FIELD EVALUATION OF HARVESTING MACHINES FOR TALL OIL PALMS

Harvesting is a very important activity in any agriculture business. Cheap and efficient harvesting processes are factors that ensure good returns. Efficient mechanical harvesting of oil palm fresh fruit bunch (FFB) remains an issue that needs to be addressed. The current methods of harvesting involve the use of a chisel or sickle, which require manual labour and is therefore tedious. As the country is facing a labour shortage in the plantation sector, the introduction of farm machinery would be one way of increasing labour productivity. This article describes the performance of two oil palm mechanical harvesting machines in the field as compared to a manual operation. The machines carried out cutting operations of the FFB, which were transported to the road side and unloaded either onto the mainline transport or to the ground. A time motion study during the cutting operation was carried out, and the quantity of detached loose fruits produced were recorded. Machine performance in terms of productivity and cost-effectiveness were also monitored. It was found that the productivity of the machines ranged from 3 to 6 t per day depending on various factors. This study also indicated that the loose fruits collection could be minimised by using the harvesting machine. A comparative study of the harvesting machines with and without grapple shows that the latter is slower, even though it is only used for cutting operation, without deposition of the bunches into the bucket. The productivity (man per day) of the complete harvesting machine was almost double, compared to manual harvesting that uses buffalo-carts for the evacuation of the FFB. However, the economic analysis shows that the cost per tonne for mechanical harvesting machine was slightly higher as compared to manual operation. It is envisaged that with the successful introduction of the mechanical harvester, opportunities for new technologies would open up for the development of more efficient and cheaper machines in the future.