Agriculture Reference
In-Depth Information
The simplest level of yield simulation assumes that economic yield is a constant
fraction of total aboveground biomass at maturity, known as the harvest index (HI).
This index can range from 0.40 to 0.55 for corn. Both the EPIC (Williams et al.
1989) and CROPSYS (Stockle et al. 1994) models are based on HI calculations.
Some models estimate corn yields using a constant rate of change in HI after silk-
ing (Muchow et al. 1990, Muchow and Sinclair 1991, Sinclair and Muchow 1995).
In this case, the rate of change of HI for corn is 0.015 d −1 during the entire period
of kernel growth. The accuracy of yield simulations by models based on the HI
concept depends on the accuracy of simulating total aboveground biomass as well
as the stability of HI. Such models are of more limited value in situations where the
crop yields are low because of water deficits that constrain HI.
Kernel number (KN) is an important predictor of yield in most cereal crops
(Evans 1993), and reflects the irreversible effects of water deficit and nutrient defi-
ciencies that occur around the time of anthesis. Crop models using the KN concept
are based on two approaches. A simple approach calculates KN from biomass at
anthesis, while a more complex one estimates KN from biomass production during
a critical period (around silking in the case of corn). SALUS, for example, uses the
simulated stem weight at anthesis to simulate grain number.
The Systems Approach to Land Use Sustainability Model
The Systems Approach to Land Use Sustainability (SALUS) (Basso et  al. 2006,
2010)  is similar to the DSSAT family of models but is designed to simulate not
only yields of crops in rotation, but also soil, water and nutrient dynamics as a func-
tion of management strategies over multiple years (Fig. 10.1). SALUS accounts
for the effects of rotations, planting dates, plant populations, irrigation and fertil-
izer applications, and tillage practices. The model simulates daily plant growth and
soil processes on a daily time step during the growing season and fallow periods.
SALUS contains (1)  crop growth modules, (2)  SOM and nutrient cycling mod-
ules, and (3) soil water balance and temperature modules. The model simulates the
effects of climate and management on the water balance, SOM, N and P dynamics,
heat balance, plant growth, and plant development. Within the water balance, sur-
face runoff, infiltration, surface evaporation, saturated and unsaturated soil water
flow, drainage, root water uptake, soil evaporation, and transpiration are simulated.
Soil organic matter decomposition, along with N mineralization and formation of
ammonium and nitrate, N immobilization, and gaseous N losses are also simulated.
Crop development in the SALUS model is based on thermal time calculations
modified by day length and vernalization. Potential crop growth depends on inter-
cepted light using solar radiation data and simulated LAI, and is reduced by water
or nitrogen limitations. The crop growth modules in SALUS are derived from the
CERES model originally developed for single-year and monoculture simulations
(Ritchie 1998, Ritchie et al. 1998). Phasic development is controlled by tempera-
ture and photoperiod and is governed by variety-specific genetic coefficients. The
main external inputs required for the crop growth simulations are the genetic coef-
ficients and climate data (daily solar radiation, precipitation, and air temperature).
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