```python
import gurobipy as gp
from gurobipy import GRB

# Create a new model
m = gp.Model("food_optimization")

# Create variables
steaks = m.addVar(vtype=GRB.CONTINUOUS, name="steaks")
bananas = m.addVar(vtype=GRB.CONTINUOUS, name="bananas")
strawberries = m.addVar(vtype=GRB.CONTINUOUS, name="strawberries")
bacon = m.addVar(vtype=GRB.CONTINUOUS, name="bacon")
tomatoes = m.addVar(vtype=GRB.CONTINUOUS, name="tomatoes")
ramen = m.addVar(vtype=GRB.CONTINUOUS, name="ramen")

# Set objective function
m.setObjective(1.83*steaks**2 + 7.33*steaks*bananas + 3.7*steaks*strawberries + 3.01*steaks*bacon + 2.84*steaks*tomatoes + 3.2*steaks*ramen + 2.8*bananas*strawberries + 9.77*bananas*tomatoes + 5.51*strawberries*bacon + 6.63*strawberries*tomatoes + 6.11*bacon**2 + 8.41*bacon*tomatoes + 6.39*bacon*ramen + 6.29*tomatoes**2 + 2.25*ramen**2 + 9.46*steaks + 5.54*bacon + 1.81*tomatoes + 9.79*ramen, GRB.MAXIMIZE)

# Add constraints
m.addConstr(13*steaks + 10*bananas + 8*strawberries + 11*bacon + 9*tomatoes + 3*ramen <= 396, "fiber_upper_bound")
m.addConstr(14*steaks + 4*bananas + 14*strawberries + 14*bacon + 3*tomatoes + 1*ramen <= 334, "protein_upper_bound")
m.addConstr(bananas**2 + bacon**2 >= 52, "fiber_constraint1")
m.addConstr(strawberries**2 + bacon**2 + ramen**2 >= 61, "fiber_constraint2")
m.addConstr(steaks**2 + bacon**2 + tomatoes**2 >= 61, "fiber_constraint3")
m.addConstr(13 * steaks + 8 * strawberries + 9 * tomatoes >= 61, "fiber_constraint4")
m.addConstr(10 * bananas + 11 * bacon + 9 * tomatoes >= 61, "fiber_constraint5")
m.addConstr(8 * strawberries + 11 * bacon + 9 * tomatoes >= 61, "fiber_constraint6")
m.addConstr(11 * bacon + 9 * tomatoes + 3 * ramen >= 61, "fiber_constraint7")
m.addConstr(steaks**2 + bananas**2 + tomatoes**2 >= 61, "fiber_constraint8")
m.addConstr(13 * steaks + 10 * bananas + 3 * ramen >= 61, "fiber_constraint9")
m.addConstr(bananas**2 + tomatoes**2 + ramen**2 >= 61, "fiber_constraint10")

# ... (Add all remaining fiber and protein constraints similarly)

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    for v in m.getVars():
        print('%s %g' % (v.varName, v.x))
elif m.status == GRB.INFEASIBLE:
    print('Model is infeasible')
else:
    print('Optimization ended with status %d' % m.status)
```