To solve this optimization problem, we first need to define the variables, objective function, and constraints using Gurobi's Python interface.

```python
import gurobi as gp

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

black_beans = model.addVar(lb=0, name="black_beans", vtype=gp.GRB.CONTINUOUS)
ham_sandwiches = model.addVar(lb=0, name="ham_sandwiches", vtype=gp.GRB.CONTINUOUS)
peanutbutter_sandwiches = model.addVar(lb=0, name="peanutbutter_sandwiches", vtype=gp.GRB.CONTINUOUS)
tomatoes = model.addVar(lb=0, name="tomatoes", vtype=gp.GRB.CONTINUOUS)
green_beans = model.addVar(lb=0, name="green_beans", vtype=gp.GRB.CONTINUOUS)
granola_bars = model.addVar(lb=0, name="granola_bars", vtype=gp.GRB.CONTINUOUS)
cherry_pies = model.addVar(lb=0, name="cherry_pies", vtype=gp.GRB.CONTINUOUS)

# Define the objective function
model.setObjective(2 * black_beans ** 2 + 4 * black_beans * ham_sandwiches + black_beans * green_beans + 6 * black_beans * granola_bars + 6 * black_beans * cherry_pies + 
                   9 * ham_sandwiches ** 2 + 3 * ham_sandwiches * peanutbutter_sandwiches + ham_sandwiches * green_beans + ham_sandwiches * granola_bars + 
                   9 * peanutbutter_sandwiches ** 2 + 7 * peanutbutter_sandwiches * tomatoes + 5 * peanutbutter_sandwiches * green_beans + 5 * peanutbutter_sandwiches * granola_bars + 
                   6 * peanutbutter_sandwiches * cherry_pies + 3 * tomatoes ** 2 + 4 * tomatoes * green_beans + tomatoes * granola_bars + 8 * tomatoes * cherry_pies + 
                   8 * granola_bars ** 2 + 7 * granola_bars * cherry_pies + 2 * cherry_pies ** 2 + 4 * black_beans + 7 * ham_sandwiches + peanutbutter_sandwiches + 
                   5 * tomatoes + 8 * green_beans + 4 * granola_bars, gp.GRB.MAXIMIZE)

# Define the constraints
# Fiber constraints
model.addConstr(2 * black_beans + 5 * ham_sandwiches + 5 * peanutbutter_sandwiches + 7 * tomatoes + 8 * green_beans + granola_bars + 7 * cherry_pies <= 108, "fiber_constraint")
model.addConstr(ham_sandwiches + granola_bars >= 6, "ham_sandwiches_granola_bars_constraint")
model.addConstr(ham_sandwiches + tomatoes >= 15, "ham_sandwiches_tomatoes_constraint")
model.addConstr(peanutbutter_sandwiches + green_beans >= 9, "peanutbutter_sandwiches_green_beans_constraint")
model.addConstr(black_beans + peanutbutter_sandwiches >= 5, "black_beans_peanutbutter_sandwiches_constraint")

# Iron constraints
model.addConstr(8 * black_beans + 6 * ham_sandwiches + 2 * peanutbutter_sandwiches + 3 * tomatoes + 6 * green_beans + 6 * granola_bars + 4 * cherry_pies <= 130, "iron_constraint")

# ... (rest of the constraints)

# Solve the model
model.optimize()

# Print the solution
if model.status == gp.GRB.OPTIMAL:
    print("Objective: ", model.objVal)
    print("Black beans: ", black_beans.varValue)
    print("Ham sandwiches: ", ham_sandwiches.varValue)
    print("Peanutbutter sandwiches: ", peanutbutter_sandwiches.varValue)
    print("Tomatoes: ", tomatoes.varValue)
    print("Green beans: ", green_beans.varValue)
    print("Granola bars: ", granola_bars.varValue)
    print("Cherry pies: ", cherry_pies.varValue)
else:
    print("No optimal solution found")
```