Stochastic Optimizationproblem with 3 Stages

I have a Problem with 3 Stage stochastic Optimization Program i writting right now:

The goal is, that in the first stage raw materials are harvested, in the second stage the product ist produced and in the final stage the product get to the customer. 

My problem is in the objectiv function: the error i get from python is: "'int' object is not subscriptable" and i think its because of the "q in produce[i]" but i dont know a different solution

from gurobipy import *


#Raw Materials
I,M = multidict({1:[(3000,2800,2500)], 2:[(3000,2700,2600)], 3:[(3000.2500,2800)], 4:[(3000,2900,2300)]})

#Production
J,Max,Min = multidict({1:[3000,200], 2:[3000,200],3:[3000,200], 4:[3000,200]})

#Raw materials q at localisation i
produce = {1:['switch'], 2:['seed'], 3:['salz'], 4:['süß']}

#Demand for product p at demandcenter k in scenario s and period t
d = {(1,'Butanol'):((0,0,0),(80,70,90),(80,70,90),(100,110,90)), (1,'Biodiesel'):((0,0,0),(90,80,100),(95,85,75),(85,75,95)), 
(2,'Butanol'):((0,0,0),(280,270,290),(280,300,290),(280,260,270)), (2,'Biodiesel'):((0,0,0),(120,130,110),(150,170,160),(110,120,130)), 
(3,'Butanol'):((0,0,0),(240,250,260),(230,250,240),(240,250,260)), (3,'Biodiesel'):((0,0,0),(140,150,130),(150,140,130),(120,150,110)), 
(4,'Butanol'):((0,0,0),(180,170,160),(130,120,140),(150,160,170)), (4,'Biodiesel'):((0,0,0),(80,70,60),(60,70,50),(80,70,60)), 
(5,'Butanol'):((0,0,0),(180,170,190),(180,170,190),(180,170,190)), (5,'Biodiesel'):((0,0,0),(80,70,90),(80,100,90),(100,80,90)) 
}

#Capacity of raffinerie j
Kapa = [0,500,600,500,300,250]

# Probability of scenario s
Prob = [0.333,0.333,0.333]

EPS = 1.e-6



K = set([k for (k,p) in d])
P = set([p for (k,p) in d])
#Periods
T = [1,2,3]
#Scenarios
S = [1,2,3]
#Fix costs
f = 4000
f_Bio = 5000

#transportation costs
weight = {'Butanol':5, 'Biodiesel':2}
cost = {(1,1):4, (1,2):6, (1,3):9, (1,4):3,
(2,1):5, (2,2):4, (2,3):7, (2,4):5,
(3,1):6, (3,2):8, (3,3):4, (3,4):6,
(4,1):8, (4,2):5, (4,3):3, (4,4):6,
(5,1):10, (5,2):8, (5,3):4, (5,4):9
}

weight_bio = {'switch':5, 'seed':2, 'salz':4, 'süß':4}
cost_bio = {(1,1):4, (1,2):6, (1,3):9, (1,4):3,
(2,1):5, (2,2):4, (2,3):7, (2,4):5,
(3,1):6, (3,2):8, (3,3):4, (3,4):6,
(4,1):8, (4,2):5, (4,3):3, (4,4):6,
(5,1):10, (5,2):8, (5,3):4, (5,4):9
}

c_bio = {}
for i in I:
for j in J:
for q in produce[i]:
c_bio[i, j, q] = cost_bio[i,j] * weight_bio[q]







c = {}
for k in K:
for j in J:
for p in P:
c[k, j, p] = cost[k,j] * weight[p]


model = Model("multi-commodity transportation")
x,y = {},{}
xBio,yBio = {},{}
L = {}
z = {}
for k,j,p in c:
for t in range(1,len(T)+1):
for s in range(0,len(S)):
x[k,j,p,t,s] = model.addVar(vtype="C", name="x[%s,%s,%s,%s,%s]" % (k, j, p, t,s)) 




for j in J:
y[j] = model.addVar(vtype="B", name="y(%s)"%j) 

for j in J:
for p in P:
z[j,p] = model.addVar(vtype="B", name="z(%s,%s)"%(j,p)) 

for k in K:
for p in P:
for t in range(0,len(T)+1):
L[k,p,t] = model.addVar(vtype="C", name="L[%s,%s,%s]"%(k,p,t)) 


for i,j,q in c_bio:
for t in range(1,len(T)+1):
for s in range(0,len(S)):
xBio[i,j,q,t,s] = model.addVar(vtype="C", name="x[%s,%s,%s,%s,%s]" % (i, j, q, t,s))




for i in I:
yBio[i]= model.addVar(vtype="B", name="y(%s)"%i)




model.update()

for k in K:
for p in P:
model.addConstr(L[k,p,0] == 0)

for k in K:
for t in range(0,len(T)+1):
model.addConstr(quicksum(L[k,p,t] for p in P) <= Kapa[k])




for k in K:
for p in P: 
for t in range(1,len(T)+1):
for s in range(0,len(S)):
model.addConstr(quicksum(x[k,j,p,t,s]*z[j,p]for j in J if (k,j,p,t,s) in x) + L[k,p,t-1] - d[k,p][t][s] == L[k,p,t])

for j in J:
for t in range(1,len(T)+1):
for s in range(0,len(S)):
model.addConstr(quicksum(x[k,j,p,t,s]*z[j,p] for (k,j2,p,t2,s) in x if j2 == j if t == t2) <= Max[j]*y[j], "Capacity[%s]" % j)

for j in J:
for t in range(1,len(T)+1):
for s in range(0,len(S)):
model.addConstr(quicksum(x[k,j,p,t,s]*z[j,p] for (k,j2,p,t2,s) in x if j2 == j if t == t2) >= Min[j]*y[j], "Capacity[%s]" % j)

for j in J:
for t in range(1,len(T)+1):
for s in range(0,len(S)):
for q in produce[i]:
model.addConstr(quicksum(x[k,j,p,t,s]*z[j,p] for (k,j2,p,t2,s) in x if j2 == j if t == t2) <= quicksum(xBio[i,j,q,t,s]*yBio[i] for (i,j,q,t,s) in xBio))





for j in J:
model.addConstr(quicksum(z[j,p] for p in P)<=1)


#Problem is in the objectiv line: i think its something with q in produce[i]
model.setObjective(quicksum(Prob[s] *quicksum(c[k,j,p]*x[k,j,p,t,s] for k in K for j in J for p in P for t in range(1,len(T)+1))for s in range(0,len(S))) + quicksum(Prob[s]* quicksum(f*y[j] for j in J )for s in range(0,len(S))+
quicksum(Prob[s] *quicksum(c_bio[i,j,q]*xBio[i,j,q,t,s] for i in I for j in J for q in produce[i] for t in range(1,len(T)+1))for s in range(0,len(S))) + quicksum(Prob[s]* quicksum(f_Bio*y[i] for i in I )for s in range(0,len(S)))), GRB.MINIMIZE)
model.update()