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The dataset available here comes from an experimental dairy cattle farm located in a mountain region in Central France, where the feeding systems are mostly pasture grazing combined with a period of indoor overwintering during the colder months. The dataset comprises individual productive and functional traits covering over 36 different variables in 185 primiparous Montbéliarde and Holstein cows, followed by data on productive longevity and reason for culling. The data was collected over a 20-year period during which animal husbandry and data collection protocols remained consistent. Potential re-users of the data are private-sector professionals, farmer associations, and researchers interested in developing statistical and mechanistic models and simulations of individual dairy cows under low-input grassland-based systems.

Although studied extensively in conventional production systems, limited research exists on the longevity of organically raised dairy cows. The objective was to discuss the factors affecting dairy cattle longevity, and to conduct an economic assessment for prolonged longevity of organic dairy cattle. A dynamic programming tool was adopted for a typical organic and conventional dairy farm in Texas, using the model developed by Groenendaal et al. (2004) to determine optimal replacement decisions for organic dairy cattle based on the retention payoff (RPO) value. The model included milk price, calf value, replacement heifer costs, veterinary expenses, financial losses at disposal, insemination, feed, carcass weight, and the discount rate, with representative values for the year 2024. Herd level inputs: average herd milk production per year per cow, birth weight, adult dairy cow weight, length of voluntary waiting period, estrus detection rate, conception rate, and age at first calving were extracted from an on-farm herd management software program. The result illustrated that economic benefits and RPO values for pregnant and open cows vary by lactation stage and number. Pregnant cows have higher RPO values than open cows in both systems. On organic farms, pregnant cows' RPO values range from -$110 to $3,373, while open cows' range from -$109 to $1,681 based on the production level and lactation. The RPO for all the lactations, pregnancy, and production level combinations were higher for organic systems. The average difference in RPOs between 2 systems ranged from $1,000 to $200 for lactations 1 and 12 respectively, with organic farms exhibiting higher RPOs in 805 out of 900 scenarios, favoring longer productive life in organic dairy farms. In conclusion, optimizing productive lifespan of dairy cows through dynamic culling decisions can lead to increased profitability for organic herds, which, in our analysis, was higher than that of conventional herds., (© 2025, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Context: Length of productive life is defined as the number of days from first calving to the last day of milking records, when the cow is no longer sufficiently productive. Although it has economic implications, length of productive life has not yet been included in Brazilian dairy cattle breeding programs because it depends on other traits such as age at first calving, milk production level and disease occurrence. In addition, its evaluation occurs later in life, and heritability coefficients are low. Aims: The aim of this study was to identify the effects of both age at first calving and accumulated 305-day milk yield in the first lactation on length of productive life in Holstein cows. Methods: Official dairy control data of 31 562 Holstein cows, calved from 2010 to 2014, in 321 herds from Paraná state, Brazil, were analysed by using the Kaplan–Meier estimator and Cox regression model. Key results: First calving at <21 months was associated with shortest productive life (1197.01 ± 232.40 days), whereas first calving at 24 months was associated with the lowest hazard ratio (0.572), suggesting that this is the most suitable age of first calving for a longer productive life. Low-yielding cows (first lactation yield <6392 kg) had the second lowest survival probability (47.20%), the shortest productive life (1150.60 ± 234.51 days) and the highest voluntary hazard ratio (1.30) and were prematurely culled from the herds. High-yielding cows (first lactation yield >12 024 kg) had lower culling risk at the first lactation. Conclusions: Cows that started their reproductive life ∼16 months of age (first calving at 24 months) had the longest productive life and an average first lactation milk yield ∼9000 kg. Implications: Reproductive management practices could affect length of productive life through effects on age at first calving and first lactation milk yield. Most of the Holstein semen used in Brazil comes from countries where longevity has already been included in selection indexes; thus, early identification of cow longevity could be used for culling decisions. Having long-lived, more profitable and more functional cows in the herd is one of the biggest challenges in dairy farming in Brazil. We assessed the effects of age at first calving and accumulated 305-day milk yield in the first lactation on length of productive life in Holstein cows. Cows that started reproductive life at ∼16 months of age had the longest productive life and an average first lactation milk yield ∼9000 kg. [ABSTRACT FROM AUTHOR]

The ability of dairy farmers to keep their cows for longer could positively enhance the economic performance of the farms, reduce the environmental footprint of the milk industry, and overall help in justifying a sustainable use of animals for food production. However, there is little published on the current status of cow longevity and we hypothesized that a reason may be a lack of standardization and an over narrow focus of the longevity measure itself. The objectives of this critical literature review were: (1) to review metrics used to measure dairy cow longevity; (2) to describe the status of longevity in high milk-producing countries. Current metrics are limited to either the length of time the animal remains in the herd or if it is alive at a given time. To overcome such a limitation, dairy cow longevity should be defined as an animal having an early age at first calving and a long productive life spent in profitable milk production. Combining age at first calving, length of productive life, and margin over all costs would provide a more comprehensive evaluation of longevity by covering both early life conditions and the length of time the animal remains in the herd once it starts to contribute to the farm revenues, as well as the overall animal health and quality of life. This review confirms that dairy cow longevity has decreased in most high milk-producing countries over time and its relationship with milk yield is not straight forward. Increasing cow longevity by reducing involuntary culling would cut health costs, increase cow lifetime profitability, improve animal welfare, and could contribute towards a more sustainable dairy industry while optimizing dairy farmers’ efficiency in the overall use of resources available.

Reproductive success is a key component of lifetime efficiency – which is the ratio of energy in milk (MJ) to energy intake (MJ) over the lifespan, of cows. At the animal level, breeding and feeding management can substantially impact milk yield, body condition and energy balance of cows, which are known as major contributors to reproductive failure in dairy cattle. This study extended an existing lifetime performance model to incorporate the impacts that performance changes due to changing breeding and feeding strategies have on the probability of reproducing and thereby on the productive lifespan, and thus allow the prediction of a cow’s lifetime efficiency. The model is dynamic and stochastic, with an individual cow being the unit modelled and one day being the unit of time. To evaluate the model, data from a French study including Holstein and Normande cows fed high-concentrate diets and data from a Scottish study including Holstein cows selected for high and average genetic merit for fat plus protein that were fed high- v. low-concentrate diets were used. Generally, the model consistently simulated productive and reproductive performance of various genotypes of cows across feeding systems. In the French data, the model adequately simulated the reproductive performance of Holsteins but significantly under-predicted that of Normande cows. In the Scottish data, conception to first service was comparably simulated, whereas interval traits were slightly under-predicted. Selection for greater milk production impaired the reproductive performance and lifespan but not lifetime efficiency. The definition of lifetime efficiency used in this model did not include associated costs or herd-level effects. Further works should include such economic indicators to allow more accurate simulation of lifetime profitability in different production scenarios.

Reproductive success is a key component of lifetime efficiency – which is the ratio of energy in milk (MJ) to energy intake (MJ) over the lifespan, of cows. At the animal level, breeding and feeding management can substantially impact milk yield, body condition and energy balance of cows, which are known as major contributors to reproductive failure in dairy cattle. This study extended an existing lifetime performance model to incorporate the impacts that performance changes due to changing breeding and feeding strategies have on the probability of reproducing and thereby on the productive lifespan, and thus allow the prediction of a cow’s lifetime efficiency. The model is dynamic and stochastic, with an individual cow being the unit modelled and one day being the unit of time. To evaluate the model, data from a French study including Holstein and Normande cows fed high-concentrate diets and data from a Scottish study including Holstein cows selected for high and average genetic merit for fat plus protein that were fed high- v. low-concentrate diets were used. Generally, the model consistently simulated productive and reproductive performance of various genotypes of cows across feeding systems. In the French data, the model adequately simulated the reproductive performance of Holsteins but significantly under-predicted that of Normande cows. In the Scottish data, conception to first service was comparably simulated, whereas interval traits were slightly under-predicted. Selection for greater milk production impaired the reproductive performance and lifespan but not lifetime efficiency. The definition of lifetime efficiency used in this model did not include associated costs or herd-level effects. Further works should include such economic indicators to allow more accurate simulation of lifetime profitability in different production scenarios. [ABSTRACT FROM PUBLISHER]

A model with a simple algorithm is presented to analyze the efficiency of milk production, taking into consideration the viability and productivity of cows, dairy herd turnover rate, and main economic indicators. Principle propositions of a general approach are set forth without any complicated mathematical formulas and equations. The impact of viability on herd profitability and reproductive performance has been analyzed with the actual data on culled Holstein Black-and-White and Holmogorskaya cows. Reducing the culling rate in first lactations should be recognized as a major breeding criterion for extending the average productive lifespan of cows. [ABSTRACT FROM AUTHOR]

• The standard method for the allocation of emissions to meat and milk is limited. • It may lead to wrong conclusions when assessing mitigation measures. • A new approach is developed based on energy requirements for milk and meat. • Its validity is demonstrated by applying it on a variety of dairy farms worldwide. • Increasing cow longevity reduced emissions only when applying the new approach. The dairy sector is urged to reduce environmental impacts, such as greenhouse gas (GHG) emissions. But dairy farms not only produce milk: surplus calves and culled cows also yield meat as co-product. To split environmental impacts between milk and meat, a biophysical allocation method proposed by the International Dairy Federation (IDF) is currently used. Its applicability to farms with large meat-to-milk output ratios (beef-to-milk ratio, BMR) may be limited and lead to wrong conclusions when assessing GHG emissions and mitigation measures at farm level. To overcome these limitations, we developed a biophysical allocation approach based on the net energy requirement for milk and meat production according to internationally agreed energy requirements for dairy cows. Both the enhanced and the existing allocation methods were tested on an international dataset that included farms with a large range of BMR, as can be found in dual-purpose production systems or on farms with low milk productivity. The results from the international dataset reveal that the allocation factor does not substantially change for production systems with low BMR. For BMR up to 0.03 kg live weight (LW)/kg of fat- and protein-corrected milk (FPCM), the maximum deviation in the allocation factor between the two methods was 0.047. For larger BMR, the developed method still allocated relevant shares of emissions to meat while the standard approach did not. The developed method is less sensitive to shifts in BMR, especially for low-performing dairy farms. In addition, both methods were tested on a dataset of 46 Swiss dairy farms. By increasing the longevity of cows (one additional lactation), the impacts of altered BMR on the modelled GHG emissions and their allocation on milk and meat could be assessed. Increased longevity resulted in fewer cows to be replaced, decreased emissions from the rearing of replacement stock (-444 kg CO 2 -equivalents/cow/year) and lower meat output (-61 kg LW/cow/year), as fewer cows were culled. Consequently, a larger share of emissions was allocated to milk. While the standard biophysical allocation approach did not result in reduced GHG emissions per kg of milk (+0.002 kg CO 2 -equivalents/kg FPCM), the newly developed approach generated a modest (-0.022 kg CO 2 -equivalents/kg FPCM), although not significant reduction. The effects of GHG mitigation measures that affect BMR are thus represented more accurately than when applying the standard approach. Based on the presented data, we encourage the revision of currently used international standards for allocating environmental impacts to milk and meat. [ABSTRACT FROM AUTHOR]

• The ability of a doe to stay in a herd (stayability) is determined by its productivity. • Production traits and stayability are favorably correlated. • Higher milk production reduces culling risk, affecting stayability. • The use of stayability for selecting animals results in herds that are more productive. • Selecting for STAY28 is efficient in keeping dairy goats in the herd, even with slower favorable changes. Our objectives were (1) to evaluate how production traits (lactation length, milk production, and protein, lactose, fat and total dry extract yields) affect the permanence of Saanen goats in the herd for longer than 28 months; (2) to estimate genetic parameters for stayability (STAY28) using an Weibull proportional risk model; and (3) to evaluate the genetic associations between both stayability and production through genetic correlations and regression analysis. Two methodologies were utilized in the evaluation: (1) survival analysis using the Weibull animal model; and (2) threshold-linear model through Bayesian approach using Gibbs sampler in two-trait analysis. The data set had 3344 information. Animal effect was included as random in both methodologies. In analyses with Weibull distribution, the contemporary group effect was considered random and in the threshold-linear model was systematic. In the Weibull risk model, production traits were divided in five classes (class 0, class 1, class 2, class 3, and class 4) and the effect of parturition age was significant (P < 0.05) for all production variables. For milk production, the highest class (class 4) presented significant effect on STAY28, with reduced culling risk of does from this class in comparison with the other ones. Heritability values for STAY28 were low in both methodologies (between 0.05 and 0.09 across classes for the Weibull model and 0.07 for the threshold-linear model). Genetic correlation estimates between STAY28 and production traits were null in the threshold-linear model. Regression of breeding values of production traits as a function of STAY28 demonstrated a significant relationship between these traits. Even with slower favorable changes, the use of STAY28 for selecting animals with higher breeding values is a viable option to increase the productive lifespan of dairy goats, resulting in animals that are more productive. Therefore, the improvement of productive traits of does brings positive effects in the stay in the herd for longer than 28 months. [ABSTRACT FROM AUTHOR]

• A methodology to calculate a new bio-economic measure for dairy farming that merges accounting and routine herd data at animal level is introduced. • The proportion of dairy cows gaining profit (or loss) and the farm-specific effect matrix of individual income over service life cost (iIOLC) were evaluated for 32 German dairy farms monitored for the period of one year. • IOLC of culled cows as well as the reasons for individual economic success or failure vary greatly between dairy cows and across dairy farms. • At death, more than half of the cows did not return the previous investments that were spent to raise them together with the costs to keep them alive and in production. • Increasing longevity would be economically reasonable for a broad range of German dairy farms. Managing a dairy farm requires a farm- and cow-specific assessment of the required resources and the revenues obtained from the production process. Due to scientific and practical reasons, the various types of data from a farm, e.g., economic and biologic data, commonly lack connectivity and compatibility at animal level. This means that the economic impacts associated with differences in rearing, productivity and culling as well as the economic values of cow-individual service lives often remain hidden under average figures. This work is based on a two-fold hypothesis: (1) large differences in cow profitability exist between farms but also between individual cows within one farm, and (2) knowledge about the farm-specific economic impact of service life characteristics provides new options for action. In this article, a farm-specific full-cost calculation that links routine herd management data and key economic figures gained from business sheets of the farm's dairy branch is introduced. The new methodology for the calculation of individual income over service life cost was exemplarily tested on a sample of 4,962 culled cows from 32 German dairy farms. Median income over service life cost of culled cows was negative for 19 farms (59%) and varied largely between farms (-€3,502 to €3,323). Within a given economic situation, i.e., cows of the same farm, the number of lactations was identified as the major lever to cow profitability for most farms, followed by the individual milk yield level and the number of days in milk at culling during last lactation. This indicates that the economic sustainability of the farm is inherently linked to the ability of cows to cope with their environment. The vastly different monetary value associated with, e.g., productivity and longevity parameters and the heterogeneity in the ranking of their effect sizes between farms also show that the economic impacts of herd characteristics are highly farm-specific. Evaluation of the overall lifetime profitability of culled cows along with identification of economically poor farm-specific herd characteristics can help to pinpoint problems, optimize herd management, and prioritize investment necessities. [ABSTRACT FROM AUTHOR]

Simple Summary: The ability of farms to produce milk sustainably is closely related to dairy cow longevity, i.e., the length of productive life. However, longevity is a very complex feature that depends on all the aspects of the lifespan of a cow and there is no standard definition nor metric to measure it. Measuring longevity is important because it influences the profitability and the environmental impact of farms as well as the welfare of the animals. The objectives of this paper were to review metrics used to measure longevity and describe its status among high milk-producing countries. Increasing dairy cow longevity would imply that an animal has an early age at first calving and a long and profitable productive life. Combining age at first calving, length of productive life, and margin over all (available) costs provides a complete evaluation of longevity. This paper also shows that dairy cow longevity has decreased in most high milk-producing countries over time, which confirm the concerns voiced by the dairy industry and other stakeholders. Increasing cow longevity would reduce health costs and increase cow profitability while improving both animal welfare and quality of life, contributing to a more sustainable dairy industry. The ability of dairy farmers to keep their cows for longer could positively enhance the economic performance of the farms, reduce the environmental footprint of the milk industry, and overall help in justifying a sustainable use of animals for food production. However, there is little published on the current status of cow longevity and we hypothesized that a reason may be a lack of standardization and an over narrow focus of the longevity measure itself. The objectives of this critical literature review were: (1) to review metrics used to measure dairy cow longevity; (2) to describe the status of longevity in high milk-producing countries. Current metrics are limited to either the length of time the animal remains in the herd or if it is alive at a given time. To overcome such a limitation, dairy cow longevity should be defined as an animal having an early age at first calving and a long productive life spent in profitable milk production. Combining age at first calving, length of productive life, and margin over all costs would provide a more comprehensive evaluation of longevity by covering both early life conditions and the length of time the animal remains in the herd once it starts to contribute to the farm revenues, as well as the overall animal health and quality of life. This review confirms that dairy cow longevity has decreased in most high milk-producing countries over time and its relationship with milk yield is not straight forward. Increasing cow longevity by reducing involuntary culling would cut health costs, increase cow lifetime profitability, improve animal welfare, and could contribute towards a more sustainable dairy industry while optimizing dairy farmers' efficiency in the overall use of resources available. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify specific emission-reduction opportunities in dairy herds arising from aspects of useful herd management with the potential to reduce emissions, which are within the scope of veterinary activities. In future, it might be one of a veterinarian's advisory capacities to deal with the aspect of climate and environmental protection in animal husbandry. The models involved are similar to those of the national agricultural emission inventory. They allow quantifying the impacts of improved animal health, extended productive lifespan and grazing of an entire dairy herd (cows, calves, heifers and bulls) on emissions from the herd itself, in addition to those originating from the entire production chain, including provision of primary energy, water, feed production and processing. Ammonia emissions are the main focus. The reductions achieved here are not huge, though noticeable. They do not create extra costs. As can be shown, improved animal health and welfare are also environmentally beneficial. The reduction of greenhouse gas and air pollutant (eutrophying and acidifying gases and particles) emissions is an acknowledged political goal. If Germany wants to achieve the emission ceilings it has agreed to, agriculture will have to contribute. Planning will have to precede action if agriculture is itself to keep control of the processes.