Abstract
A model for cotton seedling emergence (MaGi) based on malate synthase kinetics was evaluated. Cotton seeds were planted through the early spring and into typical planting times for the areas. Soil temperatures at seed depth were used as inputs into MaGi and a commonly used seedling emergence model based on heat unit accumulation (DD60). Time to 50% emergence was calculated and compared with predicted emergence using MaGi and DD60. MaGi yielded predictive capability without the need to resort to lengthy experimentation required by traditional methods. The results suggest that a physiological or semi-empirical approach incorporating both enzyme kinetics and whole plant temperature responses would be useful for rapidly constructing seedling emergence models.
Highlights
The environment influences seedling emergence through biotic and abiotic factors
The green horizontal lines above the soil temperature data represent the time to 50% emergence of individual cohorts of seeds
Over the duration of the experiment, that is, from the planting of the first cohort (DOY 64) to the observed 50% emergence of the final cohort (DOY 147) soil temperatures at planting depth ranged from −0.5 ̊ to 37.5 ̊
Summary
The environment influences seedling emergence through biotic and abiotic factors. The effects of biotic factors on seedling emergence vary greatly from site to site and are very difficult to predict with certainty, other than to make broad generalizations; for example, the observation that when the soil is cold and wet for an extended period of time seeds succumb to fungal or bacterial infection. The effects of abiotic, or physical factors are much more predictable. The effects of abiotic factors such as soil temperature and moisture on developmental seedling processes have been empirically studied for nearly a century. Such studies have resulted in fairly robust predictive models based upon empirically derived data sets.
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