To solve this optimization problem using Gurobi, we first need to define the variables, the objective function, and then add all the constraints as described. The problem involves maximizing an objective function subject to several constraints on the healthiness rating and sourness index of the variables 'rotisserie chickens', 'eggs', and 'granola bars'.

Let's denote:
- \(x_0\) as 'rotisserie chickens',
- \(x_1\) as 'eggs',
- \(x_2\) as 'granola bars'.

The objective function to maximize is:
\[3x_0^2 + 2x_0x_1 + 7x_0x_2 + x_1^2 + 2x_1x_2 + x_2^2 + x_0 + 9x_1 + 7x_2\]

The constraints are:
1. \(10x_0 + 3x_1 + 11x_2 \geq 69\)
2. \(9x_1 + 11x_2 \geq 65\)
3. \(8x_0 + 9x_2 \geq 16\)
4. \(3x_1 + 11x_2 \leq 184\)
5. \(10x_0 + 3x_1 \leq 209\)
6. \(10x_0 + 3x_1 + 11x_2 \leq 209\)
7. \(64x_0^2 + 81x_2^2 \leq 87\)
8. \(81x_1^2 + 81x_2^2 \leq 82\)
9. \(8x_0 + 9x_1 + 9x_2 \leq 82\)

And the given attributes:
- \(r0\): {'description': 'healthiness rating', 'upper_bound': 221, 'x0': 10, 'x1': 3, 'x2': 11}
- \(r1\): {'description': 'sourness index', 'upper_bound': 127, 'x0': 8, 'x1': 9, 'x2': 9}

Here is the Gurobi code to solve this problem:

```python
import gurobi

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

    # Define variables
    x0 = model.addVar(lb=-gurobi.GRB.INFINITY, name="rotisserie_chickens")
    x1 = model.addVar(lb=-gurobi.GRB.INFINITY, name="eggs", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(lb=-gurobi.GRB.INFINITY, name="granola_bars")

    # Define objective function
    model.setObjective(3*x0**2 + 2*x0*x1 + 7*x0*x2 + x1**2 + 2*x1*x2 + x2**2 + x0 + 9*x1 + 7*x2, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(10*x0 + 3*x1 + 11*x2 >= 69)
    model.addConstr(9*x1 + 11*x2 >= 65)
    model.addConstr(8*x0 + 9*x2 >= 16)
    model.addConstr(3*x1 + 11*x2 <= 184)
    model.addConstr(10*x0 + 3*x1 <= 209)
    model.addConstr(10*x0 + 3*x1 + 11*x2 <= 209)
    model.addConstr(64*x0**2 + 81*x2**2 <= 87)
    model.addConstr(81*x1**2 + 81*x2**2 <= 82)
    model.addConstr(8*x0 + 9*x1 + 9*x2 <= 82)

    # Update model
    model.update()

    # Solve model
    model.optimize()

    # Print solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Objective: ", model.objVal)
        print("rotisserie_chickens: ", x0.varValue)
        print("eggs: ", x1.varValue)
        print("granola_bars: ", x2.varValue)
    else:
        print("No optimal solution found")

solve_optimization_problem()
```