In the modern era consumer awareness on quality aspects has been a growing concern for the fresh produce market due to the fact that consumer perspective defines the bottom line of all agricultural businesses. External damage to produce does not only render fruit less attractive but damaged locations serve as entry points for pathogens resulting is food safety issues.
Because tomatoes have a limited shelf life, it is vital to control the factors that lead to earlier deterioration of the quality of the product. Shipping, handling and distribution can cause numerous forms of cuts and bruises on harvested tomatoes which compromise their quality and appearance. Furthermore the economic value to the retailer and grower is reduced (Chonhenchob et al., 2009).
Post-harvest science focus mainly on the quality of fresh produce. One of the areas of interest is the shipment of tomatoes using road transport. Trucks are one of the best methods for transporting perishable products because of shorter transport times and the ability to reach more inland destinations than any other mode of transport (Jarimopas et al., 2005; Chonhenchob et al., 2009). Although the flexibility of road transport is an advantage, previous studies have indicated that fruit and vegetables suffer mechanical damage due to in-transit vibrations which is caused by the road condition (Jarimopas et al., 2005).
The condition of roads in South Africa is dependent on the management plan execution by the managing agent. The National Road Network, maintained by SANRAL is predominantly in a good condition (Ittmann, 2013). In contrast, condition assessment data for provincial roads indicate that roads are deteriorating at an alarming pace, not to mention that the majority of road networks under municipal authorities have no data at all (SAICE, 2011).
To date there is no model that relates tomato damage and loss in shelf life to the road condition, fruit maturity and position in the container. For this experiment the in-transit conditions were monitored on trucks travelling from three farms in Limpopo, owned by the ZZ2 group, to the fresh produce market in Pietermaritzburg. These trucks drive on a variety of roads including gravel or rural roads where higher roughness values are probable along with more produce damage.
The experimental setup consisted of two phases. The first phase was the in-transit monitoring of the conditions to which tomatoes are exposed when shipped from grower to the farmers market. The second phase was the laboratory simulation of in-transit conditions to create a model for the prediction of shelf-life under controlled conditions.
Equipment for the field experiment included a profilometer to determine road conditions, accelerometers to determine in-transit vibrations, pressure sensors to determine in-transit pressures. Equipment for the laboratory experiment included a vibration table to simulate different road conditions, pressure sensors to measure pressures that can be related to in-transit pressures and a colour meter to measure colour changes in damaged and control tomatoes.
From the in-transit pressure analysis it was concluded that the amount of pressure cycles that a tomato experience increase as the roughness of the road increase and the force distribution that is applied to the tomatoes becomes wider to include forces larger in magnitude. Good correlations existed between in-transit and laboratory pressures.
Colour measurements had no strong trends that could be related to damage and an experimental model based on consumer perspective was developed. The experimental model was designed based on a marketability matrix that models the decision of the consumer on whether to purchase a tomato or not. Ultimately it is a subjective matter and each consumer would react differently towards the colour and firmness of the tomato in question.
The model indicated that for roads with high roughness values (International Roughness Index (IRI) > 8 m/km), which mostly consist of farm roads that are poorly maintained, all tomatoes in the first and second layers would acquire significant damage irrespective of the maturity of the fruit. On well-maintained roads with roughness values less than 3.5 m/km red tomatoes in the top layers tend to damage more with an increase in time as compared to tomatoes in the lower layers. Green and pink tomatoes are more resistant to damage in the top layers than the red tomatoes.
From the damage models it is apparent that as the roughness of the road increases the damage to tomatoes increase as well. Tomato maturity and the position of the tomatoes in a container also influence the amount of damage to the fruit.
With this information in hand, logistic planners can make informed decisions during route planning in weighing transportation costs to the cost of losses to produce during transportation. Similar models can be developed to include other fruits and vegetables.
Dissertation (MEng)--University of Pretoria, 2017.