Growth performance and nutrient utilization of catfish Clarias gariepinus fed varying inclusion level of fermented unsieved yellow maize

This study was conducted using 150 fish of Clarias gariepinus to investigate the growth performance and nutrient utilization of Clarias gariepinus fed five treatment diets containing varying inclusion level of fermented unsieved maize. The diets were grouped into CT, T1, T2, T3, and T4 with inclusion levels of 25%, 50%, 75%, and 100% of fermented unsieved maize respectively. Highest weight gain was recorded in T4 with value of 10.24 and lowest weight was recorded in CT with 9.17. High FCR were observed in T2 with value of 0.70 and lower value was observed in T4 with value of 0.62. While, T2, T3, and T4 have highest survival rates with values of 90% in each treatment CT and T1 recorded 80% and 70% respectively. There was a significant (p< 0.05) difference between the food conversion ratios treatment T4 with the best value and other treatments. There was a significant (p< 0.05) difference between the levels of fermented unsieved maize inclusion and the specific growth rate of the experimental fish. The highest value of protein level and feed efficiency were observed in T4 at significant difference level (p< 0.05) than other treatments. It was concluded that fermentation of maize in fish feed has positive effects on the nutritional value of the feed. It is recommend that fermented maize can replace raw maize in fish feed diet for growth performance. KEYWORDS: Fermentation, yellow maize, Clarias gariepinus, Fish, Feed.

Growth performance and nutrient utilization of catfish Clarias gariepinus fed varying inclusion level of fermented unsieved yellow maize

This study was conducted using 150 fish of Clarias gariepinus to investigate the growth performance and nutrient utilization of Clarias gariepinus fed five treatment diets containing varying inclusion level of fermented unsieved maize. The diets were grouped into CT, T1, T2, T3, and T4 with inclusion levels of 25%, 50%, 75%, and 100% of fermented unsieved maize respectively. Highest weight gain was recorded in T4 with value of 10.24 and lowest weight was recorded in CT with 9.17. High FCR were observed in T2 with value of 0.70 and lower value was observed in T4 with value of 0.62. While, T2, T3, and T4 have highest survival rates with values of 90% in each treatment CT and T1 recorded 80% and 70% respectively. There was a significant (p< 0.05) difference between the food conversion ratios treatment T4 with the best value and other treatments. There was a significant (p< 0.05) difference between the levels of fermented unsieved maize inclusion and the specific growth rate of the experimental fish. The highest value of protein level and feed efficiency were observed in T4 at significant difference level (p< 0.05) than other treatments. It was concluded that fermentation of maize in fish feed has positive effects on the nutritional value of the feed. It is recommend that fermented maize can replace raw maize in fish feed diet for growth performance.

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.