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Multi-agent-based modelling and simulation provides an adequate environment to study the real world. This paper presents the use of a multi-agent research and simulation (MARS) framework and model design based on the overview, design concepts, design (ODD) protocol to model and simulate small-scale management strategies that are important for increased milk yield per cow. In reality, strategies for farm management at a small-scale level are purely based on heuristics that cost farmers and lead to inadequate milk yields. A differential assessment of the farming strategies was conducted to yield a data-driven approach for selection of the best strategies, which in turn will optimize investments and increase milk yield. The agent-based modelling and simulation revealed that, the studied strategies based on income, farm, and farmer-based characteristics influenced an increase of up to 7.72 L of milk above the average (12.7 ± 4.89). Generally, there was an increase in milk yield based on the identified evolvement strategies; from a baseline data average milk yield of 12.7 ± 4.89 to simulated milk yield average of 17.57 ± 0.72. Evaluating the agent-based models in real-world scenarios will strengthen the assurance that the identified strategies can move small-scale dairy farmers from low to higher milk producers. [ABSTRACT FROM AUTHOR]

The dairy sector is the second largest agricultural sector in the EU and Lithuania. It faces economic challenges (price volatility, farm consolidation and downsizing, etc.), but its importance outstrips other agricultural sectors (combining agro-systems and providing valuable food products for people). The aim of the study is to identify the vulnerabilities of dairy farms and to consider how to improve their performance after analysis of dairy farms in dairy exporting EU countries. As the problem of the study is complex, a set of indicators was analysed, including farm size, milk yield per cow, number of cows per annual work unit (AWU), milk production per fodder area, feed autonomy, milk price, total operating costs, depreciation, farm net value added per AWU, milk production per capita, and GDP at current prices per capita. The analysis was carried out using data from the Farm Accountancy Data Network (FADN) for 2017–2019. As Lithuania's dairy sector is export-oriented, EU countries with more than 100% milk self–sufficiency (18 countries in total) were chosen for the comparison. The multi-criteria decision-making methods (MCDM) were used for the study. The multi-criteria evaluation revealed that countries that are leaders in dairy exports obtained the best values of dairy farm performance. These countries (Denmark, Netherlands, Ireland, and Belgium) have the highest farm size, production scale, productivity, and income indicators. While Slovenian, Latvian, and Lithuanian dairy farms performed poorly in terms of productivity and economic indicators, these countries achieve competitiveness in the dairy sector through lower milk prices, higher utilisation of own resources, and higher levels of public support. [ABSTRACT FROM AUTHOR]

The emission factor method (Tier 1) recommended by the Intergovernmental Panel on Climate Change (IPCC) is commonly used to estimate greenhouse gas (GHG) emissions from livestock and poultry farms. However, the estimation accuracy may vary due to practical differences in manure management across China. The objectives of this study were to estimate the direct and indirect nitrous oxide (N2O) emissions from dairy manure management between 1990 and 2021 in China and characterize its spatial and temporal variations following IPCC guideline Tier 2. The N2O emission factor (EF) of dairy cow manure management systems was determined at the national level and regional level as well. The results showed that the national cumulative N2O emission of manure management from 1990 to 2021 was 113.1million tons of CO2 equivalent, ranging from 90.3 to 135.9 million tons with an uncertainty of ±20.2%. The annual EF was 0.021 kg N2O-N (kg N)−1 for total emissions, while it was 0.014 kg N2O-N (kg N)−1 for direct emissions. The proportions of N2O emissions in North China, Northeast China, East China, Central and Southern China, Southwest China and Northwest China were 32.3%, 18.6%, 11.4%, 5.8%, 6.1% and 25.8%, respectively. In addition, N2O emissions varied among farms in different scales. The respective proportions of total N2O emissions from small-scale and large-scale farms were 64.8% and 35.2% in the past three decades. With the improvement in farm management and milk production efficiency, the N2O emissions per unit mass of milk decreased from 0.77 × 10−3 kg to 0.48 × 10−3 kg in 1990–2021. This study may provide important insights into compiling a GHG emission inventory and developing GHG emission reduction strategies for the dairy farming system in China. [ABSTRACT FROM AUTHOR]

In order to highlight the influence of cattle farming systems on dairy products, assessments were carried out on certain varieties of cheese—marked with the "Mountain product" quality label in comparison with those conventionally produced ones not bearing the quality label. The study was carried out using products obtained from raw milk issued from seven farms and transformed into cheese in four small dairy factories from the mountainous area of Dornelor Basin, Suceava County, Northeastern Romania. The analyzed cheese issued from the "mountain" production system were "Călimani" Schweizer, "Călimani" Cașcaval, "Călimani" smoked Cașcaval, and "Călimani" Telemea—salty brined cheese. Both the "Mountain cheese" and conventional cheese samples produced throughout the same shift were collected and kept under refrigeration conditions until laboratory analysis in order to compare the production systems. The physico-chemical analysis revealed higher amounts of minerals (2.8 to 10.7% Ca; 2.8 to 9.5% P; 12.3% to double the amount of Fe, p < 0.001) and polyunsaturated fatty acids (+5.6 to +13.7%), in mountain cheeses versus the conventionally processed ones. Also, the sanogenic indices had higher values in the "Mountain cheese", such as the polyunsaturation index (+4.3 to 7.8%) and hypocholesterolic/hypercholesterolic fatty acid ratio (+1.8 to 3.7%), while the atherogenic index and the thrombogenic index had lower values (−1.9 to −4.3%) compared to the conventionally produced cheese, thus revealing healthier properties for consumers. The Enterobacteriaceae family species were identified in "Mountain cheese", while they were absent from conventionally processed cheese, knowing the raw matter milk is thermally treated at ultra-high temperatures in the latter ones. In the "Mountain cheese", such microorganisms were found within the safety regulation limits and contributed to providing flavor, taste, color, and specific texture, making it superior in terms of sensorial quality compared to the conventionally produced cheese. [ABSTRACT FROM AUTHOR]

Texas is the third-largest milk-producing state in the U.S., with Central Texas being the second-largest milk-producing region in Texas. The average size of a dairy herd in Texas is 1829 cows. In Central Texas alone, there are 88,000 dairy cows. However, there is a lack of environmental impact research for this region. The overall objective of this case study is to evaluate the net carbon and carbon equivalent balances for a large dairy operation in Central Texas. The dairy selected for this study has a herd size of 5000 milking cows. The data assumptions were made regarding the selected dairy's performance and production for the 2021 production year. These data include herd size and management, milk production, crop production, feed purchases, and on-farm energy usage. The USDA-Integrated Farm System Model (IFSM) was used to estimate the daily and annual greenhouse gas emissions and environmental footprint of the dairy by quantifying the operation's carbon footprint based on its 2021 performance and management practices. Research outcomes identify and quantify sources of greenhouse gas (GHG) emissions produced on the dairy farm. Additionally, the carbon footprint (CF) was determined by estimating the CO2 equivalents (CO2-eq) emitted or sunk from animal and manure emissions, direct and indirect land emissions, net biogenic and anthropogenic CO2 emissions, and the production of resource inputs. The results of this case study indicated that the carbon footprint (CF) of the 5000-milking-head dairy in Central Texas was 0.40 lb. of CO2 per lb. of fat- and protein-corrected milk (FPCM) when considering biogenic CO2 and 0.83 lb. of CO2 per lb. of FPCM without biogenic CO2. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative framework to describe sustainable transitions of food systems while considering simultaneously socio-economic and environmental issues, in a just transition perspective. This framework (i) describes the structural changes needed for a sustainable transition in food systems; (ii) assess their effects on employment at the farm and processing industry level; (iii) detect the political levers needed to make this transition a just one—that is, preserving jobs and livelihoods for communities. Using the decarbonation pathway for the agricultural sector issued from the French National Low-Carbon Strategy as reference, we developed two scenarios for the French dairy sector which have the same level of climate ambitious, but a different approach to reach the target. Aiming exclusively to achieve a greenhouse gases reduction, the first scenario relies only on supply side measures. This scenario has a negative impact in terms of employment loss at the farm level and in the agri-food sector. In contrast, a multifunctional scenario considering simultaneously climate, biodiversity, health, and employment issues, and playing with policy measures targeting supply, demand and market organisation can maintain jobs in the farm and agri-food sector, contributes to restore the agro-biodiversity and develops food products compatible with healthy nutritional guidelines. [ABSTRACT FROM AUTHOR]

This paper aims to analyse the technical efficiency (TE) of dairy farms and find its determinants. To accomplish this problem, the Stochastic Frontier Analysis was applied. The data were obtained from the Farm Accountancy Data Network database for dairy farms (TF15-45—Specialist dairying) for 2004–2019. Dairy farms were divided into four clusters according to their physical size (number of livestock units per farm) and economic size (standard output per farm). The largest farms by physical and economic size are located in Denmark and Cyprus. The smallest, in comparison, are in Bulgaria, Croatia, Latvia, Lithuania, Austria, Poland, Romania, and Slovenia. Farms in the EU are relatively technically efficient, i.e., they use their resources efficiently to produce maximum output (production). However, they have the potential to achieve better economic results and be more competitive, as the size of farms' is not fully optimised. The abolition of the milk quota can be considered a factor in improving technical efficiency, as the indicator is higher after the abolition. New and old member states have almost comparable technical efficiency levels (the p-value of the t-test is 0.463), with old members having slightly higher level TE. Subsidies have contradictory effects on TE. Farm efficiency with higher subsidies per cow is higher for farms with €51–100/cow. However, as subsidies increase, TE decreases. Only the group of farms with the highest subsidies has a higher TE. More diversified farms are more technically efficient than specialised farms. Milk yield did not influence the analysed indicator. The analysis results can serve the stakeholders as a tool for modelling future agricultural policy, as the European farms are very heterogenous and show different conditions and economic outcomes. [ABSTRACT FROM AUTHOR]

This study assessed the impact of different calf rearing systems on calf health, behavior, meat quality, and oxidative stability. The study involved two groups of bull calves: conventionally penned calves (control, fed with use of automatic feeders) and calves reared alongside foster cows (experimental). The presence of foster cows was found to have a significant positive influence on calf health. Calves raised with foster cows experienced lower rates of diarrhea, delayed instances of coughing, and a reduced occurrence of rhinitis compared to conventionally reared calves. Behavioral observations revealed differences in sucking and licking behaviors between the two groups. Calves with foster cows displayed more consistent patterns of these behaviors, while conventionally reared calves exhibited greater variability. Additionally, the experimental group consistently achieved higher daily weight gains, suggesting the potential for larger and more valuable carcasses at slaughter. Importantly, there were no significant differences in the quality of veal between the two rearing groups. This included fatty acid composition, color attributes, and myoglobin levels, indicating consistent meat quality. In summary, this research highlights the advantages of rearing systems that prioritize calf health and behavior, emphasizing maternal care and natural behaviors. Such systems hold promise for improving calf welfare and enhancing the sustainability of the meat production industry. The integration of foster cows into dairy farming practices emerges as a practical and effective approach, particularly for the rearing of bull calves. [ABSTRACT FROM AUTHOR]

Studying the distribution characteristics of bioaerosols and their interaction with the environment is crucial for dairy farms. The distribution of aerosols differs in dairy farming from farming of other livestock, and their sensitivity to environmental factors varies across sites. Field experiments were conducted in an intensive commercial dairy farm in Northern China to investigate the horizontal and vertical distribution of culturable bacterial bioaerosols. Concentration levels and particle size ranges were analyzed, and the impact of multiple environmental factors on culturable bacterial bioaerosols was assessed. Significant variations in culturable bacterial bioaerosol concentrations were observed across eight functional zones, ranging from 1.14 × 103 to 7.35 × 103 CFU/m3. Culturable bacterial bioaerosols exhibited consistent carrier distribution patterns across six different size ranges. Vertical analysis revealed significantly higher culturable bacterial bioaerosol concentrations at a 1 m height compared to 4 m (p < 0.05), while similar size distributions were observed at different heights of the same sampling location. The top three environmental factors influencing culturable bacterial bioaerosol concentrations were PM100 concentration, wind direction, and air temperature. This study provides insights into the distribution characteristics of culturable bacterial bioaerosols on dairy farms and their response to environmental factors. The findings serve as a reference for evaluating bioaerosol emissions and establishing daily disinfection management measures on dairy farms. [ABSTRACT FROM AUTHOR]

Persistent organic pollutants have particular ecotoxicological importance and they are amongst the most harmful groups of persistent pollutants. The complexity of persistent organic pollutants highlights the different sources of pollution from which they came and, depending on which, their profile could be characterized. In the first part of this review, the main characteristics of persistent organic pollutants were described, focusing on their complexity and toxic potential in relation to environmental elements. The second part of the review includes data related to the occurrence and incidence of persistent organic pollutants in different types of feed and cow's milk, focusing on the characteristic profile of pollutants as an indicator of the sources of pollution. Moreover, a description regarding the timing and duration of the contamination of feed and milk was carried out, evaluating the distribution of pollutants within the analyzed samples and highlighting those whose presence is predominant or whose residues persist in the environment for long periods. The review concludes that the identification of pollution sources associated with different proportions of organic pollutants found in different samples could represent a suitable solution for biomonitoring the potential contamination in a geographical area. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the polymorphisms of the beta-casein gene and describe the association between the beta-casein genotypes and milk production in high milk-production Slovak Holstein cattle herds. Genomic DNA was isolated from the hair root samples of 1478 cows using a commercial column kit. The detection of the specific alleles A1 and A2 of the CSN2 gene was carried out using three molecular-genetics methods, including the TaqMan allelic discrimination assay, ACRS-PCR and SBE primer extension technology. The results of the molecular-genetic analysis were used for calculating the genetic structure in the analyzed population. All three genotypes, including A1A1 (5.28%), A1A2 (37.08%) and A2A2 (57.64%), were detected. The frequency of the allele A1 was 23.82% and the allele A2 was 76.18%. The statistical analysis and data preparation were performed using the SAS 9.2 Enterprise Guide 4.2 software. A general linear model (GLM) and the least squares means adjusted for multiple comparisons were used. A significant positive effect of the beta-casein genotype A2A2 on protein in kilograms and partially for the protein content in Holstein cows was found. Only the highest the least squares means for the fat percentage was found for the genotype A1A1 compared to the genotype A2A2. This can be considered a slightly negative trend. [ABSTRACT FROM AUTHOR]

The milk quantity of dairy cows is the most important piece of data in farm management. However, it is difficult to measure and record the milk quantity for small-scale dairy farms. Therefore, the automatic milk quantity recording system for small-scale dairy farms is studied. It consists of a weight scale mechanism and an embedded system installed on a wheelbarrow for measuring and recording milk quantity. For the process of the system, the milk quantity of each cow is measured based on the load cell in kilogram units. The data such as real-time clock, cow ID, and individual and total milk quantity are recorded on a microSD memory card and sent based on the Internet of Things (IoT) for recording in a Google sheet. Furthermore, the system can alert the farmers to remove the teat cups when the cow milk comes to the end by detecting the derivative of milk quantity with respect to time. The experimental results show that the proposed system can correctly measure and record milk quantity. This system can help the farmers in improving and managing dairy farms effectively. [ABSTRACT FROM AUTHOR]

This study examines the farm-level factors that influence differences in total factor productivity (TFP) on dairy farms. To this end, a fixed-effects regression approach is applied to panel data for dairy farms obtained from the Farm Accountancy Data Network for Northern Ireland over the period of 2005 to 2016. The findings are largely consistent with existing empirical evidence, showing that herd size, milk yield, stocking density, and share of hired labour have a positive and statistically significant impact on TFP, while labour input per cow, purchased feed input per cow, and share of direct payments in total farm output have a negative and statistically significant impact. The more complex relationships, namely age, education, and investment, have been unpacked using interaction terms and nonlinear approximation. The impact of age is negative, and the drag on productivity grows as age increases. Capital investment and education both have a positive impact on farm-level TFP, as well as on their interaction. Policy recommendations on strategies and best practices to help dairy farms tackle productivity constraints are suggested. [ABSTRACT FROM AUTHOR]