Preventive diagnosis of dairy cow lameness

This research aimed to develop a Fuzzy inference based on expert system to help preventing lameness in dairy cattle. Hoof length, nutritional parameters and floor material properties (roughness) were used to build the Fuzzy inference system. The expert system architecture was defined using Unified Modelling Language (UML). Data were collected in a commercial dairy herd using two different subgroups (H-1 and H-2), in order to validate the Fuzzy inference functions. The numbers of True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN) responses were used to build the classifier system up, after an established gold standard comparison. A Lesion Incidence Possibility (LIP) developed function indicates the chances of a cow becoming lame. The obtained lameness percentage in H-1 and H-2 was 8.40% and 1.77%, respectively. The system estimated a Lesion Incidence Possibility (LIP) of 5.00% and 2.00% in H-1 and H-2, respectively. The system simulation presented 3.40% difference from real cattle lameness data for H-1, while for H-2, it was 0.23%; indicating the system efficiency in decision-making.

Understanding diversity of hepatic metabolism and related adaptations in the early lactating dairy cow.

The onset of lactation in dairy cows represents a major metabolic challenge that involves large adaptations in glucose, fatty acid, and mineral metabolism to support lactation and to avoid metabolic dysfunction. The complex system of adaptation can differ considerably between cows, and may have a genetic base. In the present review, the variation in adaptive reactions in dairy cows is discussed. In these studies, the liver being a key metabolic regulator for understanding the variation in adaptive performance of the dairy cow was the main focus of research. Liver function was evaluated through gene expression measurements; to explain the associated phenotypic variability and to identify descriptors for metabolic robustness in dairy cows. Hence, the identified genes involved act as a connecting link between the genotype encoded on the DNA and the phenotypic expression of the target factors at a protein level. The integration of phenotypic data, including gene expression profiles, and genomic data will facilitate a better characterization of the complex interplay between these levels, and will improve the genetic understanding necessary to unravel a certain trait or multi-trait such as metabolic robustness in dairy cows.

Wisconsin dairy cow

Mode of access: Internet.

The relationship between the stockperson's personality and attitudes and the productivity of dairy cows

This study investigated the relationships amongst personality traits and attitudes of 311 dairy stockpeople and the milk yield they obtained. A questionnaire pack consisting of a big-five measure of personality (which includes the traits of extraversion, agreeableness, conscientiousness, emotional stability and intellect), a four-factor attitude questionnaire and associated demographic and production questions was posted out to Northern Ireland dairy farmers. Pearson correlations were used to assess the relationship between personality and attitudes and partial correlations were calculated between milk yield and these psychometric measures. The personality traits of agreeableness and conscientiousness were most strongly correlated to positive attitudes towards working with dairy cows. None of the stockpeople's personality traits were significantly correlated with the milk yield they obtained. Three of the attitude scales, however, were significantly correlated with milk yield; milk yield was related to higher levels of empathy and job satisfaction and lower levels of negative beliefs, These findings, along with previous research, suggest stockperson attitudes may be important in relation to dairy cow welfare and production.

An evaluation of the effect of altering nutrition and nutritional strategies in early lactation on reproductive performance and estrous behavior of high-yielding Holstein-Friesian dairy cows

Reproductive performance in the high-yielding dairy cow has severely decreased in the last 40 yr. The aim of this study was to compare the effectiveness of 4 nutritional strategies in improving the reproductive performance of high-yielding dairy cows. It was hypothesized that offering cows a high-starch ration in early lactation would enhance the onset of luteal activity, and that decreasing the severity of negative energy balance in the early postcalving period would improve reproductive parameters. Nutritional regimens aimed at improving fertility were applied to 96 Holstein-Friesian dairy animals. Upon calving, animals were allocated in a balanced manner to one of 4 dietary treatments. Primiparous animals were balanced according to live weight, body condition score and calving date. Multiparous animals were balanced according to parity, previous lactation milk yield, liveweight, body condition score and calving date. Treatment 1 was based on an industry best practice diet (control) to contain 170 g of crude protein/kg of dry matter. Treatment 2 was an individual cow feeding strategy, whereby the energy balance (EB) of individual animals was managed so as to achieve a predetermined target daily EB profile (+/- 10 MJ/d). Treatment 3 was a high-starch/high-fat combination treatment, whereby an insulinogenic (high-starch) diet was offered in early lactation to encourage cyclicity and followed by a lipogenic (low-starch, high-fat) diet to promote embryo development. Treatment 4 was a low-protein diet, containing 140 g of crude protein/kg of dry matter, supplemented with protected methionine at an inclusion level of 40 g per animal per day. The nutritional strategies implemented in this study had no statistically significant effects on cow fertility measures, which included the onset of luteal activity, conception rate, in-calf rate, and the incidence of atypical cycles. The individual cow feeding strategy improved EB in early lactation but had no benefit on conception rate to first insemination. However, conception rate to second insemination, 100-d pregnancy rate (from the commencement of breeding), and overall pregnancy rate tended to be higher in this group. The high-starch/high-fat treatment tended to decrease the proportion of delayed ovulations and increase the proportion of animals cycling by d 50 postcalving. Animals that failed to conceive to first insemination had a significantly longer luteal phase in the first cycle postpartum and a longer inter-ovulatory interval in the second cycle postpartum. With regards to estrous behavior, results indicate that as the size of the sexually active group increased, the intensity of estrus and the expression of mounting or attempting to mount another cow also increased. Furthermore, cows that became pregnant displayed more intense estrous behavior than cows that failed to become pregnant.

Selenium supplementation of lactating dairy cows: effects on milk production and total selenium content and speciation in blood, milk and cheese

Forty-multiparous Holstein cows were used in a 16-wk continuous design study to determine the effects of either selenium (Se) source, selenized yeast (SY) (derived from a specific strain of Saccharomyces cerevisiae CNCM I-3060 Sel-Plex®) or sodium selenite (SS), or inclusion rate of SY on Se concentration and speciation in blood, milk and cheese. Cows received ad libitum a TMR with 1:1 forage:concentrate ratio on a dry matter (DM) basis. There were four diets (T1-T4) which differed only in either source or dose of Se additive. Estimated total dietary Se for T1 (no supplement), T2 (SS), T3 (SY) and T4 (SY) was 0.16, 0.30, 0.30 and 0.45 mg/kg DM, respectively. Blood and milk samples were taken at 28 day intervals and at each time point there were positive linear effects of SY on Se concentration in blood and milk. At day 112 blood and milk Se values for T1-T4 were 177, 208, 248, 279 ± 6.6 and 24, 38, 57, 72 ± 3.7 ng/g fresh material, respectively and indicate improved uptake and incorporation of Se from SY. While selenocysteine (SeCys) was the main selenised amino acid in blood its concentration was not markedly affected by treatment, but the proportion of total Se as selenomethionine (SeMet) increased with increasing inclusion rate of SY. In milk, there were no marked treatment effects on SeCys content, but Se source had a marked effect on the proportion of total Se as SeMet. At day 112 replacing SS (T2) with SY (T3) increased the SeMet concentration of milk from 36 to 111 ng Se/g and its concentration increased further to 157 ng Se/g as the inclusion rate of SY increased further (T4) to provide 0.45 mg Se/kg TMR. Neither Se source nor inclusion rate effected the keeping quality of milk. At day 112, milk from T1, T2, and T3 was made into a hard cheese and Se source had a marked effect on total Se and the proportion of total Se comprised as either SeMet or SeCys. Replacing SS (T2) with SY (T3) increased total Se, SeMet and SeCys content from 180 to 340 ng Se/g, 57 to 153 ng Se/g and 52 to 92 ng Se/g, respectively. Key words: dairy cow, milk and cheese, selenomethionine, selenocysteine, milk keeping quality

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Alternatives to linear analysis of energy balance data from lactating dairy cows

The current energy requirements system used in the United Kingdom for lactating dairy cows utilizes key parameters such as metabolizable energy intake (MEI) at maintenance (MEm), the efficiency of utilization of MEI for 1) maintenance, 2) milk production (k(l)), 3) growth (k(g)), and the efficiency of utilization of body stores for milk production (k(t)). Traditionally, these have been determined using linear regression methods to analyze energy balance data from calorimetry experiments. Many studies have highlighted a number of concerns over current energy feeding systems particularly in relation to these key parameters, and the linear models used for analyzing. Therefore, a database containing 652 dairy cow observations was assembled from calorimetry studies in the United Kingdom. Five functions for analyzing energy balance data were considered: straight line, two diminishing returns functions, (the Mitscherlich and the rectangular hyperbola), and two sigmoidal functions (the logistic and the Gompertz). Meta-analysis of the data was conducted to estimate k(g) and k(t). Values of 0.83 to 0.86 and 0.66 to 0.69 were obtained for k(g) and k(t) using all the functions (with standard errors of 0.028 and 0.027), respectively, which were considerably different from previous reports of 0.60 to 0.75 for k(g) and 0.82 to 0.84 for k(t). Using the estimated values of k(g) and k(t), the data were corrected to allow for body tissue changes. Based on the definition of k(l) as the derivative of the ratio of milk energy derived from MEI to MEI directed towards milk production, MEm and k(l) were determined. Meta-analysis of the pooled data showed that the average k(l) ranged from 0.50 to 0.58 and MEm ranged between 0.34 and 0.64 MJ/kg of BW0.75 per day. Although the constrained Mitscherlich fitted the data as good as the straight line, more observations at high energy intakes (above 2.4 MJ/kg of BW0.75 per day) are required to determine conclusively whether milk energy is related to MEI linearly or not.

Production and metabolic effects of site of starch digestion in lactating dairy cattle

Milk solids yield in modern dairy cows has increased linearly over the last 50 years, stressing the need for maximal dietary energy intake to allow genetic potential for milk energy yield to be realized with minimal negative effects on health and reproduction. Feeding supplemental starch is a common approach for increasing the energy density of the ration and supplying carbon for meeting the substantial glucose requirement of the higher yielding cow. In this regard, it is a long held belief that feeding starch in forms that increase digestion in the small intestine and glucose absorption will benefit the cow in terms of energetic efficiency and production response, but data supporting this dogma are equivocal. This review will consider the impact of supplemental starch and site of starch digestion on metabolic and production responses of lactating dairy cows, including effects on feed intake, milk yield and composition, nutrient partitioning, the capacity of the small intestine for starch digestion, and nutrient absorption and metabolism by the splanchnic tissues (the portal-drained viscera and liver). Whilst there appears to be considerable capacity for starch digestion and glucose absorption in the lactating dairy cow, numerous strategic studies implementing postruminal starch or glucose infusions have observed increases in milk yield, but decreased milk fat concentration such that there is little effect on milk energy yield, even in early lactation. Measurements of energy balance confirm that the majority of the supplemental energy arising from postruminal starch digestion is used with high efficiency to support body adipose and protein retention, even in early lactation. These responses may be mediated by changes in insulin status, and be beneficial to the cow in terms of reproductive success and well-being. However, shifting starch digestion from the rumen impacts the nitrogen economy of the cow as well by shifting the microbial protein gained from starch digestion from potentially absorbable protein to endogenous faecal loss.