Polarized Lidar Reflectance Measurements of Vegetation at Near-Infrared and Green Wavelengths

There is growing interest in the use of lidar for remote sensing of vegetation owing to the emergence of reliable and rugged lasers and highly sensitive detectors. Lidar remote sensing has a distinct advantage over conventional techniques in vegetation remote sensing due to its capability for three-dimensional characterization of vegetative targets. The Multiwavelength Airborne Polarimetric Lidar (MAPL) system was developed primarily for vegetation remote sensing applications from an airborne platform of up to 1,000 -m altitude. The lidar system has full waveform capture and polarimetric measurement capability at two wavelengths in the near-infrared (1064 nm) and the green (532 nm) spectral regions. This study presents preliminary ground-based lidar reflectance measurements on a variety of deciduous and coniferous trees under fully foliated conditions with a view towards tree species discrimination. Variations in the reflectance characteristics of selected deciduous trees under unfoliated and fully foliated conditions were also investigated. Our study reveals distinct differences in the reflectance characteristics of various trees.     

Maintenance of Soft Calibration Models in the Determination of Zinc,Cadmium, Lead and Copper by Differential Pulse Anodic Stripping Voltammetry

A strategy for constructing a global multivariate calibration model that includes calibration samples measured over time on different days is developed and applied in electroanalysis. Both synthetic and real samples (tap, extracted and river water) are analyzed by differential‐pulse anodic stripping voltammetry, showing the suitability of the global model constructed that provides successful results similar to those of the usual multivariate calibration. In addition the capability of discrimination of this model is evaluated in prediction for the mean of three replicates with estimation of probability of false noncompliance, α, and false compliance, β, being found 3.1, 11.2, 6.7 and 64.7 nM for nominal concentrations of zinc, cadmium, lead and copper of 96.0, 40.4, 37.3 and 328.0 nM respectively when α=β=0.05. It has been proven that the use of the global calibration does not imply a loss of multivariate analytical sensitivity, using this parameter as quality index of the analytical procedure. The viability of using calibration maintenance strategies with electroanalytical techniques is shown, providing a way to save time and experimental effort when these techniques are used in routine analysis.     

Stability of the FID sensitivity during an analysis in capillary GC

The sensitivity of an FID may change when the carrier gas flow rate changes during a chromatographic run. Sample parts which are eluted at reduced FID sensitivity produce a reduced peak area, hence are discriminated as compared to other components. Sensitivity changes were studied for hydrogen as carrier gas. For the detector tested, differences in the carrier gas flow rates of 1 ml/min shifted the FID sensitivity by 1 to 5% (depending on the fuel gas supply). Thus the stability of the sensitivity is no longer ensured as soon as the carrier gas flow rate is changed manually or by an automatic programmer during an analysis. Sensitivity drifts may also occur during temperature programmed runs with a pressure regulated carrier gas supply since the gas flow through the capillary drops with increasing temperature. Such shifts in the response became noticeable as soon as relatively high carrier gas flow rates combined with long range temperature programmes were used. The typical patterns of such discriminations are shown, closing with a discussion on the possibilities for minimizing such undesired effects.     

Optical metal-organic framework sensor for selective discrimination of some toxic metal ions in water

This paper reports the development of a facile and effective approach, based on the use of Zr-based metal-organic frameworks (UiO-66) sensor with micropores geometry, shape and particle morphology for the visual detection and removal of ultra-traces of some toxic metal ions such as Bi(III), Zn(II), Pb(II), Hg(II) and Cd(II). UiO-66 was used as selective carriers for accommodating hydrophobic chromophore probes such as dithizone (DZ) without coupling agent for sensitive and selective discrimination of trace level of toxic analytes. The developed UiO-66 sensor was utilized for the detection of ultra-traces of some toxic metal ions with the naked eye. The new sensor displays high sensitivity and selectivity of a wide range of detectable metals analytes up to 10⁻¹⁰ mol dm⁻³ in solution, in a rapid analyte uptake response (seconds). The developed sensor is stable, cost effective, easy to prepare, and would be useful for rapid detection and removal of ultra-traces of toxic metal ions in water samples.     

Genetic diversity and haplotype structure of 21 Y‐STRs,including nine noncore loci,in South Tunisian Population: Forensic relevance

Y chromosome STRs (Y‐STRs) are being used frequently in forensic laboratories. Previous studies of Y‐STR polymorphisms in different groups of the Tunisian population identified low levels of diversity and discrimination capacity (DC) using various commercial marker sets. This definitely limits the use of such systems for Y‐STRs genotyping in Tunisia. In our investigation on South Tunisia, 200 unrelated males were typed for the 12 conventional Y‐STRs included in the PowerPlex® Y System. Additional set of nine noncore Y‐STRs including DYS446, DYS456, DYS458, DYS388, DYS444, DYS445, DYS449, DYS710, and DYS464 markers were genotyped and evaluated for their potential in improving DC. Allele frequency, gene diversity, haplotype diversity (HD), and DC calculation revealed that DYS464 was the most diverse marker followed by DYS710 and DYS449 markers. The standard panel of 12 Y‐STRs (DC = 80.5%) and the nine markers were combined to obtain DC of 99%. Among the 198 different haplotypes observed, 196 haplotypes were unique (HD = 99.999). Out of the nine noncore set, six Y‐STRs (DYS458, DYS456, DYS449, DYS710, DYS444, and DYS464) had the greatest impact on enhancing DC. Our data provided putative Y‐STRs combination to be used for genetic and forensic applications.     

Method of gas mixtures discrimination based on sensor array, temporal response and data driven approach

This work presents a method of gas mixtures discrimination. The principal concept of the method is to apply measurement data provided by a combination of sensors at single time point of their temporal response as input of the discrimination models. The pattern data combinations are selected for classes of target gases based on the criterion of 100% efficient discrimination. Combinations of sensors and time points, which provide pattern data combinations in course or repeated measurements, are encoded in the form of addresses. The designer of sensor system is responsible for their selection and they are included in the software of the final instrument. The study of the method involved the discrimination of gas mixtures composed of air and single chemical: hexane, ethanol, acetone, ethyl acetate and toluene. Two sensor arrays were utilized. Each consisted of six TGS sensors of the same type. The dynamic operation of sensors was employed. As an example the stop-flow mode was chosen. The work provides the evidence of the existence of sensor combinations and time points, which are successful in discrimination of studied classes of target gases. The persistence of addresses was discussed considering the ability of sensor array to recognize analytes, variability of repeated measurement results, number of repeated measurements and a twin sets of sensors. Altogether, the validity of the method was demonstrated.     

Improving discrimination in data envelopment analysis: PCA–DEA or variable reduction

Within the data envelopment analysis context, problems of discrimination between efficient and inefficient decision-making units often arise, particularly if there are a relatively large number of variables with respect to observations. This paper applies Monte Carlo simulation to generalize and compare two discrimination improving methods; principal component analysis applied to data envelopment analysis (PCA–DEA) and variable reduction based on partial covariance (VR). Performance criteria are based on the percentage of observations incorrectly classified; efficient decision-making units mistakenly defined as inefficient and inefficient units defined as efficient. A trade-off was observed with both methods improving discrimination by reducing the probability of the latter error at the expense of a small increase in the probability of the former error. A comparison of the methodologies demonstrates that PCA–DEA provides a more powerful tool than VR with consistently more accurate results. PCA–DEA is applied to all basic DEA models and guidelines for its application are presented in order to minimize misclassification and prove particularly useful when analyzing relatively small datasets, removing the need for additional preference information.     

基于可见/近红外能量光谱的苹果褐腐病和水心鉴别

快速无损鉴别苹果内部品质的优劣是当前苹果行业亟待解决的一项重要课题.针对这一现状,提出了直接采用可见一近红外能量光谱对苹果褐腐病、水心鉴别的新方法,考察了不同判别分析方法对苹果类别判定的准确性.在能量光谱经MSC或者一阶导数处理后,分别采用了峰面积判别法(PADA)、主成分分析判别法(PCADA)、偏最小二乘判别法(PLSDA)建立判别模型.结果显示,三种方法对褐腐病苹果判别正确率都为100%;对水心苹果分别是79.2%,95.0%和96.7%;对正常苹果分别是88.6%,98.2%和98.8%.其中,PCADA和PLSDA明显优于PADA,而PLSDA总判别率最高,达到98.1%,其建模标准差RMSEC为0.449,预测标准差RMSEP为0.392,说明可见一近红外能量光谱结合化学计量学算法可以快速、无损鉴别苹果褐腐病和水心.     

UPLC-Q/TOF-MS coupled with multivariate analysis for comparative analysis of metabolomic in Dendrobium nobile from different growth altitudes

Dendrobium nobile alkaloids (DNLA) and glycosides are the main active components extracted from Dendrobium nobile Lindl. (D. nobile) used for thousands of years in China. The pharmacological effects of the above chemical components are significantly different. D. nobile is mainly grown at an altitude ranging from 230 to 800 m in Chishui City, Northwest Guizhou Province. However, it is unclear whether the metabolite in D. nobile is influenced by the planting altitude. Hence, to reveal the different metabolite in D. nobile cultivated at the altitude of 336 m, 528 m, and 692 m, ultra-high performance liquid chromatography with Q/TOF-MS couple with multivariate analysis were developed. Using the orthogonal partial least squares-discriminant analysis, 19 different metabolites were discovered and then tentatively assigned their structures as alkaloids and glycosides by comparing mass spectrometry data with in-house database and literature. Moreover, the result of semiquantitative analysis showed the content of dendrobine that was belonged to alkaloids significantly increased at the altitude of 692 m, whereas the content of glycosides demonstrated an accumulation trend at the altitude of 528 m. The results could provide valuable information for the optimal clinical drug therapeutics and provide a reference for quality control.     

Illuminating the flesh of bone identification – An application of near infrared spectroscopy

Near infrared (NIR) reflectance spectroscopy coupled with chemometric analysis was evaluated as a non-destructive tool to discriminate skull bone samples from different animal species. In total 70 skull bones from animals of three classes (mammalians, avian and reptiles) were scanned in the wavelength range between 950 to 1650 nm. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR spectra of the skull samples. Correct classification rates of 96% and 81% were obtained for the classification of skull bone samples according to avian and mammalian classes, respectively. Overall, a 91% correct classification rate was obtained for the classification of skull samples according to the class (mammalian and avian). This study demonstrates the potential of NIR spectroscopy coupled with chemometric as data processing, as a means of a rapid, non-destructive classification technique for skull bone samples.