Based on the given task and feature, we need to analyze the relationship between the feature "Season" and the target variable, which is the grain yield of a soybean cultivar.

To analyze the relationship, we need to understand how different seasons might affect the grain yield. Depending on the region and specific conditions, the impact of seasons can vary. However, generally speaking, there are some known patterns:

- In regions with a distinct winter season, soybeans are usually grown during the summer months (e.g., May to September), which can be considered as Season 1. These months generally have higher temperatures and longer daylight hours, which are optimal conditions for soybean growth. Therefore, a higher grain yield could be expected for Season 1 in such regions.

- In regions with a mild climate or without a distinct winter season, soybeans can be grown throughout the year or during different seasons. If the cultivar has specific adaptations for different seasons, then the grain yield may vary accordingly.

Based on these observations, we can determine the appropriate ranges of values for the feature "Season":

- Season 1 can be represented by values between 1.0 and 1.4 (inclusive), where 1.0 corresponds to the start of the summer growing season and 1.4 corresponds to the end of the summer growing season.

- Season 2 can be represented by values between 2.0 and 2.4 (inclusive), where 2.0 corresponds to the start of the secondary growing season (if applicable) and 2.4 corresponds to the end of the secondary growing season (if applicable).

After analyzing the relationship between the feature and the task, we can create the dictionary detailing the relationship between different season values and the target classes 'low' and 'high':

```json
{
	"low": [1.1, 1.2, 1.3, 2.1, 2.2],  
	"high": [1.0, 1.4, 2.0, 2.3, 2.4]
}
```

These lists represent typical values of the feature "Season" for the target classes 'low' and 'high' respectively. These values are based on the analysis of the relationship between the feature and the task. Please note that these values are just examples and may vary depending on specific conditions and requirements.