Researchers Use Mathematical Models to Optimize Olive Oil Production

Using response surface methodology, Spanish scientists can now predict the impact that different variables have on the olive oil production process.

Jan. 9, 2019
By Rosa Gonzalez-Lamas

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A group of researchers from Spain’s University of Jaén have devel­oped new math­e­mat­i­cal mod­els that can help to pre­dict the qual­ity of extra vir­gin olive oil and opti­mize its pro­duc­tion.

RSM allows us to obtain infor­ma­tion that we will miss when employ­ing clas­si­cal method­olo­gies. Its advan­tage is that one can study the com­bined per­for­mance of sev­eral vari­able fac­tors, mean­ing the influ­ence of each and the inter­ac­tion exist­ing among all.- Francisco Espínola Lozano, pro­fes­sor at the University of Jaén

The researchers devel­oped these mod­els using response sur­face method­ol­ogy (RSM), which explores the rela­tion­ship between inde­pen­dent and depen­dent vari­ables involved in the pro­duc­tion process and is often used to max­i­mize the yield of a spe­cific sub­stance.

RSM allows us to obtain infor­ma­tion that we will miss when employ­ing clas­si­cal method­ol­ogy,” Francisco Espínola Lozano, a pro­fes­sor at the University of Jaén and lead researcher on the study, told Olive Oil Times. Its advan­tage is that one can study the com­bined per­for­mance of sev­eral vari­able fac­tors, mea­sur­ing the influ­ence of each and the inter­ac­tion exist­ing among them all.”

Espínola Lozano said that the study explored, for the first time, a com­bined research of four tech­no­log­i­cal fac­tors: the size of the sieve and of the ham­mer mill that grinds the olives; the time and the tem­per­a­ture at which the olive paste is malaxed; and the doses of tech­no­log­i­cal adju­vant used to improve the per­for­mance of the olive.

Talc and cao­lit­ica clay are already autho­rized as tech­no­log­i­cal adju­vants, but we used cal­cium car­bon­ate and had bet­ter results,” he said. This rep­re­sents a promis­ing research line.”

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According to Espínola Lozano, the use of dif­fer­ent math­e­mat­i­cal mod­els dur­ing the inves­ti­ga­tion allowed the researchers to dis­cover the rela­tion­ship between these tech­no­log­i­cal and agro­nomic fac­tors. For this rea­son, the mod­els can deter­mine the effects that olive vari­ety, degree of ripeness, kind of cul­ti­va­tion (tra­di­tional, inten­sive, super inten­sive) and the use or lack of irri­ga­tion will have on the oil pro­duc­tion process.

By apply­ing RSM to a pre­vi­ously designed sta­tis­ti­cal exper­i­ment, the researchers also devel­oped mod­els that can pre­dict the effect of the vari­a­tion cer­tain tech­no­log­i­cal aspects have on the oil.

An exam­ple of this is the model’s abil­ity to increase or reduce cer­tain phe­no­lic com­pounds with antiox­i­dant and anti-inflam­ma­tory prop­er­ties, such as oleo­can­thal, allow­ing for the cre­ation of prod­ucts with spe­cific traits and vari­ances, both in terms of fla­vor and health prop­er­ties.

In addi­tion to yields, we stud­ied reg­u­lated qual­ity para­me­ters and the con­tents of phe­no­lic com­pounds (nat­ural antiox­i­dants) and volatile con­tents, which are respon­si­ble for aro­mas, eval­u­at­ing more than 30 responses,” Espínola Lozano said.

He added that the math­e­mat­i­cal mod­els used depend on the oil trait that researchers want to improve.

These new mod­els not only help pre­dict the qual­ity of olive oils, but also facil­i­tate the automa­tion of olive oil pro­duc­tion at the mills. No spe­cific tech­no­log­i­cal adap­ta­tion seems to be required, only the appli­ca­tion of the math­e­mat­i­cal mod­els adapted to the olives processed at the mill.

In case a mill decides to man­age its pro­duc­tion in a sys­tem­atic and auto­mated man­ner, the math­e­mat­i­cal mod­els can be included in the soft­ware that is used.

Espínola Lozano empha­sized that mills cur­rently han­dle olive pro­duc­tion more as an artis­tic under­tak­ing, which trusts the expe­ri­ence and intu­ition of olive mas­ters, rather than as a process that must be han­dled with a sci­en­tific and tech­no­log­i­cal approach.

In his view, it is impor­tant that the com­pa­nies involved in olive pro­duc­tion learn about the many pos­si­bil­i­ties sci­en­tific research opens and max­i­mize their advan­tages.

This view­point is likely shared by the Junta de Andalucía, whose Council of Innovation, Science and Enterprises funded the project.





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