Sampling Method to Estimate Fresh Fruit Bunch Production in Oil Palm Using Geostatistical Techniques

In oil palm cultivation, harvesting is a task that demands the most attention, resources, and accuracy. The logistics of harvesting activities, from bunch cutting through delivery to processing, are organized as a function of yield per hectare, and this planning depends on production samples collected from plantations to estimate the number of fresh fruit bunches that will be harvested per crop management unit. Conventionally, production is estimated through sampling grids, most commonly every five rows and every five palms (5 × 5), 7 × 7, or 10 × 10. Sampling density, however, does not typically result from a statistically rigorous method. Therefore, the objective of the present study was to define, using geostatistics, adequate sampling grids for estimating production. Specifically, seven lots in different Colombian oil palm-growing regions with planting ages between 5 and 9 years were analyzed, and the number of reproductive structures of all oil palms was recorded. From the semivariogram of each lot, different models were proposed, fitted, and cross-validated. For each sampling grid, all possible samples were simulated in the respective lots to determine the degree of accuracy in estimating oil palm production. The optimal sampling grids differed between lots, ranging from 3 × 3 to 15 × 15.