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In recent years, the evaluation of the impact of production over time has become very useful for agricultural enterprises, as it is a useful tool for decision making and the design of strategies to achieve maximum efficiency and productivity (Rodríguez et al. 2015). The Statistical Model of Impact Measuring (SMIM) of Torres et al. (2008), used in Cuba (Martínez et al. 2012, Torres et al. 2013 and Rodríguez et al. 2014) and in the international sphere (Ruiz et al. 2012, Chivangulula et al.2014, Vargas et al. 2015 and Benítez et al. 2016), allows identifying those variables that most contribute to the variability of a system and indicate the changes that occur in the different productive units.
The application of this model to rabbits farms can be very useful, since reproductive traits are the most important in these farms to determine their productivity. Many are the studies that have characterized the performance of these traits in the different breeds, but the impact or the importance of the variables in each of breeds in a rabbit farm is not known. Therefore, the objective of this study is to evaluate the impact of some reproductive indicators through this methodology and to typify the performance of three of the breeds in the rabbit genetic unit from Mayabeque province.
Materials and Methods
The study was carried out with the reproductive information of the daily movement of the herd of a rabbit genetic farm from Mayabeque province, belonging to the Empresa de Ganado Menor (EGAME), corresponding to the years 2012-2013 and 2015-2016, and to the breeds White New Zealand, Cuban Brown and White Semigiant. Based on this daily information, the monthly average for each year and breed was determined, with the help of PROC SUMMARY of the statistical package SAS, version 9.3 of 2013.
The information matrix was made up of 144 observations. In the rows were placed the four years, twelve months and the three breeds, while in the columns were placed the variables under study, which were the number of live born per day (No./day), number of dead born per day (No./day), number of matings made per day (No./day) and number of kindlings per day (No./day). The final data matrix corresponded to one of order (144 x 5).
To identify the variables and indicators that define the fundamental changes in rabbit productivity, the Statistical Model of Impact Measuring (SMIM) of Torres et al. (2008 and 2013), which also allows the classification of the performance of breeds in this unit. It was considered as a criterion that the Eigen value was equal to or higher than one.
Results and Discussion
The application of the model identified correlations higher than 0.40 between the variables number of live and dead born per day and between the breed with the number of live and dead born per day. The correlation between the number of live born per day and dead born per day is antagonistic (-0.51), as expected, since the more live born there are, the fewer deaths there will be per day. However, the breed had a high but negative correlation (-0.44) with respect to the number of young rabbit born alive per day, but positive (0.60) in relation to the number of young rabbits that died per day.
They were identified, from the criterion of presenting Eigen values higher than the unit, two main components that determine the reproductive efficiency of the rabbit farm (table 1) and explain 58 % of the total variability. The most important component and which varies the most is the first (number of young rabbits born) with 34.4 % of the cumulative variance, which explains the fitted model, while the second (number of reproductive events that occur per day) contributes with 24.1 % of variability. This corresponds to the fact that the amount of young rabbits born is a determining factor in rabbit productivity.
The variables that composed each component were selected from weight factors higher than 0.65. The first is made up of the indicators number of live and dead born per day and breed. Of these relative variables, the number of dead born per day is the highest weight factor (0.85). The second is composed of the number of mating and kindlings per day, in which the variable with the higher relative weight (0.82) is the number of kindlings that occur in a day.
The fact that only 58 % of the variability is explained is due to that there are other causes of variation that are not considered in the analysis, such as the quality and quantity of the food supplied to the animals, the conditions of the cages and the maternal ability, among others that affect the performance of these reproductive indicators. The impacts or changes associated with the performance of these variables that explain the highest variance (table 1) are shown in figures 1 and 2. In this case, the breeds in the years and months studied, represented on the x axis, obtain an evaluation for each component in a values scale that shows its relative situation with respect to the rest, which are represented in the y axis by bars.
It can be seen in figure 1 that, for component one (number of young rabbits born), the White Semigiant breed has a different pattern from that of the other two breeds under study, even though they are all in the same farm where environmental conditions are the same (food, climate, medication), but the management varies according to the technician experience of the building where each breed is raised.
Figure 1 Impact indexes of the number of young rabbits born in the years 2012-2013 and 2015-2016 in the rabbit genetic farm from Mayabeque province.
If it is take into consideration the high correlation found between the breed and the number of young rabbits dead per days, variable of higher weight for the first factor, it can be inferred that the positive impacts (0 to 2.5) reached by this breed are due to a higher amount of young rabbits dead in this breed with respect to the others.
For component two (figure 2) it was found that the impact index is very changeable for each breed, valued according to the month and the year. Although in general, the year 2013 showed positive values for the three breeds between 0 and 1.5, for the number of reproductive events, while in 2016 the impact was negative (0 to -2.5). This is due to the fact that during 2013 there was stability in the supply of feed in granules form and a composition close to the requirements of the species, mainly in fiber and protein (11 and 12%, respectively). In 2016, the quality of the food was poor, with less than 10 % of fiber, little forage supply and different formulations, all in meal form.
Figure 2 Impact indexes of the number of reproductive events occurred in the years 2012-2013 and 2015-2016 in the rabbit genetic farm from Mayabeque province. White New Zealand - Cuban Brown - White Semigiant
De Blas and Nicodemus (2001) point out that when there is a nutritional deficit and a semi-intensive reproductive system is used (mating 11 d postpartum, and weaning at 35 d of age of young rabbits), such as the one used in this rabbit genetic farm, the recovery period of breeders is short, their body condition considerably deteriorates and the deficiencies in the quality of food do not allow to cover the high nutritional requirements of the breeders. Therefore, its reproductive efficiency decreases.
The classification technique, according to the results obtained for the estimated impacts of the breed, years and months studied, allowed to identify two groups of breeds per month and year. The first (I) is made up of 80 individuals, 47 from Cuban Brown and 33 from White New Zealand, while the second (II) grouped, fundamentally, the White Semigiant breed (48 individuals), in addition to 15 from White New Zealand and one of the Cuban Brown (table 2).
This classification shows that the three breeds studied, the White Semigiant that basically forms the group II, presents the lower number young rabbits born per day and therefore, the highest number of young rabbits born dead, variable of higher weight for the first factor. This confirms the inference previously made from the impact indexes obtained for this breed in the different years and analyzed months.
This reveals that the performance of this breed for the studied variables has less similarity with that of the White New Zealand and Brown Cuban, so in this breed a review of the reproductive management must be made and take the necessary measures to reduce the amount of dead born per day and therefore, increase the number of live born per day, indicators that determine the productivity of a rabbit farm.
The results obtained in this study are not comparable with others reported in the scientific literature, as it is the first time that this model has been used in rabbit. Although it has been applied in the species bovine (Chacón 2009, Vargas et al. 2011), buffalo (Prieto et al. 2015) and pigs (Chivangulula et al.2013), its purpose was not to determine and typify changes in the performance of breeds for reproductive indica- tors.
Although the SMIM had not been used before in rabbit species, its usefulness was demonstrated in the evaluation of the impact of some reproductive indicators (number of dead born and the number of kindlings per day) and in the typification of the performance of three of the breeds from the rabbit genetic farmn Mayabeque province, so it can be used by managers in decision making. However, a similar study is recommended, but with a higher number of variables and quantity of information to offer a better characterization of the performance of the different breeds in one or more rabbit genetic farm.
