Metabarcoding advances agricultural invertebrate biomonitoring by enhancing resolution, increasing throughput, and facilitating network inference DOI Open Access
Ben S. J. Hawthorne, Jordan P. Cuff, Larissa Collins

et al.

Published: Dec. 12, 2023

Biomonitoring of agriculturally important insects is increasingly given our need to understand a) the severity impacts by pests and pathogens on crop yield health, b) impact environmental change land management insects, in line with sustainable development global conservation targets. Traditional entomological traps remain an part biomonitoring toolbox, but their processing laborious introduces latency, they are variably accurate. The integration molecular techniques such as DNA metabarcoding into insect has gained increasing attention, advantages doing so, kind data this can generate, how easily effectively analyses be integrated diverse types currently used remains relatively unclear. In review, we examine combining a range conventional sampling advance way that useful researchers practitioners. We highlight some key challenges mitigate them, using examples its different methods from literature (e.g. interception, pitfall, malaise, sticky traps) demonstrate efficacy suitability. Finally, discuss these infer ecological networks, emphasising importance framework for understanding species interactions ecosystem functioning more effective descriptive biomonitoring.

Language: Английский

Current status and topical issues on the use of eDNA-based targeted detection of rare animal species DOI
Sofia Duarte, Luara Aparecida Simões, Filipe O. Costa

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 904, P. 166675 - 166675

Published: Aug. 29, 2023

Language: Английский

Citations

24
Metabarcoding advances agricultural invertebrate biomonitoring by enhancing resolution, increasing throughput and facilitating network inference DOI Creative Commons
Ben S. J. Hawthorne, Jordan P. Cuff, Larissa Collins

et al.

Agricultural and Forest Entomology, Journal Year: 2024, Volume and Issue: unknown

Published: May 8, 2024

Abstract Biomonitoring of agriculturally important insects is increasingly vital given our need to understand: (a) the severity impacts by pests and pathogens on crop yield health (b) impact environmental change land management insects, in line with sustainable development global conservation targets. Traditional entomological traps remain an part biomonitoring toolbox, but sample processing laborious introduces latency, accuracy can be variable. The integration molecular techniques such as DNA metabarcoding into insect has gained increasing attention, advantages doing so, kind data this generate, how easily effectively analyses integrated diverse types currently used remains relatively unclear. In review, we examine combining a range conventional unconventional sampling advance way that useful researchers practitioners. We highlight some key challenges mitigate them, using examples its different methods from literature (e.g., interception, pitfall sticky traps) demonstrate efficacy suitability. discuss infer ecological networks, emphasizing importance framework for understanding species interactions ecosystem functioning more effective descriptive biomonitoring. Finally, future advances are highlighted, alongside recommendations best practice both new experienced invertebrate metabarcoding.

Language: Английский

Citations

6
Development of an on‐site diagnostic LAMP assay for rapid differentiation of the invasive pest Phthorimaea absoluta (Meyrick) using insect tissues DOI

Li‐Feng Yang,

Ya‐Ge Liu,

Yun‐Li Tao

et al.

Pest Management Science, Journal Year: 2024, Volume and Issue: 80(8), P. 4069 - 4073

Published: April 2, 2024

Abstract BACKGROUND The tomato leafminer, Phthorimaea absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a destructive invasive pest that originated in South America and has spread within China since 2017. A rapid method for on‐site identification of P. urgently needed interception this across China. RESULTS We developed loop‐mediated isothermal amplification (LAMP) technique to differentiate from Liriomyza sativae , Chromatomyia horticola operculella using extracted genomic DNA, which was then refined create an LAMP diagnostic can be performed under field conditions without the need laboratory equipment. CONCLUSION In present research, we differentiation other insects with similar morphology or damage characteristics © 2024 Society Chemical Industry.

Language: Английский

Citations

5
Validation of wing geometric morphometrics in Chrysodeixis spp. (Lepidoptera: Noctuidae) to support pest identification in invasive species survey programs DOI Creative Commons

Allan H. Smith-Pardo,

Karina Torres,

Silvana V. Paula‐Moraes

et al.

Frontiers in Insect Science, Journal Year: 2025, Volume and Issue: 5

Published: Jan. 28, 2025

Looper moths of the genus Chrysodeixis (Lepidoptera: Noctuidae: Plusiinae) are important pests many crops and native plants worldwide. chalcites (Esper) is listed as an invasive species for United States with records interception. Native Plusiinae subfamily morphologically similar commonly cross-attracted in survey trapping programs C. , such includens (Walker), a economic pest. The identification relies on male genitalia dissection DNA analysis. These processes time cost-consuming require expertise. In this work, we evaluated use wing geometric morphometrics (GM) tool to overcome challenges associated complex morphologies spp. cleaned wings specimens validated were photographed under digital microscope, seven venation landmarks annotated from images. coordinates analyzed MorphoJ. Our results GM distinguishing . A limited number center was used address trap-collected lepidopteran pests. Future automation novel application identifying can be explored systems IPM surveys

Language: Английский

Citations

0
Development of an array of molecular tools for the identification of khapra beetle (Trogoderma granarium), a destructive beetle of stored food products DOI Creative Commons

Yunke Wu,

Michael J. Domingue,

Alana R. McGraw

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Feb. 27, 2023

Abstract Trogoderma granarium Everts, the khapra beetle, native to Indian subcontinent, is one of world’s most destructive pests stored food products. Early detection this pest facilitates prompt response towards invasion and prevents need for costly eradication efforts. Such requires proper identification T. , which morphologically resembles some more frequently encountered, non-quarantine congeners. All life stages these species are difficult distinguish using morphological characters. Additionally, biosurveillance trapping can result in capture large numbers specimens awaiting identification. To address issues, we aim develop an array molecular tools rapidly accurately identify among non-target species. Our crude, cheap DNA extraction method performed well spp. suitable downstream analyses including sequencing real-time PCR (qPCR). We developed a simple quick assay usingrestriction fragment length polymorphism between closely related, congeneric variabile Ballion inclusum LeConte. Based on newly generated published mitochondrial sequence data, new multiplex TaqMan qPCR with improved efficiency sensitivity over existing assays. These benefit regulatory agencies products industry by providing cost- time-effective solutions enhance from related They be added toolbox. The selection use would depend intended application.

Language: Английский

Citations

10
Bugs and Bytes: Entomological Biomonitoring in the Age of Deep Learning and Beyond DOI
Mukilan Deivarajan Suresh, Tong Xin, Darren M. Evans

et al.

Published: Jan. 3, 2024

Insects play a vital role in ecosystem functioning, but some parts of the world their populations have declined significantly recent decades due to environmental change, agricultural intensification and other anthropogenic drivers. Monitoring insect is crucial for understanding mitigating biodiversity loss, especially agro-ecosystems where focus on pests beneficial insects gaining momentum context sustainable food systems. Biomonitoring has long played an important providing early warnings vectored pathogens assessing agro-ecosystem management. However, identification invertebrates by taxonomists time-consuming fraught with numerous challenges, particularly when it comes real-time monitoring. Recent technological advances both computational image recognition molecular ecology enhanced biomonitoring efficiency accuracy, reducing labour efforts, leading unprecedented volumes data generated. This perspective article examines significance further potential deep learning image-based recognition, aided complementary technologies, advancing entomological biomonitoring. Using sticky traps as example, we discuss each step workflow required create ecological networks using multimodal learning, identify challenges inherent this method survey techniques. In order become mainstream global biomonitoring, access long-term, standardised comprehending dynamics, structure, function, population declines.

Language: Английский

Citations

3
CRISPR‐based diagnostics detects invasive insect pests DOI

P. R. Shashank,

Brandon M. Parker, Santosh R. Rananaware

et al.

Molecular Ecology Resources, Journal Year: 2023, Volume and Issue: 24(1)

Published: Oct. 27, 2023

Abstract Rapid identification of organisms is essential for many biological and medical disciplines, from understanding basic ecosystem processes, disease diagnosis, to the detection invasive pests. CRISPR‐based diagnostics offers a novel rapid alternative other methods can revolutionize our ability detect with high accuracy. Here we describe diagnostic developed universal cytochrome‐oxidase 1 gene (CO1). The CO1 most sequenced among Animalia, therefore approach be adopted nearly any animal. We tested on three difficult‐to‐identify moth species ( Keiferia lycopersicella , Phthorimaea absoluta Scrobipalpa atriplicella ) that are major pests globally. designed an assay combines recombinase polymerase amplification (RPA) CRISPR signal generation. Our has much higher sensitivity than real‐time PCR assays achieved 100% accuracy all species, limit up 120 fM P. 400 two species. does not require sophisticated laboratory, reduces risk cross‐contamination, completed in less h. This work serves as proof concept potential animal monitoring.

Language: Английский

Citations

7
A Droplet Digital PCR (ddPCR) Assay to Detect Phthorimaea absoluta (Lepidoptera: Gelechiidae) in Bulk Trap Samples DOI Creative Commons
Frida A. Zink, Luke R. Tembrock, Alicia E. Timm

et al.

Journal of Economic Entomology, Journal Year: 2022, Volume and Issue: 115(6), P. 2125 - 2129

Published: Oct. 26, 2022

Abstract The moth species Phthorimaea absoluta (Meyrick) (formerly Tuta absoluta) is serious threat to tomato and other Solanaceous crops worldwide invasive throughout Europe, Asia, Africa. While P. has not yet been found in the U.S. recent detections Caribbean have raised concerns that could be introduced mainland North America. To improve detection capacity, a droplet digital PCR (ddPCR) assay was developed employs nondestructive bulk DNA extraction method able detect one sample among 200 nontargets. Such high-throughput sensitive molecular assays are essential preventing introductions through early response. This can also used areas where established monitor outbreaks track migratory patterns.

Language: Английский

Citations

11
Effect of temperature and humidity on insect DNA integrity evaluated by real-time PCR DOI Creative Commons
Elizabeth Fowler, Melissa L. Starkie, Mark J. Blacket

et al.

Journal of Economic Entomology, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 12, 2024

Abstract Insects collected in dry traps can degrade rapidly, especially warm, humid environments where many biodiversity and biosecurity surveillance activities are undertaken. Degradation severely impact diagnostics, as trap catches become difficult to identify species level using morphological characters or, of increasing importance, molecular approaches. This is problematic for exotic tephritid fruit flies, diagnostics heavily reliant on characters. We tested the effects differing temperature humidity conditions mock samples flies a controlled environment compared our results field catches. DNA degradation was quantified real-time PCR assays, including one assay newly developed here. observed correlation between humidity. The greatest occurred under combined high (90% relative humidity) constant (35 °C). Unexpectedly, fluctuating did not have significant DNA. Other factors, such design, time field, rainfall, significantly correlate with quality across tested. When plotted against samples, clustered together, no clear pattern or predictability regarding quantity preserved, indicating other untested environmental variables may be at play. Predictably, increased exposure found detrimental effect all treatments. These findings will improve delivery through implementation shorter clearance timeframes improved designs procedures.

Language: Английский

Citations

1
Bugs and bytes: Entomological biomonitoring through the integration of deep learning and molecular analysis for merged community and network analysis DOI Creative Commons
Mukilan Deivarajan Suresh, Tong Xin, S. M. Cook

et al.

Agricultural and Forest Entomology, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Abstract Insects play a vital role in ecosystem functioning, but some parts of the world, their populations have declined significantly recent decades due to environmental change, agricultural intensification and other anthropogenic drivers. Monitoring insect is crucial for understanding mitigating biodiversity loss, especially agro‐ecosystems where focus on pests beneficial insects gaining momentum context sustainable food systems. Biomonitoring has long played an important providing early warnings vectored pathogens assessing agro‐ecosystem management. However, identification invertebrates by taxonomists time‐consuming fraught with numerous challenges, particularly when it comes real‐time monitoring. Recent technological advances both computational image recognition molecular ecology enhanced biomonitoring efficiency accuracy, reducing labour efforts, leading unprecedented volumes data generated. This perspective article examines significance further potential deep learning image‐based recognition, aided complementary technologies, advancing entomological biomonitoring. Using sticky traps as example, we discuss each step workflow required create ecological networks using multimodal learning, identify challenges inherent this method survey techniques. In order become mainstream global biomonitoring, access long‐term, standardised comprehending dynamics, structure function population declines.

Language: Английский

Citations

1