Results 11 to 20 of about 68,090 (215)
A YOLO-Based Model for Detecting Stored-Grain Insects on Surface of Grain Bulks [PDF]
Accurate, rapid, and intelligent stored-grain insect detection and counting are important for integrated pest management (IPM). Existing stored-grain insect pest detection models are often not suitable for detecting tiny insects on the surface of grain ...
Xueyan Zhu +7 more
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Competition among species of stored-product psocids (Psocoptera) in stored grain. [PDF]
We evaluated the competition among stored-product psocid species by conducting two series of laboratory experiments. In the first series, three species of Liposcelididae were used: Liposcelis bostrychophila, Liposcelis decolor, and Liposcelis paeta. Five
Christos G Athanassiou +4 more
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The detection and identification of stored grain insects is important to ensure the safety of grain during grain storage. At present, insect identification methods primarily rely on manual classification; therefore, the automatic, rapid and accurate ...
Zhichao Shi +3 more
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Method for pests detecting in stored grain based on spectral residual saliency edge detection
Pests detecting is an important research subject in grain storage field. In the past decades, many edge detection methods have been applied to the edge detection of stored grain pests.
Yao Qin, Yanli Wu, Qifu Wang, Suping Yu
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Comparative Efficiency of Selected Chemical and Bio Pesticides against some Stored Grain Insects [PDF]
Stored grain insect pests cause a high risk to the grains and seeds in storage such as weight loss, less germination, and reduced nutrition values of grains.
G. Nasr +3 more
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Biological Activity of Some Local Plant Powders against the Saw- Toothed Grain Beetle, Oryzaephilus surinamensis (L.) [PDF]
The present study aimed to investigate the bio-efficiency of five plant powders (clove, black pepper, cinnamon, thyme and capsicum) against the adult stage of the saw-toothed grain beetle, Oryzaephilus surinamensis (L.) under open laboratory conditions ...
Esraa Eldeghidy +3 more
doaj +1 more source
Application of Machine Learning for Insect Monitoring in Grain Facilities
In this study, a basic insect detection system consisting of a manual-focus camera, a Jetson Nano—a low-cost, low-power single-board computer, and a trained deep learning model was developed. The model was validated through a live visual feed. Detecting,
Querriel Arvy Mendoza +5 more
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Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy.
Gokhan Hacisalihoglu +3 more
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At any point along the post-harvest supply chain, commodities are vulnerable to insect infestation. This is due to a variety of factors, but includes landscape-scale movement of stored product insects to and from food facilities and natural refugia. Long-
Rachel V. Wilkins +5 more
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Survey on Mites Associated with Major Insect Pests Infesting Stored Grains in Middle Delta [PDF]
The present study was directed towards the habitat of various mite species as predators, fungivores or as parasitesassociated with insects inhabiting grains and stored products. Samples were collected monthly from maize, wheat flour,broad bean, wheat and
Ferial El-Sayed, Mona Ghallab
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