Modeling the profitability of investing in cooling systems in dairy farms under several intensities of heat stress in the Mediterranean

Heat stress (HS) in dairy cows affects dry matter intake, milk yield, reproduction, and culling rate. Cooling systems (CS) may partially revert these effects, but their profitability depends on the price of milk and effectiveness and cost of the CS. Because these effects may interact over time, stochastic dynamic models are useful tools to evaluate the effects of HS and the profitability of CS. Several HS intensity scenarios, from 1,000 to 31,000 temperature and humidity index load (THI_Load, units/yr), were simulated in a stochastic dynamic dairy herd simulator, with 3 milk prices (€0.28, €0.32, and €0.36/L) and 2 initial investment costs in fans and sprinklers (€100 and €200/cow). The HS and CS scenarios simulated were modeled as a function of the THI_Load to predict the technical and economic performance in 21 selected locations of the Mediterranean. The THI_Load mean of the 21 selected locations was 12,530 (ranging from 6,908 to 31,424). Heat stress reduced milk yield in a range of 346 to 1,696 L/cow per year, feeding costs in a range of €63 to €266/cow per year, and pregnancy rate in a range of 1.0 to 3.0%/yr and increased culling rates in a range of 5.7 to 16.4%/yr compared with the control scenario. The implementation of CS increased milk yield in a range from 173 to 859 L/cow per year, feeding cost in a range from €26 to €139/cow per year, and pregnancy rate in a range from 0.1 to 1.0%/yr and reduced culling rate in a range from 1.0 to 3.9%/yr compared with HS scenarios. When the THI_Load was ≤6,300, the implementation of CS was never profitable, from 6,300 to 11,000 was dependent on milk price and CS cost, and over 11,000 was consistently profitable. The Δnet margin (€/cow per year) for CS at an initial investment cost of €100/cow ranged from -9 to 239 and at an initial investment cost of €200/cow ranged from -24 to 225. The profitability of CS depends on the THI_Load, milk price, and CS cost.

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.

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.

Economics of timed artificial insemination with unsorted or sexed semen in a high-producing, pasture-based dairy production system

This study used a stochastic simulation model to estimate the potential economic benefit of using timed artificial insemination (TAI) in combination with conventional unsorted (TCONV) and sexed (TSEX) semen in heifers only (TCONV-H, TSEX-H) and in both heifers and lactating cows (TCONV-HC, TSEX-HC) in a high-producing, pasture-based production system. The scenarios were compared with a conventional reproductive policy (CONV) in which heifers and cows were inseminated with conventional unsorted semen after estrus detection. Sensitivity analysis was also used to estimate the effect of hormone costs from TAI use on the profitability of each program relative to CONV. The mean annual (± standard deviation) profit advantage (ΔPROF) over CONV for TCONV-H, TCONV-HC, TSEX-H, and TSEX-HC scenarios were €3.90/cow ± 4.65, €34.11/cow ± 25.69, €13.96/cow ± 6.83, and €41.52/cow ± 42.86, respectively. Combined application of both technologies was shown to return a greater annual ΔPROF on average compared with that achievable from TAI alone. However, the risk of not returning a positive annual ΔPROF varied across the scenarios with higher risk in TCONV-H and TSEX-HC. Specifically, TCONV-H and TSEX-HC had a 24 and 18% chance, respectively, of not returning a positive annual ΔPROF. Sensitivity analysis showed that when hormone costs increased by €10/cow TCONV-H and TSEX-HC had a 38 and 23% chance, respectively, of not returning a positive annual ΔPROF. The range in ΔPROF for TCONV policies was most sensitive to the TAI pregnancy rate and TSEX policies were most sensitive to the relative fertility achieved with sexed compared with unsorted semen. This study has shown TAI and sexed semen are complementary technologies that can increase genetic gain and profitability in a pasture-based, dairy production system.

Production costs, economic viability, and risks associated with compost bedded pack, freestall, and drylot systems in dairy farms

The adoption of intensive production systems, such as compost bedded pack (CB) and freestall (FS), has increased recently in tropical regions, mainly replacing the drylot system (DL). Thus, our objectives were to compare production costs, economic outcomes, and risk of dairy operations in CB, FS, and DL systems. We collected data from 2 181 Brazilian farms over 120 consecutive months; 960 farms (144 CB, 133 FS, and 683 DL) met our selection criteria. All costs were modeled for two animal production categories: milking cows and non-milking animals. We used a regression model that included linear and quadratic parameters, and we added the production system as a fixed variable for all parameters tested with this model. Consultant, year, herd, and herd × system interaction were included in the model as random variables. Further, we simulated annual technical and economic indexes per farm. In addition, we developed a risk analysis to measure the probability of negative profit of the farms based on a 14-year historical series of milk prices. All production costs were affected by the system. Feed, medicine, sundry, and labor costs per farm per year were greater in DL farms when milk yield (MY) was greater than 3 500 L/day. The variables such as milk yield, assets per liter, asset turnover rate, return on assets, operational profit, profit per cow, and per liter of milk variables were greater in CB and FS with high MY (>3 000 L/day). Nonetheless, DL had the greatest economic indexes with a lower MY (<3 000 L/day), lower operating costs, and greater economic outcomes. The risk analysis indicated that the probability of negative profit (risk) was reduced for CB and FS as MY increased, but DL had the lowest risk with low MY levels. In conclusion, we suggest DL as the most attractive system for farms with MY between 150 and 3 000 L of milk/day as the DL had the lowest risk and the greatest profit in this production scale. Despite similar outcomes for CB and FS in most of the farms, the profit per cow ($/year), assets turnover rate (%), risk (%) and expected profit ($/L) analysis indicated that CB could be recommended for farms with MY greater than 3 200 L of milk/day, whereas based on risk (%) and expected profit ($/L), FS would be the most profitable system in dairies producing more than 8 000 L of milk/day per farm.

Derivation of economic values for German dairy breeds by means of a bio-economic model-with special emphasis on functional traits

To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.

Reviewing age-structured epidemiological models of cattle diseases tailored to support management decisions: Guidance for the future

Mechanistic simulation models are being increasingly used as tools to assist with animal health decision-making in the cattle sector. We reviewed scientific literature for studies reporting age-structured cattle management models in application to infectious diseases. Our emphasis was on papers dedicated to support decision making in the field. In this systematic review we considered 1290 manuscripts and identified 76 eligible studies. These are based on 52 individual models from 10 countries addressing 9 different pathogens. We provide an overview of these models and present in detail their theoretical foundations, design paradigms and incorporated processes. We propose a structure of the characteristics of cattle disease models using three main features: [1] biological processes, [2] farming-related processes and [3] pathogen-related processes. It would be of benefit if future cattle disease models were to follow this structure to facilitate science communication and to allow increased model transparency.

Understanding the adoption of smartphone apps in dairy herd management

The number of decision support tools available to farmers, including dairy herd management smartphone apps, has been steadily increasing. The existing literature does not cover topics concerning the adoption and use of herd management smartphone apps or which specific functions of such apps are perceived as most useful by dairy farmers. It is unclear whether technology adoption can only be explained by economic reasoning, because the beliefs about a technology also play a role in decision-making. Therefore, this study seeks to determine whether an extended technology acceptance model can explain adoption and use of herd management smartphone apps. Results about the adoption and use of dairy herd management smartphone apps are derived from an online survey conducted in 2018 with 280 German dairy farmers. To model farmers' frequency of use of herd management smartphone apps, we applied partial least squares structural equation modeling and an ordered logit model. Our results show that 93% of the dairy farmers in our sample use a smartphone and 61% already use a herd management smartphone app. Daily use is reported by 38% of the adopters. Dairy farmers rated functions related to the observation of animal health, reproduction management, and data gathering as most useful, which should be in focus by developers and providers for future development. The key attitudinal components of the technology acceptance model, namely perceived ease of use and perceived usefulness, both positively influence the intention to use such apps. This ultimately has a positive effect on the actual usage behavior. Besides other factors, dairy farmers' education and knowledge of herd management smartphone apps have a positive effect on perceived ease of use. Our model explains 33% of the variance in the actual usage behavior related to herd management smartphone apps. Because perceived ease of use and perceived usefulness positively influence the intention to use such apps and ultimately the actual usage behavior, developers and providers should highlight the benefits of using herd management smartphone apps and also keep the interface of the apps as simple as possible.

Recording Heart Rate Variability of Dairy Cows to the Cloud-Why Smartphones Provide Smart Solutions

In the last decades, there has been an increasing interest in animal protection and welfare issues. Heart rate variability (HRV) measurement with portable heart rate monitors on cows has established itself as a suitable method for assessing physiological states. However, more forward-looking technologies, already successfully applied to evaluate HRV data, are pushing the market. This study examines the validity and usability of collecting HRV data by exchanging the Polar watch V800 as a receiving unit of the data compared to a custom smartphone application on cows. Therefore, both receivers tap one signal sent by the Polar H7 transmitter simultaneously. Furthermore, there is a lack of suitable methods for the preparation and calculation of HRV parameters, especially for livestock. A method is presented for calculating more robust time domain HRV parameters via median formation. The comparisons of the respective simultaneous recordings were conducted after artifact correction for time domain HRV parameters. High correlations (r = 0.82⁻0.98) for cows as well as for control data set in human being (r = 0.98⁻0.99) were found. The utilization of smart devices and the robust method to determine time domain HRV parameters may be suitable to generate valid HRV data on cows in field-based settings.