Based on my prior knowledge, I can analyze the relationship between the feature "Season" and the task of predicting the grain yield of this soybean cultivar. 

Here is the analysis:

1. Low grain yield:
   - In general, low grain yield in soybean cultivars can occur in seasons with unfavorable conditions such as extreme temperatures or drought.
   - Possible values of the feature "Season" that may be associated with low grain yield could be 1.0, 1.5, 2.0, 2.5, and 3.0. These values represent early spring, late spring, early summer, mid-summer, and late summer, respectively.

2. High grain yield:
   - High grain yield in soybean cultivars is typically observed in seasons with optimal growing conditions, including moderate temperatures, adequate rainfall, and good soil fertility.
   - Possible values of the feature "Season" that may be associated with high grain yield could be 4.0, 4.5, 5.0, 5.5, and 6.0. These values represent early fall, late fall, early winter, mid-winter, and late winter, respectively.

Based on this analysis, here is the dictionary with the specified format:

```json
{
	"low": [1.0, 1.5, 2.0, 2.5, 3.0],
	"high": [4.0, 4.5, 5.0, 5.5, 6.0]
}
```

Please note that the specific values for each target class may vary depending on the specific dataset and context.