Based on my prior knowledge, the feature "Season" is a numeric variable that represents the season in which the soybean cultivar is grown. In order to determine the appropriate ranges of values for this feature, I would need more information about the specific context or location in which these soybeans are being grown. However, for the purpose of this analysis, I will assume that season is represented as follows:
- 1: Spring
- 2: Summer

To analyze the relationship between the feature "Season" and the task of predicting grain yield (low or high), I will examine the historical data or any available information about soybean cultivars grown in different seasons. This analysis will help me identify typical values of Season associated with low and high grain yields.

Based on this analysis, I will create a dictionary with the appropriate float values for Season in each target class ('low' and 'high').

```json
{
	"low": [1.0, 1.0, 1.0, 1.0, 1.0],  
	"high": [2.0, 2.0, 2.0, 2.0, 2.0]  
}
```

Please note that the list of values for each target class is just a placeholder and should be replaced with actual values from the analysis.