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Abstract:
"SHOOTGRO emphasizes the development and growth of the shoot apex of
small-grain cereals such as winter and spring wheat (Triticum aestivum
L.) and spring barley (Hordeum vulgare L.). To better incorporate the
variability typical in the field, up to six cohorts, or age classes, of
plants are followed using a daily time step. Within each median plant of a cohort, the
appearance of each tiller is simulated, and for each culm (main stem and tillers),
the phenological growth stage and appearance, growth, and senescence/abortion of
each leaf, internode, spikelet, floret, kernel, rachis, and chaff is simulated. The model
has been evaluated under conditions from the Great Plains, Pacific Northwest, South Africa, Italy, and England."
Source :
SHOOTGRO Home Page
"SHOOTGRO simulates and reports date of appearance, size, date of
senescence,
and frequency in the canopy of all above-ground parts of the small grain
modeled. Events are timed in terms of the phyllochron (the interval
between
appearance of successive leaves on a culm) in the model.
The algorithm reported by Baker et.al. (1980) is used to predict the
phyllochron based on the rate of change in daylength at the time of
seedling
emergence. Developmental and growth processes are limited by the
availability
of light, nitrogen, and water. The individual plants in the community
are
divided into as many as six cohorts (based on time of emergence). Use
of
cohorts (each have a different time of emergence and therefore somewhat
different
conditions during each developmental phase) allows the simulation to
reflect
the variation between plants seen in the field. In addition to growth
parameters, the model continuously reports crop development in three
commonly
used stages - Feekes, Zadoks-Chang-Konzak, and Haun.
[ ................. ]
Model purpose
To simulate development and growth of small grains (winter and spring
wheat
and spring barley) from easily obtained input and weather
data in
response to environmental factors (nitrogen, light, and water
availability)
based on accumulation of thermal time."
Source :
Joergensen S.E., B. Halling-Soerensen and S.N Nielsen (Edts.) 1996:
Handbook
of Environmental and Ecological Modelling. CRC Press Boca Raton et al.
672 pp.
The following Information on Submodels can be found on the
SHOOTGRO Home Page:
- Phenology submodel: The phenology submodel
simulates all shoot apex developmental events using a
modified growing degree-day (GDD) approach. Rather than
using a static GDD number for the interval between growth
stages, the number of phyllochrons (or number of leaves)
is used which is a number that changes with environmental
variables. Water and N stress also alters the number of
phyllochrons between growth stages. The growth stages
predicted for the median plant of up to six age classes
and each culm on the plant are germination, emergence,
tiller initiation, single ridge, double ridge, start of
internode elongation, terminal spikelet stage (or awn
initials formed for barley), jointing, flag leaf,
booting, heading, start and end of anthesis, and
physiological maturity.
- Tillering submodels: The appearance of each
morphologically named tiller on the median plant in a
cohort is simulated according to the main stem Haun stage
(= number of leaves), which is controlled by the
phyllochron (or rate of leaf appearance). The percentage
of each tiller that appears and aborts on plants of a
cohort are controlled by water, N, and light conditions.
Tiller growth is simulated by simulating the growth
(weight and length) of each internode, including
specifically the peduncle, each leaf, and the spike
(rachis, kernels, and chaff) as affected by water and N
stress.
- Leaf submodels: The appearance, growth (length,
width, area, weight, and N concentration), and senescence
of each leaf blade and sheath on each culm on each median
plant in a cohort are simulated. Growth and senescence
are affected by water and N stress. The appearance of
leaves is determined by the submodel that calculates the
phyllochron, or rate of leaf appearance. Nine different
equations that predict the phyllochron were evaluated to
determine which equation to use. Depending on the crop,
different equations work best.
- Spike development submodels: For each culm on each
median plant in a cohort, the initiation of each
spikelet, as well as the initiation, abortion, and
fertilization of each floret within the spikelet is
simulated; controlling factors are temperature, water and
N availability, and morphological location. Also, the
spike components of the rachis and chaff (glumes, paleas,
and lemmas) are simulated for each spike. The differences
in spike inflorescence structures between wheat and
barley (both 2- and 6-rowed barley) are simulated in the
model. Kernel growth is described under the Kernel Growth
Submodels section below.
- Kernel growth submodel: The duration of grain
filling is a curvilinear function of temperature and
water and N availability. The potential growth of an
individual kernel is dependent on the morphological
location of the kernel within the spikelet, spike, and
plant. The potential growth rate of the kernel is then
reduced when water or N stress exists.
II. Technical Information
II.1 Executables:
Operation System(s): DOS, UNIX
II.2 Source-code:
Programming language(s): standard FORTRAN 77
II.3 Manuals:
II.4 Data:
II. Technical Information
II.1 Executables:
Operating System(s): DOS, UNIX
II.2 Source-code:
Programming Language(s): standard FORTRAN 77
II.3 Manuals:
II.4 Data:
III. Mathematical Information
III.1 Mathematics
III.2 Quantities
III.2.1 Input
III.2.2 Output
IV. References
McMaster, G.S., and W.W. Wilhelm. 1997. Conservation compliance creditfor winter wheat fall biomass and implication for grain production. Journal of Soil and Water Conservation 52:000-000.
Wilhelm, W.W., and G.S. McMaster. 1996. Spikelet andfloret naming scheme for grasses with spike inflorescences. Crop Science36:000-000
McMaster, G.S. 1997. Phenology, development, and growthof the wheat (Triticum aestivum L.) Shoot apex: A review. Advances inAgronomy 59:63-118. or 58:000-000.
McMaster, G.S., and W.W. Wilhelm. 1995. Accuracy of equationspredicting the phyllochron of wheat. Crop Science 35:30-36.
McMaster, G.S., W.W. Wilhelm, and P.N.S. Bartling. 1994.Irrigation and culm contribution to yield and yield components of winterwheat. Agronomy Journal 86:1123-1127.
Harrell, D.M., Wilhelm, W.W., and McMaster, G.S., 1993. SCALES: Acomputer program to convert among three developmental stage scales for wheat.Agron, J. 85: 758-763.
McMaster, M., Klepper, S., Rickmann, B.,Wilhelm, W.W., and Willis, W.O.,1991.Simulation of above-ground vegetative development and growth ofunstressedwinter wheat. Ecol. Modelling 53: 189-204.
McMaster, G.S., Morgan, J.A., and Wilhelm, W.W., 1992. Simulating winterwheatspike development and growth. Agric. For. Metreol. 60: 193-220.
McMaster, G.S., Wilhelm, W.W., Morgan, J.A., 1992. Simulating winterwheat shoot apex phenology. J. Agric. Sci. Camb. 119: 1-12.
McMaster, G.S., and W.W. Wilhelm, 1997. Growing degree-days: One equation, two interpretations. Agric. For. Meteorol. 000:000-000.
McMaster, G.S. 1993. Another wheat (Triticum spp.) model? Progress and applications in crop modeling. Rivista di Agronomia 27:264-272.
FullList
V. Further information in the World-Wide-Web
VI. Additional remarks
Last review of this document by: Greg McMaster and T.Gabele : 24-Sep-1997 updated model author
Status of the document:
last modified by
Tobias Gabele Wed Aug 21 21:44:49 CEST 2002