Assessment of relationships between precipitation and satellite derived vegetation condition in South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

Particle formation during soy protein precipitation

The current success of soy foods is driving soy ingredient manufacturers to develop innovative products for food manufacturers. One such innovation is separating the soy proteins glycinin and beta-conglycinin to take advantage of their individual functional and nutritional properties. Precipitation by acidification is a low-cost method for separating these two proteins. Separation is achieved by preferentially precipitating glycinin at pH ~ 6 while beta-conglycinin remains in solution. Understanding the particle formation during protein precipitation is important as it can influence the efficiency of the precipitation process as well as subsequent downstream processes such as the particle-liquid separation step, usually achieved by centrifugation. Most of the previous soy protein precipitation studies are limited to precipitation at pH 4 as this is the pH range most commonly used in the commercial manufacturing of soy protein isolates. To date, there have been no studies on the particle formation during precipitation at pH > 5.Precipitation of soy protein is generally thought to occur by the rapid formation of primary particles in the size range of 0.1 - 0.3 microns followed by aggregation of these particles via collision to aggregates of size about 1 - 50 microns. The formation of the primary particles occurs on a time scale much shorter than that of the overall precipitation process (Nelson and Glatz, 1985). This study shows that precipitation of soy protein is indeed rapid. At high pH levels, binary liquid-liquid separation occurs forming a protein-rich heavy phase. The protein-rich phase appears as droplets which can be coalesced to form a uniform bulk layer under centrifugation forces. Upon lowering the pH level by the addition of acid, further protein is precipitated as amorphous material which binds the droplets together to form aggregates of amorphous precipitates. Liquid-liquid separation has been observed in many protein solutions but this phenomenon has only scarcely been reported in the literature for soy proteins. It presents an exciting opportunity for an innovative product. Features of the liquid-phase protein such as protein yield and purity will be characterized.