Cannabis terpene content rapid analysis method based on glandular hair density

Abstract

The invention provides a rapid cannabinoid content analysis method based on glandular hair density, and belongs to the technical field of content detection. Comprising the following steps: collecting high-definition glandular hair pictures of industrial hemp flowers and leaves, and calculating glandular hair density and cannabinoid content data in the industrial hemp flowers and leaves; carrying out correlation analysis by utilizing the two kinds of data to obtain a correlation model of the cannabinoid content and the glandular hair density in the industrial cannabis sativa flowers and leaves; calculating the glandular hair density of the industrial cannabis sativa floral leaf to be detected through the high-definition glandular hair picture, and substituting the glandular hair density into the correlation model of the cannabis sativa terpene content and the glandular hair density to quickly obtain the cannabis sativa terpene content in the industrial cannabis sativa floral leaf to be detected. The detection method is rapid, accurate and simple to operate, does not need any expensive precision equipment, only needs to shoot several high-definition glandular hair pictures, is suitable for real-time data detection of cannabinoid on site in field planting, is short in time from sample picture acquisition to data acquisition, and greatly improves the cannabinoid detection efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of content detection, and particularly relates to a rapid analysis method for the content of cannabis terpenes based on glandular hair density. Background Art

[0002] Cannabis terpenes are actually aromatic oils, secreted by the same gland that produces cannabinoids (such as cannabidiol (CBD), tetrahydrocannabinol (THC)), and can give cannabis varieties unique flavors such as citrus, berries, mint, pine, etc. Like cannabinoids, cannabis terpenes can bind to receptors in the human body and play a role. For example, linalool can promote relaxation and relieve stress, and limonene can improve attention and acuity.

[0003] Currently, more than 100 different terpenes have been identified in cannabis plants. β-Caryophyllene is one of the most common and abundant major active terpene components in cannabis plants. Previous pharmacological studies have shown that β-caryophyllene has effects such as local anesthesia, anti-inflammatory, anthelmintic, anti-anxiety, and anti-depressant. And β-caryophyllene has low water solubility and high affinity for cell membranes, and is a selective agonist of the known cannabinoid receptor CB2. Its effects include regulating cytokine release inside and outside the central nervous system, immune cell migration, and protection against thermal stimulus nociception. β-Caryophyllene also has good drug synergistic effects with phytocannabinoids, acting together on the CB1 and CB2 receptors of the endogenous cannabinoid receptor system in the human body to exert various physiological activities.

[0004] α-Bisabolol is a naturally occurring sesquiterpene alcohol with various pharmacological effects such as anti-inflammatory, anti-tumor, analgesic, anti-parasitic, anti-Alzheimer's, and kidney protection, and has great development value and clinical application prospects.

[0005] In order to develop the medicinal properties of terpenes in industrial hemp, it is necessary to breed industrial hemp varieties with high terpene content. And during this breeding process, the detection of terpene content is essential.

[0006] Traditional methods for determining the content of cannabis terpenes include gas chromatography, gas chromatography-tandem mass spectrometry, high performance liquid chromatography, etc. These determination methods have problems such as expensive instrument equipment, high technical requirements, large workload of sample processing, and the need for professional operation. Moreover, the organic solvents used in the extraction and determination processes will cause environmental pollution and cannot meet the need for obtaining cannabis terpene content data in the field. Therefore, it is necessary to develop a more convenient, environmentally friendly, and rapid method for determining cannabis terpenes. Summary of the Invention

[0007] The object of the present invention is to propose a rapid analysis method for the content of cannabinoids based on glandular hair density. The present invention is provided to solve the problems of high equipment investment, complex detection steps, and long data feedback time in the determination of the content of cannabinoids in industrial hemp flowers and leaves by using techniques such as gas chromatography and high-performance liquid chromatography analysis. It provides a method for rapidly determining the content of cannabinoids in industrial hemp flowers and leaves based on the analysis of glandular hair density in hemp flowers and leaves.

[0008] Glandular hairs mainly secrete and store some secondary metabolites, and their secretions mainly include aroma substances of some spice crops and certain phenolic and aldehyde substances with certain characteristics. Cannabinoid substances are generally synthesized and accumulated in glandular hairs, and the content of cannabinoids is closely related to the number of glandular hairs per unit area (i.e., glandular hair density). The glandular hair density of industrial hemp generally shows that female plants are richer than male plants, and among female plants, the glandular hairs are most dense in parts such as seed bracts, flowers, and young leaves. Moreover, the glandular hair density of industrial hemp varies at different growth and development stages.

[0009] The technical solution of the present invention is realized as follows:

[0010] The present invention provides a rapid analysis method for the content of cannabinoids based on glandular hair density, including the following steps:

[0011] S1. Collect high-definition glandular hair pictures of industrial hemp flowers and leaves and calculate the glandular hair density, as well as the data of the content of cannabinoids in industrial hemp flowers and leaves;

[0012] S2. Use the above two kinds of data for correlation analysis to obtain a correlation model between the content of cannabinoids and glandular hair density in industrial hemp flowers and leaves;

[0013] S3. Calculate the glandular hair density of the industrial hemp flowers and leaves to be measured through high-definition glandular hair pictures, and substitute it into the above-mentioned correlation model between the content of cannabinoids and glandular hair density to quickly obtain the content of cannabinoids in the industrial hemp flowers and leaves to be measured.

[0014] As a further improvement of the present invention, the high-definition glandular hair pictures in step S1 include high-definition glandular hair pictures of seed bracts, flowers, and leaf parts.

[0015] As a further improvement of the present invention, the high-definition pictures in step S1 are obtained through at least one of the following imaging tools: a high-resolution mobile phone camera, an external high-power lens, or a stereomicroscope.

[0016] As a further improvement of the present invention, the number of high-definition glandular hair pictures of the same sample in step S1 is 6 - 12.

[0017] As a further improvement of the present invention, the unit of the glandular hair density in step S1 is number / cm 2 。

[0018] As a further improvement of the present invention, the glandular hair density data in step S1 is the average value of the number of glandular hairs in multiple high-definition glandular hair pictures of each part of the flower and leaf.

[0019] As a further improvement of the present invention, the content data of cannabinoids in the industrial hemp flower and leaf in step S1 is detected by gas chromatography.

[0020] As a further improvement of the present invention, the quantitative method adopted for the content data of cannabinoids in the industrial hemp flower and leaf in step S1 is the external standard method.

[0021] The present invention has the following beneficial effects: A method for rapidly determining the content of cannabinoids in industrial hemp flower and leaf based on the analysis of glandular hair density in the hemp flower and leaf is provided. This detection method is rapid, accurate, simple to operate, and does not require any expensive precision equipment. Only a few high-definition glandular hair pictures need to be taken, and it is suitable for on-site real-time data detection of cannabinoids in field planting. The time from sample picture collection to data acquisition is short, greatly improving the detection efficiency of cannabinoids. Description of the Drawings

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 It is the glandular hair diagram of the industrial hemp flower and leaf in Example 1;

[0024] Figure 2 It is the glandular hair diagram of the industrial hemp flower and leaf in Example 2;

[0025] Figure 3 It is the glandular hair diagram of the industrial hemp flower and leaf in Example 3;

[0026] Figure 4 It is the correlation diagram between the predicted value and the measured value of the β-caryophyllene content of the sample to be tested;

[0027] Figure 5 It is the correlation diagram between the predicted value and the measured value of the α-bisabolol content of the sample to be tested. Detailed Embodiments

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0029] Example 1:

[0030] I. Use a stereomicroscope to collect high-definition trichome pictures of industrial hemp flowers and leaves ( Figure 1 ) and calculate the trichome density (75.9 ± 9.8 per cm 2 ), as well as the measured data of β-caryophyllene (0.16 ± 0.06 mg / g) and the measured data of α-bisabolol content (0.21 ± 0.01 mg / g) in industrial hemp flowers and leaves.

[0031] II. Use the above two types of data for correlation analysis to obtain a correlation model between the cannabinoid terpene content and the trichome density in industrial hemp flowers and leaves.

[0032] III. Calculate the trichome density of the industrial hemp flowers and leaves to be tested through the high-definition trichome pictures, and substitute it into the above correlation model between the cannabinoid terpene content and the trichome density to quickly obtain the cannabinoid terpene content in the industrial hemp flowers and leaves to be tested.

[0033] Example 2:

[0034] I. Use a mobile phone camera to collect high-definition trichome pictures of industrial hemp flowers and leaves ( Figure 2 ) and calculate the trichome density (320.1 ± 30.4 per cm 2 ), as well as the measured data of β-caryophyllene content (0.72 ± 0.04 mg / g) and the measured data of α-bisabolol content (0.83 ± 0.02 mg / g) in industrial hemp flowers and leaves.

[0035] II. Use the above two types of data for correlation analysis to obtain a correlation model between the cannabinoid terpene content and the trichome density in industrial hemp flowers and leaves.

[0036] III. Calculate the trichome density of the industrial hemp flowers and leaves to be tested through the high-definition trichome pictures, and substitute it into the above correlation model between the cannabinoid terpene content and the trichome density to quickly obtain the cannabinoid terpene content in the industrial hemp flowers and leaves to be tested.

[0037] Example 3:

[0038] I. Use an external high-power lens to obtain high-definition trichome pictures of industrial hemp flowers and leaves ( Figure 3 ) and calculate the trichome density (160.3 ± 17.2 per cm 2), and the measured data of β-caryophyllene content (0.29±0.02mg / g) and the measured data of α-bisabolol content (0.31±0.01mg / g) in industrial hemp flowers and leaves.

[0039] Second, use the above two sets of data for correlation analysis to obtain the correlation model between the content of cannabinoids and glandular hair density in industrial hemp flowers and leaves.

[0040] Third, calculate the glandular hair density of the industrial hemp flowers and leaves to be measured through high-definition glandular hair pictures, and substitute it into the above correlation model between the content of cannabinoids and glandular hair density to quickly obtain the content of cannabinoids in the industrial hemp flowers and leaves to be measured.

[0041] Extract the volatile oil from industrial hemp by steam distillation method. The specific operation refers to the "Method A for Determination of Volatile Oils" in General Chapter 2204, Volume IV of the Chinese Pharmacopoeia 2020 Edition (ChP2020). Weigh 5g of industrial hemp flowers and leaves, place them in a round-bottom flask, add 40mL of water, and extract by steam distillation at 160°C for 5h. Collect the volatile oil and determine the content of cannabinoids in it.

[0042] Chromatographic conditions: HP-5 column (0.32mm×30m×0.25μm); carrier gas is high-purity nitrogen; carrier gas flow rate is 2.0mL / min; split ratio is 2:1; injection volume is 1μL; injection port temperature is 250°C; detector temperature is 250°C; air flow rate is 400mL / min; hydrogen flow rate is 40mL / min; tail gas blow volume is 10mL / min; column temperature is programmed temperature rise, initial temperature is 60°C, hold for 2min, rise to 120°C at 20°C / min, rise to 146°C at 2°C / min, hold for 1min, rise to 160°C at 20°C / min, hold for 1min, and post-run at 280°C for 10min.

[0043] The standard curve equation of β-caryophyllene is y = 220378x, R 2 = 0.9996;

[0044] The standard curve equation of α-bisabolol is y = 173337.18x, R 2 = 1.00.

[0045] Determine the content of cannabinoids in 100 samples by the above method, and predict the content of cannabinoids through the correlation model between glandular hair density and cannabinoid content. The comparison between the two is as Figure 4 and Figure 5As shown. The correlation between the measured value of β-caryophyllene and the predicted value of β-caryophyllene is 0.929, and the correlation between the measured value of α-bisabolol and the predicted value of α-bisabolol is 0.8763, with high prediction accuracy, indicating that the model can be used for the rapid judgment and preliminary screening of the content of cannabis terpenes in industrial hemp flowers and leaves.

[0046] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A rapid analysis method for cannabis terpene content based on glandular hair density, characterized in that: The following steps are involved: S1. Collect high-definition glandular hair images of industrial hemp flowers and leaves and calculate the density of glandular hairs, as well as the content of cannabis terpenes in industrial hemp flowers and leaves; S2. Using the above two data to conduct correlation analysis, a correlation model between the content of cannabis terpenes in industrial hemp flowers and leaves and the density of glandular hairs was obtained; S3. The glandular hair density of the industrial hemp flowers and leaves to be tested is calculated through high-definition glandular hair images, and the density of the glandular hairs is substituted into the above-mentioned correlation model between the cannabis terpene content and the glandular hair density to quickly obtain the cannabis terpene content in the industrial hemp flowers and leaves to be tested.

2. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 1, characterized in that: The high-definition glandular hair images in step S1 include high-definition glandular hair images of seed bracts, flowers, and leaves.

3. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 2, characterized in that: The high-definition picture in step S1 is obtained by at least one of the following camera tools: a high-resolution mobile phone camera, an external high-power lens, or a stereo microscope.

4. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 1, characterized in that: The number of high-definition glandular hair images of the same sample in step S1 is 6-12.

5. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 1, characterized in that: The unit of the glandular hair density in step S1 is pieces / cm 2 .

6. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 5, characterized in that: The glandular hair density data in step S1 is the average value of the number of glandular hairs in multiple high-definition glandular hair pictures of various parts of the flower and leaves.

7. The rapid analysis method of cannabis terpene content based on glandular hair density according to claim 1, characterized in that: In step S1, the cannabis terpene content data in the industrial hemp flowers and leaves are detected by gas chromatography.

8. The method for rapid analysis of cannabis terpene content based on glandular hair density according to claim 1, characterized in that: The quantitative method used for the cannabis terpene content data in the industrial hemp flowers and leaves in step S1 is the external standard method.

Images