Profile of the illegal abalone (<i>Haliotis midae</i>) fishery in the Eastern Cape, South Africa: organised pillage and management failure

Since 1997 the Eastern Cape of South Africa has become a major source of supply for the illicit abalone trade as illegal fishers have located a substantial abalone (Haliotis midae) resource. We determined illegal fishing effort and yield in the Port Elizabeth-based abalone fishery, and used biological indices to determine the impact of fishing on the abalone stock. The failure of the state to issue fishing rights and conduct effective sea-based compliance, combined with the incentives to fish abalone (high price, low cost, ease of access) created the conditions for a full scale illegal fishery to emerge very rapidly. By 2005, the scale of the fishery was remarkable: a fleet of 30 purpose built vessels existed, harvesting 1000–2000 tons of abalone with an export value of 35–70 million USD per year. The uncontrolled fishing effort had a dramatic effect on the stock: the average size of abalone decreased significantly, densities declined in the sampling areas, but recruitment of young abalone was still observed at the heavily fished Cape Recife site. It is concluded that the illegal fishing operations and the resultant ecological effects on the abalone resource, reflect deficiencies in South Africa's current abalone fisheries management and compliance paradigm

Investigation of fungal development in maize kernels using NIR hyperspectral imaging and multivariate data analysis

Near infrared (NIR) hyperspectral imaging and hyperspectral image analysis were evaluated for their potential to track changes in fungal contamination on and fungal activity immediately under the surface of whole maize kernels (Zea mays L.) infected with Fusarium verticillioides. Hyperspectral images of clean and infected kernels were acquired using a SisuChema hyperspectral pushbroom imaging system with a spectral range of 1000-2498 nm at predetermined time intervals after infection. Background, bad pixels and shading of acquired absorbance images were removed using exploratory principal component analysis (PCA). When plotting PC4 against PC5, with percentage sum of squares (%SS) 0.49% and 0.34%, three distinct clusters were apparent in the score plot and this was associated with degree of infection. Loading line plots, with prominent peaks at 1900 nm and 2136 nm, confirmed that the source of variation was due to changes in starch and protein. Partial least squares (PLS) regression models, with time as the Y variable, were calculated and also indicated that changes over time were apparent. Variable importance plots (VIP) confirmed the peaks observed in the PCA loading line plots. More systematic future experiments are needed to confirm this, but it can already be concluded that early detection of fungal contamination and activity is possible. © 2012 Elsevier Ltd