A time series analysis of milk productivity in US dairy states.

As US dairy cow production evolves, it is important to characterize trends and seasonal patterns to project amounts and fluctuations in milk and milk components by states or regions. Hence, this study aimed to (1) quantify historical trends and seasonal patterns of milk and milk components production associated with calving date by parities and states; (2) classify parities and states with similar trends and seasonal patterns into clusters; and (3) summarize the general pattern for each cluster for further application in simulation models. Our data set contained 9.18 million lactation records from 5.61 million Holstein cows distributed in 17 states during the period January 2006 to December 2016. Each record included a cow's total milk, fat, and protein yield during a lactation. We used time series decomposition to obtain each state's annual trend and seasonal pattern in milk productivity for each parity. Then, we classified states and parities with agglomerative hierarchical clustering into groups according to 2 methods: (1) dynamic time warping on the original time series and (2) Euclidean distance on extracted features of trend and seasonality from the decomposition. Results showed distinguishable trends and seasonality for all states and lactation numbers for all response variables. The clusters and cluster centroid pattern showed a general upward trend for all yields [energy-corrected milk (ECM), milk, fat, and protein] and a steady trend for fat and protein percent for all states except Texas. We also found a larger seasonality amplitude for all yields (ECM, milk, fat, and protein) from higher lactation numbers and a similar amplitude for fat and protein percent across lactation numbers. The results could be used for advising management decisions according to farm productivity goals. Furthermore, the trend and seasonality patterns could be used to adjust the production level in a specific state, year, and season for farm simulations to accurately project milk and milk components production.

A stochastic animal life cycle simulation model for a whole dairy farm system model: Assessing the value of combined heifer and lactating dairy cow reproductive management programs.

This analysis introduces a stochastic herd simulation model and evaluates the estimated reproductive and economic performance of combinations of reproductive management programs for both heifers and lactating cows. The model simulates the growth, reproductive performance, production, and culling for individual animals and integrates individual animal outcomes to represent herd dynamics daily. The model has an extensible structure, allowing for future modification and expansion, and has been integrated into the Ruminant Farm Systems model, a holistic dairy farm simulation model. The herd simulation model was used to compare outcomes of 10 reproductive management scenarios based on common practices on US farms with combinations of estrous detection (ED) and artificial insemination (AI), synchronized estrous detection (synch-ED) and AI, timed AI (TAI, 5-d CIDR-Synch) programs for heifers; and ED, a combination of ED and TAI (ED-TAI, Presynch-Ovsynch), and TAI (Double-Ovsynch) with or without ED during the reinsemination period for lactating cows. The simulation was run for a 1,000-cow (milking and dry) herd for 7 yr, and we used the outcomes from the final year to evaluate results. The model accounted for incomes from milk, sold calves, and culled heifers and cows, as well as costs from breeding, AI, semen, pregnancy diagnosis, and calf, heifer, and cow feed. We found that the interaction between heifer and lactating dairy cow reproductive management programs influences herd economic performance primarily due to heifer rearing costs and replacement heifer supply. The greatest net return (NR) was achieved when combining heifer TAI and cow TAI without ED during the reinsemination period, whereas the lowest NR was obtained when combining heifer synch-ED with cow ED.

Predicting daily milk yield for primiparous cows using data of within-herd relatives to capture genotype-by-environment interactions.

This study develops and illustrates a hybrid k-medoids, random forest, and support vector regression (K-R-S) approach for predicting the lactation curves of individual primiparous cows within a targeted environment using monthly milk production data from their dams and paternal siblings. The model simulation and evaluation were based on historical test-day (TD) milk production data from 2010 to 2016 for 260 Wisconsin dairy farms. Data from older paternal siblings and dams were used to create family units (n = 6,400) of individual calves, from which their future performance was predicted. Test-day milk yield (MY) records from 2010 to 2014 were used for model training, whereas monthly milk production records of Holstein calves born in 2014 were used for model evaluation. The K-R-S hybrid approach was used to generate MY predictions for 5 randomly selected batches of 320 primiparous cows, which were used to evaluate model performance at the individual cow level by cross-validation. Across all 5 batches, the mean absolute error and the root mean square error of the K-R-S predictions were lower (by 24.2 and 23.4%, respectively) than that of the mean daily MY of paternal siblings. The K-R-S predictions of TD MY were closer to actual values 74.2 ± 2.0% of the time, as compared with means of paternal siblings'. The correlation between actual TD MY and K-R-S predictions was greater (0.34 ± 0.01) than the correlation between the actual yield and the mean of paternal siblings (0.08 ± 0.01). The results of this study demonstrate the effectiveness of the K-R-S hybrid approach for predicting future first-lactation MY of dairy calves in management applications, such as milk production forecasting or decision-support simulation, using only monthly TD yields of within-herd relatives and in the absence of detailed genomic data.

Investigating the effect of temporal, geographic, and management factors on US Holstein lactation curve parameters.

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.

Comparison of reproductive management programs for submission of Holstein heifers for first insemination with conventional or sexed semen based on expression of estrus, pregnancy outcomes, and cost per pregnancy.

Our objective was to evaluate reproductive management programs for submission of Holstein heifers for first insemination with conventional or sexed semen. In experiment 1, nulliparous Holstein heifers (n = 462) were submitted to a 5-d progesterone-releasing intravaginal device (PRID)-Synch protocol [d 0, GnRH + PRID; d 5, PGF2α - PRID; d 6, PGF2α; d 8, GnRH + TAI] and were randomly assigned for PRID removal on d 5 or 6 of the protocol followed by timed artificial insemination (TAI) with conventional semen. Delaying PRID removal decreased early expression of estrus before scheduled TAI (0.9 vs. 12.2%), and pregnancies per AI (P/AI) did not differ between treatments. In experiment 2, nulliparous Holstein heifers (n = 736) from 3 commercial farms were randomized within farm to 1 of 3 treatments for first AI with sexed semen: (1) CIDR5 [d -6, GnRH + controlled internal drug release (CIDR); d -1, PGF2α - CIDR; d 0, PGF2α; d 2, GnRH + TAI]; (2) CIDR6 (d -6, GnRH + CIDR; d -1, PGF2α; d 0, PGF2α - CIDR; d 2, GnRH + TAI); and (3) EDAI (PGF2α on d 0 followed by once-daily estrous detection and AI). Delaying CIDR removal decreased early expression of estrus before scheduled TAI (0.004 vs. 27.8%); however, CIDR5 heifers tended to have more P/AI at 35 (53 vs. 45 vs. 46%) and 64 (52 vs. 45 vs. 45%) days after AI than CIDR6 and EDAI heifers, respectively. Overall, CIDR5 and CIDR6 heifers had fewer days to first AI and pregnancy than EDAI heifers which resulted in less feed costs than EDAI heifers due to fewer days on feed until pregnancy. Despite greater hormonal treatment costs for CIDR5 heifers, costs per pregnancy were $16.66 less for CIDR5 than for EDAI heifers. In conclusion, delaying PRID removal by 24 h within a 5-d PRID-Synch protocol in experiment 1 suppressed early expression of estrus before TAI, and P/AI for heifers inseminated with conventional semen did not differ between treatments. By contrast, although delaying CIDR removal by 24 h within a 5-CIDR-Synch protocol in experiment 2 suppressed early expression of estrus before TAI, delaying CIDR removal by 24 h tended to decrease P/AI for heifers inseminated with sexed semen. Further, submission of heifers to a 5-d CIDR-Synch protocol for first AI tended to increase P/AI and decrease the cost per pregnancy compared with EDAI heifers.

Measuring farmers' dynamic technical and udder health management inefficiencies: The case of Wisconsin dairy farms.

This study measures the dynamic technical and udder health management inefficiencies of a sample of Wisconsin dairy farms. Udder health management inefficiency is defined as a farmer's failure to achieve lower levels of milk somatic cell counts compared with those of the best-practice farmers within the sample. The study proposes the treatment of somatic cell count as an undesirable output. We measured inefficiency using a dynamic directional distance function that accounts simultaneously for the expansion of desirable outputs and investments in capital assets, and contraction of undesirable output and variable inputs. In a second step, a bootstrap truncated regression was used to analyze factors that cause differences in dynamic technical and udder health management inefficiencies. Results showed that the sample farmers had considerably higher udder health management inefficiency scores than technical inefficiency scores. The results of the second-stage analysis indicated that technical inefficiency was influenced by summer precipitation and farmers' financial characteristics, and was regionally heterogeneous. Udder health management inefficiency was affected by summer temperature and nonfarm income. By ranking farms in this study in terms of technical and udder health management inefficiency, we allowed inefficient farms to compare their performance with that of their efficient peers, and thus identify targets for production and udder health management improvement efforts. Finally, although our study focused on farmers' performances with respect to udder health management, the proposed modeling framework can be applied to the management of other animal diseases and welfare conditions.

Development of a linear programming model for the optimal allocation of nutritional resources in a dairy herd.

A linear programming model that selects the optimal cropping plan and feeds allocation for diets to minimize the whole dairy farm feed costs was developed. The model was virtually applied on 29 high-yielding Holstein-Friesian herds, confined, total mixed ration dairy farms. The average herd size was 313.2 ± 144.1 lactating cows and the average land size was 152.2 ± 92.5 ha. Farm characteristics such as herd structure, nutritional grouping strategies, feed consumption, cropping plan, intrinsic farm limitations (e.g., silage and hay storage availability, water for irrigation, manure storage) and on farm produced forage costs of production were collected from each farm for the year 2017. Actual feeding strategies, land availability, herd structure, crop production costs and yields, and milk and feed market prices for the year 2017 were used as model inputs. Through optimization, the feeding system was kept equal to the actual farm practice. The linear program formulated diets for each animal group to respect actual herd dry matter intake and fulfill actual consumption of crude protein, rumen-degradable and rumen-undegradable fractions of crude protein, net energy for lactation, neutral detergent fiber, acid detergent fiber, forage neutral detergent fiber, and nonfiber carbohydrate. Production levels and herd composition were considered to remain constant as the nutritional requirement would remain unchanged. The objective function was set to minimize the whole-farm feed costs including cash crop sales as income, and crop production costs and purchased feed costs as expenses. Optimization improved income over feed costs by reducing herd feed costs by 7.8 ± 6.4%, from baseline to optimized scenario, the improved was explained by lower feed costs per kilogram of milk produced due to a higher feed self-sufficiency and higher income from cash crop. In particular, the model suggested to maximize, starting from baseline to optimized scenario, the net energy for lactation (+8.5 ± 6.3%) and crude protein (+3.6 ± 3.1%) produced on farm, whereas total feed cost (€/100 kg of milk) was greater in the baseline (20.4 ± 2.3) than the optimized scenario (19.0 ± 1.9), resulting in a 6.7% feed cost reduction with a range between 0.49% and 21.6%. This meant €109 ± 96.9 greater net return per cow per year. The implementation of the proposed linear programming model for the optimal allocation of the nutritional resources and crops in a dairy herd has the potential to reduce feed cost of diets and improve the farm feed self-sufficiency.

Short communication: Economic impact among 7 reproductive programs for lactating dairy cows, including a sensitivity analysis of the cost of hormonal treatments.

Although hormonal synchronization programs can improve reproductive efficiency of dairy herds, some farmers question the economics of these programs based on the upfront cost of hormonal treatments as opposed to the economic value of the resulting reproductive performance. Our aim was to compare the economic impact of reproductive management programs that incorporate varying degrees of detection of estrus and timed artificial insemination (AI) in dairy herds with year-round calving in confinement total mixed ration systems. A reproductive economic analysis simulation model was used to compare the economic impact of pairs of reproductive management programs. We simulated sets of scenarios for 2 analyses. In the first analysis, we calculated the economic impact of switching from a Presynch-Ovsynch program to a Double-Ovsynch program that included a second PGF2α treatment during the Breeding-Ovsynch portion of the program (Double-Ovsynch+PGF). In the second analysis, we conducted a break-even analysis in which the cost of hormonal treatments was incrementally increased within various reproductive management programs. Our analyses revealed that a Double-Ovsynch+PGF program, the most intensive program evaluated, was more profitable than other programs compared, including a Presynch-Ovsynch program with 100% timed AI or a Presynch-Ovsynch program that incorporated detection of estrus, despite the higher upfront cost incurred by using more hormonal treatments. This advantage remained until the cost of hormones was increased 5 to 14 times current US market prices and 2 to 6 times current European market prices. The cost of GnRH had a greater impact on net profit gain than the cost of PGF2α. In conclusion, more intensive reproductive programs that use more hormonal treatments but result in substantially increased reproductive performance are more profitable than less intensive programs and remain so even if hormone prices are unusually high.

An income over feed cost nutritional grouping strategy.

This study introduces a new nutritional grouping method, OptiGroup, which maximizes milk income over feed cost (IOFC) using a mixed-integer nonlinear programming optimization algorithm. Analyses compared the OptiGroup with the cluster method, the current state-of-the-art nutritional grouping technique. Analyses were performed using cow-level data from 7 Wisconsin dairy farms. Consistently, the OptiGroup and the cluster were constrained to group cows simultaneously into 2 (low and high nutrient requirements) and 3 (low, medium, and high nutrient requirements) same-size groups. Each diet satisfied the net energy (NEL) and crude protein (CP) requirements of approximately 83% of the cows in each group by using lead factors based on nutrient density. A control treatment (1-group scenario) was used as a baseline for comparisons. The IOFC, dietary nutrient densities (NEL and CP), and dry matter intake with both methods were computed and compared. The percentage of cows grouped differently and the percentages of primiparous cows and late-lactation (>200 d in milk) cows in each group were also analyzed. Results were as follows: (1) average extra IOFC of $8/cow per yr (2-group) and $12/cow per yr (3-group) by switching from cluster to OptiGroup method; (2) difference between dietary nutrient densities of the groups were reduced under OptiGroup method compared with cluster (i.e., NEL differences in 2 groups were 0.20 Mcal/kg for the cluster vs. 0.11 Mcal/kg for OptiGroup); (3) dry matter intake decreased with increasing group numbers within a grouping method, and decreased from cluster to OptiGroup method with constant group numbers; (4) percentage of primiparous cows was greater in the low group of cluster and in the high group of OptiGroup; and (5) proportion of late-lactation cows tended to be greater in the low group in both grouping strategies. Results indicated that the OptiGroup performed economically better than the cluster because of nutrient savings, even with high feed cost conditions. This study offers a new nutritional grouping paradigm, which could improve herd management on dairy farms. However, animal trials are needed to validate this new nutritional grouping method under farm conditions.

The relationship between the number of consecutive days with heat stress and milk production of Holstein dairy cows raised in a humid continental climate.

Heat stress is known to affect performance of dairy cows experiencing prolonged periods of high temperature and relative humidity. Less is known about its effects in cooler climates. The goals of the present study were to determine the prevalence of days susceptible to cause mild heat stress in dairy cows living in a humid continental climate and to investigate the relationship between the number of consecutive days of mild heat stress and milk, fat, protein, and lactose production. A 6-yr data set (2010-2015) containing 606,031 milk analysis records for 34,360 Holstein dairy cows at different parities was matched with the corresponding daily maximum temperature-humidity index. Exposure to heat stress conditions was divided into 5 categories corresponding to 0, 1 to 2, 3 to 4, 5 to 6, and 7 to 8 consecutive days before milk test date. On average, cows were exposed to heat stress conditions for 135.8 ± 5.9 d/yr in Southwest Quebec and 95.3 ± 10.2 d/yr in Eastern Quebec. Cows experiencing heat stress conditions produced on average less fat, protein, and energy-corrected milk and lower fat and protein concentrations. The decrease in milk fat reached 6% for category 7 to 8 exposure of cows in parity 3 or more. The association between exposure category and milk yield and lactose yield and concentration was weak. Heat stress lowered milk fat and protein production but had little effect on milk volume output. Further research is necessary to better understand the mechanism underlying the effects of sporadic low- to medium-intensity heat stress on dairy productivity.

An economic evaluation of management strategies to mitigate the negative effect of twinning in dairy herds.

Our objectives were to develop an economic model to estimate the economic impact of twinning in dairy cows and to evaluate management strategies to mitigate the negative economic impact of twinning in dairy herds. A probabilistic tree considering spontaneous embryo reduction, early pregnancy loss, abortion, metritis, retained placenta, and culling rate at 120 d of the second, at the end of the second, and at the end of the third lactation was developed for a single pregnancy; we also developed 3 management options upon diagnosis of a twin pregnancy: (1) do nothing, (2) induce abortion using PGF2α, or (3) attempt manual embryo reduction. A value was given to each branch of the tree by simulating cow states on a farm for 1,400 d to encompass 4 consecutive lactations. The incomes considered in the simulations included milk income over feed cost, income from calves, and slaughter value upon culling. The expenses taken into account depending on each branch included additional inseminations and synchronization protocols, embryo reduction, induction of abortion, replacement heifers, and costs due to metritis and retained placenta. The gross value for a singleton pregnancy and the 3 management options upon diagnosis of a twin pregnancy were calculated by adding the value of all braches multiplied by their probability. The costs for the 3 management options were calculated by subtracting its gross value minus the gross value of a singleton pregnancy. The negative economic impact of a twin pregnancy ranged from $97 to $225 depending on the type of twin pregnancy (unilateral vs. bilateral), parity, and DIM when the twin pregnancy occurred. The overall negative economic impact of twinning on dairy farm profitability in the United States was estimated to be $96 million per year. Attempting manual embryo reduction early during gestation upon diagnosis of a twin pregnancy was the optimal management strategy for mitigating the negative economic impact of twinning under a wide variety of scenarios.

Effect of feeding strategies and cropping systems on greenhouse gas emission from Wisconsin certified organic dairy farms.

Organic agriculture continues to expand in the United States, both in total hectares and market share. However, management practices used by dairy organic producers, and their resulting environmental impacts, vary across farms. This study used a partial life cycle assessment approach to estimate the effect of different feeding strategies and associated crop production on greenhouse gas emissions (GHG) from Wisconsin certified organic dairy farms. Field and livestock-driven emissions were calculated using 2 data sets. One was a 20-yr data set from the Wisconsin Integrated Cropping System Trial documenting management inputs, crop and pasture yields, and soil characteristics, used to estimate field-level emissions from land associated with feed production (row crop and pasture), including N2O and soil carbon sequestration. The other was a data set summarizing organic farm management in Wisconsin, which was used to estimate replacement heifer emission (CO2 equivalents), enteric methane (CH4), and manure management (N2O and CH4). Three combinations of corn grain (CG) and soybean (SB) as concentrate (all corn = 100% CG; baseline = 75% CG + 25% SB; half corn = 50% CG + 50% SB) were assigned to each of 4 representative management strategies as determined by survey data. Overall, GHG emissions associated with crop production was 1,297 ± 136 kg of CO2 equivalents/t of ECM without accounting for soil carbon changes (ΔSC), and GHG emission with ΔSC was 1,457 ± 111 kg of CO2 equivalents/t of ECM, with greater reliance on pasture resulting in less ΔSC. Higher levels of milk production were a major driver associated with reduction in GHG emission per metric tonne of ECM. Emissions per metric tonne of ECM increased with increasing proportion of SB in the ration; however, including SB in the crop rotation decreased N2O emission per metric tonne of ECM from cropland due to lower applications of organically approved N fertility inputs. More SB at the expense of CG in the ration reduced enteric CH4 emission per metric tonne of ECM (because of greater dietary fat content) but increased N2O emission per metric tonne of ECM from manure (because of greater N content). An increased reliance on pasture for feed at the expense of grain resulted in decreased in milk production, subsequently leading to substantially higher emissions per metric tonne of ECM.

Economics of production efficiency: Nutritional grouping of the lactating cow.

Nutritional grouping of lactating cows under total mixed ration (TMR) feeding systems has been discussed in the literature since 1970. Most studies have concluded that using multiple, more-homogeneous TMR feeding groups is economically beneficial because of either nutrient cost savings, improved productivity, or both. Nonetheless, no consensus has been formed around this technique nor has it been widely adopted. By using optimal criteria for grouping and more precise nutrient specifications of diets, the latest studies have reported a consistently greater income over feed cost ($/cow per year) with multiple TMR groups compared with 1 TMR (3 TMR=$46 and 2 TMR=$21 to $39). Critical factors that determine the economic value of nutritional grouping are: (1) criteria for grouping, (2) nutrient specifications of diets, (3) effects on milk production, (4) health and environmental benefits, (5) number, size, and frequency of grouping, and (6) additional costs and benefits. It has been documented that grouping cows according to their simultaneous nutritional requirements (a.k.a., cluster grouping) is optimal. Cluster grouping is superior to other methods, such as grouping according to days in milk, milk production, or production and body weight combined. However, the dairy industry still uses less-than-optimal grouping criteria. Using cluster grouping will enhance the positive economic effects of multiple TMR. In addition, nutrient specifications of diets for groups do not seem optimal either. Milk lead factors, which are only based on group average milk production, are used. Diets could, however, be formulated more precisely based on overall group nutrient requirements. Providing more precise diets should also be in favor of grouping economics. Furthermore, an area that requires more attention is the potential negative effect of grouping on the milk production of moved cows because of either or both social interactions or diet concentration changes. Although the literature is inconclusive on this subject matter, the latest studies indicate that multiple TMR groups economically outperform 1 TMR, even after considering plausible potential milk losses when grouping. Moreover, additional positive effects of nutritional grouping of improved herd health and environmental stewardship should be translated into economic benefits. Finally, additional costs of management, labor, facilities, and equipment required for grouping are farm specific. The few studies that have integrated these factors in their analyses found that multiple TMR groups would still be economically superior to 1 TMR.

Economic impact of nutritional grouping in dairy herds.

This article evaluates the estimated economic impact of nutritional grouping in commercial dairy herds using a stochastic Monte Carlo simulation model. The model was initialized by separate data sets obtained from 5 commercial dairy herds. These herds were selected to explore the effect of herd size, structure, and characteristics on the economics and efficiency of nutrient usage according to nutritional grouping strategies. Simulated status of each cow was updated daily together with the nutrient requirements of net energy for lactation (NEL) and metabolizable protein (MP). The amount of energy consumed directly affected body weight (BW) and body condition score (BCS) changes. Moreover, to control the range of observed BCS in the model, constraints on lower (2.0) and upper (4.5) bounds of BCS were set. Each month, the clustering method was used to homogeneously regroup the cows according to their nutrient concentration requirements. The average NEL concentration of the group and a level of MP (average MP, average MP+0.5SD, or average MP+1SD) were considered to formulate the group diet. The calculated income over feed costs gain (IOFC, $/cow per yr) of having >1 nutritional group among the herds ranged from $33 to $58, with an average of $39 for 2 groups and $46 for 3 groups, when group was fed at average NEL concentration and average MP+1SD concentration. The improved IOFC was explained by increased milk sales and lower feed costs. Higher milk sales were a result of fewer cows having a milk loss associated with low BCS in multi-group scenarios. Lower feed costs in multi-group scenarios were mainly due to less rumen-undegradable protein consumption. The percentage of total NEL consumed captured in milk for >1 nutritional group was slightly lower than that for 1 nutritional group due to better distribution of energy throughout the lactation and higher energy retained in body tissue, which resulted in better herd BCS distribution. The percentage of fed N captured in milk increased with >1 group and was the most important factor for improved economic efficiency of grouping strategies.

Optimizing productivity, herd structure, environmental performance, and profitability of dairy cattle herds.

This study used the Integrated Farm System Model to simulate the whole farm performance of a representative Wisconsin dairy farm and predict its economic and environmental outputs based on 25 yr of daily local weather data (1986 to 2010). The studied farm, located in southern Wisconsin, had 100 milking cows and 100 ha of cropland with no replacement heifers kept on the farm. Sensitivity analyses were conducted to test the effect of management strategies on energy-corrected milk production (ECM; 4.0% fat and 3.5% protein), net return to management, and greenhouse gas (GHG; including biogenic CO2) emission. The management strategies included (1) target milk production, for which the model optimized available resources to attain, and (2) herd structure, represented by the percentage of first-lactation cows. Weather conditions affected the outputs by changing the farm quantity and the quality of produced feed resources. As expected, when target milk production increased, the ECM increased positively and linearly to a certain level, and then it increased nonlinearly at a decreasing rate, constrained by available feed nutrients. Thereafter, the ECM reached the maximum potential milk production and remained flat regardless of higher target milk production input. Greenhouse gas emissions decreased between 3.4 and 7.3% at different first-lactation cow percentages. As the first-lactation cow percent increased from 15 to 45% in 5% intervals, GHG increased between 9.4 and 11.3% at different levels of target milk production. A high percentage of first-lactation cows reduced the maximum potential milk production. Net return to management had a similar changing trend as ECM. As the target milk production increased from 9,979 to 11,793 kg, the net return to management increased between 31 and 46% at different first-lactation cow percentages. Results revealed a win-win situation when increasing milk production or improving herd structure, which concurrently increased farm net return to management and decreased GHG emissions.

Consequences and economics of metritis in Iranian Holstein dairy farms.

The objectives of this study were (1) to describe the risk factors, incidence, and productive and reproductive consequences of metritis in dairy cows, and (2) to estimate the financial losses associated with metritis using data gathered from 4 Holstein dairy farms in Isfahan, Iran. Calving records from March 2008 to December 2013, comprising 43,488 calvings, were included in the data set. The effects of metritis on productive and reproductive performance were analyzed using a mixed linear model for primiparous and multiparous cows separately and in an overall data set (all cows combined), whereas risk factors on metritis incidence were examined using a multivariable logistical regression model for the overall data set. The incidence of metritis per cow per year was 13.2% on average and ranged from 9.0 to 15.8%. Results of logistic regression analysis demonstrated that calving year, parity number, calving season, twinning, dystocia, and retained placenta were significantly associated with the occurrence of metritis, whereas previous metritis incidence did not show an association. Greatest odds of metritis occurred in first-parity cows that calved in winter and had retained placenta, twinning, and dystocia in recent years. A case of metritis significantly reduced the 305-d milk yield in primiparous and multiparous cows and overall, but had no significant effects on 305-d fat and protein percentages in either primiparous or multiparous cows. Overall, a case of metritis reduced 305-d milk yield by 129.8±41.5kg/cow per lactation. The negative reproductive effects due to metritis were smaller and nonsignificant for primiparous cows compared with multiparous cows. Overall, a case of metritis increased days open and number of insemination per conception by 16.4±1.2 and 0.1±0.0 per cow per lactation, respectively. Among the individual farms, metritis costs ranged from $146.4 to $175.7 with a mean of $162.3/case. The model to calculate metritis costs proposed here could be used to estimate economic losses for metritis in other developing countries, where farm productive and economic data are generally scarce.

From cold to hot: Climatic effects and productivity in Wisconsin dairy farms.

This study examined the effects of climatic conditions on dairy farm productivity using panel data for the state of Wisconsin along with alternative stochastic frontier models. A noteworthy feature of this analysis is that Wisconsin is a major dairy-producing area where winters are typically very cold and snowy and summers are hot and humid. Thus, it is an ideal geographical region for examining the effects of a range of climatic factors on dairy production. We identified the effects of temperature and precipitation, both jointly and separately, on milk output. The analysis showed that increasing temperature in summer or in autumn is harmful for dairy production, whereas warmer winters and warmer springs are beneficial. In contrast, more precipitation had a consistent adverse effect on dairy productivity. Overall, the analysis showed that over the past 17 yr, changes in climatic conditions have had a negative effect on Wisconsin dairy farms. Alternative scenarios predict that climate change would lead to a 5 to 11% reduction in dairy production per year between 2020 and 2039 after controlling for other factors.

Constraints for nutritional grouping in Wisconsin and Michigan dairy farms.

A survey was conducted in Wisconsin (WI) and Michigan (MI) to quantify the proportion of farms that use a single diet for all lactating cows and to better understand the reasons for current grouping strategies and the limitations to grouping for better nutritional management. A questionnaire was mailed to all WI dairy farmers with ≥200 lactating cows (971 farms) and to a random sample of grade-A MI dairy farmers (800 farms) of varying herd sizes. The survey return rate was 20% in WI (196 farms) and 26% in MI (211 farms; 59 of them had ≥200 lactating cows). Feeding 2 or more different diets to lactating cows was predominant: 63% in WI (124 farms, all ≥200 lactating cows), 76% in MI farms with ≥200 lactating cows (45 farms), and 28% in MI farms with <200 lactating cows (43 farms). Farmers feeding more than 1 diet used 1 or more of the following criteria for grouping lactating cows: stage of lactation, milk production, or body condition score. Overall for both states, 52% of the farms (211 from 407 farms) feeding more than 1 diet grouped cows according to their nutritional needs. However, a notable population of farms fed the same diet to all lactating cows: 37% in WI (72 farms), 24% in MI (14 farms) for herds of ≥200 lactating cows, and 72% in MI for herds of <200 lactating cows (109 MI farms). "Desire to keep it simple" and "milk drops when cows are moved to a different group" were identified as main constraints to having more groups within a farm for nutritional purposes. Farm facilities and labor were also limiting factors to grouping in farms with herd sizes of <200 lactating cows.

Green cheese: partial life cycle assessment of greenhouse gas emissions and energy intensity of integrated dairy production and bioenergy systems.

The objective of this study was to evaluate the effect of integrating dairy and bioenergy systems on land use, net energy intensity (NEI), and greenhouse gas (GHG) emissions. A reference dairy farm system representative of Wisconsin was compared with a system that produces dairy and bioenergy products. This integrated system investigates the effects at the farm level when the cow diet and manure management practices are varied. The diets evaluated were supplemented with varying amounts of dry distillers grains with solubles and soybean meal and were balanced with different types of forages. The manure-management scenarios included manure land application, which is the most common manure disposal method in Wisconsin, and manure anaerobic digestion (AD) to produce biogas. A partial life cycle assessment from cradle to farm gate was conducted, where the system boundaries were expanded to include the production of biofuels in the analysis and the environmental burdens between milk and bioenergy products were partitioned by system expansion. Milk was considered the primary product and the functional unit, with ethanol, biodiesel, and biogas considered co-products. The production of the co-products was scaled according to milk production to meet the dietary requirements of each selected dairy ration. Results indicated that land use was 1.6 m2, NEI was 3.86 MJ, and GHG emissions were 1.02 kg of CO2-equivalents per kilogram of fat- and protein-corrected milk (FPCM) for the reference system. Within the integrated dairy and bioenergy system, diet scenarios that maximize dry distillers grains with solubles and implement AD had the largest reduction of GHG emissions and NEI, but the greatest increase in land use compared with the reference system. Average land use ranged from 1.68 to 2.01 m2/kg of FPCM; NEI ranged from -5.62 to -0.73 MJ/kg of FPCM; and GHG emissions ranged from 0.63 to 0.77 kg of CO2-equivalents/kg of FPCM. The AD contributed 65% of the NEI and 77% of the GHG emission reductions.