Based on the given feature description, we can analyze the relationship between the "Cultivar" and the task of predicting "grain yield" (low or high). However, we do not have any direct information about the grain yield of each cultivar. So, we need to make some assumptions or gather additional data to make a more accurate analysis.

Since we don't have specific information on the relationship between the cultivar and grain yield, we will analyze the relationship between the "Cultivar" and the "Seeds per meter/linear" feature. Assuming that higher seed density could potentially lead to higher grain yield, we might expect the cultivars with higher "Seeds per meter/linear" values to have a higher grain yield.

Based on this assumption, we can now create the requested dictionary:

```json
{
	"low": ["FTR 4288 IPRO", "M 8644 IPRO", "FTR 4280 IPRO", "LYNDA IPRO", "ELISA IPRO"],
	"high": ["NK 8770 IPRO", "NK 8100 IPRO", "NK 7777 IPRO", "NEO 760 CE", "74K75RSF CE", "96R29 IPRO"]
}
```

Please note that this analysis is based on the assumption made about the relationship between "Seeds per meter/linear" and grain yield. Without more information or data, a more accurate analysis cannot be performed.

Furthermore, the "Cultivar" values are listed as strings and included in the dictionary in the format requested.