Current state of hyperspectral remote sensing for early plant disease detection: A review

A Terentev, V Dolzhenko, A Fedotov, D Eremenko - Sensors, 2022 - mdpi.com
The development of hyperspectral remote sensing equipment, in recent years, has provided
plant protection professionals with a new mechanism for assessing the phytosanitary state of …

Hyperspectral imaging and machine learning in food microbiology: Developments and challenges in detection of bacterial, fungal, and viral contaminants

A Soni, Y Dixit, MM Reis… - … Reviews in Food Science …, 2022 - Wiley Online Library
Hyperspectral imaging (HSI) is a robust and nondestructive method that can detect foreign
particles such as microbial, chemical, and physical contamination in food. This review …

Wheat yellow rust detection using UAV-based hyperspectral technology

A Guo, W Huang, Y Dong, H Ye, H Ma, B Liu, W Wu… - Remote Sensing, 2021 - mdpi.com
Yellow rust is a worldwide disease that poses a serious threat to the safety of wheat
production. Numerous studies on near-surface hyperspectral remote sensing at the leaf …

A novel deep learning instance segmentation model for automated marine oil spill detection

ST Yekeen, AL Balogun, KBW Yusof - ISPRS Journal of Photogrammetry …, 2020 - Elsevier
The visual similarity of oil slick and other elements, known as look-alike, affects the reliability
of synthetic aperture radar (SAR) images for marine oil spill detection. So far, detection and …

Hyperspectral sensing of plant diseases: Principle and methods

L Wan, H Li, C Li, A Wang, Y Yang, P Wang - Agronomy, 2022 - mdpi.com
Pathogen infection has greatly reduced crop production. As the symptoms of diseases
usually appear when the plants are infected severely, rapid identification approaches are …

[HTML][HTML] Hyperspectral image analysis and machine learning techniques for crop disease detection and identification: A review

YE García-Vera, A Polochè-Arango… - Sustainability, 2024 - mdpi.com
Originally, the use of hyperspectral images was for military applications, but their use has
been extended to precision agriculture. In particular, they are used for activities related to …

Advances in infrared spectroscopy and hyperspectral imaging combined with artificial intelligence for the detection of cereals quality

D An, L Zhang, Z Liu, J Liu, Y Wei - Critical Reviews in Food …, 2023 - Taylor & Francis
Cereals provide humans with essential nutrients, and its quality assessment has attracted
widespread attention. Infrared (IR) spectroscopy (IRS) and hyperspectral imaging (HSI), as …

Monitoring wheat powdery mildew based on hyperspectral, thermal infrared, and RGB image data fusion

Z Feng, L Song, J Duan, L He, Y Zhang, Y Wei, W Feng - Sensors, 2021 - mdpi.com
Powdery mildew severely affects wheat growth and yield; therefore, its effective monitoring is
essential for the prevention and control of the disease and global food security. In the …

Application of artificial intelligence in phenomics

S Nabwire, HK Suh, MS Kim, I Baek, BK Cho - Sensors, 2021 - mdpi.com
Plant phenomics has been rapidly advancing over the past few years. This advancement is
attributed to the increased innovation and availability of new technologies which can enable …

A detection of tomato plant diseases using deep learning MNDLNN classifier

R Bora, D Parasar, S Charhate - Signal, Image and Video Processing, 2023 - Springer
In the world, tomato is a significant economic crop. However, it is easily affected by various
diseases. Misprediction of disease is caused since many prevailing methodologies focused …