Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study.

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO2 equivalents per ton of fat-and-protein-corrected milk (kg CO2e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO2e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO2e/t FPCM for cows with one case of CM, by 69 kg CO2e/t FPCM for cows with two cases of CM and by 92 kg CO2e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.

Production, partial cash flows and greenhouse gas emissions of simulated dairy herds with extended lactations.

The transition period is the most critical period in the lactation cycle of dairy cows. Extended lactations reduce the frequency of transition periods, the number of calves and the related labour for farmers. This study aimed to assess the impact of 2 and 4 months extended lactations on milk yield and net partial cash flow (NPCF) at herd level, and on greenhouse gas (GHG) emissions per unit of fat- and protein-corrected milk (FPCM), using a stochastic simulation model. The model simulated individual lactations for 100 herds of 100 cows with a baseline lactation length (BL), and for 100 herds with lactations extended by 2 or 4 months for all cows (All+2 and All+4), or for heifers only (H+2 and H+4). Baseline lactation length herds produced 887 t (SD: 13) milk/year. The NPCF, based on revenues for milk, surplus calves and culled cows, and costs for feed, artificial insemination, calving management and rearing of youngstock, was k€174 (SD: 4)/BL herd per year. Extended lactations reduced milk yield of the herd by 4.1% for All+2, 6.9% for All+4, 1.1% for H+2 and 2.2% for H+4, and reduced the NPCF per herd per year by k€7 for All+2, k€12 for All+4, k€2 for H+2 and k€4 for H+4 compared with BL herds. Extended lactations increased GHG emissions in CO2-equivalents per t FPCM by 1.0% for All+2, by 1.7% for All+4, by 0.2% for H+2 and by 0.4% for H+4, but this could be compensated by an increase in lifespan of dairy cows. Subsequently, production level and lactation persistency were increased to assess the importance of these aspects for the impact of extended lactations. The increase in production level and lactation persistency increased milk production of BL herds by 30%. Moreover, reductions in milk yield for All+2 and All+4 compared with BL herds were only 0.7% and 1.1% per year, and milk yield in H+2 and H+4 herds was similar to BL herds. The resulting NPCF was equal to BL for All+2 and All+4 and increased by k€1 for H+2 and H+4 due to lower costs for insemination and calving management. Moreover, GHG emissions per t FPCM were equal to BL herds or reduced (0% to -0.3%) when lactations were extended. We concluded that, depending on lactation persistency, extending lactations of dairy cows can have a positive or negative impact on the NPCF and GHG emissions of milk production.

Estimating the economic impact of subclinical ketosis in dairy cattle using a dynamic stochastic simulation model.

The objective of this study was to estimate the economic impact of subclinical ketosis (SCK) in dairy cows. This metabolic disorder occurs in the period around calving and is associated with an increased risk of other diseases. Therefore, SCK affects farm productivity and profitability. Estimating the economic impact of SCK may make farmers more aware of this problem, and can improve their decision-making regarding interventions to reduce SCK. We developed a dynamic stochastic simulation model that enables estimating the economic impact of SCK and related diseases (i.e. mastitis, metritis, displaced abomasum, lameness and clinical ketosis) occurring during the first 30 days after calving. This model, which was applied to a typical Dutch dairy herd, groups cows according to their parity (1 to 5+), and simulates the dynamics of SCK and related diseases, and milk production per cow during one lactation. The economic impact of SCK and related diseases resulted from a reduced milk production, discarded milk, treatment costs, costs from a prolonged calving interval and removal (culling or dying) of cows. The total costs of SCK were €130 per case per year, with a range between €39 and €348 (5 to 95 percentiles). The total costs of SCK per case per year, moreover, increased from €83 per year in parity 1 to €175 in parity 3. Most cows with SCK, however, had SCK only (61%), and costs were €58 per case per year. Total costs of SCK per case per year resulted for 36% from a prolonged calving interval, 24% from reduced milk production, 19% from treatment, 14% from discarded milk and 6% from removal. Results of the sensitivity analysis showed that the disease incidence, removal risk, relations of SCK with other diseases and prices of milk resulted in a high variation of costs of SCK. The costs of SCK, therefore, might differ per farm because of farm-specific circumstances. Improving data collection on the incidence of SCK and related diseases, and on consequences of diseases can further improve economic estimations.

Animal Board Invited Review: Comparing conventional and organic livestock production systems on different aspects of sustainability.

To sustainably contribute to food security of a growing and richer world population, livestock production systems are challenged to increase production levels while reducing environmental impact, being economically viable, and socially responsible. Knowledge about the sustainability performance of current livestock production systems may help to formulate strategies for future systems. Our study provides a systematic overview of differences between conventional and organic livestock production systems on a broad range of sustainability aspects and animal species available in peer-reviewed literature. Systems were compared on economy, productivity, environmental impact, animal welfare and public health. The review was limited to dairy cattle, beef cattle, pigs, broilers and laying hens, and to Europe, North America and New Zealand. Results per indicators are presented as in the articles without performing additional calculations. Out of 4171 initial search hits, 179 articles were analysed. Studies varied widely in indicators, research design, sample size and location and context. Quite some studies used small samples. No study analysed all aspects of sustainability simultaneously. Conventional systems had lower labour requirements per unit product, lower income risk per animal, higher production per animal per time unit, higher reproduction numbers, lower feed conversion ratio, lower land use, generally lower acidification and eutrophication potential per unit product, equal or better udder health for cows and equal or lower microbiological contamination. Organic systems had higher income per animal or full time employee, lower impact on biodiversity, lower eutrophication and acidification potential per unit land, equal or lower likelihood of antibiotic resistance in bacteria and higher beneficial fatty acid levels in cow milk. For most sustainability aspects, sometimes conventional and sometimes organic systems performed better, except for productivity, which was consistently higher in conventional systems. For many aspects and animal species, more data are needed to conclude on a difference between organic and conventional livestock production systems.

Effect of dry period length on milk yield over multiple lactations.

Shortening or omitting the dry period (DP) can improve the energy balance of dairy cows in early lactation through a decrease in milk yield after calving. Little is known about the effect of a short or no DP on milk yield over multiple lactations. Our objectives were (1) to assess the effect of DP length over multiple lactations on milk yield, and (2) to assess if the prediction of milk yield in response to DP length could be improved by including individual cow characteristics before calving. Lactation data (2007 to 2015) of 16 Dutch dairy farms that apply no or short DP were used to compute cumulative milk yield in the 60 d before calving (additional yield) and in the 305 d after calving (305-d yield), and the mean daily yield over the interval from 60 d before calving to 60 d before next calving (effective lactation yield). The DP categories were no (0 to 2 wk), short (3 to 5wk), standard (6 to 8 wk), and long (9 to 12 wk). The effect of current DP and previous DP on yields was analyzed with mixed models (n=1,420 lactations). The highest effective lactation yield of fat- and protein-corrected milk (FPCM) was observed for cows with a standard current DP (27.6kg per day); a daily decrease was observed of 0.6kg for a long DP, 1.0kg for a short DP, and 2.0kg for no DP. Previous DP did not significantly affect the effective lactation yield. Thus, cows can be managed with short or no DP over consecutive lactations without a change in quantity of milk losses. Cows that received no DP for consecutive lactations had a lower additional yield before calving (-172kg of FPCM), but a higher 305-d yield (+560kg of FPCM), compared with cows that received no DP for the first time. This could lessen the improvement of the energy balance in early lactation when no DP is applied a second time compared with the first time. For the second objective, a basic model was explored to predict effective lactation yield based on parity, DP length, and first-parity 305-d yield (n=2,866 lactations). The basic model was subsequently extended with data about recent yield, days open, and somatic cell count. Extending the model reduced the error of individual predictions by only 6%. Therefore, the basic model seems sufficient to predict the effect of DP length on effective lactation yield. Other individual cow characteristics can still be relevant, however, to make a practical and tailored decision about DP length.

Dutch dairy farms after milk quota abolition: Economic and environmental consequences of a new manure policy.

The abolition of the Dutch milk quota system has been accompanied by the introduction of a new manure policy to limit phosphate production (i.e., excretion via manure) on expanding dairy farms. The objective of this study was to evaluate the effect of these recent policy changes on the farm structure, management, labor income, nitrogen and phosphate surpluses, and greenhouse gas emissions of an average Dutch dairy farm. The new manure policy requires that any increase in phosphate production be partly processed and partly applied to additional farmland. In addition, phosphate quotas have been introduced. Herein, we used a whole-farm optimization model to simulate an average farm before and after quota abolition and introduction of the new manure policy. The objective function of the model maximized labor income. We combined the model with a farm nutrient balance and life-cycle assessment to determine environmental impact. Based on current prices, increasing the number of cows after quota abolition was profitable until manure processing or additional land was required to comply with the new manure policy. Manure processing involved treatment so that phosphate was removed from the national manure market. Farm intensity in terms of milk per hectare increased by about 4%, from 13,578kg before quota abolition to 14,130kg after quota abolition. Labor income increased by €505/yr. When costs of manure processing decreased from €13 to €8/t of manure or land costs decreased from €1,187 to €573/ha, farm intensity could increase up to 20% until the phosphate quota became limiting. Farms that had already increased their barn capacity to prepare for expansion after milk quota abolition could benefit from purchasing extra phosphate quota to use their full barn capacity. If milk prices increased from €355 to €420/t, farms could grow unlimited, provided that the availability of external inputs such as labor, land, barn capacity, feed, and phosphate quota at current prices were also unlimited. The milk quota abolition, accompanied by a new manure policy, will slightly increase nutrient losses per hectare, due to an increase in farm intensity. Greenhouse gas emissions per unit of milk will hardly change, so at a given milk production per cow, total greenhouse gas emissions will increase linearly with an increase in the number of cows.

Effective lactation yield: A measure to compare milk yield between cows with different dry period lengths.

To compare milk yields between cows or management strategies, lactations are traditionally standardized to 305-d yields. The 305-d yield, however, gives no insight into the combined effect of additional milk yield before calving, decreased milk yield after calving, and a possible shorter calving interval in the case of a shortened dry period. We aimed to develop a measure that would enable the comparison of milk yield between cows with different dry period (DP) lengths. We assessed the importance of accounting for additional milk yield before calving and for differences in calving interval. The 305-d yield was compared with a 365-d yield, which included additional milk yield in the 60 d before calving. Next, an effective lactation yield was computed, defined as the daily yield from 60d before calving to 60 d before the next calving, to account for additional milk yield before calving and for differences in calving interval. Test-day records and drying-off dates of 15 commercial farms were used to compute the 305-d, 365-d, and effective lactation yields for individual cows. We analyzed 817 second-parity lactations preceded by no DP, a short DP (20 to 40 d), or a conventional DP (49 to 90 d). Compared with cows with a conventional DP, the 305-d yield of cows with no DP was 7.0 kg of fat- and protein-corrected milk (FPCM) per day lower, and the 305-d yield of cows with a short DP was 2.3 kg of FPCM per day lower. Including additional milk yield before calving in the 365-d yield reduced this difference to 3.4 kg of FPCM per cow per day for cows with no DP and to 0.9 kg of FPCM per cow per day for cows with a short DP. Compared with cows with a conventional DP, median days open were reduced by 25d for cows with no DP and by 18d for cows with a short DP. Accounting for these differences in calving interval in the effective lactation yield further decreased yield reductions for cows with no DP or a short DP by 0.3 kg of FPCM per cow per day. At the herd level, estimated 365-d yield losses for cows with no DP or a short DP differed from effective lactation yield losses by 0.4 to -0.8 kg FPCM per cow per day. Accounting for additional milk yield before calving had a major and consistent effect on yield comparisons of cows with different DP lengths. The effect of correcting for calving interval was more variable between farms and will especially be important when calving interval is affected by DP length.

Technical note: Validation of sensor-recorded lying bouts in lactating dairy cows using a 2-sensor approach.

Lying behavior is a relevant indicator for the evaluation of cow welfare. Lying can be recorded automatically by data loggers attached to one of the hind legs of a cow. A threshold for the duration of a lying bout (LB) record is required, however, to discard false records caused by horizontal leg movements, such as scratching. Previously determined thresholds for similar sensors ranged from 25s to 4min. We aimed to validate LB recorded by the IceQube sensor (with IceManager software; IceRobotics, South Queensferry, UK) and to determine a threshold to distinguish true from false LB records in lactating dairy cows. A novel method of validation, which does not require time-consuming behavioral observations, was used to generate a larger data set with potentially more incidental short LB records. Both hind legs of 28 lactating dairy cows were equipped with an IceQube sensor for a period of 6d and used as each other's validation. Classification of LB records as true (actual LB) or false (recorded while standing) was based on 3 assumptions. First, all standing records (absence of LB records) were assumed to occur while standing. Second, false LB records due to short leg movements could not occur in both hind legs simultaneously. Third, true LB only occurred if the LB records of the paired sensors coincided. False LB records constituted 4% of the records. Based on a maximum accuracy of 0.99, a minimum duration of LB records of 33 s was determined, implying a sensitivity of 0.99 and a specificity of 0.98. Applying this threshold of 33 s hardly affected estimates of daily lying time, but improved estimates of frequency and mean duration of LB for individual cows. The importance of distinguishing short LB was demonstrated specifically for detection of calving. The 2-sensor approach, using sensor outputs on both hind legs as each other's validation, is a time-efficient method to validate LB records that can be applied to different sensors and husbandry conditions.

Effect of feed-related farm characteristics on relative values of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain.

Breeding has the potential to reduce greenhouse gas (GHG) emissions from dairy farming. Evaluating the effect of a 1-unit change (i.e., 1 genetic standard deviation improvement) in genetic traits on GHG emissions along the chain provides insight into the relative importance of genetic traits to reduce GHG emissions. Relative GHG values of genetic traits, however, might depend on feed-related farm characteristics. The objective of this study was to evaluate the effect of feed-related farm characteristics on GHG values by comparing the values of milk yield and longevity for an efficient farm and a less efficient farm. The less efficient farm did not apply precision feeding and had lower feed production per hectare than the efficient farm. Greenhouse gas values of milk yield and longevity were calculated by using a whole-farm model and 2 different optimization methods. Method 1 optimized farm management before and after a change in genetic trait by maximizing labor income; the effect on GHG emissions (i.e., from production of farm inputs up to the farm gate) was considered a side effect. Method 2 optimized farm management after a change in genetic trait by minimizing GHG emissions per kilogram of milk while maintaining labor income and milk production at least at the level before the change in trait; the effect on labor income was considered a side effect. Based on maximizing labor income (method 1), GHG values of milk yield and longevity were, respectively, 279 and 143kg of CO2 equivalents (CO2e)/unit change per cow per year on the less efficient farm, and 247 and 210kg of CO2e/unit change per cow per year on the efficient farm. Based on minimizing GHG emissions (method 2), GHG values of milk yield and longevity were, respectively, 538 and 563kg of CO2e/unit change per cow per year on the less efficient farm, and 453 and 441kg of CO2e/unit change per cow per year on the efficient farm. Sensitivity analysis showed that, for both methods, the absolute effect of a change in genetic trait depends on model inputs, including prices and emission factors. Substantial changes in relative importance between traits due to a change in model inputs occurred only in case of maximizing labor income. We concluded that assumptions regarding feed-related farm characteristics affect the absolute level of GHG values, as well as the relative importance of traits to reduce emissions when using a method based on maximizing labor income. This is because optimizing farm management based on maximizing labor income does not give any incentive for lowering GHG emissions. When using a method based on minimizing GHG emissions, feed-related farm characteristics affected the absolute level of the GHG values, but the relative importance of the traits scarcely changed: at each level of efficiency, milk yield and longevity were equally important.

Methods to determine the relative value of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain.

Current decisions on breeding in dairy farming are mainly based on economic values of heritable traits, as earning an income is a primary objective of farmers. Recent literature, however, shows that breeding also has potential to reduce greenhouse gas (GHG) emissions. The objective of this paper was to compare 2 methods to determine GHG values of genetic traits. Method 1 calculates GHG values using the current strategy (i.e., maximizing labor income), whereas method 2 is based on minimizing GHG per kilogram of milk and shows what can be achieved if the breeding results are fully directed at minimizing GHG emissions. A whole-farm optimization model was used to determine results before and after 1 genetic standard deviation improvement (i.e., unit change) of milk yield and longevity. The objective function of the model differed between method 1 and 2. Method 1 maximizes labor income; method 2 minimizes GHG emissions per kilogram of milk while maintaining labor income and total milk production at least at the level before the change in trait. Results show that the full potential of the traits to reduce GHG emissions given the boundaries that were set for income and milk production (453 and 441kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively) is about twice as high as the reduction based on maximizing labor income (247 and 210kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively). The GHG value of milk yield is higher than that of longevity, especially when the focus is on maximizing labor income. Based on a sensitivity analysis, it was shown that including emissions from land use change and using different methods for handling the interaction between milk and meat production can change results, generally in favor of milk yield. Results can be used by breeding organizations that want to include GHG values in their breeding goal. To verify GHG values, the effect of prices and emissions factors should be considered, as well as the potential effect of variation between farm types.

Cost-effectiveness of feeding strategies to reduce greenhouse gas emissions from dairy farming.

The objective of this paper was to evaluate the cost-effectiveness of 3 feeding strategies to reduce enteric CH4 production in dairy cows by calculating the effect on labor income at the farm level and on greenhouse gas (GHG) emissions at the chain level (i.e., from production of farm inputs to the farm gate). Strategies included were (1) dietary supplementation of an extruded linseed product (56% linseed; 1kg/cow per day in summer and 2kg/cow per day in winter), (2) dietary supplementation of a nitrate source (75% nitrate; 1% of dry matter intake), and (3) reducing the maturity stage of grass and grass silage (grazing at 1,400 instead of 1,700kg of dry matter/ha and harvesting at 3,000 instead of 3,500kg of dry matter/ha). A dairy farm linear programing model was used to define an average Dutch dairy farm on sandy soil without a predefined feeding strategy (reference situation). Subsequently, 1 of the 3 feeding strategies was implemented and the model was optimized again to determine the new economically optimal farm situation. Enteric CH4 production in the reference situation and after implementing the strategies was calculated based on a mechanistic model for enteric CH4 and empirical formulas explaining the effect of fat and nitrate supplementation on enteric CH4 production. Other GHG emissions along the chain were calculated using life cycle assessment. Total GHG emissions in the reference situation added up to 840kg of CO2 equivalents (CO2e) per t of fat- and protein-corrected milk (FPCM) and yearly labor income of €42,605. Supplementation of the extruded linseed product reduced emissions by 9kg of CO2e/t of FPCM and labor income by €16,041; supplementation of the dietary nitrate source reduced emissions by 32kg of CO2e/t of FPCM and labor income by €5,463; reducing the maturity stage of grass and grass silage reduced emissions by 11kg of CO2e/t of FPCM and labor income by €463. Of the 3 strategies, reducing grass maturity was the most cost-effective (€57/t of CO2e compared with €241/t of CO2e for nitrate supplementation and €2,594/t of CO2e for linseed supplementation) and had the greatest potential to be used in practice because the additional costs were low.