welcome agenda introductions & brief overview of the objectives maize physiologist’s...
TRANSCRIPT
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WELCOME
Agenda•Introductions & brief overview of the objectives
•Maize physiologist’s understanding of phenology
•Maize modeling – descriptions of phenology routines
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1. To discuss the current ‘state-of-the-art’ knowledge on the physiological mechanisms controlling maize phenology.
2. To identify how various maize models quantify these mechanisms, and discuss their consistency with the physiological understanding identified above,
and possible rationale for inconsistencies.
3. To test different methodologies used to simulate phenology across a range of environmental conditions
Objectives of our meeting
(Presentations by Thijs and Greg)
(Presentations by modeling groups)
(Will be discussed)
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Objective 1To discuss the current ‘state-of-the-art’ knowledge on the physiological mechanisms controlling maize
phenology.
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Phenology
Phenology constitutes the framework within which all
processes that are simulated in a crop model are
operating.
Consequently, simulation of all crop processes are
directly dependent on an accurate estimation of
phenology .
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planting silking maturity
Phenology
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Tollenaar et al. (1979)
Lehenbauer, 1914 (seedling elongation)
Blacklaw, 1972 (radicle elongation)
Parent et al., 2010 (leaf expansion, cell division)
Tollenaar et al., 1979
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4th tip
5th tip
6th tip
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Relationship between leaf tips (x-axis) and leaf collars (y-
axis) [Muldoon et al., 1984]
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www.biochemsoctrans.org Biochem. Soc. Trans. (2005) 33, 1502-1506
Apex
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J. Colasanti, U
niv. of Guelph
Tassel Initiation - TI
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Leaf tip stage
Lejeune and Bernier, 1996
Leaf primordia (Y=1.95+1.84 × X) vs. leaf-tip stage
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Anthesis
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Anthesis
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Silking
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Half Milk Line
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Physiological maturity – Black Layer
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Modeling Phenology
• Temperature effects on duration of total life cycle and component phases
• Photoperiod effects on duration of total life cycle and component phases
• Genotypic effects on duration total life cycle and component phases
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CERES-Maize, IXIM, and Hybrid-Maize[GDD(34,8)]
0 5 10 15 20 25 30 35 40 45 500
5
10
15
20
25
30
Mean daily temperature (oC)
Deg
ree
day
s
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MAIS [Pre-silking phase]
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Beta function (Yan and Hunt , 1999)
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GTI vs. GDD(30,10) [Pre-silking phase]
GDD(30,10)
GTI
(Stew
art et al., 1998)
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GTI
GDD(30,10)
GTI vs. GDD(30,10) [Post-silking phase](S
tewart et al., 1998)
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Modeling Phenology
• Temperature effects on duration of total life cycle and component phases
• Photoperiod effects on duration of total life cycle and component phases
• Genotypic effects on duration total life cycle and component phases
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Leaf primordia (Y=1.95+1.84 × X) vs. leaf-tip stage
Leaf tip stage
Photoperiod effect on leaf number
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Photoperiod-sensitive phase for leaf number
Tollenaar and Hunter, 1983
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Photoperiod-sensitive phase for leaf number
Tollenaar and Hunter, 1983
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Reciprocal transfer experiments Summary
• End of juvenile phase: 4-leaftip stage• End of photoperiod /temperature sensitive period for
leaf number: TI• TI: ~ 0.5 * Final Leaf no.
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Issues in photoperiod response in maize
• How can we quickly characterize photoperiod sensitivity of maize hybrids?
• Is maize influenced by photoperiod during ‘other’ phases of development (e.g., grain-filling period), and if so, how?
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Modeling Phenology
• Temperature effects on duration of total life cycle and component phases
• Photoperiod effects on duration of total life cycle and component phases
• Genotypic effects on duration total life cycle and component phases
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Relationship between Relative Maturity and Accumulated Thermal Units using Different Methodologies
Phase GDD 30, 10 TLU GTI
--------------------- R2 -------------------
Planting to Anthesis 0.55 0.65 0.72
Planting to Black layer 0.26 0.39 0.78
Anthesis to Black layer 0.10 0.16 0.58
Hybrids (>1,100) representing Relative Maturities ranging from RM 75- RM125 grown at a single location in two years (approx. 550 hybrids tested each year)
Tollenaar and Kumudini, unpublished
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Temperature and Photoperiod Responses in Tropical Maize Germplasm
Greg EdmeadesJune 5, 2012
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Tropical environment, tropical adaptation
Between 30 oN or S of the equator Adaptation zones are
Lowland tropical (LT) (< 1000 masl) Mid-altitude tropical (MAT) (1000-1800 masl) Highland tropical (HT) (> 1800 masl) Temperate (>30oN or S or equator, 0-1500 masl) Differentiation on disease pressures (LT, MAT)
vs. temperature adaptation (HT vs. the others) Natural daylengths vary from 12.3 hrs to
14.3 hours. Tropical maize has evolved with daylength
variation at TI from 13-14.5 hours, over a range of altitudes (temperatures).
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No G*temperature interaction for CER
Maize carbon exchange rate asaffected by adaptation and
environment
Lowland Subtropical Highland0
10
20
30
40
50AdaptationLSD0.05 ns * ns
Environment
CE
R (
um
olC
O2 m
-2 s
-1)
Source: Lafitte & Edmeades (1997) Field Crops Res. 49:231-247
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G*temperature interaction for partitioning
Harvest indices of two highlandand two lowland tropical maizevarieties vs. mean temperature
15.0 17.5 20.0 22.5 25.0 27.5 30.00.0
0.1
0.2
0.3
0.4
0.5Lowland tropicalHighland
Temperature (deg C)
Har
vest
ind
ex (
g g
-1)
Source: Lafitte & Edmeades (1997) Field Crops Res. 49:231-247
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Allelic contribution to thermal adaptation
Correlation between proportionof highland alleles in a (HL xLT) cross and biomass, vs.
temperature
15 20 25
-0.6
-0.4
-0.2
0.0
0.2
0.4
Source: Jiang et al. (1999) Theor. Appl. Genet. 99:1106-1119
Temperature (deg C)
Co
rrel
atio
n
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Thermal adaptation and biomass production in the tropics
Highland (left) vs. temperate (right) sown same date in Toluca
2,650 masl, mean temperature during the growing season 13 oC
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Variation for developmental response to temperature
Rate of development to TI vs.temperature in highland,
temperate and lowland maize
10 15 20 25 30 35 400.00
0.25
0.50
0.75LowlandHighlandTemperate
Temperature (deg C)
Rat
e o
f p
rog
ress
to
tas
sel i
nit
iati
on
(1/
d x
10)
Source: Ellis et al. (1992) Crop Sci 32: 1225-1232
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Generalized response of leaf number to photoperiod in maize
Response of leaf number tophotoperiod around tassel
initiation
10 12 14 16 18 2015
20
25
30LowlandHighlandTemperate
Pc
Pmax
a/b = sensitivitya
b
Adaptation
Source: Edmeades et al. (1994) Agron Abstr. 86
Photoperiod (hrs)
To
tal l
eaf
nu
mb
er
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Photoperiod sensitivity in landrace Pepitilla
Photoperiods
(from left)
• 13 hr
• 14.5 hr
• 16 hr
• 17.5 hr
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Photoperiod sensitivity reduces grain yield significantly
Grain yield vs. photoperiod forfour hybrids differing in
adaptation
10.0 12.5 15.0 17.5 20.00.0
2.5
5.0
7.5
10.0LowlandMidaltitudeHighlandTemperate
Adaptation
Source: Edmeades 1995 (unpublished data: TL95A-1665)Photoperiod, Hybrid and Photoperiod x Hybrid effects sig (P< 0.01)
Photoperiod (hrs)
Gra
in y
ield
(to
n/h
a)
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Photoperiod sensitivity varies with adaptation
Photoperiod sensitivity(summer) of maize vs.
adaptation class
LT MAT HL TE0
1
2
3LowlandMid-altitudeHighlandTemperate
Adaptation
N=15 N=11
N=7
N=7
Sen
siti
vity
(le
aves
hr-1
)
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Genetics of photoperiod sensitivity
Cross between a highly sensitive lowland tropical Tuxpeño inbred CML9 and a virtually insensitive temperate line A632Ht from Minnesota
Advanced to 236 RILs by selfing to F7 Evaluated under natural daylengths (13.5 hrs
summer, 11.7 hrs winter) and extended daylengths (17 hrs, both seasons) in Tlaltizapán, Mexico (940 masl; 19oN)
Measures of sensitivity: final leaf number; change in flowering date; anthesis-silking interval
Typical climate during the growing season
Season Tmax Tmin PP at TI
Summer 33 oC 20 oC 13.4 hr
Winter 32 oC 12 oC 11.7 hr
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Photoperiod sensitivity varies with adaptation and with temperature
regime
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Photoperiod sensitivity extends beyond TI
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Photoperiod sensitivity affects ASI
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How important are these responses?
For production impact importance relatively small: Highland tropics account for 2% global
production mid-altitude tropics 8%, lowland tropics 10% but temperate around 80%.
Introgression of temperate germplasm into tropical backgrounds is occurring quite rapidly, bring photoperiod insensitivity alleles.
For effective mining of alleles adequate phenotyping is essential CIMMYT’s maize Germplasm Bank has
25,000 accessions; 22% highland; 43% midaltitude; 35% lowland tropical
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Model Name Institute/company
CERES MAIZEBoote, Ken Univ. of Florida, Gainesville, FL.Lizaso, Jon Univ. of Madrid, Madrid, Spain
HYBRID MAIZE Yang, Haishun Monsanto Co., St. Louis, MO
EPIC Kiniry, Jim USDA-ARS, Temple, TX
APSIM Hammer, Graeme Univ. of Queensland, Brisbane, Australia.
CropSyst Stöckle, Claudio Washington State Univ, Pullman, WA.
MONICA Nendel, Claas Leibniz, Germanny
MAIZESIM Timlin, Dennis USDA-ARS, Beltsville, MD
Objective 2To identify how various maize models quantify these mechanisms, and discuss their consistency with the physiological understanding identified above, and possible rationale for inconsistencies.
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Objective 3To test different methodologies used to simulate phenology across a range of environmental conditions.
1. Why? Ultimately, the usefulness of a specific methodology is indicated by how well it reflects observed outcomes. How well do the current methodologies perform and how can we improve them?
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Objective 3We need a number of datasets to evaluate the methodologies, specifically, datasets that capture phenology in terms of (1) thermal, (2) photoperiod, and (3) genotype effects.
For instance:• Different thermal regimes for same genotype(s) and
photoperiod.• Different photoperiods for same thermal regime and
genotype(s).• Different genotypes for (a) same thermal regime and
photoperiod, and (b) different thermal regimes and different photoperiods (i.e., G x T x P).
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Objective 3
2. Identify Data Sets for testing:
• What minimum data to include (e.g. ,daily Max/Min temperature, planting date, latitude, anthesis/silking date), and what format?
• Who can contribute data - 6 sets identified so far.• When available?• How data will be shared?
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Objective 3
3. Outcomes:
• Next meeting, discuss results• Writing paper(s) on outcomes for thermal,
photoperiod and genotype responses