a yield gap indicator for rice cold damages: application to the mars database r. confalonieri – a...

A yield gap indicator for rice cold damages:

application to the MARS database

R. Confalonieri – A yield gap indicator for rice cold damages - Bologna, 15 June 2005

Roberto Confalonieri, Fabio Micale, Giampiero [email protected]

Court of AuditorsCourt of Auditors

Economic and Social CommitteeEconomic and

Social Committee

Committee of the Regions

Committee of the Regions

Council of Ministers

Council of Ministers

European ParliamentEuropean Parliament

EuropeanCommissionEuropean

CommissionCourt of Justice

Court of Justice

IPSCIPSC

Commissioner for ResearchCommissioner for Research

EIEI IESIES ITUITUIRMMIRMM IPTSIPTSIHCPIHCP

DG

ENTR

DG

ENV

DG

RTD

DG

INFSO JRC

DG

SANCOEUROSTAT

DG RELEX

ECHO

DG

AGRI

AGRIFISH Unit (MARS STAT)

AGRIFISH Unit (MARS STAT)

DG

MARS-STAT section in EC Context


Mars Crops YieldMars Crops YieldForecasting SystemForecasting System

Met

eoro

log

ical

Met

eoro

log

ical

Mo

nit

ori

ng

Mo

nit

ori

ng

Cro

p M

od

el

Cro

p M

od

el

Sta

tisti

cal

Sta

tisti

cal

Scen

ari

os A

naly

sis

Scen

ari

os A

naly

sis

Veg

etat

ion

Veg

etat

ion

Mo

nit

ori

ng

Mo

nit

ori

ng


EC crop yield forecasting system


Calibration of WOFOST for rice.1(Confalonieri and Bocchi, 2005. European Journal of Agronomy. Paper in press)

Calibration Validation

JE 2 2JM 3 4I 2 2

Number of datasetsGroup of varieties

3 groups of rice varieties:

Japonica type early JE

medium late JM

Indica type I


Calibration of WOFOST for rice.2

y = 1.0292x - 0.0218

R2 = 0.9906

0

5

10

15

20

0 5 10 15 20

measured (tAGB ha-1)

sim

ula

ted

(tA

GB

ha-1

)

Validation results - an example: JE varieties

Calibration results – an example: JM varieties

0

4

8

12

16

10/6 9/7 7/8 5/9 4/10

Date

Abo

vegr

ound

bio

mas

s (t

AG

B h

a-1)

measured

CropSyst

WOFOST


3

3.5

4

4.5

5

5.5

6

6.5

7

1975 1980 1985 1990 1995 2000 2005

Years

Yie

ld (

t h

a-1)

Official

Simulated

Hp: Correspondence of model overestimations and years where high sterility verified

High sterility Low sterility



After the calibration of crop model parameters, WOFOST was generally able to accurately simulate rice growth and development

but for some years,we noticed significant overestimation.

During these years, particular meteorological conditions occurred:

Cold air irruptionsduring the pre-flowering period


Cold air irruptions in Northern Italy

Although the summer presents typical Mediterranean features, the proximity to the arctic area, may sometimes expose to summer

cold air irruptions able to influence the young panicle development

The induced spikelet sterility may, in some cases, reach values between 35 - 50% depending on the different varieties sensitivity.

They do not cause higher sterility percentages because of their duration: usually no more than 2-3 days


Cold air irruptions in Northern ItalyThe last important episode occurred on 12 July 2000

minimum air temperature = 7-8°C (sterility = 25-50%)


Cold air irruptions in Northern Italy

The frequency is about 1 event every 5-6 years

(minimum air temperature during the period 1976-2001)

8

10

12

14

16

18

20

22

24

26

10-lug 14-lug 18-lug 22-lug 26-lug 30-lug 03-ago 07-ago 11-ago

Date

Min

imu

m d

aily

tem

per

atu

re (

°C)


At the moment, simulation models...

Actually crop growth models used for rice simulations do not consider yield losses caused by cold damages during the pre-flowering period and this may lead, in some cases, to enormous yield overestimations.

In some years (when particular meteorological conditions occur), models have to be considered inadequate tools.

Crop modellers are working to improve the simulation of physiological processes which are already rather well simulated but at the moment they are not including in their models processes which have a big influence on yield and which are still considered unrelated to crop simulators.



…WARM


In this presentation

•WARM features and peculiarities will be briefly exposed

•Simulation of the yield gap caused by cold air irruptions during the pre-flowering period for:

•4 years (1991, 1993, 1994, 2000)

•11 grids (50×50 km) north Italian

•Sowing date: 27 April

•High sensitive rice variety

WARM

Crop growth model

The MARS database

TRIS(floodwater effect on T)

STEFI(spikelet sterility

model)???

T.RI.S.(Confalonieri et al., 2005. Ecological Modelling, 183, 269-280)

TRIS is a mechanistic model funded on the resolution of the energy balance equation adopting as storage term the heat

accumulation into the water.

It needs as input only maximum and minimum air daily temperatures. If other data (e.g. global solar radiation) are

available, the model can use measured values instead of estimated ones.

It computes water temperature and 10 series of air temperatures (one for each 10cm air layer starting from the water surface)


11-20 May

10

15

20

25

30

35

40

Wa

ter

tem

pe

ratu

re (

°C)

11-20 June

10

15

20

25

30

35

40

Wa

ter

tem

pe

ratu

re (

°C)

11-20 July

10

15

20

25

30

35

40

Wa

ter

tem

pe

ratu

re (

°C)

11-20 August

10

15

20

25

30

35

40

Wa

ter

tem

pe

ratu

re (

°C)

T.RI.S. – some results

Surface water temperature for the second decade of May, June, July and August(Opera (MI), 2002)


The model for sterility induced by low temperatures is based on two principles:

•daily stress inducing sterility is computed adding hourly differences between a threshold temperature and hourly temperatures simulated by TRIS at the height of the developing panicle

•total stress is obtained by adding daily values weighted by a factor (bell factor) which represents the different plant sensitivity during the panicle initiation – heading period

STE.FI. – a model for spikelet sterility


headDay

headDayi

GDDGDD

hhid

i

eTTSterility22

224

1,

2

211

2

1

bell factor...

STE.FI. – a model for spikelet sterility

hourly stresses


0

0.2

0.4

0.6

0.8

1

497 597 697 797 897 997 1097

Developing stage (GDD)

bel

l fa

cto

r

high bell factor

low bell factor

STE.FI. – the bell factor

γ

δ is used to fix the maximum value to 1

γ


CGMS WARM - Results.1(high observed sterility: 1993, 2000)

Grid50_etrs.shp00 - 0.10.1 - 0.20.2 - 0.30.3 - 0.40.4 - 0.50.5 - 1

Nuts0_etrs.shpNuts2_etrs.shp

N

EW

S

1993

Grid50_etrs.shp00 - 0.10.1 - 0.20.2 - 0.30.3 - 0.40.4 - 0.50.5 - 1


N

EW

S

2000



CGMS WARM - Results.2(low observed sterility: 1991, 1994)

Grid50_etrs.shp00 - 0.10.1 - 0.20.2 - 0.30.3 - 0.40.4 - 0.50.5 - 1


N

EW

S

20021994

Grid50_etrs.shp00.001 - 0.10.1 - 0.20.2 - 0.30.3 - 0.40.4 - 0.50.5 - 1


N

EW

S

19971991


Conclusions:

The yield gap computed basing on the spikelet sterility and on the influence of floodwater on vertical thermal profile has shown to be a powerful tool for the improvement of the precision of rice yield

forecasts

All the aspects with a high influence on yield must be taken into account and this is why other modules are currently under

development (e.g. for blast)

It is necessary that all the developed modules are compatible with the MARS database (only the already available input variable

collected at similar spatial scale)

a yield gap indicator for rice cold damages: application to the mars database r. confalonieri – a...

Documents

rice cold damages bologna

yield gap indicator

rice growth

groups of rice varieties

roberto confalonieri

years minimum air temperature

je varieties calibration

c sterility