```json
{
  "sym_variables": [
    ("x0", "coleus"),
    ("x1", "roses")
  ],
  "objective_function": "2*x0 + 9*x1",
  "constraints": [
    "0.82*x0 + 1.29*x1 >= 43",
    "-8*x0 + 8*x1 >= 0",
    "0.82*x0 + 1.29*x1 <= 117"
  ]
}
```

```python
import gurobipy as gp
from gurobipy import GRB

# Create a new model
m = gp.Model("growth_optimization")

# Create variables
coleus = m.addVar(vtype=GRB.INTEGER, name="coleus")
roses = m.addVar(vtype=GRB.INTEGER, name="roses")

# Set objective function
m.setObjective(2 * coleus + 9 * roses, GRB.MINIMIZE)

# Add constraints
m.addConstr(0.82 * coleus + 1.29 * roses >= 43, "growth_min")
m.addConstr(-8 * coleus + 8 * roses >= 0, "coleus_roses_ratio")
m.addConstr(0.82 * coleus + 1.29 * roses <= 117, "growth_max")


# Optimize model
m.optimize()

# Check for infeasibility
if m.status == GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    # Print optimal solution
    print("Optimal solution:")
    print(f"  coleus: {coleus.x}")
    print(f"  roses: {roses.x}")
    print(f"  Objective value: {m.objVal}")

```
