```json
{
  "sym_variables": [
    ("x0", "hot dogs"),
    ("x1", "cornichons"),
    ("x2", "strawberries")
  ],
  "objective_function": "7*x0 + 6*x1 + 8*x2",
  "constraints": [
    "22*x0 + 9*x2 >= 53",
    "3*x1 + 9*x2 >= 34",
    "22*x0 + 3*x1 >= 35",
    "22*x0 + 3*x1 + 9*x2 >= 35",
    "23*x0 + 19*x1 >= 26",
    "23*x0 + 7*x2 >= 46",
    "23*x0 + 19*x1 + 7*x2 >= 46",
    "7*x0 - 6*x2 >= 0",
    "5*x0 - 3*x1 >= 0",
    "22*x0 + 9*x2 <= 127",
    "3*x1 + 9*x2 <= 94",
    "22*x0 + 3*x1 + 9*x2 <= 116",
    "23*x0 + 19*x1 + 7*x2 <= 96",
    "22*x0 + 23*x0 <= 207", 
    "19*x1 + 7*x2 <= 139"
  ]
}
```

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

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

# Create variables
hot_dogs = m.addVar(vtype=GRB.CONTINUOUS, name="hot_dogs")
cornichons = m.addVar(vtype=GRB.CONTINUOUS, name="cornichons")
strawberries = m.addVar(vtype=GRB.CONTINUOUS, name="strawberries")


# Set objective function
m.setObjective(7 * hot_dogs + 6 * cornichons + 8 * strawberries, GRB.MINIMIZE)

# Add constraints
m.addConstr(22 * hot_dogs + 9 * strawberries >= 53, "protein_hot_dogs_strawberries")
m.addConstr(3 * cornichons + 9 * strawberries >= 34, "protein_cornichons_strawberries")
m.addConstr(22 * hot_dogs + 3 * cornichons >= 35, "protein_hot_dogs_cornichons")
m.addConstr(22 * hot_dogs + 3 * cornichons + 9 * strawberries >= 35, "protein_all")
m.addConstr(23 * hot_dogs + 19 * cornichons >= 26, "fat_hot_dogs_cornichons")
m.addConstr(23 * hot_dogs + 7 * strawberries >= 46, "fat_hot_dogs_strawberries")
m.addConstr(23 * hot_dogs + 19 * cornichons + 7 * strawberries >= 46, "fat_all")
m.addConstr(7 * hot_dogs - 6 * strawberries >= 0, "hot_dogs_strawberries_relation")
m.addConstr(5 * hot_dogs - 3 * cornichons >= 0, "hot_dogs_cornichons_relation")
m.addConstr(22 * hot_dogs + 9 * strawberries <= 127, "protein_hot_dogs_strawberries_upper")
m.addConstr(3 * cornichons + 9 * strawberries <= 94, "protein_cornichons_strawberries_upper")
m.addConstr(22 * hot_dogs + 3 * cornichons + 9 * strawberries <= 116, "protein_all_upper")
m.addConstr(23 * hot_dogs + 19 * cornichons + 7 * strawberries <= 96, "fat_all_upper")

# Resource constraints
m.addConstr(22 * hot_dogs + 23 * hot_dogs <= 207, "resource_r0")
m.addConstr(19 * cornichons + 7 * strawberries <= 139, "resource_r1")


# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('hot_dogs:', hot_dogs.x)
    print('cornichons:', cornichons.x)
    print('strawberries:', strawberries.x)
elif m.status == GRB.INFEASIBLE:
    print('Model is infeasible')
else:
    print('Optimization ended with status %d' % m.status)

```
