Early agricultural pathways: moving outside the 'core area' hypothesis in Southwest Asia. (73/95)

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Stress wave signal denoising using ensemble empirical mode decomposition and an instantaneous half period model. (74/95)

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Big hitting collectors make massive and disproportionate contribution to the discovery of plant species. (75/95)

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Natural history and information overload: The case of Linnaeus. (76/95)

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RNA interference can rebalance the nitrogen sink of maize seeds without losing hard endosperm. (77/95)

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Herbarium specimens, photographs, and field observations show Philadelphia area plants are responding to climate change. (78/95)

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Probability of identification: a statistical model for the validation of qualitative botanical identification methods. (79/95)

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.  (+info)

The Gatsby Plant Science Summer School: inspiring the next generation of plant science researchers. (80/95)

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