Predicting germination response to temperature. I. Cardinal-temperature models and subpopulation-specific regression.
OBJECTIVE
The purpose of this study was to compare the relative accuracy of different thermal-germination models in predicting germination-time under constant-temperature conditions. Of specific interest was the assessment of shape assumptions associated with the cardinal-temperature germination model and probit distribution often used to distribute thermal coefficients among seed subpopulations.


METHODS
The seeds of four rangeland grass species were germinated over the constant-temperature range of 3-38 degrees C and monitored for subpopulation variability in germination-rate response. Subpopulation-specific germination rate was estimated as a function of temperature and residual model error for three variations of the cardinal-temperature model, non-linear regression and piece-wise linear regression. The data were used to test relative model fit under alternative assumptions regarding model shape.


RESULTS
In general, optimal model fit was obtained by limiting model-shape assumptions. All models were relatively accurate in the sub-optimal temperature range except in the 3 degrees C treatment where predicted germination times were in error by as much as 70 d for the cardinal-temperature models.


CONCLUSIONS
Germination model selection should be driven by research objectives. Cardinal-temperature models yield coefficients that can be directly compared for purposes of screening germplasm. Other model formulations, however, may be more accurate in predicting germination-time, especially at low temperatures where small errors in predicted rate can result in relatively large errors in germination time.
Hardegree
Stuart P
SP
USDA Agricultural Research Service, Northwest Watershed Research Center, 800 Park Blvd, Suite 105, Boise, ID 83712, USA. shardegr@nwrc.ars.usda.gov
D018525:Germination; D008954:Models, Biological; D012639:Seeds / Q000502:physiology; D013696:Temperature