## Step 1: Define the symbolic representation of the variables
The variables are 'cornichons', 'oranges', and 'chicken drumsticks', which can be represented symbolically as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the objective function into symbolic notation
The objective function to maximize is $1 \cdot x_0^2 + 2 \cdot x_0 \cdot x_1 + 1 \cdot x_0 \cdot x_2 + 8 \cdot x_1^2 + 3 \cdot x_1 \cdot x_2 + 6 \cdot x_2^2 + 5 \cdot x_0 + 7 \cdot x_1 + 2 \cdot x_2$.

## 3: List the constraints in symbolic notation
The constraints are:
- $6x_0 + 9x_1 + 2x_2 \leq 256$ (grams of fat)
- $x_0 + 25x_1 + 9x_2 \leq 301$ (grams of fiber)
- $21x_0 + 26x_1 + 13x_2 \leq 211$ (umami index)
- $6x_0^2 + 9x_1^2 + 2x_2^2 \geq 51$ (at least 51 grams of fat from squares)
- $26x_1 + 13x_2 \geq 27$ (umami index from oranges and chicken drumsticks)
- $6x_0 + 2x_2 \leq 210$ (at most 210 grams of fat from cornichons and chicken drumsticks)
- $9x_1 + 2x_2 \leq 117$ (at most 117 grams of fat from oranges and chicken drumsticks)
- $6x_0 + 9x_1 + 2x_2 \leq 184$ (at most 184 grams of fat from all)
- $6x_0 + 9x_1 + 2x_2 \geq 0$ and $6x_0 + 9x_1 + 2x_2 \leq 184$ implies $0 \leq 6x_0 + 9x_1 + 2x_2 \leq 184$ (up to 184 grams of fat from all, already included)
- $x_0 + 25x_1 \leq 133$ (at most 133 grams of fiber from cornichons and oranges)
- $25x_1^2 + 9x_2^2 \leq 128$ (at most 128 grams of fiber from oranges and chicken drumsticks squared)
- $x_0 + 25x_1 + 9x_2 \leq 128$ (at most 128 grams of fiber from all)
- $21x_0 + 13x_2 \leq 103$ (umami index from cornichons and chicken drumsticks)
- $26x_1 + 13x_2 \leq 75$ (umami index from oranges and chicken drumsticks)
- $21^2x_0^2 + 26^2x_1^2 + 13^2x_2^2 \leq 174$ (umami index from squares)
- $21x_0 + 26x_1 + 13x_2 \leq 174$ (umami index from all)

## 4: Create the symbolic representation dictionary
```json
{
    'sym_variables': [('x0', 'cornichons'), ('x1', 'oranges'), ('x2', 'chicken drumsticks')],
    'objective_function': '1*x0^2 + 2*x0*x1 + 1*x0*x2 + 8*x1^2 + 3*x1*x2 + 6*x2^2 + 5*x0 + 7*x1 + 2*x2',
    'constraints': [
        '6*x0 + 9*x1 + 2*x2 <= 256',
        'x0 + 25*x1 + 9*x2 <= 301',
        '21*x0 + 26*x1 + 13*x2 <= 211',
        '6*x0^2 + 9*x1^2 + 2*x2^2 >= 51',
        '26*x1 + 13*x2 >= 27',
        '6*x0 + 2*x2 <= 210',
        '9*x1 + 2*x2 <= 117',
        '6*x0 + 9*x1 + 2*x2 <= 184',
        'x0 + 25*x1 <= 133',
        '25*x1^2 + 9*x2^2 <= 128',
        'x0 + 25*x1 + 9*x2 <= 128',
        '21*x0 + 13*x2 <= 103',
        '26*x1 + 13*x2 <= 75',
        '21^2*x0^2 + 26^2*x1^2 + 13^2*x2^2 <= 174',
        '21*x0 + 26*x1 + 13*x2 <= 174'
    ]
}
```

## Step 5: Write the Gurobi code
```python
import gurobi

def optimization_problem():
    model = gurobi.Model()

    # Define variables
    cornichons = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="cornichons")
    oranges = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="oranges")
    chicken_drumsticks = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="chicken_drumsticks")

    # Objective function
    model.setObjective(1 * cornichons**2 + 2 * cornichons * oranges + 1 * cornichons * chicken_drumsticks + 
                      8 * oranges**2 + 3 * oranges * chicken_drumsticks + 6 * chicken_drumsticks**2 + 
                      5 * cornichons + 7 * oranges + 2 * chicken_drumsticks, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(6 * cornichons + 9 * oranges + 2 * chicken_drumsticks <= 256)
    model.addConstr(cornichons + 25 * oranges + 9 * chicken_drumsticks <= 301)
    model.addConstr(21 * cornichons + 26 * oranges + 13 * chicken_drumsticks <= 211)
    model.addConstr(6 * cornichons**2 + 9 * oranges**2 + 2 * chicken_drumsticks**2 >= 51)
    model.addConstr(26 * oranges + 13 * chicken_drumsticks >= 27)
    model.addConstr(6 * cornichons + 2 * chicken_drumsticks <= 210)
    model.addConstr(9 * oranges + 2 * chicken_drumsticks <= 117)
    model.addConstr(6 * cornichons + 9 * oranges + 2 * chicken_drumsticks <= 184)
    model.addConstr(cornichons + 25 * oranges <= 133)
    model.addConstr(25 * oranges**2 + 9 * chicken_drumsticks**2 <= 128)
    model.addConstr(cornichons + 25 * oranges + 9 * chicken_drumsticks <= 128)
    model.addConstr(21 * cornichons + 13 * chicken_drumsticks <= 103)
    model.addConstr(26 * oranges + 13 * chicken_drumsticks <= 75)
    model.addConstr(441 * cornichons**2 + 676 * oranges**2 + 169 * chicken_drumsticks**2 <= 174)
    model.addConstr(21 * cornichons + 26 * oranges + 13 * chicken_drumsticks <= 174)

    # Solve the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.Status.OPTIMAL:
        print("Objective: ", model.objVal)
        print("cornichons: ", cornichons.varValue)
        print("oranges: ", oranges.varValue)
        print("chicken_drumsticks: ", chicken_drumsticks.varValue)
    else:
        print("The model is infeasible")

optimization_problem()
```