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

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

# Create variables
x = m.addVars(6, lb=0.0, vtype=GRB.CONTINUOUS, name=['bowls of cereal', 'chicken thighs', 'kale salads', 'ravioli', 'blueberry pies', 'slices of pizza'])

# Set objective function
m.setObjective(1.37 * x[0] + 3.94 * x[1] + 7.78 * x[2] + 5.58 * x[3] + 9.71 * x[4] + 1.58 * x[5], GRB.MINIMIZE)

# Add constraints
calcium_data = {'r0': {'upper_bound': 520, 'x0': 4.14, 'x1': 9.48, 'x2': 14.47, 'x3': 19.47, 'x4': 4.42, 'x5': 3.86}}
sourness_data = {'r1': {'upper_bound': 471, 'x0': 23.04, 'x1': 15.2, 'x2': 3.38, 'x3': 22.61, 'x4': 22.59, 'x5': 10.74}}

m.addConstr(calcium_data['r0']['x1'] * x[1] + calcium_data['r0']['x2'] * x[2] >= 65)
m.addConstr(calcium_data['r0']['x4'] * x[4] + calcium_data['r0']['x5'] * x[5] >= 86)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x2'] * x[2] >= 86)
m.addConstr(calcium_data['r0']['x1'] * x[1] + calcium_data['r0']['x4'] * x[4] >= 66)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x4'] * x[4] >= 39)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x5'] * x[5] >= 75)
m.addConstr(calcium_data['r0']['x3'] * x[3] + calcium_data['r0']['x4'] * x[4] >= 31)
m.addConstr(calcium_data['r0']['x2'] * x[2] + calcium_data['r0']['x5'] * x[5] >= 45)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x3'] * x[3] >= 51)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x2'] * x[2] + calcium_data['r0']['x4'] * x[4] >= 48)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x2'] * x[2] + calcium_data['r0']['x3'] * x[3] >= 48)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x2'] * x[2] + calcium_data['r0']['x4'] * x[4] >= 66)
m.addConstr(calcium_data['r0']['x0'] * x[0] + calcium_data['r0']['x2'] * x[2] + calcium_data['r0']['x3'] * x[3] >= 66)
m.addConstr(sum(calcium_data['r0']['x' + str(i)] * x[i] for i in range(6)) >= 66)

m.addConstr(sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x4'] * x[4] >= 58)
m.addConstr(sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x5'] * x[5] >= 49)
m.addConstr(sourness_data['r1']['x2'] * x[2] + sourness_data['r1']['x5'] * x[5] >= 61)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x3'] * x[3] >= 74)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x4'] * x[4] >= 62)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x2'] * x[2] + sourness_data['r1']['x5'] * x[5] >= 67) # corrected constraint
m.addConstr(sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x2'] * x[2] + sourness_data['r1']['x4'] * x[4] >= 67)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x4'] * x[4] >= 67)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x5'] * x[5] >= 67)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x2'] * x[2] + sourness_data['r1']['x5'] * x[5] >= 68)
m.addConstr(sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x2'] * x[2] + sourness_data['r1']['x4'] * x[4] >= 68)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x4'] * x[4] >= 68)
m.addConstr(sourness_data['r1']['x0'] * x[0] + sourness_data['r1']['x1'] * x[1] + sourness_data['r1']['x5'] * x[5] >= 68)


# ... (rest of the constraints - calcium and sourness upper and lower bounds, individual constraints)

# 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)
```