Risk factors of high somatic cell count and differential somatic cells in early lactation associated with selective dry cow therapy.

The routine use of intramammary antimicrobial products in all dairy cows at the beginning of the dry period is no longer allowed in European Union (EU) countries due to the new Regulation (EU) 2019/6 to reduce antimicrobial resistance. This study investigated the application of a selective dry cow therapy scheme and the risk factors of high individual milk somatic cell count (SCC) and individual neutrophil count in early lactation, as a response to the application of a selective dry cow therapy (SDCT) protocol. The study was carried out on three commercial farms, and a total of 243 lactating cows were monitored at the end of lactation and at the beginning of the next one, 91 of which were dried off without the use of antimicrobials (NoT) based on milk SCC, differential somatic cell count (DSCC), and the response of Vetscan DC-Q milk analyser, using a secret algorithm. The remaining 152 cows received antimicrobials (T). After calving, similar means were observed between the two treatment groups for SCC (4.8 vs 4.9 log10 cells/ml for T and NoT, respectively, P = 0.5) and total milk leucocyte count (TLC) (5 vs 5.1 log10 cells/ml for T and NoT, respectively, P = 0.7) in milk. However, the use of antimicrobials led to a lower DSCC (58 vs 64% for T and NoT, respectively, P = 0.01) and lower percentage of neutrophils (59 vs 64% for T and NoT, respectively, P = 0.05), although the levels of DSCC and percentage of neutrophils in cows dried off without antimicrobials remained lower than the risk threshold suggested by the international literature. A logistic regression was computed after the application of selective dry cow therapy to identify risk factors of high milk SCC (≥100 000 cells/mL) at the beginning of lactation. Increased milk SCC after calving was related to high SCC at the end of lactation and abandonment of antimicrobial therapy at dry-off. Moreover, the length of the dry period, milk protein content, and flank cleanliness in the last test day before dry-off were other factors in the logistic regression. Neutrophil counts at the beginning of the next lactation were affected by the same factors that influenced SCC, together with milk production, TLC, and macrophages on the last test day. The results obtained in these studied farms showed that selective dry cow therapy may be applied without adversely affecting the next lactation.

Comparison of the use of life cycle assessment and ecological footprint methods for evaluating environmental performances in dairy production.

One popular methodology for assessing the environmental impact of livestock sector is Life Cycle Assessment (LCA), that quantifies the environmental impact of a product. Ecological Footprint (EF) performs an environmental sustainability assessment, by comparing the demand for natural capital by an economic activity with the offer of such capital within a certain territory. The aim of the study was the comparison between LCA and EF in assessing the environmental performances of milk production, assuming as case study three cattle farms with increasing levels of production intensity. Different metrics and functional units (FU) (i.e., fat and protein corrected milk, FPCM and hectare) were adopted for LCA analysis, considering some of the major impact categories. For greenhouse gases emissions, the Global Warming Potential (GWP) and the Global Temperature Potential (GTP) were considered. Both metrics were calculated assuming or not the distinction between biogenic and fossil methane. Adopting GWP as a metric, the results per kg of FPCM provided by the LCA highlighted a different trade off compared to the EF method: the farm with the highest productive intensity produced the least impactful milk in terms of GWP but had the most negative Ecological Balance (EB). The same occurred for the other impact categories. When GTP was adopted, or the hectare was considered as FU, the least intensive farm, characterized by greater feed self-sufficiency, became the one that produced the least impactful milk and had the least negative EB. The study highlighted the scientific significance of the integration between the two approaches for creating a comprehensive representation of the effects of human activities on the environment. The LCA method evaluates impacts intensity referred to a specific functional unit and its results are strongly influenced by productive efficiency; the EF method evaluates environmental sustainability of productions in relation to the territory that supports them.

Diffusion of precision livestock farming technologies in dairy cattle farms.

The rising global demand for animal products and the growing public concerns about the environment and animal welfare require dairy farms to improve their efficiency and apply more sustainable farming systems. Precision Livestock Farming (PLF) could represent a valuable support in addressing these challenges. In recent years, dairy farms have been modernising and introducing new sensors and automatic systems for managing the herd. However, the diffusion of new technologies in Italian dairy farms is still limited and farmers are reluctant to invest in precision systems. The aim of the study was to investigate the presence of PLF tools in Italian dairy farms, the motivations, benefits and limits of technological investments from the farmers' point of view and the factors affecting the diffusion of technology. From November 2020 to June 2021, an online questionnaire was distributed and 52 responses were obtained. About 79% of the farms were located in Lombardy. The more represented milking system was the conventional milking parlour (73%), followed by automatic milking (19%). The average age of respondents was quite low: 35% of them was less than 40 years old and more than 50% was between 40 and 60. Statistical analyses were performed to evaluate the effects of different factors on the presence of technology at farm. The age of the farmer, the milk production level and the presence of an automatic milking system influenced the technological level of the farm. Precision systems that provide information on animal activity for the management of reproduction and on milk yield and flow are the most popular and are considered among the most useful. Management of reproduction and milk production are the areas where farmers appear to show interest for future investments as well. Younger farmers appear to have implemented more PLF systems than older ones, and they show a propensity to invest in latest generation precision tools. Farmers seem to have a growing interest in PLF, but some limits have been identified: the investment costs, followed by the lack of time to check information from sensor systems and the difficulty in data interpretation. As PLF technologies can play an important role in the development of sustainable, animal-friendly and efficient livestock production, further improvements and efforts are necessary to increase the propensity to PLF of dairy farmers. Results can be useful in the Italian context but also in other countries where dairy farming is rapidly intensifying but PLF is encountering resistance.

Looking for high-production and sustainable diets for lactating cows: A survey in Italy.

The aim of the present study was to evaluate, through a survey conducted on commercial farms, the global warming potential (GWP) of different lactating cow total mixed rations (TMR) and to identify the best dietary strategies to increase feed efficiency (FE) and reduce enteric CH4 emission. A total of 171 dairy herds were selected: data about dry matter intake (DMI), lactating cow TMR composition, and milk production and composition were provided by farmers. Diet GWP (kg of CO2 equivalents; CO2eq) was calculated as sum of GWP (kg of CO2eq) of each included ingredient, considering inputs needed at field level, feed processing, and transport. For soybean solvent meal, land use change was included in the assessment. Enteric methane production (g/d) was estimated [using the equation CH4 (g/d) = 2.54 + 19.14 × DMI] to calculate CH4 emission for kilograms of fat- and protein-corrected milk (FPCM). The data set was analyzed by generalized linear model and logistic analysis using SAS 9.4 (SAS Institute Inc., Cary, NC). The frequency distribution showed wide variation among farms for GWP (kg of CO2eq) of TMR: approximately 25% of the surveyed farms showed a diet GWP of 15 kg of CO2eq, 20% showed a GWP of 13 kg of CO2eq, and 16.7% showed a GWP of 17 kg of CO2eq. The variation among farms was due to the feedstuffs used. Among feedstuffs, soybean meal (SBM) had the highest correlation with the GWP of the TMR as shown by the following equation: TMR GWP (kg of CO2eq) = 2.49 × kg of SBM + 6.9 (R2 = 0.547). Moreover, diets with inclusion of SBM >15% of dry matter (DM) did not result in higher milk production than diets with a lower inclusion of SBM (≤15%). Average daily milk production of cows was 29.8 [standard deviation (SD) 4.83] kg with fat and protein contents of 3.86% (SD 0.22) and 3.40% (SD 0.14), respectively. The average DMI (kg/d) of lactating cows was 22.3 (SD 2.23). Logistic analysis demonstrated that corn silage ≤30% of diet DM was associated with higher FE. Almost 50% of farms had an average value of 15.0 g of CH4/kg of FPCM and about 30% of farms had an average of 12.5 g of CH4/kg of FPCM. The results demonstrated that lower enteric CH4 production was related to inclusion (% of diet DM) of ≤12% alfalfa hay and >30% corn silage. Diets with >34% neutral detergent fiber had higher CH4 production (>14.0 g/kg of FPCM) than those with lower neutral detergent fiber content. In contrast, lower enteric CH4 production (≤14.0 g/kg of FPCM) was related to diets characterized by net energy of lactation (NEL) >1.61 Mcal/kg and >4% ether extract. The variability in TMR GWP shows significant potential for reducing the GWP of a diet through choice and inclusion levels of ingredients (mainly SBM) and the possibility of decreasing methane enteric emission associated with milk production on a commercial scale.

Environmental impact of rabbit meat: The effect of production efficiency.

The aim of this trial was to analyse the environmental impact of the rabbit production system, through a cradle to-slaughterhouse gate using a life cycle approach. Since in a rabbit farm the production efficiency depends on the feed conversion and quantity of meat produced, scenarios characterized by different slaughter weights and dissimilar level of mortality during the fattening phase were hypothesized. Climate change determined in the standard rabbit resulted in 3.86 kg CO2 eq/kg live weight, slightly higher than that of broilers and not different from that of pork. High and Low mortality scenarios resulted in impact changes from +5.22 and -2.31%, respectively, compared with the standard system. An increase of environmental impact values (up to 36%) was registered when live weight enhanced from 2.7 to 2.9 kg for standard and heavy rabbits. The results obtained underline the strict link between the ability to convert feed into meat and the environmental sustainability of meat production also in the rabbit system.

Impact assessment of traditional food manufacturing: The case of Grana Padano cheese.

The dairy sector is recognised as one of the most impacting agricultural activities. In Italy approximately 24% of cow's milk is destined to Grana Padano, a Protected Designation of Origin long ripening cheese. The Grana Padano production has increased by 10% in the last decade and approximately reached 183,000 t in 2015. Around 38% of this production is exported to Germany, US, France and to the rest of the world. This study evaluated the environmental impact of production of Grana Padano, through a "cradle to cheese factory gate" Life Cycle Assessment. The study involved an Italian cheese factory that produces about 3.6% of the total production of Grana Padano cheese and a group of 5 dairy farms, chosen among the farms that sold all milk produced to the cheese factory. The functional unit was 1 kg of Grana Padano cheese 12-month ripened. Environmental impacts of co-products: whey, cream, butter and buttermilk were also evaluated. Two sensitivity analyses were conducted: the first one had the aim to explore the effect of different allocation methods based on dry matter content, economic or nutritive value of cheese, respectively; the second one considered the variation of the impacts of milk production and its effect on cheese environmental impact. Milk production phase gave the most important contribution to the environmental impact of cheese, with a percentage of 93.5-99.6% depending on the impact category. Excluding milk production from the system boundary, milk transport and use of electricity were the main responsible of the environmental impact of cheese-making process. The climate change impact for the production of 1 kg Grana Padano was 10.3 kg of CO2 eq, using a dry matter allocation method, while 16.9 and 15.2 kg of CO2 eq adopting economic and nutritive value allocation methods, respectively.

How can farming intensification affect the environmental impact of milk production?

The intensification process of the livestock sector has been characterized in recent decades by increasing output of product per hectare, increasing stocking rate, including more concentrated feed in the diet, and improving the genetic merit of the breeds. In dairy farming, the effects of intensification on the environmental impact of milk production are not completely clarified. The aim of the current study was to assess the environmental impacts of dairy production by a life cycle approach and to identify relations between farming intensity and environmental performances expressed on milk and land units. A group of 28 dairy farms located in northern Italy was involved in the study; data collected during personal interviews of farmers were analyzed to estimate emissions (global warming potential, acidification, and eutrophication potentials) and nonrenewable source consumption (energy and land use). The environmental impacts of milk production obtained from the life cycle assessment were similar to those of other recent studies and showed high variability among the farms. From a cluster analysis, 3 groups of farms were identified, characterized by different levels of production intensity. Clusters of farms showed similar environmental performances on product basis, despite important differences in terms of intensification level, management, and structural characteristics. Our study pointed out that, from a product perspective, the most environmentally friendly way to produce milk is not clearly identifiable. However, the principal component analysis showed that some characteristics related to farming intensification, such as milk production per cow, dairy efficiency, and stocking density, were negatively related to the impacts per kilogram of product, suggesting a role of these factors in the mitigation strategy of environmental burden of milk production on a global scale. Considering the environmental burden on a local perspective, the impacts per hectare were positively associated with the intensification level.

Interactions of vacuum, b-phase duration, and liner compression on milk flow rates in dairy cows.

Vacuum, b-phase duration, and liner compression are 3 milking machine factors that affect peak milk flow rate; however, extreme values of these factors can also have negative effects on teat tissue health. The main and interactive effects of vacuum, b-phase duration, and liner compression on peak milk flow rate were studied by independently controlling these causal variables over a wide range of settings, using a central composite experimental design (42 to 53 kPa of system vacuum, 220 to 800 ms of b-phase, and residual vacuum for massage of 16 to 30 kPa; corresponding to a liner compression of 8 to 14 kPa). The results of this study indicated that increasing the vacuum and b-phase duration always increased peak milk flow rate (no relative maximum was reached); however, the rate of increase of flow rate decreased as the vacuum and b-phase were increased. Increasing the liner compression also increased peak flow rates, with an increasing effect at greater vacuum. The interaction between vacuum and liner compression and the lack of interaction between b-phase and liner compression indicate that for a corresponding increase in peak milk flow rate, increasing the b-phase produced less teat-end tissue congestion than increasing the vacuum. The effect of milking vacuum on peak milk flow rate was smaller than that reported in previous studies, probably because of the independent adjustment of milking vacuum and liner compression used in this study. The effect of b-phase duration on peak milk flow was also smaller in this study than in previous studies, probably because of the independent adjustment of b-phase and d-phase durations used in this study.

Factors affecting milk flow traits in dairy cows: results of a field study.

The study of milk flow curves provides useful information for enhancing milking efficiency and protecting udder health by adapting milking machine and milking procedures to the physiological requirements of the cow. The aim of this experiment was to investigate, using field data, the relationships among traits of the milk flow curves, their sources of variation, and milking performances in terms of milk production, machine-on time, and udder health. A total of 2,486 milk flow curves of the whole udder were collected in 82 Italian Holstein-Friesian dairy herds in the Lombardy region of Italy. Approximately one-third (35.1%) of milk flow curves were classified as bimodal. Most flow characteristics were influenced by lactation number, days in milk, and peak flow but also strongly affected by premilking operations. Proper udder preparation, including forestripping and predipping, resulted in better milking performances compared with poor preparation, with greater milk yield per milking, shorter milking time, and lesser bimodality. Premilking delay time, between the start of teat stimulation and cup attachment, affected milking time significantly: The shortest milking time was obtained for a range of delay time between 1 and 60 s. As the delay time increased, the percentage of bimodality dropped significantly. Increasing the number of clusters per operator led to greater percentages of bimodal curves. The greater somatic cell count of cows with bimodal curves supports the hypothesis of the negative effect of bimodality on udder health and indicates the importance of avoiding its occurrence using proper pre-milking procedures.