To analyze the relationship between the feature "Number of grains per plant (NGL)" and the target variable "grain yield of soybean cultivar", we would expect a positive correlation between NGL and grain yield. This means that as the number of grains per plant increases, we would anticipate a higher grain yield.

Based on expertise and prior knowledge, we can assume that a "low" grain yield would typically correspond to a lower range of NGL values, while a "high" grain yield would correspond to a higher range of NGL values.

Now, let's create a dictionary with typical NGL values based on the target classes "low" and "high":

```json
{
	"low": [4.5, 5.2, 6.1, 6.8, 7.3],
	"high": [11.2, 12.5, 13.9, 15.2, 16.7]
}
```

Note that these values are for illustration purposes and may not accurately reflect the actual distribution of NGL values for a given soybean cultivar.