Chemometrics

Abstract

T his Review, the nineteenth of this series, and the seventeenth with the title of "Chemometrics," covers the most significant developments in the field from December 2009 through October 2012. As in the previous review covering the period from January 2008 through December 2009, new developments in chemometrics across major fields including novel applications are selected, and recent trends within the field are addressed. 1 This Review is limited to 200 or less citations, so only the most noteworthy papers are cited, taking into account the purpose of covering the topics as well as possible. Space limitation restrict the potential for more comprehensive coverage of this subject, so authors should not feel slighted if they have not been cited. This is a challenging task for the reviewers as the number of citations and diversity of publications within the field of chemometrics has continued to increase rapidly during the past two decades. If one were to search for publications using the keywords multivariate data analysis or image analysis or astrophysical spectroscopic data analysis to broaden the perspective of applications of chemometrics, then the number of papers published during this review period listing each of these keywords would be in the tens of thousands. The fields of biophysics, basic engineering, and biomedical science include thousands of citations about chemometric-like data processing methods during this review period.There has been an increased use of multivariate methods across broad ranges of scientific disciplines, and multivariate analysis tools have become routine for most graduate, and even undergraduate, level scientific disciplines. In fact, undergraduate nursing students are now required to understand multivariate regression technique in such courses as Biomedical Statistics.

High-Throughput Fabrication and Screening Improves Gold Nanoparticle Chemiresistor Sensor Performance

“…A variety of chemometric statistical methods are subsequently used to determine the presence or absence of the analyte from the "fingerprint" of the response of the sensor arrays. 4 Chemiresistors based on organothiol-functionalized gold nanoparticle (Au NP ) thin films have been shown to be useful in different sensing areas both in the gas-phase 5−9 and the liquid-phase, 10−13 for applications ranging from environmental monitoring through to medical diagnostics. These types of chemiresistors consist of a Au NP film, which changes its resistance through the partitioning of analytes into the organothiol caps surrounding the nanoparticles thus changing the electron tunneling current between the metal nanoparticle cores.…”

Diversity of Maize Kernels from a Breeding Program for Protein Quality: II. Correlatively Expressed Functional Amino Acids

“…The low R 2 and Q 2 for LYS ( Fig. Statistically, the larger the Q 2 , the greater the probability of the model to predict new samples accurately (CAMO Inc., 2011); however, PLS regression models with low Q 2 may be of value for screening purposes (Mohammadi et al, 2003;Tallada et al, 2009;Lavine and Workman, 2013). Whether the full or reduced PLS models were used, the HG and endosperm texture had no effect on MET estimation (Fig.…”

Artificial Neural Networks (ANNs) for Spectral Interference Correction Using a Large-Size Spectrometer and ANN-Based Deep Learning for a Miniature One

“…○ Use of chemometrics methods [6][7][8][9][10][11][12][13][14][15], defined as those involving the "application of mathematical or statistical methods for the treatment of chemical data". Among others, examples of chemometrics approaches include adaptive filtering, factor analysis, orthogonal polynomials or curve fitting techniques.…”