Precision Farming: Future Work on Precision Farming for Oil Palm Plantations

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Precision farming has not been implemented in the oil palm plantations to the best of our knowledge although the tools and technologies associated with it have been widely utilised. The major obstacles to precision farming in oil palm plantations are probably capital expenditure, lack of quantification of cost-benefit and risk of the new practices and resistant to change, which can be expected at this early stage of development. Currently most of the research is on adapting the new tools and technologies to solve immediate problems with little thoughts given to strategic and tactical approaches. As pointed out by McBratney and Taylor (1999), “To make precision farming work all areas of the Precision Agriculture wheel (Figure 3) need to be addressed”.

We do not intend to provide a comprehensive account of the future work required to introduce precision farming successfully to the oil palm plantations as it is beyond us. Instead, it should suffice to list out some important areas where further research may be warranted.

Mechanisation of most operations (Figure 15) is an absolute necessity for precision farming to materialise in oil palm plantations. The machines will allow dataloggers, yield monitors, GPS, sensors etc to be fitted for data collection. However, the errors and precision of the data and generated yield maps need further investigation.

Figure 15: Examples of mechanisation of field operations in oil palm plantations

Differential GPS in the market are sufficiently accurate for geo-referencing in horizontal direction (< 5m accuracy is sufficient for oil palm plantations) but inadequate for vertical direction (currently accurate to 1-3m) and generation of good DEM for assessing among other, drainage requirement, terracing and re-direction of water into the fields (rain harvest and watershed management).

Agonomic research should be targeted on understanding yield variation at a finer scale than currently done. The results are important towards the success of attribute mapping and interpretation of yield maps, and development of decision support system (DSS). The former is confounded by the perennial nature of oil palm which exhibits strong temporal yield variation and 2 to 5 year yield cycle. Methods to combine spatial and temporal data (Blackmore, 2000) and a protocol to interpret yield maps (e.g. Larscheid et al ., 1997) should be develop for oil palm. Decision support system translates data into knowledge for differential actions in the fields generally by combining database, crop models, expert system and artificial intelligence. Work should commence on the next generation of DSS which will be web-based and accessible through hand-held equipment including a telephone.

Variable rate technology (VRT) is an engineering problem (McBratney and Taylor, 1999) but much research is still needed to make it work in oil palm plantations.

There is much scope for management improvement in precision farming particularly in increasing labour productivity via better infrastructure, more precise planning, organisation, budgeting and worker friendly practices (Chew, 1998). Ultimately, it is the management who will make precision farming in oil palm plantations a success or failure.