In-Field Detection of Plant Pathogens Using Three-Dimensional-Printed Microneedles and a Portable Platform

Plant diseases threaten global food security, necessitating efficient, field-deployable diagnostics. Traditional approaches, including morphological assessments and conventional sampling methods such as swabs or multistep DNA extraction, are often unreliable in the early stages of infection when visible symptoms are absent and subsurface pathogens remain inaccessible, underscoring the need for molecular tools. Here, we present a microneedle (MN)-based diagnostic platform integrated with loop-mediated isothermal amplification (LAMP) and lateral flow assay (LFA), supported by a custom-built portable heater (LAMPbox). The MNs enable the direct extraction of plant fluids and associated pathogens, offering a rapid, simple, and efficient sampling approach. In this study, two MN types were evaluated: poly(vinyl alcohol) (PVA) and stereolithography-printed MNs fabricated from a plant-derived resin. The 3D-printed MNs exhibited superior mechanical robustness, with a displacement ratio of only 3.3% compared to 24.5% for PVA MNs, and provided an ∼12% higher DNA yield than conventional swab-based methods. Integrated with the LAMPbox, this platform enabled reliable detection of <i>Puccinia triticina</i> with clear differentiation between healthy and infected leaves. This work establishes 3D-printed MNs as mechanically robust and effective tools for pathogen sampling while demonstrating the feasibility of a low-cost, portable, and sustainable system for early plant disease diagnosis.

Authors

Institutions

Publication Details

Journal
ACS Sensors
Published
2025-11-27
DOI
https://doi.org/10.1021/acssensors.5c02361
Citations
2
Primary Topic
Advancements in Transdermal Drug Delivery
Type
article
Field-Weighted Citation Impact
1.58
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In-Field Detection of Plant Pathogens Using Three-Dimensional-Printed Microneedles and a Portable Platform

Nedim Hacıosmanoğlu, Emre Ece, Metin Burak Tatlıses, İsmail Eş et al.
2 citations
ACS Sensors
Advancements in Transdermal Drug Delivery
1.58
article

In-Field Detection of Plant Pathogens Using Three-Dimensional-Printed Microneedles and a Portable Platform

Nedim Hacıosmanoğlu, Emre Ece, Metin Burak Tatlıses, İsmail Eş, Semra Hasançebi, Murat Alp Güngen, Fatih İnci
article en
2 citations

Abstract

Plant diseases threaten global food security, necessitating efficient, field-deployable diagnostics. Traditional approaches, including morphological assessments and conventional sampling methods such as swabs or multistep DNA extraction, are often unreliable in the early stages of infection when visible symptoms are absent and subsurface pathogens remain inaccessible, underscoring the need for molecular tools. Here, we present a microneedle (MN)-based diagnostic platform integrated with loop-mediated isothermal amplification (LAMP) and lateral flow assay (LFA), supported by a custom-built portable heater (LAMPbox). The MNs enable the direct extraction of plant fluids and associated pathogens, offering a rapid, simple, and efficient sampling approach. In this study, two MN types were evaluated: poly(vinyl alcohol) (PVA) and stereolithography-printed MNs fabricated from a plant-derived resin. The 3D-printed MNs exhibited superior mechanical robustness, with a displacement ratio of only 3.3% compared to 24.5% for PVA MNs, and provided an ∼12% higher DNA yield than conventional swab-based methods. Integrated with the LAMPbox, this platform enabled reliable detection of <i>Puccinia triticina</i> with clear differentiation between healthy and infected leaves. This work establishes 3D-printed MNs as mechanically robust and effective tools for pathogen sampling while demonstrating the feasibility of a low-cost, portable, and sustainable system for early plant disease diagnosis.

ACS SensorsVol. 10(12)
Trakya University (TR), Bilkent University (TR), National Nanotechnology Research Center
Openalex Percentile: Top 14%
Advancements in Transdermal Drug Delivery
1.58
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.