A review of deep learning in multiscale agricultural sensing

D Wang, W Cao, F Zhang, Z Li, S Xu, X Wu - Remote Sensing, 2022 - mdpi.com
Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …

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 …

Alfalfa yield prediction using UAV-based hyperspectral imagery and ensemble learning

L Feng, Z Zhang, Y Ma, Q Du, P Williams, J Drewry… - Remote Sensing, 2020 - mdpi.com
Alfalfa is a valuable and intensively produced forage crop in the United States, and the
timely estimation of its yield can inform precision management decisions. However …

UAVs challenge to assess water stress for sustainable agriculture

J Gago, C Douthe, RE Coopman, PP Gallego… - Agricultural water …, 2015 - Elsevier
Unmanned aerial vehicles (UAVs) present an exciting opportunity to monitor crop fields with
high spatial and temporal resolution remote sensing capable of improving water stress …

Management of crop water under drought: a review

G Bodner, A Nakhforoosh, HP Kaul - Agronomy for Sustainable …, 2015 - Springer
Drought is a predominant cause of low yields worldwide. There is an urgent need for more
water efficient crop** systems facing large water consumption of irrigated agriculture and …

Detecting powdery mildew disease in squash at different stages using UAV-based hyperspectral imaging and artificial intelligence

J Abdulridha, Y Ampatzidis, P Roberts… - Biosystems …, 2020 - Elsevier
In this study hyperspectral imaging (380–1020 nm) and machine learning were utilised to
develop a technique for detecting different disease development stages (asymptomatic …

Drones: innovative technology for use in precision pest management

FH Iost Filho, WB Heldens, Z Kong… - Journal of economic …, 2020 - academic.oup.com
Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early
outbreak detection and treatment application are inherent to effective pest management …

Recent advances in crop water stress detection

SO Ihuoma, CA Madramootoo - Computers and Electronics in Agriculture, 2017 - Elsevier
In order to meet the demand for increased global food production under limited water
resources, implementation of suitable irrigation scheduling technique is crucial, particularly …

Corn grain yield estimation from vegetation indices, canopy cover, plant density, and a neural network using multispectral and RGB images acquired with unmanned …

H García-Martínez, H Flores-Magdaleno… - Agriculture, 2020 - mdpi.com
Corn yields vary spatially and temporally in the plots as a result of weather, altitude, variety,
plant density, available water, nutrients, and planting date; these are the main factors that …

Development of spectral indices for detecting and identifying plant diseases

AK Mahlein, T Rumpf, P Welke, HW Dehne… - Remote Sensing of …, 2013 - Elsevier
Spectral vegetation indices (SVIs) have been shown to be useful for an indirect detection of
plant diseases. However, these indices have not been evaluated to detect or to differentiate …