Overall, laboratory water quality analysis must have stability in their results, especially in laboratories accredited by ISO 17025. Accredited parameters should be strictly reliable. Using control charts to ascertain divergences between results is thus very useful. The present work applied a methodology of analysis of results through control charts to accurately monitor the results for a wastewater treatment plant. The parameters analyzed were pH, BOD₅, COD, total suspended solids, and total phosphorus. The stability of the results was analyzed from the control charts and 30 analyses performed in the last 12 months. From the results, it was possible to observe whether the results are stable, according to the rehabilitation factor that cannot exceed WN = 1.00 and the efficiency of removal of pollutants that remained above 70% for all parameters. The method of determining the technological reliability and stability of the treatment station using control charts is an efficient tool for detecting any instability in the results. These results help to monitor the results of the analyses more clearly and thus enable a rapid response to possible disturbances and maintain the quality of the analysis control, as well as determining the accreditation entities.

Olive mill wastewaters (OMWWs) are an environmental problem in the Mediterranean region, and it is crucial to explore strategies for their treatment and repurposing. The chemical precipitation technique (CPT) has been presented as a cost-effective wastewater treatment solution that might be applied to OMWW. The CPT-resulting precipitant subproducts (sludge) may be reprocessed (e.g., agricultural fertilizer and/or soil amendment), while the treated wastewater may be repurposed or reused (e.g., irrigation, aquaponic, or industrial processes). This study aimed to evaluate the efficacy of CPT in treating wastewater from the olive oil industry from an ecotoxicological perspective. Additionally, to assess the safe use of the obtained sludge in CPT treatment, its effects on soil biota were assessed. For this, a set of ecotoxicological assays using freshwater (Raphidocelis subcapitata, Daphnia magna and Danio rerio), terrestrial invertebrates (Folsomia candida and Enchytraeus crypticus), and plants (Brassica oleracea and Lolium perenne) were used as model organisms. Results demonstrated that CPT reduced OMWW toxicity to freshwater organisms, offering a favorable outlook on CPT’s potential as a wastewater treatment method. Increasing application rates of sludge in soil reduced the shoot biomass and the hydric content of both plants compared to the control. Survival of F. candida and E. crypticus was not affected by sludge in soil at any tested application rate, yet sludge application negatively affected the reproduction of both species, even at relevant sludge application rates (2%) of sludge in soils. Overall, the applicability of this sludge obtained by the CPT treatment in soils should be carefully evaluated due to the observed adverse effects on soil biota. Although the results of CPT were promising in reducing the toxicity of OMWW for these aquatic species, some adjustments/improvements should be performed to improve this technique and use all the obtained resources (treated water and sludge) in a fully circular perspective.

Improving the energy efficiency of traditional production methods while preserving their cultural and economic value is a challenge aligned with the Sustainable Development Goals of the 2030 agenda. Refrigeration during cheese maturation is particularly energy-intensive, contributing significantly to greenhouse gas emissions and operating costs. An approach to make traditional cheese production more sustainable, through the development of a prototype ripening chamber with a natural refrigerant-based refrigeration system powered by renewable energy was studied. A dedicated system based on an Internet of Things architecture was developed using low-cost sensors, microcontroller units, and single-board computers to enable real-time measurement and monitoring of environmental variables and energy consumption throughout the ripening process. A comparative analysis was conducted using ewe’s milk cheese, produced and ripened with Protected Designation of Origin conditions, in both the prototype and the conventional chambers over four weeks, quantifying energy consumption and evaluating product quality. Results demonstrate the technical feasibility of energy efficient and sustainable refrigeration systems, as well as the possibility of retrofitting installed cheese ripening chambers with affordable IoT monitoring systems, while maintaining traditional cheese quality standards.

The enzymatic coagulation of milk, crucial in cheese production, entails the hydrolysis of κ-casein and subsequent micelle aggregation. Conventional assessment standards, such as the Berridge method, depend on visual inspection and are susceptible to operator bias. Recent methods for the identification of milk-clotting time rely on optical, ultrasonic, and image-based technologies. In the present work, the composition of milk was evaluated through standard methods from ISO and AOAC. Milk coagulation time (MCT) was measured through viscosimetry, Berridge’s operator-driven technique, and a machine learning approach employing computer vision. Coagulation was additionally observed using the Optigraph, which measures micellar aggregation through near-infrared light attenuation for immediate analysis. Sheep milk samples were analysed for their composition and coagulation characteristics. Coagulation times, assessed via Berridge (BOB), demonstrated high correlation (R² = 0.9888) with viscosimetry (Visc) and machine learning (ML). Increased levels of protein and casein were linked to extended MCT, whereas lower pH levels sped up coagulation. The calcium content did not have a notable impact. Optigraph assessments validated variations in firmness and aggregation rate. Principal Component Analysis (PCA) identified significant correlations between total solids, casein, and MCT techniques. Estimates from ML-based MCT closely align with those from operator-based methods, confirming its dependability. This research emphasises ML as a powerful, automated method for evaluating milk coagulation, presenting a compelling substitute for conventional approaches.

Cheese production is an ancient practice that is associated with the food and cultural identity of different peoples. There are over 500 cheese types globally, including 207 with protected denomination of origin (PDO) and 70 with protected geographical indication (PGI) status in the European Union (EU). Each cheese has various biochemical compositions, production methods, and maturation environments. This study has provided a critical review of the environmental impacts of cheese production, focusing on energy consumption, greenhouse gas (GHG) emissions, and the integration of renewable energy sources as sustainable strategies for this sector. Based on case studies and life cycle assessment (LCA) methodologies, the analysis revealed significant variability in energy use (3.0 to 70.2 MJ/kg) and GHG emissions (up to 22.13 kg CO₂ eq/kg), influenced by factors such as the cheese type, production complexity, system boundaries, and the technological or geographical context. Particular attention was given to heat treatment, refrigeration, and maturation processes, which contribute substantially to the overall energy footprint. The paper also discusses the methodological challenges in LCA studies, including the role of co-product allocation and database limitations. Finally, strategic renewable energy options, such as biogas recovery and solar thermal integration, are discussed as sustainable alternatives to reduce the environmental footprint of the dairy sector and support its sustainability.