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The pls package implements principal component regression (PCR) and partial least squares regression (PLSR) in R (R Development Core Team 2006b), and is freely available from the Comprehensive R Archive Network (CRAN), licensed under the GNU General Public License (GPL). The user interface is modelled after the traditional formula interface, as exemplified(More)
This study investigated the relation between vegetation reflectance and elevated concentrations of the metals Ni, Cd, Cu, Zn and Pb in river floodplain soils. High-resolution vegetation reflectance spectra in the visible to near-infrared (400-1350 nm) were obtained using a field radiometer. The relations were evaluated using simple linear regression in(More)
Density-based clustering algorithms for multivariate data often have difficulties with high-dimensional data and clusters of very different densities. A new density-based clustering algorithm, called KNNCLUST, is presented in this paper that is able to tackle these situations. It is based on the combination of nonparametric k-nearest-neighbor (KNN) and(More)
Seedless grapes are greatly appreciated for fresh and dry fruit consumption. Parthenocarpy and stenospermocarpy have been described as the main phenomena responsible for seedlessness in Vitis vinifera. However, the key genes underpinning molecular and cellular processes that play a significant role in seed development are not well characterized. To identify(More)
Untargeted metabolomics are rapidly becoming an important tool for studying complex biological samples. Gas chromatography-mass spectrometry (GC-MS) is the most widely used analytical technology for metabolomic analysis of compounds that are volatile or can be chemically derivatised into volatile compounds. Unfortunately, data processing and analysis are(More)
During the past decades, large amounts of diffuse cadmium (Cd) and zinc (Zn) contaminated soil material have been deposited in the floodplains of the river Rhine in the Netherlands. As spatial information on soil quality is required at different scale levels covering the whole area, characterisation exclusively based on soil sampling and analysis is(More)
The rapid increase in the size of data sets makes clustering all the more important to capture and summarize the information, at the same time making clustering more difficult to accomplish. If model-based clustering is applied directly to a large data set, it can be too slow for practical application. A simple and common approach is to first cluster a(More)
This paper outlines a procedure that quantifies the impact of different sources of spatial variability and uncertainty on ecological risk estimates. The procedure is illustrated in a case study that estimates the risks of cadmium for a little owl (Athene noctua vidalli) living in a Dutch river flood plain along the river Rhine. A geographical information(More)