# A Full Technological Traceability System for Extra Virgin Olive Oil
## Materials and Methods
### Econometric Analysis  
Besides the technical feasibility of the TTS applications and practical potential achievable benefits, an economic evaluation was performed to underline the cost impact of such a system on the olive oil production chain and thus to assess its economic sustainability. Indeed, a traceability enabled production system provides information and safety levels that potentially attract additional consumers to pay a price for the technological integration. Where consumers, and therefore producers, are willing to pay this cost, the technology can be implemented. The econometric analysis began with the analysis of part of the production process. This was represented by the final phase of olive harvesting and transfer to the oil mill, where the TTS was directly involved. This production phase of the process was technically and economically analyzed by studying the working times and estimating the costs associated with the olive harvesting process and those relative to the TTS application, from the standing olive tree to the olives delivered to the mill. This was done to evaluate the economic impact on the final product obtained, which is EVOO. Regarding the olive harvesting process, the current and most used working system in the PDO Sabina oil area under study was observed. The harvesting technique applied was semi-mechanized [19], with the use of handheld pneumatic combs driven by an air compressor powered with a diesel engine (Figure 6A). The working team was made up of four operators; two of them assisted with the harvesting with the use of 3 m rods with combs (Figure 6B), and the other two were assigned to the movement and positioning on the ground of the olive interception nets (Figure 6C), and additionally to the loading of the olives into crates before transporting them to the oil mill. Work times were recorded in a plot of the reference farm of approximately 5500 m\({}^{2}\), on which there were 60 olive trees of the \"Frantoio\" cultivar, whose average age is about 90 years. A data set was built for each olive tree harvested, detecting the diameters, the productions obtained and the number of crates used (Table 1). For each tree examined, the working times necessary to complete the olive  
Figure 4: A schematic description EVOO traceability with implemented the blockchain data flow. Figure 5: Interconnection diagram between the INFOLIVA app developed and the blockchain. harvesting process were recorded. Along with these assessments was also recorded the time necessary for the application of the TTS on every single tree considered. This info were used to estimate the economic impact that these technologies could entail if embraced by an olive oil producer. The time study was oriented to determine the productive working time with respect to a single tree harvested. The time elements considered were the following:  
* arrangement of the nets under the tree to be harvested (CT): the work was carried out by 2 operators and included the drafting of 2 or more nets per tree in order to best cover the area where the olives will fall;
* harvest time (HT): represents the work time necessary to detach the olives from the tree; it was carried out by 2 operators by means of the pneumatic combs from the ground;
* olive accumulation time (AT): represents the time necessary to remove the nets from the harvested plant and gather the olives together in a point of the net before cleaning the twigs and leaves;
* cleaning and unload time (UT): represents the time necessary for a gross cleaning from twigs and leaves of the olives collected and the unloading of the same in the crates;
* delays (D): the whole time needed for mechanical delays as needed for service or machine repair, and personal delays as interruptions due to the operators, including rest breaks;
* net productive time (NT): represented by the sum of all precedent elements without D;
* gross productive time (GT): obtained by the sum of NT and D.