## Step 1: Define the optimization problem
The problem is to maximize the objective function: $2 \times \text{milligrams of iron} + 5 \times (\text{milligrams of vitamin B2} + 5 \times \text{milligrams of potassium} + 2 \times \text{milligrams of vitamin B4} + 4 \times \text{grams of fiber})$.

## Step 2: List all the constraints
The constraints are:
- Cognitive performance index for milligrams of iron: $3$
- Digestive support index for milligrams of iron: $8$
- Cognitive performance index of milligrams of vitamin B2: $3$
- Digestive support index of milligrams of vitamin B2: $2$
- Cognitive performance index for milligrams of potassium: $6$
- Digestive support index for milligrams of potassium: $4$
- Cognitive performance index of milligrams of vitamin B4: $6$
- Digestive support index for milligrams of vitamin B4: $5$
- Cognitive performance index of grams of fiber: $6$
- Digestive support index for grams of fiber: $1$

## 3: Formulate the constraints
Given resources/attributes:
$r0 = {'description': 'cognitive performance index', 'upper_bound': 153, 'x0': 3, 'x1': 3, 'x2': 6, 'x3': 6, 'x4': 6}$
$r1 = {'description': 'digestive support index', 'upper_bound': 88, 'x0': 8, 'x1': 2, 'x2': 4, 'x3': 5, 'x4': 1}$

## 4: Translate into Gurobi code
```python
import gurobi

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

# Define the variables
iron = model.addVar(name="iron", lb=0)  # No lower bound specified
vitamin_B2 = model.addVar(name="vitamin_B2", lb=0, integrality=1)  # Integer
potassium = model.addVar(name="potassium", lb=0, integrality=1)  # Integer
vitamin_B4 = model.addVar(name="vitamin_B4", lb=0)  # No lower bound specified
fiber = model.addVar(name="fiber", lb=0, integrality=1)  # Integer

# Objective function
model.setObjective(2 * iron + 5 * (vitamin_B2 + 5 * potassium + 2 * vitamin_B4 + 4 * fiber), gurobi.GRB.MAXIMIZE)

# Constraints
# Cognitive performance index constraints
model.addConstr(3 * iron + 3 * vitamin_B2 + 6 * potassium + 6 * vitamin_B4 + 6 * fiber <= 153)

# Digestive support index constraints
model.addConstr(8 * iron + 2 * vitamin_B2 + 4 * potassium + 5 * vitamin_B4 + fiber <= 88)

# Individual cognitive performance index constraints
model.addConstr(3 * iron <= r0['x0'] * iron)
model.addConstr(3 * vitamin_B2 <= r0['x1'] * vitamin_B2)
model.addConstr(6 * potassium <= r0['x2'] * potassium)
model.addConstr(6 * vitamin_B4 <= r0['x3'] * vitamin_B4)
model.addConstr(6 * fiber <= r0['x4'] * fiber)

# Individual digestive support index constraints
model.addConstr(8 * iron <= r1['x0'] * iron)
model.addConstr(2 * vitamin_B2 <= r1['x1'] * vitamin_B2)
model.addConstr(4 * potassium <= r1['x2'] * potassium)
model.addConstr(5 * vitamin_B4 <= r1['x3'] * vitamin_B4)
model.addConstr(fiber <= r1['x4'] * fiber)

# Combined cognitive performance index constraints
model.addConstr(3 * iron + 6 * vitamin_B4 >= 29)
model.addConstr(3 * iron + 6 * potassium >= 11)
model.addConstr(6 * vitamin_B4 + 6 * fiber >= 13)
model.addConstr(3 * iron + 3 * vitamin_B2 >= 21)
model.addConstr(3 * iron + 3 * vitamin_B2 + 6 * potassium >= 17)
model.addConstr(3 * vitamin_B2 + 6 * potassium + 6 * fiber >= 17)
model.addConstr(3 * iron + 6 * vitamin_B4 + 6 * fiber >= 17)
model.addConstr(3 * iron + 6 * potassium + 6 * vitamin_B4 >= 17)
model.addConstr(3 * iron + 3 * vitamin_B2 + 6 * fiber >= 17)
model.addConstr(6 * potassium + 6 * vitamin_B4 + 6 * fiber >= 17)

# Additional constraints
model.addConstr(2 * iron + 5 * vitamin_B2 >= 0)
model.addConstr(3 * potassium + 3 * vitamin_B4 <= 143)
model.addConstr(3 * iron + 3 * vitamin_B2 <= 140)
model.addConstr(3 * iron + 6 * fiber <= 136)
model.addConstr(6 * potassium + 6 * fiber <= 141)
model.addConstr(3 * vitamin_B2 + 6 * potassium + 6 * fiber <= 105)
model.addConstr(6 * potassium + 6 * vitamin_B4 + 6 * fiber <= 49)
model.addConstr(3 * iron + 6 * potassium + 6 * fiber <= 41)
model.addConstr(3 * iron + 3 * vitamin_B2 + 6 * potassium + 6 * vitamin_B4 + 6 * fiber <= 41)

# Digestive support index constraints
model.addConstr(8 * iron + 4 * potassium <= 53)
model.addConstr(4 * potassium + fiber <= 86)
model.addConstr(8 * iron + fiber <= 72)
model.addConstr(8 * iron + 2 * vitamin_B2 <= 31)
model.addConstr(5 * vitamin_B4 + fiber <= 30)
model.addConstr(8 * iron + 4 * potassium + fiber <= 27)
model.addConstr(8 * iron + 2 * vitamin_B2 + 4 * potassium + 5 * vitamin_B4 + fiber <= 27)

# Optimize
model.optimize()

# Print the results
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objVal)
    print("Iron: ", iron.varValue)
    print("Vitamin B2: ", vitamin_B2.varValue)
    print("Potassium: ", potassium.varValue)
    print("Vitamin B4: ", vitamin_B4.varValue)
    print("Fiber: ", fiber.varValue)
else:
    print("No optimal solution found")
```