## Step 1: Define the symbolic representation of the problem

Let's denote:
- $x_1$ as the number of kayaks
- $x_2$ as the number of canoes

The objective is to maximize profit, where the profit per kayak is $300 and per canoe is $450. Therefore, the objective function can be represented as:
\[ \text{Maximize:} \quad 300x_1 + 450x_2 \]

## Step 2: Define the constraints based on the given resources

The company has available 8000 minutes for assembly and 4000 minutes for quality checking. Each kayak takes 60 minutes of assembly and 15 minutes of quality checking. Each canoe takes 80 minutes of assembly and 25 minutes of quality checking. This gives us the following constraints:
\[ 60x_1 + 80x_2 \leq 8000 \] (assembly time constraint)
\[ 15x_1 + 25x_2 \leq 4000 \] (quality checking time constraint)
Additionally, $x_1 \geq 0$ and $x_2 \geq 0$ because the number of kayaks and canoes cannot be negative.

## 3: Symbolic representation in JSON format

```json
{
    'sym_variables': [('x1', 'kayaks'), ('x2', 'canoes')],
    'objective_function': '300*x1 + 450*x2',
    'constraints': [
        '60*x1 + 80*x2 <= 8000',
        '15*x1 + 25*x2 <= 4000',
        'x1 >= 0',
        'x2 >= 0'
    ]
}
```

## 4: Convert the problem into Gurobi code

```python
import gurobipy as gp

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

# Define the variables
x1 = model.addVar(name="kayaks", lb=0, vtype=gp.GRB.INTEGER)  # Number of kayaks
x2 = model.addVar(name="canoes", lb=0, vtype=gp.GRB.INTEGER)  # Number of canoes

# Define the objective function
model.setObjective(300*x1 + 450*x2, gp.GRB.MAXIMIZE)

# Define the constraints
model.addConstr(60*x1 + 80*x2 <= 8000, name="assembly_time")
model.addConstr(15*x1 + 25*x2 <= 4000, name="quality_checking_time")

# Solve the model
model.optimize()

# Print the solution
if model.status == gp.GRB.OPTIMAL:
    print(f"Optimal number of kayaks: {x1.varValue}")
    print(f"Optimal number of canoes: {x2.varValue}")
    print(f"Maximal profit: {model.objVal}")
else:
    print("The model is infeasible")
```