Effect of Stocking Density and Rearing Facility on Growth and Profitability of Tilapia rendalli Fry
A study was conducted to compare the growth potential of Tilapia rendalli at three different stocking densities, using different rearing facilities. T. rendalli fry of 0.9±0.1g average weight were stocked in tanks and hapa-in-ponds at the stocking density of 30, 60 and 90 fry/m 3 . Locally made feed (CP-18%) was administered at 5% body weight three times a day for three months. Monthly sampling was conducted to assess growth by measuring weight and length for specific growth rate (SGR), average daily gain (ADG), weight gain (WG), and biomass (BM). The results of the study showed a significantly higher (P 0.05) as well as within the stocking densities (P > 0.05). The results of this study have a significant contribution towards stocking densities as well as rearing facilities used by hatchery operators. It is recommended that hapas mounted in pond fry rearing for T. rendalli fingerling production is most ideal. The results of the present study suggested that production of good quality fingerlings at stocking densities of 30 fry/m 3 must be adopted in the culture of T. rendalli as fish grows faster than the other stocking densities of 60 and 90 fry/m 3 as demonstrated in this study.
Genetic evaluation of four strains of Oreochromis shiranus for harvest body weight in a diallel cross
Abstract Estimates of strain additive genetic, total heterosis and general reciprocal effects were obtained from a complete diallel cross with four strains (Shire, Nkhotakota, Chilwa and Chiuta) of Oreochromis shiranus in Malawi. Growth was recorded at harvest on 367 individually tagged progeny from 16 strain combinations after a grow-out period of 180 days across three test environments that represented different agro-climatic zones of the country. Each of the 16 strain combinations was produced from 3 to 5 five single-pair matings; i.e., 6–10 parents per strain combination. In total, the number of contributing sires per strain ranged from 14 to 16 and the number of contributing dams also from 14 to16. Across the test environments, the mean body weight was 75 g and the males had a significantly higher body weight at harvest than the females (23%; P P  > 0.05) meaning that with respect to the harvest body weight trait, there is no need to develop specific strains for the different agro-climatic conditions of the country. The strain total heterosis effect accounted for 15.3% ( P P P  > 0.05) effects. For the strain additive genetic effect, Shire was the best and Chiuta the poorest strain, performing 16.9% above and 10.3% below the mean of the purebred strains, respectively. Five out of the six strain crosses showed a significant positive total heterosis effect ranging from 12.3% to 17.0% above the mean body weight of the purebred strains. The average heterosis effect was 12.5%. The correlation between the strain additive genetic and the strain additive genetic plus total heterosis performance of the six strain crosses was low ( r  = 0.25). The results show that for harvest body weight there are substantial additive genetic and total heterosis differences among pure and crossbred strains of O. shiranus . The exploitation of these genetic differences in a breeding program is discussed.
Mining Words in the Minds of Second Language Learners: Learner-Specific Word Difficulty
While there have been many studies on measuring the size of learners’ vocabulary or the vocabulary they should learn, there have been few studies on what kind of words learners actually know. Therefore, we investigated theoretically and practically important models for predicting second language learners’ vocabulary and propose another model for this vocabulary prediction task. With the current models, the same word difficulty measure is shared by all learners. This is unrealistic because some learners have special interests. A learner interested in music may know special music-related terms regardless of their difficulty. To solve this problem, our model can define a learner-specific word difficulty measure. Our model is also an extension of these current models in the sense that these models are special cases of our model. In a qualitative evaluation, we defined a measure for how learner-specific a word is. Interestingly, the word with the highest learner-specificity was “twitter”. Although “twitter” is a difficult English word, some low-ability learners presumably knew this word through the famous micro-blogging service. Our qualitative evaluation successfully extracted such interesting and suggestive examples. Our model achieved an accuracy competitive with the current models.