Results 51 to 60 of about 1,038,852 (333)
ENDOPHYTIC TESTING OF Serratia marcescens strain NPKC3_2_21 AGAINST INPARA 3 RICE VARIETY
Pest management is a crucial concern, especially when dealing with insect pests that can cause extensive damage to agricultural crops and the economy.
Gunawan Sutio +3 more
doaj +1 more source
The efficient identification of rice pests and diseases is crucial for preventing crop damage. To address the limitations of traditional manual detection methods and machine learning-based approaches, a new rice pest and disease recognition model based ...
Liangquan Jia +6 more
doaj +1 more source
This study presents a comprehensive solution for precise and timely pest monitoring in field environments through the development of an advanced rice pest detection system based on the YOLO-RMD model. Addressing critical challenges in real-time detection
Jiangdong Yin +9 more
semanticscholar +1 more source
Deep-Learning-Based Rice Disease and Insect Pest Detection on a Mobile Phone
The realization that mobile phones can detect rice diseases and insect pests not only solves the problems of low efficiency and poor accuracy from manually detection and reporting, but it also helps farmers detect and control them in the field in a ...
Jizhong Deng +8 more
semanticscholar +1 more source
Rice is one of serealea comodity that susceptible with pest storage. One of the pest that often attack the rice in storage is Sitophilus oryzae L. The alternative for control S. oryzae L. as fumigant which enviromentally sound is Gliricidia sepium Jacq.
Rusli Rustam +2 more
doaj +1 more source
This review highlights recent advancements in stabilizing single metal atoms on graphitic carbon nitride emphasizing innovative synthesis strategies and emerging applications in electrocatalysis, photocatalysis and organic transformations, along with key challenges and future perspective. Abstract Emerging as a new frontier in catalysis science, single‐
Wenyao Zhang +6 more
wiley +1 more source
A Lightweight Rice Pest Detection Algorithm Using Improved Attention Mechanism and YOLOv8
Intelligent pest detection algorithms are capable of effectively detecting and recognizing agricultural pests, providing important recommendations for field pest control.
Jianjun Yin +3 more
semanticscholar +1 more source
Soybean employs its circadian clock, governed by GmCCA1, to rhythmically defend against soybean cyst nematodes. The pathogen retaliates by secreting the effector Hg4E02, which hijacks the clock to suppress defense and co‐opt the host's translation machinery for nutrient acquisition.
Xingwei Wang +21 more
wiley +1 more source
Controlling sap-sucking insect pests with recombinant endophytes expressing plant lectin [PDF]
We developed a novel pest management strategy, which uses endophytes to express anti-pest plant lectins. Fungal endophyte of Chaetomium globosum YY-11 with anti-fungi activities was isolated from rape seedlings, and bacterial endophytes of SJ-10 ...
Gaofu Qi +4 more
core +1 more source
The brown planthopper Nilaparvata lugens (BPH) is one of the most harmful insect pests in rice paddy fields, which causes considerable yield loss and consequent economic problems, particularly in the central plain of Thailand.
Sukij Skawsang +3 more
semanticscholar +1 more source

