Agriculture Reference
In-Depth Information
100
100
75
75
50
50
ethylene
no ethylene
25
25
0
0
A
B
C
D
C
D
chain type
chain type
Fig. 14.6
RTE Performance using four chain scenarios (batch 1,
left hand side
plot) or two chain
scenarios (batch 2,
right hand side
plot)
sive, mangoes could be suffering from chilling injury during transport and further
ripening during transport is not possible. This last point could be very useful when
the transportation time between the wholesaler and the end market is quite long.
Ripening rooms could be limiting at the wholesaler by ripening during transport
the throughput rate at the wholesaler could be increased. Therefore two of the four
chain scenarios have variable transport temperatures, this allows for the mangoes to
ripen further during transport.
Mangoes of batch 1 (origin Israel) were sorted on firmness at arrival at the
wholesaler and gathered in four sub-batches for batch 1. Mangoes in the sub-batch
with the lowest firmness were used for scenario A; mangoes in the sub-batch with
the second lowest firmness were used for scenario B etc. Mangoes of batch 2 (origin
Brazil) were treated the same, but now only two scenarios were simulated, scenario
C and D. Half of the mangoes in every sub-batch were exposed to high levels of
ethylene, the other half were not exposed. Ripening (between 17 and 20 °C) and
transport temperatures (between 13 and 20 °C) were calculated using the mango ac-
ceptance model. Some of the results are depicted in Fig.
14.6
, showing the percent-
age of the fruits within the established consumer acceptance limits at the end of the
chain. For all the batches the number of fruits within the acceptance limits is around
80 % when ethylene is used. These are promising results and can be transformed
into a ripening protocol.
An integrated overview of improvement opportunities when implementing the
QCL concept in the tomato and mango supply chain is presented in Table
14.2
.
Conclusions
Operations management in FSCN usually takes quality as given; if one approaches
product quality as a dynamic issue and uses time dependent quality information
more degrees of freedom come to the forefront that will improve supply chain per-
