Delwedd Flaen

Epidemiology and Control of Plant Diseases

This reprint is intended for a broad readership of phytopathologists. It includes different scientific contributions focused on many crucial aspects, such as the identification, characterization and rapid detection of plant diseases; predictive models and deep learning networks; and ecofriendly meas...

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Wedi'i Gadw mewn:
Fformat: Online
Iaith:Saesneg
Cyhoeddwyd: MDPI - Multidisciplinary Digital Publishing Institute 2023
Pynciau:
leaf wetness
temperatures
validation
Venturia oleaginea
Coniella diplodiella
environmental factors
infection pathway
inoculum dose
incubation
commercial seed lots
Capsicum annuum
epidemiology
source of infection
outbreak
pathway
plant disease management
Solanum lycopersicum
Pectobacterium parmentieri
qPCR
bacterial taxonomy
bacterial identification
sensitivity
soft rot
pathogen detection
wilt
passion fruit
Fusarium oxysporum species complex
Thielaviopsis punctulata
date palm
black scorch disease
multi-locus phylogeny
anatomy
biotic stress
catalase
early blight
paclobutrazol
peroxidase
phytopathogens
disease index
antifungal
chlorophyll content
LAMP
OEGV
Geminiviridae
olive viruses
Jute
disease detection
deep learning
YOLO-JD
image processing
climate change
diversity
food security
multi-gene phylogeny
new species
plant pathology
taxonomy
legumes
metabolomics
stress tolerance
metabolome annotation
organic vineyards
sustainable management
powdery mildew
gray mold
sour rot
postharvest quality
contamination
health
infection
molecular techniques
selection
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes
Mynediad Ar-lein:ONIX_20230405_9783036569536_187
Tagiau: Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
Crynodeb:This reprint is intended for a broad readership of phytopathologists. It includes different scientific contributions focused on many crucial aspects, such as the identification, characterization and rapid detection of plant diseases; predictive models and deep learning networks; and ecofriendly measures for disease management.

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