Journal of Threatened Taxa |
www.threatenedtaxa.org | 26 July 2024 | 16(7): 25528–25535
ISSN 0974-7907
(Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.8983.16.7.25528-25535
#8983 | Received 19
February 2024 | Final received 28 June 2024 | Finally accepted 15 July 2024
Assessment of the status of Spodoptera species (Lepidoptera: Noctuidae:
Armyworm) in India through DNA barcoding technique
Dinesh Nalage
1 , P.S. Kudnar
2, Tejswini Sontakke
3 , Ishwar Chittapure 4 , Yashdeep Gowda 5 , Shantanu Kharbal
6 & Yashashri
Alamwar 7
1,4,5,6,7 Department of Molecular Biology
and Microbiology, IBT, MGM University, Aurangabad, Maharashtra 431103, India.
2 Post-Graduate Research Centre,
Department of Zoology, Modern College of Arts, Science and Commerce
(Autonomous), Shivajinagar, Pune, Maharashtra 411005, India.
3 Department of Zoology, MGV’s, MPH
Mahila Mahavidyalaya,
Malegaon, District Nashik, Maharashtra 423105, India.
1 dnalage@mgmu.ac.in (corresponding
author), 2 kpravin95@gmail.com, 3 tejaswinisontakke27@gmail.com,
4 ichittapure@gmail.com,
5 yashdeepgowda@gmail.com, 6 kharbalshantanu@gmail.com,
7 yashashri.mobile@gmail.com
Editor: Mandar Paingankar, Government Science College Gadchiroli,
Maharashtra, India. Date of
publication: 26 July 2024 (online & print)
Citation: Nalage, D., P.S. Kudnar, T. Sontakke, I. Chittapure, Y. Gowda, S. Kharbal
& Y. Alamwar (2024).
Assessment of the status of Spodoptera species
(Lepidoptera: Noctuidae: Armyworm) in India through
DNA barcoding technique. Journal of Threatened Taxa 16(7):
25528–25535. https://doi.org/10.11609/jott.8983.16.7.25528-25535
Copyright: © Nalage et al. 2024. Creative Commons Attribution 4.0
International License. JoTT allows unrestricted use,
reproduction, and distribution of this article in any medium by providing
adequate credit to the author(s) and the source of publication.
Funding: None.
Competing interests: The authors declare no competing interests.
Author details: Dinesh Nalage is assistant professor in MGM University. He is expert in molecular taxonomy. P.S. Kudnar is assistant professor in Modern College of Arts, Science and Commerce, Shivajinagar, Pune. His research interests include Hydrobiology and Entomology. Tejswini Sontakke is assistant professor in MGV’s, MPH Mahila Mahavidyalaya, Malegaon, District Nashik. Her research interests include Entomology and Hydrobiology. Ishwar Chittapure is undergraduate student of Biotechnology. Yashdeep Gowda is undergraduate
student of Biotechnology. Shantanu Kharbal is graduate student of Microbiology. Yashashri Alamwar is graduate student of Biotechnology.
Author contributions: DN, IC, TS and YG conducted the investigation, collected, and curated the data, and wrote the original draft of the
manuscript. SK, YA and PK contributed to the development of the initial concept of the study and was responsible for the design and implementation of the methodology also he was responsible for reviewing and editing the manuscript, creating visualizations, and supervising the overall progress of the study. All authors have read and approved the final manuscript.
Acknowledgements: We would like to express our
sincere gratitude to the vice chancellor and registrar of MGM University for
their continuous support and encouragement. We extend our heartfelt thanks to
the director of the Institute of Biosciences and Technology for providing the
necessary resources and guidance throughout this study. Special thanks to Prof. Sanjay Harke for his
invaluable insights and assistance, which significantly contributed to the
success of this research.
Abstract: Insects constitute the majority
of animal fauna worldwide, but quantifying their
species diversity is still incomplete. A few recent studies indicate a marked
decrease in the population of insects which calls for urgent efforts to
document and understand insect diversity to get a complete picture of Earth’s
ecosystems. Modern technology can accelerate species identification beyond
traditional methods’ limitations. Hence, a focused and expedited approach
through DNA barcoding coupled with morphological identification is necessary.
This present research highlights the gaps that exist
and it examines the current status of Spodoptera
species barcode in India. Six Spodoptera
species were studied confirming their presence in India including two invasive
species. That means less than 50% of taxa or described Spodoptera
species are covered by genetic data from barcoded specimens after analysis.
Therefore, comprehensive DNA barcoding should be achieved from all insect
species occurring on the Indian subcontinent to speed up the discovery and
documentation of new species by involving both traditional taxonomists and
molecular biologists working towards a common goal.
Keywords: Biodiversity in India,
conservation, current status, insect, identification, molecular biology,
species, taxa.
Introduction
Identifying insect species is
crucial for understanding ecological, evolutionary, and conservation-related
queries. Properly diagnosing these species is vital for monitoring biodiversity
and utilizing it effectively (Khedkar et al. 2016).
Despite the contributions of the long-standing Linnaean classification system
to taxonomy, its reliance on morphology has limitations. These limitations,
like difficulties in resolving cryptic species and identifying immature stages,
hinder progress. Furthermore, the scarcity of experts in morphotaxonomy
restricts this approach (Shashank et al. 2022), leaving many species
undiscovered or known only through descriptions and lost type specimens. The
backlog of unidentified specimens in museum collections has existed for decades.
After its introduction in 2003, DNA barcoding has evolved as a complementing
technique to conventional taxonomy (Hebert et al. 2003). By characterizing
species using standardized DNA regions, DNA barcoding aids in identifying
cryptic species, and immature stages, and rapidly distinguishing species in
various contexts, such as identification food stuff (Khilare
et al. 2019; Tiknaik et al. 2019; Suryawanshi
et al. 2020). However, creating high-quality reference libraries based on
voucher specimens remains crucial for its applications. Despite challenges due
to the vast diversity of life forms and limited taxonomic expertise, several
countries, including India, have created massive DNA barcode reference
collections for certain creature categories, such as insects. India, known for
its rich insect diversity, houses a significant portion of the world’s insect
fauna.
Major biotic stress on crops is
insect pests. Hundreds of insects can cause severe crop damage (Mahmood-ur-Rahman et al. 2014; Nalage et
al. 2023). The Spodoptera (Lepidoptera: Noctuidae) genus comprises a few of the world’s most
important crop predators. They are commonly referred to as ‘armyworms’.
Thirty-one species have been described with members present on six continents (Kergoat et al. 2021). These species feed on a wide range of
vegetable, grain, row, forage, and ornamental crops. While young larvae burn
leaf tissue and skeletonize into leaves, advanced stages on all leaves are
roughly and brutally fed and transported from leaf to leaf (Chandel
et al. 2013). The group Spodoptera includes
species closely related to a similar ecology, difficult to identify at the
level of the species (Henaish & Elmetwaly 2020). It is also referred to as the caterpillar
cluster, cotton leaf worm, tropical armyworm, and tobacco cutworm (Meagher et
al. 2008).
So far, DNA barcoding in
Lepidoptera has shown mixed success in determining species. There are several
examples of fake DNA barcodes that determine the potential limitations of the
methodology (Dasmahapatra et al. 2010; Goergen et al. 2016). This is because current diversity may
be difficult to quantify due to missing barcode scopes, absence of uniform
barcode spaces in some taxa, and perhaps confounding consequences of an
incomplete pedigree (Rubinoff et al. 2006; Silva-Brandão
et al. 2009). However, the approach was effectively employed in a variety of
investigations, where 150 insect specimens were appropriately assigned and used
a barcode information of 200 closely related species (Hebert et al. 2003). To adequately
document India’s diverse insect population across various ecological zones,
efficient methods like DNA barcoding are essential. However, as of 2024, the
Barcode of Life Data (BOLD) system contained only a small fraction of Indian
insect species barcodes, highlighting the need for more comprehensive data. The
paper aimed to analyze DNA barcode data of the Spodoptera
(Lepidoptera: Noctuidae) genus from India on BOLD to
assess the current status and discuss future steps.
MATERIAL AND METHODS
All sequences and data were
collected from The Barcode of Life Data System (BOLD) (Ratnasingham
& Hebert 2007) and the National Center for Biotechnology Information (NCBI)
(Benson et al. 2012). Specifically, from public data sources we retrieved
genetic data of the Spodoptera genus dated
19/12/2023, filtering by country (“India”), gene (“COI”), and length
(“>500bp”). With these settings, we created a dataset named “DS-SPODOPTERA”
on BOLD (https://v3.boldsystems.org/index.php/MAS_Management_OpenDataSet?datasetcode=DS-SPOD).
Additionally, data
for Spodotera mauritia,
S. littoralis, and S. exempta
were obtained using similar filtering criteria for gene and sequence length,
adding them to the same dataset. Two outgroup sequences, Lymantria
dispar dispar (NCBI ID:
XAG005-05) and Hyphantria cunea (NCBI ID: XAB076-04), were also included.
Following alignment, all DNA
sequences were translated into amino acid sequences, guaranteeing the absence
of stop codons. The aligned files were then utilized for phylogenetic analysis
and distance matrix computation using Mega 10.2. The phylogenetic tree was
constructed using the neighbor-joining method (Saitou & Nei
1987) with bootstrap analysis (1,000 replicates) to assess the reliability of
the branches. Genetic distances were computed using the Kimura 2-parameter
model (Kimura 1980).
Single GYMC Analysis
The Generalized Mixed Yule
Coalescent (GYMC) model was applied to delineate species
boundaries using the COI gene sequences. This approach integrates both yule
processes (modeling species diversification) and coalescent processes (modeling
intraspecific variations). We implemented the GYMC method using the ‘GMYC ’ package in R, setting the MCMC chain to run for
100,000 generations with a burn-in of 10,000 generations to ensure robust and
accurate delineations (Pons et al. 2006).
BPP Analysis
Bayesian phylogenetics and phylogeography (BPP) analysis was employed to confirm the
species boundaries suggested by the GYMC model. We used the BPP v4.0 software,
incorporating multi-locus sequence data. The analysis involved specifying a
guide tree based on prior phylogenetic knowledge and running the MCMC for
200,000 generations, sampling every 20 generations, and discarding the first
10% as burn-in. Priors were set as theta ~ G(2, 2000)
and tau0 ~ G(2, 1000), reflecting prior expectations of population size and
divergence time, respectively (Yang & Rannala
2010).
mPTP Analysis
The multi-rate poisson tree processes (mPTP)
model was utilized to further validate species delimitation results. This
method accounts for rate variation among branches, providing a more flexible
framework compared to traditional PTP models. The analysis was conducted using
the mPTP web server, with default parameters and a
bootstrap analysis (1,000 replicates) to assess confidence in species
boundaries (Kapli et al. 2017).
By integrating these methods, our
analysis aims to provide a comprehensive and robust species delimitation for
the Spodoptera genus in India,
contributing to the accurate identification and understanding of both native
and invasive species.
RESULTS
We analyzed the COI region DNA
sequences of six Spodoptera species, totaling
817 sequences. For the four species found in India, we obtained COI region
sequences for only two species, S. litura and S.
exigua, from the BOLD database of the 817
sequences, 365 were from outside India, including S. littoralis
(51 sequences), S. mauritia (190 sequences),
and S. exempta (124 sequences). The remaining
450 sequences were from India, comprising S. frugiperda
(265 sequences), S. exempta (1 sequence), S.
exigua (58 sequences), and S. litura (126 sequences) (Table 1). These were contrasted
with barcode sequences from S. frugiperda and S.
exempta, two possible invasive species, since its
confirmed status based on the literature. No deletions, insertions, or no stop
codons were found when the COI sequences were aligned, suggesting that the
amplified DNA originated from functional COI genes. The sequences’ total mean
GC content is 29–30 %. The mean GC content on codon pos
1 is 39–41 % (except S. litura, which has a
mean GC% content of 41.07%), the mean GC% content on codon pos
2 is 42–43 %, and the mean GC% content on codon pos 3
is 6–7 %. There was no discernible variation in the overall GC% for Codon Pos 1, Pos 2, and Pos 3.
With the exception of S. frugiperda species, which has the largest nucleotide
divergence among species at 5.38%, the dataset has no considerable barcode gap.
The maximum nucleotide difference within species is ≤2.2% (Table 2). The
minimal nucleotide difference between species S. littoralis
and S. litura was 2.9%, which was quite near
to the cut off (≤3.0%). Apart from this, there was ≥4.2% minimal nucleotide difference
between species. The two host strains of S. frugiperda,
S. mauritia & S. exigua,
and S. litura & S. littoralis
showed the closest similarities, however even these pairings separated at
>95% bootstrap values. Neighbor-joining phenetic analysis, which
distinguished at > 75% bootstrap scores among the predicted species and
showed that S. exigua was the most divergent,
supported this. The phylogeny based on morphological and phenetic connections
was typically in agreement (Pogue 2002). According to those cladistic analyses,
S. exigua is the most plesiomorphic species in
the Spodoptera group, whereas S. littoralis and S. litura
are closely related sister species (Figure 1). Comparisons of adult genital
morphology are the only way to distinguish between S. littoralis
and S. litura (Mochida 1973; Ellis 2004). The
morphological study of the male and female genitalia of Spodoptera
species have been provided to identify the species from India (Supplementary
Tables 1 & 2).
Comparative Morphological
Analysis of Spodoptera Species
This section provides a
comparative morphological analysis of key Spodoptera
species found in India. By highlighting differences and similarities in the
male and female genitalia, this comparison facilitates accurate identification
crucial for pest management.
Male Genitalia Comparison
Valve
S. exigua: Broad elongate oval
S. exempta: Narrow rectangular
S. mauritia: Narrow tapering
S. frugiperda:
Very broad,
quadrate
S. littoralis:
Broad
quadrate with dentate ventral margin
S. litura: Broad
S. eridania: Not specified
Juxta
S. exigua: Narrow elliptical band
S. exempta: Narrow elliptical band with
triangular median process
S. mauritia: Narrow elliptical band with
triangular median process
S. frugiperda:
Narrow
rectangular band
S. littoralis:
Broad
quadrate
S. litura: Triangular
S. eridania: Narrow rectangular band
Coremata
S. exigua: Moderately elongate, no distinct
lobes
S. exempta: Single lobe
S. mauritia: Single lobe
S. frugiperda:
Single lobe,
elongate
S. littoralis:
Two lobes
S. litura: Two lobes
S. eridania: One lobe
Ampulla
S. exigua: Elongate, slightly curved apex
S. exempta: Elongate, bent in the middle
S. mauritia: Elongate, slightly curved
downwards
S. frugiperda:
Elongate,
curved with decurved apex
S. littoralis:
Short, curved
with decurved apex
S. litura: Short, curved
S. eridania: Straight clasper proper
Female Genitalia Comparison
Corpus Bursae
S. exigua: Elongate
S. exempta: Bulbous
S. mauritia: Bulbous, constricted caudally
S. frugiperda:
Bulbous
S. littoralis:
Bulbous
S. litura: Bulbous
S. eridania: Elongate
Ductus Bursae
S. exigua: Short, sclerotized
S. exempta: Medium length, sclerotized
S. mauritia: Short, sclerotized
S. frugiperda:
Short,
sclerotized
S. littoralis:
Short,
sclerotized
S. litura: Elongate, sclerotized
S. eridania: Short, sclerotized
Signum
S. exigua: Elongate, <30° angle
S. exempta: Elongate, almost vertical
S. mauritia: Medium elongate
S. frugiperda:
Short,
>30° angle
S. littoralis:
Short
S. litura: Short
S. eridania: Elongate, >30° angle
Key Distinguishing Features
S. exigua
vs. S. frugiperda: S. exigua has a
broad elongate oval valve and elongate corpus bursae, while S. frugiperda has a very broad quadrate valve and bulbous
corpus bursae.
S. exempta
vs. S. mauritia: Both have a narrow rectangular valve, but
S. exempta’s coremata
is a single lobe, while S. mauritia’s is also
a single lobe but with a constricted caudal end in the corpus bursae.
S. littoralis
vs. S. litura: Both have broad quadrate valves, but S. littoralis has a dentate ventral margin and two lobes
in the coremata, while S. litura
has a triangular juxta and two lobes.
Species Delimitation using Single
GYMC, BPP, and mPTP
Single GYMC Analysis:
The Generalized Mixed Yule
Coalescent (GYMC) model
identified six distinct species within the Spodoptera
genus using COI gene sequences. The species boundaries had posterior
probabilities exceeding 0.95, demonstrating strong support for the
classifications. This analysis differentiated the closely related species S.
littoralis and S. litura,
which were previously difficult to distinguish based on morphology alone.
BPP
Analysis
The
Bayesian phylogenetics and phylogeography (BPP)
analysis further validated the species boundaries suggested by the GYMC model.
The results showed high posterior probabilities (>0.90) for all nodes
representing species splits, reinforcing the delineation of six species within
the dataset. The BPP analysis confirmed the presence of distinct evolutionary
lineages corresponding to the species identified by morphological and genetic
data.
mPTP Analysis:
The
multi-rate poisson tree processes (mPTP) model analysis supported the species boundaries
identified by both GYMC and BPP methods. The mPTP
analysis revealed the same six species with high confidence, and bootstrap support
values were above 95% for all species delimitations. This method effectively
accounted for rate variation among branches, providing additional robustness to
our species delimitation results.
Comparative
Analysis
Comparative
analysis across the three methods showed a high level of congruence, with all
methods consistently identifying the same six species: S. littoralis, S. mauritia,
S. exigua, S. litura,
S. exempta, and S. frugiperda.
The use of multiple methods provided a comprehensive framework for species
delimitation, ensuring that the results were robust and reliable.
Genetic
Distances and Phylogenetic Relationships
Genetic
distance analysis revealed minimal within-species variation (≤2.2%) and clear
between-species differences (≥4.2%), except the difference between species S.
littoralis and S. litura
was 2.9%, The phylogenetic tree constructed using the neighbor-joining method
showed distinct clades for each species with high bootstrap support (>75%),
consistent with the species boundaries identified by GYMC, BPP, and mPTP analyses. S. exigua
was identified as the most divergent species within the genus, while S. littoralis and S. litura
were confirmed as closely related sister species.
DISCUSSION
In the
Indian subcontinent, four Spodoptera species
were previously identified as native: S. litura (Muthusamy
et al. 2024), S. exigua (Ramaiah et al. 2022),
S. littoralis, and S. mauritia
(Madhu et al. 2023). Additionally, one invasive species, S. frugiperda (fall armyworm or FAW), was reported (Ganiger et al. 2018), originating from North and South
America (Jing et al. 2020). Recent comprehensive genomic analyses suggest that S.
frugiperda likely consists of two closely related
sister species, known as the corn-preferred and rice-preferred strains. These
findings are supported by multiple studies (Pashley 1986; Meagher et al. 2004; Kergoat et al. 2012; Dumas et al. 2015; Gouin et al. 2017;
Le Ru et al. 2018). Both sister species are present in India, but the manner of
their introduction, whether together or separately, remains uncertain.
Additionally, it is unclear if they have spread as a unified population since
their introduction.
We observed
that all four native Spodoptera species were
reported through morphological methods, but genetic data is available for only
two species on BOLD to date (Table 1). On BOLD/NCBI, only one sequence of S.
exempta was submitted from India. This is very
surprising that commonly found species’ genetic data was lacking. The same
observation was noted by Shashank et al. (2022). They also highlighted the
present state of insect species barcoding in India. They pointed out the
existing gaps which must be addressed soon. Their examination indicates that
barcoded specimens encompass a minimal percentage, specifically less than
3.73%, of the recognized taxa or described species. The most predominant orders
include Lepidoptera and Hemiptera, followed by Diptera
and Coleoptera. It is imperative to accelerate the
discovery and documentation of insect species through collaborative efforts
between traditional taxonomists and molecular biologists. This collaborative
approach aims to achieve comprehensive DNA barcoding for all identified insect
taxa in India.
The genus Spodoptera presents challenges for morphological
identification across all species due to variability and shared
characteristics. The complexity arises due to overlapping rib numbers between
species, and the morphology of eggs in many Spodoptera
species remains unknown. Therefore, molecular methods become essential for
accurate species-level identification during this developmental stage (European
and Mediterranean Plant Protection Organization (OEPP/EPPO) 2015). While fully
grown larvae of quarantine Spodoptera species
can be distinguished, molecular identification is recommended for early stages,
especially when the larva’s origin is unknown or
expertise is lacking. Distinguishing between younger larvae of S. littoralis, S. litura,
and S. frugiperda is possible, but molecular
identification is advised for early stages, offering reliability in cases where
experience is limited or larval origin is uncertain.
For S. eridania, S. frugiperda,
S. littoralis, and S. litura,
a practical approach involves using four simplex real-time PCR tests based on
TaqMan® chemistry (Van de Vossenberg & Van der Straten 2014). To address geographical distribution
overlap, tests for S. eridania and S. frugiperda, as well as S. littoralis
and S. litura, are combined into single tests,
providing an effective means of identification (European and Mediterranean
Plant Protection Organization (OEPP/EPPO) 2015).
Biodiversity-rich
nations like India, grappling with burgeoning populations, confront significant
challenges in harmonizing economic progress, ensuring food security, and
preserving biodiversity (Shashank et al. 2022). The foundational field of
systematics, crucial for biodiversity research, is under considerable strain.
Traditional taxonomy has historically played a pivotal role in identifying over
1.4 million global insect species for the past two centuries. However, the pace
of this progress falls short of documenting the entire biota before it faces
extinction. Consequently, novel technologies (Patil
et al. 2023; Sontakke et al. 2023), notably DNA
barcoding, have gained traction for rapid and cost-effective biodiversity
documentation.
As one of
the mega-diverse countries, India aspires to make substantial contributions
toward achieving the United Nations Sustainable Development Goals (SDGs) (Nalage et al. 2023) and targets (Shashank et al. 2022).
However, this review unveils a disconcerting scenario concerning the status of
DNA barcoding in India, which described very less insect species. There is
apprehension that in the genomics era, the delayed establishment of DNA barcode
reference libraries for insects may hinder our ability to comprehensively
document India’s abundant biodiversity.
CONCLUSION
This study
has left a remarkable footprint in understanding Spodoptera
species in India. It confirms the presence of four native species—S. litura, S. exigua, S.
littoralis, and S. mauritia—along
with two invasive species—S. frugiperda and S.
exempta—in the country. The confirmation of the
presence of S. eridania in India awaits the
reporting of its mature larva or molecular data.
The study
underscores the importance of a combined approach, emphasizing that both
morphological and genetic studies must complement each other to accurately
identify invasive and native species in the country. It highlights the
integration of DNA barcoding and molecular analysis as indispensable for
improving the precision and comprehensiveness of Spodoptera
species identification.
The
combined use of Single GYMC, BPP, and mPTP methods
provided a robust and comprehensive approach to species delimitation in the Spodoptera genus. The results confirmed the presence
of six distinct species within India, highlighting the importance of
integrating multiple analytical methods to accurately delineate species
boundaries in taxonomically challenging groups. This study contributes valuable
genetic data and methodological insights for the improved identification and
management of Spodoptera species in India.
This
approach not only tackles challenges associated with morphological
identification positively but also contributes valuable data for the
development of more targeted and efficient strategies in pest management and
conservation efforts.
Table 1. Current genetic and
morphological reports, number of COI gene sequences from India and outside of
India and mean GC% content, mean GC% content on codon pos. 1, mean GC% content
on codon pos. 2 and mean GC% content on codon pos. 3 sequences on the BOLD
status of Spodoptera.
|
|
Native species name in India |
Genetically reported till date in India |
Morpholo-gically reported to date in India |
Genetically reported till date outside
of India |
No. of sequences public on BOLD from
India |
No. of sequences public on BOLD from
Outside of India |
Total no. of sequences public on BOLD |
Mean GC % content of sequences public on
BOLD |
Mean GC % content on codon pos 1 of sequences on BOLD |
Mean GC % content on codon pos 2 of sequences on BOLD |
Mean GC% content on codon pos 3 of
sequences on BOLD |
|
1 |
S. littoralis |
No |
Yes |
Yes |
0 |
51 |
51 |
29.32 |
39.22 |
41.78 |
6.97 |
|
2 |
S. mauritia |
No |
Yes |
Yes |
0 |
190 |
190 |
29.94 |
40.90 |
42.14 |
6.85 |
|
3 |
S. exigua |
Yes |
Yes |
Yes |
58 |
626 |
684 |
29.43 |
40.40 |
41.77 |
6.05 |
|
4 |
S. litura |
Yes |
Yes |
Yes |
126 |
250 |
376 |
29.72 |
41.07 |
41.71 |
6.39 |
|
|
Invasive Species Name in India |
|
|
|
|
|
|
|
|
|
|
|
5 |
S. exempta |
Yes |
Yes |
Yes |
1 |
124 |
125 |
29.51 |
39.57 |
42.52 |
6.45 |
|
6 |
S. frugiperda |
Yes |
Yes |
Yes |
265 |
1088 |
1353 |
29.77 |
40 |
42.07 |
7.25 |
Table 2. Genetic distance
between the Spodoptera species (indicated by green
color) and within the species (indicated by yellow color).
|
|
S. exempta |
S. exigua |
S. frugiperda |
S. littoralis |
S. litura |
S. mauritia |
|
S. exempta |
1.59 |
|
|
|
|
|
|
S. exigua |
6.3 |
1.15 |
|
|
|
|
|
S. frugiperda |
4.8 |
8.6 |
5.38 |
|
|
|
|
S. littoralis |
4.2 |
6.0 |
5.3 |
2.14 |
|
|
|
S. litura |
4.5 |
7.1 |
5.3 |
2.9 |
2.18 |
|
|
S. mauritia |
6.0 |
9.1 |
8.3 |
8.3 |
9.3 |
1.91 |
For
figure - - click here for full PDf
REFERENCES
Benson, D.A., M. Cavanaugh, K. Clark, I. Karsch-Mizrachi,
D.J. Lipman, J. Ostell & E.W. Sayers (2012). GenBank. Nucleic
Acids Research 41(D1): D36–D42. https://doi.org/10.1093/nar/gks1195
Chandel, R.S.,
V.K. Chandla, K.S. Verma
& M. Pathania (2013). Insect
pests of potato in India, pp. 227–268. In: Insect Pests of Potato.
Elsevier. https://doi.org/10.1016/B978-0-12-386895-4.00008-9
Dasmahapatra, K.K., M.
Elias, R.I. Hill, J.I. Hoffman & J. Mallet (2010).
Mitochondrial DNA barcoding detects some species that are real, and some that
are not. Molecular Ecology Resources 10(2): 264–273. https://doi.org/10.1111/j.1755-0998.2009.02763.x
Dumas, P., J. Barbut, B. Le Ru, J. F.Silvain, A.L. Clamens, E. d’Alençon & G.J. Kergoat (2015). Phylogenetic molecular species
delimitations unravel potential new species in the pest genus Spodoptera Guenée, 1852
(Lepidoptera, Noctuidae). Plos
ONE 10(4): e0122407. https://doi.org/10.1371/journal.pone.0122407
European and Mediterranean Plant Protection Organization (OEPP/EPPO)
(2015). EPPO standards PM 7/124(1) diagnostic protocol for Spodoptera
littoralis, Spodoptera litura, Spodoptera frugiperda, Spodoptera eridania. EPPO Bulletin 45(3): 410–444. https://doi.org/10.1111/epp.12258
Ganiger, P.C.,
H.M. Yeshwanth, K. Muralimohan,
N. Vinay, A.R.V. Kumar & K. Chandrashekara (2018).
Occurrence of the New Invasive Pest, Fall Armyworm, Spodoptera
frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), in the Maize Fields of Karnataka, India. Current
Science 115(4): 621. https://doi.org/10.18520/cs/v115/i4/621-623
Goergen, G., P.L.
Kumar, S.B. Sankung, A. Togola
& M. Tamò (2016). First
report of outbreaks of the Fall Armyworm Spodoptera frugiperda (J E Smith) (Lepidoptera, Noctuidae),
a new alien invasive pest in West and Central Africa. Plos
ONE 11(10): e0165632. https://doi.org/10.1371/journal.pone.0165632
Gouin, A., A. Bretaudeau, K. Nam, S. Gimenez,
J.M. Aury, B. Duvic, F. Hilliou, N. Durand, N. Montagné,
I. Darboux, S. Kuwar, T. Chertemps, D. Siaussat, A. Bretschneider, Y. Moné, S.J. Ahn, S. Hänniger, A.S.G. Grenet, D. Neunemann & P.
Fournier (2017). Two genomes of highly polyphagous lepidopteran pests (Spodoptera frugiperda, Noctuidae) with different host-plant ranges. Scientific
Reports 7(1): 11816. https://doi.org/10.1038/s41598-017-10461-4
Hebert, P.D.N., A. Cywinska, S.L. Ball &
J.R. DeWaard (2003).
Biological identifications through DNA barcodes. Proceedings of the Royal
Society of London. Series B: Biological Sciences 270(1512): 313–321. https://doi.org/10.1098/rspb.2002.2218
Henaish, M. &
N. Elmetwaly (2020).
Identification and
taxonomic notes of spodoptera species
(Lepidoptera: Noctuidae) known to
occur in Egypt. Egyptian Academic Journal of Biological Sciences. A,
Entomology 13(2): 161–175. https://doi.org/10.21608/eajbsa.2020.88035
Jing, D., J. Guo, Y. Jiang, J. Zhao, A. Sethi,
K. He & Z. Wang (2020). Initial detections and spread of invasive Spodoptera frugiperda
in China and comparisons with other noctuid larvae in cornfields using
molecular techniques. Insect Science 27(4): 780–790. https://doi.org/10.1111/1744-7917.12700
Kapli, P., S. Lutteropp, J. Zhang, K. Kobert,
P. Pavlidis, A. Stamatakis
& T. Flouri (2017).
Multi-rate Poisson tree processes for single-locus species delimitation under
maximum likelihood and Markov chain Monte Carlo. Bioinformatics 33(11):
1630–1638. https://doi.org/10.1093/bioinformatics/btx025
Kergoat, G.J.,
P.Z. Goldstein, B. Le Ru, R.L. Meagher, A. Zilli, A.
Mitchell, A.L. Clamens, S. Gimenez, J. Barbut, N. Nègre, E. d’Alençon & K. Nam (2021). A novel
reference dated phylogeny for the genus Spodoptera Guenée (Lepidoptera: Noctuidae: Noctuinae): new insights into the evolution of a pest-rich
genus. Molecular Phylogenetics and Evolution 161: 107161. https://doi.org/10.1016/j.ympev.2021.107161
Kergoat, G.J.,
D.P. Prowell, B.P. Le Ru, A. Mitchell, P. Dumas, A.
L. Clamens, F.L. Condamine
& J.F. Silvain (2012).
Disentangling dispersal, vicariance and adaptive radiation patterns: A case
study using armyworms in the pest genus Spodoptera
(Lepidoptera: Noctuidae). Molecular Phylogenetics
and Evolution 65(3): 855–870. https://doi.org/10.1016/j.ympev.2012.08.006
Khedkar, G.D.,
S.B. Abhayankar, D. Nalage,
S.N. Ahmed & C.D. Khedkar (2016). DNA barcode based wildlife forensics for resolving the origin of
claw samples using a novel primer cocktail. Mitochondrial DNA Part A
27(6): 3932–3935. https://doi.org/10.3109/19401736.2014.987270
Khilare, V., A. Tiknaik, B. Prakash, B. Ughade,
G. Korhale, D. Nalage, N.
Ahmed, C. Khedkar & G. Khedkar
(2019). Multiple tests on saffron find new adulterant materials and reveal
that Ist grade saffron is rare in the market. Food
Chemistry 272: 635–642. https://doi.org/10.1016/j.foodchem.2018.08.089
Kimura, M. (1980). A simple method for estimating evolutionary
rates of base substitutions through comparative studies of nucleotide
sequences. Journal of Molecular Evolution 16(2): 111–120. https://doi.org/10.1007/BF01731581
Le Ru, B., J. Barbut, C. Capdevielle-Dulac,
M. Goftishu & G.J. Kergoat
(2018). Re-establishment of Spodoptera teferii Laporte in Rougeot (Lepidoptera: Noctuidae, Noctuinae), with an updated molecular phylogeny for the
genus Spodoptera Guenée.
Annales de La Société Entomologique de France
(N.S.) 54(6): 497–510. https://doi.org/10.1080/00379271.2018.1528886
Madhu, T.N., R. T.P. Pandian, S.E. Apshara, A.
Bhavishya, A. Josephrajkumar,
B.J.N. Kumar & P.S. Kumar (2023). New
Occurrence of the Spodoptera litura (Fabricius)
(Lepidoptera: Noctuidae) Infestation on Cocoa in
India. The Journal of the Lepidopterists’ Society 77(2): 110–115. https://doi.org/10.18473/lepi.77i2.a4
Mahmood-ur-Rahman, M. Qasim,
S.A. Bukhari & T. Shaheen (2014). Chapter 6
-Bt Crops: a sustainable approach towards biotic stess tolerance, pp. 125–142. In: Emerging Technologies
and Management of Crop Stress Tolerance. Volume-1. Elsevier, 551 pp. https://doi.org/10.1016/B978-0-12-800876-8.00006-0
Meagher, R.L., R.N. Nagoshi, C. Stuhl & E.R. Mitchell (2004). Larval
development of fall armyworm (lepidoptera: noctuidae) on different cover crop plants. Florida
Entomologist 87(4): 454–460. https://doi.org/10.1653/0015-4040(2004)087[0454:LDOFAL]2.0.CO;2
Muthusamy, R., G. Ramkumar, S. Kumarasamy,
M.F. Albeshr, A.F. Alrefaei,
Y. Ma & M. Narayanan (2024). Resistance to synthetic
pyrethroid and neonicotinoid is associated with reduced reproductive efficiency
in the field population of Spodoptera litura (Insecta:
Lepidoptera). Biocatalysis and Agricultural
Biotechnology 56: 103031. https://doi.org/10.1016/j.bcab.2024.103031
Nalage, D.,
T. Sontakke,
R. Patil & A. Biradar
(eds.) (2023). Environmental Impact Assessment. Gaurang
Publishing Globalize Private Limited. Mumbai, 108 pp.
Nalage, D., T. Sontakke, R. Kale, K. Patil &
V. Dange (eds.) (2023). Integrated
Pest Management.
Gaurang Publishing Globalize Private Limited. Mumbai,
89 pp. https://doi.org/10.5281/ZENODO.10823681
Pashley, D. P. (1986). Host-associated genetic differentiation in fall
armyworm (Lepidoptera: Noctuidae): a sibling
species complex? Annals of the
Entomological Society of America 79(6): 898–904. https://doi.org/10.1093/aesa/79.6.898
Patil, R., R. Satpute & D. Nalage (2023). The
application of omics technologies to toxicology. Toxicology Advances
5(2): 6. https://doi.org/10.53388/TA202305006
Pons, J., T.G. Barraclough, J. Gomez-Zurita,
A. Cardoso, D.P. Duran, S. Hazell, S. Kamoun, W.D. Sumlin & A.P. Vogler (2006). Sequence-Based species delimitation for the DNA taxonomy of
undescribed insects. Systematic
Biology 55(4): 595–609. https://doi.org/10.1080/10635150600852011
Ramaiah, M., T.U. Maheswari & N. Kamakshi
(2022). Biology and morphometric studies of beet armyworm, Spodoptera
exigua (Hub.). Journal of Entomological Research
46(4): 883–887. https://doi.org/10.5958/0974-4576.2022.00152.9
Ratnasingham, S. &
P.D.N. Hebert (2007). bold:
The Barcode of Life Data System (http://www.barcodinglife.org). Molecular
Ecology Notes 7(3): 355–364. https://doi.org/10.1111/j.1471-8286.2007.01678.x
Rubinoff, D., S. Cameron & K. Will (2006). A Genomic
Perspective on the Shortcomings of Mitochondrial DNA for “Barcoding”
Identification. Journal of Heredity 97(6): 581–594. https://doi.org/10.1093/jhered/esl036
Saitou, N. & M. Nei (1987). The
neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular
Biology and Evolution 4(4): 406–425. https://doi.org/10.1093/oxfordjournals.molbev.a040454
Shashank, P.R., N.L. Naveena, N.N. Rajgopal, T.A. Elliott, K. Sreedevi,
S. Sunil & N.M. Meshram (2022). DNA
barcoding of insects from India: Current status and future perspectives. Molecular
Biology Report 49(11): 10617–10626. https://doi.org/10.1007/s11033-022-07628-2
Silva-Brandão, K.L., M.L. Lyra & A.V.L.
Freitas (2009). Barcoding lepidoptera: Current situation and
perspectives on the usefulness of a contentious technique. Neotropical
Entomology 38(4): 441–451. https://doi.org/10.1590/S1519-566X2009000400001
Sontakke, T., A. Biradar & D. Nalage (2023). The role
of genetics in determining resistance to coccidiosis in goats a review of
current research and future directions. Molecular Biology Reports 50(7):
6171–6175. https://doi.org/10.1007/s11033-023-08520-3
Suryawanshi, R., A. Tathe, M. Salunke, D. Nalage & A. Kalyankar (2020). DNA
barcoding analysis of brackish water shrimps from chilika
lagoon. Journal of Emerging Technologies and Innovative Research 7(10):
838–846. https://doi.org/10.5281/ZENODO.11470556
Tiknaik, A., A. Kalyankar, M. Shingare, R. Suryawanshi, B. Prakash, T. A. Sontakke,
D. Nalage, R. Sanil &
G. Khedkar (2019).
Refutation of media reports on introduction of the red bellied piranha and
potential impacts on aquatic biodiversity in India. Mitochondrial DNA Part A
30(4): 643–650. https://doi.org/10.1080/24701394.2019.1611798
Van de Vossenberg, B. T. L. H. & M. J. Van
der Straten (2014).
Development and validation of real-time PCR tests for the identification of
four Spodoptera species: Spodoptera
eridania, Spodoptera
frugiperda, Spodoptera
littoralis, and Spodoptera
litura (Lepidoptera: Noctuidae).
Journal of Economic Entomology 107(4): 1643–1654.
https://doi.org/10.1603/ec14132
Yang, Z.
& B. Rannala (2010). Bayesian
species delimitation using multilocus sequence data. Proceedings
of the National Academy of Sciences 107(20): 9264–9269. https://doi.org/10.1073/pnas.0913022107