A review of deep learning used in the hyperspectral image analysis for agriculture

C Wang, B Liu, L Liu, Y Zhu, J Hou, P Liu… - Artificial Intelligence …, 2021 - Springer
Hyperspectral imaging is a non-destructive, nonpolluting, and fast technology, which can
capture up to several hundred images of different wavelengths and offer relevant spectral …

Drones in plant disease assessment, efficient monitoring, and detection: A way forward to smart agriculture

A Abbas, Z Zhang, H Zheng, MM Alami, AF Alrefaei… - Agronomy, 2023 - mdpi.com
Plant diseases are one of the major threats to global food production. Efficient monitoring
and detection of plant pathogens are instrumental in restricting and effectively managing the …

Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress

A Lowe, N Harrison, AP French - Plant methods, 2017 - Springer
This review explores how imaging techniques are being developed with a focus on
deployment for crop monitoring methods. Imaging applications are discussed in relation to …

Machine learning for high-throughput stress phenoty** in plants

A Singh, B Ganapathysubramanian, AK Singh… - Trends in plant …, 2016 - cell.com
Advances in automated and high-throughput imaging technologies have resulted in a
deluge of high-resolution images and sensor data of plants. However, extracting patterns …

[HTML][HTML] Advanced high-throughput plant phenoty** techniques for genome-wide association studies: A review

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AK Mahlein - Plant disease, 2016 - Am Phytopath Society
Early and accurate detection and diagnosis of plant diseases are key factors in plant
production and the reduction of both qualitative and quantitative losses in crop yield. Optical …

[HTML][HTML] A review of advanced technologies and development for hyperspectral-based plant disease detection in the past three decades

N Zhang, G Yang, Y Pan, X Yang, L Chen, C Zhao - Remote Sensing, 2020 - mdpi.com
The detection, quantification, diagnosis, and identification of plant diseases is particularly
crucial for precision agriculture. Recently, traditional visual assessment technology has not …

From visual estimates to fully automated sensor-based measurements of plant disease severity: status and challenges for improving accuracy

CH Bock, JGA Barbedo, EM Del Ponte… - Phytopathology …, 2020 - Springer
The severity of plant diseases, traditionally the proportion of the plant tissue exhibiting
symptoms, is a key quantitative variable to know for many diseases and is prone to error …

Hyperspectral sensors and imaging technologies in phytopathology: state of the art

AK Mahlein, MT Kuska, J Behmann… - Annual review of …, 2018 - annualreviews.org
Plant disease detection represents a tremendous challenge for research and practical
applications. Visual assessment by human raters is time-consuming, expensive, and error …

Challenges and opportunities in machine-augmented plant stress phenoty**

A Singh, S Jones, B Ganapathysubramanian… - Trends in Plant …, 2021 - cell.com
Plant stress phenoty** is essential to select stress-resistant varieties and develop better
stress-management strategies. Standardization of visual assessments and deployment of …