Fluorescence spectra of apple juice were recorded with a view to evaluating the information content in relation to picking date of the apples and possible correlation to traditional harvest indices. The data analysis was performed by using chemometric methods (PCA, PLS, SIMCA). It was shown that the fluorescence spectra correlated with the content of soluble solids in the apple juice and the two apple varieties could be correctly classified by their spectra. Keywords: Apple maturity; chemometrics; fluorescence spectroscopy; multivariate analysis

An analytical method is described for the extraction of metsulfuron-methyl from soil at sub-parts per billion levels (LOQ = 0.2 microgram kg(-1)). The herbicide was quantitatively determined and identified by ESI LC/MS/MS. The method has been applied to a field dissipation study in which metsulfuron-methyl was applied to spring barley at three dosage rates: 4, 8, and 16 g of active ingredient ha(-)(1). The results of 2 years are presented. The dissipation rate of metsulfuron-methyl in topsoil was very rapid, with a calculated half-life of 6.5 days. Laboratory mineralization studies with native soils in contrast to autoclaved soils indicated that microbial degradation of (14)C-labeled metsulfuron-methyl and (14)C-labeled 2-amino-4-methoxy-6-methyl-1,3,5-triazine in soil microcosms is an important factor for the complete degradation of metsulfuron-methyl in the field. However, the mineralization rate of the sulfonamide was much higher.

Dose-response models are intensively used in herbicide bioassays. Despite recent advancements in the development of new herbicides, statistical analyses are commonly based on asymptotic approximations that are sometimes poor. This paper presents the use of recent results in higher order asymptotics for likelihood-based inference in nonlinear regression. The methods presented provide accurate approximation for the distribution of test statistics and for prediction limits. Analyses of the fit and measures of detection limits of the bioassays are considered, and the potential of the methods is illustrated by examples with real data.

Because of the increasing presence of scientific publications on the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research on techniques and methods for retrieval of scientific Web publications is called for. In this article, we report on the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based on specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AllTheWeb, and AltaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AltaVista and AllTheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.

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