## Step 1: Define the symbolic representation of the problem
The problem involves two variables: 'tomatoes' and 'apples', which we can represent symbolically as $x_1$ and $x_2$ respectively.

## Step 2: Translate the objective function into symbolic notation
The objective function to maximize is $9.8x_1 + 9.86x_2$.

## 3: List the constraints in symbolic notation
The constraints given are:
- $15x_1 + 23x_2 \geq 24$ (total combined tastiness rating from tomatoes and apples has to be at least 24)
- $3x_1 + 15x_2 \geq 59$ (at least 59 grams of carbohydrates from tomatoes and apples)
- $22x_1 + 2x_2 \geq 47$ (at least 47 milligrams of iron from tomatoes and apples)
- $9x_1 - 10x_2 \geq 0$ (nine times the number of tomatoes plus minus ten times the number of apples must be at least zero)
- $15x_1 + 23x_2 \leq 138$ (total combined tastiness rating from tomatoes and apples has to be at most 138)
- $3x_1 + 15x_2 \leq 225$ (no more than 225 grams of carbohydrates from tomatoes and apples)
- $22x_1 + 2x_2 \leq 80$ (at most 80 milligrams of iron can come from tomatoes and apples)

## 4: Define the symbolic variables and the optimization problem
The symbolic variables are:
- $x_1$ represents 'tomatoes'
- $x_2$ represents 'apples'

## 5: Write down the optimization problem in a symbolic form
```
{'sym_variables': [('x1', 'tomatoes'), ('x2', 'apples')], 
 'objective_function': '9.8*x1 + 9.86*x2', 
 'constraints': [
    '15*x1 + 23*x2 >= 24',
    '3*x1 + 15*x2 >= 59',
    '22*x1 + 2*x2 >= 47',
    '9*x1 - 10*x2 >= 0',
    '15*x1 + 23*x2 <= 138',
    '3*x1 + 15*x2 <= 225',
    '22*x1 + 2*x2 <= 80'
  ]
}
```

## 6: Convert the problem into Gurobi code
```python
import gurobi

def solve_optimization_problem():
    # Create a new model
    model = gurobi.Model()

    # Define the variables
    tomatoes = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="tomatoes")
    apples = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="apples")

    # Define the objective function
    model.setObjective(9.8 * tomatoes + 9.86 * apples, gurobi.GRB.MAXIMIZE)

    # Add constraints
    model.addConstr(15 * tomatoes + 23 * apples >= 24, name="tastiness_rating_min")
    model.addConstr(3 * tomatoes + 15 * apples >= 59, name="carbohydrates_min")
    model.addConstr(22 * tomatoes + 2 * apples >= 47, name="iron_min")
    model.addConstr(9 * tomatoes - 10 * apples >= 0, name="tomatoes_vs_apples")
    model.addConstr(15 * tomatoes + 23 * apples <= 138, name="tastiness_rating_max")
    model.addConstr(3 * tomatoes + 15 * apples <= 225, name="carbohydrates_max")
    model.addConstr(22 * tomatoes + 2 * apples <= 80, name="iron_max")

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Tomatoes: {tomatoes.x}")
        print(f"Apples: {apples.x}")
        print(f"Objective: {model.objVal}")
    else:
        print("No optimal solution found.")

solve_optimization_problem()
```