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Marshall, T. T., Hoover, T. S., Reiling, B. A., & Downs, K. M. (1998). Experiential learning in the animal sciences: effect of 13 years of a beef cattle management practicum. J. Anim Sci., 76(11), 2947–2952.
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Davis, S. L., & Cheeke, P. R. (1998). Do domestic animals have minds and the ability to think? A provisional sample of opinions on the question. J. Anim Sci., 76(8), 2072–2079.
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Schiffman, S. S. (1998). Livestock odors: implications for human health and well-being. J. Anim Sci., 76(5), 1343–1355.
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Swanson, J. C. (1999). What are animal science departments doing to address contemporary issues? J. Anim Sci., 77(2), 354–360.
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Hopster, H., van der Werf, J. T., Erkens, J. H., & Blokhuis, H. J. (1999). Effects of repeated jugular puncture on plasma cortisol concentrations in loose-housed dairy cows. J Anim. Sci, 77(3), 708–714.
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Lanier, J. L., Grandin, T., Green, R. D., Avery, D., & McGee, K. (2000). The relationship between reaction to sudden, intermittent movements and sounds and temperament. J. Anim Sci., 78(6), 1467–1474.
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Olesen, I., Groen, A. F., & Gjerde, B. (2000). Definition of animal breeding goals for sustainable production systems. J. Anim Sci., 78(3), 570–582.
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Marc, M., Parvizi, N., Ellendorff, F., Kallweit, E., & Elsaesser, F. (2000). Plasma cortisol and ACTH concentrations in the warmblood horse in response to a standardized treadmill exercise test as physiological markers for evaluation of training status. J. Anim Sci., 78(7), 1936–1946.
Abstract: Reliable physiological markers for performance evaluation in sport horses are missing. To determine the diagnostic value of plasma ACTH and cortisol measurements in the warmblood horse, 10 initially 3-yr-old geldings of the Hannovarian breed were either exposed to a training schedule or served as controls. During experimental Phase 1, horses were group-housed, and half of the horses were trained for 20 wk on a high-speed treadmill. During Phase 2, groups were switched and one group was trained for 10 wk as during Phase 1, whereas the control group was confined to boxes. During Phase 3 horses were initially schooled for riding. Thereafter, all horses were regularly schooled for dressage and jumping, and half of the horses received an additional endurance training for 24 wk. During all phases horses were exposed at regular intervals to various standardized treadmill exercise tests. During and after the tests frequent blood samples were taken from an indwelling jugular catheter for determination of ACTH and cortisol. Treadmill exercise increased both hormones. Maximum ACTH concentrations were recorded at the end of exercise, and maximum cortisol levels were recorded 20 to 30 min later. Except for one test there were no differences in ACTH levels between trained horses and controls. There was no significant effect of training on the cortisol response (net increase) to treadmill exercise in any of the tests during Phase 1. During Phase 2 higher cortisol responses were recorded in controls than in trained horses (P < .05) after 10 wk of training (controls confined to boxes). During Phase 3 plasma cortisol responses were also higher in controls than in trained horses (P < .05 after 6, 18, and 24, P < or = .07 after 12 wk of training) when the inclination of the treadmill was 5%, but not at 3%. There was no overlap in net cortisol responses at 30 min between trained and untrained horses. An ACTH application after 24 wk of training resulted in higher cortisol responses in controls than in trained horses (P < or = .05), without any overlap between the groups at 30 min after ACTH. Plasma cortisol responses to either treadmill exercise or ACTH injection may be a reliable physiological marker for performance evaluation. Prerequisites are sufficient differences in training status and sufficient intensity of exercise test conditions.
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Kimura, R. (2001). Volatile substances in feces, urine and urine-marked feces of feral horses. Can. J. Anim. Sci., 81(3), 411–420.
Abstract: The identity and amount of volatile substances in the feces, urine and feces scent-marked with urine (i.e., feces mixed with urine) of feral horses was determined by acid/steam distillation and gas chromatography-mass spectrometry. The frequency of excretion and scent marking, as evaluated in the breeding and non-breeding seasons, showed clear evidence of seasonal behavioral differences. The concentration of each substance (fatty acids, alcohols, aldehydes, phenols, amines and alkanes) in the feces differed according to maturity, sex and stage in the reproductive process. They had a characteristic chemical fingerprint. Although the levels of tetradecanoic and hexadecanoic acids in the feces of estrous mares were significantly higher than the respective levels in the feces of non-estrous mares, in the case of scent-marked feces by stallions, the levels of them in the feces from estrous mares had decreased to levels similar to those in non-estrous mares. The concentration of these substances in mares were not significantly different. The presence of a high concentration of cresols in the urine of stallions in the breeding season suggests that one role of scent marking by stallions is masking the odor of the feces produced by mares.
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Bracke, M. B. M., Spruijt, B. M., Metz, J. H. M., & Schouten, W. G. P. (2002). Decision support system for overall welfare assessment in pregnant sows A: Model structure and weighting procedure. J. Anim Sci., 80(7), 1819–1834.
Abstract: The problem of how to objectively assess the overall welfare status of animals under farming conditions has contributed to an ongoing debate that has hampered actual decision making on animal welfare. For this reason we constructed a model based on the assumed hierarchical organization of the animals' needs for overall welfare assessment in the case of pregnant sows. This model is implemented in a computer-based decision support system that takes a description of a housing and management system as input and produces a welfare score as output. A formalized procedure was used to construct the model for welfare assessment in pregnant sows on the basis of available scientific knowledge. This SOWEL (from SOw WELfare) model contains 37 attributes that describe the welfare-relevant properties of housing and management systems. In the decision support system these attributes are linked to scientific statements and a list of needs to provide a scientific basis for welfare assessment. Weighting factors that represent the relative importance of the attributes are derived from the scientific statements about the various welfare performance criteria that have been measured by scientists. The welfare score is calculated as the weighted average score. All information in the decision support system is stored in tables in a relational database such that newly available knowledge and insights can be incorporated to refine the model. The model has been developed in line with several existing models but it differs from these models in that it is the first to provide a formalized procedure to explicate the reasoning steps involved in welfare assessment based on available scientific knowledge. N1 -
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