Discriminant Analysis of Shodhana (Processing) on Baliospermum Montanum Muell (Danti) Root Samples Based on Near Infrared Spectroscopy and Multivariate Chemometric Technique

Rout, Siba Prasad; Acharya, Rabinarayan; Maji, Jayanta Kumar

doi:10.22159/ijpps.2017v9i7.18272

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…The peak around 1200 nm could be attributed to the 1 st overtone of C-H stretch [ 50 ]. These absorption bands are characteristics of proteins, fats, and aromatic compounds found in cocoa beans [ 45 , 51 , 52 ]. Observable absorption band around 1608 nm might be ascribed to 1 st overtone of C-H stretching (Zhang et al [ 53 ]).…”

Section: Resultsmentioning

confidence: 99%

Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques

Anyidoho

Teye

Agbemafle

2021

International Journal of Food Science

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The global market for organic cocoa beans continues to show sturdy growth. A low-cost handheld NIR spectrometer (900-1700 nm) combined with multivariate classification algorithms was used for rapid differentiation analysis of organic cocoa beans’ integrity. In this research, organic and conventionally cultivated cocoa beans were collected from different locations in Ghana and scanned nondestructively with a handheld spectrometer. Different preprocessing treatments were employed. Principal component analysis (PCA) and classification analysis, RF (random forest), KNN ( K -nearest neighbours), LDA (linear discriminant analysis), and PLS-DA (partial least squares-discriminant analysis) were performed comparatively to build classification models. The performance of the models was evaluated by accuracy, specificity, sensitivity, and efficiency. Second derivative preprocessing together with PLS-DA algorithm was superior to the rest of the algorithms with a classification accuracy of 100.00% in both the calibration set and prediction set. Second derivative algorithm was found to be the best preprocessing tool. The identification rates for the calibration set and prediction set were 96.15% and 98.08%, respectively, for RF, 91.35% and 92.31% for KNN, and 90.38% and 98.08% for LDA. Generally, the results showed that a handheld NIR spectrometer coupled with an appropriate multivariate algorithm could be used in situ for the differentiation of organic cocoa beans from conventional ones to ensure food integrity along the cocoa bean value chain.

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Section: Resultsmentioning

confidence: 99%

Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques

Anyidoho

Teye

Agbemafle

2021

International Journal of Food Science

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“…NIR spectroscopy has been widely applied in the agricultural, food and beverage industries [7,8]. For pharmaceutical industry field, NIR spectroscopy along with chemometric methods can be applied for both qualitative and quantitative analysis such as API content, excipient content [9,10], drug stability [11] state of solid material [12] and identification of herbal extract [13,14]. Furthermore, NIR spectroscopy is an effective tool for enabling the real-time release of pharmaceutical products.…”

Section: Introductionmentioning

confidence: 99%

Application of Near Infrared Spectroscopy for Endpoint Determination of Blending and Influence of Loading Order

Sodata

Peerapattana

2020

Int J App Pharm

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Objective: This study aimed to apply near-infrared spectroscopy along with a thief as a tool to determine the endpoint of the blending process. Methods: The calibration model was constructed by partial least square regression. The best model was applied to determine the endpoint of the blending process, also the effect of loading order on the endpoint for the blending of the formulation containing a low concentration of the active pharmaceutical ingredient. Results: The best partial least square regression model yielded the lowest root mean square error of calibration of 1.4004, the lowest root mean square error of prediction of 1.4108 and the highest correlation coefficient of 0.9921. Validation study revealed the reference values were not statistically different from those of the predicted values. The model could predict the endpoint of the blending process with acceptable precision and accuracy. Standard deviation of the content of active pharmaceutical ingredients was ≤ 3% of the target after eighteen minutes of the blending process, which indicated the uniformity of powder blends. Additionally, the model revealed the order of powder loading slightly affected the blending time. The protocol that loaded the active pharmaceutical ingredient first or last needed a longer time to achieve the uniformity of blend. Conclusion: NIR spectroscopy is the rapid and effective tools that could be applied to study the blending process in the pharmaceutical manufacturing.

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Discriminant Analysis of Shodhana (Processing) on Baliospermum Montanum Muell (Danti) Root Samples Based on Near Infrared Spectroscopy and Multivariate Chemometric Technique

Cited by 2 publications

References 7 publications

Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques

Differentiation of Organic Cocoa Beans and Conventional Ones by Using Handheld NIR Spectroscopy and Multivariate Classification Techniques

Application of Near Infrared Spectroscopy for Endpoint Determination of Blending and Influence of Loading Order

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