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Kaesberg, A. -K. U.; Louton, H.; Erhard, M.; Schmidt, P.; Zepp, M.; Helmer, F. and Schwarzer, A. (2018): Development of a prognostic tool for the occurrence of feather pecking and cannibalism in laying hens. In: Poultry Science, Vol. 97, No. 3: pp. 820-833

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In July 2015, a German voluntary decree stipulated that the keeping of beak-trimmed laying hens after the 1st of January 2017 will no longer be permitted. Simultaneously, the present project was initiated to validate a newly developed prognostic tool for laying hen farmers to forecast, at the beginning of a laying period, the probability of future problems with feather pecking and cannibalism in their flock. For this purpose, we used a computer-based prognostic tool in form of a questionnaire that was easy and quick to complete and facilitated comparisons of different flocks. It contained various possible risk factors that were classified into 3 score categories (1 = "no need for action," 2 = "intermediate need for action," 3 = "instant need for action"). For the validation of this tool, 43 flocks of 41 farms were examined twice, at the beginning of the laying period (around the 20th wk of life) and around the 67th wk of life. At both visits, the designated investigators filled out the questionnaire and assessed the plumage condition and the skin lesions (as indicators of occurrence of feather pecking and cannibalism) of 50 laying hens of each flock. The average prognostic score of the first visit was compared with the existence of feather pecking and cannibalism in each flock at the end of the laying period. The results showed that the prognostic score was negatively correlated with the plumage score (r =-0.32;95% confidence interval [CI]: [-0.56;-0.02]) and positively correlated with the skin lesion score (r = 0.38;95% CI: [0.09;0.61]). These relationships demonstrate that a better prognostic score was associated with a better plumage and skin lesion score. After performing a principal component analysis on the single scores, we found that only 6 components are sufficient to obtain highly sensitive and specific prognostic results. Thus, the data of this analysis should be used for creating applicable software for use on laying hen farms.

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