Sviluppo e applicazione di metodi cromatografici per la determinazione quali-quantitativa di costituenti minoritari di prodotti d'alveare

All the products originating in the beehive are attractive ingredients for functional foods. Honey has been used since ancient times as part of traditional medicine although nowadays it is mainly used as a sweetener. The actual composition of honeys varies depending on many factors such as the pollen source, climate, environmental conditions and processing. Royal jelly is the exclusive food of queen honey bee. The chief components of royal jelly are water, proteins, carbohydrates, lipids, mineral salts and vitamins, whereas a large number of bioactive substances characterizes the minority composition. For these reasons royal jelly is commonly used like a dietary supplement. In the first part of this thesis, the typical profile of the free amino acids contained in strawberry-tree (Arbutus unedo L.) honey is reported. An optimized reversed-phase liquid chromatographic method with phenyl isothiocyanate precolumn derivatization was used. In the second part, a direct RP-HPLC method for the determination of furanic aldehydes and acids in honey is presented. Hypotheses relating to the formation of minority furanic compounds are also proposed. Finally, the assessment and validation of two chromatographic methods for the determination of water-soluble vitamins in honey and royal jelly is proposed. All the analytical methods were fully validated in terms of detection and quantification limits, precision, linearity and bias. They are all characterized by excellent analytical performances

Extraction and Analysis of Phenolic Compounds in Rice: A Review

Rice represents the main source of calorie intake in many world countries and about 60% of the world population include rice in their staple diet. Whole grain rice, also called brown rice, represent the unpolished version of the more common white rice including bran, germ, and endosperm. Many health-promoting properties have been associated to the consumption of whole grain rice and, for this reason, great attention has been paid by the scientific community towards the identification and the quantification of bioactive compounds in this food item. In this contribution, the last five years progresses in the quali-quantitative determination of phenolic compounds in rice have been highlighted. Special attention has been devoted to the most recent strategies for the extraction of the target compounds from rice along with the analytical approaches adopted for the separation, identification and quantification of phenolic acids, flavonoids, anthocyanins, and proanthocyanidins. More specifically, the main features of the “traditional” extraction methods (i.e., maceration, ultrasound-assisted extraction) have been described, as well as the more innovative protocols involving advanced extraction techniques, such as MAE (microwave-assisted extraction). The predominant role of HPLC in the definition of the phenolic profile has been examined also presenting the most recent results obtained by using mass spectrometry-based detection systems. In addition, the most common procedures aimed to the quantification of the total amount of the cited classes of phenolic compounds have been described together with the spectrophotometric protocols aimed to the evaluation of the antioxidant properties of rice phenolic extracts (i.e., FRAP, DPPH, ABTS and ORAC)

Elemental fingerprinting combined with machine learning techniques as a powerful tool for geographical discrimination of honeys from nearby regions

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors

Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machinelearning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictor

Recent Advances in the Analysis of Phenolic Compounds in Unifloral Honeys

Honey is one of the most renowned natural foods. Its composition is extremely variable, depending on its botanical and geographical origins, and the abundant presence of functional compounds has contributed to the increased worldwide interest is this foodstuff. In particular, great attention has been paid by the scientific community towards classes of compounds like phenolic compounds, due to their capability to act as markers of unifloral honey origin. In this contribution the most recent progress in the assessment of new analytical procedures aimed at the definition of the qualitative and quantitative profile of phenolic compounds of honey have been highlighted. A special emphasis has been placed on the innovative aspects concerning the extraction procedures, along with the most recent strategies proposed for the analysis of phenolic compounds. Moreover, the centrality of validation procedures has been claimed and extensively discussed in order to ensure the fitness-for-purpose of the proposed analytical methods. In addition, the exploitation of the phenolic profile as a tool for the classification of the botanical and geographical origin has been described, pointing out the usefulness of chemometrics in the interpretation of data sets originating from the analysis of polyphenols. Finally, recent results in concerning the evaluation of the antioxidant properties of unifloral honeys and the development of new analytical approaches aimed at measuring this parameter have been reviewed

Effect of Alternative Protein Feeds on the Content of Selected Endogenous Bioactive and Flavour-Related Compounds in Chicken Breast Meat

: Currently, soybean meal constitutes the main protein source for poultry production. However, the environmental and social issues related to soybean production are calling for more sustainable protein sources that can offset soybean requirements in animal production. Hermetia illucens larvae and the microalga spirulina (Arthrospira platensis) have proven to be effective alternatives to soybean meal for poultry production. In this study, the effect of 100% replacement of soy with partially defatted Hermetia illucens larvae and spirulina on the contents of selected endogenous bioactive (anserine, creatine and carnosine) and flavour-related (inosine and inosine-5´-monophosphate, IMP) compounds in chicken breast meat was evaluated. The results showed that the spirulina-based diet lowered the levels of anserine, carnosine and creatine compared to the control diet (3.3 vs. 4.1 mg/g, 0.15 vs. 0.72 mg/g and 1.49 vs. 2.49 mg/g, respectively) while IMP levels tended to be higher in spirulina-fed samples. Compared to the control group, Hermetia illucens-fed samples showed a lower content of bioactive peptides (anserine: 3.6 vs. 4.1 mg/g; carnosine: 0.39 vs. 0.72 mg/g; creatine: 2.03 vs. 2.49 mg/g), albeit to a lesser extent than the spirulina treatment group

The effect of insect or microalga alternative protein feeds on broiler meat quality

Background: In order to combat environmental and food security concerns associated with the increasing demand for soymeal related to increasing meat consumption, this study determines the chicken meat quality derived when soymeal is substituted for either partially de-fatted Hermetia illucens larval meal or spirulina (Arthrospira platensis) in broiler diets. Physicochemical parameters, sensory traits, and fatty acid composition of the meat are investigated, as well as an experiment to evaluate the impact of highly oxygenated atmosphere versus vacuum-bag packaging on shelf life was conducted. Results: Hermetia illucens did not compromise quality; meat was slightly more yellow (higher b*), had a slightly decreased pH, and was less adhesive during chewing compared to the soy-fed control. Furthermore, Hermetia illucens resulted in higher saturated fatty acids proportions in thigh meat. Spirulina resulted in redder (higher a*) and more yellow (higher b*) meat with a slightly increased umami and chicken flavour. Spirulina-fed chicken meat had higher lipid oxidation levels compared to the control after being packaged in a highly oxygenated atmosphere; although, differences between the spirulina-fed and control fatty acid composition in thigh meat were minor. Conclusion: Both alternative protein feeds show potential to replace soymeal in broiler diets; however, they do result in moderately altered products

Progress in Analytical Methods for the Characterization, Quality and Safety of the Beehive Products

Peer reviewe

The Effect of Algae or Insect Supplementation as Alternative Protein Sources on the Volatile Profile of Chicken Meat

The aim of this study was to investigate the differences in the volatile profile of meat from chickens fed with alternative protein diets (such as algae or insect) through two different trials. In Trial 1, broiler chicken at one day of age were randomly allocated to three experimental groups: a basal control diet (C) and two groups in which the soybean meal was replaced at 75% (in the starter phase) and 50% (in the grower phase) with partially defatted Hermetia illucens (HI) larvae or Arthrospira platensis (SP). In Trial 2, broiler chickens were housed and reared similar to Trial 1, with the exception that the experimental diets replaced soybean meal with either 100% partially defatted HI or 100% SP. In both trials, chickens were slaughtered at day 35. Per group, 10 chickens were submitted to volatile analysis by using solid-phase microextraction (HS-SPME) and gas chromatography–mass spectrometry (GC-MS) analysis. Results in both trials showed that levels of several lipid-derived compounds were found to be lower in chickens fed an HI diet, which could be linked to a possibly lower level of polyunsaturated fatty acid content in HI-fed chicken. In addition, the dietary treatments could be discriminated based on the volatile profile, i.e., the substitution of soy with HI or SP distinctively affected the levels of flavor compounds

Classification of Unifloral Honeys from SARDINIA (Italy) by ATR-FTIR Spectroscopy and Random Forest

: Nowadays, the mislabeling of honey floral origin is a very common fraudulent practice. The scientific community is intensifying its efforts to provide the bodies responsible for controlling the authenticity of honey with fast and reliable analytical protocols. In this study, the classification of various monofloral honeys from Sardinia, Italy, was attempted by means of ATR-FTIR spectroscopy and random forest. Four different floral origins were considered: strawberry-tree (Arbutus Unedo L.), asphodel (Asphodelus microcarpus), thistle (Galactites tormentosa), and eucalyptus (Eucalyptus calmadulensis). Training a random forest on the infrared spectra allowed achieving an average accuracy of 87% in a cross-validation setting. The identification of the significant wavenumbers revealed the important role played by the region 1540-1175 cm-1 and, to a lesser extent, the region 1700-1600 cm-1. The contribution of the phenolic fraction was identified as the main responsible for this observation