SlideShare a Scribd company logo
AgrometeorologicalAgrometeorological MonitoringMonitoring
and Forecasts for Pest andand Forecasts for Pest and
Disease ControlDisease Control
Simone Orlandini
Department of Plant, Soil and Environmental Science
University of Florence
International Workshop on Addressing the Livelihood Crisis of Farmers
Belo Horizonte, Brazil, 12-14 July 2010
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
BackgroundBackground
Widening of
biological
knowledge
BackgroundBackground
Development of
computer science and
telecommuncations
Most affected regions: tropics
and developing Countries
Causes:
o Lack of technologies
o Crop successions
o High temperatures
o Possibility to have more than one
cycle per year
Area Crop losses (%)
Europe 25
Oceania 28
North and central
America
29
URSS e China 30
South America 33
Africa 42
Asia 43
BackgroundBackground
Constant level of crop
losses 0
5
10
15
20
25
30
35
40
anni 50 anni 60-70 oggi
insetti malattie infestantipest diseas
e
weed
1960-19701950 current
High level of
pesticide utilisation
BackgroundBackground
NeedsNeeds of informationof information
o There is the need of information disseminated to the growers to
rationalise crop protection.
o Usually farmers carry out their decision in condition of high risk
and uncertainty.
o The lack of knowledge increases the level of risk in farm
management, and farmers have to increase the quantity of
chemical and energy inputs, without solving the problems.
o A way to help growers during their activity is represented by the
acquisition of high quality elaborated information, so reducing
decision making uncertainty minimising the use of chemical and
energy inputs.
AgrometeorologicalAgrometeorological modelling can be the suitable toolmodelling can be the suitable tool
to provide this informationto provide this information
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
Field stationsField stations
LeafLeaf
wetnesswetness
sensorssensors
Remote sensingRemote sensing –– input datainput data
maps of downy mildewmaps of downy mildew
infectioninfection
1.00E+00
1.00E+01
1.00E+02
1.00E+03
1.00E+04
1.00E+05
1.00E+06
1.00E+07
1.00E+08
1.00E+09
1.00E+10
06.05.
11.05.
16.05.
21.05.
26.05.
31.05.
05.06.
10.06.
15.06.
20.06.
25.06.
30.06.
05.07.
10.07.
15.07.
measured LW
dropben LW
sweb LW
control LW
Radar (RAINFALL)
Epidemiological
model
Ground stations
LWD model
Remote sensingRemote sensing –– identification of symptomsidentification of symptoms
on crop canopies usingon crop canopies using multispectralmultispectral imagesimages
Numerical weatherNumerical weather
modelsmodels
Seasonal forecastSeasonal forecast
GISGIS
Map of number of days for the
outbreak of the current infection
Number of generation of
Bactrocera oleae
Simulated impactsSimulated impacts
of leafof leaf--damagingdamaging
pest infestation onpest infestation on
maize yield atmaize yield at
regional scale (30regional scale (30--
arcminute grids inarcminute grids in
Tanzania). LeafTanzania). Leaf
damages wasdamages was
implementedimplemented
through a leaf areathrough a leaf area
coupling point incoupling point in
thethe DSSAT modelDSSAT model
www.regional.org.au
Crop modelsCrop models
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
MechanisticMechanistic EmpiricalEmpirical
http://www.ipm.ucdavis.edu
Cornell University in Geneva, New York
Other approaches:Other approaches:
fuzzy, neural networkfuzzy, neural network
fuzzyfuzzy
inferenceinference
dede--
fuzzificationfuzzification
yesyes
oror
nono
TT
RHRH
fuzzificationfuzzification
fuzzificationfuzzification
base ofbase of
rulesrules
QuantitativeQuantitative
informationinformation
QualitativeQualitative
informationinformation
&&
R. D. Magarey, T. B. Sutton, and C. L. Thayer
Department of Plant Pathology, North Carolina State
University, Raleigh 27696..
Main modelsMain models
Coltura Malat. Mod.
ABETE 3 3
AGRUMI 1 1
AVENA 2 2
AVOCADO 1 1
BANANA 2 4
BARBABIET. 2 2
BEGONIA 1 1
CACAO 1 1
CAFFÈ 1 1
CANNAZUC. 1 1
CAROTA 2 2
CASTAGNO 1 1
CAUCCIÙ’ 2 3
CAVOLO 2 3
CEREALI 4 6
CILIEGIO 2 2
CIPOLLA 2 2
COCOMERO 1 1
COTICOERB. 1 1
COTONE 3 4
CRESCIONE 1 1
DUGLASIA 1 1
FAGIOLO 4 4
FRAGOLA 4 5
GINEPRO 1 1
GIRASOLE 2 2
WHEAT 10 58
LUPPOLO 1 3
Coltura Malat. Mod.
MAIS 4 4
MANDORLO 1 1
MANGO 1 1
MEDICA 2 3
APPLE 4 18
MELONE 1 1
PEANUT 5 13
NOCCIOLO 1 1
OLMO 1 1
BARLEY 5 13
POTATO 4 21
PESCO 1 1
PINO 4 4
PIOPPO 3 3
PISELLO 1 1
POMODORO 4 6
QUERCIA 1 1
RAPA 2 4
RICE 4 17
SEDANO 1 1
SEGALE 1 1
SOIA 5 9
SORGO 7 7
SPINACI 1 1
SUSINO 1 1
TABACCO 2 2
TRIFOGLIO 1 1
GRAPEVINE 4 17
Source: Erick D. DeWolf and Scott A. Isard, 2007. Disease Cycle Approach to Plant Disease Prediction
Annu. Rev. Phytopathol. 2007. 45:203–20
Year of formulationYear of formulation
ContinentContinent
0
10
20
30
40
50 Eur.
Asia
Africa
S.Am.
N.Am.
Oceania
Input example:Input example: PlasmoparaPlasmopara viticolaviticola
simulation modelssimulation models
Type Model Temp. Precip. RH LWD
Goidanich G G
Rule of 3 10 G G
DM CAST O O O O
EPI Winter M 10 G
Empirical EPI Summer G 3 O d
POM G
PCOP G G
Dyonis G 3 O d
MILVIT 3 O 3 O
VINEMILD O O O
O d O d O d
Mechanistic 15 MI n 15 MI n 15 MI n
Freiburg O O O O
PLASMO O O O O
Rules
PRO O
Output example:Output example:
PlasmoparaPlasmopara
viticolaviticola
simulationsimulation
modelsmodels
Model Output
Goidanich SINGLEINFORMATION
Reg. 310
dmCAST INFECTIONPOTENTIAL
EPIInv.
EPIEst.
POM
PCOP
Dyonis
MILVIT SPECIFICBIOLOGICALAND
Vinemild EPIDEMIOLOGICALDATA
PRO
Freiburg
PLASMO
DMsim.
Example of variables included into different kinds of modelsExample of variables included into different kinds of models
L. M. Contreras-Medina, I. Torres-Pacheco, R. G. Guevara-González, R. J. Romero-Troncoso, I. R. Terol-Villalobos, R. A. Osornio-Rios, 2009.
Mathematical modeling tendencies in plant pathology. African Journal of Biotechnology Vol. 8 (25), pp. 7399-7408
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
Condition of applicationCondition of application
o Climatic classification
o Future climatic scenario for climate change and variability
analysis
o Field monitoring and forecast for crop protection
ClimaticClimatic
classificationclassification
Potato late blight riskPotato late blight risk
Climatic risk for potato late blight in the Andes region of Venezuela (Beatriz
Ibet Lozada Garcia; Paulo Cesar Sentelhas; Luciano Roberto Tapia; Gerd
Sparovek, 2008)
Predicted severity of phoma stemPredicted severity of phoma stem
canker (L. maculans) at harvestcanker (L. maculans) at harvest
(Sc) on winter oilseed rape crops.(Sc) on winter oilseed rape crops.
a)1960-1990
d) 2050 LO
c)2020 HI
b)2020 LO
e) 2050 HI
Zhou et al. 1999)
Climate changeClimate change
impactimpact
Probable number ofProbable number of
generations of leafgenerations of leaf
miner (Leucopteraminer (Leucoptera
coffeella) on coffeecoffeella) on coffee
plant in Brazilplant in Brazil
Source: Ghini R. et al., 2008. Risk analysis of climate change on coffee nematodes
and leaf miner in Brazil. Pesq. agropec. bras. vol.43 n.2.
To treatTo treat
Not to treatNot to treat
Field monitoring and forecast for cropField monitoring and forecast for crop
protectionprotection
Information utilisationInformation utilisation
For using information obtained by models or by decision making systems in order
to define the field treatment epochs, different aspects have to be highlighted
Necessary to treat when
• the pathogen is present
• the crop is susceptible
• the treatment is efficacious
To avoid treatments
• in advance, for losses of efficacy due to the product degradation and to the
growth of plants
• late, for losses of efficacy due to a too developed infective process
Factors to consider
• character of the farmer
• need to have all the information concerning the disease and the crop
• position of the threshold of action and damage
• application with strategic or tactical aims
State Disease Crop Pathogen Benefit
UK Stem canker, 
light leaf spot 
oil rape Leptosphaeria 
maculans
Pyrenopeziza brassicae
increase average yields by up to 
0.5 t/ha (equivalent to £75/ha or 
£15 million/annum if benefits 
occur on 200,000ha)
1
Virginia 
(USA)
leaf spot peanut 
growers 
Cercospora arachidicola 1987‐1990: input costs reduced 
by 33% or $57 per ha
1990‐1995: input costs reduced 
by 43% or $66 per ha
2
Italy Grapevine 
downy mildew
grapevine Plasmopara viticola The threshold for an economical 
convenience in the adoption of 
the agrometeorological system is 
about 6 ha.
3
Florida Brown spot citrus Alternaria alternata 4
1. Dr Peter Gladders, ADAS Boxworth, Cambridge. LK0944: Validation of disease models in PASSWORD integrated decision support for pests and diseases in
oilseed rape. HGCA conference 2004: Managing soil and roots for profitable production
2. Phipps PM, Deck SH,Walker DR. 1997.Weather-based crop and disease advisories for peanuts in Virginia. Plant Dis. 81:236–44
3. L. Massetti, A. Dalla Marta and S. Orlandini, Preliminary economic evaluation of an agrometeorological system for Plasmopara viticola infections management.
4. Alka Bhatia, P. D. Roberts, L. W. Timmer, 2003. Evaluation of the Alter-Rater Model for Timing of Fungicide Applications for Control of Alternaria Brown Spot of
Citrus. Plant Disease / September 2003.
Model application economic benefitsModel application economic benefits
Costs and benefits ofCosts and benefits of AlterAlter--Rater ModelRater Model
Benefits from theBenefits from the
IPM impactIPM impact
studiesstudies
Economic Impacts of Integrated Pest Management in Developing Countries:
Evidence from the IPM CRSP
Tatjana Hristovska
Thesis submitted to the faculty of the Virginia Polytechnic Institute and State
University, 2009
Other benefitsOther benefits
reduction of chemical inputs in the ecosystem
soil fertility conservation
smaller amount of chemical residuals in food
work quality improvement
reduction in the development of resistant forms
safeguarding of natural predatory
reduction of new diseases
ImplementationImplementation of the modelof the model
Tables for manual calculations
Simplicity of application, difficulty to obtain information for an
efficacious use
Electronic plant stations
Collocation in field, complete automation, imprecise results,
frequent damages
Computer
Rapidity of intervention (tactic), possibility to analyse past
conditions, possible simulation with future scenarios (strategic),
automatic collection of data, use for different aims, precision of
results
Manual calculation: Mills table (apple scab)Manual calculation: Mills table (apple scab)
LEAF WETNESS HOURS
Temperature Light Medium Severe
8 18 23 34
9 15.5 20.5 30
10 12.5 19 28
11 11.5 17 26
12 10.5 16 24
13 10 14 22.5
14 9.5 13 21
15 9 12.5 20
16 9 12.5 19
17 9 12.5 18
18 9 12.5 18
19 9 12.5 18
20 9 12.5 18
21 9 12.5 18
22 9 12.5 18
23 9 12.5 18
24 9.5 12.5 19
25 10.5 14 21
ElectronicElectronic
plantplant
stationstation
Personal computer andPersonal computer and
network ofnetwork of
meteorological sensorsmeteorological sensors
and stationsand stations
OutlineOutline
o Background
o Input data
o Models for crop protection
o Use and application
o Dissemination of information
Conditions of applicationConditions of application
Farm: in this case the model is applied directly by farmers,
with evident benefits in the evaluation of real
epidemiological condition and microclimate evaluation. On
the other hand, the management of the simulations and
the updating of the systems represent big obstacles.
Territory: it is probably preferable because it allows a better
management and updating of the system. This solution
requires the application of suitable methods for the
information dissemination among the users.
Information dissemination: the bulletinsInformation dissemination: the bulletins
o Advises and information to the users can be disseminated
by using: personal contact, newspaper and magazines,
radio and television, videotel, televideo, telefax, mail,
phone, INTERNET, SMS.
Mobile phoneMobile phone
From Omondi Lwande and Muchemi Lawrence (2008)
Powdery mildewPowdery mildew
riskrisk
http://www.apsnet.org/online/feature/pmildew/
Veneto (Italy)Veneto (Italy) –– infection rainfall mapinfection rainfall map
www.mausam.gov
In Florida AgroClimate.org provides a set of tools to help producers reduce risks
associated with climate variability.
In particular, the Strawberry Diseases Tool can help you with recommendations for
timing fungicide applications for Anthracnose and Botrytis fruit rot.
Maps of light leaf spot forecastMaps of light leaf spot forecast
http://www.rothamsted.bbsrc.ac.ukhttp://www.rothamsted.bbsrc.ac.uk
Lupin bean yellow mosaic virusLupin bean yellow mosaic virus
(BYMV) Forecast(BYMV) Forecast
www.syngenta-crop.co.uk/brassica-alert.aspx
Syngenta CropSyngenta Crop
Protection UK LtdProtection UK Ltd
Growers and agronomists already
registered on the Syngenta
website will automatically have
free access to Brassica Alert
AgrometeorologicalAgrometeorological MonitoringMonitoring
and Forecasts for Pest andand Forecasts for Pest and
Disease ControlDisease Control
Simone Orlandini
Department of Plant, Soil and Environmental Science
University of Florence
International Workshop on Addressing the Livelihood Crisis of Farmers
Belo Horizonte, Brazil, 12-14 July 2010
Thank you for your attention!!!
Thank you for your attention!!!

More Related Content

What's hot

Integration of maize Lethal Necrosis disease management in crop-livestock int...
Integration of maize Lethal Necrosis disease management in crop-livestock int...Integration of maize Lethal Necrosis disease management in crop-livestock int...
Integration of maize Lethal Necrosis disease management in crop-livestock int...
africa-rising
 
GRM 2013: Global Cassava Partnership for the 21st Century (GCP21) -- C Fauquet
GRM 2013: Global Cassava Partnership  for the  21st Century (GCP21) -- C FauquetGRM 2013: Global Cassava Partnership  for the  21st Century (GCP21) -- C Fauquet
GRM 2013: Global Cassava Partnership for the 21st Century (GCP21) -- C Fauquet
CGIAR Generation Challenge Programme
 
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
Mohamed Mostafa
 
Common diseases of Cassava and diseases assessment in west Africa
Common diseases of Cassava and diseases assessment in west AfricaCommon diseases of Cassava and diseases assessment in west Africa
Common diseases of Cassava and diseases assessment in west Africa
International Institute of Tropical Agriculture
 
Maize Lethal Necrosis Disease (MLND) in Kenya
Maize Lethal Necrosis Disease (MLND) in KenyaMaize Lethal Necrosis Disease (MLND) in Kenya
Maize Lethal Necrosis Disease (MLND) in Kenya
CIMMYT
 
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
ICRISAT
 
MLN Workshop: Maize lethal necrosis: the disease -- B Das
MLN Workshop: Maize lethal necrosis:  the disease -- B DasMLN Workshop: Maize lethal necrosis:  the disease -- B Das
MLN Workshop: Maize lethal necrosis: the disease -- B Das
CIMMYT
 
A region-wide response to emerging cassava pests and diseases in SE Asia
A region-wide response to emerging cassava pests and diseases in SE AsiaA region-wide response to emerging cassava pests and diseases in SE Asia
A region-wide response to emerging cassava pests and diseases in SE Asia
CGIAR Research Program on Roots, Tubers and Bananas
 
Psyllid microflora: Implications for liberibacter disease surveillance and pe...
Psyllid microflora: Implications for liberibacter disease surveillance and pe...Psyllid microflora: Implications for liberibacter disease surveillance and pe...
Psyllid microflora: Implications for liberibacter disease surveillance and pe...
Plant Biosecurity Cooperative Research Centre
 
Workshop on MLN Diagnostics and Managment in Africa
Workshop on MLN Diagnostics and Managment in AfricaWorkshop on MLN Diagnostics and Managment in Africa
Workshop on MLN Diagnostics and Managment in Africa
CIMMYT
 
Incidence and Impact of Maize Lethal Necrosis Disease in Tanzania
Incidence and Impact of Maize Lethal Necrosis Disease in TanzaniaIncidence and Impact of Maize Lethal Necrosis Disease in Tanzania
Incidence and Impact of Maize Lethal Necrosis Disease in Tanzania
CIMMYT
 
Global germplasm collections: sure benefits without seedborne diseases
Global germplasm collections: sure benefits without seedborne diseasesGlobal germplasm collections: sure benefits without seedborne diseases
Global germplasm collections: sure benefits without seedborne diseases
CIAT
 
Cassava
CassavaCassava
Cassava
CIAT
 
Technologies to drive maize yield improvement
Technologies to drive maize yield improvementTechnologies to drive maize yield improvement
Technologies to drive maize yield improvement
CIMMYT
 
Napier grass smut and stunt resistance: Introducing the Project
Napier grass smut and stunt resistance: Introducing the ProjectNapier grass smut and stunt resistance: Introducing the Project
Napier grass smut and stunt resistance: Introducing the Project
ILRI
 
Baptiste Dungu
Baptiste Dungu Baptiste Dungu
Baptiste Dungu
ExternalEvents
 
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe RustBGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
ICARDA
 
Theme 3: Managing Priority Pest & Diseases of RTB Crops
Theme 3: Managing Priority Pest & Diseases of RTB CropsTheme 3: Managing Priority Pest & Diseases of RTB Crops
Theme 3: Managing Priority Pest & Diseases of RTB Crops
CGIAR Research Program on Roots, Tubers and Bananas
 
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et alMLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
CIMMYT
 
18. *Satellite, Yields and Management - Alex Whitley
18. *Satellite, Yields and Management - Alex Whitley18. *Satellite, Yields and Management - Alex Whitley
18. *Satellite, Yields and Management - Alex Whitley
EasternOntarioCropConference
 

What's hot (20)

Integration of maize Lethal Necrosis disease management in crop-livestock int...
Integration of maize Lethal Necrosis disease management in crop-livestock int...Integration of maize Lethal Necrosis disease management in crop-livestock int...
Integration of maize Lethal Necrosis disease management in crop-livestock int...
 
GRM 2013: Global Cassava Partnership for the 21st Century (GCP21) -- C Fauquet
GRM 2013: Global Cassava Partnership  for the  21st Century (GCP21) -- C FauquetGRM 2013: Global Cassava Partnership  for the  21st Century (GCP21) -- C Fauquet
GRM 2013: Global Cassava Partnership for the 21st Century (GCP21) -- C Fauquet
 
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
التقدم في تكنولوجيا المعلومات للكشف عن أمراض النباتات Advances in Informatio...
 
Common diseases of Cassava and diseases assessment in west Africa
Common diseases of Cassava and diseases assessment in west AfricaCommon diseases of Cassava and diseases assessment in west Africa
Common diseases of Cassava and diseases assessment in west Africa
 
Maize Lethal Necrosis Disease (MLND) in Kenya
Maize Lethal Necrosis Disease (MLND) in KenyaMaize Lethal Necrosis Disease (MLND) in Kenya
Maize Lethal Necrosis Disease (MLND) in Kenya
 
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
Research Program Genetic Gains (RPGG) Review Meeting 2021: Identification of ...
 
MLN Workshop: Maize lethal necrosis: the disease -- B Das
MLN Workshop: Maize lethal necrosis:  the disease -- B DasMLN Workshop: Maize lethal necrosis:  the disease -- B Das
MLN Workshop: Maize lethal necrosis: the disease -- B Das
 
A region-wide response to emerging cassava pests and diseases in SE Asia
A region-wide response to emerging cassava pests and diseases in SE AsiaA region-wide response to emerging cassava pests and diseases in SE Asia
A region-wide response to emerging cassava pests and diseases in SE Asia
 
Psyllid microflora: Implications for liberibacter disease surveillance and pe...
Psyllid microflora: Implications for liberibacter disease surveillance and pe...Psyllid microflora: Implications for liberibacter disease surveillance and pe...
Psyllid microflora: Implications for liberibacter disease surveillance and pe...
 
Workshop on MLN Diagnostics and Managment in Africa
Workshop on MLN Diagnostics and Managment in AfricaWorkshop on MLN Diagnostics and Managment in Africa
Workshop on MLN Diagnostics and Managment in Africa
 
Incidence and Impact of Maize Lethal Necrosis Disease in Tanzania
Incidence and Impact of Maize Lethal Necrosis Disease in TanzaniaIncidence and Impact of Maize Lethal Necrosis Disease in Tanzania
Incidence and Impact of Maize Lethal Necrosis Disease in Tanzania
 
Global germplasm collections: sure benefits without seedborne diseases
Global germplasm collections: sure benefits without seedborne diseasesGlobal germplasm collections: sure benefits without seedborne diseases
Global germplasm collections: sure benefits without seedborne diseases
 
Cassava
CassavaCassava
Cassava
 
Technologies to drive maize yield improvement
Technologies to drive maize yield improvementTechnologies to drive maize yield improvement
Technologies to drive maize yield improvement
 
Napier grass smut and stunt resistance: Introducing the Project
Napier grass smut and stunt resistance: Introducing the ProjectNapier grass smut and stunt resistance: Introducing the Project
Napier grass smut and stunt resistance: Introducing the Project
 
Baptiste Dungu
Baptiste Dungu Baptiste Dungu
Baptiste Dungu
 
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe RustBGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
BGRI Global Rust Monitoring: Challenges and Opportunities for Stripe Rust
 
Theme 3: Managing Priority Pest & Diseases of RTB Crops
Theme 3: Managing Priority Pest & Diseases of RTB CropsTheme 3: Managing Priority Pest & Diseases of RTB Crops
Theme 3: Managing Priority Pest & Diseases of RTB Crops
 
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et alMLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
MLN Workshop: Agronomic management of maize lethal necrosis -- S Mugo, et al
 
18. *Satellite, Yields and Management - Alex Whitley
18. *Satellite, Yields and Management - Alex Whitley18. *Satellite, Yields and Management - Alex Whitley
18. *Satellite, Yields and Management - Alex Whitley
 

Similar to S3 orlandini presentation about prognosis models

Nuclear Techniques in Food and Agriculture
Nuclear Techniques in Food and AgricultureNuclear Techniques in Food and Agriculture
Nuclear Techniques in Food and Agriculture
Jeju National University
 
Plant genetic resources and climate change
Plant genetic resources and climate changePlant genetic resources and climate change
Plant genetic resources and climate change
Decision and Policy Analysis Program
 
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
Global Risk Forum GRFDavos
 
Louise barwell wp3 14 Nov 19
Louise barwell wp3 14 Nov 19Louise barwell wp3 14 Nov 19
Louise barwell wp3 14 Nov 19
Forest Research
 
Food security- The role of agricultural technologies
Food security- The role of agricultural technologiesFood security- The role of agricultural technologies
Food security- The role of agricultural technologies
New Food Innovation Ltd
 
Food security
Food securityFood security
Food security
Fatimata Kone
 
Influence of fertilizers on incidence and severity of early blight and late b...
Influence of fertilizers on incidence and severity of early blight and late b...Influence of fertilizers on incidence and severity of early blight and late b...
Influence of fertilizers on incidence and severity of early blight and late b...
Innspub Net
 
Challenges and opportunities in a 4 degrees warmer world in dry areas
Challenges and opportunities in a 4 degrees warmer world in dry areasChallenges and opportunities in a 4 degrees warmer world in dry areas
Challenges and opportunities in a 4 degrees warmer world in dry areas
CCAFS | CGIAR Research Program on Climate Change, Agriculture and Food Security
 
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
Borlaug Global Rust Initiative
 
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
Borlaug Global Rust Initiative
 
Crop diversity and climate change
Crop diversity and climate changeCrop diversity and climate change
Crop diversity and climate change
Luigi Guarino
 
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
Agriculture Journal IJOEAR
 
Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...
CIAT
 
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
Komal Kute
 
Achievements and outcomes in implementation of Napier smut and stunt resistan...
Achievements and outcomes in implementation of Napier smut and stunt resistan...Achievements and outcomes in implementation of Napier smut and stunt resistan...
Achievements and outcomes in implementation of Napier smut and stunt resistan...
ILRI
 
Pesticide risk management through farmer field schools in the Senegal and Nig...
Pesticide risk management through farmer field schools in the Senegal and Nig...Pesticide risk management through farmer field schools in the Senegal and Nig...
Pesticide risk management through farmer field schools in the Senegal and Nig...
FAO
 
Sj iwmt mzoa==
Sj iwmt mzoa==Sj iwmt mzoa==
Sj iwmt mzoa==
editorijserin
 
Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...
CIAT
 
International Winter Wheat Improvement Program: breeding strategies and meth...
International Winter Wheat Improvement Program: breeding strategies and meth...International Winter Wheat Improvement Program: breeding strategies and meth...
International Winter Wheat Improvement Program: breeding strategies and meth...
ICARDA
 
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
IFAD International Fund for Agricultural Development
 

Similar to S3 orlandini presentation about prognosis models (20)

Nuclear Techniques in Food and Agriculture
Nuclear Techniques in Food and AgricultureNuclear Techniques in Food and Agriculture
Nuclear Techniques in Food and Agriculture
 
Plant genetic resources and climate change
Plant genetic resources and climate changePlant genetic resources and climate change
Plant genetic resources and climate change
 
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
One Health Perspective And Assessment Of Giardia & Cryptosporidium Infections...
 
Louise barwell wp3 14 Nov 19
Louise barwell wp3 14 Nov 19Louise barwell wp3 14 Nov 19
Louise barwell wp3 14 Nov 19
 
Food security- The role of agricultural technologies
Food security- The role of agricultural technologiesFood security- The role of agricultural technologies
Food security- The role of agricultural technologies
 
Food security
Food securityFood security
Food security
 
Influence of fertilizers on incidence and severity of early blight and late b...
Influence of fertilizers on incidence and severity of early blight and late b...Influence of fertilizers on incidence and severity of early blight and late b...
Influence of fertilizers on incidence and severity of early blight and late b...
 
Challenges and opportunities in a 4 degrees warmer world in dry areas
Challenges and opportunities in a 4 degrees warmer world in dry areasChallenges and opportunities in a 4 degrees warmer world in dry areas
Challenges and opportunities in a 4 degrees warmer world in dry areas
 
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in S...
 
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
Stripe Rust and the Turkey-ICARDA Regional Cereal Rust Research Center at Izm...
 
Crop diversity and climate change
Crop diversity and climate changeCrop diversity and climate change
Crop diversity and climate change
 
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
Cattle Ticks and Risk Factors Related to Tick Infestation of Livestock in Per...
 
Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...
 
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
HIGH-THROUGHPUT PHENOTYPING METHODS FOR ECONOMIC TRAITS and DESIGNER PLANT TY...
 
Achievements and outcomes in implementation of Napier smut and stunt resistan...
Achievements and outcomes in implementation of Napier smut and stunt resistan...Achievements and outcomes in implementation of Napier smut and stunt resistan...
Achievements and outcomes in implementation of Napier smut and stunt resistan...
 
Pesticide risk management through farmer field schools in the Senegal and Nig...
Pesticide risk management through farmer field schools in the Senegal and Nig...Pesticide risk management through farmer field schools in the Senegal and Nig...
Pesticide risk management through farmer field schools in the Senegal and Nig...
 
Sj iwmt mzoa==
Sj iwmt mzoa==Sj iwmt mzoa==
Sj iwmt mzoa==
 
Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...Poster98: Seed system security asssessment new methods for understanding farm...
Poster98: Seed system security asssessment new methods for understanding farm...
 
International Winter Wheat Improvement Program: breeding strategies and meth...
International Winter Wheat Improvement Program: breeding strategies and meth...International Winter Wheat Improvement Program: breeding strategies and meth...
International Winter Wheat Improvement Program: breeding strategies and meth...
 
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
Session 3.1 Review of Genetic Tools and Knowledge that could Contribute to Ca...
 

Recently uploaded

Phenomics assisted breeding in crop improvement
Phenomics assisted breeding in crop improvementPhenomics assisted breeding in crop improvement
Phenomics assisted breeding in crop improvement
IshaGoswami9
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Leonel Morgado
 
The cost of acquiring information by natural selection
The cost of acquiring information by natural selectionThe cost of acquiring information by natural selection
The cost of acquiring information by natural selection
Carl Bergstrom
 
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero WaterSharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Texas Alliance of Groundwater Districts
 
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
AbdullaAlAsif1
 
8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf
by6843629
 
aziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobelaziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobel
İsa Badur
 
Bob Reedy - Nitrate in Texas Groundwater.pdf
Bob Reedy - Nitrate in Texas Groundwater.pdfBob Reedy - Nitrate in Texas Groundwater.pdf
Bob Reedy - Nitrate in Texas Groundwater.pdf
Texas Alliance of Groundwater Districts
 
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
Leonel Morgado
 
Medical Orthopedic PowerPoint Templates.pptx
Medical Orthopedic PowerPoint Templates.pptxMedical Orthopedic PowerPoint Templates.pptx
Medical Orthopedic PowerPoint Templates.pptx
terusbelajar5
 
Eukaryotic Transcription Presentation.pptx
Eukaryotic Transcription Presentation.pptxEukaryotic Transcription Presentation.pptx
Eukaryotic Transcription Presentation.pptx
RitabrataSarkar3
 
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
Abdul Wali Khan University Mardan,kP,Pakistan
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
Sérgio Sacani
 
Sciences of Europe journal No 142 (2024)
Sciences of Europe journal No 142 (2024)Sciences of Europe journal No 142 (2024)
Sciences of Europe journal No 142 (2024)
Sciences of Europe
 
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptxESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
PRIYANKA PATEL
 
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Sérgio Sacani
 
NuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyerNuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyer
pablovgd
 
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxThe use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
MAGOTI ERNEST
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
vluwdy49
 
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
University of Maribor
 

Recently uploaded (20)

Phenomics assisted breeding in crop improvement
Phenomics assisted breeding in crop improvementPhenomics assisted breeding in crop improvement
Phenomics assisted breeding in crop improvement
 
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
 
The cost of acquiring information by natural selection
The cost of acquiring information by natural selectionThe cost of acquiring information by natural selection
The cost of acquiring information by natural selection
 
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero WaterSharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
 
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
 
8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf
 
aziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobelaziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobel
 
Bob Reedy - Nitrate in Texas Groundwater.pdf
Bob Reedy - Nitrate in Texas Groundwater.pdfBob Reedy - Nitrate in Texas Groundwater.pdf
Bob Reedy - Nitrate in Texas Groundwater.pdf
 
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
 
Medical Orthopedic PowerPoint Templates.pptx
Medical Orthopedic PowerPoint Templates.pptxMedical Orthopedic PowerPoint Templates.pptx
Medical Orthopedic PowerPoint Templates.pptx
 
Eukaryotic Transcription Presentation.pptx
Eukaryotic Transcription Presentation.pptxEukaryotic Transcription Presentation.pptx
Eukaryotic Transcription Presentation.pptx
 
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...THEMATIC  APPERCEPTION  TEST(TAT) cognitive abilities, creativity, and critic...
THEMATIC APPERCEPTION TEST(TAT) cognitive abilities, creativity, and critic...
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
 
Sciences of Europe journal No 142 (2024)
Sciences of Europe journal No 142 (2024)Sciences of Europe journal No 142 (2024)
Sciences of Europe journal No 142 (2024)
 
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptxESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
 
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
 
NuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyerNuGOweek 2024 Ghent programme overview flyer
NuGOweek 2024 Ghent programme overview flyer
 
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxThe use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptx
 
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
 
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...
 

S3 orlandini presentation about prognosis models

  • 1. AgrometeorologicalAgrometeorological MonitoringMonitoring and Forecasts for Pest andand Forecasts for Pest and Disease ControlDisease Control Simone Orlandini Department of Plant, Soil and Environmental Science University of Florence International Workshop on Addressing the Livelihood Crisis of Farmers Belo Horizonte, Brazil, 12-14 July 2010
  • 2. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 3. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 6. Most affected regions: tropics and developing Countries Causes: o Lack of technologies o Crop successions o High temperatures o Possibility to have more than one cycle per year Area Crop losses (%) Europe 25 Oceania 28 North and central America 29 URSS e China 30 South America 33 Africa 42 Asia 43 BackgroundBackground Constant level of crop losses 0 5 10 15 20 25 30 35 40 anni 50 anni 60-70 oggi insetti malattie infestantipest diseas e weed 1960-19701950 current
  • 7. High level of pesticide utilisation BackgroundBackground
  • 8. NeedsNeeds of informationof information o There is the need of information disseminated to the growers to rationalise crop protection. o Usually farmers carry out their decision in condition of high risk and uncertainty. o The lack of knowledge increases the level of risk in farm management, and farmers have to increase the quantity of chemical and energy inputs, without solving the problems. o A way to help growers during their activity is represented by the acquisition of high quality elaborated information, so reducing decision making uncertainty minimising the use of chemical and energy inputs. AgrometeorologicalAgrometeorological modelling can be the suitable toolmodelling can be the suitable tool to provide this informationto provide this information
  • 9. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 12. Remote sensingRemote sensing –– input datainput data maps of downy mildewmaps of downy mildew infectioninfection 1.00E+00 1.00E+01 1.00E+02 1.00E+03 1.00E+04 1.00E+05 1.00E+06 1.00E+07 1.00E+08 1.00E+09 1.00E+10 06.05. 11.05. 16.05. 21.05. 26.05. 31.05. 05.06. 10.06. 15.06. 20.06. 25.06. 30.06. 05.07. 10.07. 15.07. measured LW dropben LW sweb LW control LW Radar (RAINFALL) Epidemiological model Ground stations LWD model
  • 13. Remote sensingRemote sensing –– identification of symptomsidentification of symptoms on crop canopies usingon crop canopies using multispectralmultispectral imagesimages
  • 16. GISGIS Map of number of days for the outbreak of the current infection Number of generation of Bactrocera oleae
  • 17. Simulated impactsSimulated impacts of leafof leaf--damagingdamaging pest infestation onpest infestation on maize yield atmaize yield at regional scale (30regional scale (30-- arcminute grids inarcminute grids in Tanzania). LeafTanzania). Leaf damages wasdamages was implementedimplemented through a leaf areathrough a leaf area coupling point incoupling point in thethe DSSAT modelDSSAT model www.regional.org.au Crop modelsCrop models
  • 18. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 20. Other approaches:Other approaches: fuzzy, neural networkfuzzy, neural network fuzzyfuzzy inferenceinference dede-- fuzzificationfuzzification yesyes oror nono TT RHRH fuzzificationfuzzification fuzzificationfuzzification base ofbase of rulesrules QuantitativeQuantitative informationinformation QualitativeQualitative informationinformation &&
  • 21. R. D. Magarey, T. B. Sutton, and C. L. Thayer Department of Plant Pathology, North Carolina State University, Raleigh 27696..
  • 22. Main modelsMain models Coltura Malat. Mod. ABETE 3 3 AGRUMI 1 1 AVENA 2 2 AVOCADO 1 1 BANANA 2 4 BARBABIET. 2 2 BEGONIA 1 1 CACAO 1 1 CAFFÈ 1 1 CANNAZUC. 1 1 CAROTA 2 2 CASTAGNO 1 1 CAUCCIÙ’ 2 3 CAVOLO 2 3 CEREALI 4 6 CILIEGIO 2 2 CIPOLLA 2 2 COCOMERO 1 1 COTICOERB. 1 1 COTONE 3 4 CRESCIONE 1 1 DUGLASIA 1 1 FAGIOLO 4 4 FRAGOLA 4 5 GINEPRO 1 1 GIRASOLE 2 2 WHEAT 10 58 LUPPOLO 1 3 Coltura Malat. Mod. MAIS 4 4 MANDORLO 1 1 MANGO 1 1 MEDICA 2 3 APPLE 4 18 MELONE 1 1 PEANUT 5 13 NOCCIOLO 1 1 OLMO 1 1 BARLEY 5 13 POTATO 4 21 PESCO 1 1 PINO 4 4 PIOPPO 3 3 PISELLO 1 1 POMODORO 4 6 QUERCIA 1 1 RAPA 2 4 RICE 4 17 SEDANO 1 1 SEGALE 1 1 SOIA 5 9 SORGO 7 7 SPINACI 1 1 SUSINO 1 1 TABACCO 2 2 TRIFOGLIO 1 1 GRAPEVINE 4 17
  • 23. Source: Erick D. DeWolf and Scott A. Isard, 2007. Disease Cycle Approach to Plant Disease Prediction Annu. Rev. Phytopathol. 2007. 45:203–20
  • 24. Year of formulationYear of formulation
  • 26. Input example:Input example: PlasmoparaPlasmopara viticolaviticola simulation modelssimulation models Type Model Temp. Precip. RH LWD Goidanich G G Rule of 3 10 G G DM CAST O O O O EPI Winter M 10 G Empirical EPI Summer G 3 O d POM G PCOP G G Dyonis G 3 O d MILVIT 3 O 3 O VINEMILD O O O O d O d O d Mechanistic 15 MI n 15 MI n 15 MI n Freiburg O O O O PLASMO O O O O Rules PRO O
  • 27. Output example:Output example: PlasmoparaPlasmopara viticolaviticola simulationsimulation modelsmodels Model Output Goidanich SINGLEINFORMATION Reg. 310 dmCAST INFECTIONPOTENTIAL EPIInv. EPIEst. POM PCOP Dyonis MILVIT SPECIFICBIOLOGICALAND Vinemild EPIDEMIOLOGICALDATA PRO Freiburg PLASMO DMsim.
  • 28. Example of variables included into different kinds of modelsExample of variables included into different kinds of models L. M. Contreras-Medina, I. Torres-Pacheco, R. G. Guevara-González, R. J. Romero-Troncoso, I. R. Terol-Villalobos, R. A. Osornio-Rios, 2009. Mathematical modeling tendencies in plant pathology. African Journal of Biotechnology Vol. 8 (25), pp. 7399-7408
  • 29. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 30. Condition of applicationCondition of application o Climatic classification o Future climatic scenario for climate change and variability analysis o Field monitoring and forecast for crop protection
  • 32. Potato late blight riskPotato late blight risk Climatic risk for potato late blight in the Andes region of Venezuela (Beatriz Ibet Lozada Garcia; Paulo Cesar Sentelhas; Luciano Roberto Tapia; Gerd Sparovek, 2008)
  • 33. Predicted severity of phoma stemPredicted severity of phoma stem canker (L. maculans) at harvestcanker (L. maculans) at harvest (Sc) on winter oilseed rape crops.(Sc) on winter oilseed rape crops. a)1960-1990 d) 2050 LO c)2020 HI b)2020 LO e) 2050 HI Zhou et al. 1999) Climate changeClimate change impactimpact
  • 34.
  • 35. Probable number ofProbable number of generations of leafgenerations of leaf miner (Leucopteraminer (Leucoptera coffeella) on coffeecoffeella) on coffee plant in Brazilplant in Brazil Source: Ghini R. et al., 2008. Risk analysis of climate change on coffee nematodes and leaf miner in Brazil. Pesq. agropec. bras. vol.43 n.2.
  • 36. To treatTo treat Not to treatNot to treat Field monitoring and forecast for cropField monitoring and forecast for crop protectionprotection
  • 37. Information utilisationInformation utilisation For using information obtained by models or by decision making systems in order to define the field treatment epochs, different aspects have to be highlighted Necessary to treat when • the pathogen is present • the crop is susceptible • the treatment is efficacious To avoid treatments • in advance, for losses of efficacy due to the product degradation and to the growth of plants • late, for losses of efficacy due to a too developed infective process Factors to consider • character of the farmer • need to have all the information concerning the disease and the crop • position of the threshold of action and damage • application with strategic or tactical aims
  • 38.
  • 39. State Disease Crop Pathogen Benefit UK Stem canker,  light leaf spot  oil rape Leptosphaeria  maculans Pyrenopeziza brassicae increase average yields by up to  0.5 t/ha (equivalent to £75/ha or  £15 million/annum if benefits  occur on 200,000ha) 1 Virginia  (USA) leaf spot peanut  growers  Cercospora arachidicola 1987‐1990: input costs reduced  by 33% or $57 per ha 1990‐1995: input costs reduced  by 43% or $66 per ha 2 Italy Grapevine  downy mildew grapevine Plasmopara viticola The threshold for an economical  convenience in the adoption of  the agrometeorological system is  about 6 ha. 3 Florida Brown spot citrus Alternaria alternata 4 1. Dr Peter Gladders, ADAS Boxworth, Cambridge. LK0944: Validation of disease models in PASSWORD integrated decision support for pests and diseases in oilseed rape. HGCA conference 2004: Managing soil and roots for profitable production 2. Phipps PM, Deck SH,Walker DR. 1997.Weather-based crop and disease advisories for peanuts in Virginia. Plant Dis. 81:236–44 3. L. Massetti, A. Dalla Marta and S. Orlandini, Preliminary economic evaluation of an agrometeorological system for Plasmopara viticola infections management. 4. Alka Bhatia, P. D. Roberts, L. W. Timmer, 2003. Evaluation of the Alter-Rater Model for Timing of Fungicide Applications for Control of Alternaria Brown Spot of Citrus. Plant Disease / September 2003. Model application economic benefitsModel application economic benefits
  • 40. Costs and benefits ofCosts and benefits of AlterAlter--Rater ModelRater Model
  • 41. Benefits from theBenefits from the IPM impactIPM impact studiesstudies Economic Impacts of Integrated Pest Management in Developing Countries: Evidence from the IPM CRSP Tatjana Hristovska Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University, 2009
  • 42. Other benefitsOther benefits reduction of chemical inputs in the ecosystem soil fertility conservation smaller amount of chemical residuals in food work quality improvement reduction in the development of resistant forms safeguarding of natural predatory reduction of new diseases
  • 43. ImplementationImplementation of the modelof the model Tables for manual calculations Simplicity of application, difficulty to obtain information for an efficacious use Electronic plant stations Collocation in field, complete automation, imprecise results, frequent damages Computer Rapidity of intervention (tactic), possibility to analyse past conditions, possible simulation with future scenarios (strategic), automatic collection of data, use for different aims, precision of results
  • 44. Manual calculation: Mills table (apple scab)Manual calculation: Mills table (apple scab) LEAF WETNESS HOURS Temperature Light Medium Severe 8 18 23 34 9 15.5 20.5 30 10 12.5 19 28 11 11.5 17 26 12 10.5 16 24 13 10 14 22.5 14 9.5 13 21 15 9 12.5 20 16 9 12.5 19 17 9 12.5 18 18 9 12.5 18 19 9 12.5 18 20 9 12.5 18 21 9 12.5 18 22 9 12.5 18 23 9 12.5 18 24 9.5 12.5 19 25 10.5 14 21
  • 46. Personal computer andPersonal computer and network ofnetwork of meteorological sensorsmeteorological sensors and stationsand stations
  • 47. OutlineOutline o Background o Input data o Models for crop protection o Use and application o Dissemination of information
  • 48. Conditions of applicationConditions of application Farm: in this case the model is applied directly by farmers, with evident benefits in the evaluation of real epidemiological condition and microclimate evaluation. On the other hand, the management of the simulations and the updating of the systems represent big obstacles. Territory: it is probably preferable because it allows a better management and updating of the system. This solution requires the application of suitable methods for the information dissemination among the users.
  • 49. Information dissemination: the bulletinsInformation dissemination: the bulletins o Advises and information to the users can be disseminated by using: personal contact, newspaper and magazines, radio and television, videotel, televideo, telefax, mail, phone, INTERNET, SMS.
  • 50. Mobile phoneMobile phone From Omondi Lwande and Muchemi Lawrence (2008)
  • 52. Veneto (Italy)Veneto (Italy) –– infection rainfall mapinfection rainfall map
  • 54. In Florida AgroClimate.org provides a set of tools to help producers reduce risks associated with climate variability. In particular, the Strawberry Diseases Tool can help you with recommendations for timing fungicide applications for Anthracnose and Botrytis fruit rot.
  • 55. Maps of light leaf spot forecastMaps of light leaf spot forecast http://www.rothamsted.bbsrc.ac.ukhttp://www.rothamsted.bbsrc.ac.uk
  • 56. Lupin bean yellow mosaic virusLupin bean yellow mosaic virus (BYMV) Forecast(BYMV) Forecast
  • 57. www.syngenta-crop.co.uk/brassica-alert.aspx Syngenta CropSyngenta Crop Protection UK LtdProtection UK Ltd Growers and agronomists already registered on the Syngenta website will automatically have free access to Brassica Alert
  • 58. AgrometeorologicalAgrometeorological MonitoringMonitoring and Forecasts for Pest andand Forecasts for Pest and Disease ControlDisease Control Simone Orlandini Department of Plant, Soil and Environmental Science University of Florence International Workshop on Addressing the Livelihood Crisis of Farmers Belo Horizonte, Brazil, 12-14 July 2010 Thank you for your attention!!! Thank you for your attention!!!