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Mineralogy of Changa??e-4 landing site: preliminary results of visible and near-infrared imaging spectrometer
摘要： The exploration of ma?c anomaly in South Pole-Aitken (SPA, the largest con?rmed) basin on the Moon provides important insights into lunar interior. The landing of Chang’e-4 (CE-4) and deployment of Yutu-2 rover on the discontinuous ejecta from Finsen crater enabled in-situ measurements of the unusual mineralogy in the central portion of SPA basin with visible and near-infrared imaging spectrometer (VNIS). Here we present detailed processing procedures based on the level 2B data of CE-4 VNIS and preliminary mineralogical results at the exploration area of Yutu-2 rover. A systematic processing pipeline is developed to derive credible re?ectance spectra, based on which several spectral and mineral indices are calculated to constrain the ma?c mineralogy. The ma?c components in the soils and boulder around CE-4 landing site are concluded as clinopyroxene-bearing with intermediate composition and probably dominated by pigeonite although the possibility of mixing orthopyroxen (OPX) and calcic clinopyroxene (CPX) also exists. These mineralogical results are more consistent with a petrogenesis that the CE-4 regolith and rock fragment are derived from rapid-cooling magmatic systems and we interpret that the materials at the CE-4 landing site ejected from Finsen crater are probably recrystallized from impact melt settings.
关键词： Chang’e-4,the Moon,visible and near-infrared spectroscopy,mineralogy,impact melt
更新于2025-09-23 15:19:57
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Vis-NIR spectroscopy Combined with Wavelengths Selection by PSO Optimization Algorithm for Simultaneous Determination of Four Quality Parameters and Classification of Soy Sauce
摘要： The performance of Vis-NIR techniques combined with variable select by a simple modified particle swarm optimization (PSO) algorithm for the determination of four quality parameters in soy sauce was evaluated. Compared with full-spectral support vector machine regression (Full-SVMR) and SVMR based on competitive adaptive reweighted sampling (CARS-SVM) method, the application of PSO wavelength selection provided a notably improved SVM regression model. The root-mean-square error of amino acid nitrogen, salt, total acid content, and color ratio obtained by PSO-SVMR are 0.0075 g/100 ml, 0.2176 g/100 ml, 0.0077 g/100 ml, and 0.0506 in predicted sets, respectively. The correlation coefficients of predicted sets obtained by PSO-SVMR reached 0.9997, 0.9462, 0.9996, and 0.9998, respectively. Meanwhile, a classification study constructed with principal component analysis and SVM classification model based on the feature wavelengths selected by PSO shows that Vis-NIR spectra can be used to classify soy sauce according to their brands and quality. The result showed that the Vis-NIR spectroscopy technique based on PSO wavelength selection has high potential to predict the quality parameters in a nondestructive way. This analytical tool may also contribute to the detection of fraud and mislabeling in the soy sauce market and certainly contribute to improvement in quality and reliability of the soy sauce market.
关键词： Quality parameters,Wavelength selection,Modified particle swarm optimization algorithm,Visible and near-infrared spectroscopy,Soy sauce
更新于2025-09-09 09:28:46