The literature concerning the nutritional content of white clover as a grazed herbage or conserved crop offered to dairy cattle and aspects of frothy bloat are reviewed. In the first nine week change-over design experiment the effect on milk production and behaviour of spring calving dairy cows grazing white clover/grass swards at contrasting sward heights were examined. Grazing the clover/perennial ryegrass sward to a height of 4 cm increased clover content, but reduced milk production. The 8 cm sward increased milk yields by 15.8%. This was accompanied by an increase in fat and protein yields. Grazing time and biting rate were increased on the 4 cm sward. Cows offered choice between sward types produced intermediate milk production values. A second change-over design experiment conducted over 12 weeks examined milk production and behaviour of spring calving dairy cows in early lactation grazing perennial ryegrass or White clover/perennial ryegrass swards alone or offered a choice between the two sward types or grazed on clover/perennial ryegrass during the day and perennial ryegrass at night. The inclusion of clover in the diet of the dairy cows significantly increased milk production, but reduced fat content. Protein content, fat and protein yields were increased. Cows offered a choice or mixed day and night grazing regime produced similar results, which were intermediate between the clover/ryegrass and perennial ryegrass treatments. Grazing time was increased on clover/perennial ryegrass swards. This experiment also 1 demonstrated the ability of cows to adjust their grazing time to maximise herbage intake. The third experiment compared the value in relation to milk production of three different buffer forages fed to spring calving dairy cows in late lactation grazing either clover/ryegrass or ryegrass swards. The forages were ryegrass and ryegrass/clover silages and ryegrass hay. Milk yield and composition were not affected by forage type, but intakes were higher for grass silage for cows grazing clover/ryegrass swards and visa versa. Hay OM intake was low. The final experiment conducted over the first 15 weeks of the grazing season studied the effect of energy:protein concentration of strawmix supplements on the productivity of spring calving dairy cows grazing a high white clover sward. Milk yields were increased by the provision of a strawmix supplement. The energy:protein ratio had a significant effect on milk composition except fat content. The high energy:high protein supplement tended to precipitate ruminal tympany (bloat), while the low energy:high protein supplement tended to reduce ruminal tympany on this clover based sward. These experiments have given some insight into the use of clover and stimulated questions which require further investigation to enable the farmer to safely incorporate clover into dairy farming systems.

No description available.

The goal of this research was to explore the use of machine learning to assist in the development of knowledge-based systems (KBS) in dairy farming. A framework was first developed which described the various types of management and control activities in dairy farming and the types of information flows among these activities. This framework provided a basis for the creation of computerized information systems and helped to identify the analysis of group-average lactation curves as a promising area of application. A case-acquisition and decision-support system was developed to assist a domain specialist in generating example cases for machine learning. The specialist classified data from 33 herds enrolled with the Quebec dairy herd analysis service, resulting in 1428 lactations and 7684 tests of individual cows, classified as outlier or non-outlier, and 99 interpretations of group-average lactation curves. To enable the performance analysis of classifiers, generated with machine learning from these small data sets, a method was established involving cross-validation runs, relative operating characteristic curves, and analysis of variance. In experiments to filter lactations and tests, classification performance was significantly affected by preprocessing of examples, creation of additional attributes, choice of machine-learning algorithm, and algorithm configuration. For the filtering of individual tests, naive-Bayes classification showed significantly better performance than decision-tree induction. However, the specialist considered the decision trees as more transparent than the knowledge generated with naive Bayes. The creation of a series of three classifiers with increased sensitivity at the expense of reduced specificity per classification task, allows users of a final KBS to choose the desired tendency of classifying new cases as abnormal. For the main interpretation tasks, satisfactory performance was achieved. For the filtering tasks, performance was fai

Thesis (M. Com. (Agr.)) -- Lincoln University, 2009. / Also available via the World Wide Web.

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No description available.

Thesis (Ph. D.) -- Lincoln University, 2009. / Also available via the World Wide Web.

Thesis (M.S.)--Virginia Polytechnic Institute, 1962. / Also available via the Internet.

Thesis (Ed.D.) -- Teachers College, Columbia University, 1989. / Typescript; issued also on microfilm. Sponsor: Joan Gussow. Dissertation Committee: Isobel Contento. Bibliography: leaves 112-119.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1980. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.