## Step 1: Define the symbolic representation of the variables
The variables are defined as follows: 
- $x_0$ represents milligrams of calcium
- $x_1$ represents milligrams of vitamin B3
- $x_2$ represents grams of fiber
- $x_3$ represents milligrams of vitamin D
- $x_4$ represents milligrams of vitamin E
- $x_5$ represents milligrams of vitamin A

## Step 2: Convert the objective function into a symbolic representation
The objective function to maximize is:
$9x_0^2 + 3x_0x_1 + 7x_0x_2 + x_0x_3 + 5x_1^2 + 6x_1x_2 + 6x_1x_4 + 8x_2^2 + x_2x_3 + 7x_2x_4 + x_2x_5 + 6x_3^2 + x_3x_4 + 4x_3x_5 + 2x_4x_5 + 3x_5^2 + 5x_1 + 2x_2 + 5x_3 + 3x_4$

## Step 3: List the constraints in symbolic notation
Constraints:
- $28x_0 \leq 435$
- $23x_0 \leq 543$
- $8x_0 \leq 580$
- $13x_1 \leq 435$
- $16x_1 \leq 543$
- $17x_1 \leq 580$
- $22x_2 \leq 435$
- $3x_2 \leq 543$
- $18x_2 \leq 580$
- $5x_3 \leq 435$
- $27x_3 \leq 543$
- $22x_3 \leq 580$
- $20x_4 \leq 435$
- $29x_4 \leq 543$
- $28x_4 \leq 580$
- $31x_5 \leq 435$
- $11x_5 \leq 543$
- $27x_5 \leq 580$
- $28x_0 + 22x_2 \geq 59$
- $28^2x_0^2 + 13^2x_1^2 + 20^2x_4^2 \geq 56$
- $28^2x_0^2 + 22^2x_2^2 + 31^2x_5^2 \geq 56$
- $28x_0 + 13x_1 + 20x_4 \geq 70$
- $28x_0 + 22x_2 + 31x_5 \geq 70$
- $3x_2 + 11x_5 \geq 31$
- $23^2x_0^2 + 29^2x_4^2 \geq 45$
- $16x_1 + 29x_4 \geq 31$
- $16x_1 + 3x_2 \geq 83$
- $16^2x_1^2 + 31^2x_5^2 \geq 50$
- $17^2x_1^2 + 18^2x_2^2 + 22^2x_3^2 \geq 48$
- $28^2x_0^2 + 13^2x_1^2 \leq 85$
- $28^2x_0^2 + 31^2x_5^2 \leq 210$
- $22x_2 + 31x_5 \leq 400$
- $22^2x_2^2 + 22^2x_3^2 \leq 158$
- $22x_2 + 20x_4 \leq 290$
- $13x_1 + 22x_2 \leq 189$
- $28x_0 + 20x_4 \leq 350$
- $28x_0 + 5x_3 \leq 126$
- $20x_4 + 31x_5 \leq 115$
- $13x_1 + 5x_3 \leq 330$
- $28x_0 + 13x_1 + 22x_2 + 5x_3 + 20x_4 + 31x_5 \leq 330$
- $16^2x_1^2 + 31^2x_5^2 \leq 244$
- $23^2x_0^2 + 16^2x_1^2 + 31^2x_5^2 \leq 214$
- $3x_2 + 27x_3 + 11x_5 \leq 354$
- $23x_0 + 16x_1 + 3x_2 + 27x_3 + 29x_4 + 11x_5 \leq 354$
- $8x_0 + 18x_2 \leq 550$
- $27x_3 + 29x_4 \leq 404$
- $8^2x_0^2 + 27^2x_5^2 \leq 297$
- $29x_4 + 27x_5 \leq 188$
- $18^2x_2^2 + 22^2x_3^2 \leq 394$
- $17^2x_1^2 + 22^2x_3^2 \leq 410$
- $8^2x_0^2 + 13^2x_1^2 \leq 104$
- $8x_0 + 13x_1 + 5x_3 \leq 192$
- $8x_0 + 13x_1 + 27x_5 \leq 567$
- $13x_1 + 18x_2 + 27x_5 \leq 193$
- $8^2x_0^2 + 13^2x_1^2 + 20^2x_4^2 \leq 462$
- $13x_1 + 18x_2 + 29x_4 \leq 528$
- $8x_0 + 18x_2 + 29x_4 \leq 574$
- $8x_0 + 29x_4 + 27x_5 \leq 577$
- $13x_1 + 29x_4 + 27x_5 \leq 530$
- $8x_0 + 13x_1 + 18x_2 + 5x_3 + 29x_4 + 27x_5 \leq 530$
- $x_0 \in \mathbb{Z}$
- $x_1 \in \mathbb{Z}$
- $x_2 \in \mathbb{R}$
- $x_3 \in \mathbb{Z}$
- $x_4 \in \mathbb{Z}$
- $x_5 \in \mathbb{R}$

## 4: Implement the optimization problem using Gurobi

```python
import gurobi as gp

# Define the model
m = gp.Model()

# Define the variables
x0 = m.addVar(vtype=gp.GRB.INTEGER, name="x0")  # milligrams of calcium
x1 = m.addVar(vtype=gp.GRB.INTEGER, name="x1")  # milligrams of vitamin B3
x2 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x2")  # grams of fiber
x3 = m.addVar(vtype=gp.GRB.INTEGER, name="x3")  # milligrams of vitamin D
x4 = m.addVar(vtype=gp.GRB.INTEGER, name="x4")  # milligrams of vitamin E
x5 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="x5")  # milligrams of vitamin A

# Objective function
m.setObjective(9*x0**2 + 3*x0*x1 + 7*x0*x2 + x0*x3 + 5*x1**2 + 6*x1*x2 + 6*x1*x4 + 8*x2**2 + x2*x3 + 7*x2*x4 + x2*x5 + 6*x3**2 + x3*x4 + 4*x3*x5 + 2*x4*x5 + 3*x5**2 + 5*x1 + 2*x2 + 5*x3 + 3*x4, gp.GRB.MAXIMIZE)

# Constraints
m.addConstr(28*x0 <= 435)
m.addConstr(23*x0 <= 543)
m.addConstr(8*x0 <= 580)
m.addConstr(13*x1 <= 435)
m.addConstr(16*x1 <= 543)
m.addConstr(17*x1 <= 580)
m.addConstr(22*x2 <= 435)
m.addConstr(3*x2 <= 543)
m.addConstr(18*x2 <= 580)
m.addConstr(5*x3 <= 435)
m.addConstr(27*x3 <= 543)
m.addConstr(22*x3 <= 580)
m.addConstr(20*x4 <= 435)
m.addConstr(29*x4 <= 543)
m.addConstr(28*x4 <= 580)
m.addConstr(31*x5 <= 435)
m.addConstr(11*x5 <= 543)
m.addConstr(27*x5 <= 580)
m.addConstr(28*x0 + 22*x2 >= 59)
m.addConstr(28**2*x0**2 + 13**2*x1**2 + 20**2*x4**2 >= 56)
m.addConstr(28**2*x0**2 + 22**2*x2**2 + 31**2*x5**2 >= 56)
m.addConstr(28*x0 + 13*x1 + 20*x4 >= 70)
m.addConstr(28*x0 + 22*x2 + 31*x5 >= 70)
m.addConstr(3*x2 + 11*x5 >= 31)
m.addConstr(23**2*x0**2 + 29**2*x4**2 >= 45)
m.addConstr(16*x1 + 29*x4 >= 31)
m.addConstr(16*x1 + 3*x2 >= 83)
m.addConstr(16**2*x1**2 + 31**2*x5**2 >= 50)
m.addConstr(17**2*x1**2 + 18**2*x2**2 + 22**2*x3**2 >= 48)
m.addConstr(28**2*x0**2 + 13**2*x1**2 <= 85)
m.addConstr(28**2*x0**2 + 31**2*x5**2 <= 210)
m.addConstr(22*x2 + 31*x5 <= 400)
m.addConstr(22**2*x2**2 + 22**2*x3**2 <= 158)
m.addConstr(22*x2 + 20*x4 <= 290)
m.addConstr(13*x1 + 22*x2 <= 189)
m.addConstr(28*x0 + 20*x4 <= 350)
m.addConstr(28*x0 + 5*x3 <= 126)
m.addConstr(20*x4 + 31*x5 <= 115)
m.addConstr(13*x1 + 5*x3 <= 330)
m.addConstr(28*x0 + 13*x1 + 22*x2 + 5*x3 + 20*x4 + 31*x5 <= 330)
m.addConstr(16**2*x1**2 + 31**2*x5**2 <= 244)
m.addConstr(23**2*x0**2 + 16**2*x1**2 + 31**2*x5**2 <= 214)
m.addConstr(3*x2 + 27*x3 + 11*x5 <= 354)
m.addConstr(23*x0 + 16*x1 + 3*x2 + 27*x3 + 29*x4 + 11*x5 <= 354)
m.addConstr(8*x0 + 18*x2 <= 550)
m.addConstr(27*x3 + 29*x4 <= 404)
m.addConstr(8**2*x0**2 + 27**2*x5**2 <= 297)
m.addConstr(29*x4 + 27*x5 <= 188)
m.addConstr(18**2*x2**2 + 22**2*x3**2 <= 394)
m.addConstr(17**2*x1**2 + 22**2*x3**2 <= 410)
m.addConstr(8**2*x0**2 + 13**2*x1**2 <= 104)
m.addConstr(8*x0 + 13*x1 + 5*x3 <= 192)
m.addConstr(8*x0 + 13*x1 + 27*x5 <= 567)
m.addConstr(13*x1 + 18*x2 + 27*x5 <= 193)
m.addConstr(8**2*x0**2 + 13**2*x1**2 + 20**2*x4**2 <= 462)
m.addConstr(13*x1 + 18*x2 + 29*x4 <= 528)
m.addConstr(8*x0 + 18*x2 + 29*x4 <= 574)
m.addConstr(8*x0 + 29*x4 + 27*x5 <= 577)
m.addConstr(13*x1 + 29*x4 + 27*x5 <= 530)
m.addConstr(8*x0 + 13*x1 + 18*x2 + 5*x3 + 29*x4 + 27*x5 <= 530)

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("x0: ", x0.varValue)
    print("x1: ", x1.varValue)
    print("x2: ", x2.varValue)
    print("x3: ", x3.varValue)
    print("x4: ", x4.varValue)
    print("x5: ", x5.varValue)
else:
    print("No solution found")
```