An Innovative Malaxer Equipped with SCADA Platform for Improving Extra Virgin Olive Oil Quality.

Agriculture 4.0 is gaining more attention, and all companies are thinking about innovating machines to increase income and improve the quality of the final products. In the agro-food sector, there is space for innovation, as it is far behind the industrial sector. This paper reports an industrial-scale study on the application of an innovative system for the extraction of Sicilian EVOO (extra virgin olive oil) to improve both process management and the quality of the product. Based on previous studies, the authors suggested an innovative machine equipped with a SCADA (supervisory control and data acquisition system) for oxygen and process duration monitoring and control. The objective of the research was thus to discuss the development of a SCADA platform applied to the malaxer and the establishment of an optimized approach to control the main process parameters for obtaining high-quality EVOO. The SCADA system application in the EVOO extraction process allowed a qualitative improvement of the Sicilian EVOO of Nocellara del Belice and Cerasuola cultivars. The use of the innovative system made it possible to increase the values of tocopherols (by about 25%) in Cerasuola cultivar and total phenol content (by about 30%) in Nocellara del Belice cultivar EVOOs.

Biodiversity and dairy traits of lactic acid bacteria from foliage of aromatic plants before and after dehydration process monitored by a smart sensors system.

The main hypothesis of this work was to evaluate the presence of lactic acid bacteria (LAB) intrinsically resistant to plant essential oils in sage (Salvia officinalis L.) and laurel (Laurus nobilis), for future applications in functional cheese production by addition of aromatic herbs. The effect of the drying process on the viability of LAB was evaluated with three biomass densities (3, 4 and 5 kg/m2). The drying densities did not affect weight loss, but influenced the levels of LAB of sage and laurel. A total of 10 different strains of Enterococcus faecium, Enterococcus mundtii, Enterococcus raffinosus and Leuconostoc mesenteroides were identified from laurel, while sage did not host any LAB species. In particular, L. mesenteroides was the only species sensitive to the heat treatment. Only five strains, all enterococci, were resistant to at least one antibiotic, even though no strain showed gelatinase or haemolytic activity. The investigation on the technological traits useful in cheese making demonstrated that all LAB can be considered non starter LAB, because they were characterized by a slow acidification capacity (the pH was still above 6.00 after 3 d) and a very limited autolysis (the maximum decrease of the optical density at 599 nm was barely 0.2).

Application of A Precision Apiculture System to Monitor Honey Daily Production.

Precision beekeeping or precision apiculture is an apiary management strategy based on the monitoring of individual bee colonies to minimize resource consumption and maximize the productivity of bees. Bees play a fundamental role in ensuring pollination; they can also be considered as indicators of the state of pollution and are used as bio monitors. Beekeeping needs continuous monitoring of the animals and can benefit from advanced intelligent ambiance technologies. The aim of this study was the design of a precision apiculture system (PAS) platform for monitoring and controlling the following environmental parameters: wind, temperature, and relative humidity inside and outside the hive, in order to assess their influence on honey production. PAS is based on an Arduino board with an Atmel microcontroller, and the connection of a load cell for recording the weight of the hive, relative humidity and temperature sensor inside the hive, and relative humidity and temperature sensor outside the hive using an anemometer. PAS was installed in common hives and placed in an open field in a French honeysuckle plot; the system was developed to operate in continuous mode, monitoring the period of 24 April-1 June 2019. Temperature was constant in the monitored period, around 35 °C, inside the hive, proving that no criticalities occurred regarding swarming or absconding. In the period between 24 and 28 May, a lack of honey production was recorded, attributed to a lowering of the external temperature. PAS was useful to point out the eventual reduction in honey production due to wind; several peaks of windiness exceeding 5 m s-1 were recorded, noting that honey production decreases with the peaks in wind. Therefore, the data recorded by PAS platform provided a valid decisional support to the operator. It can be implemented by inserting additional sensors for detecting other parameters, such as rain or sound.

Risk exposure to vibration and noise in the use of agricultural track-laying tractors.

Human exposure to mechanical vibration may represent a significant risk factor for exposed workers in the agricultural sector. Also, noise in agriculture is one of the risk factors to be taken into account in the evaluation of workers' health and safety. One of the major sources of discomfort for the workers operating a tractors is the noise to which they are exposed during work. The aim of this study was to evaluate the risk of exposure to whole-body vibration for the operator driving track-laying tractors in vineyard orchard and the noise level. The experimental tests were performed with six different track-laying tractors coupled with the same rototilling machine. The results showed that the vibration values of track-laying tractors coupled to rototilling machine, referred to the 8-hour working day, were always higher than 0.5 m s-2, the daily exposure action value established by Directive 2002/44/EC of the European Parliament. The daily noise exposure levels always exceeded the exposure limit value of 87 dB(A) established by Directive 2003/10/EC of the European Parliament. The ANOVA repeated measures model showed that the factor 'site', namely, the soil characteristics, did not influence the vibration level on the X and Y-axes of the tractors measured, regardless of their age. In the Z-axis, the vibration level was enhanced as the soil structure increased. As tractor age increased, the influence of soil characteristics was less important. In term of the age of the tractor and the number of hours worked, it was possible to identify three risk classes, which were up to 3,000 hours worked and offered a low risk; from 3,000 - 6,000 hours worked with a medium risk, and over 6,000 hours with a high risk level.