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In the first four installments of this calibration science series, we covered sources of error, signal-to-noise ratio (SNR), precision, accuracy, reducing noise, how to plot a calibration line, and how to measure calibration quality (1-4). In this, the fifth installment, we will continue the calibration quality control theme. Sometimes in a data set used to generate a calibration, one or more data points will stand out as being not like the others and these data points are called outliers. How to spot outliers and potential ways to correct them will be discussed here.

Back in the day on the American children’s show Sesame Street (5) they played the game “Which of These Things is Not Like the Others”. For example, they might show pictures of a duck, a hen, a pigeon, and a dog. In this case, the thing not like the others was the dog since it is a mammal and not a bird, making the dog an outlier. In calibration science spotting outliers is like this, spotting data points that are not like the others.

For our purposes we will limit ourselves to a discussion of outliers in the types of analyses performed in a cannabis analysis lab. Probably the most important thing measured in these labs is total tetrahydrocannabinol (THC) or potency. Two of the most common potency methods are high pressure liquid chromatography (HPLC) with ultraviolet-visible (UV-Vis) detection (6) and mid-infrared spectroscopy (7). In both these cases, spectral absorbance readings and concentration data are used to plot calibration lines. Thus, we will restrict our discussion to spotting concentration and spectral outliers.

A good way to spot concentration outliers is to first calculate a set of concentration residuals

 A concentration residual is the difference between the known and predicted concentration for a standard used in a calibration. This quantity is calculated using 

 is the concentration residual; C is the actual concentration; and C’ is the predicted concentration.

The concentration residual measures how well the concentration in a specific standard was predicted.

The next step in spotting concentration outliers is to plot the residuals versus sample number as seen in 

. The data in this case are for the isopropyl alcohol (IPA) calibration discussed in a previous column (4), thus the units of the residuals are volume percent IPA.

Under normal circumstances this plot should be a random scatter of points with no apparent structure and with the magnitude of all the residuals approximately the same. Note in the plot that for samples 1,3,4, and 5 the residuals are all right around 1% IPA, but that for sample 2 the residual is -15.9% IPA; this thing is certainly not like the others! This residual is 15 times bigger than the others.

Once we spot an outlier, the question we have to ask is whether to include that standard’s data in a calibration or not. Ideally, we need to find the assignable cause as to why something is an outlier. This term is statistics speak for the reason why something is an outlier. If we understand why something is an outlier, we can fix the problem or justify not using the data in a calibration.

In the case of sample 2 in Figure 1 the assignable cause was easy to find: I typed the wrong concentration value for sample 2 into the spreadsheet used to generate the calibration line. Correcting this typo gave the concentration residual plot seen in 

With the typo corrected the concentration residual for sample 2 was reduced from -15.9% IPA to 0.3% IPA, illustrating the power of concentration residual plots to improve calibrations.

There are a number of reasons why concentration outliers happen including:

1. Transcription Errors: In other words, typos. Often times the absorbance and concentration data for a calibration have to be typed into a spreadsheet or some other computer program. It is very easy to mess up the transcription of these numbers, i.e. to commit a typo. This is exactly what we saw with Figures 1 and 2 above.

2. Poorly made standards: In calibrations that use concentration data, the error in the known concentrations in the standards is often times the biggest source of error in the analysis, and lack of care and poor technique when making standards can condemn you to always having poor calibrations. Hence,anything you can do to improve the quality of known concentrations in your standards will pay dividends in calibration quality.

3. Sample Problems: If the concentration of the analyte in your standard changes between when you make the standard and when you measure its absorbance that is a problem. Things that can cause this to happen include reactions taking place within the sample, evaporation of the sample, or analyte precipitating out of the sample. A good way to check this problem is to monitor your standard samples over time. For instance, once you make a fresh standard measure its absorbance every few minutes, then hours, to see if it is stable or not.

Remember our calibration consists of concentration data and spectral absorbance data. Spotting concentration outliers involved calculating concentration residuals, similarly, spotting an outlier in the spectral absorbance data is done by calculating a spectral residual, the formula for which is seen in 

 is the spectral residual; A is the actual absorbance; and A’ is the predicted absorbance and where the actual and predicted absorbances may be peak heights or peak areas.

For the calculation of concentration residuals we had the predicted concentration, C’, already in our hands since we needed it to calculate calibration metrics. Where do we obtain the predicted absorbance? From the calibration line equation itself. The calibration line for our IPA method is seen in 

We discussed calibration lines in previous articles (1-4). Briefly, 0.165 is the slope of the calibration line, and -0.6834 is the 

-intercept. Since peak area (spectral absorbance) is on the 

-axis, if we know the concentration of any given IPA sample (X), we can calculate its corresponding peak area by plugging the concentration value into Equation 3 and then solving.

Now, to obtain the predicted peak area as needed for the spectral residual calculation we would use the predicted concentration as the X in Equation 3, and solving for Y would give us the predicted absorbance. The predicted absorbance represents the peak area the calibration says would correspond to a given predicted concentration.

For example, in Figure 2 the concentration residual for sample 1 is -1.4% IPA. The known concentration for sample 1 is 9% (4). If we rearrange Equation 1 we can solve for the predicted concentration as seen in 

In our example then C = 9%,
R = -1.4%, and the predicted concentration C’ is then 10.4%. To predict the peak area that corresponds to this concentration we set X = 10.4 in Equation 3 and to obtain 

to see that the predicted peak area that corresponds to a concentration of 10.4% IPA is 1.03. The right-hand column in 

 shows the measured peak areas for each IPA standard.

To calculate the spectral residual for the 5 standards used to determine the calibration line seen in Figure 3 one would repeat the exercise seen above for sample 1 for all 5 samples. This will yield a set of five spectral residuals. Like with concentration residuals, it is useful to plot spectral residuals versus sample number to look for outliers. Such a plot is seen in 

Note in Figure 4, that all the residuals are small, about the same magnitude, and do not have a discernible pattern. This is unlike Figure 1 where the sample with the concentration residual of -15.9% was clearly an outlier.

: Same as for concentration outliers, typos happen. This is the first thing to check when any outlier of any type is spotted.

: The peak height or area to be used in the calibration must be measured properly. More on that in a future column.

: Recall (1,2) that all measurements have noise/error, and this is true of spectra as well. Calibrations are always a garbage in/garbage out process, and noisy spectra will give inaccurate predicted concentrations. How to improve the SNR of spectra was discussed previously (1-4).

: Analytical instruments are finicky beasts and don’t always work properly leading to incorrectly measured data. Before using any analytical instrument for quantitative work make sure it has been calibrated, passed its quality control checks, and that you are following the method standard operating procedure (SOP) properly.

: If a molecule other than the analyte absorbs light at the same wavelength where we are measuring the peak height or area, this will interfere with the correct determination of the concentration of the analyte, hence the term interferents. Traditionally we dealt with interferents by making sure only the analyte contributed to the peak being used in the calibration. More recently, algorithmic methods known as chemometrics can get around the problem of interferents (8). However, this discussion is beyond the scope of this column series. Thus, for our purposes, it is important to choose a calibration peak that is known to be free of interferents.

: As always humans are fallible and make mistakes. Make sure the person using the instrument has been properly trained, the method has an SOP, and that it is followed properly.

What if There is No Assignable Cause for an Outlier?

This gets tricky. A data point may be an outlier because there is truly something wrong with the measurement, or it might contain information important for the calibration model that is not consistent with the other data points. Statisticians have spilled much ink as to what to do in this case, here is my rule of thumb based on my understanding of the literature. The first thing you should do is calculate the average of the residuals by using 

 is the average residual; i is the sample index; |R

| is the absolute value of an individual residual; and N is the number of residuals.

The purpose of using the absolute value is to keep positive and negative residual values from cancelling each other. For the five concentration residuals seen in Figure 2 their absolute values are 1.4, 0.3, 1.0, 0.2, and 0.9 % IPA, and their average is 0.76%.

In general, outliers whose residual is 10x that of the average can be discarded without an assignable cause, which would have been the case with the -15.6% concentration outlier, although we did find an assignable cause for it. Outliers of 3x or less should almost always be included in the calibration. The gray area is where the residual is >3x but <10x the residual average. In the absence of an assignable cause some judgement for these is needed. What I tend to do is remake the standard, measure its peak height or area, calculate its residual, and see if the residual value is reproducible. If so, I tend to keep this data point.

Outliers are data points in a calibration not like the others. They can be spotted by calculating residuals and plotting them versus sample number. Calculating the average residual and comparing it against individual residuals can be used to judge whether an outlier should be included or excluded from a calibration. Assignable causes of concentration and spectral outliers were discussed.

Smith, B., Calibration Science, Part I: Precision, Accuracy, and Random Error, 

Smith, B., Calibration Science, Part II: Systematic Error, Signal-to-Noise Ratios, and How to Reduce Random Error, 

Smith, B., Calibration Science, Part III: Calibration Lines and Correlation Coefficients, 

Smith, B., Calibration Science, Part IV: Calibration Metrics, 

https://en.wikipedia.org/wiki/Sesame_Street

Giese, M. E; Lewis, M. A.; Giese, L.; and Smith, K. M.; 

Smith, B., A Proposed Representative Sampling Plan for Hemp Grows, 

Quantitative Spectroscopy: Theory and Practice

Smith, B., Calibration Science, Part V: Spotting Outliers, 

, PhD, is Founder, CEO, and Chief Technical Officer of Big Sur Scientific. He is the inventor of the BSS series of patented mid-infrared based cannabis analyzers. Dr. Smith has done pioneering research and published numerous peer-reviewed papers on the application of mid-infrared spectroscopy to cannabis analysis, and sits on the editorial board of 

. He has worked as a laboratory director for a cannabis extractor, as an analytical chemist for Waters Associates and PerkinElmer, and as an analytical instrument salesperson. He has more than 30 years of experience in chemical analysis and has written three books on the subject. Dr. Smith earned his PhD on physical chemistry from Dartmouth College.
Direct correspondence to: 

Cannabis Analysis 

Here, we discuss how to spot outliers and potential ways to correct them in data sets.

Calibration Science, Part V: Spotting Outliers

In indoor cannabis cultivation, increasing lighting penetration is crucial to maximize yield and ensure quality and consistent phytochemical content. Many factors influence how light penetrates the canopy, impacting photosynthesis and overall plant growth. We discuss methods to increase plant canopy penetration for indoor cannabis cultivation, increasing crop size while enhancing cannabinoid, terpene, and flavonoid production.

Shortcomings of Lighting in Indoor Horticulture

In the realm of cannabis cultivation, sunlight remains unmatched in its ability to penetrate plant canopies effectively. Despite advancements in indoor lighting technologies, these systems fail to achieve the same depth and uniformity of light penetration that sunlight provides. The inadequacies of lighting penetration in indoor horticulture can be attributed to deficiencies in lighting intensity, spectrum, and distribution, as well as thermal management of the grow environment. Moreover, certain plant functions, such as tropisms, photoreceptor and pigment protein saturation and activation, adversely influence light penetration, affecting plant health in indoor cannabis operations. For the purposes of this discussion, this paper addresses the use of full-spectrum light emitting diodes (LEDs) lighting in indoor grow operations. Although the term “full-spectrum” is used, LED lighting systems fall short of delivering the true full spectrum of light delivered by the sun.

Lighting intensity is a critical factor that directly influences photosynthesis, impacting yield and phytochemical composition in cannabis cultivation. Cannabis plants require a specific light intensity range for optimal growth. Insufficient lighting can stunt growth, reduce biomass, and accelerate leaf shedding by impairing photosynthesis and hormone signaling. Excessive light intensity can cause photoinhibition, which damages the photosynthetic apparatus and induces a stress response. Interestingly, these stress responses are not always detrimental; in some cases, they can lead to the enhanced production of secondary metabolites. Since these responses occur at the subcellular level, they present significant challenges for study and analysis (1).

Lighting intensity, quantified in micromoles per square meter per second (µmol/m²/s), is a fundamental metric in cannabis cultivation. During the vegetative growth phase, cannabis plants typically require light intensities ranging from 400-600 µmol/m²/s. This requirement increases to approximately 600-900 µmol/m²/s during the flowering stage to support flower development and resin production.For reference, sunlight within the Photosynthetically Active Radiation (PAR) spectrum of 400-700 nanometers (nm), strikes the Earth at an intensity of around 2000 µmol/m

In contrast, LED lighting seldom achieves intensities exceeding 1000 µmol/m

/s at the plant canopy, and when it does, the lighting footprint provided is very limited. Several factors influence LED lighting performance, including the efficacy of the LEDs, typically measured in lumens per Watt (lm/W), and the ability to control lighting output to achieve uniform coverage with minimal waste. Although the efficacy of LEDs is improving, the theoretical maximum for full-spectrum LEDs stands at 300-400 lumens per Watt (2).

Incorrect lighting placement is a common issue in cultivation. LED lighting has an output that is either too wide causing “spill” or wasted light that doesn’t strike the plant canopy, or too narrow, providing adequate lighting to only a limited portion of the plant canopy. The height at which lights are mounted is a critical factor as well, especially with horticultural fixtures that were designed to be mounted very close to the plant canopy. For instance, one manufacturer recommends a mounting height of 8 in above the plant tops. If this distance is doubled, the light intensity, and therefore photon delivery, decreases by 75% (refer to the Inverse Square Law for Lighting). This demonstrates how small variations of just a few inches can significantly change lighting delivery.

“Lighting spectrum” refers to the wavelengths emitted by a light source, encompassing the visible light spectrum and extending into the ultra-violet (UV) and infrared (IR) regions. Blue light (400-500 nm) is essential for vegetative growth, regulating stomatal opening and chlorophyll synthesis. Red light (600-700nm) is pivotal in driving photosynthesis and influencing flowering and photomorphology. Far Red light (700-800nm) increases growth and helps to regulate photoperiod. Amber light peaks at 620 nm and provides protective properties, which we identify later.

Despite the high configurability of LED spectrum delivery by manufacturers, their ability to compete with natural sunlight in terms of intensity and spectrum remains constrained by high costs and current technological limitations. Nevertheless, LED technology has significantly advanced, offering superior capabilities that far outweigh those of more traditional horticultural lighting solutions, such as High Pressure Sodium (HPS), Metal Halide (MH) including Ceramic Metal Halide (CMH), and fluorescent technologies. It is now common knowledge that LED lighting produces higher quality cannabis in greater yields than the industry’s previously adopted lighting solutions.

The advantages of LED lighting stem from its ability to tailor the light spectrum to the specific needs of cannabis plants at different growth stages. This generally requires a combination of broad-spectrum and discrete frequencies to create an optimal light recipe for cannabis growth. This means some frequencies are underserved while some frequencies may provide too much light. The underserved frequencies lack the power to penetrate deep into the canopy and maximize yields. On the other hand, the overabundant frequencies can lead to photoreceptor and pigment saturation, causing plants to activate protective mechanisms or suffer from growth and quality issues.

An overabundance of light can lead to the saturation of photoreactive plant elements, which play vital roles in growth, development and stress responses of plants. These elements include pigments such as chlorophyll, carotenoids, anthocyanins and flavonoids, as well as photoreceptors like phytochromes, cryptochromes, phytotropins and UVR8.

Chlorophyll, the most crucial pigment in plants, is essential for photosynthesis, where it converts light energy into chemical energy, transforming water (H2O) and carbon dioxide (CO

). Excessive light can saturate chlorophyll, causing growth to plateau and potentially damage leaves. Photoinhibition results when the plant's photosynthetic machinery is overwhelmed, decreasing photosynthesis efficiency and energy production. Photoinhibition can also generate reactive oxygen species (ROS), including free radicals and peroxides, which may oxidize vital cellular components like proteins, lipids, and nucleic acids, leading to significant cellular damage or death (4).

Carotenoids are critical for protecting chlorophyll from photooxidation and facilitating non-photochemical quenching—a process that turns excess light energy into heat. If this pigment experiences light saturation, carotenoids can undergo photobleaching. This degradation results in the loss of their color, light absorption capabilities, and antioxidant functions (5).

Anthocyanins absorb blue-green and ultraviolet light, functioning as photoreceptive agents to mitigate cellular damage. Additionally, they also produce red and blue hues in plants. However, when these pigments become saturated, their protective properties diminish, potentially leading to altered or faded coloration within the plant tissues (6).

Flavonoids, a diverse group of phytonutrients, encompass various pigments including anthocyanins, and are renowned for their antioxidant properties. They play a vital role in neutralizing ROS and protecting plant cells from oxidative stress. Prolonged exposure to excessive light can cause flavonoids to become saturated and could damage enzymatic pathways. This may also disrupt their structural integrity and functionality thus affecting the overall plant health and resilience.

Phytochromes are photoreceptors that are sensitive to red and far-red receptors. Phytochromes help regulate processes such as seed germination, stem elongation, leaf expansion, and the timing of flowering in response to changes in light conditions. During seed germination, where they detect light quality and quantity, which is crucial for breaking seed dormancy and initiating growth. They are also able to detect the light environment, distinguishing between shaded and full light conditions. Furthermore, phytochromes are integral in photoperiodism, influencing the timing of flowering based on day length.

Cryptochromes are photoreceptors that are sensitive to blue-light and to ultraviolet-A (UV-A) radiation.They control several functions, including seedling development, flowering time, and circadian rhythms. They play a crucial role in enabling plants to gauge the overall quality of light, important for growth and development.

Phototropins, another group of blue-light responsive photoreceptors are primarily involved in mediating phototropism—the growth of plant organs towards or away from light. They influence chloroplast movement, stomatal opening, and possibly light-induced water uptake mechanisms.

The saturation of these photoreceptors can lead to a range of issues, from altered growth patterns and developmental timing to reduced photosynthetic efficiency and stress responses.

The following discusses the importance of maintaining high photosynthetic photon flux density (PPFD) levels for optimal plant growth and details strategies to maximize light penetration within a plant canopy effectively. It highlights various methods to ensure plants receive sufficient light without risking light saturation or damage, essential for achieving high yields and superior phytochemical content in cannabis.

High PPFD levels ensure that plants receive adequate light for maximum photosynthetic activity, leading to higher yields, and higher quality phytochemical content. However, maintaining an optimal PPFD without causing light saturation or damage is crucial to plant function.

Here are the primary methods for maximizing canopy penetration without harming plants:

Use LED Luminaires: LEDs can increase penetration due to their lower waste heat output, allowing them to be placed closer to the plant canopy without causing heat stress. If purchasing new lighting, make sure you have enough lights to cover your crop correctly. Adjust the power settings to meet the PAR requirements for all stages of growth. Purchasing LED fixtures that utilize Total Internal Reflective lensing will further increase PPFD and penetration with minimal wasted light.

Optimize Light Placement and Mounting Height: Arrange your lights to maximize coverage over your canopy with minimal spill and wasted light. Use enough light fixtures to cover your crop, then increase your luminaire density until PAR values required by your plants for their specific stage of growth are met. Use an LED-specific extended PAR lighting meter (400-750 nm) to verify accuracy of your setup.

Use Under Lighting: Not a common practice but worth mentioning is the use of under-lighting specifically designed to illuminate plants from below is worth considering. Though a costly endeavor, it may prove advantageous for high-end boutique cultivation operations. Great care must be taken to ensure these lighting fixtures are built for the task: they should be water and dust proof, possess excellent thermal management to prevent LEDs from overheating, and include robust electrical protection.

Adjust Lighting Intensity as Plants Grow: Increasing light intensity gradually as plants mature can maintain highest penetration possible while minimizing light stress. There are several methods to accomplish this:

1. Some LED fixtures have dimming capabilities, either manually adjusted or automatically tuned via various equipment and applications. 

2. Traditionally, non-LED lighting technologies have required manual adjustment of height for each light. This can become quite a chore if the operation uses many lights.

3. Automated light movers can be used for height adjustment, but their use is generally not recommended due to their high cost and potential maintenance challenges.

4. To accomplish this task with minimal capital and operational (labor) costs, it is highly recommended to place lights at a height far enough above the plants to cause them to “stretch” into the lighting. As plants stretch towards the light source, PAR values will increase. Once plants reach their maturity height, the lights may be raised or lowered to tune the PAR values. After the first few crops run in your facility, with known genetics and specific light fixtures, growers can usually place lights and never have to touch them again during the flowering stages.

Use Reflective Materials: Use reflective surfaces to bounce light under and around plant canopies. Flat white paint covering walls and flooring is inexpensive and helps spread light evenly. For those using grow trays, some manufacturers build them in flat white for this purpose.

Control Plant Density and Canopy Management: Regularly tend plants to manage canopy density and branch positioning. Techniques like topping, low-stress training (LST), and defoliation can help create a more open canopy, allowing light to penetrate deeper. This not only improves light penetration but also air circulation.

Monitor and Adjust Environment: Ensure temperature, humidity, and CO

 levels are optimized. Waste heat (energy converted to heat instead of light) can increase leaf temperature, so adequate ventilation and air conditioning may be necessary to keep temperatures within an ideal range (typically 70-85° F during the light period). Monitor this by ensuring proper Vapor Pressure Deficit (VPD) is maintained (7).

Using these spectrum strategies, you can further improve light penetration in an indoor cannabis operation, while minimizing the risk of light-induced stress or damage due to saturation.

Use Full-Spectrum LEDs: Full-spectrum LED lights attempt to replicate natural sunlight and provide a balanced spectrum that includes wavelengths that target the known photoreceptors and pigments. Although full spectrum LEDs cannot entirely replicate sunlight, they offer other advantages. These LEDs, which consist of blue base LED coated with an excitable phosphor material, provide smooth and continuous transitions across an extended PAR curve (usually 425-750 nm). Leaving no gaps in spectrum coverage is extremely beneficial to plants, particularly since most photobiologists agree that science is far from fully understanding a plant’s use of light.

Supplement with Discrete (targeted narrowband) Red and Far-Red Light for Flowering Cannabis: Adding discrete red and far-red lights can improve light penetration and stimulate deeper canopy growth due to their longer wavelengths. These wavelengths are absorbed less superficially and have fewer receptors than blue light, allowing them to reach further down into the plant, enhancing photosynthesis in lower leaves without the risk of light saturation. It is important to note that plant photosystems require only 1 or 2 blue photons to process a CO

molecule while the red end of the spectrum requires 8-10 photons to process CO

Make Sure Your LEDs Take Advantage of the Emerson Effect (9): By understanding and applying the Emerson Effect, cultivators can significantly improve both the efficiency of photosynthesis and the overall productivity of plant crops. The Emerson Effect is a phenomenon in photosynthesis whereby the rate of photosynthesis is significantly increased when red light (~660 nm) and far-red light (~730 nm) are provided simultaneously, compared to each light wavelength supplied alone. This effect highlights the synergistic interaction between two photosystems involved in the light-dependent reactions of photosynthesis: Photosystem I (PSI) and Photosystem II (PSII).

Optimizing lighting penetration in indoor cannabis cultivation is essential for maximizing yield and ensuring high-quality phytochemical content. While indoor lighting systems, particularly LEDs, offer significant advantages over traditional methods, they still face challenges in replicating the intensity and spectrum of natural sunlight. Effective strategies to enhance light penetration include proper light placement, utilizing full-spectrum LEDs, supplementing with red and far-red light, and employing reflective materials. Additionally, managing plant canopy and environmental conditions are crucial for achieving the best results. By implementing these techniques, cultivators can overcome the limitations of indoor lighting and improve both the productivity and quality of their cannabis crops.

Alves, P.; Magalhães, A.; Barja, P. The phenomenon of photoinhibition of photosynthesis and its importance in reforestation. 

Schubert, E. F. Solid-State Light Sources Getting Smart. 

McCree, K. J. The Action Spectrum, Absorptance and Quantum Yield of Photosynthesis in Crop Plants. 

https://doi.org/10.1016/0002-1571(71)90022-7

Mansoor, S.; Ali Wani, O.; Lone, J. K.; Manhas, S.; Kour, N.; Alam, P.; Ahmad, A.; Ahmad, P. Reactive Oxygen Species in Plants: From Source to Sink. 

Lima-Melo, Y.; Alencar, V. T. C. B.; Lobo, A. K. M.; Sousa, R. H. V.; Tikkanen, M.; Aro, E.-M.; Silveira, J. A. G.; Gollan, P. J. Photoinhibition of Photosystem I Provides Oxidative Protection during Imbalanced Photosynthetic Electron Transport in Arabidopsis Thaliana. 

Hildenbrand, Z. L.; Mendoza-Dickey, H.; Manes, R. Enhancing Anthocyanin Levels in Cannabis: Environmental Factors at Play. 

Mendoza-Dickey, H., Manes, R., & Hildenbrand, Z. L. Intensity and spectrum: The role of lighting in vapor pressure deficit. 

https://doi.org/10.1007/978-1-4612-6024-0

EMERSON, R. Dependence of yield of photo-synthesis in long wave red on wavelength and intensity of supplementary light. 

 is a research Professor at the University of Texas at El Paso, the principal founder of Inform Environmental, a partner of Medusa Analytical, and is a director of the Curtis Mathes Corporation (OTC:CMCZ). Direct correspondence to: 

 has a MS degree in Chemistry and is the founder of Green Matter Consulting. 

 is the CEO and CTO of the publicly-traded Curtis Mathes Corporation, where he specializes in the creation and manufacture of frequency-specific lighting for horticulture and phototherapy purposes.

Hildenbrand, Z., Mendoza-Dickey, H., Manes, R., Lighting Penetration in Indoor Cannabis Cultivation, 

The Cultivation Classroom

A look at how some cultivation methods are used to increase plant canopy penetrationfor indoor cannabis cultivation, increasing crop size while enhancing cannabinoid, terpene, and flavonoid production.


Lighting Penetration in Indoor Cannabis Cultivation

In this study, polysorbate 80 is used in homogenization of cannabis concentrates to first determine if this additive aids in the extraction of the cannabis extract matrix. Secondly, polysorbate 80 is then tested to see how well target organisms survive in the extraction environment. Through linear regression, it was found that not only does polysorbate 80 assist in the extraction of matrix into solution, but it also offers a suitable environment for select target organisms. Ultimately by referencing a modified Food and Drug Administration (FDA) Bacteriological Analytical Manual (B.A.M.) method of extraction, we as cannabis scientists can begin to merge the knowledge of preexisting microbiology with cannabis microbiology to aid in the safety of the consumer.

It has been estimated that by 2028, US adult-use cannabis sales may reach upwards of $56.9 billion (1). With growth comes new products to the marketplace and ultimately the responsibility for ensuring the safety of the finished product falls onto compliance laboratories. Although cannabis-containing products are illegal on a federal level, certain states have legalized them for medicinal or recreational use. Due to this, the regulatory framework governing cannabis testing is determined on a state-by-state basis (2). Detection methods are structured either on a detect/ non-detect whereas any amount of target will fail the product or a threshold system, wherein microorganisms may be detected, but as long as they are below the target threshold, they are considered safe for human consumption or use. In large quantities, it has been found that these categories of microorganisms can lead to harm if not properly tested for (3).

One of the more complex matrices to test for is cannabis extracts. These extracts are formulated by utilizing solvents and/or manual means to isolate cannabinoids and terpenes from the cannabis plant. The solvents employed in this extraction process include butane, propane, ethanol, or carbon dioxide (CO

) (4). Additionally, alternative solventless extraction methods are available. Apart from potential matrix interferences that may affect quality indicators of microorganisms due to high levels of cannabinoids, the matrix itself poses challenges in terms of weighing, extracting, and quantifying due to the consistency of the sample. Chapter 23 of the FDA Bacteriological Analytical Manual (B.A.M.) references the use of polysorbate 80 in the homogenization of solids, powders, and oil-based products to aid in the these matrixes coming into solution (5). The addition of surfactants to cannabis microbiology is not new science, but by leveraging existing knowledge in the field of microbiology, a modified FDA B.A.M. method was put to the test (11).

In this study, step-wise increasing percentages of polysorbate 80 were added to Butterfield’s phosphate buffer, resulting in a total volume of 9 ml (see 

) When following true FDA B.A.M. chapter 23, the preparation procedure is to “Aseptically remove and weigh 1 g sample into 20 x 150 mm screw-cap test tube containing 1 ml sterile Tween 80. Disperse product in Tween 80 with sterile spatula. Add 8 ml sterile MLB and mix thoroughly. This will be the 10-1 dilution,” (5). Due to the difficulty in handling the cannabis extract matrix, the sample was weighed into a 50 ml centrifuge tube and the Tween 80 was added to the tube. A sterile spatula was used to mix the concentrate and tween 80 together until mixed. Following mixing, 8 ml of sterile Butterfield’s phosphate buffer was added. The diluent was subsequently tested to address two key questions. The first question was whether the combination of polysorbate 80 and Butterfield’s phosphate buffer allowed the matrix to be effectively extracted into the solution. The second question was whether the mixture of polysorbate 80 and Butterfield’s phosphate buffer provided a suitable environment for microorganisms to thrive, enabling their quantification through culture-based methods in microbiology. Culture-based methods of quantification allow for living and viable organisms to grow on their selective media. For this to be accomplished the target organism must survive the environment that is used for extraction.

Target dilution was created by combining polysorbate 80 and Butterfields phosphate diluent to the desired percentage as described in Table II. Distillate was added to solution and appropriate test was conducted after.

 1 gram of the sample was weighed out to assess the effectiveness of polysorbate 80 in extracting matrix into the solution. In this study, the samples were subsequently diluted with Butterfield’s phosphate buffer and polysorbate 80, increasing stepwise by 1% from 0% to 10% of polysorbate 80 as described in Table II. Samples were conducted in triplicate. Once diluted, the samples were shaken and further diluted with methanol. Upon dilution, the samples were vialed, and cannabinoid concentration was determined via HPLC-UV, following a modified AOAC Official Method of Analysis 2018.11 (9). While broad-spectrum cannabinoids can be determined, ∆

-THC) was the only analyte plotted, as the cannabis distillate is primarily composed of this cannabinoid. Statistical analysis was conducted on ethanol extracted cannabis distillate, but additional solvent-based, and non-solvent concentrates are included.

 To assess the viability of polysorbate 80 as an suitable environment, target organisms as depicted in 

 were cultivated in single analyte cultures and aseptically added to one gram of cannabis distillate. The samples were then diluted with Butterfield’s phosphate buffer and polysorbate 80 as described in Table II. Once diluted, samples were prepared onto their respective media for quantification. Samples were replicated 8 times to conduct enough data points.

Rapid aerobic plate count petrifilm by 3M is a self-contained dehydrated media that facilitates the growth of bacteria aerobically for the purpose of enumeration. Plates of 1 mL of sample were pipetted to the center of the plate and pushed with a 3M spreader. These plates were incubated at 35 ±1°C for 48 ±2 hours. This was done in accordance with the instructions given by the manufacturer and AOAC recommendations (6). Following incubation, colony forming units (CFU) were counted as a measure of microbial survival. All target organisms aside from 

: Rapid yeast and mold petrifilm by 3M is a simple ready to use plate system with specialized antibiotics to facilitate the growth of only yeast and mold on the plate in a rapid manner. The plates of 1 mL of sample were pipetted to the center of the plate and pushed with a 3M flat spreader.These plates were incubated at 25 ±1°C for 60-72 hours (7,8). This was done in accordance with the instructions given by the manufacturer and AOAC recommendations. Following incubation CFU were counted as a measure of yeast survival.

TEMPO YM test comprises a vial of culture medium and a card specifically designed for this purpose. The culture medium is inoculated and then transferred to a YM-specific card, which contains 48 wells of three different volumes, simulating Most Probable Number (MPN) (10). Following inoculation, the plates are incubated according to the manufacturer’s instructions and AOAC recommendations (10). During the incubation period, any yeasts and molds present in the card metabolize the substrate in the culture medium, leading to the appearance of a fluorescent signal (10). This signal is detected by the TEMPO Reader instrument. The TEMPO MPN technology was selected for the quantification of 

 to avoid the issue of colony spreading on plates that may occur and alter results.

To determine associations between polysorbate 80 levels and microorganism counts, a series of linear regressions were fit, using percentage polysorbate 80 as the independent variable. Another linear regression was fit comparing Delta 9- concentration with polysorbate 80 levels, again using polysorbate 80 as the independent variable. Scatter plots indicated that the relationship between polysorbate 80 and 

 count was non-linear, so a quadratic term was added to the model for better fit. Significance was set a priori at 5%, and all analyses were conducted in R version 4.3.1.

In both the full data and the analysis data with removed values, there were positive correlation between polysorbate 80 percentage and ∆

Statistical analysis was conducted on cannabis distillate, alongside testing of five additional cannabis extracts to explore their relevance in both solvent and non-solvent based cannabis concentrates, as well as the varying types of solvents used in extract production. Bubble Hash is a solventless cannabis concentrate made by agitating cannabis plant material in ice water and filtering it through fine mesh screens. Budder is a cannabis concentrate made using a solvent extraction process, often with butane or CO

. Live Rosin is a solventless cannabis concentrate created by pressing freshly frozen cannabis flower or bubble hash to extract resinous trichomes. Rick Simpson Oil (RSO) is a full-spectrum cannabis extract made using a solvent extraction method, typically with ethanol or isopropyl alcohol. Sugar, also known as ‘sugar wax’ or ‘sauce’, is a cannabis concentrate with a crystalline, granular texture, produced through a combination of solvent extraction and purification techniques.

 (migula). A non-linear relationship was observed in 

, which was handled with the addition of a quadratic term to the model.

There was a significant association with polysorbate 80 percentage and concentration, with every percent increase of polysorbate 80 associated with a mean increase of 76 (95% CI: 43, 110) in the analysis data, and a mean increase of 159 (95% CI: 131, 188) in the full data.

There were no significant associations between polysorbate 80 levels and 

(migula). There was a significant association between polysorbate 80 and 

 count, with every percent increase in polysorbate 80 associated with a mean decrease of -2.1 (95% CI: -2.7, -1.5) in 

 count. Initially, the relationship between 

 and polysorbate was modeled with a linear fit. However, diagnostic residual plots indicated there was a non-linear relationship between 

 and polysorbate 80. Adding a quadratic term (the percentage of polysorbate 80 squared) led to a better fit. The new quadratic model indicates that increasing percentage of polysorbate 80 is associated with a mean decrease of -2.8 (95% CI: -4.2, -1.4) 

 count, but only up to a certain point. Around 6% polysorbate 80, higher percentages are associated with an increase in 

 count. However, these results are impacted by larger levels of missingness in 

count for polysorbate 80 percentages between 3-6%, and future research is needed to validate these findings. A linear regression without the quadratic term found no significant relationship between polysorbate 80 and 

As microbiologists, prioritizing customer safety drives our efforts to pull valuable resources from relevant matrices. This study is designed to address two key questions: firstly, whether polysorbate 80 can effectively extract cannabis distillate into solution when combined with Butterfield’s phosphate diluent, and secondly, whether increasing the concentration of polysorbate 80 maintains a conducive environment for microbial contaminants.

As the relative percentage of polysorbate 80 in the solution increases, there is a corresponding increase in the amount of ∆

). Based on this data, we can conclude that there exists a statistically significant relationship between the concentration of polysorbate 80 and the extraction of ∆

-THC, confirming the success of the extraction process in both solvent and non-solvent based concentrates.

Secondly, to determine the suitable environment for polysorbate 80 and Butterfield’s phosphate mixture, we evaluated the solution using five different target organisms shown in Table I. 

 showed no significant impact from the increasing concentration of polysorbate 80 (refer to 

, although non-significant upon initial assessment, warrants further investigation with additional data points, especially within middle concentrations, to observe and analyze any potential linear relationship (see Figure 3, Table IV). Lastly, increasing levels of polysorbate 80 demonstrated a decreasing effect on CFU count for 

 (refer to Figure 3, Table IV). At the time of this publication, only four states include 

 as a target organism for compliance testing (2). However, as regulatory frameworks evolve, it’s crucial to acknowledge potential biases in target organisms resulting from their extraction methods. Furthermore, this study employed culture-based microbiology methods, whereas current testing regulations for 

 favor a molecular approach for the detect/non-detect threshold. Additional research is warranted to ascertain the detectability of 

The concentrate matrix poses one of the most difficult challenges in the cannabis testing industry. From its sticky consistency to its high concentration of cannabinoids, this matrix stands out as truly unique. As microbiologists, our commitment to customer safety drives us to extract valuable insights from similar matrices, exploring whether they can offer solutions to enhance testing processes in cannabis. As cannabis laboratories, it’s imperative that we play our part in ensuring both the safety of our clients and the refinement of testing methodologies for these distinctive matrices.

Thank you to Method Testing Labs for allowing this research to be funded and conducted within its testing space.

Lamers, M.; Robertson, K.; Roberts, C. Projected US Legal Medical and Recreational Cannabis Market Size. MJBizDaily. 2023. 

https://mjbizdaily.com/us-cannabis-sales-estimates/

Dailey, S. Cannabis Microbial Testing Regulations by State. Medicinal Genomics. 2021. 

https://www.medicinalgenomics.com/cannabis-microbial-testing-regulations-by-state/

Upton, R.; Craker, L.; ElSohly, M.; Romm, A.; Russo, E.; Sexton, M. Cannabis Inflorescence: Cannabis spp.; Standards of Identity, Analysis, and Quality Control; American Herbal Pharmacopoeia, 2014.

Precisionextraction. The Ultimate Guide to Cannabis Extract. Precision Extraction Solutions. 2023. 

https://precisionextraction.com/2021/04/cannabis-extract-guide/

Food and Drug Administration. Bacteriological Analytical Manual. Chapter 23, Microbiological Methods for Cosmetics; 2001. 

https://www.fda.gov/food/laboratory-methods-food/bacteriological-analytical-manual-bam

AOAC. Official Method 2015.13: Enumeration of Aerobic Bacteria in Food Using 3M™ Petrifilm™ Rapid Aerobic Count Plate; First Action, 2015.

Neogen. Neogen Petrifilm Rapid Yeast and Mold Count Plate Interpretation Guide. https://multimedia.3m.com/mws/media/902046O/3m-petrifilm-rapid-ym-count-plate-interpretation-guide.pdf (accessed July 24, 2024).

Bird, P.; Flannery, J.; Crowley, E.; Agin, J.; Goins, D.; Jechorek, R. Evaluation of the 3M Petrifilm Rapid Yeast and Mold Count Plate for the Enumeration of Yeast and Mold in Food: Collaborative Study, First Action 2014.05. J. AOAC Int. 2014, 97 (6), 1760-1770.

Latimer, G. W., Jr., Ed. Official Methods of Analysis of AOAC INTERNATIONAL, 22nd ed.; AOAC Publications, 2023; online edn, January 4, 2023. 

https://doi.org/10.1093/9780197610145.001.0001

BIOMÉRIEUX. BIOMÉRIEUX Tempo YM (Yeast/Molds) Package Insert; BIOMÉRIEUX, January 2015

Repay, A.; Tarter, W. Optimal Dilution of Polysorbate (Tween) 20 for the Determination of Enterobacteria and Total Yeast and Mold on Cannabis Concentrate. Cannabis Science Technology, 2022, 5 (1), 16-20 .zrDGCQWR2RUJxnAAC9CXtJyCys?domain=cannabissciencetech.com. Accessed July 8, 2024.

, M.S., is currently serving as Laboratory Director of Method Testing Laboratories, a cannabis compliance testing laboratory located in Brandon, Florida. Since joining the cannabis testing community, Anthony has aimed to innovate and advance the field of cannabis microbiology by publishing peer-reviewed papers and contributing to method development through the AOAC Research Institute. Anthony currently sits on the Cannabis Analytical Science Program’s Expert Review Panel in Microbiology, oversees method development for Method testing labs for methods submitted to AOAC Research Institute, and sits on the Board of Directors for AOAC Southern Section. 

, M.S., is the Lead Microbiologist at Method Testing Laboratories. 

 is a microbiologist at Method Testing Laboratories. 

, M.S., is a data scientist for the University of Minnesota. 

 is a Data Science & Engineering Manager with a solid foundation in mathematics and data science. He earned his B.A. in Mathematics from Wabash College and is currently pursuing a Master’s in Data Science from Eastern University in Pennsylvania. John’s professional work involves leveraging data to drive strategic decision-making and innovation within the healthcare industry. Outside of his professional life, he thrives on adrenaline-pumping activities, whether it’s snowboarding, track racing, or competing with his cats to the fallen bag of cheese.

Repay, A., Grover, N., Shipman, R., Lang, J., and Tarter, W. Polysorbate 80: An Emulsifying Agent in Cannabis Concentrate Microbiology, 

Peer-Reviewed Article

This study shares how polysorbate80 can be used in homogenization of
cannabis concentrates to first determine if this additive aids in the extraction of the cannabis extract matrix and then testing to see how well target organisms survive in the extraction environment.

Polysorbate 80: An Emulsifying Agent in Cannabis Concentrate Microbiology

The regulatory landscape for hemp-derived cannabinoids is undergoing significant transformations, driven by both federal and state legislative actions. This article provides an analysis of current regulations and proposed changes that could impact the hemp industry. The 2018 Farm Bill initially provided a legal framework for hemp cultivation and the production of non-intoxicating cannabinoids. However, recent amendments to the 2024 Farm Bill paired with major regulatory changes on the state level seek to redefine hemp and increase regulations for hemp consumer goods. This article examines these regulatory shifts, their motivations, and the potential consequences for farmers, producers, and consumers in the hemp industry. The analysis underscores the need for balanced regulations that ensure product safety without stifling industry growth and innovation.

The hemp industry has seen substantial growth and transformation since the passage of the 2018 Farm Bill, which legalized the cultivation of hemp and the production of non-intoxicating cannabinoids like cannabidiol (CBD). As the industry matures, the regulatory environment continues to evolve, presenting both opportunities and challenges for stakeholders. This article aims to provide a comprehensive overview of the current and emerging regulations impacting hemp-derived cannabinoids, with a particular focus on recent legislative developments at the federal and state levels.

The Farm Bill is a comprehensive piece of legislation that governs an array of agricultural and food programs in the United States. These bills are typically passed every five years by the US Congress and are critical for setting the country’s agricultural and food policy. The Farm Bill encompasses a wide range of topics including farm subsidies, food assistance programs, agricultural conservation, rural development, and more.

The 2018 Farm Bill: A Foundation for Hemp

The 2018 Farm Bill marked a pivotal moment for the hemp industry, removing hemp (defined as cannabis with less than 0.3% tetrahydrocannabinol [THC]) from the list of controlled substances. This legislation allowed for the legal cultivation, processing, and sale of hemp and its derivatives, leading to a surge in the production and commercialization of hemp-derived products, particularly CBD.

: The bill federally legalized hemp, distinguishing it from cannabis based on its THC content.

: States and Native American tribes were required to submit hemp production plans for approval by the United States Department of Agriculture (USDA).

: The bill protected the interstate commerce of hemp and hemp products, preventing states from prohibiting the transportation of legally produced hemp.

Building on the framework established by the 2018 Farm Bill, the 2024 Farm Bill introduces several amendments aimed at addressing regulatory gaps and ensuring the safety and quality of hemp-derived products. These amendments reflect growing concerns over the rapid expansion of the hemp industry and the need for more robust oversight.

: The 2024 Farm Bill proposes a redefinition of hemp to include not only the plant itself but also any derivatives, extracts, and cannabinoids, regardless of their THC content, as long as the final product contains less than 0.3% THC.

Enhanced Testing and Labeling Requirements

: To ensure consumer safety, the bill mandates rigorous testing for contaminants and accurate labeling of hemp-derived products.

This article provides an analysis of current regulations and proposed changes that could impact the hemp industry.

July/August 2024

Cannabis Science and Technology July/August 2024 Interactive Digital Edition

Calibration Science, Part V: Spotting Outliers

Lighting Penetration in Indoor Cannabis Cultivation

Polysorbate 80: An Emulsifying Agent in Cannabis Concentrate Microbiology

Current and Emerging Regulations for Hemp-Derived Cannabinoids: Implications for the Hemp Industry

Cannabis Packaging 101: Sustainable Innovations and Challenges