Emerging Sensor Technology in Agriculture

Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of...

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I whakaputaina: MDPI - Multidisciplinary Digital Publishing Institute 2021
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Urunga tuihono:ONIX_20210501_9783039436132_1091
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collection Directory of Open Access Books
description Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of research. The diversity of applications in which digital agriculture can make an important difference in day-to-day farming decision making makes this discipline an important focus of research internationally.
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id doab-20.500.12854ir-69345
institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-693452024-03-28T03:31:35Z Emerging Sensor Technology in Agriculture Fuentes, Sigfredo Poblete-Echeverria, Carlos apple orchards modeling and simulation unmanned aerial vehicles fruit ripeness ethylene gas detection 3D crop modeling remote sensing on-ground sensing depth images parameter acquisition capacitor sensor deposit mass pesticide droplets formulations ionization CFD airflow field test monitoring method spectral sensor crop growth computer vision deep learning image processing pose estimation animal detection precision livestock Citrus sinensis L. Osbeck mechanical harvesting acceleration sensor vibration time logistic regression adaptive thresholding fruit detection parameter tuning phenotype phenotyping phenomics Triticum aestivum water deficit stress infrared leaf area index cocoa beans volatile compounds artificial neural networks VitiCanopy app bushfires infrared thermography near-infrared spectroscopy smoke taint artificial intelligence Kinect sensor RGB RGB-D image segmentation colour thresholding bunch area bunch volume point cloud mesh surface reconstruction image analysis cluster morphology machine learning non-invasive sensing technologies proximal sensing precision viticulture partial least square support vector machine Gaussian processes soybean pigeon pea guar tepary bean n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography Digital agriculture is gaining traction among scientists implementing different new and emerging sensor technologies to monitor complex soil–plant–atmosphere interactions in an accurate, cost-effective and user-friendly manner. This book presents some of the latest advances in this emerging area of research. The diversity of applications in which digital agriculture can make an important difference in day-to-day farming decision making makes this discipline an important focus of research internationally. 2021-05-01T15:47:13Z 2021-05-01T15:47:13Z 2020 book ONIX_20210501_9783039436132_1091 9783039436132 9783039436149 https://directory.doabooks.org/handle/20.500.12854/69345 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/3137 https://mdpi.com/books/pdfview/book/3137 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03943-614-9 10.3390/books978-3-03943-614-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039436132 9783039436149 240 Basel, Switzerland open access
spellingShingle apple orchards
modeling and simulation
unmanned aerial vehicles
fruit ripeness
ethylene gas detection
3D crop modeling
remote sensing
on-ground sensing
depth images
parameter acquisition
capacitor sensor
deposit mass
pesticide droplets
formulations
ionization
CFD
airflow field test
monitoring method
spectral sensor
crop growth
computer vision
deep learning
image processing
pose estimation
animal detection
precision livestock
Citrus sinensis L. Osbeck
mechanical harvesting
acceleration sensor
vibration time
logistic regression
adaptive thresholding
fruit detection
parameter tuning
phenotype
phenotyping
phenomics
Triticum aestivum
water deficit
stress
infrared
leaf area index
cocoa beans
volatile compounds
artificial neural networks
VitiCanopy app
bushfires
infrared thermography
near-infrared spectroscopy
smoke taint
artificial intelligence
Kinect sensor
RGB
RGB-D
image segmentation
colour thresholding
bunch area
bunch volume
point cloud
mesh
surface reconstruction
image analysis
cluster morphology
machine learning
non-invasive sensing technologies
proximal sensing
precision viticulture
partial least square
support vector machine
Gaussian processes
soybean
pigeon pea
guar
tepary bean
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
Emerging Sensor Technology in Agriculture
title Emerging Sensor Technology in Agriculture
title_full Emerging Sensor Technology in Agriculture
title_fullStr Emerging Sensor Technology in Agriculture
title_full_unstemmed Emerging Sensor Technology in Agriculture
title_short Emerging Sensor Technology in Agriculture
title_sort emerging sensor technology in agriculture
topic apple orchards
modeling and simulation
unmanned aerial vehicles
fruit ripeness
ethylene gas detection
3D crop modeling
remote sensing
on-ground sensing
depth images
parameter acquisition
capacitor sensor
deposit mass
pesticide droplets
formulations
ionization
CFD
airflow field test
monitoring method
spectral sensor
crop growth
computer vision
deep learning
image processing
pose estimation
animal detection
precision livestock
Citrus sinensis L. Osbeck
mechanical harvesting
acceleration sensor
vibration time
logistic regression
adaptive thresholding
fruit detection
parameter tuning
phenotype
phenotyping
phenomics
Triticum aestivum
water deficit
stress
infrared
leaf area index
cocoa beans
volatile compounds
artificial neural networks
VitiCanopy app
bushfires
infrared thermography
near-infrared spectroscopy
smoke taint
artificial intelligence
Kinect sensor
RGB
RGB-D
image segmentation
colour thresholding
bunch area
bunch volume
point cloud
mesh
surface reconstruction
image analysis
cluster morphology
machine learning
non-invasive sensing technologies
proximal sensing
precision viticulture
partial least square
support vector machine
Gaussian processes
soybean
pigeon pea
guar
tepary bean
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
topic_facet apple orchards
modeling and simulation
unmanned aerial vehicles
fruit ripeness
ethylene gas detection
3D crop modeling
remote sensing
on-ground sensing
depth images
parameter acquisition
capacitor sensor
deposit mass
pesticide droplets
formulations
ionization
CFD
airflow field test
monitoring method
spectral sensor
crop growth
computer vision
deep learning
image processing
pose estimation
animal detection
precision livestock
Citrus sinensis L. Osbeck
mechanical harvesting
acceleration sensor
vibration time
logistic regression
adaptive thresholding
fruit detection
parameter tuning
phenotype
phenotyping
phenomics
Triticum aestivum
water deficit
stress
infrared
leaf area index
cocoa beans
volatile compounds
artificial neural networks
VitiCanopy app
bushfires
infrared thermography
near-infrared spectroscopy
smoke taint
artificial intelligence
Kinect sensor
RGB
RGB-D
image segmentation
colour thresholding
bunch area
bunch volume
point cloud
mesh
surface reconstruction
image analysis
cluster morphology
machine learning
non-invasive sensing technologies
proximal sensing
precision viticulture
partial least square
support vector machine
Gaussian processes
soybean
pigeon pea
guar
tepary bean
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
url ONIX_20210501_9783039436132_1091