## Step 1: Define the symbolic representation of the variables
The variables are 'vincas', 'roses', 'bean stalks', 'chives' which can be represented symbolically as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the objective function into symbolic notation
The objective function to minimize is $3 \cdot vincas + 1 \cdot roses + 7 \cdot bean\ stalks + 7 \cdot chives$. In symbolic notation, this becomes $3x_0 + 1x_1 + 7x_2 + 7x_3$.

## 3: Define the symbolic representation of the constraints
1. $3vincas \geq 33$ becomes $3x_0 \geq 33$.
2. $10roses + 9chives \geq 33$ becomes $10x_1 + 9x_3 \geq 33$.
3. $3vincas + 10roses + 10bean\ stalks + 9chives \geq 33$ becomes $3x_0 + 10x_1 + 10x_2 + 9x_3 \geq 33$.
4. $10roses + 11bean\ stalks \geq 22$ becomes $10x_1 + 11x_2 \geq 22$.
5. $11bean\ stalks + 7chives \geq 26$ becomes $11x_2 + 7x_3 \geq 26$.
6. $10vincas + 10roses \geq 20$ becomes $10x_0 + 10x_1 \geq 20$.
7. $10vincas + 11bean\ stalks \geq 15$ becomes $10x_0 + 11x_2 \geq 15$.
8. $10vincas + 10roses + 11bean\ stalks \geq 25$ becomes $10x_0 + 10x_1 + 11x_2 \geq 25$.
9. $10roses + 11bean\ stalks + 7chives \geq 25$ becomes $10x_1 + 11x_2 + 7x_3 \geq 25$.
10. $10vincas + 10roses + 7chives \geq 25$ becomes $10x_0 + 10x_1 + 7x_3 \geq 25$.
11. $10vincas + 10roses + 11bean\ stalks \geq 30$ becomes $10x_0 + 10x_1 + 11x_2 \geq 30$.
12. $10roses + 11bean\ stalks + 7chives \geq 30$ becomes $10x_1 + 11x_2 + 7x_3 \geq 30$.
13. $10vincas + 10roses + 7chives \geq 30$ becomes $10x_0 + 10x_1 + 7x_3 \geq 30$.
14. $10vincas + 10roses + 11bean\ stalks \geq 41$ becomes $10x_0 + 10x_1 + 11x_2 \geq 41$.
15. $10roses + 11bean\ stalks + 7chives \geq 41$ becomes $10x_1 + 11x_2 + 7x_3 \geq 41$.
16. $10vincas + 10roses + 7chives \geq 41$ becomes $10x_0 + 10x_1 + 7x_3 \geq 41$.
17. $10vincas + 10roses + 11bean\ stalks + 7chives \geq 41$ becomes $10x_0 + 10x_1 + 11x_2 + 7x_3 \geq 41$.
18. $10roses + 10bean\ stalks \leq 159$ becomes $10x_1 + 10x_2 \leq 159$.
19. $3vincas + 10roses \leq 138$ becomes $3x_0 + 10x_1 \leq 138$.
20. $10vincas + 10roses + 11bean\ stalks \leq 75$ becomes $10x_0 + 10x_1 + 11x_2 \leq 75$.
21. $10vincas + 10roses + 7chives \leq 93$ becomes $10x_0 + 10x_1 + 7x_3 \leq 93$.

## 4: Define the variable bounds
- $x_0, x_1, x_2, x_3$ are integers.
- $3x_0 \leq 183$
- $10x_0 \leq 172$
- $10x_1 \leq 172$
- $11x_2 \leq 172$
- $7x_3 \leq 172$

## 5: Write down the problem in JSON format
```json
{
    'sym_variables': [
        ('x0', 'vincas'), 
        ('x1', 'roses'), 
        ('x2', 'bean stalks'), 
        ('x3', 'chives')
    ], 
    'objective_function': '3*x0 + 1*x1 + 7*x2 + 7*x3', 
    'constraints': [
        '3*x0 >= 33',
        '10*x1 + 9*x3 >= 33',
        '3*x0 + 10*x1 + 10*x2 + 9*x3 >= 33',
        '10*x1 + 11*x2 >= 22',
        '11*x2 + 7*x3 >= 26',
        '10*x0 + 10*x1 >= 20',
        '10*x0 + 11*x2 >= 15',
        '10*x0 + 10*x1 + 11*x2 >= 25',
        '10*x1 + 11*x2 + 7*x3 >= 25',
        '10*x0 + 10*x1 + 7*x3 >= 25',
        '10*x0 + 10*x1 + 11*x2 >= 30',
        '10*x1 + 11*x2 + 7*x3 >= 30',
        '10*x0 + 10*x1 + 7*x3 >= 30',
        '10*x0 + 10*x1 + 11*x2 >= 41',
        '10*x1 + 11*x2 + 7*x3 >= 41',
        '10*x0 + 10*x1 + 7*x3 >= 41',
        '10*x0 + 10*x1 + 11*x2 + 7*x3 >= 41',
        '10*x1 + 10*x2 <= 159',
        '3*x0 + 10*x1 <= 138',
        '10*x0 + 10*x1 + 11*x2 <= 75',
        '10*x0 + 10*x1 + 7*x3 <= 93'
    ]
}
```

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

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

# Define the variables
x0 = m.addVar(name="vincas", vtype=gurobi.GRB.INTEGER)
x1 = m.addVar(name="roses", vtype=gurobi.GRB.INTEGER)
x2 = m.addVar(name="bean_stalks", vtype=gurobi.GRB.INTEGER)
x3 = m.addVar(name="chives", vtype=gurobi.GRB.INTEGER)

# Objective function
m.setObjective(3*x0 + x1 + 7*x2 + 7*x3, gurobi.GRB.MINIMIZE)

# Constraints
m.addConstr(3*x0 >= 33, name="min_vincas")
m.addConstr(10*x1 + 9*x3 >= 33, name="min_roses_chives")
m.addConstr(3*x0 + 10*x1 + 10*x2 + 9*x3 >= 33, name="total_min_spend")
m.addConstr(10*x1 + 11*x2 >= 22, name="min_resilience_roses_bean_stalks")
m.addConstr(11*x2 + 7*x3 >= 26, name="min_resilience_bean_stalks_chives")
m.addConstr(10*x0 + 10*x1 >= 20, name="min_resilience_vincas_roses")
m.addConstr(10*x0 + 11*x2 >= 15, name="min_resilience_vincas_bean_stalks")
m.addConstr(10*x0 + 10*x1 + 11*x2 >= 25, name="min_resilience_vincas_roses_bean_stalks")
m.addConstr(10*x1 + 11*x2 + 7*x3 >= 25, name="min_resilience_roses_bean_stalks_chives")
m.addConstr(10*x0 + 10*x1 + 7*x3 >= 25, name="min_resilience_vincas_roses_chives")
m.addConstr(10*x0 + 10*x1 + 11*x2 >= 30, name="resilience_vincas_roses_bean_stalks")
m.addConstr(10*x1 + 11*x2 + 7*x3 >= 30, name="resilience_roses_bean_stalks_chives")
m.addConstr(10*x0 + 10*x1 + 7*x3 >= 30, name="resilience_vincas_roses_chives")
m.addConstr(10*x0 + 10*x1 + 11*x2 >= 41, name="resilience_vincas_roses_bean_stalks_min")
m.addConstr(10*x1 + 11*x2 + 7*x3 >= 41, name="resilience_roses_bean_stalks_chives_min")
m.addConstr(10*x0 + 10*x1 + 7*x3 >= 41, name="resilience_vincas_roses_chives_min")
m.addConstr(10*x0 + 10*x1 + 11*x2 + 7*x3 >= 41, name="total_resilience_min")
m.addConstr(10*x1 + 10*x2 <= 159, name="max_spend_roses_bean_stalks")
m.addConstr(3*x0 + 10*x1 <= 138, name="max_spend_vincas_roses")
m.addConstr(10*x0 + 10*x1 + 11*x2 <= 75, name="max_resilience_vincas_roses_bean_stalks")
m.addConstr(10*x0 + 10*x1 + 7*x3 <= 93, name="max_resilience_vincas_roses_chives")

# Resource constraints
m.addConstr(3*x0 <= 183, name="budget_vincas")
m.addConstr(10*x0 <= 172, name="resilience_vincas")
m.addConstr(10*x1 <= 172, name="resilience_roses")
m.addConstr(11*x2 <= 172, name="resilience_bean_stalks")
m.addConstr(7*x3 <= 172, name="resilience_chives")

# Solve the model
m.optimize()

# Print the solution
if m.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", m.objval)
    print("Vincas: ", x0.varValue)
    print("Roses: ", x1.varValue)
    print("Bean Stalks: ", x2.varValue)
    print("Chives: ", x3.varValue)
else:
    print("No solution found")
```