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Studies of dairy cow longevity usually focus on the animal life after first calving, with few studies considering early life conditions and their effects on longevity. The objective was to evaluate the effect of birth conditions routinely collected by Dairy Herd Improvement agencies on offspring longevity measured as length of life and length of productive life. Lactanet provided 712,890 records on offspring born in 5,425 Quebec dairy herds between January 1999 and November 2015 for length of life, and 506,066 records on offspring born in 5,089 Quebec dairy herds between January 1999 and December 2013 for length of productive life. Offspring birth conditions used in this study were calving ease (unassisted, pull, surgery, or malpresentation), calf size (small, medium, or large), and twinning (yes or no). Observations were considered censored if the culling reason was "exported," "sold for dairy production," or "rented out" as well as if the animals were not yet culled at the time of data extraction. If offspring were not yet culled when the data were extracted, the last test-day date was considered the censoring date. Conditional inference survival trees were used in this study to analyze the effect of offspring birth conditions on offspring longevity. The hazard ratio of culling between the groups of offspring identified by the survival trees was estimated using a Cox proportional hazard model with herd-year-season as a frailty term. Five offspring groups were identified with different length of life based on their birth condition. Offspring with the highest length of life [median = 3.61 year; median absolute deviation (MAD) = 1.86] were those classified as large or medium birth size and were also the result of an unassisted calving. Small offspring as a result of a twin birth had the lowest length of life (median = 2.20 year; MAD = 1.69) and were 1.52 times more likely to be culled early in life. Six groups were identified with different length of productive life. Offspring that resulted from an unassisted or surgery calving and classified as large or medium when they were born were in the group with the highest length of productive life (median = 2.03 year; MAD = 1.63). Offspring resulting from a malpresentation or pull in a twin birth were in the group with the lowest length of productive life (median = 1.15 year; MAD = 1.11) and were 1.70 times more likely to be culled early in life. In conclusion, birth conditions of calving ease, calf size, and twinning greatly affected offspring longevity, and such information could be used for early selection of replacement candidates. more...

The series of events leading to the decision to cull a cow is complex, involving both individual-level and herd-level factors. While the decision is guided by financial returns, it is also influenced by social and psychological factors. Research studies on the motivational and behavioural aspects of farmers' decision utility are sparse, and nonexistent regarding culling expectations and its decision process. Our goal was to identify shared criteria on culling decisions held by dairy producers and farm advisers, with the help of the Q-methodology. Forty-one dairy producers and 42 advisers (17 veterinarians, 13 feed mill advisers, and 12 dairy herd improvement (DHI) advisers) undertook a Q-sort with 40 statements that represented a range of views about cow and herd health, production performance, management issues, and material factors that might impact their culling decision-making process. The sorts were analysed by-person using factor analysis and oblimin rotation. A single view on culling could be identified among dairy producers that can be extended to dairy farm advisers, who showed two variations of the same well-structured, uni-dimensional decision-making process. Udder health, milk production performance, and milk quota management were the key criteria for the culling decision. Farm management parameters (debts, amortization, employees, milking parlour capacity, herd size) did not play any role in the decision process. Three key differences were, however, identified between producers and the two types of advisers. One group of advisers followed the recommendations from mathematical models, where pregnancy is a major determinant of a cow's value. They assessed the cow in a more abstract way than did the other participants, still taking into account udder health and milk production, but adding economic considerations, like the availability of financial incentives and an evaluation of the post-partum health of the cow. Dairy producers were also more concerned about producing healthy and safe milk, which might reflect a different value given to dairy farming than by advisers. Very different degrees of importance were given to animal welfare by the three groups, which could represent different views on the attributed relationships between dairy farmers and their animals. Our findings suggest that dairy producers and their advisers hold a general common view regarding culling decision-making. However there are significant differences between producers and advisers, and among advisers. Understanding and managing these differences is important for assisting the change management processes required to increase farm profitability, and call for further investigation. more...

There is growing interest among the public in farm animal welfare and a need for methods to assess animal welfare on farm. A survey on calf rearing practices that might affect dairy calf welfare was performed via a 1-h interview on 115 dairy farms (mean +/- SD: herd size=52.5+/-20.9 cows; milk production=8,697+/-1,153L) distributed throughout the province of Quebec. Despite frequent recommendations, many dairy producers continue to use management practices that increase the health risks of milk-fed calves. Major risk factors for poor calf welfare identified were 1) no use of calving pen in 51.3% of herds and low level of surveillance of calvings, especially at nighttime (once every 12h), 2) no disinfection of newborn's navel in 36.8% of herds, and delayed identification and, hence, calf monitoring (3 d), 3) 15.6% of farms relied on the dam to provide colostrum and none checked colostrum quality or passive transfer of immunity, 4) dehorning and removal of extra teats proceeded at late ages (6.4 wk and 6.7 mo, respectively) and without adequate pain control, 5) use of traditional restrictive milk feeding and waste milk distributed to unweaned calves without precaution in 48.2% of herds, 6) abrupt weaning performed in 16.5% of herds, and 7) calves housed individually in 87.9% of herds, and most inappropriate housing systems (crate=27.0%, tie-stall=13.9%, attached against a wall=5.7%) remained. This risk factor assessment was the first step in an intervention strategy to improve calf welfare on dairy farms. more...

The reduction in milk production caused by subclinical mastitis in dairy cattle was assessed through the regression of test day milk yield on log-transformed somatic cell counts (LnSCC). Data was obtained from Valacta, Quebec, and a total of 312,756 test day records from Ayrshire cows and 1,869,785 test day records from Holstein cows were included in the analyses. A segmented regression was fitted to estimate the cutoff point in the LnSCC scale where milk yield starts to be affected by mastitis. The statistical model used to explain daily milk yield included the effects of herd–year-season of test (random), days in milk, age at calving and LnSCC, and analyses were performed by breed, parity and stage of lactation. The cutoff point where milk yield starts to be affected by changes in LnSCC was estimated from data to be around 2 (approximately 7400 cells/mL) for Canadian Ayrshires and Holsteins. Milk losses per unit increase in LnSCC varied from 0.55 to 0.84 kg/day in first lactation Ayrshires, from 0.33 to 0.55 kg/day in first lactation Holsteins, from 0.74 to 2.45 kg/day in adult Ayrshires and from 0.77 to 1.78 kg/day in adult Holsteins. Daily milk losses caused by changes in LnSCC were dependent on breed, parity and stage of lactation, and these factors should be considered when estimating losses associated with subclinical mastitis. more...

The objectives of this research were: (a) to perform a survey of current research in the area of multi-agent systems in order to learn more about how they could be designed and implemented; (b) to investigate the feasibility of such an approach for agriculture, based on an integration of currently existing technologies; and, more specifically (c) to assess the potential of a multi-agent approach in the context of decision support for dairy production. The results of this work highlighted a number of key concepts in multi-agent system design, including the importance of selecting an appropriate system architecture for agent coordination (e.g., peer-to-peer, federated, or blackboard-based) and the need for well-defined agent communication methods (language and ontology). Alternative technologies, used in the implementation of multi-agent systems (e.g., communication protocols and distributed computing methods), were also explored. Lastly, a case study was carried out, in which some of the discussed technologies were tested and implemented to create a multi-agent heifer management system. The system consists of two different types of agents and several databases, and was implemented on a PC-based network. The agents work together to synthesize data about heifer development from different sources and to present this to the user in a graphical format. The system demonstrates the feasibility of applying an agent-based approach, using currently available technology, to problems such as dairy herd management in which a distributed decision-support solution is often required. It is concluded that the constraints for the implementation of multi-agent systems do not appear to be of a technological nature; the challenge seems to be more one of defining and accepting a common ontology and communication language by members of a given industry. In addition, large-scale distributed systems will require sophisticated agent-coordination methods to ensure robust and efficient operation. more...

Machine-learning techniques are increasingly used to deal with a variety of problems in agriculture. However, challenges with the application of machine-learning, such as analyzing the performance achieved through learning from small data sets, still remain. This study focused on using graphical and statistical techniques to analyze the results of machine-learning experiments involving data preprocessing and algorithm tuning. Data consisted of 1428 cases that were classified by a dairy-nutrition specialist as outliers (34 cases) or non-outliers. The performance of classifiers, generated with decision-tree induction, was estimated through ten-fold cross validation. Relative operating characteristic (ROC) curves were used to visualize the achieved trade-offs between correctly classifying positive and negative cases. A performance index, representing the mean true positive rate of these curves for a limited range of false positive rate values, was developed to facilitate comparison among classification schemes. Analysis of variance (ANOVA) was used to determine whether real differences existed for the expected performance on new data among the different combinations of data preprocessing and algorithm configurations evaluated in this study. In terms of data preprocessing, randomly assigning herds to the folds of the cross validation did not perform significantly differently from assigning cases to folds, while using a special value to indicate irrelevant attribute values significantly improved the performance over treating these values as unknown. Tuning the configuration of the decision-tree induction algorithm significantly improved the classification performance. The application of ten-fold cross validation in combination with ROC curves and ANOVA was found to be useful in analyzing the results of machine-learning experiments involving decision-tree induction and small data sets. These methods could also be used with other machine-learning techniques such as artificial neural networks and instance-based learning. more...

Machine learning has been identified as a promising approach to knowledge-based system development. This study focused on the use of decision-tree induction for knowledge acquisition to filter individual-cow lactations for group-average lactation curve analysis. Data consisted of 1428 cases, classified by a dairy-nutrition specialist as outliers (34 cases) or non-outliers. The classification performance was estimated through 10-fold cross validation. A relative operating characteristic curve was used to visualize the achievable range of trade-offs between correctly classifying positive and negative cases. A series of three final decision trees with increasing tendency of classifying a lactation as outlier was induced from the entire data set. For these trees, the expected true positive rates were 52, 68 and 92%, at false positive rates of 1.5, 3.5 and 8.6%, respectively. However, due to the low prevalence of outlier lactations (cases), this performance was associated with many false positives. The performance of individual decision nodes was tested against the entire data set to identify potentially counter-intuitive nodes resulting from overspecialization to the training data. The specialist reviewed the final trees and adjusted two decision nodes. This study suggests that although the input from a domain specialist remains important, decision-tree induction is a useful technique to support knowledge acquisition involved in the removal of outlier lactations. more...

1) In a beechwood, male shoots of Mercurialis perennis were more frequent than female shoots in canopy openings, while females were more frequent at treebases than in canopy openings. 2) Flowering shoots were more frequent than non-flowering in openings. 3) The pH, moisture and organic content of the soil were similar at treebases and openings. The light climate was similar in both habitats in April but greater in the openings in August. 4) Removal of canopies of Pteridium aquilinum and Rubus fruticosus, above populations of M. perennis, resulted in a greater increase in the numbers of male shoots than of female shoots. 5) These results suggest that male and female plants differ in numbers, or growth, in different woodland microhabitats and that these differences are correlated with the above-ground environment (e.g. light). more...