scholarly journals Visible + Near Infrared Spectroscopy as taxonomic tool for identifying birch species

Silva Fennica ◽  
2018 ◽  
Vol 52 (4) ◽  
Author(s):  
Mulualem Tigabu ◽  
Mostafa Farhadi ◽  
Lars-Göran Stener ◽  
Per Odén
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Absorption Bands ◽  
Orthogonal Projections ◽  
Projections To Latent Structures ◽  
Discriminant Models ◽  
Single Seeds ◽  
Latent Structures ◽  
Multivariate Discriminant

The genus L. is composed of several species, which are difficult to distinguish in the field on the basis of morphological traits. The aim of this study was to evaluate the taxonomic importance of using visible + near infrared (Vis + NIR) spectra of single seeds for differentiating Roth and Ehrh. Seeds from several families (controlled crossings of known parent trees) of each species were used and Vis + NIR reflectance spectra were obtained from single seeds. Multivariate discriminant models were developed by Orthogonal Projections to Latent Structures – Discriminant Analysis (OPLS-DA). The OPLS-DA model fitted on Vis + NIR spectra recognized with 100% classification accuracy while the prediction accuracy of class membership for was 99%. However, the discriminant models fitted on NIR spectra alone resulted in 100% classification accuracies for both species. Absorption bands accounted for distinguishing between birch species were attributed to differences in color and chemical composition, presumably polysaccharides, proteins and fatty acids, of the seeds. In conclusion, the results demonstrate the feasibility of NIR spectroscopy as taxonomic tool for classification of species that have morphological resemblance.BetulaBetula pendulaBetula pubescensB. pubescensB. pendula

Application of near-infrared spectroscopy for the detection of internal insect infestation inPiceaabiesseed lots

2004 ◽  
Vol 34 (1) ◽  
pp. 76-84 ◽  
Author(s):  
Mulualem Tigabu ◽  
Per Christer Odén ◽  
Tong Yun Shen
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Least Squares Regression ◽  
Absorption Bands ◽  
Classification Rate ◽  
Data Set ◽  
Storage Lipids ◽  
Nir Absorption ◽  
Seed Origin ◽  
Single Seeds

The use of near-infrared (NIR) spectroscopy to discriminate between uninfested seeds of Picea abies (L.) Karst and seeds infested with Plemeliella abietina Seitn (Hymenoptera, Torymidae) larva is sensitive to seed origin and year of collection. Five seed lots collected during different years from Sweden, Finland, and Belarus were used in this study. Initially, seeds were classified as infested or uninfested with X-radiography, and then, NIR spectra from single seeds were collected with a NIR spectrometer from 1100 to 2498 nm with a resolution of 2 nm. Discriminant models were derived by partial least squares regression using raw and orthogonal signal corrected spectra (OSC). The resulting OSC model developed on a pooled data set was more robust than the raw model and resulted in 100% classification accuracy. Once irrelevant spectral variations were removed by using OSC pretreatment, single-lot calibration models resulted in similar classification rates for the new samples irrespective of origin and year of collection. Dis criminant analyses performed with selected NIR absorption bands also gave nearly 100% classification rate for new samples. The origin of spectral differences between infested and uninfested seeds was attributed to storage lipids and proteins that were completely depleted in the former by the feeding larva.

Discrimination of Storage Duration of Apples Stored in a Cooled Room and Shelf-Life by Visible-Near Infrared Spectroscopy

2007 ◽  
Vol 15 (3) ◽  
pp. 169-177 ◽  
Author(s):  
C. Camps ◽  
P. Guillermin ◽  
J.C. Mauget ◽  
D. Bertrand
Keyword(s):  
Spectral Data ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Absorption Bands ◽  
Storage Duration ◽  
Data Set ◽  
Global Models ◽  
Duration Of Storage ◽  
Apple Cultivars

Improved non-destructive instrumental approaches for grading fruit during post-harvest could be an efficient way to monitor stock in the apple industry. The objective of this study was to evaluate the ability of visible-near infrared (vis-NIR) spectroscopy in reflectance mode for classifying apples left on the shelf or stored in a cooled room. The ability of NIR spectroscopy to classify the duration of storage of three apple cultivars in two storage modalities was evaluated. A total of 450 fruit, sampled after 7, 14, 28, 60, 90 and 120 days of storage in a cooled room (CR) and 7, 14 and 28 days in shelflife (SL), has been studied. The classification of these modalities was analysed by factorial discriminant analysis (FDA) pooling the spectral data of all cultivars (global models) into a common data set. Then, the cultivar effect on the classification of the same modalities was analysed by processing data from each cultivar in separate factorial descriminant analyses. A preliminary analysis showed the genetic variability of spectral data due to the three apple cultivars. We show that vis-NIR spectroscopy allowed the correct classification of the fruits of each cultivar by more than 95%. The classification relied on both vis and NIR absorption bands: 500, 680, 1400 to 1700, 1850, 1950, 2200 and 2300 nm. We show that storage modalities of global models can be classified by more than 75% and 83% for fruits stored in a cooled room and shelf, respectively. Classification of the same storage modalities was improved by cultivar models with percentage of individuals correctly classified of 86% (Gala), 89% (Elstar) and 85% (Smoothee) for fruits stored in a cooled room and 95% (Gala), 98% (Elstar) and 95% (Smoothee) for fruits left in shelflife. We conclude that despite the slight increase of efficiency of the models when we considered each apple cultivar separately, global models applicable to a set of different cultivars presents a correct level of classification and could be usefull for some commercial applications.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

Brachyspira Species Avidity to Colonic Mucins from Pigs with and without Brachyspira hyodysenteriae Infection is Species-Specific and Varies between Strains

2021 ◽  
Author(s):  
Macarena P. Quintana-Hayashi ◽  
Mattias Erhardsson ◽  
Maxime Mahu ◽  
Vignesh Venkatakrishnan ◽  
Freddy Haesebrouck ◽  
...  
Keyword(s):  
Sialic Acid ◽  
Hierarchical Cluster ◽  
Swine Industry ◽  
Binding Ability ◽  
Orthogonal Projections ◽  
Brachyspira Hyodysenteriae ◽  
Projections To Latent Structures ◽  
Latent Structures ◽  
Species Specific

Brachyspira hyodysenteriae is commonly associated with swine dysentery (SD), a disease that has an economic impact in the swine industry. B. hyodysenteriae infection results in changes to the colonic mucus niche with a massive mucus induction, which substantially increases the amount of B. hyodysenteriae binding sites in the mucus. We have previously determined that a B. hyodysenteriae strain binds to colon mucins in a manner that differs between pigs and mucin types. Here, we investigated if adhesion to mucins is a trait observed across a broad set of B. hyodysenteriae strains and isolates and furthermore at a genus level ( B. innocens, B. pilosicoli, B. murdochii, B. hampsonii and B. intermedia strains). Our results show that binding to mucins appears to be specific to B. hyodysenteriae , and within this species, the binding ability to mucins varies between strains/isolates, increases to mucins from pigs with SD, and is associated to sialic acid epitopes on mucins. Infection with B. hyodysenteriae strain 8dII results in mucin glycosylation changes in the colon including a shift in sialic acid containing structures. Thus, we demonstrate through hierarchical cluster analysis and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) models of the relative abundances of sialic acid-containing glycans, that sialic acid containing structures in the mucin O -glycome are good predictors of B. hyodysenteriae strain 8dII infection in pigs. The results emphasize the role of sialic acids in governing B. hyodysenteriae interactions with its host, which may open perspectives for therapeutic strategies.

scholarly journals Comparative Inner Morphological and Chemical Studies on Reynoutria Species in Korea

Plants ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 222
Author(s):  
Atif Ali Khan Khalil ◽  
Kazi-Marjahan Akter ◽  
Hye-Jin Kim ◽  
Woo Sung Park ◽  
Dong-Min Kang ◽  
...  
Keyword(s):  
High Performance ◽  
Spectroscopic Studies ◽  
Array Detector ◽  
Vascular Bundles ◽  
Orthogonal Projections ◽  
Flowering Season ◽  
Projections To Latent Structures ◽  
Chemical Profiles ◽  
Chemical Studies ◽  
Latent Structures

Reynoutria species are medicinal plants that belong to the family Polygonaceae and are widely distributed in eastern Asia, North America and Europe. Although the phylogeny and morphological and anatomical studies of some species in Korea have been previously reported, there are no discriminative anatomical and chemical data available. Therefore, anatomical characterization of the leaf, stem and root, and high performance liquid chromatography–diode array detector (HPLC–DAD) analyses were carried out to assess the differences in anatomical and chemical profiles among the Reynoutria plants in Korea, i.e., R. japonica, R. sachalinensis, R. forbesii and R. japonica for. elata. The anatomical evaluation showed discriminative characteristics, such as the shape of the stomata and the stomatal index of the lower leaf surface; the ratio of the adaxial/abaxial height, the size of the vascular bundles and the frequency of druse in the midrib, petiole, and stem; and the pericycle number in the root. For the HPLC analysis, ten compounds corresponding to each major peak were isolated from R. japonica roots and their structures were identified by comprehensive spectroscopic studies. Samples collected before the flowering season showed higher contents of these ten major compounds than those collected after the flowering season. The orthogonal projections to latent structures-discrimination analysis (OPLS-DA) with the inner morphological and HPLC quantification results, clearly discriminated these plants. These results provide anatomical parameters and HPLC profiling that can be used to distinguish the four Reynoutria plants, which supports quality control for their precise identification.

Classification of Chinese Soybean Paste by Fourier Transform Near-Infrared (FT-NIR) Spectroscopy and Different Supervised Pattern Recognition

2011 ◽  
Vol 5 (4) ◽  
pp. 928-934 ◽  
Author(s):  
Hui Jiang ◽  
Guohai Liu ◽  
Xiahong Xiao ◽  
Shuang Yu ◽  
Congli Mei ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Fourier Transform ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Soybean Paste

Estimation of Wood Stiffness and Strength Properties of Hybrid Larch by Near-Infrared Spectroscopy

2007 ◽  
Vol 61 (8) ◽  
pp. 882-888 ◽  
Author(s):  
Takaaki Fujimoto ◽  
Hiroyuki Yamamoto ◽  
Satoru Tsuchikawa
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Strength Properties ◽  
Density Variation ◽  
Modulus Of Rupture ◽  
Cellulose Content ◽  
Hybrid Larch ◽  
Absorption Bands ◽  
Wood Stiffness ◽  
Predicted Values

This work was undertaken to investigate the feasibility of near-infrared (NIR) spectroscopy for estimating wood mechanical properties, i.e., modulus of elasticity (MOE) and modulus of rupture (MOR) in bending tests. Two sample sets having large and limited density variation were prepared to examine the effects of wood density on estimation of MOE and MOR by the NIR technique. Partial least squares (PLS) analysis was employed and it was found that the relationships between laboratory-measured and NIR-predicted values were good in the case of sample sets having large density variation. MOE could be estimated even when density variation in the sample set was limited. It was concluded that absorption bands due to the OH group in the semi-crystalline or crystalline regions of cellulose strongly influenced the calibrations for bending stiffness of hybrid larch. This was also suggested from the result that both α-cellulose content and cellulose crystallinity showed moderate positive correlation to wood stiffness.

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