Deviation of behavioural and productive parameters in dairy cows due to a lameness event: a synthesis of reviews

Lameness is a widespread multifactorial condition affecting the health and performance of dairy cows. Despite the growing support by precision farming technologies, farmers still lack reliable data-driven tools to early identify lame cows. This study used a synthesis of reviews to identify cow’s behavioural and productive parameters most related to lameness and estimate their deviation due to a lameness event. The methodological approach used reviews as starting point to identify the most pertinent studies with the intention of extracting and analysing data from these primary studies. The final dataset used information collected from 31 research papers, cited in 15 reviews, and involved more than 25,000 dairy cows. Five parameters were suitable for the meta-analysis: one about eating behaviour (eating time), three regarding activity and resting behaviour (lying bouts, lying bout duration and lying time) and milk yield. The meta-analysis revealed that all parameters had a significant deviation in cows affected by lameness. The calculation of the pooled means allowed to quantify a mean value for the deviation imposed by a severe lameness event from the value recorded on nonlame cows. Compared to a nonlame animal, a lame cow had a significant negative deviation for eating time (−39 min/day), number of lying bouts (−0.5/day), and milk yield (−3 kg/day). Lame cows had positive deviations for lying bout duration (+12 min/bout) and daily lying time (+42 min/day). The individual or combined use of these mean deviation values as alarm reference thresholds could improve the accuracy of the current automated lameness detection systems

Production of benzaldehyde, benzyl alcohol and benzoic acid by yeasts and Botrytis cinerea isolated from grape musts and wines

The capacity of 100 yeast strains - isolated from grape musts and wines from the Istituto Sperimentale per l'Enologia collection - to produce benzaldehyde, benzyl alcohol and benzoic acid was verified by inoculation into a synthetic nutrient medium (MNS). Schizosaccharomyces and Zygosaccharomyces were strongest in producing benzaldehyde (maximal amount found 1200 µg/l) and benzyl alcohol (maximally 523 µg/l). Zygosaccharomyces was also most effective in the production of benzoic acid (maximally 536 µg/l), followed by Saccharomyces, Cryptococcus, Kloeckera and Torulaspora. The hypothesis was verified that yeasts can be an exogenous source of the benzyl alcohol oxidizing enzyme in grape musts and wines. Wine yeast strains of Saccharomyces spp., Zygosaccharomyces spp. and Schizosaccharomyces spp. fermenting MNS containing 150 g/l glucose, with benzyl alcohol added, transformed this into benzoic acid only when glucose was disappearing, but not into benzaldehyde. No difference was observed between aerobic and anaerobic fermentation conditions. The uptake of benzyl alcohol was rapid in fermentation essays in presence of only 10 g/l glucose and in assimilation essais performed in yeast nitrogen base broth with assimilable carbon compounds added. A catabolic repression by glucose appears likely. Botrytis cinerea was able to transform benzyl alcohol into benzaldehyde and benzoic acid on Czapek-Dox broth with 30 g/l sucrose added. Benzyl alcohol was transformed by wine yeasts into benzoic acid when the concentration of glucose in the mineral medium was less than 10 g/l, but no production of benzaldehyde was observed. A catabolic repression of this transformation by glucose is likely. Botrytis cinerea was able to produce benzaldehyde in a mineral medium with benzyl alcohol and sucrose added

Retrospective analysis of dry period length in Italian Holstein cows

This research studied the relevance of potential sources of variation for dry period length in Italian Holstein cows reared in northern Italy and investigated the effect of days dry (DD) on milk production and calving interval in the subsequent lactation. Field data of individual cow DD were merged: a) with information from the previous lactation (6832 lactations, 87 herds) and analysed to investigate factors influencing DD; b) with milk yield (MY) and calving interval (CI) of the subsequent lactation (≈4000 lactations, >80 herds) and analysed to investigate the effect of DD on subsequent lactation performance. Individual cow DD averaged 67±27d, with a median of 62d; nearly 20% of DD were greater than 80 d. Herd had the greatest impact on DD; average herd DD was 71 d and >50% of herds had a mean dry period length >70d. Longer DD were associated with second or later parity cows, lower daily MY at dryoff, and extremes in the length of the previous lactation, either short or long. After an adjustment for MY genetic merit, dry periods 80d resulted in a 100kg increase in subsequent MY. However, yield lost in the subsequent lactation caused by average DD<65 d might be offset completely by the higher yield obtained in the previous lactation due to its longer length. Conversely, dry period length did not significantly affect ensuing CI. Therefore, data from this study and literature analysis suggest that a decrease in the duration of DD could be profitable for most herds considered. A general recommendation towards dry periods between 45 to 60d could be advised

Short communication: Reference limits for blood analytes in Holstein late-pregnant heifers and dry cows: Effects of parity, days relative to calving, and season.

Abstract Reference limits for metabolic profiles in Holstein late-pregnant heifers and dry cows were determined considering the effects of parity, days relative to calving, and season. Blood samples were collected from 104 pregnant heifers and 186 dry cows (68 primiparous and 118 pluriparous) from 60 to 10 d before the expected calving date in 31 dairy farms in northeastern Italy. Sampling was performed during summer (182 samples) and the following winter (108 samples). All the animals were judged as clinically healthy at a veterinary visit before sampling. Outliers were removed from data of each blood analyte, and variables that were not normally distributed were log transformed. A mixed model was used to test the fixed effects of parity (late-pregnant heifers, primiparous or pluriparous dry cows), class of days relative to calving (60–41 d, 40–21 d, 20–10 d), season (summer or winter), and the interactions between parity and class of days relative to calving and between parity and season, with farm as random effect. Single general reference limits and 95% confidence intervals were generated for analytes that did not vary according to fixed effects. Whenever a fixed effect included in the model significantly affected a given analyte, specific reference limits and 95% confidence intervals were generated for each of its levels. Albumin, urea, triglycerides, alanine aminotransferase, aspartate aminotransferase, creatinine kinase, conjugated bilirubin, calcium, phosphorus, magnesium, potassium, chloride, zinc, copper, and iron concentrations were not influenced by any of the fixed effects. Total protein, globulins, creatinine, glucose, alkaline phosphatase, gamma glutamyltransferase, lactate dehydrogenase, and sodium plasma concentrations were affected by parity. The class of days relative to calving had a significant effect on the concentrations of total protein, globulins, fatty acids, cholesterol, total bilirubin, and sodium. Season affected plasma concentrations of creatinine, glucose, fatty acids, lactate dehydrogenase, and sodium. Interactions between parity and class of days relative to calving and between parity and season did not significantly affect any of the blood analytes tested. The reference limits and the 95% confidence intervals for blood analytes determined in the study could help dairy practitioners to improve the accuracy of metabolic profile interpretation in Holstein late-pregnant cattle

Short communication: Reference values for blood parameters in Holstein dairy cows: Effects of parity, stage of lactation, and season of production

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A survey on sensor systems used in Italian dairy farms and comparison between performances of similar herds equipped or not equipped with sensors

Sensor systems (SS) were developed over the last few decades to help dairy farmers manage their herds. Such systems can provide both data and alerts to several productive, behavioral, and physiological indicators on individual cows. Currently, there is still a lack of knowledge on both the proportion of dairy farms that invested in SS and type of SS installed. Additionally, it is still unclear whether the performances of herds equipped with SS differ from those of similar herds managed without any technological aid. Therefore, the aims of this study were (1) to provide an insight into SS spread among Italian dairy farms and (2) to analyze the performances of similar herds equipped or not equipped with SS. To reach the former goal, a large survey was carried out on 964 dairy farms in the northeast of Italy. Farmers were interviewed by the technicians of the regional breeders association to collect information on the type of SS installed on farms and the main parameters recorded. Overall, 42% of the surveyed farms had at least 1 SS, and most of them (72%) reared more than 50 cows. Sensors for measuring individual cow milk yield were the most prevalent type installed (39% of the surveyed farms), whereas only 15% of farms had SS for estrus detection. More sophisticated parameters, such as rumination, were automatically monitored in less than 5% of the farms. To reach the latter goal of the study, a subset of 100 Holstein dairy farms with similar characteristics was selected: half of them were equipped with SS for monitoring at least individual milk yield and estrus, and the other half were managed without any SS. Average herd productive and reproductive data from official test days over 3 yr were analyzed. The outcomes of the comparison showed that farms with SS had higher mature-equivalent milk production. Further clustering analysis of the same 100 farms partitioned them into 3 clusters based on herd productive and reproductive data. Results of the Chi-squared test showed that the proportion of farms equipped with SS was greater in the cluster with the best performance (e.g., higher milk yield and shorter calving interval). However, the presence of a few farms equipped with SS in the least productive cluster for the same parameters pointed out that although the installation of SS may support farmers in time- and labor-saving or in data recording, it is not a guarantee of better herd performance

Effect of period of milk production and ripening on quality traits of Asiago cheese

After 6 and 12 months of ripening, samples of Asiago d'Allevo were analyzed for quality traits. Cheeses were produced during 3 periods using milk from cows fed a total mixed ration (TMR, May) or grazing on alpine pasture (AG) in early (July) and late (Sept.) summer. Data were submitted to ANOVA considering ripening, milk production period and farm as main effects, and whole cheese weight as covariate. During ripening, pH of AGcheese was significantly lower than that of TMR-cheese; crude fat and protein significantly increased. According to period, July-samples showed the significantly lowest value of dry matter (DM), maybe due to a lower crude fat content; however, variability in skimming method could have altered proximate composition. No texture differences were found, although increasing weight of whole cheese significantly reduced max shear force as result of a lower DM content. Lightness (L*) and yellowness (b*) significantly decreased during ripening. AG feeding system caused a lower L* and higher b* than TMR one, probably as a consequence of a different amount of milk pigments. Cheese varied also within AG season: Sept.-samples showed the lowest L* value and the highest b*

Western cape land use model overview

The Western Cape Land Use Model (WCLM) is integrated with the Western Cape Transport Model and Western Cape Freight Model in a system constituting the Western Cape Land Use and Transport Interaction Model (WCLUTI). The WCLM includes several model components: regions are stratified by inside and outside the City of Cape Town, markets are divided by residential and non-residential, and land use identity is divided by “formal” and “informal”. The “formal” component is modelled using CUBE Land software, which is designed to forecast the expected occupied real estate supply, location of households and firms/jobs, and rent values. The “informal” residential land use (additional informal dwellings and informal settlements) is modelled by means of utility-based supplemental models, affecting the available land and the formal location behaviour in areas close to informal property groups through a feedback loop. The objective of the joint model is to predict these components for the forecasting year under different user-defined scenarios of population and economic growth, regulations and subsidies, real estate projects and accessibility/attractiveness levels provided by the transportation system. These forecasts feed the transportation model in an integrated system, informing the land use and transport planning process through performance-based indicators, helping to achieve coordination across different sectors.Papers presented virtually at the 39th International Southern African Transport Conference on 05 -07 July 202