Results 1 to 10 of about 372,426 (253)

Improving detection probabilities for pests in stored grain [PDF]

Pest Management Science, 2010
BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their ...
Andreas Kiermeier, Grant Hamilton
exaly   +7 more sources

Competition among species of stored-product psocids (Psocoptera) in stored grain. [PDF]

PLoS ONE, 2014
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, Nickolas G Kavallieratos, Nickolas G Kavallieratos, James E Throne, Christos T Nakas   +4 more
doaj   +5 more sources

A YOLO-Based Model for Detecting Stored-Grain Insects on Surface of Grain Bulks [PDF]

Insects
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, Dandan Li, Yancheng Zheng, Yiming Ma, Xiaoping Yan, Qing Zhou, Qin Wang, Yili Zheng   +7 more
doaj   +2 more sources

Controlling insects in stored grain by disturbing the grain

Julius-Kühn-Archiv, 2018
Insects can cause damage to stored grain, especially on smallholder farms in the tropics. Sitophilus zeamais (maize weevil, MW) and Rhyzopertha dominica (lesser grain borer, LGB) are often involved. Our objective was to determine, by four experiments, if
Bern, Carl, Bbosa, Denis, Brumm, Thomas, Suleiman, Rashid, Rosentrater, Kurt, Rau, Tyler, Maier, Dirk, Barnes, Rachael, Friedmann, Michelle   +8 more
doaj   +2 more sources

Detection and Identification of Stored-Grain Insects Using Deep Learning: A More Effective Neural Network

IEEE Access, 2020
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, Hao Dang, Zhicai Liu, Xiaoguang Zhou   +3 more
doaj   +3 more sources

Method for pests detecting in stored grain based on spectral residual saliency edge detection

Grain & Oil Science and Technology, 2019
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
doaj   +3 more sources

Effects of Microwave on Mortality and Detection Efficiency of Three Stored Grain Insect Adults in Stored Paddy, and on Grain Quality [PDF]

Insects
Microwave heating has been widely used for disinfestation in the food industry due to its selective heating. However, research on the effects of microwave heating on stored product insects is still relatively limited, which has restricted its broader ...
Shiyuan Miao, Yiting Zhou, Suisui Wang, Zhipeng Yang, Adrien Guverinoma, Yaru Zhao, Yujie Lu   +6 more
doaj   +2 more sources

Localized corrosion of friction stir welded Al–Cu–Li alloy: The influence of grain-stored energy on grain boundary micro-chemistry

Journal of Materials Research and Technology
In the present study, friction stir welding (FSW) was conducted on an Al–Cu–Li alloy, resulting in significant variations of precipitation and grain-stored energy across the weldment, with the highest corrosion susceptibility showing in the ...
Yuheng Li, Yuchen Wang, You Lv, Yanyan Li, Bing Liu, Zehua Dong, Xinxin Zhang   +6 more
doaj   +3 more sources

Application of Machine Learning for Insect Monitoring in Grain Facilities

AI, 2023
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, Lester Pordesimo, Mitchell Neilsen, Paul Armstrong, James Campbell, Princess Tiffany Mendoza   +5 more
doaj   +1 more source

Compositional analysis in sorghum (Sorghum bicolor) NIR spectral techniques based on mean spectra from single seeds

Frontiers in Plant Science, 2022
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, Paul R. Armstrong, Princess Tiffany D. Mendoza, Bradford W. Seabourn   +3 more
doaj   +1 more source