Based on prior knowledge, we can analyze the relationship between the Season feature and the grain yield of the soybean cultivar. Here are the steps to conduct the analysis:

1. Gather data: Collect a dataset that includes the Season feature and the corresponding grain yield values for the soybean cultivar.

2. Exploratory Data Analysis: Analyze the distribution of the target variable (grain yield) across different values of the Season feature. Calculate summary statistics such as mean, median, and standard deviation for grain yield values associated with each Season value.

3. Visualize the relationship: Create visualizations such as scatter plots or box plots to visualize the relationship between the Season feature and grain yield. Plot grain yield values on the y-axis and Season values on the x-axis.

4. Statistical analysis: Perform statistical tests, such as t-tests or ANOVA, to determine if there is a significant difference in grain yield between different values of the Season feature.

Based on the analysis, we can create a dictionary with the specific details. Here's an example:

```json
{
	"low": [1.1, 1.2, 1.3, 1.4, 1.5],  
	"high": [2.1, 2.2, 2.3, 2.4, 2.5]
}
```

Note: The values in the dictionary are just placeholders. The actual values should be based on the analysis conducted using the dataset.