```json
{
  "sym_variables": [
    ("x0", "hydrangeas"),
    ("x1", "tulips"),
    ("x2", "aloe vera"),
    ("x3", "decorative cabbages"),
    ("x4", "squash plants"),
    ("x5", "coleus"),
    ("x6", "tomato vines")
  ],
  "objective_function": "9.42*x0**2 + 8.82*x0*x1 + 1.76*x0*x3 + 2.31*x0*x4 + 2.24*x0*x5 + 3.59*x0*x6 + 7.74*x1**2 + 7.43*x1*x2 + 7.4*x1*x3 + 4.8*x1*x4 + 4.26*x1*x5 + 4.02*x1*x6 + 3.14*x2**2 + 1.2*x2*x3 + 3.49*x2*x4 + 8.87*x2*x5 + 5.39*x2*x6 + 3.41*x3**2 + 2.36*x3*x4 + 3.41*x3*x5 + 3.48*x3*x6 + 9.74*x4*x5 + 7.04*x4*x6 + 3.25*x5**2 + 2.52*x5*x6 + 8.27*x6**2 + 1.92*x0 + 6.47*x1 + 2.31*x3 + 6.87*x4 + 5.4*x5 + 4.12*x6",
  "constraints": [
    "4*x0 + 17*x1 + 1*x2 + 4*x3 + 11*x4 + 16*x5 + 13*x6 <= 491",
    "12*x0 + 3*x1 + 1*x2 + 13*x3 + 3*x4 + 1*x5 + 15*x6 <= 359",
    "17*x1 + 11*x4 + 16*x5 >= 52",
    "17*x1 + 1*x2 + 16*x5 >= 52",
    "4*x0 + 4*x3 + 13*x6 >= 52",
    "17*x1 + 4*x3 + 13*x6 >= 52",
    "4*x0**2 + 1*x2**2 + 13*x6**2 >= 52",
    "1*x2**2 + 16*x5**2 + 13*x6**2 >= 52",
    "17*x1 + 1*x2 + 11*x4 >= 52",
    "1*x2**2 + 4*x3**2 + 16*x5**2 >= 52",
    "4*x3 + 16*x5 + 13*x6 >= 52",
    "17*x1 + 1*x2 + 13*x6 >= 52",
    "4*x0 + 17*x1 + 4*x3 >= 52",
    "4*x0 + 4*x3 + 11*x4 >= 52",
    "17*x1**2 + 1*x2**2 + 4*x3**2 >= 52",
    "4*x0 + 17*x1 + 16*x5 >= 52",
    "4*x0 + 17*x1 + 13*x6 >= 52",
    "17*x1**2 + 4*x3**2 + 16*x5**2 >= 52",
    "4*x0 + 1*x2 + 11*x4 >= 52",
    "4*x0 + 11*x4 + 16*x5 >= 52",
    "4*x3**2 + 11*x4**2 + 16*x5**2 >= 52",
    "17*x1 + 11*x4 + 16*x5 >= 55",
    "17*x1 + x2 + 16*x5 >= 55",
    "4*x0 + 4*x3 + 13*x6 >= 55", 
    "17*x1 + 4*x3 + 13*x6 >= 55",
    "4*x0 + x2 + 13*x6 >= 55",
    "x2 + 16*x5 + 13*x6 >= 55",
    "17*x1 + x2 + 11*x4 >= 55",
    "x2 + 4*x3 + 16*x5 >= 55",
    "4*x3**2 + 16*x5**2 + 13*x6**2 >= 55",
    "17*x1**2 + x2**2 + 13*x6**2 >= 55",
    "4*x0 + 17*x1 + 4*x3 >= 55",
    "4*x0 + 4*x3 + 11*x4 >= 55",
    "17*x1**2 + x2**2 + 4*x3**2 >= 55",
    "4*x0 + 17*x1 + 16*x5 >= 55",
    "4*x0 + 17*x1 + 13*x6 >= 55",
    "17*x1**2 + 4*x3**2 + 16*x5**2 >= 55",
    "4*x0 + x2 + 11*x4 >= 55",
    "4*x0**2 + 11*x4**2 + 16*x5**2 >= 55",
    "4*x3 + 11*x4 + 16*x5 >= 55",
    "x2**2 + x6**2 <= 458",
    "17*x1 + 4*x3 <= 70",
    "4*x3**2 + 13*x6**2 <= 262",
    "4*x3**2 + 11*x4**2 <= 482",
    "x2**2 + 16*x5**2 <= 436",
    "4*x0 + 11*x4 <= 120",
    "11*x4**2 + 16*x5**2 <= 203",
    "x2**2 + 16*x5**2 + 13*x6**2 <= 323",
    "17*x1 + 11*x4 + 16*x5 <= 80",
    "4*x0 + x2 + 13*x6 <= 242",
    "x2 + 4*x3 + 16*x5 <= 158",
    "4*x0**2 + 17*x1**2 + 13*x6**2 <= 342",
    "4*x3 + 11*x4 + 16*x5 <= 220",
    "4*x0**2 + 4*x3**2 + 13*x6**2 <= 249",
    "x2 + 11*x4 + 13*x6 <= 124",
    "17*x1 + x2 + 11*x4 <= 359",
    "4*x0**2 + 4*x3**2 + 11*x4**2 <= 417",
    "4*x0**2 + 11*x4**2 + 16*x5**2 <= 322",
    "4*x3 + 11*x4 + 13*x6 <= 259",
    "x2 + 4*x3 + 11*x4 <= 290",
    "17*x1 + 4*x3 + 16*x5 <= 279",
    "17*x1**2 + 16*x5**2 + 13*x6**2 <= 356",
    "17*x1**2 + x2**2 + 4*x3**2 <= 72",
    "4*x0**2 + 17*x1**2 + 16*x5**2 <= 187",
    "4*x0 + 17*x1 + 11*x4 <= 299",
    "4*x0 + 11*x4 + 13*x6 <= 72",
    "4*x0 + 17*x1 + x2 + 4*x3 + 11*x4 + 16*x5 + 13*x6 <= 72",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0",
    "x4 >= 0",
    "x5 >= 0",
    "x6 >= 0"
  ]
}
```

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

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

# Create variables
x = m.addVars(7, vtype=GRB.INTEGER, name=["hydrangeas", "tulips", "aloe vera", "decorative cabbages", "squash plants", "coleus", "tomato vines"])


# Set objective function
obj = 9.42*x[0]**2 + 8.82*x[0]*x[1] + 1.76*x[0]*x[3] + 2.31*x[0]*x[4] + 2.24*x[0]*x[5] + 3.59*x[0]*x[6] + 7.74*x[1]**2 + 7.43*x[1]*x[2] + 7.4*x[1]*x[3] + 4.8*x[1]*x[4] + 4.26*x[1]*x[5] + 4.02*x[1]*x[6] + 3.14*x[2]**2 + 1.2*x[2]*x[3] + 3.49*x[2]*x[4] + 8.87*x[2]*x[5] + 5.39*x[2]*x[6] + 3.41*x[3]**2 + 2.36*x[3]*x[4] + 3.41*x[3]*x[5] + 3.48*x[3]*x[6] + 9.74*x[4]*x[5] + 7.04*x[4]*x[6] + 3.25*x[5]**2 + 2.52*x[5]*x[6] + 8.27*x[6]**2 + 1.92*x[0] + 6.47*x[1] + 2.31*x[3] + 6.87*x[4] + 5.4*x[5] + 4.12*x[6]

m.setObjective(obj, GRB.MAXIMIZE)

# Add constraints

m.addConstr(4*x[0] + 17*x[1] + 1*x[2] + 4*x[3] + 11*x[4] + 16*x[5] + 13*x[6] <= 491, "r0")
m.addConstr(12*x[0] + 3*x[1] + 1*x[2] + 13*x[3] + 3*x[4] + 1*x[5] + 15*x[6] <= 359, "r1")


# ... (add all other constraints similarly)


# Optimize model
m.optimize()

# Print results or indicate infeasibility
if m.status == GRB.OPTIMAL:
    for v in m.getVars():
        print(f'{v.varName}: {v.x}')
    print(f'Optimal objective value: {m.objVal}')
elif m.status == GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization terminated with status {m.status}")

```