Evidence map›Paper›PMID 39435502›Full record

ArticlePest management science2026

RETRACTED: Revealing pest patterns: A comparative spatial distribution analysis of insect threats in Kharif rice across the key agricultural regions in the Eastern India.

Koushik Garai

RetractedAbstract readRetracted Publication
In one paragraph

Article in Pest management science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Koushik GaraiDepartment of Agricultural Entomology, Palli Siksha Bhavana (Institute of Agriculture), Visva Bharati, Sriniketan, India.ORCID https://orcid.org/0009-0002-1003-8566

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study investigates the spatial distribution and aggregation patterns of major insect pests in Kharif rice fields during the 2023 growing season in Eastern India. The analysis focuses on key pests such as yellow stem borer (YSB), gall midge, green leaf hopper (GLH), and brown planthopper (BPH), as well as rice thrips, caseworm, whorl maggot, Gundhi bug, grasshopper, and leaf folder. Using statistical indices, this study aims to understand pest behavior across Standard Meteorological Weeks (SMWs) to better inform pest control strategies.

resultsThe study reveals significant clustering and aggregation patterns among the pests. YSB exhibited variance-mean ratio (VMR) values between 1.14 (40th SMW) and 1.96 (31st SMW), with dispersion parameter (K) values ranging from 0.57 to 21.65, and a peak index of dispersion of 132.66 (43rd SMW). Similarly, gall midge showed VMR values from 6.19 to 10.48, whereas GLH and BPH recorded VMR ranges of 1.19 to 132.10 and 1.01 to 1.50, respectively. These spatial distribution trends were confirmed through values for Iwao's patchiness index and Taylor's power law, indicating strong pest aggregation in specific areas.

conclusionThe results underscore the need for region-specific integrated pest management strategies that take into account pest clustering and environmental factors influencing pest distribution. Although an S-curve pattern of infestation-showing gradual population increases, rapid peaks, and eventual decline-was observed, the primary focus remains spatial patterns, which are critical for optimizing pest management and improving rice crop sustainability in the region. © 2024 Society of Chemical Industry.

Indexed as

Dispersion parameter (K)Integrated pest management (IPM)Iwao's patchiness indexTaylor's power lawVariance–mean ratio (VMR)

Identifiers

PMID39435502
PMCPMC13352303

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.