New Method for Identifying Olive Cultivars

A new semi-auto­matic method­ol­ogy for iden­ti­fy­ing olive cul­ti­vars accord­ing to the appear­ance of leaves and fruit is intended to serve as the basis for a phone app for pro­duc­ers and con­tri­bu­tions to a new inter­na­tional olive tree data­base, accord­ing to Konstantinos Blazakis, a researcher work­ing with Panagiotis Kalaitzis in the Department of Horticultural Genetics and Biotechnology at the Mediterranean Agronomic Institute of Chania (MAICh) in Crete, Greece.

Blazakis hopes one appli­ca­tion of this new method will be a cell phone app that will be able to iden­tify the cul­ti­var based on a photo of an olive fruit, leaf, or endo­carp. He expects to start with Greek cul­ti­vars within the next year or two and hopes to gain sup­port to add inter­na­tional cul­ti­vars to this app as a sup­ple­men­tary project later. He admits that the cell phone app will prob­a­bly be most help­ful in coun­tries where there are many dif­fer­ent olive vari­eties, as farm­ers want to be sure they know which cul­ti­var they have.

Another of Blazakis’s goals is to con­tribute to a new inter­na­tional online data­base that will cat­a­log infor­ma­tion about the appear­ance and chem­i­cal analy­sis, among other things, of olive vari­eties world­wide. He said fif­teen part­ners from a num­ber of coun­tries are work­ing together to pre­pare this user-friendly data­base for the gen­eral pub­lic, which will be ​“based on the genetic, phys­i­o­log­i­cal, mol­e­c­u­lar, and mor­pho­log­i­cal study of each cul­ti­var.” The researchers intend to incor­po­rate pre­vi­ous data, dou­ble checked for accu­racy, as well as adding new infor­ma­tion.

This is part of the wide-rang­ing, ambi­tious Bioresources For Oliviculture, or BeFOre, project which has received fund­ing from the European Union’s Horizon 2020 research and inno­va­tion pro­gram under the Marie Skłodowska-Curie grant agree­ment and is also sup­ported by the International Olive Council.

BeFOre is ​“focused on estab­lish­ing inte­grated com­mon pro­to­cols to phe­no­type and char­ac­ter­ize plants at mol­e­c­u­lar, mor­pho­log­i­cal and phys­i­o­log­i­cal level, and eval­u­at­ing the olive oil qual­ity related to vari­eties,” accord­ing to its web­site, ​“expect­ing to improve the poten­tial of the Olive Germplasm col­lec­tions, repos­i­to­ries and banks as main sources of vari­abil­ity and of eval­u­a­tion tools to be used to increase sus­tain­abil­ity of olivi­cul­ture and to face exist­ing and aris­ing prob­lems.”

Emphasizing the impor­tance of eval­u­at­ing and char­ac­ter­iz­ing the diver­sity of olive species in order to pre­serve the rich vari­ety of genetic resources with all their dif­fer­ent health ben­e­fits, Blazakis focuses on the form and struc­ture, or mor­phol­ogy, of olives, olive trees, and their leaves.

At the 3^rd International Symposium on Horticulture in Europe in Chania, Crete in mid-October, Blazakis pre­sented the work he is doing in col­lab­o­ra­tion with Luciana Baldoni and Marina Bufacchi from the Italian National Research Council, Abdelmajid Moukhli from INRA Marrakech in Morocco, and Panagiotis Kalaitzis from MAICh (which is part of the International Center for Advanced Mediterranean Agronomic Studies).

In a pre­sen­ta­tion titled ​“Advanced Mathematical Algorithms to Characterize Olive Varieties through Morphological Parameters,” Blazakis explained that his ​“study aims to present a com­pletely new semi-auto­matic method­ol­ogy for detect­ing var­i­ous mor­pho­log­i­cal para­me­ters” of dif­fer­ent olive cul­ti­vars. His method involves 5 steps:

• col­lect sam­ples of leaves and fruit: 25 or 30 from the mid­dle of a tree whose vari­ety has been deter­mined at a nurs­ery
• cre­ate imag­ing data: take pho­tos of them
• seg­men­ta­tion: sep­a­rate the pic­ture of the leaves, olives, or seeds from the back­ground using sci­en­tific soft­ware
• apply math­e­mat­i­cal algo­rithms: use MATLAB soft­ware to cre­ate a set of instruc­tions related to var­i­ous aspects of the olive’s or leaf’s form and struc­ture, for exam­ple (for the fruit) area, perime­ter, height, max­i­mum width, posi­tion of max­i­mum width, sym­me­try or lack of sym­me­try, ellipse shape, cur­va­ture, nip­ple
• trans­late results: end up with num­bers that describe each aspect of the form and struc­ture of each olive cul­ti­var

Blazakis men­tioned that it is nec­es­sary to run more tests to be sure that the mor­pho­log­i­cal para­me­ters his team is work­ing with can dis­tin­guish between dif­fer­ent cul­ti­vars, but he believes they will suc­ceed. He added that the auto­mated tool he is devel­op­ing will pro­vide a faster and less expen­sive method to deter­mine an olive cul­ti­var than DNA analy­sis and pro­vide a use­ful option for many farm­ers who seek infor­ma­tion about their trees.

• Bioresources For Oliviculture, or BeFOre Project Description


• III International Symposium on Horticulture in Europe — SHE2016