Deep learning-based rice pest detection research. [PDF]
PLoS OneWith the increasing pressure on global food security, the effective detection and management of rice pests have become crucial. Traditional pest detection methods are not only time-consuming and labor-intensive but also often fail to achieve real-time ...
Xiong P, Zhang C, He L, Zhan X, Han Y.
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Migration dynamics of an important rice pest: The brown planthopper (Nilaparvata lugens) across Asia-Insights from population genomics. [PDF]
Evol Appl, 2020 Brown planthoppers (Nilaparvata lugens) are the most serious insect pests of rice, one of the world’s most important staple crops. They reproduce year-round in the tropical parts of their distribution, but cannot overwinter in the temperate areas where ...
Hereward JP +5 more
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Recent advances in molecular biology research of a rice pest, the brown planthopper
Journal of Integrative Agriculture, 2019 The brown planthopper, Nilaparvata lugens Stål, has become a major threat in tropical Asian and China since the rice green revolution of the 1960s. Currently, insecticide application remains the primary choice for controlling this rice insect pest, but ...
Yan-yuan BAO, Chuan-xi ZHANG
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Landscape structure influences natural pest suppression in a rice agroecosystem
Scientific Reports, 2023 Agricultural landscapes are constantly changing as farmers adopt new production practices and respond to changing environmental conditions. Some of these changes alter landscape structure with impacts on natural pest control, pesticide use, and ...
M. P. Ali +5 more
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Agronomy, 2023 The System of Rice Intensification (SRI) developed in Madagascar has spread to many parts of the world, including India. This study assessing insect pest prevalence on rice grown with SRI vs.
Santosha Rathod
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FasterPest: A Multi-Task Classification Model for Rice Pest Recognition
IEEE AccessIn the field of precision agriculture and plant protection, this paper proposes a multi-task classification model named FasterPest to improve the accuracy of rice pest identification.
Xiaoyun Zhan +5 more
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MAVM-UNet: multiscale aggregated vision MambaU-Net for field rice pest detection [PDF]
Frontiers in Plant SciencePests in rice fields not only affect the yield and quality of rice but also cause serious ecological and environmental problems due to the heavy reliance on pesticides.
Congqi Zhang, Ting Zhang, Guanyu Shang
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Research on Insect Pest Identification in Rice Canopy Based on GA-Mask R-CNN
Agronomy, 2023 Aiming at difficult image acquisition and low recognition accuracy of two rice canopy pests, rice stem borer and rice leaf roller, we constructed a GA-Mask R-CNN (Generative Adversarial Based Mask Region Convolutional Neural Network) intelligent ...
Sitao Liu +7 more
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An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection
IEEE AccessAccurate pest identification is crucial for ensuring both high quality and high yield in rice production. This paper proposes RicePest-YOLO, a practical and generalizable model designed for agricultural pest detection, based on structural optimization ...
Guisuo Liu +4 more
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Characterization and comparative analysis of microRNAs in the rice pest Sogatella furcifera. [PDF]
PLoS One, 2018 MicroRNAs (miRNAs) are a class of endogenous regulatory RNA molecules 21-24 nucleotides in length that act as functional regulators of post-transcriptional repression of messenger RNA.
Chang ZX, Akinyemi IA, Guo DY, Wu Q.
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