Ensuring food security: Strategies for insect pest detection in storage - A review

The infestation of stored food grains by insect pests poses an important threat to global food security and economic stability. The loss of stored food grains may be due to insect pest infestation, microbial spoilage, or inadequate storage conditions. Among these losses, insect pest infestations cause major losses in stored food commodities. Therefore, early detection of storage pests is highly important to farmers and warehouse managers/owners. Conventional detection methods such as visual/manual inspection, grain probes and insect traps, pheromones, visual lures, and Berlese funnel methods are time-consuming and destructive methods. As conventional detection requires repeated sampling and monitoring, the insect pests can be detected only after the adult emergence. At present, non-destructive methods, viz., improved and advanced techniques such as hidden infestation detectors, NIR, X-ray imaging, uric acid analysis, microwave resonators, conductive roller mills, ELISA, acoustic detection, environmental sensing, electronic-nose methods, thermal imaging, solid-phase microextraction (SPME), and machine vision are explored for their potential in enhancing the efficiency and scalability of detection systems. The advantages and limitations of each method are critically assessed, considering factors such as accuracy, cost-effectiveness, and applicability in storage environments. The present review explores various improved and advanced detection techniques employed in the monitoring of insect pests in stored food commodities.

Authors

Publication Details

Journal
International Food Research Journal
Published
2025-04-01
DOI
https://doi.org/10.47836/ifrj.32.2.05
Citations
2
Primary Topic
Food Waste Reduction and Sustainability
Type
article
Field-Weighted Citation Impact
2.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ensuring food security: Strategies for insect pest detection in storage - A review

G. Preetha, V. R. Saminathan, B. Keerthana, T. Eevera et al.
2 citations
International Food Research Journal
Food Waste Reduction and Sustainability
2.32
article

Ensuring food security: Strategies for insect pest detection in storage - A review

G. Preetha, V. R. Saminathan, B. Keerthana, T. Eevera, M Ashok, D.B. Ramesh, K. Logeswaran
article en
2 citations

Abstract

The infestation of stored food grains by insect pests poses an important threat to global food security and economic stability. The loss of stored food grains may be due to insect pest infestation, microbial spoilage, or inadequate storage conditions. Among these losses, insect pest infestations cause major losses in stored food commodities. Therefore, early detection of storage pests is highly important to farmers and warehouse managers/owners. Conventional detection methods such as visual/manual inspection, grain probes and insect traps, pheromones, visual lures, and Berlese funnel methods are time-consuming and destructive methods. As conventional detection requires repeated sampling and monitoring, the insect pests can be detected only after the adult emergence. At present, non-destructive methods, viz., improved and advanced techniques such as hidden infestation detectors, NIR, X-ray imaging, uric acid analysis, microwave resonators, conductive roller mills, ELISA, acoustic detection, environmental sensing, electronic-nose methods, thermal imaging, solid-phase microextraction (SPME), and machine vision are explored for their potential in enhancing the efficiency and scalability of detection systems. The advantages and limitations of each method are critically assessed, considering factors such as accuracy, cost-effectiveness, and applicability in storage environments. The present review explores various improved and advanced detection techniques employed in the monitoring of insect pests in stored food commodities.

International Food Research JournalVol. 32(2)
Openalex Percentile: Top 11%
Food Waste Reduction and Sustainability
2.32
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.