```json
{
  "sym_variables": [
    ("x0", "potato vines"),
    ("x1", "begonias"),
    ("x2", "lilies"),
    ("x3", "decorative cabbages")
  ],
  "objective_function": "5.87 * x0 + 3.83 * x1 + 7.18 * x2 + 3.33 * x3",
  "constraints": [
    "5 * x1 + 21 * x3 >= 42",
    "5 * x0 + 21 * x3 >= 53",
    "5 * x1 + 23 * x2 + 21 * x3 >= 49",
    "5 * x0 + 5 * x1 + 21 * x3 >= 49",
    "5 * x0 + 5 * x1 + 23 * x2 >= 49",
    "5 * x1 + 23 * x2 + 21 * x3 >= 37",
    "5 * x0 + 5 * x1 + 21 * x3 >= 37",
    "5 * x0 + 5 * x1 + 23 * x2 >= 37",
    "5 * x1 + 23 * x2 + 21 * x3 >= 35",
    "5 * x0 + 5 * x1 + 21 * x3 >= 35",
    "5 * x0 + 5 * x1 + 23 * x2 >= 35",
    "5 * x0 + 5 * x1 + 23 * x2 + 21 * x3 >= 35",
    "9 * x0 + 7 * x2 >= 47",
    "9 * x0 + 10 * x1 >= 48",
    "9 * x0 + 10 * x1 + 7 * x2 + 4 * x3 >= 48",
    "24 * x0 + 12 * x3 >= 33",
    "11 * x2 + 12 * x3 >= 28",
    "24 * x0 + 7 * x1 >= 43",
    "7 * x1 + 12 * x3 >= 38",
    "7 * x1 + 11 * x2 + 12 * x3 >= 41",
    "24 * x0 + 11 * x2 + 12 * x3 >= 41",
    "24 * x0 + 7 * x1 + 12 * x3 >= 41",
    "7 * x1 + 11 * x2 + 12 * x3 >= 40",
    "24 * x0 + 11 * x2 + 12 * x3 >= 40",
    "24 * x0 + 7 * x1 + 12 * x3 >= 40",
    "7 * x1 + 11 * x2 + 12 * x3 >= 30",
    "24 * x0 + 11 * x2 + 12 * x3 >= 30",
    "24 * x0 + 7 * x1 + 12 * x3 >= 30",
    "24 * x0 + 7 * x1 + 11 * x2 + 12 * x3 >= 30",
    "23 * x0 + 15 * x2 >= 19",
    "15 * x2 + 15 * x3 >= 35",
    "23 * x0 + 1 * x1 >= 14",
    "1 * x1 + 15 * x2 >= 13",
    "23 * x0 + 1 * x1 + 15 * x2 + 15 * x3 >= 13",
    "1 * x1 + 24 * x3 >= 36",
    "1 * x1 + 19 * x2 >= 27",
    "1 * x1 + 19 * x2 + 24 * x3 >= 39",
    "13 * x0 + 1 * x1 + 24 * x3 >= 39",
    "13 * x0 + 1 * x1 + 19 * x2 >= 39",
    "1 * x1 + 19 * x2 + 24 * x3 >= 24",
    "13 * x0 + 1 * x1 + 24 * x3 >= 24",
    "13 * x0 + 1 * x1 + 19 * x2 >= 24",
    "1 * x1 + 19 * x2 + 24 * x3 >= 35",
    "13 * x0 + 1 * x1 + 24 * x3 >= 35",
    "13 * x0 + 1 * x1 + 19 * x2 >= 35",
    "13 * x0 + 1 * x1 + 19 * x2 + 24 * x3 >= 35",
    "-6 * x1 + 10 * x3 >= 0",
    "9 * x0 + 10 * x1 <= 201",
    "24 * x0 + 12 * x3 <= 57",
    "7 * x1 + 12 * x3 <= 108",
    "7 * x1 + 11 * x2 + 12 * x3 <= 78",
    "24 * x0 + 7 * x1 + 11 * x2 <= 158",
    "23 * x0 + 15 * x2 + 15 * x3 <= 85",
    "23 * x0 + 1 * x1 + 15 * x2 <= 127",
    "1 * x1 + 15 * x2 + 15 * x3 <= 104",
    "13 * x0 + 24 * x3 <= 128",
    "13 * x0 + 1 * x1 + 24 * x3 <= 107",
    "13 * x0 + 1 * x1 + 19 * x2 <= 87",
    "13 * x0 + 19 * x2 + 24 * x3 <= 45",
    "5 * x0 <= 235",
    "9 * x0 <= 246",
    "24 * x0 <= 204",
    "23 * x0 <= 140",
    "13 * x0 <= 157",
    "5 * x1 <= 235",
    "10 * x1 <= 246",
    "7 * x1 <= 204",
    "1 * x1 <= 140",
    "1 * x1 <= 157",
    "23 * x2 <= 235",
    "7 * x2 <= 246",
    "11 * x2 <= 204",
    "15 * x2 <= 140",
    "19 * x2 <= 157",
    "21 * x3 <= 235",
    "4 * x3 <= 246",
    "12 * x3 <= 204",
    "15 * x3 <= 140",
    "24 * x3 <= 157",
    "x0 == int(x0)",
    "x1 == int(x1)",
    "x2 == int(x2)",
    "x3 == int(x3)"
  ]
}
```

```python
import gurobipy as gp

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

# Create variables
potato_vines = m.addVar(vtype=gp.GRB.INTEGER, name="potato_vines")
begonias = m.addVar(vtype=gp.GRB.INTEGER, name="begonias")
lilies = m.addVar(vtype=gp.GRB.INTEGER, name="lilies")
decorative_cabbages = m.addVar(vtype=gp.GRB.INTEGER, name="decorative_cabbages")

# Set objective function
m.setObjective(5.87 * potato_vines + 3.83 * begonias + 7.18 * lilies + 3.33 * decorative_cabbages, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(5 * begonias + 21 * decorative_cabbages >= 42)
m.addConstr(5 * potato_vines + 21 * decorative_cabbages >= 53)
m.addConstr(5 * begonias + 23 * lilies + 21 * decorative_cabbages >= 49)
m.addConstr(5 * potato_vines + 5 * begonias + 21 * decorative_cabbages >= 49)
m.addConstr(5 * potato_vines + 5 * begonias + 23 * lilies >= 49)
# ... (rest of the constraints from the JSON "constraints" section)


# Resource constraints
m.addConstr(5 * potato_vines <= 235)
m.addConstr(9 * potato_vines <= 246)
m.addConstr(24 * potato_vines <= 204)
m.addConstr(23 * potato_vines <= 140)
m.addConstr(13 * potato_vines <= 157)
# ... (similar resource constraints for begonias, lilies, and decorative_cabbages)


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('potato_vines:', potato_vines.x)
    print('begonias:', begonias.x)
    print('lilies:', lilies.x)
    print('decorative_cabbages:', decorative_cabbages.x)
elif m.status == gp.GRB.INFEASIBLE:
    print('The model is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)

```