Based on prior knowledge, the number of grains per plant (NGL) can be a relevant feature for predicting the grain yield of a soybean cultivar. It is expected that a higher number of grains per plant would result in a higher grain yield, while a lower number of grains per plant would result in a lower grain yield.

To generate the dictionary with specific details, I will assume the following:

- For the "low" target class (indicating low grain yield), the NGL values would be in the lower range.
- For the "high" target class (indicating high grain yield), the NGL values would be in the higher range.

Let's create the dictionary:

```json
{
	"low": [10.2, 12.5, 9.8, 11.0, 11.9], 
	"high": [15.6, 16.2, 14.9, 17.3, 15.8]
}
```

Note: These values are just hypothetical examples to demonstrate the format of the output dictionary. In a real scenario, the values would be specific to the dataset and should be determined based on actual observations or expert knowledge.