Life cycle assessment of Parmigiano Reggiano PDO cheese with product environmental footprint method: A case study implementing improved slurry management strategies

Association Between Herd Size and the Chemical Composition and Technological Properties of Milk Intended for Parmigiano Reggiano PDO Cheese

The aim of this research was to compare the chemical composition and the technological characteristics of milk for Parmigiano Reggiano cheese produced in herds with different numbers of cows. The research was carried out on 5760 Italian Friesian herd milk samples collected from a total of 160 farms (one sample per month in each farm for three years). On each milk sample, lactose, fat, protein, casein, titratable acidity, total bacterial count, somatic cells, coliform bacteria, clostridia spores, and rennet coagulation properties were determined. Increasing herd size was positively correlated with milk production and with milk somatic cell and clostridia spores' contents (8133 kg/cow/lactation, 5.280 Log10cells/mL and 1.782 spores/L for herds with less than 30 cows; 9109 kg/cow/lactation, 5.548 Log10cells/mL and 2.138 spores/L for herds with more than 200 cows, respectively). Moreover, herd size was negatively correlated with milk fat content and with total bacterial and coliform bacteria counts (3.73 g/100 g, 4.931 Log10CFU/mL and 3.176 Log10CFU/mL for herds with less than 30 cows; 3.51 g/100 g, 4.770 Log10CFU/mL and 3.121 Log10CFU/mL for herds with more than 200 cows, respectively). Farms with more than 100 cows raised were characterised by higher milk production per cow per lactation, but the milk produced by them was also characterised by lower fat content. Finally, milk produced in the herds with a higher number of cows showed a higher frequency of optimal lactodynamographic types (better rennet-coagulation properties) than milk produced in the other herds.

Leveraging milk mid-infrared spectroscopy to authenticate animal welfare, farming practices, and dairy systems of Parmigiano Reggiano cheese

Increasing consumer concerns underscore the importance of verifying the practices and origins of food, especially certified premium products. The aim of this study was to evaluate the ability of Fourier-transform mid-infrared (FT-MIR) spectroscopy to authenticate animal welfare parameters, farming practices, and dairy systems. Data on farm characteristics were obtained from the Parmigiano Reggiano Consortium in northern Italy. Animal welfare data were collected by trained veterinarians using the assessment protocol developed by the Italian National Reference Center for Animal Welfare (CREnBA), while bulk milk test-day data were obtained from the laboratory of the Breeders Association of the Emilia Romagna Region (ARAER). A merged final data set of 12,083 bulk FT-MIR spectra records from 949 farms was created. Using a non-hierarchical clustering approach, the farms were classified into 5 dairy systems: 2 'traditional' systems, comprising farms located in either the Apennines or the Po Plain, and 2 'modern' systems, those that used TMR and that did not; a further 'traditional' dairy system was identified comprising farms rearing local breeds. To evaluate the ability of bulk milk to capture differences in farming systems, we conducted an ANOVA on milk composition. The linear models included the following effects: season, dairy system, farm, and the interaction between dairy system and season. The effect of the dairy system was significant for all milk composition traits. A 10-iteration linear discriminant analysis (LDA) was used to evaluate the discriminative ability of the spectra in classifying farming practices and dairy systems. The average results of the area under the receiver operating characteristic curve (ROC-AUC) revealed good authentication performance for genetic type (0.98), housing system (0.91), and feeding system (0.89), medium-low authentication performance for geographical area (0.70), while poor results were obtained for the percentage of concentrate in the diet and animal welfare parameters (0.57 - 0.64). With regard to dairy systems, the best result was obtained when dairy systems were grouped into 2 simplified categories, 'traditional' vs 'modern' (0.89), instead of the 5 categories (0.87). The results of this study show that FT-MIR is a useful tool for authenticating farming practices and dairy systems, but not animal welfare as defined by CREnBA evaluation criteria. Our results show that infrared spectroscopy has the potential to authenticate dairy products and quality label certifications.

Life cycle assessment of food catering menus in a university canteen located in Southern Italy

Life Cycle Assessment (LCA) is acknowledged to be suited for the assessment of the energy-environmental burdens of foods, which are estimated to be overall one of the main impact sources worldwide. A right nutrition is even more fundamental for the healthy growing of the population, which has now, however, to consider ever more the aspect connected to its environmental impact. Under this perspective, this study aims at exploring the environmental burdens associated with a local university canteen for students through the application of LCA to a set of meal combination scenarios offered weekly to consumers. For the assessment, the authors designed a set of eight meal alternatives to create four daily meal combinations (DMCs), assuming 150 customers frequent the canteen service daily. Sixteen DMC scenarios based on a 1-to-3 weekly offer frequency have been tested. Results show the environmental impacts are highly affected by the food content and the weekly offer frequency, with the largest contributions coming when higher frequencies are combined with more impactful foods in the menus. The study highlights, overall, that global warming, eutrophication, acidification, and the depletion of the abiotic elements are the most relevant indicators for such an evaluation. The study aims at building a more sustainable and resilient future for the planet, starting with producing and consuming foods that are ecologically responsible, fair and accessible, local, healthy and safe, and waste free.

A framework for cost-effectiveness analysis of greenhouse gas mitigation measures in dairy industry with an application to dairy farms in China

The dairy industry is a significant contributor to global greenhouse gas emissions (GHG). Although much effort has been directed to explore the cost-effective measures for many sectors such as electricity, building infrastructure, transportation, research on mitigation measures within dairy industry remains limited. A notable obstacle is the absence of a cost-effectiveness analysis (CEA) framework to guide decision-makers and practitioners in this sector. In response, we propose a comprehensive CEA framework tailored to mitigate GHG emissions in the dairy industry. Our conceptual framework consists of six steps: defining the system boundary to determine the activities generating GHG emissions; identifying GHG emission sources within the system boundary; identifying potential mitigation measures; determining methods to quantify GHG emissions; collecting data to estimate both GHG emissions and mitigation costs; and applying general econometric methodologies to analyze the cost-effectiveness of mitigation measures. We further conducted a case study focusing on dairy farms in China, analyzing three categories of mitigation measures: feed, energy, and manure management. The results indicate that implementing effective feed and energy measures is a cost-saving strategy, reducing the cost per unit of milk production. Conversely, adopting effective manure management measures may lead to increased costs for dairy farms. The findings offer strategic recommendations for reducing GHG emissions from dairy production in China and provide analytical insights and strategic references applicable to other developing countries.

Effect of extended heat stress in dairy cows on productive and behavioral traits

This study evaluates the response of dairy cows to short and extended heat stressing conditions (from 1 to 28 days), as expressed in changes in their behavior. Due to climate change, heat stress and strong heat waves are frequently affecting the productivity and behavior of dairy cows. In the five years under study from 2018 to 2022, two were characterized by extremely strong heat waves occurring in the region analyzed in this study (Northern Italy). The dairy cattle farm involved in this study is located in Northern Italy and includes about 1 600 Holstein Friesian lactating dairy cows. Phenotypic data were provided by the Afimilk system and compromised behavioral and productive traits. Behavioral traits analyzed were activity, rest time, rest bouts, rest ratio, rest per bout and restlessness. Production traits were daily milk yield, average milking time, somatic cell count, fat percentage, protein percentage and lactose percentage. Climate data came from the National Aeronautics and Space Administration/Prediction of Worldwide Energy Resources database. Heat stress was analyzed considering Temperature-Humidity Index (THI) averaged over 28 different time windows of continuous heat stress. Results showed that rest time and milk yield were the two traits most affected by the increased THI. Rest time was immediately affected by high THI, showing a marked decrease already from 1d window and maintaining this all over the other windows. Furthermore, results show that rest time and rest ratio were only slightly negatively correlated with milk yield (-0.14 and -0.15). In addition, heat stress has a different effect depending on parity and lactation stages on the studied traits. In conclusion, the results indicate that heat stress increases activity and compromises milk production, rest time and milk quality traits. Results further suggest that rest time can be a better parameter than activity to describe the effects of heat stress on dairy cattle. The novel approach used in this study is based on the use of different time windows (up to 28 days) before the emergence of undesired THI and allows to identify the traits that are immediately influenced by the undesirable THI values and those that are influenced only after a prolonged heat stress period.

Consumer Perception and Liking of Parmigiano Reggiano Protected Designation of Origin (PDO) Cheese Produced with Milk from Cows Fed Fresh Forage vs. Dry Hay

This study aimed to investigate consumer sensory profiles and liking of Parmigiano Reggiano PDO cheese produced with milk from cows reared indoors and fed with different forage sources, i.e., dry hay and fresh forage. Two cheese samples were tested by 119 Italian subjects, following a protocol that included a Check-All-That-Apply method to assess the sensory profile, a Just-About-Right scale to evaluate the adequacy of attributes, and questions on liking (9-point hedonic scale). A questionnaire related to personal information and consumption habits was also submitted. The color of the two samples, based on image analysis, was different: the sample produced with milk from the dairy cows fed fresh forage had a higher intensity of yellow than the other; they were also described differently (p ≤ 0.05) by participants in the consumer test. Indeed, Parmigiano Reggiano produced with milk from the cows that were fed dry hay was mainly characterized by a "fresh milk" and "solubility", while the sample produced with milk from cows fed fresh forage was described as "yellow", "seasoned", "pungent", and with a "cheese crust" flavor. Even if no significant differences were observed between the two samples in terms of liking (p ≤ 0.05), the attribute "graininess" showed a great impact on liking ratings together with "yellow" (p ≤ 0.05), apparently corresponding to a specific expectation regarding the intensity of these attributes. Data were also analyzed according to the gender of consumers, highlighting that for women, the adequacy of "fresh milk", "sweet", and "graininess" greatly impacted liking for the cheese from cows fed dry hay.

Using the product environmental footprint to strengthen the green market for sustainable feed ingredients; Lessons from a green biomass biorefinery in Denmark

Finding new and sustainable proteinaceous feed ingredients, especially those produced from locally available resources, is at the top of the agenda of many countries, including Denmark, to become feed protein self-sufficient. Protein concentrate (PC) production via the biorefining of green biomass has attracted considerable interest in recent years since they are more land efficient and productive than soybeans. The biorefining of clover-grass into protein concentrate (GPC) is a promising substitute for soybean and soybean meal, however, the environmental impacts of GPC have not been studied. The Product Environmental Footprint (PEF) method, developed by EU Joint Research Centre for the "Single Market for Green Products Initiative" was employed to assess the environmental footprints of organic GPC. The instructions, methodology, and guidelines detailed in Product Environmental Footprint Category Rules (PEFCR) Feed for Food-Producing Animals were followed to implement this PEF study. The results were intended for in-house management, process improvement, early guidance on the environmental footprint (EF) of compound feeds containing GPC, and the EF of livestock and animal production whose feed ration contains GPC. Our results showed that GPC would have a climate change impact of 1091.47 kg CO₂,eq/t GPC. We found that farming/cultivation, more specifically direct emissions from manure slurry, dominated most impact categories, including acidification and eutrophication. The results were found sensitive to the choice of allocation method and very case-specific. For instance, the climate change impact of GPC was higher under economic allocation than direct substation, but the acidification impact was lower in economic allocation than direct substitution. However, the direct substitution method, showed that treating the process residues in biogas plants could result in GPC with lower EFs. The sensitivity analysis confirmed that increasing the clover-grass productivity and decreasing either manure slurry application or nitrogenous emissions from its application are the keys to further decreasing the overall environmental impacts.

Mitigation Actions Scenarios Applied to the Dairy Farm Management Systems

The environmental impacts of the dairy industry, particularly global warming, are heavily influenced by milk production. Thus, there is an urgent need for farm-level actions and opportunities for improvement, implying mitigation strategies. The aim of this paper is to investigate five possible mitigation actions at the dairy farm and which one the farmers were willing to adopt: management and distribution of livestock manure and fertilizers, anaerobic manure treatment, optimization of the herd composition, feed quality, and heat recovery. A life cycle assessment was conducted on 63 farms using the product environmental footprint approach. The latter was divided into four quartiles, from which four representative farms were selected. For each farm, three scenarios have been analyzed considering the reference impact (reference scenario), the application of the mitigation actions (best-case scenario), and what farmers would implement (realistic scenario). Overall, the most effective mitigation actions in the best-case scenario were anaerobic manure treatment and the management and distribution of livestock manure and fertilizers, showing a potential reduction in total environmental impacts of 7-9% and 6-7%, respectively. Farmers' responses indicated a willingness to implement the latter mitigation strategy better. The optimization of the herd composition, feed quality, and heat recovery reported a range impact reduction between 0.01-5%.