Ecological and social factors influence interspecific pathogens occurrence among bees.

The interspecific transmission of pathogens can occur frequently in the environment. Among wild bees, the main spillover cases are caused by pathogens associated with Apis mellifera, whose colonies can act as reservoirs. Due to the limited availability of data in Italy, it is challenging to accurately assess the impact and implications of this phenomenon on the wild bee populations. In this study, a total of 3372 bees were sampled from 11 Italian regions within the BeeNet project, evaluating the prevalence and the abundance of the major honey bee pathogens (DWV, BQCV, ABPV, CBPV, KBV, Nosema ceranae, Ascosphaera apis, Crithidia mellificae, Lotmaria passim, Crithidia bombi). The 68.4% of samples were positive for at least one pathogen. DWV, BQCV, N. ceranae and CBPV showed the highest prevalence and abundance values, confirming them as the most prevalent pathogens spread in the environment. For these pathogens, Andrena, Bombus, Eucera and Seladonia showed the highest mean prevalence and abundance values. Generally, time trends showed a prevalence and abundance decrease from April to July. In order to predict the risk of infection among wild bees, statistical models were developed. A low influence of apiary density on pathogen occurrence was observed, while meteorological conditions and agricultural management showed a greater impact on pathogen persistence in the environment. Social and biological traits of wild bees also contributed to defining a higher risk of infection for bivoltine, communal, mining and oligolectic bees. Out of all the samples tested, 40.5% were co-infected with two or more pathogens. In some cases, individuals were simultaneously infected with up to five different pathogens. It is essential to increase knowledge about the transmission of pathogens among wild bees to understand dynamics, impact and effects on pollinator populations. Implementing concrete plans for the conservation of wild bee species is important to ensure the health of wild and human-managed bees within a One-Health perspective.

Green Chemometric-Assisted Characterization of Common and Black Varieties of Celery.

Celery (Apium graveolens L., var. Dulce), is a biennial herbaceous plant belonging to the Apiaceae family, cultivated in humid soils in the Mediterranean basin, in Central-Southern Europe, and in Asia. Despite its wide diffusion and although it is well-known that cultivar/origin strongly influences plant composition, only a few studies have been carried out on the different types of celery. The present work aims to investigate four different Italian types of celery (two common, Elne and Magnum celery, and two black, Torricella Peligna Black and Trevi Black celery), and to test, whether the combination of FT-IR spectroscopy and chemometrics allows their ecotype discrimination. The peculiarity of this study lies in the fact that all the analyzed celeries were grown in the same experimental field under the same soil and climate conditions. Consequently, the differences captured by the FT-IR-based tool are mainly imputable to the different ecotypes. In order to achieve this goal, FT-IR profiles were handled by two diverse classifiers: sequential preprocessing through ORThogonalization (SPORT) and soft independent modeling by class analogy (SIMCA). Eventually, the highest classification rate (90%, on an external set of 100 samples) has been achieved by SPORT.

Geographical Discrimination of Bell Pepper (Capsicum annuum) Spices by (HS)-SPME/GC-MS Aroma Profiling and Chemometrics.

Dried and ground red pepper is a spice used as seasoning in various traditional dishes all over the world; nevertheless, the pedoclimatic conditions of the diverse cultivation areas provide different chemical characteristics, and, consequently, diverse organoleptic properties to this product. In the present study, the volatile profiles of 96 samples of two different ground bell peppers harvested in diverse Italian geographical areas, Altino (Abruzzo) and Senise (Lucania), and a commercial sweet paprika, have been studied by means of headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The investigation of their volatile profile has led to the identification of 59 analytes. Eventually, a discriminant classifier, Partial Least Squares Discriminant Analysis (PLS-DA), was exploited to discriminate samples according to their geographical origin. The model provided very accurate results in external validation; in fact, it correctly classified all the 30 test samples, achieving 100% correct classification (on the validation set). Furthermore, in order to understand which volatiles contribute the most at differentiating the bell peppers from the different origins, a variable selection approach, Variable Importance in Projection (VIP), was used. This strategy led to the selection of sixteen diverse compounds which characterize the different bell pepper spices.