## Step 1: Define the symbolic representation of the problem
The problem involves three variables: 'cherry pies', 'bagged salads', and 'green beans', which we can denote as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the natural language objects into symbolic notation
The symbolic variables and their corresponding natural language objects are:
- $x_0$ : cherry pies
- $x_1$ : bagged salads
- $x_2$ : green beans

## 3: Define the objective function in symbolic notation
The objective function to minimize is $6.26x_0 + 3.48x_1 + 2.79x_2$.

## 4: List the constraints in symbolic notation
The constraints are:
- $21x_1 + 23x_2 \geq 95$
- $1x_0 + 23x_2 \geq 58$
- $1x_0 + 21x_1 \geq 106$
- $1x_0 + 21x_1 + 23x_2 \geq 106$
- $22x_1 + 2x_2 \geq 31$
- $3x_0 + 22x_1 \geq 14$
- $3x_0 + 22x_1 + 2x_2 \geq 14$
- $16x_1 + 6x_2 \geq 59$
- $19x_0 + 16x_1 + 6x_2 \geq 59$
- $15x_0 + 1x_1 \geq 90$
- $15x_0 + 1x_1 + 3x_2 \geq 98$
- $5x_1 + 10x_2 \geq 61$
- $10x_0 + 5x_1 \geq 109$
- $10x_0 + 5x_1 + 10x_2 \geq 109$
- $x_1 - 10x_2 \geq 0$
- $1x_0 + 21x_1 \leq 144$
- $3x_0 + 22x_1 \leq 90$
- $3x_0 + 2x_2 \leq 119$
- $16x_1 + 6x_2 \leq 291$
- $19x_0 + 6x_2 \leq 164$
- $15x_0 + 1x_1 + 3x_2 \leq 307$

## 5: Provide the symbolic representation in JSON format
```json
{
    'sym_variables': [('x0', 'cherry pies'), ('x1', 'bagged salads'), ('x2', 'green beans')],
    'objective_function': '6.26*x0 + 3.48*x1 + 2.79*x2',
    'constraints': [
        '21*x1 + 23*x2 >= 95',
        'x0 + 23*x2 >= 58',
        'x0 + 21*x1 >= 106',
        'x0 + 21*x1 + 23*x2 >= 106',
        '22*x1 + 2*x2 >= 31',
        '3*x0 + 22*x1 >= 14',
        '3*x0 + 22*x1 + 2*x2 >= 14',
        '16*x1 + 6*x2 >= 59',
        '19*x0 + 16*x1 + 6*x2 >= 59',
        '15*x0 + x1 >= 90',
        '15*x0 + x1 + 3*x2 >= 98',
        '5*x1 + 10*x2 >= 61',
        '10*x0 + 5*x1 >= 109',
        '10*x0 + 5*x1 + 10*x2 >= 109',
        'x1 - 10*x2 >= 0',
        'x0 + 21*x1 <= 144',
        '3*x0 + 22*x1 <= 90',
        '3*x0 + 2*x2 <= 119',
        '16*x1 + 6*x2 <= 291',
        '19*x0 + 6*x2 <= 164',
        '15*x0 + x1 + 3*x2 <= 307'
    ]
}
```

## 6: Implement the optimization problem using Gurobi
```python
import gurobi

# Create a new model
model = gurobi.Model()

# Define the variables
x0 = model.addVar(name="cherry_pies", lb=0)
x1 = model.addVar(name="bagged_salads", lb=0)
x2 = model.addVar(name="green_beans", lb=0)

# Set the objective function
model.setObjective(6.26 * x0 + 3.48 * x1 + 2.79 * x2, gurobi.GRB.MINIMIZE)

# Add constraints
model.addConstr(21 * x1 + 23 * x2 >= 95)
model.addConstr(x0 + 23 * x2 >= 58)
model.addConstr(x0 + 21 * x1 >= 106)
model.addConstr(x0 + 21 * x1 + 23 * x2 >= 106)
model.addConstr(22 * x1 + 2 * x2 >= 31)
model.addConstr(3 * x0 + 22 * x1 >= 14)
model.addConstr(3 * x0 + 22 * x1 + 2 * x2 >= 14)
model.addConstr(16 * x1 + 6 * x2 >= 59)
model.addConstr(19 * x0 + 16 * x1 + 6 * x2 >= 59)
model.addConstr(15 * x0 + x1 >= 90)
model.addConstr(15 * x0 + x1 + 3 * x2 >= 98)
model.addConstr(5 * x1 + 10 * x2 >= 61)
model.addConstr(10 * x0 + 5 * x1 >= 109)
model.addConstr(10 * x0 + 5 * x1 + 10 * x2 >= 109)
model.addConstr(x1 - 10 * x2 >= 0)
model.addConstr(x0 + 21 * x1 <= 144)
model.addConstr(3 * x0 + 22 * x1 <= 90)
model.addConstr(3 * x0 + 2 * x2 <= 119)
model.addConstr(16 * x1 + 6 * x2 <= 291)
model.addConstr(19 * x0 + 6 * x2 <= 164)
model.addConstr(15 * x0 + x1 + 3 * x2 <= 307)

# Solve the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", model.objval)
    print("Cherry pies: ", x0.varValue)
    print("Bagged salads: ", x1.varValue)
    print("Green beans: ", x2.varValue)
else:
    print("The model is infeasible")
```