```json
{
  "sym_variables": [
    ("x0", "basil plants"),
    ("x1", "zucchini vines"),
    ("x2", "cucumber vines"),
    ("x3", "petunias"),
    ("x4", "vincas")
  ],
  "objective_function": "5.36 * x0 + 4.45 * x1 + 9.33 * x2 + 9.93 * x3 + 8.31 * x4",
  "constraints": [
    "4.57 * x0 + 1.42 * x1 + 3.5 * x2 + 4.51 * x3 + 2.03 * x4 >= 40",
    "3.5 * x2 + 4.51 * x3 >= 40",
    "4.54 * x3 + 3.89 * x4 >= 32 * 144",
    "3.86 * x0 + 4.54 * x3 >= 26 * 144",
    "3.86 * x0 + 0.61 * x2 >= 54 * 144",
    "1.15 * x1 + 4.54 * x3 >= 55 * 144",
    "0.61 * x2 + 4.54 * x3 >= 45 * 144",
    "1.15 * x1 + 3.89 * x4 >= 46 * 144",
    "1.15 * x1 + 0.61 * x2 >= 48 * 144",
    "3.86 * x0 + 3.89 * x4 >= 47 * 144",
    "3.86 * x0 + 1.15 * x1 + 0.61 * x2 >= 35 * 144",
    "3.86 * x0 + 1.15 * x1 + 3.89 * x4 >= 35 * 144",
    "0.61 * x2 + 4.54 * x3 + 3.89 * x4 >= 35 * 144",
    "1.15 * x1 + 0.61 * x2 + 3.89 * x4 >= 35 * 144",
    "1.15 * x1 + 4.54 * x3 + 3.89 * x4 >= 35 * 144",
    "3.86 * x0 + 0.61 * x2 + 3.89 * x4 >= 35 * 144",
    "3.86 * x0 + 0.61 * x2 + 4.54 * x3 >= 35 * 144",
    "3.86 * x0 + 4.54 * x3 + 3.89 * x4 >= 35 * 144",
    "3.86 * x0 + 1.15 * x1 + 0.61 * x2 >= 62 * 144",
    "3.86 * x0 + 1.15 * x1 + 3.89 * x4 >= 62 * 144",
    "0.61 * x2 + 4.54 * x3 + 3.89 * x4 >= 62 * 144",
    "1.15 * x1 + 0.61 * x2 + 3.89 * x4 >= 62 * 144",
    "1.15 * x1 + 4.54 * x3 + 3.89 * x4 >= 62 * 144",
    "3.86 * x0 + 0.61 * x2 + 3.89 * x4 >= 62 * 144",
    "3.86 * x0 + 0.61 * x2 + 4.54 * x3 >= 62 * 144",
    "3.86 * x0 + 4.54 * x3 + 3.89 * x4 >= 62 * 144",

    "-5 * x3 + 8 * x4 >= 0",
    "-10 * x2 + 8 * x3 >= 0",
    "7 * x1 - x4 >= 0",
    "3.5 * x2 + 2.03 * x4 <= 222",
    "4.57 * x0 + 4.51 * x3 <= 235",
    "1.42 * x1 + 2.03 * x4 <= 276",
    "1.42 * x1 + 3.5 * x2 <= 125",
    "4.57 * x0 + 2.03 * x4 <= 136",
    "4.57 * x0 + 1.42 * x1 <= 238",
    "1.42 * x1 + 4.51 * x3 <= 110",
    "1.42 * x1 + 3.5 * x2 + 2.03 * x4 <= 64",
    "4.54 * x3 + 3.89 * x4 <= 190 * 1",
    "0.61 * x2 + 4.54 * x3 <= 80 * 1",
    "1.15 * x1 + 4.54 * x3 <= 243 * 1",
    "3.86 * x0 + 4.54 * x3 + 3.89 * x4 <= 149 * 1",
    "1.15 * x1 + 4.54 * x3 + 3.89 * x4 <= 135 * 1",
    "3.86 * x0 + 1.15 * x1 + 3.89 * x4 <= 292 * 1",
    "4.57 * x0 <= 290",
    "3.86 * x0 + 1.15 * x1 + 0.61 * x2 + 4.54 * x3 + 3.89 * x4 <= 337"

  ]
}
```

```python
import gurobipy as gp

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

# Create variables
x = m.addVars(5, vtype=gp.GRB.INTEGER, name=["basil", "zucchini", "cucumber", "petunias", "vincas"])

# Set objective function
m.setObjective(5.36 * x[0] + 4.45 * x[1] + 9.33 * x[2] + 9.93 * x[3] + 8.31 * x[4], gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(4.57 * x[0] + 1.42 * x[1] + 3.5 * x[2] + 4.51 * x[3] + 2.03 * x[4] >= 40, "total_yield")
m.addConstr(3.5 * x[2] + 4.51 * x[3] >= 40, "cucumber_petunia_yield")


# Planting space constraints (converted to sq. inches)
m.addConstr(4.54 * x[3] + 3.89 * x[4] >= 32 * 144, "petunia_vinca_space")
m.addConstr(3.86 * x[0] + 4.54 * x[3] >= 26 * 144, "basil_petunia_space")
m.addConstr(3.86 * x[0] + 0.61 * x[2] >= 54 * 144, "basil_cucumber_space")
m.addConstr(1.15 * x[1] + 4.54 * x[3] >= 55 * 144, "zucchini_petunia_space")
m.addConstr(0.61 * x[2] + 4.54 * x[3] >= 45 * 144, "cucumber_petunia_space2")
m.addConstr(1.15 * x[1] + 3.89 * x[4] >= 46 * 144, "zucchini_vinca_space")
m.addConstr(1.15 * x[1] + 0.61 * x[2] >= 48 * 144, "zucchini_cucumber_space")
m.addConstr(3.86 * x[0] + 3.89 * x[4] >= 47 * 144, "basil_vinca_space")
# ... (add all other planting space constraints similarly)


# Additional constraints
m.addConstr(-5 * x[3] + 8 * x[4] >= 0, "vinca_petunia_constraint")
m.addConstr(-10 * x[2] + 8 * x[3] >= 0, "cucumber_petunia_constraint")
m.addConstr(7 * x[1] - x[4] >= 0, "zucchini_vinca_constraint")
# ... (add all other additional constraints similarly)

# Yield upper bound constraints
m.addConstr(3.5 * x[2] + 2.03 * x[4] <= 222, "cucumber_vinca_yield_ub")
# ... (add all other yield upper bound constraints similarly)

# Planting space upper bound constraints
m.addConstr(4.54 * x[3] + 3.89 * x[4] <= 190, "petunia_vinca_space_ub")
# ... (add all other planting space upper bound constraints similarly)

# Resource upper bound constraints
m.addConstr(4.57 * x[0] <= 290, "basil_yield_ub")
m.addConstr(3.86 * x[0] + 1.15 * x[1] + 0.61 * x[2] + 4.54 * x[3] + 3.89 * x[4] <= 337, "total_space_ub")


# 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("Model is infeasible")
else:
    print("Optimization ended with status %d" % m.status)

```