Application of the Statistical Model of Impact Measuring (SMIM) to evaluate reproductive indicators in a rabbit farm

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Yoleisy García
V. Torres
Raquel Ponce de León
Marta Mora

Abstract

In order to evaluate the impact of some reproductive indicators of the White New Zealand, Cuban Brown and White Semigiant breeds in the years 2012-2013 and 2015-2016, information on the daily movement of the herd was used. The data matrix was constituted by 144 observations and five variables (144 x 5). The variables under study were: number of born alive and dead, mating and kindlings, per day. With the application of the Statistical Model of Impact Measurring (SMIM), two components that determine the reproductive efficiency, the number of young rabbits, formed by the live and dead born and the breed were identified, while the number
of reproductive events constituted the mating and kindlings per day, results that allowed typifying the performance of the three breeds. For component one, the White Semigiant showed a different pattern to that of the other two breeds, with positive impact indexes (0 to 2.5). In general, the impact on component two, for the three breeds races, showed positive values (0 to 1.5) in 2013 and negative (0 to -2.5) in 2016. The classification technique identified two groups, the first represented by 47 from Cuban Brown and 33 from White New Zealand, while the second grouped, fundamentally, the White Semigiant (48 individuals). The usefulness of this model was showed in the evaluation of the impact of reproductive indicators and the typification of three breeds performance, which can be applied in decision making.
Key words: rabbits, breeds, reproductive efficiency, main components

Article Details

How to Cite
García, Y., Torres, V., Ponce de León, R., & Mora, M. (2018). Application of the Statistical Model of Impact Measuring (SMIM) to evaluate reproductive indicators in a rabbit farm. Cuban Journal of Agricultural Science, 52(1). Retrieved from https://cjascience.com/index.php/CJAS/article/view/785
Section
Biomathematics

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