## Step 1: Define the symbolic representation of the variables
The variables are 'corn cobs', 'kale salads', 'chicken breasts', and 'slices of pizza', which can be represented symbolically as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the objective function into a symbolic representation
The objective function to maximize is $4.31x_0 + 3.65x_1 + 2.39x_2 + 8.9x_3$.

## Step 3: List all the constraints in symbolic notation
1. $25x_0 + 22x_1 + 28x_2 + 9x_3 \geq 57$
2. $2x_0 + 14x_2 + 28x_3 \geq 72$
3. $25x_0 + 28x_2 \leq 163$
4. $25x_0 + 9x_3 \leq 299$
5. $28x_2 + 9x_3 \leq 103$
6. $25x_0 + 22x_1 \leq 281$
7. $25x_0 + 22x_1 + 28x_2 + 9x_3 \leq 281$
8. $27x_1 + 28x_3 \leq 247$
9. $2x_0 + 27x_1 \leq 321$
10. $14x_2 + 28x_3 \leq 318$
11. $2x_0 + 28x_3 \leq 310$
12. $27x_1 + 14x_2 \leq 93$
13. $2x_0 + 27x_1 + 14x_2 + 28x_3 \leq 93$

## 4: Define the symbolic representation of the problem
```json
{
'sym_variables': [('x0', 'corn cobs'), ('x1', 'kale salads'), ('x2', 'chicken breasts'), ('x3', 'slices of pizza')],
'objective_function': '4.31*x0 + 3.65*x1 + 2.39*x2 + 8.9*x3',
'constraints': [
'25*x0 + 22*x1 + 28*x2 + 9*x3 >= 57',
'2*x0 + 14*x2 + 28*x3 >= 72',
'25*x0 + 28*x2 <= 163',
'25*x0 + 9*x3 <= 299',
'28*x2 + 9*x3 <= 103',
'25*x0 + 22*x1 <= 281',
'25*x0 + 22*x1 + 28*x2 + 9*x3 <= 281',
'27*x1 + 28*x3 <= 247',
'2*x0 + 27*x1 <= 321',
'14*x2 + 28*x3 <= 318',
'2*x0 + 28*x3 <= 310',
'27*x1 + 14*x2 <= 93',
'2*x0 + 27*x1 + 14*x2 + 28*x3 <= 93'
]
}
```

## 5: Implement the optimization problem using Gurobi
```python
import gurobi

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

    # Define the variables
    x0 = model.addVar(name="corn_cobs", lb=0)
    x1 = model.addVar(name="kale_salads", lb=0)
    x2 = model.addVar(name="chicken_breasts", lb=0)
    x3 = model.addVar(name="slices_of_pizza", lb=0)

    # Define the objective function
    model.setObjective(4.31 * x0 + 3.65 * x1 + 2.39 * x2 + 8.9 * x3, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(25 * x0 + 22 * x1 + 28 * x2 + 9 * x3 >= 57)
    model.addConstr(2 * x0 + 14 * x2 + 28 * x3 >= 72)
    model.addConstr(25 * x0 + 28 * x2 <= 163)
    model.addConstr(25 * x0 + 9 * x3 <= 299)
    model.addConstr(28 * x2 + 9 * x3 <= 103)
    model.addConstr(25 * x0 + 22 * x1 <= 281)
    model.addConstr(25 * x0 + 22 * x1 + 28 * x2 + 9 * x3 <= 281)
    model.addConstr(27 * x1 + 28 * x3 <= 247)
    model.addConstr(2 * x0 + 27 * x1 <= 321)
    model.addConstr(14 * x2 + 28 * x3 <= 318)
    model.addConstr(2 * x0 + 28 * x3 <= 310)
    model.addConstr(27 * x1 + 14 * x2 <= 93)
    model.addConstr(2 * x0 + 27 * x1 + 14 * x2 + 28 * x3 <= 93)

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("corn cobs: ", x0.varValue)
        print("kale salads: ", x1.varValue)
        print("chicken breasts: ", x2.varValue)
        print("slices of pizza: ", x3.varValue)
    else:
        print("The model is infeasible")

optimize_problem()
```