Abstract

This study was carried out to predict average number of kits per birth and mortality number of non-descript rabbits in Plateau State, Nigeria using artificial neural network (ANN). Data were obtained from a total of 100 rabbit farmers. The predicted mean value for number of kits per birth using ANN (6.60) was similar to the observed value (6.52). As regards mortality, the predicted mean value using ANN (17.75) was also similar to the observed value (17.80). Primary occupation, experience in rabbit keeping, flock size and credit type were the parameters of utmost importance in predicting number of kits per birth. The fairly high coefficient of determination (R2) (55.7%) and low root mean square error (RMSE) value of 1.22 conferred reliability on the ANN model. The R2 value obtained in the prediction of mortality using ANN implies that 61.1% of the variation in the number of mortality can be largely explained by the explanatory variables such as flock size, age of farmers, experience in rabbit keeping and average number of kits per birth. The low RMSE value of 3.82 also gave credence to the regression model. The present information may be exploited in taking appropriate management decisions to boost production.

Highlights

  • The need for rabbits (Oryctolagus cuniculus) and attention given to rabbit production in the agricultural sector in Nigeria is growing high with respect to the increase in demand for animal protein (Amaefule, Iheukwumere, & Nwaokoro, 2005; Yakubu & Adua, 2010; Oseni, & Lukefahr, 2014) and as experimental animals (Ansa, Akpere, & Imasuen, 2017; Oloruntoba, Ayodele, Adeyeye, & Agbede, 2018).)

  • Experience in rabbit keeping, flock size and credit type were the variables of utmost importance in predicting litter size

  • The R2 value obtained in the prediction of average number of kits using artificial neural network (ANN) implies that 55.7% of the variation in average number of kits can be explained by the explanatory variables especially primary occupation, experience in rabbit keeping, flock size and credit type (Figure 2)

Read more

Summary

Introduction

The need for rabbits (Oryctolagus cuniculus) and attention given to rabbit production in the agricultural sector in Nigeria is growing high with respect to the increase in demand for animal protein (Amaefule, Iheukwumere, & Nwaokoro, 2005; Yakubu & Adua, 2010; Oseni, & Lukefahr, 2014) and as experimental animals (Ansa, Akpere, & Imasuen, 2017; Oloruntoba, Ayodele, Adeyeye, & Agbede, 2018).). There is need to identify associated factors so as to devise appropriate means to improve on rabbit productivity and profitability. In this context, the use of appropriate modelling techniques will facilitate understanding of such underlying factors

Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.