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Ricotta forte is a traditional fermented whey cheese cream mainly manufactured in Apulia and locally in Southern Italy; it is included among the traditional agrifood products of Italian Ministry of Agricultural, Food and Forestry Policies aiming to be preserved for its cultural and gastronomic heritage. This product, obtained starting from acid-thermal denatured cheese whey added with small amounts of various milks (ricotta), undergoes a long fermentation and aging processes (over 6 months) that confers a distinctive organoleptic bouquet (pungent and cheesy flavour) and high palatability score (Faccia et al., 2018). The few microbiological studies focus on sample-specific heterofermentative lactobacilli and yeast populations, supposed to promote acidification, proteolysis and lipolysis (Baruzzi et al., 2000; Caputo et al., 2018). Since Ricotta forte is receiving increasing interest by the gourmet food markets, a standardized and sustainable manufacturing process is to develop to obtain Ricotta forte with high level of safety and quality without preservatives. In this context, OR7 workpackage of Innotipico project cod. 3QKDQX3 (Apulia Regional INNONETWORK programme 2018-2019 ) aims to develop a process of production of Ricotta forte compromising three main steps (acidification, maturation and refinement) mediated by selected microbial strains (lactic acid bacteria, yeasts and fungi, respectively) from artisanal whey cheese and ITEM Microbial Culture Collection of ISPA. The ongoing activities have already allowed to find 10 lactic acid bacteria and yeast strains able to quickly acidify the fresh ricotta and improve its spreadability and its flavour. These skills will be validated in semi-industrial productions during the experimental development activities.eng, Dr. Pasquale Del Vecchio offered data management support.

In the laboratory of a bakery, PM2,5 indoor samplings have been performed every each six hour meanly from 7th to 19th April 2013. For each daily sampling four PM2,5 samples have been collected. In total 40 samples were obtained. On each sample the following PAHs were determined: BaA(228), Bb,kF (252), BaP (252), BgP (276), Ip (276), DbA (278). The mean PAHs concentrations per sampling hourly range have shown, in the first and last sampling range, higher values than the other two hourly ranges. Because of it was not possible to perform samplings in the store of the baker, we have used the Computational Fluid Dynamics model in order to obtain information about dynamics and dispertion of human health hazard pollutants in the store and have an extimation of B(a)P concentration in that area.

Indoor air pollution assessment in work environments remains challenging due to a combination of logistic reasons and availability of costly instrumentation for data acquisition and post-processing. Existing literature focuses on energy production environments, hospitals, and less so on food production spaces. Studies on indoor air quality in bakeries are scarce or even absent. Motivated by this, the present study investigates indoor air quality in a bakery located in Bari province in South Italy, using a combination of approaches including analytical chemistry analyses and compu- tational fluid dynamics to reconstruct the air ventilation in response to air temperature gradients within the working environment. PM2.5 indoor samplings were collected every 6 h from 7 to 19 April 2013 in the proximity of two bakery ovens powered by gas and wood, respectively. For each sampling day, 4 PM2.5 samples were collected: from 3:00 to 9:00 h (first), from 9:00 to 13:30 h (second), from 14:00 to 21:00 h (third), and from 21:00 to 3:00 h (fourth). In total, 40 samples were collected. On each sample, several polycyclic aromatic hydrocarbons (PAHs) were deter- mined such as benzo[a]anthracene (228), benzo[b]fluoranthene (252), benzo[k]fluoranthene (252), benzo[a]pyrene (252), benzo[g,h,i]perylene (276), indeno[1,2,3-cd]pyrene (276), and dibenzo[a,h]anthracene (278), the main com- pounds of 16 priority US Environmental Protection Agency (US-EPA) PAHs in particulate phase. The PAH mean concentrations showed higher values during the first (from 3:00 to 9:00 h) and fourth (from 21:00 to 3:00 h) sampling intervals than the other two with benzo[a]pyrene mean values exceeding the Italian law limit of 1 ng/m3. Taking into account benzo[a]pyrene mean concentration for the first interval and the first plus the second one, which are the hours with the largest working activity, we have estimated that the baker and co-workers are exposed to a cancer risk of 4.3 × 10-7 and 5.8 × 10-7, respectively (these values are lower than US-EPA recommended guideline of 10-6). Our study was complemented by numerical analyses using state-of-the-art computational fluid dynamics to reconstruct at high resolution air movement from the various working places, i.e., the bakery and the selling area which were connected via a door. The numerical simulations were possible given that surface temperature using infrared thermog- raphy as well as air temperature was continuously recorded throughout the sampling acquisition. The use of this approach allowed us to estimate the transport and diffusion of benzo[a]pyrene from one area to the other thus complementing the point sampling information. Computational fluid dynamic simulation results confirm the presence of benzo[a]pyrene in the laboratory as obtained from the measurements and suggests its presence in the sales' area of the bakery with concentrations similar those found in the laboratory.