Machine learning for high-throughput stress phenotyping 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 …

A review of advanced machine learning methods for the detection of biotic stress in precision crop protection

J Behmann, AK Mahlein, T Rumpf, C Römer… - Precision …, 2015 - Springer
Effective crop protection requires early and accurate detection of biotic stress. In recent
years, remarkable results have been achieved in the early detection of weeds, plant …

Using deep learning for image-based plant disease detection

SP Mohanty, DP Hughes, M Salathé - Frontiers in plant science, 2016 - frontiersin.org
Crop diseases are a major threat to food security, but their rapid identification remains
difficult in many parts of the world due to the lack of the necessary infrastructure. 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 …

The future of Internet of Things in agriculture: Plant high-throughput phenotypic platform

J Fan, Y Zhang, W Wen, S Gu, X Lu, X Guo - Journal of Cleaner Production, 2021 - Elsevier
With continuous collaborative research in sensor technology, communication technology,
plant science, computer science and engineering science, Internet of Things (IoT) in …

Chlorophyll fluorescence imaging uncovers photosynthetic fingerprint of citrus Huanglongbing

H Cen, H Weng, J Yao, M He, J Lv, S Hua… - Frontiers in plant …, 2017 - frontiersin.org
Huanglongbing (HLB) is one of the most destructive diseases of citrus, which has posed a
serious threat to the global citrus production. This research was aimed to explore the use of …

Improving plant disease classification by adaptive minimal ensembling

A Bruno, D Moroni, R Dainelli, L Rocchi… - Frontiers in Artificial …, 2022 - frontiersin.org
A novel method for improving plant disease classification, a challenging and time-
consuming process, is proposed. First, using as baseline EfficientNet, a recent and …

Combining multicolor fluorescence imaging with multispectral reflectance imaging for rapid citrus Huanglongbing detection based on lightweight convolutional neural …

C He, X Li, Y Liu, B Yang, Z Wu, S Tan, D Ye… - … and Electronics in …, 2022 - Elsevier
Citrus Huanglongbing (HLB) has posed a great challenge to the citrus production. Timely
removal of HLB infected trees was considered as one of the most effective strategies for …

A review on agricultural advancement based on computer vision and machine learning

A Paul, S Ghosh, AK Das, S Goswami… - Emerging Technology in …, 2020 - Springer
The importance of agriculture in modern society need not be overstated. In order to meet the
huge requirements of food and to mitigate, the conventional problems of cropping smart and …

An artificial intelligence and cloud based collaborative platform for plant disease identification, tracking and forecasting for farmers

KK Singh - 2018 IEEE international conference on cloud …, 2018 - ieeexplore.ieee.org
Plant diseases are a major threat to farmers, consumers, environment and the global
economy. In India alone, 35% of field crops are lost to pathogens and pests causing losses …