Canonical Correlation Analysis of Mid- and Near-Infrared Oil Spectra

1993 ◽  
Vol 47 (7) ◽  
pp. 1024-1029 ◽  
Author(s):  
M. F. Devaux ◽  
P. Robert ◽  
A. Qannari ◽  
M. Safar ◽  
E. Vigneau
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Principal Component ◽  
Canonical Variate ◽  
Mid Infrared ◽  
Highly Correlated ◽  
Spectral Patterns

A mathematical procedure based on Canonical Correlation Analysis (CCA) was used in order to assign the wavelengths of the near-infrared spectra through knowledge of the mid-infrared spectra. The relevance of the treatment was tested on commercial oils that mainly differ in their level of unsaturation. Initially, two separated Principal Component Analyses (PCAs) were performed on the near- and mid-infrared data to overcome the high intercorrelations across the wavelengths. CCA was then applied to the resulting principal components. Near- and mid-infrared canonical variates were assessed so that they achieved maximum correlation. The procedure makes it possible to draw CCA spectral patterns that exhibit significant positive and negative peaks. The first near-infrared canonical variate was highly correlated with the first mid-infrared canonical variate ( r2 = 0.97). The corresponding near- and mid-infrared CCA spectral patterns were therefore given the same interpretation. The mid-infrared pattern opposed negative peaks characteristic of CH2 groups to the positive peaks of CH3 and =CH groups. Consequently, in the near-infrared pattern, the positive peaks at 1708, 2140, 2170, and 2480 nm were assigned to CH3 or =CH groups, and the negative peaks at 2304, 2344, and 2445 nm were assigned to CH2 groups. A more precise interpretation was obtained by comparing the wavelengths observed to theoretical values and to previous assignments.

Mid and near Infrared Study of Carbohydrates by Canonical Correlation Analysis

1993 ◽  
Vol 1 (2) ◽  
pp. 99-108 ◽  
Author(s):  
P. Robert ◽  
M.F. Devaux ◽  
A. Qannari ◽  
M. Safar
Keyword(s):  
Correlation Analysis ◽  
Infrared Spectra ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Sugar Content ◽  
Infrared Region ◽  
Total Sugar ◽  
Mid Infrared ◽  
Total Sugar Content ◽  
Near Infrared Spectra

Multivariate data treatments were applied to mid and near infrared spectra of glucose, fructose and sucrose solutions in order to specify near infrared frequencies that characterise each carbohydrate. As a first step, the mid and near infrared regions were separately studied by performing Principal Component Analyses. While glucose, fructose and sucrose could be clearly identified on the similarity maps derived from the mid infrared spectra, only the total sugar content of the solutions was observed when using the near infrared region. Characteristic wavelengths of the total sugar content were found at 2118, 2270 and 2324 nm. In a second step, the mid and near infrared regions were jointly studied by a Canonical Correlation Analysis. As the assignments of frequencies are generally well known in the mid infrared region, it should be useful to study the relationships between the two infrared regions. Thus, the canonical patterns obtained from the near infrared spectra revealed wavelengths that characterised each carbohydrate. The OH and CH combination bands were observed at: 2088 and 2332 nm for glucose, 2134 and 2252 nm for fructose, 2058 and 2278 nm for sucrose. Although a precise assignment of the near infrared bands to chemical groups within the molecules was not possible, the present work showed that near infrared spectra of carbohydrates presented specific features.

scholarly journals Analysis of Soil-Vegetation Interrelationships in a South-Southern Secondary Forest of Nigeria

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
D. D. Eni ◽  
A. I. Iwara ◽  
R. A. Offiong
Keyword(s):  
Organic Matter ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
State Government ◽  
Canonical Correlation ◽  
Secondary Forest ◽  
Principal Component ◽  
Tree Density ◽  
Tree Size ◽  
Canonical Variate

Soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria were studied using principal component analysis (PCA) and canonical correlation analysis (CCA). The grid system of vegetation sampling was employed to randomly collect vegetation and soil data from fifteen quadrats of 10 m × 10 m. PCA result showed that exchangeable sodium, organic matter, cation exchange capacity, exchangeable calcium, and sand content were the major soil properties sustaining the regenerative capacity and luxuriant characteristics of the secondary forest, while tree size and tree density constituted the main vegetation parameters protecting and enriching the soil for its continuous support to the vegetation after decades of anthropogenic disturbance (food crop cultivation and illegal logging activities) before its acquisition and subsequent preservation by the Cross River State government in 2003. In addition, canonical correlation analysis showed result similar to PCA, as it indicated a pattern of relationship between soil and vegetation. The only retained canonical variate revealed a positive interrelationship between organic matter and tree size as well as an inverse relationship between organic matter and tree density. These extracted soil and vegetation variables are indeed significantly important in explaining soil-vegetation interrelationships in the highly regenerative secondary forest.

scholarly journals A Canonical Correlation Analysis of Relationships Between Growth, Compositional Traits and Longevity, Lifetime Productivity and Efficiency in Polish Landrace Sows

2014 ◽  
Vol 14 (2) ◽  
pp. 257-270 ◽  
Author(s):  
Magdalena Sobczyńska ◽  
Tadeusz Blicharski ◽  
Mirosław Tyra
Keyword(s):  
Growth Rate ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Performance Test ◽  
Selection Index ◽  
Phenotypic Selection ◽  
Backfat Thickness ◽  
Canonical Variate ◽  
Weaned Piglets

Abstract Relationships between performance test traits (growth rate, backfat thickness, loin depth, lean meat percentage, exterior, phenotypic selection index) and longevity traits (length of productive life, number of litters, total number of weaned pigs, number of weaned piglets per year, number of litters per year) in Landrace sows were evaluated using canonical correlation analysis. The data set consisted of 23,012 purebred sows that farrowed from 1994 to 2011 in 161 herds. The first three canonical correlations (0.37, 0.25, 0.07) were highly significant (P<0.0001). Correlations of the first canonical variate with the original measured variables indicated that sows with high values for this variate had lower growth rate (r=-0.31) and loin depth (r=-0.43), greater backfat thickness (r=0.23), as well as being older at birth of their last litter (r=0.98). These sows also had a greater number of litters (r=0.94) and better lifetime efficiency (r=0.61 and r=0.70 for number of weaned piglets per year and number of litters per year, respectively). Canonical loadings for the second canonical function indicate that sows with high values for the second set of variates had high growth rate (r=0.79) and phenotypic selection index (r=0.83), excellent conformation (r=0.62), as well as better efficiency in pig production (r=0.67). The squared multiple correlations show that the first canonical variate of the performance traits is a poor predictor of longevity (0.13) and nearly useless for predicting efficiency traits (0.07). Performance test traits explain 11% of the variance in the variables of longevity and lifetime productivity, whereas dependent variables explain only 3% of the variance in performance test traits. The relationships between performance test data and subsequent lifetime productivity or longevity were significant and unfavourable but low for Polish Landrace population

Improved calibration transfer between near-Infrared (NIR) spectrometers using canonical correlation analysis

2019 ◽  
Vol 52 (14) ◽  
pp. 2188-2202 ◽  
Author(s):  
Junxing Yang ◽  
Xiaoping Lou ◽  
Hongqi Yang ◽  
Huibing Yang ◽  
Chaoying Liu ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Near Infrared ◽  
Calibration Transfer

The Effect of Chain Length on Mid-Infrared and Near-Infrared Spectra of Aliphatic 1-Alcohols

2017 ◽  
Vol 72 (2) ◽  
pp. 288-296 ◽  
Author(s):  
Michał Kwaśniewicz ◽  
Mirosław A. Czarnecki
Keyword(s):  
Correlation Analysis ◽  
Chain Length ◽  
Near Infrared ◽  
Hydrophobic Interactions ◽  
Principal Component ◽  
Butyl Alcohol ◽  
Two Dimensional ◽  
Data Set ◽  
Mid Infrared ◽  
Spectral Changes

Effect of the chain length on mid-infrared (MIR) and near-infrared (NIR) spectra of aliphatic 1-alcohols from methanol to 1-decanol was examined in detail. Of particular interest were the spectra-structure correlations in the NIR region and the correlation between MIR and NIR spectra of 1-alcohols. An application of two-dimensional correlation analysis (2D-COS) and chemometric methods provided comprehensive information on spectral changes in the data set. Principal component analysis (PCA) and cluster analysis evidenced that the spectra of methanol, ethanol, and 1-propanol are noticeably different from the spectra of higher 1-alcohols. The similarity between the spectra increases with an increase in the chain length. Hence, the most similar are the spectra of 1-nonanol and 1-decanol. Two-dimensional hetero-correlation analysis is very helpful for identification of the origin of bands and may guide selection of the best spectral ranges for the chemometric analysis. As shown, normalization of the spectra pronounces the intensity changes in various spectral regions and provides information not accessible from the raw data. The spectra of alcohols cannot be represented as a sum of the CH3, CH2, and OH group spectra since the OH group is involved in the hydrogen bonding. As a result, the spectral changes of this group are nonlinear and its spectral profile cannot be properly resolved. Finally, this work provides a lot of evidence that the degree of self-association of 1-alcohols decreases with the increase in chain length because of the growing meaning of the hydrophobic interactions. For butyl alcohol and higher 1-alcohols the hydrophobic interactions are more important than the OH OH interactions. Therefore, methanol, ethanol, and 1-propanol have unlimited miscibility with water, whereas 1-butanol and higher 1-alcohols have limited miscibility with water.

scholarly journals Canonical correlation analysis of the career attitudes and strategies inventory and the adult career concerns inventory

2006 ◽  
Vol 32 (3) ◽  
Author(s):  
Charlene C Lew ◽  
Gideon P De Bruin
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Career Concerns ◽  
Canonical Variate ◽  
Career Attitudes ◽  
Family Commitment ◽  
Adult Career ◽  
Adult Career Concerns Inventory ◽  
High Level

This study investigated the relationships between the scales of the Adult Career Concerns Inventory (ACCI) and those of the Career Attitudes and Strategies Inventory (CASI). The scores of 202 South African adults for the two inventories were subjected to a canonical correlation analysis. Two canonical variates made statistically significant contributions to the explanation of the relationships between the two sets of variables. Inspection of the correlations of the original variables with the first canonical variate suggested that a high level of career concerns in general, as measured by the ACCI, is associated with high levels of career worries, more geographical barriers, a low risk-taking style and a non-dominant interpersonal style, as measured by the CASI. The second canonical variate suggested that concerns with career exploration and advancement of one’s career is associated with low job satisfaction, low family commitment, high work involvement, and a dominant style at work.

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