## Step 1: Define the symbolic representation of the variables
The variables are ['milligrams of vitamin D', 'milligrams of vitamin B7', 'milligrams of magnesium', 'milligrams of zinc', 'milligrams of vitamin B2']. Let's denote them as $x_1, x_2, x_3, x_4, x_5$ respectively.

## Step 2: Convert the natural language objects into symbolic notation
The symbolic representation of the variables is:
- $x_1$ : milligrams of vitamin D
- $x_2$ : milligrams of vitamin B7
- $x_3$ : milligrams of magnesium
- $x_4$ : milligrams of zinc
- $x_5$ : milligrams of vitamin B2

## 3: Define the objective function in symbolic notation
The objective function to maximize is $5.67x_1 + 8.95x_2 + 7.6x_3 + 4.9x_4 + 4.43x_5$.

## 4: List the constraints in symbolic notation
Constraints:
1. $x_2 + x_4 \geq 9$
2. $x_2 + x_3 + x_4 \geq 6$
3. $x_2 + x_4 + x_5 \geq 6$
4. $x_1 + x_4 + x_5 \geq 6$
5. $x_2 + x_3 + x_5 \geq 6$
6. $x_2 + x_3 + x_4 \geq 8$
7. $x_2 + x_4 + x_5 \geq 8$
8. $x_1 + x_4 + x_5 \geq 8$
9. $x_2 + x_3 + x_5 \geq 8$
10. $x_2 + x_3 + x_4 \geq 6$
11. $x_2 + x_4 + x_5 \geq 6$
12. $x_1 + x_4 + x_5 \geq 6$
13. $x_2 + x_3 + x_5 \geq 6$
14. $x_2 + x_3 + x_4 \geq 12$
15. $x_2 + x_4 + x_5 \geq 12$
16. $x_1 + x_4 + x_5 \geq 12$
17. $x_2 + x_3 + x_5 \geq 12$
18. $x_4 + x_5 \leq 58$
19. $x_3 + x_4 \leq 54$
20. $x_1 + x_4 \leq 31$
21. $x_1 + x_3 \leq 41$
22. $x_2 + x_3 \leq 48$
23. $x_2 + x_3 + x_5 \leq 35$
24. $x_1 + x_2 + x_3 \leq 44$
25. $x_1 + x_2 + x_5 \leq 50$
26. $x_3 + x_4 + x_5 \leq 45$
27. $x_2 + x_4 + x_5 \leq 33$
28. $x_1 + x_2 + x_3 + x_4 + x_5 \leq 33$

## 5: Define variable types
- $x_1$ : Continuous
- $x_2$ : Integer
- $x_3$ : Continuous
- $x_4$ : Integer
- $x_5$ : Integer

## 6: Write the Gurobi code
```python
import gurobi

# Create a new model
model = gurobi.Model()

# Define variables
x1 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="x1")  # milligrams of vitamin D
x2 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, vtype='I', name="x2")  # milligrams of vitamin B7
x3 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="x3")  # milligrams of magnesium
x4 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, vtype='I', name="x4")  # milligrams of zinc
x5 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, vtype='I', name="x5")  # milligrams of vitamin B2

# Objective function
model.setObjective(5.67 * x1 + 8.95 * x2 + 7.6 * x3 + 4.9 * x4 + 4.43 * x5, gurobi.GRB.MAXIMIZE)

# Constraints
model.addConstr(x2 + x4 >= 9)
model.addConstr(x2 + x3 + x4 >= 6)
model.addConstr(x2 + x4 + x5 >= 6)
model.addConstr(x1 + x4 + x5 >= 6)
model.addConstr(x2 + x3 + x5 >= 6)
model.addConstr(x2 + x3 + x4 >= 8)
model.addConstr(x2 + x4 + x5 >= 8)
model.addConstr(x1 + x4 + x5 >= 8)
model.addConstr(x2 + x3 + x5 >= 8)
model.addConstr(x2 + x3 + x4 >= 6)
model.addConstr(x2 + x4 + x5 >= 6)
model.addConstr(x1 + x4 + x5 >= 6)
model.addConstr(x2 + x3 + x5 >= 6)
model.addConstr(x2 + x3 + x4 >= 12)
model.addConstr(x2 + x4 + x5 >= 12)
model.addConstr(x1 + x4 + x5 >= 12)
model.addConstr(x2 + x3 + x5 >= 12)
model.addConstr(x4 + x5 <= 58)
model.addConstr(x3 + x4 <= 54)
model.addConstr(x1 + x4 <= 31)
model.addConstr(x1 + x3 <= 41)
model.addConstr(x2 + x3 <= 48)
model.addConstr(x2 + x3 + x5 <= 35)
model.addConstr(x1 + x2 + x3 <= 44)
model.addConstr(x1 + x2 + x5 <= 50)
model.addConstr(x3 + x4 + x5 <= 45)
model.addConstr(x2 + x4 + x5 <= 33)
model.addConstr(x1 + x2 + x3 + x4 + x5 <= 33)

# Optimize
model.optimize()

# Print solution
if model.status == gurobi.GRB.Status.OPTIMAL:
    print("Objective: ", model.objVal)
    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")
```

## 7: Symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x1', 'milligrams of vitamin D'),
        ('x2', 'milligrams of vitamin B7'),
        ('x3', 'milligrams of magnesium'),
        ('x4', 'milligrams of zinc'),
        ('x5', 'milligrams of vitamin B2')
    ],
    'objective_function': '5.67*x1 + 8.95*x2 + 7.6*x3 + 4.9*x4 + 4.43*x5',
    'constraints': [
        'x2 + x4 >= 9',
        'x2 + x3 + x4 >= 6',
        'x2 + x4 + x5 >= 6',
        'x1 + x4 + x5 >= 6',
        'x2 + x3 + x5 >= 6',
        'x2 + x3 + x4 >= 8',
        'x2 + x4 + x5 >= 8',
        'x1 + x4 + x5 >= 8',
        'x2 + x3 + x5 >= 8',
        'x2 + x3 + x4 >= 6',
        'x2 + x4 + x5 >= 6',
        'x1 + x4 + x5 >= 6',
        'x2 + x3 + x5 >= 6',
        'x2 + x3 + x4 >= 12',
        'x2 + x4 + x5 >= 12',
        'x1 + x4 + x5 >= 12',
        'x2 + x3 + x5 >= 12',
        'x4 + x5 <= 58',
        'x3 + x4 <= 54',
        'x1 + x4 <= 31',
        'x1 + x3 <= 41',
        'x2 + x3 <= 48',
        'x2 + x3 + x5 <= 35',
        'x1 + x2 + x3 <= 44',
        'x1 + x2 + x5 <= 50',
        'x3 + x4 + x5 <= 45',
        'x2 + x4 + x5 <= 33',
        'x1 + x2 + x3 + x4 + x5 <= 33'
    ]
}
```