Assessment of feeds and feeding techniques adoption in Ijebu Ode zone of Ogun State Agricultural Development Programme, Nigeria

The study was conducted to assess the feeds and feeding techniques adopted in fish farming in the six extension blocks of Ijebu-Ode zone of the Ogun State Agricultural Development Programme, South Western Nigeria. The areas covered are Ala, Ago-Iwoye, Isonyin, Ijebu-Igbo, Ijebu-Ife and Ibi-Ade. Primary data were obtained from ninety fish farmers with well structed interview guides while combination of purposive and convenience sampling procedure was used in selecting the fish farmers. The result obtained showed that majority (34%) of the respondent fell within the economic active age distribution of 40-49 years, male (87%) married (90%:Christian 73.3%), tertiary education (47.7%), farming experience (54.4%), membership of cooperative society (63.3%),household size of above five (55.6%), annual income of above N51,000 (94.4%) and 34.4% of the respondents sourced their finance from personal saving. Most of the fish farmers adopted use of concrete tanks, intensive and semi-intensive culture system, culture Clarias and Heterobranchus species, produced about two tons per culture circle of six months. Majority (61.1%) of the respondents combine use of supplementary feed because of readily available desired feed.Recommendations are availability of credit and subsidies facilities, accessibility feed supplies, farmers’ cooperative, enabling government policies and farmers training and extension service provision

Effect of rainfall pattern on fish production in Ogun State, Nigeria

The role of water in fish production could not be overemphasized. This is because water is required for the total functioning of fishes. This study therefore examined the relationship/effect of rainfall pattern on fish production. Secondary data were collected on mean annual rainfall and total annual fish output for the period of 10 years (2000-2009). The study showed that high rainfall was recorded in the year 2001 which marked the lowest fish production year due to floods effect on fish enclosures. These therefore implies that fish farmers should be encouraged to construct ponds with protective measures such as screens, dykes, freeboards, etc. which prevents total loss of stocks during heavy rainfall

Efficiency of different traps for silver catfish fishery and its aquaculture implications in the face of climate change

Climate change has the potential to severely impact coastal and inland environments and ecosystems, and by extension fisheries and aquaculture. Coastal regions of the world are already experiencing flooding due to rise in sea level. In recent times, salinization of coastal areas due to flooding from storm surges and high tidal influence has been observed. Aquaculture is a fast growing agri-business venture in Nigeria presently and many coastal communities derive their livelihood from it. The culture of freshwater fish species that are very sensitive to high salinity may be threatened leading to mortality of stocked fish and loss of livelihood for coastal population. Consequently, there is urgent need for development and domestication of the Silver catfish, Chrysichthys nigrodigitatus that can tolerate higher salinity more than Mudcatfish (Clarias gariepinus). This will help mitigate the impact of salinization of coastal areas arising from sea water flooding on culture of fresh water fish species

Physical, chemical and sensory properties of cassava (Manihot esculenta) – sweet potato (Ipomoea batatas) gari

Open Access JournalIntroduction. Food safety is one of the problems facing sub-Sahara African countries like Nigeria. The use of wholesome indigenous crops and improved methods of production of major foods is a way forward. Materials and methods. A factorial research design was used to obtain eight samples of cassava and sweet potato gari from three modifications of the traditional production method for gari. Effects of these methods on the physical, chemical and sensory properties of the gari were evaluated using standard methods. Results and discussion. The results revealed that the inclusion of sweet potato significantly (p<0.05) influenced the proximate composition of the cassava-sweet potato gari and the values are also within the recommended levels for quality gari. Moisture content ranged from 10.10 to 12.30%, crude fibre 1.93 to 1.98%, ash content 1.13 to 1.31%, protein content 1.43 to 4.29%, and carbohydrate content 78.11 – 83.59%. The cyanide contents ranged from 0.58 to 2.16 mg/100 g, with 100% cassava gari having the highest while 100% sweet potato gari recorded the lowest. A decrease in porosity from 40 ± 2 % for the 100% cassava gari to 27.33 ± 2 % for sweet-potato gari was observed. The particle size of the sweet potato gari had the highest angle of repose of 38° while 100% cassava gari recorded the lowest angle of repose (29°). The swelling index of the samples ranged from 330 to 450% and100% sweet potato gari had the highest loose and packed densities. The sensory evaluation results showed that the cassava sweet potato (10%) gari was rated the best for colour (8.07), texture (7.67), and aroma (6.87), while 100% cassava gari had highest value for taste (7.47), and both shared the highest value (7.60) in overall acceptability. Conclusions. The study showed that 10% sweet potato can traditionally be added to cassava for quality gari production

An end-to-end convolutional selective autoencoder approach to Soybean Cyst Nematode eggs detection

This paper proposes a novel selective autoencoder approach within the framework of deep convolutional networks. The crux of the idea is to train a deep convolutional autoencoder to suppress undesired parts of an image frame while allowing the desired parts resulting in efficient object detection. The efficacy of the framework is demonstrated on a critical plant science problem. In the United States, approximately $1 billion is lost per annum due to a nematode infection on soybean plants. Currently, plant-pathologists rely on labor-intensive and time-consuming identification of Soybean Cyst Nematode (SCN) eggs in soil samples via manual microscopy. The proposed framework attempts to significantly expedite the process by using a series of manually labeled microscopic images for training followed by automated high-throughput egg detection. The problem is particularly difficult due to the presence of a large population of non-egg particles (disturbances) in the image frames that are very similar to SCN eggs in shape, pose and illumination. Therefore, the selective autoencoder is trained to learn unique features related to the invariant shapes and sizes of the SCN eggs without handcrafting. After that, a composite non-maximum suppression and differencing is applied at the post-processing stage.Comment: A 10 pages, 8 figures International Conference on Machine Leaning(ICML) Submissio