Near infrared spectroscopy combined with chemometrics for growth stage classification of cannabis cultivated in a greenhouse from seized seeds

Borille, Bruna Tassi; Marcelo, Marcelo Caetano Alexandre; Ortiz, Rafael S.; Mariotti, Kristiane de Cássia; Ferrão, Marco Flôres; Limberger, Renata Pereira

doi:10.1016/j.saa.2016.09.040

Cited by 57 publications

(42 citation statements)

References 26 publications

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“…Although previous studies have reported the successful use of NIR spectroscopy and PLS regression to determine different cannabinoids in Cannabis sativa L. plant material [9, 10], to date no reports have been found describing the quantification of a cannabinoid in a final pharma-grade product and its validation consistent with the European Medicines Agency (EMA) [11] and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) [12] guidelines.…”

Section: Introductionmentioning

confidence: 99%

Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression

Grekopoulos¹

2019

Med Cannabis Cannabinoids

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There is an increasing interest in cannabinoids as they are being proved to effectively treat the symptoms of a variety of medical conditions. Commercialization of cannabinoid-based pharmaceutical products is expected to grow in the near future, favored by the recent changes in medical regulations in many developed countries. Hence, robust and reliable analytical methods for determining the content of the active pharmaceutical ingredient will be needed, as this is one of the most relevant parameters for the decision to release the final pharmaceutical product into the market. The aim of this work was to demonstrate that near-infrared (NIR) spectroscopy fulfills the needed requirements for this purpose, as well as to provide a methodology to be applied to other cannabinoid-based products. We present two validated methods for the quantification of different liquid pharma-grade cannabidiol (CBD) formulations based on NIR spectroscopy and partial least squares regression modelling. The methods were constructed and validated with spectra belonging both to production samples and to laboratory samples specifically made for this purpose, and they fulfill European Medicines Agency and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use guideline requirements. These methods allow determining the CBD content with results comparable to the usual method of choice while saving reagent- as well as time-related costs.

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Section: Introductionmentioning

confidence: 99%

Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression

Grekopoulos¹

2019

Med Cannabis Cannabinoids

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“…And crucially, near infrared spectroscopy is capable of simultaneous analysis of many components. In recent years, near infrared spectroscopy coupled with chemometrics has been widely applied as a quantitative analysis tool in many fields, such as food, medicinal materials, microbial metabolites and so on [11][12][13][14]. It has been reported that near infrared spectroscopy has been applied to the quantitative analysis of components in water [15,16].…”

Section: Introductionmentioning

confidence: 99%

Using Near Infrared Spectroscopy to Quickly Analyze Different Nitrogens during the Shortcut Biological Removal of Nitrogen from a Polluted River

Jian¹,

Li²,

Zhang³

et al. 2019

Pol. J. Environ. Stud.

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During shortcut biological nitrogen removal in a polluted river, total nitrogen, ammonia nitrogen and nitrite nitrogen were quantified by near infrared spectroscopy and the synergy interval partial least squares (siPLS) algorithm. Spectral data of 138 water samples were obtained with a near infrared spectrometer. In addition, the real values of total nitrogen, ammonia nitrogen and nitrite nitrogen were measured with traditional chemical methods. SiPLS analysis models of total nitrogen, ammonia nitrogen and nitrite nitrogen were built through the siPLS algorithm based on spectral data and real values. The results obtained from the siPLS analysis model of total nitrogen revealed that, when the full spectra were divided into 19 intervals, the combination of the 7 th , 12 th and 19 th subintervals yielded the best model. The correction coefficient (R p ) is 0.9931, with the root mean squared error of calibration (RMSECV) being 1.7869. The results obtained from the siPLS analysis model of ammonia nitrogen indicated that, when the full spectra were divided into 16 intervals, the combination of the 1 st , 7 th , 15 th and 16 th subintervals yielded the best model. The R p is 0.9947 and the RMSECV is 1.3419. For nitrite nitrogen, the siPLS analysis model indicated that, when the full spectra were divided into 16 intervals, the combination of the 7th and the 11th subintervals yielded the best model. The R p and RMSECV was 0.9951 and 1.0518. These findings demonstrated that the proposed approach may effectively analyze the concentrations of total nitrogen, ammonia nitrogen and nitrite nitrogen during the treatment of a polluted river based on shortcut biological nitrogen removal. This approach, *

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“…A Cannabis sativa é uma das plantas que o homem conhece há mais tempo e seu uso data de milênios nas regiões central e nordeste do continente asiático. 1 Em diversas partes do mundo a planta é ou já foi utilizada para diversos fins, desde a confecção de têxteis até em rituais religiosos. 2 A Cannabis é a droga de abuso mais comum e mais traficada em todo o mundo 1,3 e em 2015 estimavam-se cerca de 181,8 milhões de usuários de Cannabis ao redor do globo.…”

Section: Os Canabinoidesunclassified

“…1 Em diversas partes do mundo a planta é ou já foi utilizada para diversos fins, desde a confecção de têxteis até em rituais religiosos. 2 A Cannabis é a droga de abuso mais comum e mais traficada em todo o mundo 1,3 e em 2015 estimavam-se cerca de 181,8 milhões de usuários de Cannabis ao redor do globo. Embora o número de usuários tenha se mantido relativamente estável nos últimos anos, a Cannabis tem ganhado espaço na área de pesquisa internacional de saúde, devido principalmente a mudanças em políticas de legalização e descriminalização em algumas partes do mundo.…”

Section: Os Canabinoidesunclassified

“…Os limites de detecção e de quantificação foram respectivamente de 5 ng mL -1 e 20 ng mL -1 , para os compostos THC e THC-OH, na faixa linear de 25 a 250 ng mL -1 . Para o composto THC-COOH os limites de detecção e quantificação alcançados foram de 1 ng mL -1 e 5 ng mL -1 , respectivamente, na faixa linear de 5 a 170 ng mL - 1 . O método apresentou valores razoáveis de precisão entre 3,2% (THC-COOH) e 25,1% (THC) e de exatidão, que variou entre -18,4 e 17,4 (ambos para o THC).…”

Section: Introductionunclassified

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Microextração de canabinoides em urina usando dispositivo empacotado com polímero molecularmente impresso e análise por cromatografia líquida - espectrometria de massas sequencial

Sartore¹

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Near infrared spectroscopy combined with chemometrics for growth stage classification of cannabis cultivated in a greenhouse from seized seeds

Cited by 57 publications

References 26 publications

Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression

Construction and Validation of Quantification Methods for Determining the Cannabidiol Content in Liquid Pharma-Grade Formulations by Means of Near-Infrared Spectroscopy and Partial Least Squares Regression

Using Near Infrared Spectroscopy to Quickly Analyze Different Nitrogens during the Shortcut Biological Removal of Nitrogen from a Polluted River

Microextração de canabinoides em urina usando dispositivo empacotado com polímero molecularmente impresso e análise por cromatografia líquida - espectrometria de massas sequencial

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