The optimal high pressure processing treatments (200-400 MPa, 5-15 min) of a pasty matrix of beepollen mixed with peptone water (1.5 g/mL) and bee-pollen added to a pineapple juice-based beverage matrix (0-10% (w/v)) were studied in order to guarantee food safety and maximum retention of bioactive compounds. Salmonella and yeasts were used as target microorganisms, while total carotenoid content (TCC), total phenolic content (TPC), and antioxidant capacity (FRAP) were studied from the food quality point of view. For the pasty matrix of bee-pollen, the results showed a significant influence of pressure and time, increasing the levels of TPC, FRAP, and TCC, in comparison with a control sample. A treatment of 395 MPa for 15 min was found as the optimal. For the pineapple juicebased beverage matrix, the factors pressure and bee-pollen concentration increased the levels of TPC, FRAP and TCC. Optimal conditions were found at 315 MPa for 14.5 min with 8% (w/v) of beepollen.

The electronic nose is one of the most innovative techniques which had been used in the analysis of food and other aroma matrices. This device imitates the human olfactory system through sensors which are partially specific for different groups of volatile chemicals and differentiating and classifying food (by involving multivariate statistics) and it is also used for establishing quality and control parameters. Although the technique has been increasingly applied in research and industry, few studies have been published in the scientific literature referring to validating its use as an analytical methodology. This work' s main objective was to standardise and validate the aromatic profile analysis method for differentiating apiculture products: honey, pollen and propolis. Standardisation involved modifying sample preparation and system variables while validation involved analysis of repeatability and intermediate repeatability of the method and establishing its uncertainty. The results showed that it was possible to set suitable operational parameters for each apicultural product while validation data showed that this technique did not reveal significant differences as reliable values were obtained when using this device as an analysis and quality control tool.

The transmission of passive immunity from the sow to the neonate piglets through colostrum is crucial for their future development. The aim of this experiment was to demonstrate that feeding the live yeast Saccharomyces cerevisiae boulardii CNCM I-1079 (SCB) increases the immunoglobulin G (IgG) concentration in colostrum. In total, 620 colostrum samples were taken from mixed-parity sows (1-9) in 11 farms in Colombia. There were 2 treatments: control (CON; standard feed in gestation and lactation), and SCB (CON + 1 × 109 colony forming units (CFU)/kg, fed from 3 weeks before the expected farrowing date). The samples were taken within the first 4 hours after the birth of the first piglet, from both sides of the teats of the sow, and immediately analyzed with a MA871 refractometer to obtain a °Brix value. Furthermore, each value was attributed to 1 of the 4 following categories regarding IgG concentration: Very good, Adequate, Limited, and Poor. Data were analyzed with SPSS Statistics 26.0 (IBM) and submitted to an analysis of variance with farm as random effect, parity rank and treatment as fixed effects, and their interactions. However, no interaction was found between any of the variables studied. Colostrum from sows in the SCB treatment displayed a higher °Brix value (P < 0.001) than the 1 from sows in the CON treatment. Additionally, the percentage of sows fitting the categories Very good and Adequate was greater in the SCB treatment than in the CON, and the one fitting the categories Limited and Poor was greater in the CON treatment than in the SCB. It is concluded that supplementing sows with Saccharomyces cerevisiae boulardii CNCM I-1079 from 3 weeks before farrowing increases IgG concentration in colostrum, helping the neonate piglets to acquire the passive immunity necessary to improve later performance.

Honey is a natural sweetener and its quality labels are associated to its botanical or geographical origin, which is being established by palynological and sensorial analysis. The use of fast and non-invasive techniques such as an electronic nose can become an alternative for honey classification. In this study, the operational parameters of a commercial electronic nose were validated to determine the honey odor profile. A central composite design with five factors, three levels and 28 assays was used, varying sample amounts (1, 2 and 3 g), incubation temperature (30, 40 and 50 °C), incubation time 30 min), gas flow (50, 150 and 250 mL/min) and injection time (100, 200 and 300 s). The commercial nose had ten sensors. Repeatability was evaluated with a coefficient of variation of 10 %. The response surface methodology was used and the optimal operating conditions were: 3 g of sample, incubation at 50 °C for 17 min, gas flow of 100 mL/min and sampling time of 150 s. Finally, these parameters were used to analyze 19 samples of honey, which were classified according to their odor profiles, showing that it can be a useful tool to classify honey.

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