Climate change impact and potential adaptation strategies under alternate climate scenarios for yam production in the sub-humid savannah zone of West Africa

Globally, yam (Dioscorea spp.) is the fifth most important root crop after sweet potatoes (Ipomoea batatas L.) and the second most important crop in Africa in terms of production after cassava (Manihot esculenta L.) and has long been vital to food security in sub-Saharan Africa (SSA). Climate change is expected to have its most severe impact on crops in food insecure regions, yet very little is known about impact of climate change on yam productivity. Therefore, we try estimating the effect of climate change on the yam (variety: Florido) yield and evaluating different adaptation strategies to mitigate its effect. Three regional climate models REgional MOdel (REMO), Swedish Meteorological and Hydrological Institute Regional Climate Model (SMHIRCA), and Hadley Regional Model (HADRM3P) were coupled to a crop growth simulation model namely Environmental Policy Integrated Climate (EPIC) version 3060 to simulate current and future yam yields in the Upper Ouémé basin (Benin Republic). For the future, substantial yield decreases were estimated varying according to the climate scenario. We explored the advantages of specific adaptation strategies suggesting that changing sowing date may be ineffective in counteracting adverse climatic effects. Late maturing cultivars could be effective in offsetting the adverse impacts. Whereas, by coupling irrigation and fertilizer application with late maturing cultivars, highest increase in the yam productivity could be realized which accounted up to 49 % depending upon the projection of the scenarios analyzed.     

Diversity of gastropods at Pudhumadam coast region and unusual occurrence of Tetraclita rubescens on conus shell

The marine environment is continuously subjected to chemical pollution, which may exert a detrimental effect on aquatic organisms. Biodiversity of marine invertebrates has been proven to be difficult to assess accurately using traditional morphological methods. Major problems include dearth of characters in many taxa. Hence, it is necessary to assess the eco-health of this marine invertebrate using reliable measurements of environmental quality as required in the present study. With the backdrop of information, the Pudhumadam coastal area was surveyed for the diversity of ruined/washed out gastropods species. As a competitor for space with gastropods, these barnacles settle on the conus for its food and habitat. In our study, the occurrence of acorn barnacles was observed on gastropod shells. The pink adult and many white small barnacles were noted on the shells. If these barnacles increase their habitat this may lead to destruction of diversity of gastropods.     

Study of the effect of refinery waste water exposure on Allium cepa's enzymatic antioxidant defense: probing potential biomarkers

The effects of heavy metals, hydrocarbons, and various toxicants present in Mathura Refinery Waste Water (MRWW) on Allium cepa were examined as a model plant system. The study was based on exposure of A. cepa to different concentrations of MRWW and compared to untreated control (exposure of onion bulbs with aquaguard purified water) to determine the total protein content and activities of certain antioxidant enzymes. These enzymes were evaluated for their efficacy to serve as biomarkers of refinery waste water pollution. DNA damaging potential of MRWW was also investigated. Data demonstrated maximal enhancement in ascorbate peroxidase activity subsequent to MRWW insult, although a significant increase in activities was also noted for other enzymes in the following order: superoxide dismutase?>?glutathione-S-transferase?> catalase. This is suggestive of their potency as a biomarker of MRWW toxicity. Increase in activities of monodehydroascorbate reductase (MDHAR; 152%) and deoxyribonuclease (345%) were also found in the A. cepa system as a result of MRWW exposure. In conclusion, A. cepa system might thus serve as an appropriate tool for monitoring water pollution, especially produced by petroleum waste and heavy metals in term of induction of glutathione peroxidase, MDHAR, and deoxyribonuclease activity.     

Experimental investigation of solar still with opaque north triangular face

Developing a compact, simple, and productive solar still is a main challenge. This paper describes a simple modification of the solar still that significantly enhances its productivity. A laboratory scale of modified single effect double slope glass solar still with the opaque triangular north wall has been developed and tested for enhancement of productivity in sunny days of the summer season in the month of April. The experiments on still have been carried out under three levels of water depths from 1 to 3 cm and compared it with the performance of conventional still of double slope single effect solar still of the same size. It is clear from the observations that opaque type still gave maximum distillate of 1793 ml at 1 cm depth of water while conventional still could produce only 1519 ml for the same depth of water. Also, for 2 and 3 cm depth of water, the opaque type still found to be more productive than conventional double slope solar still. As the former produced 1532 and 1464 ml while the latter produced 1328 and 1235 ml, for 2 and 3 cm depth of water, respectively.     

Applying artificial neural network methodology to ocean color remote sensing

Artificial neural networks (ANN) are widely used as continuous models to fit non-linear transfer functions. In this study we used ANN to retrieve chlorophyll pigments in the near-surface of oceans from Ocean Color measurements. This bio-optical inversion is established by analyzing concomitant sun-light spectral reflectances over the ocean surface and pigment concentration. The relationships are complex, non-linear, and their biological nature implies a significant variability. Moreover, the sun-light reflectances are usually measured by satellite radiometers flying at 800 km over the ocean surface, which affect the data by adding radiometric noise and atmospheric correction errors. By comparison with the polynomial fit usually employed to treat this problem, we show the advantages of neural function approximation like the association of non-linear complexity and noise filtering.