The nutritional peculiarities of dairy products made with milk from pasture-fed ruminants would require a rapid control to be authenticated and limit the risk of fraud. In the current study, ninety milk samples from two groups of goats were analysed by electronic nose, quantitative descriptive sensory (QDA) and gas chromatography-mass spectrometry analysis with the aim of discriminating between milk produced on grazing and on a confinement feeding system. The raw milk samples were taken at five different times over a period of three months (April, May and June 2021) from eighteen individual Saanen goats divided into two groups, one of which was fed outdoors on a highly biodiverse pasture. Linear discriminant analysis (LDA), carried out on electronic nose data, was able to classify the two types of milk in terms of an animal feeding system (88% correct classification). Pasture milk scored higher for sensory descriptors such as “Grassy” and “Sweet aromatic” odours. Terpene compounds were the chemical class that qualitatively differentiates the pasture milk while volatile fatty acids were the most present quantitatively. Electronic nose has proven to be a rapid, reproducible and simple method for authenticating pasture raw milk in routine control analyses.

Water Buffalo Mozzarella (BM) is a typical cheese from Southern Italy with unique flavor profile and texture. It is produced following a traditional back-slopping procedure and received the Protected Designation of Origin (PDO) label. To better understand the link between the production area, the microbiome composition and the flavor profile of the products, we performed a multiomic characterization of PDO BM collected from 57 different dairies located in the two main PDO production area, i.e. Caserta (n = 35) and Salerno (n = 22). Thus, we assessed the microbiome by high-throughput shotgun metagenomic sequencing and the Volatile Organic Compounds (VOCs) by gas chromatography/mass spectrometry (GC/MS). Streptococcus thermophilus, Lactobacillus helveticus, and Lactobacillus delbrueckii subsp. delbrueckii were identified as the core microbiome present in all samples. However, the microbiome taxonomic profiles resulted in a clustering of the samples based on their geographical origin, also showing that BM from Caserta had a greater microbial diversity. Consistently, Caserta and Salerno samples also showed different VOC profiles. These results suggest that the microbiome and its specific metabolic activity are part of the terroir that shape BM specific features, linking this traditional product with the area of production, thus opening new clues for improving traceability and fraud protection of traditional products.

Whipped chickpea aquafaba (WAF) exhibits foaming, emulsifying, and gelling properties, making it a potential ingredient for replacing cream in ice cream formulations. The aim of this study was to use WAF in combination with whey protein isolate (WPI) to produce low‐fat coffee ice cream with 50% (L50) and 80% (L80) milk cream replacement. The melting rate, color, texture, volatile compounds, and sensory attributes were analyzed to explore the physical, chemical, and sensory properties of the low‐fat ice creams compared to their full‐fat counterparts. Fat substitute performance varied based on cream replacement levels, with L50 1:0 (WAF:WPI) and L80 1:0 achieving 25% and 40% reductions in calorie content, respectively. The foaming properties of aquafaba resulted in an increased overrun, particularly in formulations where the cream reduction was 50%. While the 80% replacement showed higher intensity of “hardness,” “brown color,” and “melting” sensory descriptors, the 50% cream‐replaced ice cream showed only slight differences compared to the full‐fat version, like a higher perception of ice crystals. The combination of WAF and WPI in ice cream provides sensory properties and releases pyrazines, responsible for the coffee aroma, similar to full‐fat ice cream. The 1:1 WAF:WPI mixture for 50% cream reduction provided a suitable cream replacement, as this formulation resulted in ice cream that was not identified as different from the full‐fat control ice cream in the triangle test. Practical Application: This study demonstrates that whipped aquafaba, a by‐product of chickpea processing, can be effectively used to reduce the fat content in ice cream without compromising sensory quality. In addition to promoting the development of healthier low‐fat ice creams, this approach also contributes to food industry sustainability by reusing a commonly discarded by‐product.

The traceability of the geographical origin of coffee is a challenging issue to protect producers and consumers from the risk of fraud. A total of 162 Arabica from Peru, Colombia and Brazil, and Robusta from India, Vietnam and Uganda, espresso coffee (EC) samples of different degrees of roasting (light, medium and dark) were characterized for physico-chemical features (lipids, solids, and chlorogenic acids) and analyzed via SHS-GC/MS analysis, with the aim of discriminating the samples according to their geographical origin. Linear discriminant analysis (LDA), performed on the data of the chemical classes of the volatile organic compounds (VOCs), was able to correctly identify 97.53% of the tested samples through cross-validation. The dark roasting of the coffee beans implied a higher quantity of volatile compounds in the headspace of the EC, belonging to chemical classes of furans, esters, N-heterocyclic and sulfur compounds, reducing the differences by geographical origin. Light- and medium-roasted Robusta EC showed a major contribution of pyrazines and pyrimidines, while aldehydes, alcohols and ketones were generally more representative in Arabica samples. The quantitative distribution of volatile compounds proved to be a useful tool to discriminate samples by geographical origin.

This study investigated the feasibility of integrating hydroponic barley forage (HBF) production into dairy ruminant production, focusing on its effect on milk yield and components, energy and water footprints, and economic implications. Maize silage (MS) was used as a benchmark for comparison. The research was conducted on a water buffalo dairy farm equipped with a fully automated hydroponic system producing approximately 6,000 kg/d of HBF as fed (up 1,000 kg/d on DM basis). Thirty-three lactating water buffaloes were assigned to 3 dietary treatments based on the level of MS or HBF in the diet: D0 (100% MS), D50 (50% MS and 50% HBF), and D100 (100% HBF). The feeding trial lasted 5 weeks plus a 2-week adaptation period during which each cow underwent a weighing, BCS scoring, recording of milk yield and components, including somatic cell count and coagulation characteristics. Based on the data obtained from the in vivo study, the water and energy footprints for the production of MS and HBF and buffalo milk, as well as income over feed cost, were evaluated. Complete replacement of MS with HBF resulted in a slight increase in milk yield without significant impact on milk component. The resource footprint analysis showed potential benefits associated with HBF in terms of water consumption. However, the energy footprint assessment showed that the energy ratio of HBF was less than 1 (0.88) compared with 11.89 for MS. This affected the energy efficiency of milk yield in the 3 diets, with the D50 diet showing poorer performance due to similar milk yield compared with D0, but higher energy costs due to the inclusion of HBF. The production cost of HBF was about 4 times higher than that of farm-produced MS, making feed costs for milk yield more expensive. Nevertheless, HBF can potentially improve income over feed costs if it increases milk yield enough to offset its higher production costs. Overall, the results suggest that the current practice of using HBF to replace high quality feedstuffs as concentrates is likely to result in energy and economic losses.