCO1490 and HCO2198 [25]. Each 25 μl of reaction mixture contained 12.5 μl of DreamTaq® Master Mix (Thermo Scientific), 1 μl of each primer (10 μM), 1 μl of template DNA and 9.5 μl of nuclease free water. The thermal cycling parameters, followed for reaction were as follows: initial denaturation at 95 °C for 4 min; 35 cycles of 95 °C for 1 min, 52 °C for 1 min, and 72 °C for 1 min 30 sec; followed by a final extension at 72 °C for 7 min. Products of PCR reaction were segregated through gel electrophoresis in 1.6% agarose gel containing ethidium bromide (Thermo Scientific) and 100 bp DNA ladder (GeneDirex®). Results were visualised and documented using gel documentation unit (BioRad Laboratories Inc. USA). Subsequently, the positive products were sequenced through sanger sequencing method from Barcode Bioscience (Karnataka, India) to validate the amplification quality. The obtained sequences were then bioinformatically assessed using BioEdit version 7.2.5, CLC Sequence Viewer version 8.0, Finch TV version 1.4.0 and NCBI BLAST software (Supplementary fig 3–6). The newly generated sequences (Supplementary Table 7) were compared with NCBI reference database sequences of the selected species and a phylogenetic tree was also constructed using the generated sequences through the new methods taking retrived Culex quinquefasciatus sequences as an outgroup (Supplementary fig. 7).

PCR amplification success across different extraction methods, species and life stages is presented in supplementary Table 8 and supplementary fig. 8–13. Among the four methods, RDI and PBS exhibited the highest consistency, with successful amplification observed in the majority of samples, whereas Chelex buffer showed moderate success with some variability across developmental stages and TE buffer exhibited comparatively lower success rates, particularly in certain larval and pupal samples. Reduced amplification in certain samples may be attributed to the presence of PCR inhibitors from gut contents in larval stages and to inhibitory compounds and co-extracted pigments in pupal and adult stages.

Statistical analysis

The mean DNA concentration obtained from spectrophotometric and fluorometric measurements and along with purity (A280/260 and A260/230) derived from spectrophotometric readings, across different extraction methods were analyzed using one-way ANOVA in SPSS software version 2022. Statistical significance was determined at the 95% confidence level (p < 0.005). One-way ANOVA revealed that the effect of DNA extraction methods varied across species and developmental stages. In Z. cucurbitae, significant differences were observed in most parameters, particularly in pupal and adult stages, indicating strong method dependent variation in DNA yield and quality (Supplementary Table 9–11). In Z. tau and B. dorsalis, larval stages showed no significant differences, while pupal and adult stages exhibited selective variation mainly in DNA concentration (Supplementary Table 12–17). In B. zonata, significant differences were primarily limited to Qubit-based DNA yield, especially in larval and pupal stages, with comparable DNA purity across methods (Supplementary Table 18–20). In B. divenderi, extraction methods significantly influenced DNA yield and organic contamination in most stages, while protein purity remained largely unaffected (Supplementary Table 21–23). Overall, DNA extraction efficiency and quality were more variable in pupal and adult stages than in larvae, with Qubit measurements showing greater sensitivity to differences among methods.

Suitability of different extraction methods

The methods are simple, rapid and low-cost DNA, requiring only 20–45 min, and provide a practical alternative for laboratories in resource-poor laboratories (Supplementary Table 24). Based on concentration, purity and PCR success, the RDI buffer consistently produced high DNA yield with reliable amplification, making it suitable for rapid and routine diagnostics. PBS buffer showed the most consistent PCR success across species and life stages, therefore recommended for routine and high-throughput applications. TE buffer yielded comparatively cleaner DNA, but showed lower amplification success in some samples, indicating its suitability where DNA purity and stability are prioritized. In contrast, the Chelex method provided relatively higher fluorometric DNA concentrations but variable PCR performance suggesting its use in applications requiring higher DNA yield with moderate consistency. Despite these variations, all methods yielded DNA suitable for DNA barcoding.

Key findings

  • Establishment of four simple, rapid and low-cost DNA extraction methods from major fruit fly pests.

  • The methods require only 20–45 min, without special equipment and produces DNA of sufficient quality for PCR-based barcoding.

  • Provides a practical alternative for laboratories in resource-poor laboratories.

Limitations

None

Ethics statements

In compliance with institutional norms, we followed laboratory safety protocols and handled fruit fly specimens in a safe manner during our experimental investigations.

CRediT author statement

P.R.S., conceptualized and supervised the research. S.B., P.R.S. and S.K.S designed the research. Laboratory experiments done by S.B. non-target insects were sourced and identified by S.B. and G.H. P.R.S., S.K.S and N.G. planned and assisted with the implementation of this study. S.B. and D.D. drafted the initial manuscript which was revised by all the authors. P.R.S., S.K.S., S.R. and N.G. critically reviewed the manuscript. P.R.S. and M.K.D. involved in funding the work. All authors read, edited and approved the manuscript.

Supplementary material and/or additional information [OPTIONAL]

Provided separately

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Research was supported by the Indian Council of Agricultural Research (ICAR), Department of Agricultural Research and Education (DARE), Government of India. We acknowledge The Graduate School, ICAR-Indian Agricultural Research Institute, New Delhi for providing ICAR-PG Fellowship to first author. P.R.S acknowledges Indian Council of Agricultural Research and ICAR-IARI for funded project titled “Genome editing for improving resource use efficiency, quality, stress tolerance and yield of crops (Flagship Project: CRSCIARISIL20210053338)” and Dr. Viswanathan Chinnusamy, JD(Research), ICAR-IARI for supporting the work. We acknowledge Ms. Sudipa Das, Dr. Mailem Yazing Shimray and Mr. Suraj Singh Rawat for helping laboratory work.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.mex.2026.103900.

Contributor Information

Suman Barman, Email: sumanbarman21302@gmail.com.

Shashank Pathour Rajendra, Email: spathour@gmail.com.

Damini Diksha, Email: daminidiksha@gmail.com.

Susheel Kumar Sharma, Email: susheelsharma19@gmail.com.

Nitika Gupta, Email: nitika.iari@gmail.com.

Godavari Hadpad, Email: godavarihadpad14@gmail.com.

Mukesh Kumar Dhillon, Email: mukeshdhillon@rediffmail.com.

Soham Ray, Email: sohamray27@gmail.com.

Appendix. Supplementary materials

mmc1.docx (17.1MB, docx)

Data availability

No data was used for the research described in the article.

References

  • 1.Cusson M. The molecular biology toolbox and its use in basic and applied insect science. BioSci. 2008;58(8):691–700. doi: 10.1641/B580806. [DOI] [Google Scholar]
  • 2.Christiaens O., Niu J., Nji Tizi T.C. RNAi in insects: a revolution in fundamental research and pest control applications. Insects. 2020;11(7):415. doi: 10.3390/insects11070415. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Shashank P.R., et al. DNA barcoding of insects from India: current status and future perspectives. Mol. Bio. Rep. 2022;49(11):10617–10626. doi: 10.1007/s11033-022-07628-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Madden M.J., Young R.G., Brown J.W., Miller S.E., Frewin A.J., Hanner R.H. Using DNA barcoding to improve invasive pest identification at US ports-of-entry. PLoS One. 2019;14(9) doi: 10.1371/journal.pone.0222291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Murthy M.K., Khandayataray P., Tara M., Buragohain P., Giri A., Gurusubramanian G. Optimisation of DNA isolation and PCR techniques for beetle (Order: coleoptera) specimens. Int. J. Trop. Insect Sci. 2022;42(3):2761–2771. doi: 10.1007/s42690-022-00736-3. [DOI] [Google Scholar]
  • 6.Ekesi S., De Meyer M., Mohamed S.A., Virgilio M., Borgemeister C. Taxonomy, ecology, and management of native and exotic fruit fly species in Africa. Annu. Rev. Entomol. 2016;61(1):219–238. doi: 10.1146/annurev-ento-010715-023603. [DOI] [PubMed] [Google Scholar]
  • 7.Hulme P.E. Trade, transport and trouble: managing invasive species pathways in an era of globalization. J. Appl. Ecol. 2009;46(1):10–18. doi: 10.1111/j.1365-2664.2008.01600.x. [DOI] [Google Scholar]
  • 8.Singh S.K., David K.J., Ramani S., Sachin K. An updated checklist for fruit flies (Diptera: tephritidae) of India with new species and new distribution records. Zootaxa. 2025;5607(1):1–71. doi: 10.11646/zootaxa.5607.1.1. [DOI] [PubMed] [Google Scholar]
  • 9.Singh S.K., Kumar D., Ramamurthy V.V. Biology of Bactrocera (Zeugodacus) tau (Walker) (Diptera: tephritidae) Entomol. Res. 2010;40(5):259–263. doi: 10.1111/j.1748-5967.2010.00296.x. [DOI] [Google Scholar]
  • 10.Sh W., Kerdelhue C., Ye H. Genetic structure and colonization history of the fruit fly Bactrocera tau (Diptera: tephritidae) in China and Southeast Asia. J. Econ. Entomol. 2014;107(3):1256–1265. doi: 10.1603/EC13266. [DOI] [PubMed] [Google Scholar]
  • 11.Dhillon M.K., Singh R., Naresh J.S., Sharma H.C. The melon fruit fly, Bactrocera cucurbitae: a review of its biology and management. J. Insect Sci. 2005;5(1):40. doi: 10.1093/jis/5.1.40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Lall B.S., Singh B.N. Studies on the biology and control of melon fly Dacus cucurbitae (Coq.) diptera, trypetidae, Labdev. J. Sci. Tech. B. 1969;7(2):148–153. [Google Scholar]
  • 13.A. Bakri, Bactrocera cucurbitae (melon fly), CABI Compendium. (2008), 10.1079/cabicompendium.17683. [DOI]
  • 14.Blacket M.J., Semeraro L., Malipatil M.B. Barcoding Queensland fruit flies (Bactrocera tryoni): impediments and improvements. Mol. Eco. Res. 2012;12(3):428–436. doi: 10.1111/j.1755-0998.2012.03124.x. [DOI] [PubMed] [Google Scholar]
  • 15.Dadour I.R., Yeates D.K., Postle A.C. Two rapid diagnostic techniques for distinguishing Mediterranean fruit fly from Bactrocera tryoni (Froggatt) (Diptera: tephritidae) J. Econ. Entomol. 1992;85(1):208–211. doi: 10.1093/jee/85.1.208. [DOI] [Google Scholar]
  • 16.Armstrong K.F., Ball S.L. DNA barcodes for biosecurity: invasive species identification. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 2005;360(1462):1813–1823. doi: 10.1098/rstb.2005.1713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Kakouli-Duarte T., Casey D.G., Burnell A.M. Development of a diagnostic DNA probe for the fruit flies Ceratitis capitata and Ceratitis rosa (Diptera: tephritidae) using amplified fragment-length polymorphism. J. Econ. Entomol. 2001;94(4):989–997. doi: 10.1603/0022-0493-94.4.989. [DOI] [PubMed] [Google Scholar]
  • 18.Chua T.H., Chong Y.V., Lim S.H. Species determination of Malaysian Bactrocera pests using PCR-RFLP analyses (Diptera: tephritidae) Pest. Manag. Sci. 2010;66(4):379–384. doi: 10.1002/ps.1886. [DOI] [PubMed] [Google Scholar]
  • 19.Onah I.E., Taylor D., Eyo I.E. Molecular identification of tephritid fruit flies (Diptera: tephritidae) infesting sweet oranges in Nsukka Agro-Ecological Zone, Nigeria, based on PCR-RFLP of COI gene and DNA barcoding. Afr. Entomol. 2015;23(2):342–347. https://hdl.handle.net/10520/EJC176579 [Google Scholar]
  • 20.Zhang Y., Singh S., Kaur S., Li Z.H. Molecular identification of Bactrocera zonata (Diptera: tephritidae) based on DNA barcoding. Plant Quar. 2019;33:1. [Google Scholar]
  • 21.Jiang F., Fu W., Clarke A.R., Schutze M.K., Susanto A., Zhu S., Li Z. A high-throughput detection method for invasive fruit fly (Diptera: tephritidae) species based on microfluidic dynamic array. Mol. Eco. Res. 2016;16(6):1378–1388. doi: 10.1111/1755-0998.12542. [DOI] [PubMed] [Google Scholar]
  • 22.Koohkanzade M., Zakiaghl M., Dhami M.K., Fekrat L., Namaghi H.S. Rapid identification of Bactrocera zonata (Dip.: tephritidae) using TaqMan real-time PCR assay. PLoS One. 2018;13(10) doi: 10.1371/journal.pone.0205136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Zheng L., et al. New species-specific primers for molecular diagnosis of Bactrocera minax and bactrocera tsuneonis (Diptera: tephritidae) in China based on DNA barcodes. Insects. 2019;10(12):447. doi: 10.3390/insects10120447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Blacket M., Semeraro L., Malipatil M. The Australian Handbook For the Identification of Fruit Flies, Version 1. 2011. DNA barcoding in tephritid fruit flies; pp. 44–49. [Google Scholar]
  • 25.Folmer O., Black M., Hoeh W., Lutz R., Vrijenhoek R. DNA primers for amplifcation of mitochondrial cytochrome oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 1994;3:294–299. [PubMed] [Google Scholar]
  • 26.Starkie M.L., et al. Loop-mediated isothermal amplification (LAMP) assays for detection of the New Guinea fruit fly Bactrocera trivialis (Drew) (Diptera: tephritidae) Sci. Rep. 2022;12 doi: 10.1038/s41598-022-16901-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Li W., Cai B., Chen R., Cui J., Wang H., Li Z. Application of recombinase polymerase amplification with CRISPR/Cas12a and multienzyme isothermal rapid amplification with lateral flow dipstick assay for Bactrocera correcta. Pest. Manag. Sci. 2024;80(7):3317–3325. doi: 10.1002/ps.8035. [DOI] [PubMed] [Google Scholar]
  • 28.Chahal A., Addula S.R., Jain A., Gulia P., Gill N.S. Systematic analysis based on conflux of machine learning and Internet of things using bibliometric analysis. J. Intell. Syst. Internet Things. 2024;13(1):196–224. doi: 10.54216/JISIoT.130115. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

mmc1.docx (17.1MB, docx)

Data Availability Statement

No data was used for the research described in the article.


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