Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition

Basati, Zahra; Jamshidi, Bahareh; Rasekh, Mansour; Abbaspour‐Gilandeh, Yousef

doi:10.1016/j.saa.2018.05.123

Cited by 56 publications

(24 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The technique is an advanced selective method designed to reduce the number of variables used for modeling, minimize collinearity from each wavelength number position (Liu & He, 2009), and improve the conditioning of multiple linear regression by minimizing collinearity effects in the calibration data set (Sun et al, 2019). The above optimization algorithms could remove the spectral regions with large noise and irrelative information and enhanced the predictive ability of modeling (Basati, Jamshidi, Rasekh, & Abbaspour‐Gilandeh, 2018; Li & Su, 2018).…”

Section: Methodsmentioning

confidence: 99%

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics

Huang

Ren

Sun

et al. 2020

Food Science & Nutrition

View full text Add to dashboard Cite

The evaluation of Chinese dianhong black tea (CDBT) grades was an important indicator to ensure its quality. A handheld spectroscopy system combined with chemometrics was utilized to assess CDBT from eight grades. Both variables selection methods, namely genetic algorithm (GA) and successive projections algorithm (SPA), were employed to acquire the feature variables of each sample spectrum. A partial least‐squares discriminant analysis (PLS‐DA) and support vector machine (SVM) algorithms were applied for the establishment of the grading discrimination models based on near‐infrared spectroscopy (NIRS). Comparisons of the portable and benchtop NIRS systems were implemented to obtain the optimal discriminant models. Experimental results showed that GA‐SVM models by the handheld sensors yielded the best predictive performance with the correct discriminant rate (CDR) of 98.75% and 100% in the training set and prediction set, respectively. This study demonstrated that the handheld system combined with a suitable chemometric and feature information selection method could successfully be used for the rapid and efficient discrimination of CDBT rankings. It was promising to establish a specific economical portable NIRS sensor for in situ quality assurance of CDBT grades.

show abstract

Section: Methodsmentioning

confidence: 99%

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics

Huang

Ren

Sun

et al. 2020

Food Science & Nutrition

View full text Add to dashboard Cite

show abstract

“…Ward's algorithm and the squared Euclidian distance were used to generate a dendrogram for analysis of the clustering trend. 28,29…”

Section: Methodsmentioning

confidence: 99%

Rapid identification of Lactobacillus species using near infrared spectral features of bacterial colonies

Shi

Zhang

et al. 2019

Journal of Near Infrared Spectroscopy

View full text Add to dashboard Cite

The feasibility of rapid identification of Lactobacillus species using near-infrared spectral features coupled with chemometrics was investigated. First, bacterial colonies of 11 Lactobacillus strains covering four species ( Lactobacillus casei, Lactobacillus reuteri, Lactobacillus brevis, and Lactobacillus fermentum) were cultured using the spread-plate technique. Near-infrared spectra data of the Lactobacillus species were collected directly from the bacterial colonies. Second, 10 wavenumbers were selected from the near-infrared spectra data using uninformative variables elimination and genetic algorithm, and calibration models based on the 10 selected wavenumbers were built using least squares support vector machine. The identification rates for the prediction set and validation set were 89.04 and 85%, respectively. Third, chemical groups of the Lactobacillus cells contributing to the identification of the Lactobacillus strains were identified using mid infrared. The results of mid infrared data analysis indicated that 9 chemical groups could be considered characteristics for categorizing the 11 Lactobacillus strains. The relationship between the 10 selected wavenumbers and identified chemical groups was identified, which supported the satisfactory performance of the least squares support vector machine calibration model. This study demonstrated that near-infrared spectral features of bacterial colonies could be used for Lactobacillus typing at the strain level.

show abstract

“…It applies a linear transformation to decompose spectral data into several principal components (PCs), which are not correlated [36,37]. The first two PCs are utilized to analyze the common features among samples and their grouping [38]. Two supervised classification techniques, including linear discriminant analysis (LDA) and K-nearest neighbor (KNN) were used for quantitative differentiation of samples before and after alkali treatment.…”

Section: Classificationmentioning

confidence: 99%

Quantitative visualization of subcellular lignocellulose revealing the mechanism of alkali pretreatment to promote methane production of rice straw

Sha

Xia

et al. 2020

Biotechnol Biofuels

View full text Add to dashboard Cite

Background: As a renewable carbon source, biomass energy not only helps in resolving the management problems of lignocellulosic wastes, but also helps to alleviate the global climate change by controlling environmental pollution raised by their generation on a large scale. However, the bottleneck problem of extensive production of biofuels lies in the filamentous crystal structure of cellulose and the embedded connection with lignin in biomass that leads to poor accessibility, weak degradation and digestion by microorganisms. Some pretreatment methods have shown significant improvement of methane yield and production rate, but the promotion mechanism has not been thoroughly studied. Revealing the temporal and spatial effects of pretreatment on lignocellulose will greatly help deepen our understanding of the optimization mechanism of pretreatment, and promote efficient utilization of lignocellulosic biomass. Here, we propose an approach for qualitative, quantitative, and location analysis of subcellular lignocellulosic changes induced by alkali treatment based on label-free Raman microspectroscopy combined with chemometrics. Results: Firstly, the variations of rice straw induced by alkali treatment were characterized by the Raman spectra, and the Raman fingerprint characteristics for classification of rice straw were captured. Then, a label-free Raman chemical imaging strategy was executed to obtain subcellular distribution of the lignocellulose, in the strategy a serious interference of plant tissues' fluorescence background was effectively removed. Finally, the effects of alkali pretreatment on the subcellular spatial distribution of lignocellulose in different types of cells were discovered. Conclusions: The results demonstrated the mechanism of alkali treatment that promotes methane production in rice straw through anaerobic digestion by means of a systemic study of the evidence from the macroscopic measurement and Raman microscopic quantitative and localization two-angle views. Raman chemical imaging combined with chemometrics could nondestructively realize qualitative, quantitative, and location analysis of the lignocellulose of rice straw at a subcellular level in a label-free way, which was beneficial to optimize pretreatment for the improvement of biomass conversion efficiency and promote extensive utilization of biofuel.

show abstract

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition

Cited by 56 publications

References 40 publications

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics

Qualitative discrimination of Chinese dianhong black tea grades based on a handheld spectroscopy system coupled with chemometrics

Rapid identification of Lactobacillus species using near infrared spectral features of bacterial colonies

Quantitative visualization of subcellular lignocellulose revealing the mechanism of alkali pretreatment to promote methane production of rice straw

Contact Info

Product

Resources

About