WO2022066700A1

WO2022066700A1 - Infrared spectroscopic methods for evaluating compositions

Info

Publication number: WO2022066700A1
Application number: PCT/US2021/051448
Authority: WO
Inventors: Steve Bobzin; Adam D. RICHARDSON
Original assignee: Central Coast Agriculture, Inc.
Priority date: 2020-09-22
Filing date: 2021-09-22
Publication date: 2022-03-31

Abstract

Described herein are systems and methods for quantitating one or more cannabinoids or terpenoids in a sample, including but not limited to fresh Cannabis plants and flowers.

Description

INFRARED SPECTROSCOPIC METHODS FOR EVALUATING COMPOSITIONS

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of U.S. Provisional Patent Application Number 63/081,722 filed September 22, 2020, which is incorporated herein by reference in its entirety.

BACKGROUND

[0002] Spectroscopy is the study of the interaction of electromagnetic radiation with matter. Instruments called spectrometers are used in spectroscopy to measure what are called spectra. The types of samples that spectrometers can analyze can be divided up into the three phases of matter: solids, liquids, and gases. For all three phases of matter, there is a need to identify and quantify the chemical species in samples. There exist general use spectrometers capable of performing this type of work, but they are often expensive, difficult to use, and bulky. Therefore, in view of the aforementioned difficulties, there is an unsolved need for methods and systems for a compact and portable spectrometer, including methods and systems for the analysis of Q//wa/v.s-based fluid-based and solid-based products in a compact form factor.

SUMMARY

[0003] The present disclosures provides, in part, methods and systems that provide for rapid, high-throughput, and inexpensive approaches (e.g., field-based approaches) for determining cannabinoid and terpenoid compositions in samples, including but not limited to compositional analyses of Cannabis plants and flowers during cultivation cycles, for breeding and selection programs, and for other in-field operations. Said methods and systems can use chemical analysis devices (e.g., an infrared spectrometer, e.g., a portable infrared spectrometer) to accomplish the rapid, high-throughput, and inexpensive approaches of the present disclosure.

[0004] Accordingly, provided herein, in an embodiment, are systems and methods for quantitating cannabinoids and terpenoids in samples, such as samples comprising certain weight percentages of water (e.g., at least 15% by weight) based on the total weight of the sample. In some embodiments, said sample is a fresh plant or flower (e.g., a fresh Cannabis plant growing in a field, a fresh Cannabis plant recently extracted from a field, or fresh flowers thereof). In some embodiments, the Cannabis plant is one of Cannabis sativa or Cannabis indica.

[0005] In one embodiment, provided herein is a system for quantitating one or more cannabinoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising: (i) a chemical analysis device configured to irradiate the sample with mid-infrared radiation to create a signal, and detect the signal to create a first output; and (ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

[0006] In another embodiment, provided herein is a method for quantitating one or more cannabinoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze a representation (e.g., transmittance, absorbance, or reflectance) of the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

[0007] In another embodiment, provided herein is a method for quantitating one or more cannabinoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

[0008] In another embodiment, provided herein is a system for quantitating one or more terpenoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising: (i) a chemical analysis device configured to irradiate the sample with mid-infrared radiation to create a signal, and detect the signal to create a first output; and (ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

[0009] In another embodiment, provided herein is a method for quantitating one or more terpenoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze a representation (e.g., transmittance, absorbance, or reflectance) of the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

[00010] In another embodiment, provided herein is a method for quantitating one or more terpenoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

BRIEF DESCRIPTION OF THE DRAWINGS

[00011] FIG. 1 represents exemplary results for the PLS model after applying SNV and 1^st derivative with 3 smoothing points and random 20 segment cross-validation.

[00012] FIG. 2 represents exemplary absorbances of diluted terpenes at different concentrations.

[00013] FIG. 3 represents exemplary absorbances of eucalyptol at different concentrations.

[00014] FIG. 4 represents exemplary PCA scores of samples at different concentrations.

[00015] FIG. 5 represents exemplary spectra of neat and spiked flower with various terpenes after applying SNV. DETAILED DESCRIPTION

Systems for quantitating cannabinoids

[00016] The present disclosure provides, in part, systems for quantitating one or moore cannabinoids or terpenoids in samples. In some embodiments, the system comprises a chemical analysis device. In some embodiments, the chemical analysis device is configured to irradiate the sample with radiation to create a signal and detect said signal. In some embodiments, the radiation is near-infrared radiation. In some embodiments, the radiation is mid-infrared radiation. In some embodiments, the radiation is far-infrared radiation.

[00017] The systems described herein can comprise a spectral analysis model to analyze a first output created by a chemical analysis device described herein to create a second output comprising a calculated amount of the one or more cannabinoids in a sample. Examples of spectral analysis models include those known to one of skill in the art, such as a multivariate chemometric algorithm including principal component analysis, principal component regression, a partial least squares analysis, and multivariate curve resolution. In some embodiments, the spectral analysis model is derived by regression among spectroscopic data (e.g., by multiple-linear regression, by partial least squares, or by neural network analysis).

[00018] In some embodiments, the disclosure provides software for developing spectroscopic (e.g., MIR) models. For example, the software can correlate spectroscopic data with quantification of cannabinoids or terpenoids in Cannabis samples. The software can establish validated mathematical correlations between spectra and independently determined chemical constituents using multivariate statistical regression methods, such as those discussed above.

[00019] In one embodiment, provided herein is a system for quantitating one or more cannabinoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising: (i) a chemical analysis device configured to irradiate the sample with mid-infrared radiation to create a signal, and detect the signal to create a first output; and (ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample. [00020] In some embodiments, the sample is a //waZv.s-based sample. In some embodiments, the Q//waZv'.s-based sample is a fresh Cannabis plant. In some embodiments, the sample is a fresh flower of a Cannabis plant. In some embodiments, the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹. In some embodiments, second output comprises a calculated amount of the one or more cannabinoids within an error of ±20%. In some embodiments, second output comprises a calculated amount of the one or more cannabinoids within an error of ±10%. In some embodiments, the calculated amount is provided in units of weight percentage. In some embodiments, the calculated amount is provided in units of parts per million. In some embodiments, the spectral analysis model is a multivariate chemometric algorithm. In some embodiments, the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, a partial least squares analysis, and a multivariate curve resolution. In some embodiments, the one or more cannabinoids is selected from the group consisting of tetrahydrocannabinol, cannabigerol, cannabichromene, tetrahydrocannabivarin, cannabidiol, cannabinol, cannabigerivarin, tetrahydrocannabivarian, cannabidivarin, cannabichromevarin, and carboxylic acid derivatives thereof. In some embodiments, the carboxylic acid derivative is tetrahydrocannabinolic acid (e.g., A9- tetrahydrocannabinolic acid) or cannabidiolic acid. In some embodiments, the first output is selected from the group consisting of absorbance, transmittance, and reflectance. In some embodiments, the system is configured to quantitate the total cannabinoid content of the same.

[00021] In some embodiments, the sample comprises water in an amount of at least 16%, at least 17%, at least 18%, at least 19%, at least 20%, at least 21%, at least 22%, at least

23%, at least 24%, at least 25%, at least 26%, at least 27%, at least 28%, at least 29%, at least

30%, at least 31%, at least 32%, at least 33%, at least 34%, at least 35%, at least 36%, at least

37%, at least 38%, at least 39%, at least 40%, at least 41%, at least 42%, at least 43%, at least

44%, at least 45%, at least 46%, at least 47%, at least 48%, at least 49%, or at least 50% by weight based on the total weight of the sample. In some embodiments, the sample comprises water in an amount of about 20-30%, 30-40%, 40-50%, 50-60%, 60-70%, 70-80%, 80-90%, or 90-99% by weight based on the total weight of the sample. In some embodiments, the sample comprises water in an amount of about 60-70% by weight based on the total weight of the sample. In some embodiments, the sample comprises water in an amount of about 60- 80% by weight based on the total weight of the sample. In some embodiments, the sample comprises water in an amount of 80-99% by weight based on the total weight of the sample.

[00022] In some embodiments, the sample comprises one or more cannabinoids (e.g., A9-THC) in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 5%-l 0% by weight based on the total weight of the sample.

[00023] In some embodiments, the sample comprises a total cannabinoid content in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 5%-l 0% by weight based on the total weight of the sample.

[00024] In one embodiment, provided herein is a system for quantitating one or more terpenoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising: (i) a chemical analysis device configured to irradiate the sample with mid-infrared radiation to create a signal, and detect the signal to create a first output; and (ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

[00025] In some embodiments, the sample is a ( z/////aA/.s-based sample. In some embodiments, the ( z/////aA/.s-based sample is a fresh sample of a Cannabis plant. In some embodiments, the fresh sample is a fresh flower of a Cannabis plant. In some embodiments, the fresh flower of a Cannabis plant is homogenized. In some embodiments, the homogenized fresh flower of a Cannabis plant has a particle size of about 0.5 to about 5 mm, about 0.5 to about 2 mm, or about 1 to about 2 mm. In some embodiments, the homogenized fresh flower of a Cannabis plant has a moisture content of about 50% to about 95%, about 60 to about 90%, about 70 to about 90%, or about 70 to about 80% by weight of water based on the total weight of the sample. In some embodiments, the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹. In some embodiments, second output comprises a calculated amount of the one or more terpenoids within an error of ±20%. In some embodiments, second output comprises a calculated amount of the one or more terpenoids within an error of ±10%. In some embodiments, the calculated amount is provided in units of weight percentage. In some embodiments, the calculated amount is provided in units of parts per million. In some embodiments, the spectral analysis model is a multivariate chemometric algorithm. In some embodiments, the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, a partial least squares analysis, and a multivariate curve resolution. In some embodiments, the one or more terpenoids is selected from the group consisting of alpha thujene, alpha pinene, camphene, beta pinene, beta myrcene, p-mentha-l,5-diene, 3-carene, alpha terpinene, p-cymene, D-limonene, beta ocimene, terpinolene, linalool, fenchol, trans-2- pinanol, alpha terpineol, beta caryophyllene, gamma elemene, alpha bergamotene, humulene, caryophyllene oxide, 4,8,12-Tetradecatrienal, beta selinene, alpha selinene, alpha bulnesene, alpha famesene, beta maaliene, (4aR,8aS)-4a-Methyl-l-methylene-7-(propan-2- ylidene)decahydronaphthalene, cis nerolidol, trans nerolidol, Selina-3, 7(1 l)-diene, trans alpha bisabolene, beta guaiene, epi-gamma-eudesmol, longifolene, cis beta guaiene, aromandendrene, alpha eudesmol, alpha bulnesene, alpha bisabolol, juniper camphor, and beta bisabolene. In some embodiments, the first output is selected from the group consisting of absorbance, transmittance, and reflectance. In some embodiments, the system is configured to quantitate the total terpenoid content of the same.

[00026] In some embodiments, the sample comprises water in an amount of at least 16%, at least 17%, at least 18%, at least 19%, at least 20%, at least 21%, at least 22%, at least

[00027] In some embodiments, the sample comprises one or more terpenoids in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 5%-10% by weight based on the total weight of the sample.

[00028] In some embodiments, the sample comprises a total terpenoid content in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 5%-l 0% by weight based on the total weight of the sample.

Methods of quantitating cannabinoids

[00029] The present disclosure also provides methods of quantitating one or more cannabinoids or one or more terpenoids in a sample. In some embodiments, the methods comprises the use a chemical analysis device. In some embodiments, the chemical analysis device is configured to irradiate the sample with radiation to create a signal and detect said signal. In some embodiments, the radiation is near-infrared radiation. In some embodiments, the radiation is mid-infrared radiation. In some embodiments, the radiation is far-infrared radiation.

[00030] The methods described herein can comprise the use of a spectral analysis model to analyze a first output created by a chemical analysis device described herein to create a second output comprising a calculated amount of the one or more cannabinoids in a sample. Examples of spectral analysis models include those known to one of skill in the art, such as a multivariate chemometric algorithm including principal component analysis, principal component regression, a partial least squares analysis, and multivariate curve resolution.

[00031] In one embodiment, provided herein is a method for quantitating one or more cannabinoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze a representation (e.g., transmittance, absorbance, or reflectance) of the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

[00032] In another embodiment, provided herein is a method for quantitating one or more cannabinoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

[00033] In some embodiments, the sample is a //wa/v.s-based sample. In some embodiments, the ( z/////aA/.s-based sample is a fresh sample of a Cannabis plant. In some embodiments, the fresh sample is a fresh flower of a Cannabis plant. In some embodiments, the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm' f In some embodiments, the second output comprises a calculated amount of the one or more cannabinoids within an error of ±20%. In some embodiments, the second output comprises a calculated amount of the one or more cannabinoids within an error of ±10%. In some embodiments, the calculated amount is provided in units of weight percentage. In some embodiments, the calculated amount is provided in units of parts per million. In some embodiments, the spectral analysis model is a multivariate chemometric algorithm. In some embodiments, the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, and a partial least squares analysis, and a multivariate curve resolution. In some embodiments, the one or more cannabinoids is selected from the group consisting of tetrahydrocannabinol, cannabigerol, cannabichromene, tetrahydrocannabivarin, cannabidiol, cannabinol, cannabigerivarin, tetrahydrocannabivarian, cannabidivarin, cannabichromevarin, and carboxylic acid derivatives thereof. In some embodiments, the carboxylic acid derivative is tetrahydrocannabinolic acid (e.g., A9- tetrahydrocannabinolic acid) or cannabidiolic acid. In some embodiments, the first output is selected from the group consisting of absorbance, transmittance, and reflectance. In some embodiments, the method comprises quantitating the total cannabinoid content in the sample.

[00034] In some embodiments, the sample comprises water in an amount of at least 16%, at least 17%, at least 18%, at least 19%, at least 20%, at least 21%, at least 22%, at least

[00035] In In some embodiments, the sample comprises one or more cannabinoids (e.g., A9-THC) in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 5%-l 0% by weight based on the total weight of the sample.

[00036] In some embodiments, the sample comprises a total cannabinoid content in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 5%-l 0% by weight based on the total weight of the sample.

[00037] In another embodiment, provided herein is a method for quantitating one or more terpenoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze a representation (e.g., transmittance, absorbance, or reflectance) of the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

[00038] In one embodiment, provided herein is a method for quantitating one or more terpenoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising: (i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and (ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

[00039] In some embodiments, the sample is a //wa/v.s-based sample. In some embodiments, the ( z/////aA/.s-based sample is a fresh sample of a Cannabis plant. In some embodiments, the fresh sample is a fresh flower of a Cannabis plant. In some embodiments, the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm' ^x. In some embodiments, second output value comprises a calculated amount of the one or more terpenoids within an error of ±20%. In some embodiments, second output value comprises a calculated of the one or more terpenoids within an error of ±10%. In some embodiments, the calculated amount is provided in units of weight percentage. In some embodiments, the calculated amount is provided in units of parts per million. In some embodiments, the spectral analysis model is a multivariate chemometric algorithm. In some embodiments, the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, and a partial least squares analysis, and a multivariate curve resolution. In some embodiments, the one or more terpenoids is selected from the group consisting of alpha thujene, alpha pinene, camphene, beta pinene, beta myrcene, p-mentha-l,5-diene, 3-carene, alpha terpinene, p-cymene, D- limonene, beta ocimene, terpinolene, linalool, fenchol, trans-2-pinanol, alpha terpineol, beta caryophyllene, gamma elemene, alpha bergamotene, humulene, caryophyllene oxide, 4,8,12- Tetradecatrienal, beta selinene, alpha selinene, alpha bulnesene, alpha farnesene, beta maaliene, (4aR,8aS)-4a-Methyl-l-methylene-7-(propan-2-ylidene)decahydronaphthalene, cis nerolidol, trans nerolidol, Selina-3, 7(1 l)-diene, trans alpha bisabolene, beta guaiene, epi- gamma-eudesmol, longifolene, cis beta guaiene, aromandendrene, alpha eudesmol, alpha bulnesene, alpha bisabolol, juniper camphor, and beta bisabolene. In some embodiments, the first output is selected from the group consisting of absorbance, transmittance, and reflectance. In some embodiments, the method comprises quantitating the total terpenoid content in the sample.

[00040] In some embodiments, the sample comprises water in an amount of at least 16%, at least 17%, at least 18%, at least 19%, at least 20%, at least 21%, at least 22%, at least

[00041] In some embodiments, the sample comprises one or more terpenoids in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises a cannabinoid in an amount of about 5%-10% by weight based on the total weight of the sample.

[00042] In some embodiments, the sample comprises a total terpenoid content in an amount of at least 0.01%, at least, 0.1%, at least 0.5%, at least 1%, at least 2%, at least 3%, at least 4%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, at least 10%, at least 11%, at least 12%, at least 13%, at least 14%, or at least 15% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 1%- 10% by weight based on the total weight of the sample. In some embodiments, the sample comprises the one or more cannabinoids in an amount of about 5%-l 0% by weight based on the total weight of the sample.

Chemical Analysis Devices

[00043] A chemical analysis device can be used in the methods and systems for quantitating cannabinoids and terpenoids described herein. In some embodiments, the chemical analysis device is a spectrometer (e.g., a near-infrared spectrometer, a mid-infrared spectrometer, a far-infrared spectrometer, or a Raman spectrometer). In some embodiments, the chemical analysis device is a portable spectrometer (e.g., a portable near-infrared spectrometer, a portable mid-infrared spectrometer, a portable far-infrared spectrometer, or a portable Raman spectrometer).

[00044] Non-limiting examples of chemical analysis devices that can be used in the present systems and methods are described in WO 2018/080938 and WO 2017/134669, which are incorporated herein by reference.

Definitions

[00045] As used herein, the term "about" denotes an approximate range of plus or minus 10% from a specified value. For instance, the language "about 20%" encompasses a range of 18-22%. As used herein, "about" also includes the exact amount. Hence "about 20%" means "about 20% " and also "20%. "

[00046] As used herein and unless otherwise specified, the term “terpenoid” may refer to either a “terpene compound” or “terpenoid-type compound.” “Terpene compound” refers to isoprene-containing hydrocarbons, having isoprene units (CH2C(CH3)CHCH2) in a head- to-tail orientation. Terpene compounds in general, have the molecular formula (C5Hs)_n, and include hemiterpenes, (C5), monoterpenes (CIO), sesquiterpenes (Cl 5), diterpenes (C20), triterpenes (C30), and tetraterpenes (C40) which respectively have 1, 2, 3, 4, 6 and 8 isoprene units. Terpene compounds may be further classified as acyclic or cyclic. “Terpenoid-type compound” refers to a terpene-related compound, which contains at least one oxygen atom in addition to isoprene units, and thus includes alcohols, aldehydes, ketones, ethers, such as but not limited to, carboxylic acids derivatives thereof, such as esters. Terpenoid-type compounds are subdivided according to the number of carbon atoms in a manner similar to terpene and thus include hemiterpenoids, (C5), monoterpenoid-type compounds (CIO), sesquiterpenoid-type (Cl 5), diterpenoid-type (C20), triterpenoid-type (C30), and tetraterpenoid-type compounds (C40) which respectively have 1, 2, 3, 4, 6 and 8 isoprene units. The skeleton of terpenoid-type compounds may differ from strict additivity of isoprene units by the loss or shift of a fragment, commonly a methyl group. Examples of monoterpenoid-type compounds include camphor, eugenol, menthol and borneol. Examples of diterpenoid-type compounds include phytol, retinol and taxol. Examples of triterpenoid- type compounds include betulinic acid and lanosterol. Terpenoid-type compounds may be acyclic or may contain one or more ring-structures. Triterpenoid-type compounds may be acyclic or may contain one or more ring-structures. The rings may contain only carbon atoms, or alternatively may contain one or more oxygen atoms besides carbon atoms. Common ring-sizes range from three-membered rings to ten-membered rings. Larger ring sizes of up to at least twenty -membered rings are possible. More than one ring and more than one ring-size maybe present in a single tri terpenoid-type compounds. In case a triterpenoid- type compound contains more than one ring, the rings may be present and separated by one or more acyclic bonds; alternatively, the rings may be directly connected via connections of the annealed type, the bridged type, the spiro-type or combinations of any of these types. Multiply annealed, fused, bridged, or spiro-type ring systems are possible. Combinations of singly and multiply annealed, bridged, fused, spiro-type rings are possible. Combinations of isolated rings and connected rings in the same triterpenoid-type are possible.

[00047] Cannabinoid," as used herein, is meant to include compounds which interact with a cannabinoid receptor, and various cannabinoid mimetics, such as certain tetrahydropyran analogs (e.g., A⁹-tetrahydrocannabinol, A⁸-tetrahydrocannabinol, 6,6,9- trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-l-ol, 3-(l,l-dimethylheptyl)-6,6a,7,8, 10,10a- hexahydro-1 -hydroxy-6, 6-dimethyl-9H-dibenzo[b,d]pyran-9-one, (-)-(3S,4S)-7-hydroxy-A⁶- tetrahydrocannabinol-1, 1 -dimethylhept- yl, (+)-(3 S,4S)-7-hydroxy-A⁶ -tetrahydrocannabinol- 1,1-dimethylh- eptyl, 11-hydroxy-A⁹ -tetrahydrocannabinol, and A⁸-tetrahydrocannabinol-l 1- oic acid)); certain piperidine analogs (e.g., (-)-(6S,6aR,9R,10aR)-5,6,6a,7,8,9,10,10a- octahydro-6-methyl-3-[(R)-l-meth- yl-4-phenylbutoxy]-l,9-phenanthridinediol 1-acetate)), certain aminoalkylindole analogs (e.g., (R)-(+)-[2,3-dihydro-5-methyl-3-(4- morpholinylmethyl)-pyrrolo[ 1 ,2,3 -de]- 1 - ,4-benzoxazin-6-yl]- 1 -naphthal enyl-methanone), certain open pyran ring analogs (e.g., 2-[3-methyl-6-(l-methylethenyl)-2-cyclohexen-l-yl]-5- pentyl- 1,3 -benzenediol and 4-(l,l-dimethylheptyl)-2,3'-dihydroxy-6'alpha-(3- hydroxypropyl)-l',- 2',3',4',5',6'-hexahydrobiphenyl), as well as their pharmaceutically acceptable salts, solvates, metabolites (e.g., cutaneous metabolites), and metabolic precursors.

[00048] As used herein, “near-infrared radiation” refers to infrared radiation from about 12,500 cm'¹ to 4,000 cm'¹. As used herein, “mid-infrared” radiation refers to infrared radiation from about 4,000 cm'¹ to 400 cm'¹. As used herein, “far-infrared radiation” refers to infrared radiation from about 400 cm'¹ to 10 cm'¹.

EXAMPLES

[00049] In order that the present disclosure may be more fully understood, the following example is set forth. The example described in this application is offered to illustrate the embodiments provided herein and is not to be construed in any way as limiting their scope.

Example 1. In-field analysis of fresh Cannabis flowers using a mid-infrared spectrometer and spectral analysis model.

[00050] The quantitation of the composition of select cannabinoids and terpenoids in the flower of a fresh Cannabis plant growing in a field was determined by mid-infrared spectroscopic analysis. Briefly, an instrument containing a portable mid-infrared spectrometer, irradiated the fresh plant with mid-infrared radiation to produce a spectrum. The instrument then analyzed the spectrum to identify and select cannabinoids and terpenoids present in the flower and then applied a chemometric algorithm, including a principal component analysis and a partial least squares analysis, to quantitate these cannabinoids and terpenoids. The instrument quantitated the cannabinoids and terpenoids against an internal calibration, which was a standard curve obtained by a quantitative HPLC-UV method for cannabinoids and a GC-MS method for terpenoids. Chemometric Data Analysis

[00051] Spectral and analytical data were imported into Unscrambler (vl 1, CAMO Analytics). The data were then visualized via line and scatter plots to determine the quality of the data and if any pre-processing was necessary. Principal component models were computed, and any gross outliers were removed before proceeding to perform a partial least squares regression (PLS). Several PLS models were made, with various pre-processing techniques, and the resulting models were judged based on the number of components or factors, root mean square error (RMSE), slope, and R² values. The PLS models with the best results were then validated with a separate set of data.

In-field analysis of fresh Cannabis flowers using a mid-infrared spectrometer and spectral analysis model:

[00052] MIR spectra were collected for 101 varieties of cannabis by selecting the healthiest flower from 4 plants of the same species. Approximately another 5” of flower was harvested to have similar sample volume. The weight varied between plant species ranging from 3g - 13g. From the harvested flower, 3-5 points were selected from the plant (roughly a dimes size) with at least one from the top, mid-section, and one from the bottom of the flower. Those 3-5 pieces were then homogenized using a pro250 Homogenizer w/ 10mm probe from Proscientific for 1 min. A small spatula size sample was then scanned on the spectrometer (Big Sur Scientific) and was repeated 2 more times with fresh sample. The remaining sample was placed in a 4x6 plastic zip lock bag, transported in at 0 degree, and stored in -20°C for 3-10 days.

[00053] Several different PLS models (see “Chemometric Data Analysis” above) were built to determine the total THC percent using the data, with various pre-processing treatments in order to reduce the systematic noise in the spectra. Table 1 shows the results of those models. Based on having the lowest RMSECV (root mean square error of cross validation) and highest R-square (how much of the y-variance is being captured by the model), it was determined that SNV (standard normal variate) + 1^st derivative with 3 smoothing points was the best model. FIG. 1 shows the Predicted vs. Reference plot for this model. The blue values and data points are for the full calibration model and the red are for the cross-validation (20 random segments). These values are in close alignment with each other and meet the needs for our purpose of binning the varieties into Go/No-Go for further production.

Table 1: Results from PLS models for total THC percent built with various pre-processing techniques

Primary method of measuring:

[00054] Fresh/frozen flower material was collected by a California-licensed standard reference laboratory from various locations throughout the plant/batch. These collected samples were then combined and homogenized to create a single batch of material as the representative sample. Homogenization of the wet flower was performed via automation. Homogenization was very consistent. The resulting particle size was estimated at 1-2 mm as the moisture content causes the material to aggregate. A sub-sample of this material was then analyzed for total moisture content. Fresh/frozen flower consistently yielded a moisture content of 70-80%. A separate sub-sample was extracted with ethanol and analyzed by HPLC (diode array) for cannabinoid content. Eleven cannabinoids were quantified via total absorbance (AUC) against external calibration curves.

[00055] A separate sub-sample was extracted w/ butane and analyzed by GC/MS for terpene content. 42 cannabinoids were quantified via Selected Ion Monitoring signals (AUC) against external calibration curves.

[00056] The analyte concentrations of the cannabinoids and terpenes were corrected for moisture content and sample mass. Final results of the cannabinoid and terpene contents in a given sample were reported in both mg/g and percent (w/w) of the original material. [00057] The State of California regulations for cannabis testing labs are written to ensure analytical accuracy of +/- 30% when assays are performed in a compliant manner. MIR modeling of terpenes and spiked samples:

[00058] Terpene standards analyzed were manufactured through Agilent. This included 16 (Table 2) individual standards in IPA solvent, that were diluted in methanol and analyzed at a concentration of 1 mg/mL, 0.5 mg/mL, and 0.1 mg/mL. These samples were allowed to equilibrate to room temperature prior to analysis. Of the sixteen, four (limonene, alpha terpinolene, beta myrcene, and beta caryophyllene) individual terpenes were used to spike a sample of fresh cannabis flower at a concentration of 0.5 mg/mL. The sample was homogenized using a Pro Scientific Pro250 homogenizer prior to being analyzed. The sample was first analyzed with no additional terpene concentration, then followed by analysis with spiked terpene. All samples were analyzed in triplicate.

Table 2: Terpene standards used in the modeling study

[00059] FIG. 2 shows a line plot of all the diluted terpenes at the different concentrations. They all follow a similar shape (the spectra with peaks at 1045 and 1080 cm' are from the system checks), which shows that this spectral technique is not capable of discriminating between types of terpenes. The banding correlates to the concentration (FIG. 3). [00060] FIG. 4 is a PCA (principal components analysis) scores plot of the samples and we can see the different concentrations group together nicely, confirming the previous assessment that quantification could be possible, but not differentiation between individual terpene components. Fresh flower was scanned before and after it was individually spiked with beta caryophyllene, beta myrcene, alpha terpinolene, and limonene at 0.5 mg/mL concentration. FIG. 5 shows the resulting spectra, after applying a SNV transform. There are discernable differences between the spectra taken of the flower before and after spiking with a terpene. As we have noticed throughout this study, there is no way to determine the type of terpene, only that terpene(s) was added. These concentrations are considerably lower than those expected to be seen in grown flower, so we believe there is a possibility for quantification of terpenes, albeit without the ability to distinguish terpene profiles.

Claims

CLAIMS What is claimed is:

1. A system for quantitating one or more cannabinoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising:

(i) a chemical analysis device configured to irradiate the sample with mid-infrared radiation to create a signal, and detect the signal to create a first output; and

(ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

2. The system of claim 1, wherein the sample is a ( /////c/A/.s-based sample.

3. The system of claim 1, wherein the Q//wa/v'.s-based sample is a fresh Cannabis plant.

4. The system of claim 1, wherein the sample is a fresh flower of a Cannabis plant.

5. The system of claim 4, wherein the fresh flower of a Cannabis plant is homogenized.

6. The system of claim 5, wherein the homogenized fresh flower of a Cannabis plant has a particle size of about 0.5 to about 2 mm.

7. The system of claim 5, wherein the homogenized fresh flower of a Cannabis plant has a moisture content of about 60 to about 90% by weight of water based on the total weight of the sample.

8. The system of claim 1, wherein the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹.

9. The system of claim 1, wherein second output comprises a calculated amount of the one or more cannabinoids within an error of ±20%.

10. The system of claim 1, wherein second output comprises a calculated amount of the one or more cannabinoids within an error of ±10%.

11. The system of claim 1, wherein the calculated amount is provided in units of weight percentage.

12. The system of claim 1, wherein the calculated amount is provided in units of parts per million.

13. The system of claim 1, wherein the spectral analysis model is a multivariate chemometric algorithm.

14. The system of claim 13, wherein the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, a partial least squares analysis, and a multivariate curve resolution.

15. The system of claim 1, wherein the one or more cannabinoids is selected from the group consisting of tetrahydrocannabinol, cannabigerol, cannabi chromene, tetrahydrocannabivarin, cannabidiol, cannabinol, cannabigerivarin, tetrahydrocannabivarian, cannabidivarin, cannabichromevarin, and carboxylic acid derivatives thereof.

16. The system of claim 1, wherein the first output is selected from the group consisting of absorbance, transmittance, and reflectance.

17. A method for quantitating one or more cannabinoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising:

(i) using a chemical analysis device to irradiate the sample with mid-infrared radiation to create a signal and detect the signal to create a first output; and

(ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more cannabinoids in the sample, thereby quantitating the one or more cannabinoids in the sample.

18. The method of claim 17, wherein the sample is a ( z/////aA/.s-based sample.

19. The method of claim 17, wherein the Q/////a/v.s-based sample is a fresh sample of a Cannabis plant.

20. The method of claim 17, wherein the fresh sample is a fresh flower of a Cannabis plant.

21. The system of claim 20, wherein the fresh flower of a Cannabis plant is homogenized.

22. The system of claim 21, wherein the homogenized fresh flower of a Cannabis plant has a particle size of about 0.5 to about 2 mm.

23. The system of claim 21, wherein the homogenized fresh flower of a Cannabis plant has a moisture content of about 60 to about 90% by weight of water based on the total weight of the sample.

24. The method of claim 17, wherein the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹.

25. The method of claim 17, wherein second output comprises a calculated amount of the one or more cannabinoids within an error of ±20%.

26. The method of claim 17, wherein second output comprises a calculated amount of the one or more cannabinoids within an error of ±10%.

27. The method of claim 17, wherein the calculated amount is provided in units of weight percentage.

28. The method of claim 17, wherein the calculated amount is provided in units of parts per million.

29. The method of claim 17, wherein the spectral analysis model is a multivariate chemometric algorithm.

30. The method of claim 29, wherein the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, and a partial least squares analysis, and a multivariate curve resolution.

31. The method of claim 17, wherein the one or more cannabinoids is selected from the group consisting of tetrahydrocannabinol, cannabigerol, cannabi chromene, tetrahydrocannabivarin, cannabidiol, cannabinol, cannabigerivarin, tetrahydrocannabivarian, cannabidivarin, cannabichromevarin, and carboxylic acid derivatives thereof.

32. The method of claim 17, wherein the first output is selected from the group consisting of absorbance, transmittance, and reflectance.

33. The method of claim 17, comprising quantitating the total cannabinoid content in the sample.

34. A system for quantitating one or more terpenoids in a sample comprising water in an amount of at least 15% by weight based on the total weight of the sample, the system comprising:

(ii) a computer that applies a spectral analysis model to analyze the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

35. The system of claim 34, wherein the sample is a ( z/////aA/.s-based sample.

36. The system of claim 34, wherein the ( z/////aA/.s-based sample is a fresh sample of a Cannabis plant.

37. The system of claim 34, wherein the fresh sample is a fresh flower of a Cannabis plant.

38. The system of claim 37, wherein the fresh flower of a Cannabis plant is homogenized.

39. The system of claim 38, wherein the homogenized fresh flower of a Cannabis plant has a particle size of about 0.5 to about 2 mm.

40. The system of claim 38, wherein the homogenized fresh flower of a Cannabis plant has a moisture content of about 60 to about 90% by weight of water based on the total weight of the sample.

41. The system of claim 34, wherein the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹.

42. The system of claim 34, wherein second output comprises a calculated amount of the one or more terpenoids within an error of ±20%.

43. The system of claim 34, wherein second output comprises a calculated amount of the one or more terpenoids within an error of ±10%.

44. The system of claim 34, wherein the calculated amount is provided in units of weight percentage.

45. The system of claim 34, wherein the calculated amount is provided in units of parts per million.

46. The system of claim 34, wherein the spectral analysis model is a multivariate chemometric algorithm.

47. The system of claim 46, wherein the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, a partial least squares analysis, and a multivariate curve resolution.

48. The system of claim 34, wherein the one or more terpenoids is selected from the group consisting of alpha thujene, alpha pinene, camphene, beta pinene, beta myrcene, p- mentha-l,5-diene, 3-carene, alpha terpinene, p-cymene, D-limonene, beta ocimene, terpinolene, linalool, fenchol, trans-2-pinanol, alpha terpineol, beta caryophyllene, gamma elemene, alpha bergamotene, humulene, caryophyllene oxide, 4,8,12-Tetradecatrienal, beta selinene, alpha selinene, alpha bulnesene, alpha famesene, beta maaliene, (4aR,8aS)-4a- Methyl-l-methylene-7-(propan-2-ylidene)decahydronaphthalene, cis nerolidol, trans nerolidol, Selina-3, 7(1 l)-diene, trans alpha bisabolene, beta guaiene, epi-gamma-eudesmol, longifolene, cis beta guaiene, aromandendrene, alpha eudesmol, alpha bulnesene, alpha bisabolol, juniper camphor, and beta bisabolene.

49. The system of claim 34, wherein the first output is selected from the group consisting of absorbance, transmittance, and reflectance.

50. A method for quantitating one or more terpenoids in a sample comprising at least 15% by weight water based on the total weight of the sample, the method comprising:

(ii) applying a spectral analysis model to analyze the transmittance of the first output to create a second output comprising a calculated amount of the one or more terpenoids in the sample, thereby quantitating the one or more terpenoids in the sample.

51. The method of claim 50, wherein the sample is a Q//waZv'.s-based sample.

52. The method of claim 50, wherein the Q//waZv'.s-based sample is a fresh sample of a Cannabis plant.

53. The method of claim 50, wherein the fresh sample is a fresh flower of a Cannabis plant.

54. The system of claim 53, wherein the fresh flower of a Cannabis plant is homogenized.

55. The system of claim 54, wherein the homogenized fresh flower of a Cannabis plant has a particle size of about 0.5 to about 2 mm.

56. The system of claim 54, wherein the homogenized fresh flower of a Cannabis plant has a moisture content of about 60 to about 90% by weight of water based on the total weight of the sample.

57. The system of claim 50, wherein the mid-infrared radiation comprises photons having a wavenumber of 4000 cm'¹ - 1000 cm'¹.

58. The method of claim 50, wherein second output value comprises a calculated amount of the one or more terpenoids within an error of ±20%.

59. The method of claim 50, wherein second output value comprises a calculated of the one or more terpenoids within an error of ±10%.

60. The method of claim 50, wherein the calculated amount is provided in units of weight percentage.

61. The method of claim 50, wherein the calculated amount is provided in units of parts per million.

62. The method of claim 50, wherein the spectral analysis model is a multivariate chemometric algorithm.

63. The method of claim 62, wherein the multivariate chemometric algorithm is selected from the group consisting of a principal component analysis, a principal component regression, and a partial least squares analysis, and a multivariate curve resolution.

64. The method of any one of claim 50, wherein the one or more terpenoids is selected from the group consisting of alpha thujene, alpha pinene, camphene, beta pinene, beta myrcene, p-mentha-l,5-diene, 3-carene, alpha terpinene, p-cymene, D-limonene, beta ocimene, terpinolene, linalool, fenchol, trans-2-pinanol, alpha terpineol, beta caryophyllene, gamma elemene, alpha bergamotene, humulene, caryophyllene oxide, 4,8,12- Tetradecatrienal, beta selinene, alpha selinene, alpha bulnesene, alpha famesene, beta maaliene, (4aR,8aS)-4a-Methyl-l-methylene-7-(propan-2-ylidene)decahydronaphthalene, cis nerolidol, trans nerolidol, Selina-3, 7(1 l)-diene, trans alpha bisabolene, beta guaiene, epi- gamma-eudesmol, longifolene, cis beta guaiene, aromandendrene, alpha eudesmol, alpha bulnesene, alpha bisabolol, juniper camphor, and beta bisabolene.

65. The method of claim 50, wherein the first output is selected from the group consisting of absorbance, transmittance, and reflectance.

66. The method of claim 50, comprising quantitating the total terpenoid content in the sample.