Qualitative and quantitative analysis in sandalwood oils using near infrared spectroscopy combined with chemometric techniques

Kuriakose, Saji; Joe, Hubert

doi:10.1016/j.foodchem.2012.04.073

Cited by 18 publications

(11 citation statements)

References 17 publications

(18 reference statements)

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“…To our basic knowledge, the nearer the value of and come to 1, the better the line of cal ibration and prediction result could be; the lower the value of RMSEC, RMSECV and RMSECP is, the more accurate the calibration model and prediction could be. As to the RPD, it is equal to the value of SD (mean square deviation) being dividing by RMSEP, with the use of evaluating the model's ability of predic tions, the bigger the value of RPD is, the higher pre diction ability the model has, and when it is bigger than three, it means that the model can predict accu rately [17].…”

Section: Comparison Of Different Spectral Pretreatment Methodsmentioning

confidence: 99%

Absorption and quantitative characteristics of C-H bond and O-H bond of NIR

Ouyang

Shi

et al. 2014

Opt. Spectrosc.

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The previous study mainly focused on the interpretation of the relationship between absorption characteristics and quantitative contribution in each near infrared (NIR) frequency range. Furthermore, the absorption characteristics of NIR mainly cover overtones and combinations of molecular vibrations such as CH, OH, SH, and NH bonds. And it has been know that NIR wavelengths of C-H bond and O-H bond are assigned to different radio frequencies. This paper was intended to investigate the absorption characteristics of bond C-H and O-H bonds in NIR spectral range. Water and acetone which correspond to O-H and C⎯H bonds have been selected as typical solvents, as well as solutes. Calibration models were established using par tial least square regression (PLS) and multiple linear regression (MLR). The parameter of the model were optimized by different spectral pretreatment methods. The result showed that the model set by Savitzky⎯Go lay smooth (SG) in the spectral region of 810-1100 nm could successfully make accurate predictions. Short wave NIR region has been discovered as optimum characteristic absorption of C-H and O-H bonds.

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Section: Comparison Of Different Spectral Pretreatment Methodsmentioning

confidence: 99%

Absorption and quantitative characteristics of C-H bond and O-H bond of NIR

Ouyang

Shi

et al. 2014

Opt. Spectrosc.

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“…The role of regularization parameter (c) and kernel parameter (r 2 ) for making a good LS-SVM model with high prediction accuracy and stability is crucial [28,[40][41][42][43][44][45][46]. Root mean squared error for prediction is described as a statistical evaluation index for performance of the LS-SVM prediction models and obtained by Eq.…”

Section: Continuous Wavelet Transform Methodsmentioning

confidence: 99%

“…A set of linear equations is required to be solved during the training of LS-SVM and the complexity of calculation is decreased much [28][29][30]. Due to the choice of quadratic function, LS-SVM loses more sparseness for empirical risk in comparison to SVM.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a trained LS-SVM can increase the computation load of decision function especially for large scales problems [31]. Recently, the LS-SVM method has been coupled with the spectral analysis as a rapid and non-destructive method for simultaneous quantitative analysis of multicomponent mixtures [27][28][29][30][31][32] In order to existence strong overlapping among the absorption spectra of Myricetin, Kaempferol and Quercetin, the UV spectroscopy cannot be applied for simultaneous determination of them alone. Thus, Chemometric methods can be integrated with UV spectroscopy methods [11].…”

Section: Introductionmentioning

confidence: 99%

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The application of continuous wavelet transform and least squares support vector machine for the simultaneous quantitative spectrophotometric determination of Myricetin, Kaempferol and Quercetin as flavonoids in pharmaceutical plants

Sohrabi

Darabi

2016

Spectrochimica Acta Part A: Molecular and Biomolecular Spectros

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“…From 2004 to 2007, much research on the application of the SVM method in disease and insect pest recognition was conducted by Tian et al [ 14 ], which discovered that the SVM method has high recognition performance. Santalum album Linn , a semi-parasitic small tree of the genus Santalum and of the family Santalaceae , is one of the most expensive types of wood [ 14 , 15 , 16 , 17 , 18 ] and is listed as one of the national key protected plants. Sandalwood have long medical history [ 19 ], based on the object of research, the pathogen of seedlings early destruction [ 20 ], the articles about its spike disease [ 21 ], and the spike disease phytoplasma identification [ 22 , 23 ], and report about sandalwood ulcer disease problems.…”

Section: Introductionmentioning

confidence: 99%

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing

Wang

2017

PLoS ONE

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This paper presents a survey on a system that uses digital image processing techniques to identify anthracnose and powdery mildew diseases of sandalwood from digital images. Our main objective is researching the most suitable identification technology for the anthracnose and powdery mildew diseases of the sandalwood leaf, which provides algorithmic support for the real-time machine judgment of the health status and disease level of sandalwood. We conducted real-time monitoring of Hainan sandalwood leaves with varying severity levels of anthracnose and powdery mildew beginning in March 2014. We used image segmentation, feature extraction and digital image classification and recognition technology to carry out a comparative experimental study for the image analysis of powdery mildew, anthracnose disease and healthy leaves in the field. Performing the actual test for a large number of diseased leaves pointed to three conclusions: (1) Distinguishing effects of BP (Back Propagation) neural network method, in all kinds of classical methods, for sandalwood leaf anthracnose and powdery mildew disease are relatively good; the size of the lesion areas were closest to the actual. (2) The differences between two diseases can be shown well by the shape feature, color feature and texture feature of the disease image. (3) Identifying and diagnosing the diseased leaves have ideal results by SVM, which is based on radial basis kernel function. The identification rate of the anthracnose and healthy leaves was 92% respectively, and that of powdery mildew was 84%. Disease identification technology lays the foundation for remote monitoring disease diagnosis, preparing for remote transmission of the disease images, which is a very good guide and reference for further research of the disease identification and diagnosis system in sandalwood and other species of trees.

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Qualitative and quantitative analysis in sandalwood oils using near infrared spectroscopy combined with chemometric techniques

Cited by 18 publications

References 17 publications

Absorption and quantitative characteristics of C-H bond and O-H bond of NIR

Absorption and quantitative characteristics of C-H bond and O-H bond of NIR

The application of continuous wavelet transform and least squares support vector machine for the simultaneous quantitative spectrophotometric determination of Myricetin, Kaempferol and Quercetin as flavonoids in pharmaceutical plants

Preliminary research on the identification system for anthracnose and powdery mildew of sandalwood leaf based on image processing

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