Modeling longevity during storage
You have learned so far that although we cannot predict the longevity of an individual seed, when you look at populations of seeds, repeatable patterns start to emerge. You have also learned that moisture content and temperature are important to longevity of seeds in storage. These factors can be analyzed and quantified, in ways that allow us to make mathematical models which help us to predict the longevity of seeds in storage.
In the next section, you will explore a tool that performs this type of calculation. Although we will not be going into the statistical formulae in depth, they rely on the existence of certain viability constants that researchers have divined over the years. These are defined in Table 2 (below).
| Term | Meaning |
| KE | The expected longevity of a population of seeds at 1% moisture content and 0°C. This is a useful concept, because inherent longevity varies between species, and enables us to make comparisons between species.
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| CW | Another species-specific constant, which describes the effect of making changes to moisture content during storage. This too varies between species, allowing comparisons to be made.
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| CH and CQ | These two constants together describe the effect of changes in temperature of storage on seed longevity as a quadratic relationship. Unlike KE and CW, these constants have the same ‘universal’ values that do not vary between species.
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Table 2: seed viability constants
You are now ready to use these viability constants, and other data, and make predictions about seed behavior in storage.
Manipulating longevity during storage