## Step 1: Define the symbolic representation of the problem

First, let's define the symbolic representation of the problem, including the variables, objective function, and constraints.

## Step 2: Identify the variables and their corresponding symbolic notation

The variables are: 
- bean stalks: x0
- strawberry bushes: x1
- agave: x2
- tulips: x3

## Step 3: Define the objective function in symbolic notation

The objective function to maximize is: 
1 * x0 + 2 * x1 + 7 * x2 + 2 * x3

## Step 4: List the constraints in symbolic notation

Constraints:
- 6x0 + 6x1 + 2x2 + 21x3 <= 327
- x0, x1, x2, x3 are non-negative integers (except the problem states that x2 and x3 must be non-fractional, implying they can be continuous but for simplicity and given the context, we'll treat them as integers)
- 6x1 + 2x2 >= 80
- 6x1 + 21x3 >= 53
- 15x0 + x1 >= 31
- x1 + 3x2 + 16x3 >= 58
- 13x0 + 11x2 + 21x3 >= 48
- 13x0 + 17x1 + 21x3 >= 48
- 13x0 + 11x2 + 21x3 >= 51
- 13x0 + 17x1 + 21x3 >= 51
- 10x0 + 8x2 + 23x3 >= 27
- 10x0 + 4x1 + 23x3 >= 27
- 10x0 + 8x2 + 23x3 >= 22
- 10x0 + 4x1 + 23x3 >= 22
- 2x2 + 21x3 <= 175
- 6x0 + 2x2 <= 299
- 6x1 + 2x2 <= 142
- 6x0 + 6x1 + 2x2 + 21x3 <= 142
- x1 + 16x3 <= 173
- 15x0 + 16x3 <= 84
- 15x0 + 3x2 <= 72
- 3x2 + 16x3 <= 186
- 15x0 + x1 + 3x2 <= 109
- 15x0 + x1 + 16x3 <= 196
- 15x0 + x1 + 3x2 + 16x3 <= 196
- 13x0 + 21x3 <= 162
- 17x1 + 11x2 <= 62
- 13x0 + 11x2 <= 150
- 13x0 + 17x1 + 11x2 <= 160
- 13x0 + 17x1 + 11x2 + 21x3 <= 160
- 4x1 + 23x3 <= 136
- 10x0 + 8x2 <= 126
- 10x0 + 23x3 <= 52
- 10x0 + 4x1 + 23x3 <= 150
- 10x0 + 8x2 + 23x3 <= 88
- 10x0 + 4x1 + 8x2 + 23x3 <= 88

## Step 5: Provide the symbolic representation in JSON format

```json
{
    'sym_variables': [
        ('x0', 'bean stalks'),
        ('x1', 'strawberry bushes'),
        ('x2', 'agave'),
        ('x3', 'tulips')
    ],
    'objective_function': '1*x0 + 2*x1 + 7*x2 + 2*x3',
    'constraints': [
        '6*x0 + 6*x1 + 2*x2 + 21*x3 <= 327',
        '6*x1 + 2*x2 >= 80',
        '6*x1 + 21*x3 >= 53',
        '15*x0 + x1 >= 31',
        'x1 + 3*x2 + 16*x3 >= 58',
        '13*x0 + 11*x2 + 21*x3 >= 48',
        '13*x0 + 17*x1 + 21*x3 >= 48',
        '13*x0 + 11*x2 + 21*x3 >= 51',
        '13*x0 + 17*x1 + 21*x3 >= 51',
        '10*x0 + 8*x2 + 23*x3 >= 27',
        '10*x0 + 4*x1 + 23*x3 >= 27',
        '10*x0 + 8*x2 + 23*x3 >= 22',
        '10*x0 + 4*x1 + 23*x3 >= 22',
        '2*x2 + 21*x3 <= 175',
        '6*x0 + 2*x2 <= 299',
        '6*x1 + 2*x2 <= 142',
        '6*x0 + 6*x1 + 2*x2 + 21*x3 <= 142',
        'x1 + 16*x3 <= 173',
        '15*x0 + 16*x3 <= 84',
        '15*x0 + 3*x2 <= 72',
        '3*x2 + 16*x3 <= 186',
        '15*x0 + x1 + 3*x2 <= 109',
        '15*x0 + x1 + 16*x3 <= 196',
        '15*x0 + x1 + 3*x2 + 16*x3 <= 196',
        '13*x0 + 21*x3 <= 162',
        '17*x1 + 11*x2 <= 62',
        '13*x0 + 11*x2 <= 150',
        '13*x0 + 17*x1 + 11*x2 <= 160',
        '13*x0 + 17*x1 + 11*x2 + 21*x3 <= 160',
        '4*x1 + 23*x3 <= 136',
        '10*x0 + 8*x2 <= 126',
        '10*x0 + 23*x3 <= 52',
        '10*x0 + 4*x1 + 23*x3 <= 150',
        '10*x0 + 8*x2 + 23*x3 <= 88',
        '10*x0 + 4*x1 + 8*x2 + 23*x3 <= 88'
    ]
}
```

## Step 6: Write the Gurobi code

```python
import gurobi

def solve_optimization_problem():
    # Create a new Gurobi model
    model = gurobi.Model()

    # Define the variables
    x0 = model.addVar(name="bean_stalks", vtype=gurobi.GRB.INTEGER)
    x1 = model.addVar(name="strawberry_bushes", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(name="agave", vtype=gurobi.GRB.INTEGER)
    x3 = model.addVar(name="tulips", vtype=gurobi.GRB.INTEGER)

    # Define the objective function
    model.setObjective(1 * x0 + 2 * x1 + 7 * x2 + 2 * x3, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(6 * x0 + 6 * x1 + 2 * x2 + 21 * x3 <= 327)
    model.addConstr(6 * x1 + 2 * x2 >= 80)
    model.addConstr(6 * x1 + 21 * x3 >= 53)
    model.addConstr(15 * x0 + x1 >= 31)
    model.addConstr(x1 + 3 * x2 + 16 * x3 >= 58)
    model.addConstr(13 * x0 + 11 * x2 + 21 * x3 >= 48)
    model.addConstr(13 * x0 + 17 * x1 + 21 * x3 >= 48)
    model.addConstr(13 * x0 + 11 * x2 + 21 * x3 >= 51)
    model.addConstr(13 * x0 + 17 * x1 + 21 * x3 >= 51)
    model.addConstr(10 * x0 + 8 * x2 + 23 * x3 >= 27)
    model.addConstr(10 * x0 + 4 * x1 + 23 * x3 >= 27)
    model.addConstr(10 * x0 + 8 * x2 + 23 * x3 >= 22)
    model.addConstr(10 * x0 + 4 * x1 + 23 * x3 >= 22)
    model.addConstr(2 * x2 + 21 * x3 <= 175)
    model.addConstr(6 * x0 + 2 * x2 <= 299)
    model.addConstr(6 * x1 + 2 * x2 <= 142)
    model.addConstr(6 * x0 + 6 * x1 + 2 * x2 + 21 * x3 <= 142)
    model.addConstr(x1 + 16 * x3 <= 173)
    model.addConstr(15 * x0 + 16 * x3 <= 84)
    model.addConstr(15 * x0 + 3 * x2 <= 72)
    model.addConstr(3 * x2 + 16 * x3 <= 186)
    model.addConstr(15 * x0 + x1 + 3 * x2 <= 109)
    model.addConstr(15 * x0 + x1 + 16 * x3 <= 196)
    model.addConstr(15 * x0 + x1 + 3 * x2 + 16 * x3 <= 196)
    model.addConstr(13 * x0 + 21 * x3 <= 162)
    model.addConstr(17 * x1 + 11 * x2 <= 62)
    model.addConstr(13 * x0 + 11 * x2 <= 150)
    model.addConstr(13 * x0 + 17 * x1 + 11 * x2 <= 160)
    model.addConstr(13 * x0 + 17 * x1 + 11 * x2 + 21 * x3 <= 160)
    model.addConstr(4 * x1 + 23 * x3 <= 136)
    model.addConstr(10 * x0 + 8 * x2 <= 126)
    model.addConstr(10 * x0 + 23 * x3 <= 52)
    model.addConstr(10 * x0 + 4 * x1 + 23 * x3 <= 150)
    model.addConstr(10 * x0 + 8 * x2 + 23 * x3 <= 88)
    model.addConstr(10 * x0 + 4 * x1 + 8 * x2 + 23 * x3 <= 88)

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("bean stalks: ", x0.varValue)
        print("strawberry bushes: ", x1.varValue)
        print("agave: ", x2.varValue)
        print("tulips: ", x3.varValue)
    else:
        print("The model is infeasible")

solve_optimization_problem()
```