Upload
phunglien
View
213
Download
0
Embed Size (px)
Citation preview
A preliminary analysis of the official yield statistics, collated
by FAO, shows high variability among the countries where
Sentinel sites are located (Figure 5). In spite of the reliability
of the statistics, the values depict the challenges that the
trans-disciplinary team will face when modeling potential
yield for such diverse conditions.
Figure 5. National average potato yield per country (FAO)
AgMIP POTATO PILOT: A summary of progress made
Bruno Condori1, Carolina Barreda1, David Fleisher2, and Roberto Quiroz1
The potato cropping systems are quite variable spanning
from rain-fed low input conditions to high-tech precision
agriculture. Among those conditions five sentinel sites have
been selected in Bolivia, Peru, Burundi, Denmark and USA
(Figure 4). A preliminary analysis of the yield statistics
around sentinel sites - 10 to 100 tons of fresh tubers per
hectare – summarizes the challenges that the trans-
disciplinary team will face.
Figure 4. Agro-climatic characteristics and geographic coordinates of Sentinel sites.
Light green panel highlights the crop cycle period.
Experimental groups confirmed.
Modeling groups confirmed.
Climate data for every sentinel site provided by Alex
Ruane.
Two additional potential Southern Latitude sentinel sites
under negotiation: Argentina and New Zealand.
The potato crop (Solanum sp.) has a significant social and
economic importance for many developing and developed
countries. This crop is dispersed around the world,
growing in very high contrasting environments: from 0 to
4000 meters above sea level, latitudes from 65° to -40°,
and photoperiods ranging from 12 to 15 hours (Figure 1).
Figure 1. Reliable crop growing days (RCGD) and photoperiod for potato crop
The AgMIP potato is a new pilot of the international effort
that links the climate, crop, and economic modeling
communities with cutting-edge information technology to
produce improved crop and economic models and the
next generation of climate impact projections for the
agricultural sector (Rosenzweig et. al., 2013). So far, 28
researchers and 10 potato modeling groups (Figure 3)
have agreed to become part of this initiative.
Results
Materials and Methods
Forthcoming
Introduction
1 International Potato Center. Lima, Peru. 2 United States Department of Agriculture – Agricultural Research Service, Beltsville, MD, USA.
United Statesof America
Denmark
BoliviaPeru
Burundi
Furthermore, a striking difference with other crops of
global importance is the variation in the cultivated ploidy
(2x=24, 3x=36, 4x=48 and 5x=60) in Figure 2, conferring
the crop a wide adaptation range and thus adding
complexity to the assessment of the response to climate
variability and change.
Figure 2. Morphological contrast due to the ploidy of the potatoes
Climate change factors, including increased CO2, warmer
mean temperatures, and higher likelihoods of extreme
temperature and rainfall fluctuations, will profoundly
influence potato production characteristics.
CIP, 2006. Catalogo de variedades de papa nativa de Huancavelica.
FAO, 2013. National statistics online at http://faostat.fao.org/site/567/default.aspx#ancor
Rosenzweig et. al., 2013. The Agricultural Model Intercomparison and Improvement
Project (AgMIP): Protocols and pilot studies. Agricultural and Forest Meteorology,
Volume 170, 15 March 2013, Pages 166–182.
The European Cultivated Potato Database online at http://www.europotato.org/
References
S. curtilobum 2n=5x=60 “Yuraq Siri”
S.tuberosum ssp. tuberosum 2n=4x=48 “Desiree”
S. chaucha 2n=3x=36 “Peruanita Wayru”
S. Stenotomum 2n=2x=24 “Yuraq Tumbay"
Figure 3. Models involved in the Potato pilot modelling effort
0
50
100
150
200
250
300
350
400
450
-4
0
4
8
12
16
20
24
28
32
36
40
J F M A M J J A S O N D
Ra
in (
mm
)
Te
mp
era
ture
(°C
)
Rain Tmin Tmax
0
50
100
150
200
250
300
350
400
450
-4
0
4
8
12
16
20
24
28
32
36
40
J F M A M J J A S O N D
Ra
in (
mm
)
Tem
pe
ratu
re (
°C)
Rain Tmin Tmax
0
50
100
150
200
250
300
350
400
450
-4
0
4
8
12
16
20
24
28
32
36
40
J F M A M J J A S O N D
Ra
in (
mm
)
Te
mp
era
ture
(°C
)
Rain Tmin Tmax
0
50
100
150
200
250
300
350
400
450
-4
0
4
8
12
16
20
24
28
32
36
40
J F M A M J J A S O N D
Rain
(m
m)
Tem
pera
ture
(°C
)
Rain Tmin Tmax
0
50
100
150
200
250
300
350
400
450
-4
0
4
8
12
16
20
24
28
32
36
40
J F M A M J J A S O N D
Ra
in (
mm
)
Te
mp
era
ture
(°C
)
Rain Tmin Tmax
Bolivia
Chinoli
La -19.63
Lo -65.37
Al 3292
USA
Washington
La 45.90
Lo -119.50
Al 90
Dinamarca
Jyndevad
La 54.90
Lo 9.13
Al 15
Peru
La Molina
La -12.08
Lo -76.95
Al 323
Burundi
Gisozi
La -3.57
Lo 29.68
Al 2033