A spatial and temporal analysis of Texas bays and marine species
This thesis examines temporal trends and spatial differences in populations of several fish and invertebrates living in the Gulf of Mexico. Viscovery SOMine is used to analyze the relationship between populations and environmental factors, such as water temperature, salinity and oxygen concentration for different species and habitats.
Pixel clustering in spatial data mining; an example study with Kumeu wine region in New Zealand
437 888 pixels describing wine regions are identified on a GIS map of New Zealand. The pixels are then clustered with respect to corresponding geo-coded data for landscape, microclimate and soil properties using Viscovery SOMine. For detailed micro-scale analysis, the pixels belonging to Kumeu wine regions are selected and another self-organizing-map model is calculated and compared to the general model.
Modelling the seasonal climate effects on grapevine yield at different spatial and unconventional temporal scales
In this article, the connection between microclimate, grape yield and wine quality is investigated. Viscovery SOMine is used to cluster the different vintages according to quality and visualize the corresponding weather data. The self-organizing map results are compared to regression and discriminative analysis.
Metabolite profiling of spinach (Spinacia oleracea L.) leaves by altering the ratio of NH4+ / NO3- in the culture solution
The influence of different nitrogen suppliers on the metabolite profiles of spinach leaves is analyzed. A cluster analysis is conducted with Viscovery SOMine, ordering the 53 identified metabolites into six distinct clusters.
Differences in the Metabolite Profiles of Spinach (Spinacia oleracea L.) Leaf in Different Concentrations of Nitrate in the Culture Solution
Metabolite profiling using gas chromatography-mass spectrometry is used to evaluate the effect of nitrogen levels on spinach tissue, comparing two cultivars that differ in their ability to use nitrogen. Self-organizing-map (SOM) analysis using Viscovery SOMine is used to describe changes in the metabolites of mature spinach leaves. Both PCA and SOM reveal that metabolites are broadly divided into two types, correlating either positively or negatively with plant nitrogen content. The simple and co-coordinated metabolic stream, containing both general and spinach-specific aspects of plant nitrogen content, will be useful in future research on such topics as the detection of environmental effects on spinach through comprehensive metabolic profiling.
Use of neural networks to detect minor and major pathogens that cause bovine mastitis
Viscovery SOMine and a multi-layer perceptron are both used to detect bacterial pathogens in 4852 cow milk samples. The Viscovery model provides better agreement with results from conventional microbiological methods and may be used in future in-line milking systems to detect bovine mastitis at early stages.
Unlocking successful new rural industries: is supply chain management the key?
This report for the Rural Industries Research and Development Corporation (RIRDC) examines how chain supply management influences economic success in Australian agricultural industries. Viscovery SOMine is used to cluster fifteen supply chain cases from five different agricultural industries with respect to several different performance metrics, revealing three distinct groups of supply chain strategies.
Breeding Rubus cultivars for high anthocyanin content and high antioxidant capacity
Anthocyanin content and antioxidant activity from HortResearch Rubus clones are assessed, and a diverse range of anthocyanins and total anthocyanin content are reported. These data could be used to improve commercial production of high-health Rubus crops with significantly higher anthocyanin content and antioxidant capacity than found in existing cultivars.
Visualising spatial patterns in fruit quality and productivity of persimmon orchards using self organising maps
Fruit quality and productivity datasets obtained over two seasons from 24 New Zealand persimmon orchards are analyzed. Viscovery SOMine is used to construct a 2000 node self-organizing map (Kohonen, 1997) from input features (latitude, longitude, and growing region) obtained from each orchard replicate. By depicting fruit quality and tree productivity over the map, spatial patterns between orchards can be observed. In addition, climatic data from regional meteorological stations are associated with the map.