Persistence and insecticidal evaluation of Inert-PMS formulation on wheat stored grains against Rhyzopertha dominica, Tribolium castaneum, Cryptolestes ferrugineus and Liposcelis paeta

Hafeez, Faisal; Ashraf, Misbah; Wakil, Waqas; Farooq, Muhammad

doi:10.16970/ted.72128

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…(Linnaeus, 1758) (Coleoptera: Silvanidae) (Ziaee et al, 2016), Tribolium castaneum (Herbst, 1797) (Coleoptera: Tenebrionidae) (Frederick and Subramanyam, 2016), Tribolium confusum (Jacquelin Du Val, 1863) (Coleoptera: Tenebrionidae) (Delgarm et al, 2019), Prostephanus truncatus (Horn, 1878) (Coleoptera: Bostrichidae) (Kavallieratos et al, 2018), Liposcelis paeta (Pearman, 1942) (Psocoptera: Liposcelididae) (Saeed et al, 2018), and Cryptolestes ferrugineus (Stephens, 1831) (Coleoptera: Laemophloeidae) (Ashraf et al, 2016). DE consists of naturally occurring fossilized remains of diatoms, with particle sizes ranging from 10 to 200 μm.…”

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confidence: 99%

Insecticidal effect of diatomaceous earth and dolomite powder against Corn weevil Sitophiluszeamais Motschulsky, 1855 (Coleoptera: Curculionidae)

Freitas¹,

Gigliolli²,

Caleffe³

et al. 2020

Turk J Zool

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Sitophilus zeamais Motschulsky, 1855 (Coleoptera: Curculionidae) which develops inside the grain, is an aggressive pest of stored grains. Here, we evaluated the efficiency of diatomaceous earth (DE), Diatomita CI/325 CX, and dolomite (DOL), Dolomita Dr. Kanyo, against S. zeamais reared on corn under laboratory conditions and observed external alterations on treated insects using scanning electron microscopy (SEM). Insects treated with both DE and DOL were impregnated with particles on the body surface, and they showed 100% mortality after 10 days of exposure. Damages caused by inert dusts may have contributed to dehydration and desiccation, consequently, leading insects to death. Thus, diatomaceous and dolomite were effective against S. zeamais under laboratory conditions.

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confidence: 99%

Insecticidal effect of diatomaceous earth and dolomite powder against Corn weevil Sitophiluszeamais Motschulsky, 1855 (Coleoptera: Curculionidae)

Freitas¹,

Gigliolli²,

Caleffe³

et al. 2020

Turk J Zool

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“…Efficiently using agricultural resources and minimizing postharvest losses-which represent 20% to 40% of total losses, with 55% happening during storage [3]-becomes crucial. Insects contribute significantly to these grain losses, accounting for approximately 10-40% globally [4]. In Asia, around 6% of post-harvest losses stem from inadequate storage, with insects and fungi causing about half of these [5].…”

Section: Introductionmentioning

confidence: 99%

MCSNet+: Enhanced Convolutional Neural Network for Detection and Classification of Tribolium and Sitophilus Sibling Species in Actual Wheat Storage Environments

Yang,

Li,

Xin

et al. 2023

Foods

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Insect pests like Tribolium and Sitophilus siblings are major threats to grain storage and processing, causing quality and quantity losses that endanger food security. These closely related species, having very similar morphological and biological characteristics, often exhibit variations in biology and pesticide resistance, complicating control efforts. Accurate pest species identification is essential for effective control, but workplace safety in the grain bin associated with grain deterioration, clumping, fumigator hazards, and air quality create challenges. Therefore, there is a pressing need for an online automated detection system. In this work, we enriched the stored-grain pest sibling image dataset, which includes 25,032 annotated Tribolium samples of two species and five geographical strains from real warehouse and another 1774 from the lab. As previously demonstrated on the Sitophilus family, Convolutional Neural Networks demonstrate distinct advantages over other model architectures in detecting Tribolium. Our CNN model, MCSNet+, integrates Soft-NMS for better recall in dense object detection, a Position-Sensitive Prediction Model to handle translation issues, and anchor parameter fine-tuning for improved matching and speed. This approach significantly enhances mean Average Precision (mAP) for Sitophilus and Tribolium, reaching a minimum of 92.67 ± 1.74% and 94.27 ± 1.02%, respectively. Moreover, MCSNet+ exhibits significant improvements in prediction speed, advancing from 0.055 s/img to 0.133 s/img, and elevates the recognition rates of moving insect sibling species in real wheat storage and visible light, rising from 2.32% to 2.53%. The detection performance of the model on laboratory-captured images surpasses that of real storage facilities, with better results for Tribolium compared to Sitophilus. Although inter-strain variances are less pronounced, the model achieves acceptable detection results across different Tribolium geographical strains, with a minimum recognition rate of 82.64 ± 1.27%. In real-time monitoring videos of grain storage facilities with wheat backgrounds, the enhanced deep learning model based on Convolutional Neural Networks successfully detects and identifies closely related stored-grain pest images. This achievement provides a viable solution for establishing an online pest management system in real storage facilities.

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Persistence of diatomaceous earth, SilicoSec® against three stored grain beetles

Mortazavi

Toprak

Emekçi

et al. 2020

Journal of Stored Products Research

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Persistence and insecticidal evaluation of Inert-PMS formulation on wheat stored grains against Rhyzopertha dominica, Tribolium castaneum, Cryptolestes ferrugineus and Liposcelis paeta

Cited by 4 publications

References 32 publications

Insecticidal effect of diatomaceous earth and dolomite powder against Corn weevil Sitophiluszeamais Motschulsky, 1855 (Coleoptera: Curculionidae)

Insecticidal effect of diatomaceous earth and dolomite powder against Corn weevil Sitophiluszeamais Motschulsky, 1855 (Coleoptera: Curculionidae)

MCSNet+: Enhanced Convolutional Neural Network for Detection and Classification of Tribolium and Sitophilus Sibling Species in Actual Wheat Storage Environments

Persistence of diatomaceous earth, SilicoSec® against three stored grain beetles

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