No abstract

A research aimed at evaluating the reproductive performance of pigs as influenced by breed, season, and parity was carried out. Reproductive performance records of 1383 sows made up of 204 primiparous and 1179 multiparous large white (687) and Duroc × large white crosses (696) obtained over a 3-year period (2013 to 2016) were used. Data on reproductive performance taken were farrowing rate, litter size at birth and at weaning, piglet weight at birth and at weaning farrowing interval and pre-weaning mortality. To determine the effect of season, parity and breed on reproductive performance, the 4-way analysis of variance (ANOVA) was used. A mixed model was fitted using the generalized linear model (GLM) procedure of the GenStat (Discovery Edition) to investigate the fixed effects of breed (two classes), season of birth (three classes) and parity (five classes) on the reproductive traits. Where differences in means were observed, the means were separated using the least significant difference at 5% level of significance. Results obtained indicated litter size at birth of 12.5 ± 0.3 and 14.2 ± 0.5 for the large white and the Duroc × large white respectively and farrowing rates of 90.0 ± 2.3 and 94.5 ± 2.5% for the large white and the Duroc × large white respectively. Litter size at birth and at weaning, farrowing rate and piglet weight at birth were all influenced by parity and season with increasing parity significantly reducing litter size at birth and at weaning. Reproductive traits of the sows were superior during the rainy season, an indication of the need to consider season of birth in making decision.

No abstract

No abstract

The agricultural sector remains the major source of livelihood for rural communities in Nigeria. But the sector is faced with challenges of changes in climate. These continuous changes have adversely affected rural farmers who are dependent on rainfall for farming and livelihood as evident in low precipitation and drought. The continuous changes in pattern of climate have necessitated adaptation to its impact. A study was therefore conducted to estimate the factors influencing rural farmers' adaptation decision to the effects of climate change. Multistage sampling technique was employed to select the representative farmers