## Step 1: Define the optimization problem and its components
The problem is to minimize the objective function $9 \times \text{steaks} + 6 \times \text{slices of pizza} + 1 \times \text{chicken drumsticks} + 3 \times \text{corn cobs}$ subject to various constraints on iron content and sourness index from different food items.

## 2: List all the constraints
1. $\text{steaks} \times 2.73 + \text{slices of pizza} \times 6.21 + \text{chicken drumsticks} \times 8.01 + \text{corn cobs} \times 6.38 \leq 178$ (iron content)
2. $\text{steaks} \times 2.53 + \text{slices of pizza} \times 1.96 + \text{chicken drumsticks} \times 0.64 + \text{corn cobs} \times 2.58 \leq 220$ (sourness index)
3. $\text{chicken drumsticks} \times 8.01 + \text{corn cobs} \times 6.38 \geq 16$ (iron from chicken and corn)
4. $\text{steaks} \times 2.73 + \text{chicken drumsticks} \times 8.01 \geq 28$ (iron from steaks and chicken)
5. $\text{steaks} \times 2.73 + \text{slices of pizza} \times 6.21 \geq 14$ (iron from steaks and pizza)
6. $\text{slices of pizza} \times 6.21 + \text{chicken drumsticks} \times 8.01 \geq 26$ (iron from pizza and chicken)
7. $\text{steaks} \times 2.73 + \text{corn cobs} \times 6.38 \geq 29$ (iron from steaks and corn)
8. $\text{steaks} \times 2.73 + \text{slices of pizza} \times 6.21 + \text{chicken drumsticks} \times 8.01 + \text{corn cobs} \times 6.38 \geq 29$ (total iron)
9. $\text{steaks} \times 2.53 + \text{corn cobs} \times 2.58 \geq 32$ (sourness from steaks and corn)
10. $\text{chicken drumsticks} \times 0.64 + \text{corn cobs} \times 2.58 \geq 21$ (sourness from chicken and corn)
11. $\text{steaks} \times 2.53 + \text{slices of pizza} \times 1.96 \geq 25$ (sourness from steaks and pizza)
12. $\text{slices of pizza} \times 1.96 + \text{corn cobs} \times 2.58 \geq 23$ (sourness from pizza and corn)
13. $\text{slices of pizza} \times 1.96 + \text{chicken drumsticks} \times 0.64 \geq 25$ (sourness from pizza and chicken)
14. $\text{steaks} \times 2.53 + \text{slices of pizza} \times 1.96 + \text{chicken drumsticks} \times 0.64 + \text{corn cobs} \times 2.58 \geq 25$ (total sourness)
15. $2 \times \text{steaks} - 7 \times \text{corn cobs} \geq 0$ (steaks and corn relationship)
16. $\text{steaks} \times 2.73 + \text{slices of pizza} \times 6.21 \leq 139$ (iron limit from steaks and pizza)
17. $\text{slices of pizza} \times 6.21 + \text{corn cobs} \times 6.38 \leq 49$ (iron limit from pizza and corn)
18. $\text{steaks} \times 2.53 + \text{slices of pizza} \times 1.96 \leq 107$ (sourness limit from steaks and pizza)
19. $\text{chicken drumsticks} \times 0.64 + \text{corn cobs} \times 2.58 \leq 91$ (sourness limit from chicken and corn)

## 3: Formulate the problem in Gurobi
We will use Gurobi's Python interface to formulate and solve this problem.

```python
import gurobi as gp

# Define the model
m = gp.Model("optimization_problem")

# Define the variables
steaks = m.addVar(name="steaks", lb=0)
slices_of_pizza = m.addVar(name="slices_of_pizza", lb=0)
chicken_drumsticks = m.addVar(name="chicken_drumsticks", lb=0)
corn_cobs = m.addVar(name="corn_cobs", lb=0)

# Objective function
m.setObjective(9 * steaks + 6 * slices_of_pizza + chicken_drumsticks + 3 * corn_cobs, gp.GRB.MINIMIZE)

# Constraints
m.addConstr(2.73 * steaks + 6.21 * slices_of_pizza + 8.01 * chicken_drumsticks + 6.38 * corn_cobs <= 178)
m.addConstr(2.53 * steaks + 1.96 * slices_of_pizza + 0.64 * chicken_drumsticks + 2.58 * corn_cobs <= 220)
m.addConstr(8.01 * chicken_drumsticks + 6.38 * corn_cobs >= 16)
m.addConstr(2.73 * steaks + 8.01 * chicken_drumsticks >= 28)
m.addConstr(2.73 * steaks + 6.21 * slices_of_pizza >= 14)
m.addConstr(6.21 * slices_of_pizza + 8.01 * chicken_drumsticks >= 26)
m.addConstr(2.73 * steaks + 6.38 * corn_cobs >= 29)
m.addConstr(2.73 * steaks + 6.21 * slices_of_pizza + 8.01 * chicken_drumsticks + 6.38 * corn_cobs >= 29)
m.addConstr(2.53 * steaks + 2.58 * corn_cobs >= 32)
m.addConstr(0.64 * chicken_drumsticks + 2.58 * corn_cobs >= 21)
m.addConstr(2.53 * steaks + 1.96 * slices_of_pizza >= 25)
m.addConstr(1.96 * slices_of_pizza + 2.58 * corn_cobs >= 23)
m.addConstr(1.96 * slices_of_pizza + 0.64 * chicken_drumsticks >= 25)
m.addConstr(2.53 * steaks + 1.96 * slices_of_pizza + 0.64 * chicken_drumsticks + 2.58 * corn_cobs >= 25)
m.addConstr(2 * steaks - 7 * corn_cobs >= 0)
m.addConstr(2.73 * steaks + 6.21 * slices_of_pizza <= 139)
m.addConstr(6.21 * slices_of_pizza + 6.38 * corn_cobs <= 49)
m.addConstr(2.53 * steaks + 1.96 * slices_of_pizza <= 107)
m.addConstr(0.64 * chicken_drumsticks + 2.58 * corn_cobs <= 91)

# Solve the model
m.optimize()

# Print the solution
if m.status == gp.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Steaks: ", steaks.varValue)
    print("Slices of Pizza: ", slices_of_pizza.varValue)
    print("Chicken Drumsticks: ", chicken_drumsticks.varValue)
    print("Corn Cobs: ", corn_cobs.varValue)
else:
    print("The model is infeasible")
```