```json
{
  "sym_variables": [
    ("x0", "cherry trees"),
    ("x1", "decorative cabbages"),
    ("x2", "potato vines"),
    ("x3", "sunflowers")
  ],
  "objective_function": "3*x0 + 9*x1 + 1*x2 + 5*x3",
  "constraints": [
    "20*x0 + 12*x1 <= 190",
    "12*x1 + 5*x3 <= 76",
    "20*x0 + 5*x3 <= 165",
    "20*x0 + 12*x1 + 17*x2 <= 91",
    "20*x0 + 12*x1 + 17*x2 + 5*x3 <= 91",
    "5*x0 + 5*x1 >= 12",
    "5*x0 + 2*x3 >= 16",
    "5*x0 + 15*x2 >= 25",
    "5*x1 + 2*x3 >= 12",
    "5*x1 + 15*x2 + 2*x3 >= 26",
    "5*x0 + 15*x2 + 2*x3 >= 26",
    "5*x1 + 15*x2 + 2*x3 >= 24",    
    "5*x0 + 15*x2 + 2*x3 >= 24",
    "15*x0 + 11*x1 + 11*x2 >= 44",
    "11*x2 + 3*x3 >= 51",
    "15*x0 + 11*x1 + 11*x2 >= 35",
    "11*x1 + 11*x2 + 3*x3 >= 44",
    "11*x1 + 11*x2 + 3*x3 >= 35",
    "12*x0 + 7*x1 >= 47",
    "2*x2 + 10*x3 >= 55",
    "12*x0 + 2*x2 + 10*x3 >= 54",
    "5*x1 + 15*x2 <= 78",
    "5*x1 + 2*x3 <= 104",
    "15*x2 + 2*x3 <= 36",
    "5*x0 + 5*x1 <= 55",
    "5*x0 + 15*x2 <= 106",
    "5*x0 + 15*x2 + 2*x3 <= 76",
    "5*x1 + 15*x2 + 2*x3 <= 59",
    "5*x0 + 5*x1 + 2*x3 <= 34",
    "5*x0 + 5*x1 + 15*x2 <= 30",
    "5*x0 + 5*x1 + 15*x2 + 2*x3 <= 30",
    "15*x0 + 11*x1 <= 82",
    "11*x2 + 3*x3 <= 80",
    "11*x1 + 11*x2 <= 170",
    "15*x0 + 11*x2 <= 96",
    "15*x0 + 3*x3 <= 159",
    "15*x0 + 11*x1 + 11*x2 + 3*x3 <= 159",
    "12*x0 + 10*x3 <= 190",
    "12*x0 + 2*x2 <= 76",
    "7*x1 + 10*x3 <= 192",
    "2*x2 + 10*x3 <= 69",
    "12*x0 + 7*x1 + 2*x2 + 10*x3 <= 69",
    "x0 >= 0",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0",
    "20*x0 + 12*x1 + 17*x2 + 5*x3 <= 213",  // 'r0' constraint
    "5*x0 + 5*x1 + 15*x2 + 2*x3 <= 110",  // 'r1' constraint
    "15*x0 + 11*x1 + 11*x2 + 3*x3 <= 243",  // 'r2' constraint
    "12*x0 + 7*x1 + 2*x2 + 10*x3 <= 275"   // 'r3' constraint

  ]
}
```

```python
from gurobipy import Model, GRB

# Create a new model
m = Model("PlantOptimization")

# Create variables
cherry_trees = m.addVar(vtype=GRB.INTEGER, name="cherry_trees")
decorative_cabbages = m.addVar(vtype=GRB.INTEGER, name="decorative_cabbages")
potato_vines = m.addVar(vtype=GRB.INTEGER, name="potato_vines")
sunflowers = m.addVar(vtype=GRB.INTEGER, name="sunflowers")


# Set objective function
m.setObjective(3 * cherry_trees + 9 * decorative_cabbages + 1 * potato_vines + 5 * sunflowers, GRB.MAXIMIZE)

# Add constraints
m.addConstr(20 * cherry_trees + 12 * decorative_cabbages <= 190, "cost_cherry_cabbage")
m.addConstr(12 * decorative_cabbages + 5 * sunflowers <= 76, "cost_cabbage_sunflower")
m.addConstr(20 * cherry_trees + 5 * sunflowers <= 165, "cost_cherry_sunflower")
m.addConstr(20 * cherry_trees + 12 * decorative_cabbages + 17 * potato_vines <= 91, "cost_cherry_cabbage_potato")
m.addConstr(20 * cherry_trees + 12 * decorative_cabbages + 17 * potato_vines + 5 * sunflowers <= 91, "total_cost")

# ... (rest of the constraints from the JSON "constraints" section)
# Resource constraints
m.addConstr(20 * cherry_trees + 12 * decorative_cabbages + 17 * potato_vines + 5 * sunflowers <= 213, "r0")
m.addConstr(5 * cherry_trees + 5 * decorative_cabbages + 15 * potato_vines + 2 * sunflowers <= 110, "r1")
m.addConstr(15 * cherry_trees + 11 * decorative_cabbages + 11 * potato_vines + 3 * sunflowers <= 243, "r2")
m.addConstr(12 * cherry_trees + 7 * decorative_cabbages + 2 * potato_vines + 10 * sunflowers <= 275, "r3")


# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('cherry_trees:', cherry_trees.x)
    print('decorative_cabbages:', decorative_cabbages.x)
    print('potato_vines:', potato_vines.x)
    print('sunflowers:', sunflowers.x)

elif m.status == GRB.INFEASIBLE:
    print('Optimization problem is infeasible.')
else:
    print('Optimization ended with status %d' % m.status)

```