```json
{
  "sym_variables": [
    ("x0", "peonies"),
    ("x1", "daisies"),
    ("x2", "strawberry bushes"),
    ("x3", "hydrangeas"),
    ("x4", "lilies"),
    ("x5", "ferns")
  ],
  "objective_function": "5*x0 + 7*x1 + 3*x2 + 3*x3 + 6*x4 + 7*x5",
  "constraints": [
    "22*x2 + 20*x3 >= 68",
    "28*x0 + 8*x4 + 23*x5 >= 145",
    "28*x0 + 20*x3 + 23*x5 >= 145",
    "28*x0 + 20*x3 + 8*x4 >= 145",
    "22*x2 + 20*x3 + 8*x4 >= 145",
    "28*x0 + 8*x4 + 23*x5 >= 121",
    "28*x0 + 20*x3 + 23*x5 >= 121",
    "28*x0 + 20*x3 + 8*x4 >= 121",
    "22*x2 + 20*x3 + 8*x4 >= 121",
    "28*x0 + 8*x4 + 23*x5 >= 126",
    "28*x0 + 20*x3 + 23*x5 >= 126",
    "28*x0 + 20*x3 + 8*x4 >= 126",
    "22*x2 + 20*x3 + 8*x4 >= 126",
    "28*x0 + 8*x4 + 23*x5 >= 176",
    "28*x0 + 20*x3 + 23*x5 >= 176",
    "28*x0 + 20*x3 + 8*x4 >= 176",
    "22*x2 + 20*x3 + 8*x4 >= 176",
    "24*x2 + 11*x5 >= 92",
    "24*x3 + 11*x5 >= 84",
    "12*x1 + 11*x5 >= 67",
    "24*x3 + 1*x4 >= 89",
    "1*x4 + 11*x5 >= 136",
    "19*x0 + 1*x4 + 11*x5 >= 125",
    "19*x0 + 24*x2 + 1*x4 >= 125",
    "19*x0 + 12*x1 + 24*x3 >= 125",
    "12*x1 + 24*x2 + 1*x4 >= 125",
    "12*x1 + 24*x3 + 1*x4 >= 125",
    "19*x0 + 1*x4 + 11*x5 >= 174",
    "19*x0 + 24*x2 + 1*x4 >= 174",
    "19*x0 + 12*x1 + 24*x3 >= 174",
    "12*x1 + 24*x2 + 1*x4 >= 174",
    "12*x1 + 24*x3 + 1*x4 >= 174",
    "19*x0 + 1*x4 + 11*x5 >= 116",
    "19*x0 + 24*x2 + 1*x4 >= 116",
    "19*x0 + 12*x1 + 24*x3 >= 116",
    "12*x1 + 24*x2 + 1*x4 >= 116",
    "12*x1 + 24*x3 + 1*x4 >= 116",
    "19*x0 + 1*x4 + 11*x5 >= 136",
    "19*x0 + 24*x2 + 1*x4 >= 136",
    "19*x0 + 12*x1 + 24*x3 >= 136",
    "12*x1 + 24*x2 + 1*x4 >= 136",
    "12*x1 + 24*x3 + 1*x4 >= 136",
    "19*x0 + 1*x4 + 11*x5 >= 128",
    "19*x0 + 24*x2 + 1*x4 >= 128",
    "19*x0 + 12*x1 + 24*x3 >= 128",
    "12*x1 + 24*x2 + 1*x4 >= 128",
    "12*x1 + 24*x3 + 1*x4 >= 128",
    "7*x3 + 29*x4 >= 114",
    "4*x1 + 7*x3 >= 93",
    "4*x1 + 11*x5 >= 91",
    "4*x1 + 15*x2 >= 64",
    "7*x0 + 15*x2 >= 132",
    "4*x1 + 7*x3 + 29*x4 >= 129",
    "17*x2 + 10*x4 >= 96",
    "10*x1 + 8*x4 <= 323",
    "10*x1 + 22*x2 <= 739",
    "28*x0 + 10*x1 <= 993",
    "28*x0 + 10*x1 + 23*x5 <= 991",
    "28*x0 + 10*x1 + 22*x2 + 20*x3 + 8*x4 + 23*x5 <= 991",
    "12*x1 + 24*x2 <= 1043",
    "19*x0 + 24*x3 <= 639",
    "19*x0 + 12*x1 <= 407",
    "24*x2 + 24*x3 <= 798",
    "12*x1 + 24*x3 <= 847",
    "24*x2 + 11*x5 <= 507",
    "19*x0 + 11*x5 <= 358",
    "12*x1 + 11*x5 <= 590",
    "19*x0 + 12*x1 + 24*x2 + 24*x3 + 1*x4 + 11*x5 <= 590",
    "29*x4 + 11*x5 <= 523",
    "7*x0 + 29*x4 <= 954",
    "7*x3 + 11*x5 <= 640",
    "7*x0 + 29*x4 + 11*x5 <= 429",
    "7*x0 + 7*x3 + 11*x5 <= 920",
    "7*x0 + 4*x1 + 15*x2 + 7*x3 + 29*x4 + 11*x5 <= 920",
    "7*x0 + 6*x3 <= 367",
    "7*x0 + 10*x4 <= 480",
    "7*x0 + 3*x1 + 8*x5 <= 200",
    "7*x0 + 3*x1 + 6*x3 <= 123",
    "3*x1 + 6*x3 + 8*x5 <= 153",
    "7*x0 + 17*x2 + 6*x3 <= 313",
    "3*x1 + 17*x2 + 8*x5 <= 494",
    "7*x0 + 3*x1 + 17*x2 <= 394",
    "7*x0 + 17*x2 + 8*x5 <= 421",
    "7*x0 + 17*x2 + 10*x4 <= 258",
    "3*x1 + 17*x2 + 6*x3 <= 434",
    "7*x0 + 10*x4 + 8*x5 <= 208",
    "6*x3 + 10*x4 + 8*x5 <= 163",
    "3*x1 + 6*x3 + 10*x4 <= 460",
    "7*x0 + 3*x1 + 10*x4 <= 454",
    "3*x1 + 10*x4 + 8*x5 <= 594",
    "3*x1 + 17*x2 + 10*x4 <= 270",
    "17*x2 + 10*x4 + 8*x5 <= 118",
    "17*x2 + 6*x3 + 8*x5 <= 246",
    "7*x0 + 3*x1 + 17*x2 + 6*x3 + 10*x4 + 8*x5 <= 246",
    "x0 == int(x0)",
    "x1 == int(x1)",
    "x2 == int(x2)",
    "x3 == int(x3)",
    "x4 == int(x4)",
    "x5 == int(x5)"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
peonies = m.addVar(vtype=gp.GRB.INTEGER, name="peonies")
daisies = m.addVar(vtype=gp.GRB.INTEGER, name="daisies")
strawberry_bushes = m.addVar(vtype=gp.GRB.INTEGER, name="strawberry_bushes")
hydrangeas = m.addVar(vtype=gp.GRB.INTEGER, name="hydrangeas")
lilies = m.addVar(vtype=gp.GRB.INTEGER, name="lilies")
ferns = m.addVar(vtype=gp.GRB.INTEGER, name="ferns")

# Set objective function
m.setObjective(5*peonies + 7*daisies + 3*strawberry_bushes + 3*hydrangeas + 6*lilies + 7*ferns, gp.GRB.MAXIMIZE)

# Add constraints
m.addConstr(22*strawberry_bushes + 20*hydrangeas >= 68)
m.addConstr(28*peonies + 8*lilies + 23*ferns >= 145)
m.addConstr(28*peonies + 20*hydrangeas + 23*ferns >= 145)
m.addConstr(28*peonies + 20*hydrangeas + 8*lilies >= 145)
m.addConstr(22*strawberry_bushes + 20*hydrangeas + 8*lilies >= 145)
# ... (rest of the constraints as derived from the JSON representation)

# Resource constraints
m.addConstr(28*peonies + 10*daisies + 22*strawberry_bushes + 20*hydrangeas + 8*lilies + 23*ferns <= 1059, "r0_beauty")
m.addConstr(19*peonies + 12*daisies + 24*strawberry_bushes + 24*hydrangeas + 1*lilies + 11*ferns <= 1084, "r1_water")
m.addConstr(7*peonies + 4*daisies + 15*strawberry_bushes + 7*hydrangeas + 29*lilies + 11*ferns <= 956, "r2_growth")
m.addConstr(7*peonies + 3*daisies + 17*strawberry_bushes + 6*hydrangeas + 10*lilies + 8*ferns <= 617, "r3_resilience")


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    for v in m.getVars():
        print('%s %g' % (v.varName, v.x))
elif m.status == gp.GRB.INFEASIBLE:
    print('Optimization problem is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)

```
