Dynamic forecasting of individual cow milk yield in automatic milking systems

Accurate forecasting of dairy cow milk yield is useful to dairy farmers, both in relation to financial planning and for detection of deviating yield patterns, which can be an indicator of mastitis and other diseases. In this study we developed a dynamic linear model (DLM) designed to forecast milk yields of individual cows per milking, as they are milked in milking robots. The DLM implements a Wood's function to account for the expected total daily milk yield. It further implements a second-degree polynomial function to account for the effect of the time intervals between milkings on the proportion of the expected total daily milk yield. By combining these 2 functions in a dynamic framework, the DLM was able to continuously forecast the amount of milk to be produced in a given milking. Data from 169,774 milkings on 5 different farms in 2 different countries were used in this study. A separate farm-specific implementation of the DLM was made for each of the 5 farms. To determine which factors would influence the forecast accuracy, the standardized forecast errors of the DLM were described with a linear mixed effects model (lme). This lme included lactation stage (early, middle, or late), somatic cell count (SCC) level (nonelevated or elevated), and whether or not the proper farm-specific version of the DLM was used. The standardized forecast errors of the DLM were only affected by SCC level and interactions between SCC level and lactation stage. Therefore, we concluded that the implementation of Wood's function combined with a second-degree polynomial is useful for dynamic modeling of milk yield in milking robots, and that this model has potential to be used as part of a mastitis detection system.     

Estimation of circulating bovine leukemia virus levels using conventional blood cell counts

Bovine leukemia virus (BLV) is widely prevalent in Japanese dairy farms. To control BLV infections in Japan, segregating or managing cows according to their proviral load (PVL) is a rational strategy. This study was conducted to establish a quantitative procedure for estimating blood PVL per microliter using a statistical model to offer a cost-effective alternative to the conventional quantitative real-time PCR method. In total, 250 Holstein cows infected with BLV were identified from 10 commercial dairy farms. Information on age was collected and blood samples were tested for white blood cell and lymphocyte counts and PVL using PCR. Generalized linear models with quasi-Poisson errors were used to estimate PVL by selecting age, logarithm of lymphocyte count, and their interaction term as explanatory variables. To evaluate the model, blood samples of 92 BLV-infected Holstein cows from 2 other commercial dairy farms were tested, and measured PVL values were compared with estimated PVL values by the model. The logPVL per microliter was modeled by positive associations with log lymphocyte count and age and a negative association with the interaction term. In the evaluation, measured PVL values had a strong correlation with estimated PVL values (Spearman's ρ = 0.87). In conclusion, our model provides a cost-effective and more rapid alternative to the conventional method to facilitate test and segregation or management of BLV-suspected cows.     

Risk assessment of exposure to mycotoxins (aflatoxins and fumonisins) through corn tortilla intake in Veracruz City (Mexico)

This study aimed to assess aflatoxin and fumonisin intake through corn tortilla consumption in Veracruz city. Between October 2013 and February 2015, a total of 120 corn tortilla samples (2 kg samples, 40 samples per year) were randomly collected. Aflatoxins and fumonisins were quantified by high performance liquid chromatography coupled with a fluorescence detector. A probability density function (PDF) was used for describing corn tortilla intake, body weight of the Veracruz city population, mycotoxin content of corn tortilla samples and estimated mycotoxin daily intake. The Monte Carlo method with 10,000 iterations was employed to assess the population exposure risk. The highest level of total aflatoxins (AFT) was 22.17 μg kg^?1, and 526.6 μg kg^?1 for fumonisins B₁ plus B₂, with 85% and 90% of contaminated samples respectively. Up to 69.7 % of the population was estimated to consume a higher aflatoxin dose than that recommended by the JECFA (1 ng kg^?1 of body weight per day); it was found that the recommended dose was exceeded to a greater extent in the male population, due to higher consumption of corn. The risk of fumonisin intake was less than 5 % due to the low presence and levels of these toxins in corn tortillas. The results suggest that corn tortilla consumers are at dietary risk caused by AFT contamination; this information should be considered when taking action to protect public health.     

Approximate Model-Free Assessment of Oscillation Stability Determined by the PLLs in a Weakly Grid-Connected Wind Farm with Multiple PMSGs

Abstract

The study investigates the oscillation stability determined by phase locked loops (PLLs) in a weakly grid-connected wind farm with multiple permanent magnet synchronous generators (PMSGs). To this end, an equivalent model of the wind farm is derived. Based on the derived equivalent model, the oscillation stability of the wind farm as determined by the dynamics of the PLLs is analytically examined. This paper explains why the PLLs equipped by the PMSGs in the wind farm can lead to instability risk under the condition of weak grid connection. A simple index is proposed to approximately assess instability risk of the wind farm due to the PLLs. The parametric model of the wind farm with the PMSGs is not necessary to calculate the proposed simple index. Hence, it is model-free and applicable in practice when it is difficult to establish the parametric model. An example of a grid-connected wind farm with 12 PMSGs is presented to evaluate and demonstrate the analysis conducted and the simple index proposed in the paper.     

Technoeconomic study for the optimization of turbine size and wind farm layouts

A technoeconomic analysis and optimization of wind turbine size and layout are performed using WAsP software. A case study of a 100‐MW wind farm located in Egypt is considered. Wind atlas for Egypt was used as the input data of the WAsP software. Two turbine models of powers 52 and 80 MW are considered for this project. The wind turbine size and distributions are selected based on the technoeconomic optimization, namely minimum wake effect, maximum annual energy production (AEP) rate, optimum cash flow, and payback period. The future worth method is adopted in economic comparison between the two alternatives, and the cash flow diagram provided the payback period and future worth after the lifetime of the plant. The results showed that (1) the AEP dramatically decreases for a wind farm area less than 15 km²; (2) the turbine spacing, spacing‐to‐diameter ratio, and the setback distances decrease and the wind turbine density and wake losses increase with decreasing the wind turbines size; (3) the total net AEP using G52 is lower than that of using G80 by about 16%; (4) the technoeconomic analysis recommended using G80 as it has higher profit than those of G52 by about $20 million.     

Synergistic effect in anaerobic co-digestion of rice straw and dairy manure - a batch kinetic study

Methane yield of seven co-digestion mixture proportions (1:0, 5:1, 3:1, 1:1, 1:3, 1:5, and 0:1) of rice straw and dairy manure was investigated at a total solids (TS) loading of 8%. Methane yield was improved by 50–57% and 9–10% with co-digestion at mixture proportions of 1:1,1:3 and 1:5 compared to mono digestion of rice straw and dairy manure, respectively. The modified Gompertz model accounted well for the kinetic behavior of methane yield with an R² of 0.99 and Root Mean Square Error of 0.06–1.70. It was observed that the co-digestion caused a reduction in lag phase time and improvement in the maximum methane production rate. The positive synergistic effects are a result of nutrient balance with the co-digestion of dairy manure and rice straw.     

Quantifying calf mortality on dairy farms: Challenges and solutions

In the Netherlands, the mortality rate of ear-tagged calves <1 yr is one of the indicators that is continuously monitored in census data and is defined as the number of deceased calves relative to the number of calf-days-at-risk. In 2017, yearly calf mortality rates were published in the lay press and resulted in discussions about the calculation of this parameter among stakeholders because the same parameter appeared to be calculated in many different ways by different organizations. These diverse definitions of calf mortality answered different aims such as early detection of deviations, monitoring trends, or providing insight into herd-specific results, but were difficult to understand by stakeholders. The aim of this study was to evaluate several definitions of calf mortality for scientific validity, usefulness for policymakers, and comprehensibility by farmers. Based on expert consultations, 10 definitions for calf mortality were evaluated that assessed different age categories, time periods, and denominators. Differences in definitions appeared to have a large effect on the magnitude of mortality. For example, with the original mortality parameter, the mortality rate was 16.5% per year. When the first year of life was subdivided into 3 age categories, the mortality rate was 3.3, 4.5, and 3.1% for postnatal calves (≤14 d), preweaned calves (15–55 d), and weaned calves (56 d–1 yr), respectively. Although it was logical that these mortality rates were lower than the original, the sum of the 3 separate mortality rates was also lower than the original mortality rate. The reason was that the number of calves present in a herd and the risk of mortality are not randomly distributed over a calf's first year of life and the conditional nature of mortality rates when calculated for different age categories. Ultimately, 4 parameters to monitor calf mortality in Dutch dairy herds were chosen based on scientific value, usefulness for monitoring of trends, and comprehensibility by farmers: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (≤14 d), preweaned calf mortality rate (15–55 d), and weaned calf mortality rate (56 d–1 yr). Slight differences in definitions of parameters can have a major effect on results, and many factors have to be taken into account when defining an important health indicator such as mortality. Our evaluation resulted in a more thorough understanding of the definitions of the selected parameters and agreement by the stakeholders to use these key indicators to monitor calf mortality.     

Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships

Efforts to improve dairy production in smallholder farming systems of East Africa over the past decade have had limited impact because of the lack of records on performance to guide targeted breeding programs. Estimates of genetic parameters in these systems are lacking. Using data generated through a project (“Germplasm for Dairy Development in East Africa”) in Kenya and a genomic relationship matrix from genotypic records, we examined the potential impact of different models handling contemporary groups or herd effects on estimates of genetic parameters using a fixed regression model (FRM) for test-day (TD) milk yields, and the covariance structure for TD milk yield at various stages of lactation for animals using a random regression model (RRM). Models in which herd groups were defined using production levels derived from the data fitted the data better than those in which herds were grouped depending on management practices or were random. Lactation curves obtained for animals under different production categories did not display the typical peak yield characteristic of improved dairy systems in developed countries. Heritability estimates for TD milk yields using the FRM varied greatly with the definition of contemporary herd groups, ranging from 0.05 ± 0.03 to 0.27 ± 0.05 (mean ± standard error). The analysis using the RRM fitted the data better than the FRM. The heritability estimates for specific TD yields obtained by the RRM were higher than those obtained by the FRM. Genetic correlations between TD yields were high and positive for measures within short consecutive intervals but decreased as the intervals between TD increased beyond 60 d and became negative with intervals of more than 5 mo. The magnitude of the genetic correlation estimates among TD records indicates that using TD milk records beyond a 60-d interval as repeated measures of the same trait for genetic evaluation of animals on smallholder farms would not be optimal. Although each individual smallholder farmer retains only a few animals, using the genomic relationship between animals to link the large number of farmers operating under specified environments provides a sufficiently large herd-group for which a breeding program could be developed.     

Effect of manipulating progesterone before timed artificial insemination on reproductive and endocrine outcomes in high-producing multiparous Holstein cows

Our objective was to evaluate the effect of manipulating progesterone (P4) concentrations before timed artificial insemination (TAI) on reproductive and endocrine outcomes in high-producing Holstein cows. Multiparous lactating Holstein cows (n = 80) were synchronized for first TAI using a Double-Ovsynch protocol and were randomly assigned to receive 25 mg of PGF_2α 1 d after the first GnRH treatment of the Breeding-Ovsynch protocol that included a once-used P4 insert (low-P4 group) or to receive 2 new P4 inserts during the Breeding-Ovsynch protocol (high-P4 group). Blood samples were collected thrice weekly from ?10 to 32 d relative to TAI for all cows and from 32 to 67 d after TAI for pregnant cows and were analyzed for P4 and pregnancy-specific protein B (PSPB) concentrations. Expression of IFNτ-stimulated gene 15 (ISG15) was assessed in blood leukocytes 18 and 20 d after TAI. As expected, P4 concentrations were greater for high-P4 cows than for low-P4 cows from 3 to 8 d before TAI. Incidence of double ovulation was 3-fold greater for low-P4 cows than for high-P4 cows (33 vs. 10%), which resulted in more twin pregnancies 32 d after TAI for low-P4 cows than for high-P4 cows (29 vs. 0%). Low-P4 cows had larger preovulatory follicles at the last GnRH treatment of the Double-Ovsynch protocol and greater P4 concentrations than high-P4 cows after TAI. Relative expression of ISG15 mRNA 18 and 20 d after TAI was greater for low-P4 cows than for high-P4 cows and for pregnant cows than for nonpregnant cows. Overall, PSPB concentrations tended to be greater for low-P4 cows than for high-P4 cows, and pregnant cows had greater P4 concentrations than nonpregnant cows. In summary, cows with low P4 before TAI had increased preovulatory follicle diameter, PSPB concentrations, relative expression of ISG15 mRNA 18 and 20 d after TAI, double ovulations, and twinning compared with cows with high P4 before TAI. Increasing P4 before TAI may effectively decrease double ovulation and twinning in high-producing multiparous Holstein cows.