Production

New Software Models Increase Efficiency of Olive Oil Production

This program takes factors such as the harvester's budget, potential climate risks and the level of synchronization between plantation and refineries into account before providing advice to olive growers.

Region del Maule, Chile
Nov. 15, 2017
By Daniel Dawson
Region del Maule, Chile

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Sci­en­tists in Chile have devel­oped a soft­ware mod­el­ing pro­gram to assist olive grow­ers in mak­ing key deci­sions about when to plant and har­vest their crops.

The plan gen­er­ated by the model extracted four per­cent more olive oil than the plan given by the tra­di­tional man­ual pro­ce­dure.- Eduardo Alvarez-Miranda

This pro­gram takes fac­tors such as the har­vester’s bud­get, poten­tial cli­mate risks and the level of syn­chro­niza­tion between plan­ta­tion and refiner­ies into account before pro­vid­ing advice to olive grow­ers.

In olive oil pro­duc­tion two main agents are involved, the deci­sion-maker in the field and the deci­sion-maker in the mill,” said Eduardo Alvarez-Miranda, a researcher on the project. The pro­posed model allows both deci­sions to be uni­fied by deter­min­ing the best flow of fruit from the field to the mill.”

The pro­gram was tested on an olive plan­ta­tion in the Region del Maule in cen­tral Chile and led to an increase in oil pro­duc­tion.

With the same input of resources, they had a higher out­put of olive oil,” said Alvarez-Miranda. The plan gen­er­ated by the model extracted four per­cent more olive oil than the plan given by the tra­di­tional man­ual pro­ce­dure.”

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The way in which the mod­el­ing improved pro­duc­tiv­ity the most was by pro­vid­ing data about when to har­vest the olives and how many peo­ple and har­vest­ing machines were needed to do so.

For the plan­ning stage it was espe­cially impor­tant,” said Alvarez-Miranda. The mod­els told them how many peo­ple they needed to hire at cer­tain times dur­ing the har­vest sea­son as well as when to rent machines. It turned out they needed fewer har­vest­ing machines than they thought.”

The soft­ware pro­gram also pro­vided advice to the plan­ta­tion own­ers about man­ag­ing their resources more effi­ciently. The com­pany had been rent­ing the refin­ery to other olive pro­duc­ers in order to earn some extra income.

We man­aged to incor­po­rate this into the model,” said Alvarez-Miranda. We found that they were, in fact, los­ing money by let­ting their olives sit while they extracted oil from other pro­duc­ers’ olives.”

Olives must be processed soon after har­vest­ing in order to main­tain oil con­tent and avoid oxi­da­tion.

Alvarez-Miranda believes there is huge poten­tial in Chile for this type of sta­tis­ti­cal mod­el­ing.

A sim­i­lar model has already been used in Chile for har­vest­ing grapes. Sci­en­tists from Pon­ti­f­i­cia Uni­ver­si­dad Catolica de Chile were able to decrease the oper­a­tional costs of one grape har­vester by 27 per­cent and labor costs by 16 per­cent.

How­ever, there are a cou­ple of issues pre­vent­ing the pro­gram from being widely adopted among olive grow­ers: spe­cific com­puter soft­ware is required and not many olive pro­duc­ers are will­ing to pur­chase it. Then the data must be input into the soft­ware and the pro­gram must be run.

Only one per­son knows how to use the tool at that plan­ta­tion,” said Alvarez-Miranda. Even so, the plan­ta­tions own­ers paid for it and are likely to keep using it as long as that per­son stays on.”





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