Hemp Descriptors version 1, archived 2023-02-16 |
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USDA Hemp Descriptor and Phenotyping Handbook
Zachary Stansell, Anya Osatuke
30-Sep-2021
ABOUT
The USDA Hemp Descriptor and Phenotyping Handbook was undertaken with the following objectives:
- To assist breeders and researchers in identifying accessions with specific traits to facilitate germplasm selection within hemp (Cannabis sativa L.) improvement programs.
- To identify gaps in the existing hemp collections and help formulate strategies for future collection and conservation efforts.
- To designate and maintain a core collection of critical materials.
- To increase NPGS user utility and accessibility to hemp germplasm and associated data.
- To identify duplicate accessions and reduce costs of hemp genetic resource conservation.
The methods and protocols are based on peer-reviewed literature and/or crowd-sourced from the hemp community. The robust, reliable, and high-dimensional data generated from these phenotyping efforts will empower conservation of hemp genetic diversity and aid selection of materials with unique trait combinations for breeding programs.
We have attempted to compile a list of standardized characterization and evaluation methods to capture passport information and to quantify morphology, horticultural and agronomic quality, pathogen resistance, and metabolic profile. This document can be used a reference to standardize phenotypic data collection across the broader pool of hemp germplasm and will be updated periodically as better methodologies become available.
The information gained from these phenotyping efforts will be digitally stored and made publicly available within GRIN-Global alongside the hemp germplasm held within the Plant Genetic Resources Unit (PGRU) in Geneva, NY.
PGRU coordinates hemp germplasm collection and exchanges from domestic and foreign sources. Information related to plant genetic resources increases usefulness to diverse stakeholders. Phenotypic data can be collected either by the curator during routine multiplication or by collaborators during collection, germplasm screening, or breeding experiments. PGRU asks germplasm recipients or donors to provide as much data associated with these materials as possible.
Collected data can be stored in a spreadsheet using the trait_name
as column headings and PUID
as row names. This document can then be emailed to zachary.stansell@usda.gov for inclusion into GRIN-Global.
The authors gratefully acknowledges the critical review, editing, and the numerous suggestions for improvements made by Olivia Aldin, Masoume Amirkhani, Anthony Barraco, Gary Bergstrom, Mark Berhow, Peter Bretting, Mark Bridgen, Kadie Britt, Zachary Brym, Carlyn Buckler, Ali Cali, Brian Campbell, Craig Carlson, Jeffrey Carstens, Ernst Cebert, David Chalkley, Chengci Chen, Alyssa Collins, Whitney Cranshaw, Randy Crowl, Heather Darby, David Dierig, Jorge de Silva, Chris Delhom, Sadanand Dhekney, Shelby Ellison, David Fang, David Gang, Nicholas Genna, Heather Grab, Jason Griffin, Kelly Gude, Joshua Havill, Yu Jiang, Nick Kaczmar, Joanne Labate, Michael Loos, Jessica Lubell-Brand, Tyler Mark, Victoria Meakem, Virginia Moore, Jay Noller, Bear Reel, Andrew Ristvey, Savanna Shelnutt, Chris Smart, Lawrence Smart, George Stack, Jeffrey Steiner, Conor Stephen, Alan Taylor, Jacob Toth, Daniela Vergara, and Don Viands.
The drawing on the front cover is used with permission by Anya Osatuke. Kadie Britt provided many primary source images and text for the invertebrate section. Craig Carlson provided original figures, methods, and many ideas. Jacob Toth, Joshua Havill, Savanna Shelnutt, Brian Campbell, Shelby Ellison, and Jeffrey Carstens provided many helpful comments, references, protocols, and edits. We have tried to acknowledge everyone who’s helped with this work, but any omissions are solely Zachary Stansell’s fault.
This work has drawn heavily on input from the Cornell Hemp Stakeholder Survey. Please take the survey if you have not already done so.
Please contact zachary.stansell@usda.gov with any questions, comments, remarks, or ideas.
The United States Department of Agriculture (USDA) prohibits discrimination in its programs on the basis of race, color, national origin, sex, religion, age, disability, political beliefs, and marital or familial status. Not all prohibited bases apply to all programs. Persons with disabilities who require alternative means for communication of program information (Braille, large print, audiotape, etc.) should contact the USDA Office of Communications at (202)720-5881 (voice) or (202)720-7808 (TOO). To file a complaint, write to the Secretary of Agriculture, U.S. Department of Agriculture, Washington, DC 0250, or call (202)720-7327 (voice) or (202)720- 1127 (TOO). USDA is an equal employment opportunity employer.
Editors
- Zachary Stansell (Hemp Curator, USDA-ARS, Plant Genetic Resources Unit)
- Anya Osatuke (Cornell Cooperative Extension)
Boxes
This document uses several special colored text boxes:
Phenotype/Descriptor
trait_name
[datatype; units]
elevation_meters
[decimal; m]
Elevation of collecting site above sea level.
🧪Phenotyping Protocol🧪
Seed germination
- 10 waterproof trays
- Sterile water-holding material (cotton wool, paper towels)
- 200 seeds, stored between 4 to 56 weeks…
📐Equation📐
Percent moisture may be calculated as:
\(\frac{(wet - dry)}{wet} \times 100\%\)
📜List📜
Invertebrate pests
- Acherontia atropos
- Aculops cannabicolus
- Aecidium cannabis
- …
📚Additional References📚
One of the earliest publications lauding hemp was “The Praise Of Hemp Seed” by John Taylor (1620).
Keywords
- hemp
- Cannabis sativa L.
- germplasm
- phenotype
- trait
- characterization
- evaluation
- USDA
- ARS
- NPGS
- PGRU
Language
GRIN-Global supports displaying data in multiple languages for system-level data. That is, if the system requires text to be displayed that is not actual GRIN-Global data, that text should be in the appropriate language for the current user. This is accomplished by using a table ending with _lang
as a child table.
Data types & units
datetime
A datetime data type that can handle time in nanoseconds and has a year range extending from the year “0001” to “9999.”
decimal
The decimal data type can store a maximum of 38 digits, all of which can be to the right of the decimal point. The decimal data type stores an exact representation of the number; there is no approximation of the stored value.
int
The integer data type is stored as a 4-byte integer; numeric values can range from \(-2^{31}\) through \(2^{31} – 1\).
nvarchar
An nvarchar field can store a string of text characters (maximum 4,000). The “n” in nvarchar means uNicode. “varchar” is an abbreviation for variablelength character string. Essentially, nvarchar is variable text field that supports two-byte characters, therefore capable of handling non-English symbols.
Units
All units are SI unless otherwise indicated.
PASSPORT
An accession consists of seed or plant material representing a sample of a single species, collected at a single time and location. An accession may be a sample of multiple plants found at the same location at the same time, or it may be collected from a single individual. By default, NPGS will retain different samples of a putative cultivar/population as discrete inventories nested within the Plant Introduction accession.
Accession
taxonomy_species_id
[nvarchar]
Scientific name of accession linking the accession record to its taxonomy parent (genus / species). Modified from GRIN-Global. Subtaxon may be included:
- ‘subsp.’ (subspecies)
- ‘var.’ (variety; not the same as the breeder’s named variety [uniform & stable product of breeding] or cultivar.)
- ‘f.’ (form)
- ‘group’ (botanical variety not cultivar name )
PUID
[nvarchar]
If persistent, unique identifier has been previously assigned, report. Assigned to one accession to be unambiguously referenced at the global level, with associated information aggregated via automated means. Genebanks not applying a true PUID should use a combination of Institute Code, Accession Number, and the Genus as a globally unique identifier. Modified from Bioversity International, FAO (2015).
improvement_status
[nvarchar]
Short paragraph. If known, elaborate on material improvement status, e.g., wild, landrace, breeding material, hybrid, founder stock, colonal selection, mutant, polyploid, mapping population, transgenic, etc.
plant_name
[nvarchar]
Top name assigned to display (sometimes referred to as the top name), typically given by farmer, breeder, seed-saver. Cultivar name is a possible type of top name. If in non-Latin alphabet, provide original spelling alongside a Latin-alphabet transliteration in remarks. Modified from GRIN-Global and Bioversity International, FAO (2015).
accession_pedigree
[nvarchar]
Description of plant pedigree, if known, e.g.:
- “Selection from ‘Carmagnola’”
- ‘Beniko’/‘Carmagnola’//‘Futura 75’///‘Carmaleonte’/‘Felina 32’//‘Futura 75’ * “Mutation found in ‘Beniko’”
ploidy
[int]
Record ploidy if known. If mixoploid or other, elaborate in passport_remarks
. See Adriel Garay and Sabry Elias (1998).
accession_ipr
[nvarchar]
State PVP registration status, if applicable. U.S. Link.
Varieties may also be protected by a U.S. Plant Patent (e.g. CW2A
) or Utility Patent and/or Plant Breeder’s Right from a UPOV country; e.g., Canada.
- US patents search
- UPOV requires account to search Variety Database.
- Canada
crop_use
[nvarchar]
Explain crop use(s); e.g., oil, fiber, secondary metabolite, ecosystem services.
Germplasm source
source_cooperator_id
[nvarchar]
Field associating the cooperator (person or organization) who was the source of the germplasm.
collector_cooperator_id
[nvarchar]
Indicating the individual collecting sample.
developer
[nvarchar]
List the name of the organization (or person) that bred the material.
Sampling & location
Modified from S-1084 Collection Protocols, GRIN-Global, personal conversations with hemp researchers, and Bioversity International, FAO (2015) standards.
number_plants_sampled
[int]
Number of plants sampled to collect the accession material ( S-1084 Collection Protocols).
source_date
[datetime]
Date when germplasm is collected from source material ( S-1084 Collection Protocols).
geography_id
[nvarchar]
The internal geographic identifier indicating the cooperator’s country and state ( S-1084 Collection Protocols).
elevation_meters
[decimal; m]
Elevation of collecting site above sea level ( S-1084 Collection Protocols).
latitude
& longitude
[decimal]
Latitude and longitude in decimal degree format. The format is 10 integers and 8 decimals. Positive values are east of the Greenwich Meridian; negative values are west of the Greenwich Meridian ( S-1084 Collection Protocols).
coordinate_method
[nvarchar]
Georeferencing method used (e.g.; GPS, map, estimated). Modified from Bioversity International, FAO (2015).
uncertainty
[decimal; m]
Maximum coordinate uncertainty radius.
georeference_datum
[nvarchar]
Geodetic datum/spatial reference system; WGS84 datum is preferred.
accession_inv_voucher_note
[nvarchar]
If applicable, include additional voucher information.
ARCHITECTURE
Unless stated otherwise, measure plant architecture traits as the mean of 10 unpruned plants during week of harvest. Samples submitted to NPGS will be evaluated by a USDA-ARS laboratory using similar protocols as described below.
Morphology
Architectural traits modified from Carlson et al. (2021).
ht
[decimal; cm]
Height of the stem from the ground to tip apical inflorescence, modified from Carlson et al. (2021).
mcd
[decimal; cm]
Maximum canopy diameter (mcd
) as width of plant at widest set of branches, see Carlson et al. (2021). Measured from widest tip to tip without stretching branches. Include flowering tissue in measurement.
mcdh
[decimal; cm]
Height evaluated at maximum canopy diameter (mcdh
) from ground to max canopy diameter, see Carlson et al. (2021).
trkl
[decimal; cm]
Trunk length (trkl
) is evaluated as distance from ground to first branch. See Carlson et al. (2021).
inl
[decimal; cm]
Average internode length (inl
) is calculated between internodes along the primary stem (50 cm max, see diagram). See Carlson et al. (2021).
kite_hypot
[decimal; cm]
See Carlson et al. (2021).
kite_perimeter
[decimal; cm]
See Carlson et al. (2021).
kite_area
[decimal; \(m^2\)]
See Carlson et al. (2021).
ba
[decimal; (0°-180°)]
Kite branch angle ba
is calculated from the lower kite triangle, using the difference of maximum canopy diameter height and trunk length. See Carlson et al. (2021).
branches
[int]
Number of branches
per plant. When grown from seed, branching is initially opposite, transitioning to alternate as the plant matures. Plants propagated from cuttings generally have alternate branching in the whole plant Stack et al. (2021). Modified Carlson et al. (2021).
In the above figure, branches = 24
for this plant
kite.circularity
[categorical]
A continuous scale of apical dominance can be derived (2021):
\(kite.circularity = \frac{4\pi\cdot kite.area}{kite.perimeter^2}\)
Stems
dia
[decimal; mm]
Diameter of the stem at soil level using forestry measuring tape or fabric measuring tape, modified from Carlson et al. (2021).
pith_diameter
[decimal; mm]
Diameter of the pith in the stem cross section at stem midpoint , modified from International Union for the Protection of New Varieties of Plants (2012).
Uncrewed aerial vehicle evaluation
uav_xxx
[TBA]
See Carlson et al. (2021).
Remarks
architecture_remarks
[nvarchar]
If possible, report date of measurement [days from sowing], sex average, minimum, and maximum height and width observed in a planting (cm).
📚Additional References📚
- Anderson (1980)
- Werf, Haasken, and Wijlhuizen (1994)
- Werf et al. (1995)
- Meijer and Keizer (1996)
- Ranalli (1999)
- Mishchenko and Lajko (2016)
- Magagnini, Grassi, and Kotiranta (2018)
- Backer et al. (2018)
- Spitzer-Rimon et al. (2019)
- Carlson et al. (2021)
- Danziger and Bernstein (2021)
- Stack et al. (2021)
- Vergara et al. (2021)
LEAF
Unless otherwise noted, gather leaf data from the uppermost set of mature leaves, as mean of 5 leaves gathered from each of 10 different plants immediately before onset of flowering.
Morphology
petiole_length
[decimal; cm]
central_leaflet_length
[decimal; cm] central_leaflet_width
[decimal; cm]
Leaf is flattened and measured from tip until start of rachis; petiole is flattened and measured from base of rachis until petiole base, modified from (2012) and (1980).
(A) central_leaflet_length
and (B) petiole_length
measurement.
Imaging
leaf_color_L
[decimal]
leaf_color_a
[decimal]
leaf_color_b
[decimal]
The average color of uppermost set of mature leaves, collected before flowering, measured with a colorimeter, modified from (2012). A RHS color chart may also be used, but values should be converted to (L*a*b*) before addition to GRIN. There are many programmatic solutions to convert colors (I use R for everything: 1,2,3) as well as many online tools (e.g., Colormine).
Consider printing a label to include in the scan as well. PGRU germplasm imaging and scans typically include accession ID, species, and plant id name (e.g. ‘FIN-314’). PGRU uses a small color wheel in the corner of our templates (DOWNLOAD), but that might not be necessary for you since you are measuring color with a colorimeter.
leaf_variegation
[nvarchar; Y/N]
Indicate whether not variegation has been noted or is present.
Variegated leaves are most likely not virus based, but it might be worth investigating.
leaf_scan_protocol
[.jpg or .png]
🧪Scan protocol🧪
Equipment
- Flatbed scanner
- Desktop monitor
- Black cloth, ideally velvet, of equal dimensions to scanner bed.
Protocol
- Gather one mature leaf from a representative sample of 10 plants a week before the onset of flowering. Retain petioles. Keep on ice if wilting is a concern.
- Scan leaves within the hour of collection using a scanner with the lid open, draping black fabric over the leaves to absorb background light. Include scale or ruler (cm) and
puid
. - Convert the scanned leaf image into .png file and save.
Leaf imagaging setup at PGRU
📚Additional References📚
- Haney and Kutscheid (1975)
- Dayanandan and Kaufman (1976)
- Anderson (1980)
- Meijer and Keizer (1996)
- Amaducci et al. (2008)
- Hall, Bhattarai, and Midmore (2012)
- Mishchenko and Lajko (2016)
- Magagnini, Grassi, and Kotiranta (2018)
- Spitzer-Rimon et al. (2019)
- Carlson et al. (2021)
- Stack et al. (2021)
- Vergara et al. (2021)
SEX & INFLORESCENCE
Unless otherwise noted, record mean of 10 plants at harvest. Specify field or greenhouse conditions in sex_remarks
, as well as photoperiod or day length.
Sex ratio
sex_ratio
[nvarchar]
Sex ratio during flowering.
Target a sample of 100 individuals in the field before flowering begins. Label and number sample plants clearly. Record F:M:O; as the number of female, male, and monoecious (male + female flowers) individuals, respectively.
If plants are wild-collected, 100 plants may not be available; measure as many as possible (See S-1084 Collection Protocols).
Phenology
days_to_flower_female
[integer]
days_to_flower_male
[integer]
days_to_flower_monoecious
[integer]
Pre-terminal date when axial flowers with shortening internodes and terminal pistils (clusters of flowers at shoot termini) were observed Carlson et al. (2021) as days from sowing to first observed open female and male inflorescence. See also Faux et al. (2013); Shams et al. (2020)
maturity
[int; d]
Days from germination to commercial maturity.
day_neutrality
[nvarchar]
Describe flowering behavior as critical day length and/or day neutral response. A more precise definition is required to define this phenotype quantitatively.
Inflorescence
inflorescence_length
[decimal; cm]
Length of inflorescence cluster (cola) at the uppermost branch, excluding leaves. Remove leaves with more than 1 leaflet. Retain stems and seeds; inflorescence may be retained as clusters.
inflorescence_weight
[decimal; cm]
Measure weight after drying at room temperature for >48 hr.
inflorescence_yield
[decimal; \(kg\cdot ha^{-1}\)]
Combine inflorescence dry weight data with planting density to calculate kg/ha.
inflorescence_color
[nvarchar; L*a*b*]
Measured with a colorimeter at commercial maturity. A RHS color chart may also be used, but values should be converted to (L*a*b*) before addition to GRIN.
Remarks
sex_remarks
[nvarchar]
Short paragraph, if possible/applicable include:
- If plants were grown in field, greenhouse, or growth chamber.
- Planting density (e.g., \(\frac{plants}{100 cm^{2}}\)) if applicable.
- Female and male bract, stigma, and flower color.
- Date of collection.
- Day length (hh:mm) on the date of the first observed open female flower.
📚Additional References📚
- Schaffner (1921)
- Grishko, NN and Levchenko, VI and Seletski, VI (1937)
- Werf, Haasken, and Wijlhuizen (1994)
- Mandolino et al. (1999)
- Ranalli (1999)
- Lisson, Mendham, and Carberry (2000)
- Shao, Song, and Clarke (2003)
- Pahkala, Pahkala, and Syrjälä (2008)
- Cosentino et al. (2012)
- Hall, Bhattarai, and Midmore (2012)
- Faux et al. (2013)
- Razumova (2014)
- Lynch et al. (2016)
- Razumova et al. (2016)
- Vergara et al. (2016)
- Punja, Rodriguez, and Chen (2017)
- Zhang et al. (2018)
- Eichhorn Bilodeau et al. (2019)
- Salentijn, Petit, and Trindade (2019)
- Kovalchuk et al. (2020)
- Punja and Holmes (2020)
- Toth et al. (2020)
- Adal et al. (2021)
- Danziger and Bernstein (2021)
- Dowling, Melzer, and Schilling (2021)
- Hurgobin et al. (2021)
- Stack et al. (2021)
SEED
Samples submitted to NPGS will be evaluated by a USDA-ARS laboratory using similar protocols as described below.
General
hundred_seed_weight
[decimal; g]
Record mass of 100 seeds.
seed_image
[.jpg or .png]
🧪SEED IMAGE🧪
Equipment
- Flatbed scanner
- Desktop monitor
- Black cloth, ideally velvet, of equal dimensions to scanner bed.
- Transparent, flat-bottomed tray or transparency film to protect scanner bed from scratches.
Protocol
- Gather a sample of 20 grains.
- Scatter samples across tray or transparency film.
- Convert the scanned seed image into .PNG file and save.
Seed image. Photo credit Alan Taylor,Michael Loos, and Masoume Amirkhani
seed_size_length
[nvarchar]
seed_size_width
[nvarchar]
Size of the largest, smallest, and median seed in the lot (mm) as L:S:M using using Tomato Analyzer, Smart Grain, Photoshop, GNU Image Manipulation Program, or other imaging software to make these calculations based on a scanned image of 20 seeds.
seed_moisture
[%]
Dry seeds in a single layer in a constant temperature oven held at 105 ˚C for 20 h.
📐% Moisture📐
\(\frac{(wet - dry)}{wet} \times 100\%\)
Germination/viability
percent_germ
[%]
🧪SPROUT TEST🧪
Equipment
- 10 waterproof trays
- Sterile water-holding material (cotton wool, paper towels)
- Water source
- 200 seeds, stored between 4 to 56 weeks after harvest in dry conditions between 16 - 25˚C.
Protocol
- 4 sub-samples of 50 seeds are isolated.
- Each sub-sample is spread evenly on trays lined with water-holding material. Seeds may be placed on top of water holding material and in between rolls.
- Each tray is saturated with water and placed in a temperature-controlled room: 16 hours of dark at 20˚C, 8 hours of light at 30˚C. Trays are kept moist.
- Live, normal, sprouted seeds are counted by hand, sprouts are then removed from the germination tray.
- After 7, 14, and 21, days the number of live, normal, sprouted seeds is counted by hand. The duration of experiment may be extended if dormancy is an issue (record in
germ_remarks
) - Germination percentage for each tray is calculated as: \(\frac{ sprouted}{total} \times 100\%\) and averaged per tray.
- Consider executing TZ tests for lots with high dormancy to verify they truly are dormant and not dead.
Seed germ testing (photo credit: Alan Taylor, Michael Loos, and Masoume Amirkhani).
Modified from Seed Laboratory Oregon State University (2018), NPGS protocols, and communication with Alan Taylor, Jeffrey Carstens, and Joshua Havill.
germ_remarks
[nvarchar]
Record any dormancy issues and stratification methods used. Note: dormancy in feral/naturalized populations may also be important to characterize.
Cold stratification may be the norm in feral specimens with a temperate origin.
Yield
grain_yield
[decimal; kg/Ha]
Subsample larger strip trials (transect method) at seed maturity. Subsamples are chosen depending on the size of the field/plot to estimate kg/hectare.
shattering
[nvarchar; L,M,H]
Retain subsample of field planting for shattering evaluation and report as low, medium, or high. A more precise definition is required to define this phenotype quantitatively. See Planteome ontology.
Oil
oil_content
[decimal; %]
The percentage of oil constituting the whole, unhulled seed mass calculated as:
\(\frac{extracted.oil}{ground.sample} \times 100\%\)
Indicate whether measurement was made using Nuclear Magnetic Resonance (NMR) imaging, or using a Soxhlet extractor in seed_remarks
.
🧪Soxhlet evaluation🧪
- Seeds are ground to a particle size of 0.5 mm ± 0.1.
- Place 10 g of ground seed into an extractor thimble, extracting with 100 mL hexane for 24 h at 70 ˚C.
If a different protocol is used, record the sample weight (g), solvent name (IUPAC) and volume (mL), extraction time (h) and extraction temperature (˚C).
Adapted from Devi and Khanam (2018).
🧪NMR evaluation🧪
- To ensure accurate NMR evaluation of hemp seed, seed moisture content must be below 8%.
- Subsample 10-15 seeds after evaluation of moisture content.
- The sample is evaluated with a 40 mm diameter sample probe.
- Prior to being placed in a sample box, seeds are to be further temperature-conditioned in the drying oven or a heating block at 40 ˚C for 90 min.
- Instrument settings:
- 5 mHZ operating frequency
- 4 scans
- 1 second re-cycle delay
- 40 ˚C magnetic box temperature.
- A calibration curve is constructed by comparing several varieties with a range of oil concentrations.
- A linear calibration curve is constructed against the peak area of the NMR resonance signal normalized against sample mass.
- The y-axis of the plot reports normalized peak area, and the x-axis reports % oil concentration.
- Validate oil concentration from seeds of the same batch using Soxhlet extraction .
- Indicate the % oil concentration of seed and the R2 value of the linear equation.
- If a different NMR setting is used, list the weight of seeds sampled (g), seed temperature conditioning (˚C), operating frequency (mHZ) and line equation.
Adapted from Hutton, Garbow, and Hayes (1999). See also Shams et al. (2020); Yadav and Murthy (2016).
seed_fatty_acid
See ISO 12966-1:2014 gas chromatography protocols for determination of fatty acids, free and bound, in animal and vegetable fats and oils following their conversion to fatty acid methyl esters (FAMEs).
Protein
combustion_analysis
[decimal]
🧪Protein combustion analysis🧪
- 150 mg seeds are frozen in liquid nitrogen and ground.
- Seeds are placed into a combustion analyzer.
- Combustion tube is at 960 °C, and oxygen is dosed for 80 s at 170 mL.
Adapted from Schultz et al. (2020).
🧪Kjeldahl method🧪
Based on an adaption of AOAC Official Method 991.20 by Thiex et al. (2002), where
Kjeldahl N %
= ([std.acid sample (mL)
] - [std.acid blank (mL)
]) x ([HCl]
) x 14.01) / (weight (g)
x 10)
Crude protein %
= % Kjeldahl N
x 6.25
📚Additional References📚
- Boyce (1900)
- Mah (1923)
- Tuma (1972)
- Ribnicky et al. (2000)
- Vaknin et al. (2011)
- Sera et al. (2012)
- Small and Brookes (2012)
- Serkov (2015)
- Suriyong et al. (2015)
- Yadav and Murthy (2016)
- Citti, Pacchetti, et al. (2018)
- Hu, Liu, and Liu (2018)
- Devi and Khanam (2018)
- Jian et al. (2018)
- Williams (2019)
- He et al. (2020)
- Moon et al. (2020)
- Punja and Holmes (2020)
- Schultz et al. (2020)
- Serkov et al. (2020)
FIBER
Samples submitted to NPGS will be evaluated by a USDA-ARS laboratory using similar protocols as described below.
Yield
Hemp stem cross section. A = epidermis; B = bast and cortex; C = pith, also known as hurd, D = inner core, usually hollow but not at joints.
fiber_yield
[decimal; \(\frac{kg}{Ha}\)]
Fiber yield; modified from Serkov (2015). See also Backer et al. (2018). Harvest 10 plants, remove top and bottom 15 cm, defoliate run sample through a chipper, and measure mass. Calculate fiber_yield
based on planting density.
wet_fiber_biomass
[decimal; g]
Harvest stems 15 cm from base, remove top 15 cm, and defoliate. Wet biomass is average weight per stem without inflorescences from a sample of 10 plants Modified from Carlson et al. (2021).
dry_fiber_biomass
[decimal; g]
Use sample from wet_fiber_biomass
measurements. Dry biomass is average weight per stem dried at 65 ˚C until brittle from a sample of 10 plants. Modified from Carlson et al. (2021).
bast
[decimal; %]
Stems collected from a sample of 10 plants, dried until brittle, and separated into bast (bark) and hurd (core) using a flax breaker, or by hand. Record as fraction of oven-dried mass.
hurd
[decimal; %]
Stems collected from a sample of 10 plants, dried until brittle, and separated into bast (bark) and hurd (core) using a flax breaker, or by hand. Record as fraction of oven-dried mass.
📐Bast & hurd content📐
bast
= \(\frac{bast}{dry} \times 100\%\)
hurd
= \(100\% - bast\)
bast_soluble
& fiber_solubility
[decimal; %]
Soluble materials in bark after evaluation with sodium hydroxide evaluation.
🧪Sodium hydroxide evaluation🧪
Protocol
- 10 - 15 g isolated hurd samples isolated from dry stems, or 10 - 15 g isolated bast samples from dry stems.
- Pulp dispersion apparatus, consisting of a variable speed motor and a stainless steel stirrer with a shell.
- Thermometer
- Vacuum source
- Filtering flasks, 100 mL
- Graduated cylinder, 100 mL
- Watch glasses
- Stirring rods
- Tall, 200 mL beakers
- Water bath with cover and holes to securely submerge the bottoms of tall, 200 mL beakers.
- Filtering crucibles, 30 mL, 10 - 15 µm maximum pore size.
- 1000 mL sodium hydroxide solution, 1.0 % ± 0.1 NaOH (0.25 N)
- 1000 mL acetic acid, 10 %.
- Grind hurd or bast sample into a fine meal.
- Dry filtering crucibles before use in an oven at 105° ± 3 °C for 60 min, cool in a desiccator, and record weight.
- Heat water bath to 97 - 100 ˚C
- Adjust speed of the motor and the angle of the blades so that no air is drawn into the pulp suspension during stirring.
- Place 10 g meal into 200 mL beaker and add 100 mL 1 % NaOH and stir with glass rod.
- Cover beaker with watch glass and place into water bath for 1 h. Keep water level above level of alkali solution in the beaker at all times.
- Stir the meal with a rod for about 5 s at 10, 15, and 25 min after placing into the bath.
- At the end of 1 h, transfer the material to a tared filtering crucible and wash with 100 mL of hot water.
- Add 25 mL of 10 /% acetic acid and allow to soak for 1 min before removal. Repeat this step once again.
- Wash material with 100 mL hot water three times to remove acid.
- Dry crucible and contents in the oven at 105 - 108 ˚C until constant weight.
- Cool in desiccator.
📐% Soluble materials📐
\(\frac{meal.before - meal.after}{meal.before} \times 100\%\)
non_fiber
[TBD]
Protocol for evaluating stem non-fiber components not determined.
Quality
There is little modern research on hemp fiber quality evaluation protocols. This work will be conducted in collaboration with the Southern Regional Research Center (SRRC).
📜Candidate fiber traits📜
- fiber length
- fiber strength
- fiber flexibility; see Werf, Haasken, and Wijlhuizen (1994)
- fiber length/diameter ratio; see Ranalli (1999)
- tensile strength; see Ranalli (1999)
- brittleness; see Ranalli (1999)
- crystallization/cellulose crystallinity Rongpipi et al. (2019)
- cross linking
- elasticity; see Ranalli (1999)
- ease of decortication
- mechanical vs microbial retting
- cellulose:lignin ratio
fiber_remarks
[nvarchar]
Remarks are used to add notes or to elaborate on fiber descriptors
📚Additional References📚
- Charles (1708)
- Unknown (1720)
- David (1729)
- Slator (1735)
- Marcandier (1764)
- Gee (1767)
- Farmer (1775)
- Wissett (1808)
- Humphrey (1919)
- Vavilov (1957)
- Werf et al. (1995)
- Daryl T. Ehrensing (1998)
- Rustichelli et al. (1998)
- Hampton (2000)
- Struik et al. (1999)
- Hillig (2005)
- Pahkala, Pahkala, and Syrjälä (2008)
- Zatta, Monti, and Venturi (2012)
- Piluzza et al. (2013)
- Salentijn et al. (2015)
- Serkov (2015)
- Mishchenko and Lajko (2016)
- Grassi and McPartland (2017)
- Tang et al. (2016)
- Weijde et al. (2016)
- Johnson (2018)
- Musio, Müssig, and Amaducci (2018)
- Salentijn, Petit, and Trindade (2019)
- Williams (2019)
- Petit et al. (2020)
SECONDARY METABOLITES
Unless otherwise stated, collect from a sample of 10 plants at harvest. Samples submitted to NPGS will be evaluated by a USDA-ARS laboratory using similar protocols as described below.
Chemotype
chemotype
[int; 1-6]
Note that living tissues synthesize acid forms of most cannabinoids (i.e. THC-a, CBD-a) and these are often decarboxylated to non-acid forms during evaluation (i.e. THC, CBD). Chemotype is largely driven by segregation of alleles at the \(B\) or \(O\) loci Toth et al. (2020).
1 = Mostly THC(A)
2 = ~1.5:1 CBD(A):THC(A)
3 = Mostly CBD(A)
4 = Mostly CBG(A)
5 = Low overall cannabinoid content
6 = Other
chemotype_segregation
[nvarchar]
To not mask chemotype, we recommend measuring cannabinoids from 10 individual plants rather than pooling samples. If multiple individuals are evaluated for chemotype and differing chemotypes are observed in the same population, indicate the percentage of each chemotype using the chemotype
scale (1:#;2:#;3:#,4:#,5:#).
Cannabinoids
cannabinoids
[decimal; \(\frac{μg}{mg}\)]
Cannabinoid content is evaluated either by UPLC or HPLC. THC is a ‘’sticky’’ compound and residues will persist on laboratory equipment and analytical vessels following cleaning. THC carryover onto subsequent samples may erroneously increase the reported THC content. We strongly advise against re-using sample vials for UPLC and HPLC cannabinoid evaluation.
UPLC uses a shorter run time per sample, however HPLC provides better resolution for minor cannabinoids. Both methods are sufficient for quantifying total THC in compliance with the 2020 Hemp Final Rule.
10 samples collected from 10 individual plants. Each sample should be analysed in triplicate. Cannabinoid content is variable across the height of the plant. THC-a decarboxylates into THC following exposure to heat. We advise against decarboxylating cannabis samples prior to instrument evaluation, as this process introduces error through the volatilization of a variable percentage of the total cannabinoid content.
Instead, we recommend combining the THC-a and THC content of unheated plant samples to calculate the total THC content. The formula for this is:
📐THC & Cannabinoid analytes📐
\(THC_{total.potential}(μg/mg) = THC + 0.877 \cdot THC_a\)
\(Cannabinoid.analyte = C_e\frac{V_f}{W_s}\)
where:
\(C_e\): Conc of the sample in the extraction solution (\(\frac{μg}{μL}\))
\(V_f\): Final volume of the sample (\(μl\))
\(W_s\): Weight of the sample (\(mg\))
🧪UPLC cannabinoid evaluation🧪
Sample run time: 15 min.
Equipment
- Sonicator
- Thermo Scientific UltiMate 3000 controlled by Chromeleon software
- IntertSustain C18 3 μm chromatographic column (2.1 x 100 mm)
- 5 mM aqueous ammonium formate
- 0.1 % formic acid
- 95 % formic acid
- Acetonitrile
- Volumetric flasks: 1.5 L, 50 mL.
- 0.45 µm membrane filter.
Standards:
- Cannabicyclolic acid (CBLA)
- Δ9 Tetrahydrocannabinolic acid A (THCA)
- Cannabidiolic acid (CBDA)
- Cannabinolic acid (CBNA)
- Cannabigerolic acid (CBGA)
- Cannabidivarinic acid (CBDVA)
- Tetrahydrocannabivarinic acid (THCVA)
- Cannabichromene acid (CBCA)
- Analyte mixture of the 8 main decarboxylated cannabinoids:
- Δ9 Tetrahydrocannabinol (THC-d9)
- Δ8 Tetrahydrocannabinol (THC-d8)
- Cannabidiol (CBD)
- Cannabinol (CBN)
- Cannabigerol (CBG)
- Cannabivarin (CBDV)
- Tetrahydrocannabivarin (THCV)
- Cannabichromene (CBC)
- Potentially add CBGVA, THCP, CBGM, others?
Standard preparation
- All standard solutions are to be prepared at a concentration of 100 µg/mL.
- Cannabinoid acid standards are prepared in acetonitrile. Decarboxylated cannabinoids are prepared in methanol.
Reagent preparation
- 1 L reagent for Mobile Phase A: Combine 0.21 mL 95 % formic acid with 5 mM ammonium hydroxide (0.62 mL 30 % sodium hydroxide solution) with millipore water to 999 mL. Add 1 mL 1 % formic acid.
- 1 L reagent for Mobile Phase B: Combine acetonitrile with formic acid to 0.1 % formic acid.
Protocol
- Dry Inflorescences at room temperature (20 ˚C) to < 10 % moisture.
- Grind samples.
- Combine 0.1 g sample with 10 mL acetonitrile and 0.1 % formic acid
- Sonicate sample at 230 V for 30 min at room temperature, then rest sample for 6 h.
- Filter supernatant two times through the 45 µm membrane filter.
- Dilute filtrate to 200x, then inject 1 µL sample volume into the ULPC system.
- Set flow rate to 0.55 mL/min.
- Set mobile phase to 2.5 min equilibrating at 60 % B between injections, with the gradient elution:
- 0-2 min, 70 % B;
- 2-8 min, 75 % B;
- 8-9 min, 100 % B;
- 9-10 min, 100 % B;
- 10-10.5 min, 60 % B;
- 10.5-11 min, 60 % B.
- Quantify peaks at 228 nm.
Methods provided by Berhow and Gude (2021).
🧪HPLC cannbinoid evaluation🧪
Cannaflavin A & B is evaluated on the 342 nm range using the HPLC protocol over 27 min
Equipment
- Sonicator
- Shimadzu LC20 AT HLPC controlled by LabSolutions Software
- Intersil ODS3 5 µm column (4.6 x 250 mm)
- 5 mM aqueous ammonium formate
- 0.1 % formic acid
- Acetonitrile
- Methanol
- Volumetric flasks: 1.5 L, 50 mL.
- 0.45 µm membrane filter.
- Standards: See above UPLC standards.
Reagent preparation
- All standard solutions are to be prepared at a concentration of 100 µg/mL.
- Cannabinoid acid standards are prepared in acetonitrile.
- Decarboxylated cannabinoids are prepared in methanol.
- 1 L reagent for Mobile Phase A: Combine 5 mM aqueous ammonium formate with 0.1 % formic acid.
- 1 L reagent for Mobile Phase B: Combine an equal amount of acetonitrile with methanol, then bring to 0.1 % formic acid.
Protocol
- Dry Inflorescences at room temperature (20 ˚C) to >10 % moisture.
- Grind samples.
- Combine 0.1 g sample with 10 mL acetonitrile and 0.1 % formic acid
- Sonicate sample at 230 V for 30 min at room temperature, then rest sample for 6 h.
- Filter supernatant two times through the 45 µm membrane filter.
- Dilute filtrate to 200x, then inject 20 µL sample volume into the HLPC. 7.Set flow rate to 1.2 mL/min.
- Set column to 50 ˚C.
- Set mobile phase to 2.5 min equilibrating at 60 % B between injections, with the gradient elution:
- 0 min, 70 % B;
- 3-5 min, 85 % B;
- 5-10 min, 95 % B;
- 10-15 min, 100 % B;
- 15-25, 100 % B;
- 25-26, 70 % B;
- 26-27, 60 % B.
Methods provided by Berhow and Gude (2021).
Other metabolites
terpenes
[decimal]
🧪Terpene evaluation🧪
Equipment
- GC/MS (Agilent 7890B GC, Agilent 5977B MSD, PAL 3) controlled by LabSolutions software
- HP-5MS UI, 30 m × 0.25 mm, film 0.25 μm column
- 0.45 μm filter
- Hexane
Standards
- β-bisabolol
- Bulnesol
- m-Camphorene
- p-Camphorene
- Δ3-Carene
- β-Caryophyllene
- 10-epi-γ-Eudesmol
- α-eudesmol
- β-eudesmol
- α-humulene
- Limonene
- Linalool
- β-Myrcene
- Plastochromanol-8
- α-Phellandrene
- α-Pinene
- cis-Sabinene hydrate
- γ-Selmene
- Selna-3,7(11)-diene
- α-Tocopherol
- β-Tocopherol
- δ-Tocopherol
- γ-Tocopherol
- β-Pinene
- Nerolidol
- Camphene
- Terpinolene
- Ocimene
- α-Terpinene
- γ-Terpinene
Protocol
- Dilute essential oil standards with hexane to a concentration of 0.1 mg/mL.
- Dry inflorescences at room temperature (20 ˚C) to > 10 % moisture.
- Grind samples.
- Combine 20 mg plant material with hexane.
- Pass through the 0.45 µm filter to extract terpenes.
- Dilute filtrate 1:20 with hexane.
- Inject samples into split injection port (1:5).
- Instrument settings as follows:
- Injection port held at 100 ˚C with an initial time of 4 min.
- Inlet temperature fixed at 250 ˚C.
- Detector temperature fixed at 280 ˚C.
- Column held at 35 °C for 5 min, then raise to 150 °C at 5 °C/min. Then raise to 250 ˚C at 15˚ C/min. Hold time 90 min.
- Helium serves as carrier gas, with flow rate 1 mL/min.
Adapted from Hanuš and Hod (2020).
See also hops methods
flavonol_index
[decimal]
🧪Flavonol evaluation🧪
A handheld MPM-100 meter by ADC BioScientific can do this measurement instantly. (See)
- Flavonoids: Spectroscopic measurement of fluorescence at different wavelengths (F660 nm and F325 nm):
- Flavonols: (F660 nm/F325 nm).
anthocyanins
[decimal]
🧪Anthocyanin evaluation🧪
Sample prep and extraction
- Samples are ground into a fine powder with a coffee mill and passed through a 60 mesh filter to collect the fine ground fraction.
- Batches of 250 grams of ground sample are extracted with 1 % HCl in methanol with stirring overnight at room temperature.
- The liquid is decanted and filtered through Whatman 54 filter paper.
- The remaining solid material is extracted with only methanol a second time with stirring overnight and decanted and filtered.
- The extracts are pooled, and approximately 400 mL of water is added, and allowed to evaporate over 72 hours in the hood or rotovaped at 45 °C to remove the methanol.
- The concentrated extract is filtered gain to remove any remaining solid material.
Method A: Preparative Chromatography
- A Buchi (Newcastle, DE) Sepacore flash chromatography system with dual C-605 pump modules, C-615 pump manager, C-660 fraction collector, C-635 UV photometer, with SepacoreRecord 1.2 chromatography software is used.
- A 40 x 150 mm flash cartridge column with approximately 90 grams of preparative C18 reverse phase end capped bulk packing material (Silicycle SiliSep BUC18 (17%) 60 Angstroms, 40-63 um, Silicycle, Quebec, Canada) is used for the preparative separation.
- The columns are installed in the flash chromatography system, and new dry columns are initially washed with methanol and then equilibrated with 0.2% acetic acid in water for five minutes at a flow rate of 50 mL per min.
- After samples (50-100 mL) are loaded on the column, the column is developed with a binary gradient to 40% methanol over 10 minutes, then to 100% methanol over an additional 5 minutes. For anthocyanins, the effluent is monitored at 520 nm and 50 mL fractions are collected in the fraction collector by the software program.
- Fractions are concentrated by evaporation in the hood at room temperature or methanol is removed by rotovap at 45 °C.
- The fractions containing the DGA are pooled and freeze dried over 2-5 days to dryness.
Method B: HPLC Analysis
- Samples are run on a stand-alone Shimadzu 10A HPLC system (SCL-10A system controller, two LC-10A pumps, CTO-10A column oven, and SIL-10A autoinjector).
- Peaks are monitored using a Hewlett-Packard 1040A photodiode array detector running under the HP Chemstation software version A.02.05.
- The column used is an Inertsil ODS-3 reverse phase C-18 column (5 µM, 250 x 4.6 mm, with a Metaguard column, from Varian).
- The initial conditions are 2% acetonitrile and 0.5% acetic acid in water, at a flow rate of 1 ml per minute.
- The effluent is monitored at 520 nm on the PDA.
- After injection (typically 25 µL), the column is held at the initial conditions for 2 minutes, and then developed to 100% acetonitrile in a linear gradient over 60 minutes.
- Standard curves based on nanomoles injected are prepared from a pure standard of delphnidin-3-O-glucoside purchased from Chromadex (Irvine, CA).
- Extinction coefficients are calculated from a linear regression formula based on four different nanomole concentrations of anthocyanin standards (purchased from Chromadex) injected and their respective mAbs areas.
- The extinction coefficient for each anthocyanin is then used to calculate respective anthocyanin glycoside concentration in the samples by the following formula:
\[ mAbs(area) \cdot extc.coef(\frac{nM}{mAbs}) \cdot \frac{1}{inj.vol(μL)} \cdot vol.extract(mL) \cdot MW_{anth.glucoside}(\frac{μg}{nM}) \cdot \frac{1}{sample(g)}\]
- Addition of a glycosyl groups to the anthocyanin has little effect on its absorption profile, so anthocyanin aglycones can be used to prepare standard curves for anthocyanin glycosides on a molar basis (Berhow 2002, Mabry 1970, Markham, 1982).
Method C: LC-ESI-MS Analysis of Anthocyanins
- Samples are run on an Thermo Electron LTQ Orbitrap Discovery Mass Spectrometer – a linear ion trap (LTQ XL) MS, coupled to a high precision electrostatic ion trap (Orbitrap) MS with a higher energy C-trap dissociation (HCD) cell attached – with an Ion Max electrospray ionization (ESI) source; a Thermo Scientific ACCELA series HPLC system (ACCELA 1250 UHPLC pump; ACCELA1 HTC cool stack autoinjector; and a ACCELA 80 Hz PDA detector); all running under Thermo Scientific Xcalibur 2.1.0.1140 LC-MS software.
- HPLC conditions: The column is a 3 mm x 150 mm Inertsil reverse phase C-18, ODS 3, 3 µ column (Metachem, Torrance, CA).
- For anthocyanin analysis, the initial solvent system is 10% methanol verses water with 0.1% formic acid at a flow rate of 0.25 mL per minute.
- After injection (1 µl or less) the column is held at the initial conditions for 2 minutes then developed with a linear gradient to 100% methanol and 0.1% formic acid over 50 additional min.
- The column effluent is monitored at 520 nm by the PDA detector.
- The MS is run with the ESI probe in the positive mode.
- The source inlet temperature is set to 300 ˚C, the sheath gas rate is set at 50 arbitrary units, the auxiliary gas rate is set at 5 arbitrary units and the sweep gas rate is set at 2 arbitrary units.
- The maximal mass resolution is set at 30,000, the spray voltage is set at 3.0 kV, the tube lens is set at 100 V.
- The MS is typically calibrated at least weekly with a standard calibration mixture recommended by Thermo Scientific and the signal detection optimized by running the autotune software feature as needed.
- Other parameters are determined and set by the calibration and tuning process.
- The software package will usually be set to collect mass data between 100-2000 AMUs.
- Generally the most significant sample ions generated under these conditions are [M]+.
Methods provided by Berhow and Gude (2021), see also Giusti and Wrolstad (2001).
phenolics
[decimal]
🧪Phenolic evaluation🧪
Sample prep and extraction
- Freeze-dry samples overnight and grind each to a fine powder.
- Weigh samples ~0.25 g and place in vial with 3 mL methanol:DMSO (1:1) solvent.
- Sonicate for 30 min, allow to stand overnight at room temperature.
- Filter extract through a 0.45 µM nylon 66 filter
Methodology
- We use a Shimadzu LC-20 HPLC system (LC-20AT quaternary pump, DGU-20A5 degasser, SIL-20A HT autosampler, and a SPD M20A photodiode array detector, running under Shimadzu LCSolutions version 1.22 chromatography software, Columbia, MD, USA) and an Inertsil ODS-3 reverse phase C-18 column (5 µm, 250 x 4.6 mm, GL Sciences, Torrance, CA).
- For phenolic compound analysis, the initial conditions are 10% methanol (or acetonitrile) with 0.25% trifluroacetic acid and 90% water with 0.25% trifluroacetic acid, at a flow rate of 1 ml per minute.
- The effluent is monitored at 280 and 340 nm on the VWD
- After injection (typically 25 µL), the column is held at the initial conditions for 2 minutes, then developed to 100% methanol with 0.25% trifluroacetic acid in a linear gradient over 50 additional minutes.
- Five-point standard curves are used for the evaluation of the concentration of the identified phenolics for the determination of extinction coefficients at 280 and 340 nm.
LC-ESI-MS Confirmation
- Samples are run on an Thermo Electron LTQ Orbitrap Discovery Mass Spectrometer – a linear ion trap (LTQ XL) MS, coupled to a high precision electrostatic ion trap (Orbitrap) MS with a high energy collision (HCD) cell – with an Ion Max electrospray ionization (ESI) source, and a Thermo Scientific ACCELA series HPLC system (ACCELA 1250 UHPLC pump, ACCELA1 HTC cool stack autoinjector, and a ACCELA 80 Hz PDA detector) all running under Thermo Scientific Xcalibur 2.1.0.1140 LC-MS software.
- The MS is typically calibrated at least weekly with a standard calibration mixture recommended by Thermo Scientific and the signal detection optimized by running the autotune software feature as needed.
- The MS is run with the ESI probe in the negative mode.
- The source inlet temperature is 300 ˚C, the sheath gas rate is typically set at 50 arbitrary units, the auxiliary gas rate is usually set at 5 arbitrary units and the sweep gas rate is set at 2 arbitrary units.
- The maximal mass resolution is set at 30,000, the spray voltage is set at 3.0 kV, the tube lens is set at -100 V.
- Other parameters are determined and set by the calibration and tuning process.
- For phenolic analysis, the initial solvent system is 10% methanol verses water with 0.25% formic acid at a flow rate of 0.25 mL per minute.
- After injection (5 µl or less) the column is developed with a linear gradient to 100% methanol over 50 to 60 min.
- The column effluent is monitored at 280 nm and 340 nm in the PDA detector. * The software package is set to collect mass data between 100-2000 AMUs. Generally, the most significant sample ions generated under these conditions are [M-1]- and [M+HCOO]-.
- Six mass spec “events” are programmed to run in sequence in the MS detection scheme.
- LTQ(IT)-MS full scan m/z 150 to 2000.
- LTQ(IT)-MS set to trap the most abundant ion above a threshold of 500 units and perform CID at 35% energy, with the resulting ions being detected by the IT-MS.
- FT-MS (Orbitrap) full scan m/z 150 to 2000.
- Mass-dependent MS/MS on the most abundant ion trapped by the IT-MS in Event 1 and perform HCD at 25% energy with the resulting fragmentation ions being detected by the FT-MS.
- Mass-dependent MS3 on the most abundant fragment ion generated from Event 2 and perform HCD at 25% energy with the resulting fragmentation ions being detected by FT-MS.
- Mass-dependent MS3 on the most abundant fragmentation ion generated from Event 2 and perform CID at 35% energy with the resulting ions being detected by IT-MS.
- For the evaluation of Xcalibur accurate mass data by the Cerno BioScience LLC MassWorks 5.0.0.0 software the FTMS is set to collect spectra at a resolution of 7500 and a range of m/z of 100 to 2000 and then evaluated by sCLIPS (self Calibrating Line-shape Isotope Profile Search) which enhances formula ID accuracy.
Remarks
metabolite_remarks
[nvarchar]
Identification of other metabolites may be provided in the metabolite_remarks
field.
📚Additional References📚
- Turner, Hemphill, and Mahlberg (1978)
- Rustichelli et al. (1998)
- Meijer and Hammond (2005)
- De Backer et al. (2009)
- USDA (2009)
- Casano et al. (2011)
- Russo (2011)
- Hazekamp and Fischedick (2012)
- Pertwee (2014)
- Pandohee et al. (2015)
- Lynch et al. (2016)
- Weijde et al. (2016)
- Brighenti et al. (2017)
- Dufresnes et al. (2017)
- Jin et al. (2017)
- Patel, Wene, and Fan (2017)
- Ciolino, Ranieri, and Taylor (2018)
- Citti, Braghiroli, et al. (2018)
- Citti, Pacchetti, et al. (2018)
- Palmieri et al. (2018)
- Pellati et al. (2018)
- Pollastro, Minassi, and Fresu (2018)
- Wang et al. (2018)
- Zivovinovic et al. (2018)
- Booth and Bohlmann (2018)
- Comeau et al. (2018)
- Hädener, König, and Weinmann (2018)
- Laverty et al. (2018)
- Mandrioli et al. (2018)
- Protti et al. (2018)
- Reimann-Philipp et al. (2018)
- Pavlovic et al. (2019)
- Nahar, Onder, and Sarker (2020)
- Križman (2020)
- Danziger and Bernstein (2021)
- Hurgobin et al. (2021)
- Stack et al. (2021)
PATHOGEN/PEST
Diseases are scored by indicating % area of planting affected and whether crop failure occurred in conjunction with infection. If one data score is provided for multiple plantings, provide the highest area coverage observed. Ideally the hemp community should decide on a set of check-varieties to include in every trial to compare between seasons.
For consistent scoring of disease and stress data, it is recommended that the same individual be responsible for rating the entire planting.
Refrain from capturing data for a small set or singular accessions, instead prefer an actual growout of a replicated trial that contains numerous accessions in a single season.
Record other relevant information in the disease_remarks
field. Specifically, it will be useful to distinguish between hop powdery mildew, caused by P. macularis, and cannabis powdery mildew, caused by Golovinomyces ambrosiae. These appear to possess varying degrees of aggressiveness and phenotyping remarks should include information about which pathogen species was used for phenotyping.
Fungal and oomycetes
fungal_xxx
[decimal; %]
Known or suspected fungal/oomycete pathogens:
- Alternaria spp
- Ascochyta spp
- Athelia rolfsii or Sclerotium rolfsii
- Bipolaris spp
- Bipolaris gigantea
- Boeremia
- Botrytis cinerea
- Botrytis pseudocinerea
- Botrytis porri
- Cercospora cf. flagellaris
- Chaetomium globosum
- Cladosporium spp
- Colletotrichum spp
- Curvularia spp
- Diaporthe eres/ D. subordinaria
- Exserohilum spp
- Fusarium avenaceum
- Fusarium brachygibbosum
- Fusarium chlamydosporum
- Fusarium equiseti
- Fusarium graminearum
- Fusarium lichenicola
- Fusarium oxysporum
- Fusarium proliferatum
- Fusarium solani
- Fusarium sporotrichiodes
- Fusarium tricinctum
- Globisporangium irregulare
- Globisporangium ultimum
- Golovinomyces ambrosiae
- Golovinomyces cichoracearum
- Golovinomyces spadiceus
- Lasiodiplodia theobromae
- Leveillula taurica
- Leptosphaeria
- Neofusicoccum parvum
- Penicillium spp
- Phoma spp
- Phoma multirostrata
- Phomopsis spp
- Phytophthora spp
- Podosphaera macularis (syn. Sphaerotheca macularis)
- Pseudocercospora spp
- Pythium aphanidermatum
- Pythium catenulatum
- Pythium dissotocum
- Pythium myriotylum
- Rhizoctonia solani
- Sclerotinia sclerotiorum
- Sclerotinia minor
- Sclerotium rolfsii
- Septoria spp
- Stemphylium spp
- Thielaviopsis basicola
- Uredo kriegeriana
- Verticillium dahliae
Bacterial
bacterial_xxx
[decimal; %]
Known or suspected bacterial pathogens:
- Agrobacterium tumefaciens
- Pseudomonas koreensis
- Pseudomonas syringae
- Serratia marcescens
- Sphingomonas yanoikuyae
- Xanthomonas campestris pv. cannabis
Virus/Viroid
virus_xxx
[decimal; %]
Known or suspected virus/viroid/phytoplasma pathogens:
- Alfalfa mosaic virus (AMV)
- Arabis mosaic virus (ArMV)
- Beet curly top virus
- Cannabis sativa mitovirus 1
- Cannabis cryptic virus
- Citrus yellow-vein associated virus
- Cucumber mosaic virus (CMV)
- Curly top virus
- Lettuce chlorosis virus (LCV)
- Tobacco ringspot virus (TRSV)
- Tomato ringspot virus (ToRSV)
- Tobacco streak virus (TSV)
- Tomato mosaic virus (ToMV)
viroid_xxx
[decimal; %]
- Hop latent viroid (HLVd)
phytoplasma_xxx
- Candidatus phytoplasma trifolii
nematode_xxx
- Meloidogyne incognita (Root knot nematodes)
Remarks
disease_remarks
[nvarchar]
In a short paragraph, describe the disease. Please include the anatomy of the plant affected, the growth stage of the plant affected, symptoms of infection, patterns of spread in field or greenhouse, evidence leading to conclusion of the nature of the pathogen, and any other relevant observations.
Invertebrate
Key pests
Many insects and mites can be observed in hemp and the pest complex can differ depending on whether the crop is cultivated indoors or outdoors. While many arthropods can be found in hemp, some of the most often-seen pests include corn earworm, twospotted spider mite, cannabis aphid, and hemp russet mite.
Invertebrate pests are scored by indicating % area of planting affected and whether crop failure occurred in conjunction with infestation.
Refrain from capturing data for a small set or singular accessions, instead prefer an actual growout of a replicated trial that contains numerous accessions in a single season. Ideally the hemp community should decide on a set of check-varieties to include in every trial to compare between seasons.
Images and text were very generously provided by Kadie Britt (2021). We highly recommend McPartland, Clarke, and Watson (2000), Cranshaw et al. (2019), and Britt (2021) as excellent overviews.
Corn earworm
helicoverpa_zea
[decimal; %]
Helicoverpa zea or corn earworm is the most damaging pest of hemp grown in outdoor environments as it targets marketable portions of hemp plants – floral regions of CBD and seeds of grain varieties (2021).
Young corn earworm larva. (Photo credit: Kadie Britt)
Bud rot in floral hemp bud from corn earworm feeding. (Photo credit: Kadie Britt
Adult corn earworm moth on hemp plant. (Photo credit: Katlyn Catron)
Hemp russet mite
aculops_cannabicola
[decimal; %]
Aculops cannabicola or hemp russet mite is a microscopic, cannabis-specific mite that can be found in indoor and outdoor hemp. Mites have four legs on their white- to beige-colored, cigar shaped bodies and are not visible without the use of magnification Kadie Britt (2021) and McPartland and Hillig (2003).
Hemp russet mites on underside of hemp leaf. (Photo credit: Kadie Britt)
Upward curling of hemp leaves. Can sometimes be a symptom of hemp russet mite feeding injury to hemp but depends on cultivar. (Photo credit: Kadie Britt)
Twospotted spider mite
tetranychus_urticae
[decimal; %]
Tetranychus urticae or twospotted spider mite is a generalist mite pest that can be found indoors and outdoors. Feeding injury causes stippling marks on leaves (Figure 1.7) and webbing can sometimes be observed in apical portions of plants (Figure 1.8). This mite is small and oval in shape, has 8 legs, and can be orange/red or brown with two distinct dark spots on the body (2021).
Twospotted spider mite on hemp leaf. (Photo Credit: Kadie Britt)
Stippling on leaves due to twospotted spider mite feeding. (Photo credit: Kadie Britt)
Webbing in apical portion of plant due to twospotted spider mite populations. (Photo credit: Kadie Britt)
Cannabis aphid
phorodon_cannabis
[decimal; %] Phorodon cannabis or cannabis aphid is a specialist, piercing-sucking insect that feeds exclusively on hemp. Populations can rapidly increase in favorable environments (Figure 1.10) as aphids can reproduce via asexual reproduction Kadie Britt (2021) and Cranshaw et al. (2018).
Cannabis aphid infestation on indoor hemp plant. (Photo credit: Kadie Britt)
Cannabis aphid skins caught in honeydew on surface of hemp leaves. (Photo credit: Kadie Britt)
Other pests
Known or suspected pests:
- Acherontia atropos
- Aculops cannabicola
- Aecidium cannabis
- Agallia constricta
- Aglais urticae
- Agromyza reptans
- Aphis fabae
- Aphis gossypii
- Camnula pellucida
- Ceutorhynchus assimilis
- Chinavia hilaris
- Chloealtis conspersa
- Chlorochroa ligata
- Chlorochroa uhleri
- Chromatomyia horticola
- Cosmopepla lintneriana
- Bemisia tabaci
- Diabrotica undecimpunctata howardi
- Ditylenchus dipsaci
- Empoasca fabae
- Estigmene acrea
- Euschistus servus
- Frankliniella fusca
- Frankliniella occidentalis
- Graphocephala versuta
- Grapholita delineana
- Halyomorpha halys
- Helicoverpa zea
- Heterodera humuli
- Hysteroneura setariae
- Liorhyssus hyalinus
- Liriomyza cannabis
- Liriomyza strigata
- Loxostege sticticalis
- Mamestra configurata
- Melanchra picta
- Melanoplus bivittatus
- Melanoplus femurrubrum
- Melanoplus lakinus
- Melanoplus differentialis
- Microtechnites bractatus
- Micrutalis calva
- Miridae
- Nezara viridula
- Oebalus pugnax
- Ostrinia nubilalis
- Pentatomidae
- Peridroma saucia
- Phorodon cannabis
- Phyllophaga tristis
- Phyllotreta pusilla
- Podosphaera macularis
- Polyphagotarsonemus latus
- Popillia japonica
- Prionus
- Pseudoperonospora cannabina
- Pseudoperonospora humuli
- Psylliodes attenuata
- Rhopalidae
- Rhopalosiphum abdominalis
- Spilosoma virginica
- Spissistilus festinus
- Spodoptera exigua
- Spodoptera ornithigalli
- Strymon melinus
- Systena blanda
- Systena elongata
- Tetramorium caespitum
- Tetranychus urticae
- Thamnurgus caucasicus
- Thrips tabaci
- Thyanta custator
- Trichiocampus cannabis
- Uredo kriegeriana
- Vanessa cardui
- Known European species
📚Additional References📚
- H M G Van der Werf, W C A van Geel, and M Wijlhuizen (1995)
- Punja, Rodriguez, and Chen (2017)
- Cranshaw et al. (2019)
- Eric Anderson (2019)
- Campbell et al. (2019)
- McKernan et al. (2020)
- Szarka et al. (2020)
- Farinas and Peduto (2020)
- Thiessen et al. (2020)
- Hu, Masson, and Dickey (2020)
- Stack et al. (2021)
COLLECTION
🧪Feral hemp collection protocol🧪
This feral hemp collection protocol was very generously provided by Shelby Ellison via work with the S-1084 USDA Hatch Multistate Research Project: Industrial Hemp Production, Processing, and Marketing in the U.S..
Secure state licensing to possess industrial hemp in your jurisdiction.
Secure written authorization from your regulatory agency (state department of agriculture) and/or University counsel to collect and hold feral hemp that has not been certified as < 0.3% ∆9-THC.
Collect GPS coordinates (record Google Maps point on a smartphone), and record a thorough description of the site – drainage patterns, surrounding vegetation, elevation, and soils classification from Web Soil Survey. Contact Zachary Stansell for a collection template.
- Preferred population size up to 50 random female individuals
- Populations should be separated by at least 5 miles (8 km) to assure pollen isolation.
- Give each population an ID code in this scheme: state (WI), year (2022), five-digit sequential accession number for your program (00001), and plant number (01) – i.e. WI-2022-00001-01. If there are multiple programs collecting in a state, the state identifier should be modified (WI-M) for Wisconsin-Madison, for example.
Secure verbal and/or written permission from the landowner to collect plant material.
Using sharp pruning shears, cut down up to 50 random female plants. Label a large brown paper bag for each plant with ID code. Thresh each plant individually, place seed into the separate and individually-labeled large paper bag.
Dry all material at room temp (or <100F°) with a fan providing moving air for at least one week. Thresh and sieve seeds if possible or clean on a Clipper seed cleaner or similar.
First contact then send cleaned seed to Zachary Stansell at zachary.stansell@usda.gov at 21 Crabapple Dr. Geneva NY, 14456.
REFERENCES
Adal, Ayelign M., Ketan Doshi, Larry Holbrook, and Soheil S. Mahmoud. 2021. “Comparative RNA-Seq Analysis Reveals Genes Associated with Masculinization in Female Cannabis Sativa.” Planta 253 (1). https://doi.org/10.1007/s00425-020-03522-y.
Adriel Garay, and Sabry Elias. 1998. “Ploidy by Flow Cytometry: An Ideal Technology for Determining the Ploidy Level in Ryegrass and Other Species.” https://seedlab.oregonstate.edu/sites/seedlab.oregonstate.edu/files/value-ploidy-test-2006.pdf.
Amaducci, Stefano, Michele Colauzzi, Gianni Bellocchi, and Gianpietro Venturi. 2008. “Modelling Post-Emergent Hemp Phenology (Cannabis Sativa L.): Theory and Evaluation.” European Journal of Agronomy 28 (2): 90–102. https://doi.org/10.1016/j.eja.2007.05.006.
Anderson, Loran C. 1980. “Leaf Variation Among Cannabis Species from a Controlled Garden.” Botanical Museum Leaflets, Harvard University 28 (1): 61–69. http://www.jstor.org/stable/41762825.
Backer, Rachel, Timothy Schwinghamer, Phillip Rosenbaum, Vincent McCarty, Samuel Eichhorn Bilodeau, Dongmei Lyu, Md Bulbul Ahmed, et al. 2018. “Closing the Yield Gap for Cannabis: A Meta-Analysis of Factors Determining Cannabis Yield.” Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.00495.
Berhow, Mark, and Kelly Gude. 2021. “Materials and Methods - UPLC & HPLC for Cannabinoid Analysis in Hemp.” National Center for Agricultural Utilization Research.
Bioversity International, FAO. 2015. “Fao/Bioversity Multi-Crop Passport Descriptors V.2.1.” FAO/Bioversity Multi-Crop Passport Descriptors V.2.1 [MCPD V.2.1]. https://www.bioversityinternational.org/fileadmin/user_upload/online_library/publications/pdfs/FAOBIOVERSITY_MULTI-CROP_PASSPORT_DESCRIPTORS_V.2.1_2015_2020.pdf.
Booth, Judith K., and Jörg Bohlmann. 2018. “Terpenes in Cannabis Sativa – from Plant Genome to Humans.” Plant Science 284: 67–72. https://doi.org/10.1016/j.plantsci.2019.03.022.
Boyce, Sidney Smith. 1900. Hemp (Cannabis Sativa) a Practical Treatise on the Culture of Hemp for Seed and Fiber: With a Sketch of the History and Nature of the Hemp Plant. New York: Orange Judd co.
Brighenti, Virginia, Federica Pellati, Marleen Steinbach, Davide Maran, and Stefania Benvenuti. 2017. “Development of a New Extraction Technique and HPLC Method for the Analysis of Non-Psychoactive Cannabinoids in Fibre-Type Cannabis Sativa L. (Hemp).” Journal of Pharmaceutical and Biomedical Analysis 143: 228–36. https://doi.org/10.1016/j.jpba.2017.05.049.
Britt, Kadie Elizabeth. 2021. “Insect Pest Management in Hemp in Virginia,” April. https://vtechworks.lib.vt.edu/handle/10919/103014.
Campbell, Brian J., Abdel F. Berrada, Chris Hudalla, Stefano Amaducci, and John K. McKay. 2019. “Genotype × Environment Interactions of Industrial Hemp Cultivars Highlight Diverse Responses to Environmental Factors.” Agrosystems, Geosciences & Environment 2 (1): 180057. https://doi.org/https://doi.org/10.2134/age2018.11.0057.
Carlson, Craig H., George M. Stack, Yu Jiang, Bircan Taşkıran, Ali R. Cala, Jacob A. Toth, Glenn Philippe, Jocelyn K. C. Rose, Christine D. Smart, and Lawrence B. Smart. 2021. “Morphometric Relationships and Their Contribution to Biomass and Cannabinoid Yield in Hybrids of Hemp (Cannabis Sativa).” bioRxiv, 2021.05.09.443329. https://doi.org/10.1101/2021.05.09.443329.
Casano, S., G. Grassi, V. Martini, and M. Michelozzi. 2011. “Variations in Terpene Profiles of Different Strains of Cannabis Sativa L.” Acta Horticulturae, no. 925: 115–21. https://doi.org/10.17660/ActaHortic.2011.925.15.
Charles, Bill. 1708. An Act for Continuing the Act for Ascertaining the Tythes of Hemp and Flax. [London: printed by Charles Bill,; the executrix of Thomas Newcomb, deceas’d; printers to the Queens most excellent Majesty. http://galenet.galegroup.com/servlet/ECCO?c=1&stp=Author&ste=11&af=BN&ae=N053264&tiPG=1&dd=0&dc=flc&docNum=CW124018875&vrsn=1.0&srchtp=a&d4=0.33&n=10&SU=0LRJ&locID=cornell.
Ciolino, Laura A., Tracy L. Ranieri, and Allison M. Taylor. 2018. “Commercial Cannabis Consumer Products Part 2: HPLC-DAD Quantitative Analysis of Cannabis Cannabinoids.” Forensic Science International 289: 438–47. https://doi.org/10.1016/j.forsciint.2018.05.033.
Citti, Cinzia, Daniela Braghiroli, Maria Angela Vandelli, and Giuseppe Cannazza. 2018. “Pharmaceutical and Biomedical Analysis of Cannabinoids: A Critical Review.” Journal of Pharmaceutical and Biomedical Analysis, Review issue 2017, 147: 565–79. https://doi.org/10.1016/j.jpba.2017.06.003.
Citti, Cinzia, Barbara Pacchetti, Maria Angela Vandelli, Flavio Forni, and Giuseppe Cannazza. 2018. “Analysis of Cannabinoids in Commercial Hemp Seed Oil and Decarboxylation Kinetics Studies of Cannabidiolic Acid (CBDA).” Journal of Pharmaceutical and Biomedical Analysis 149: 532–40. https://doi.org/10.1016/j.jpba.2017.11.044.
Comeau, Zachary J., Nicholas T. Boileau, Tiah Lee, Owen A. Melville, Nicole A. Rice, Yen Troung, Cory S. Harris, Benoît H. Lessard, and Adam J. Shuhendler. 2018. “On the Spot Detection and Speciation of Cannabinoids Using Organic Thin-Film Transistors.” ACS Sensors 4 (10): 2706–15. https://doi.org/10.1021/acssensors.9b01150.
Cosentino, Salvatore Luciano, Giorgio Testa, Danilo Scordia, and Venera Copani. 2012. “Sowing Time and Prediction of Flowering of Different Hemp (Cannabis Sativa L.) Genotypes in Southern Europe.” Industrial Crops and Products 37 (1): 20–33. https://doi.org/10.1016/j.indcrop.2011.11.017.
Cranshaw, Whitney, Melissa Schreiner, Kadie Britt, Thomas P Kuhar, John McPartland, and Jerome Grant. 2019. “Developing Insect Pest Management Systems for Hemp in the United States: A Work in Progress.” Journal of Integrated Pest Management 10 (1). https://doi.org/10.1093/jipm/pmz023.
Cranshaw, Whitney S., Susan E. Halbert, Colin Favret, Kadie E. Britt, and Gary L. Miller. 2018. “Phorodon Cannabis Passerini (Hemiptera: Aphididae), a Newly Recognized Pest in North America Found on Industrial Hemp.” Insecta Mundi, October. https://journals.flvc.org/mundi/article/view/0662.
Danziger, Nadav, and Nirit Bernstein. 2021. “Light Matters: Effect of Light Spectra on Cannabinoid Profile and Plant Development of Medical Cannabis (Cannabis Sativa L.).” Industrial Crops and Products 164: 113351. https://doi.org/10.1016/j.indcrop.2021.113351.
Daryl T. Ehrensing. 1998. “Feasibility of Industrial Hemp Production in the United States Northwest.” Department of Crop; Soil Science Oregon State University. https://catalog.extension.oregonstate.edu/sites/catalog/files/project/pdf/sb681.pdf.
David, James. 1729. “Short Rules and Observations for Sowing of Lint-Seed and Hemp-Seed, and for Pulling and Dressing the Flax and Hemp.” Commissioners; Trustees for Improving Fisheries; Manufactures in Scotland.
Dayanandan, P., and Peter B. Kaufman. 1976. “Trichomes of Cannabis Sativa L. (Cannabaceae).” American Journal of Botany 63 (5): 578–91. https://doi.org/10.2307/2441821.
De Backer, Benjamin, Benjamin Debrus, Pierre Lebrun, Laetitia Theunis, Nathalie Dubois, Lies Decock, Alain Verstraete, Philippe Hubert, and Corinne Charlier. 2009. “Innovative Development and Validation of an HPLC/DAD Method for the Qualitative and Quantitative Determination of Major Cannabinoids in Cannabis Plant Material.” Journal of Chromatography B 877 (32): 4115–24. https://doi.org/10.1016/j.jchromb.2009.11.004.
Devi, Vibha, and Shabina Khanam. 2018. “Comparative Study of Different Extraction Processes for Hemp (Cannabis Sativa) Seed Oil Considering Physical, Chemical and Industrial-Scale Economic Aspects.” Journal of Cleaner Production 207: 645–57. https://doi.org/10.1016/j.jclepro.2018.10.036.
Dowling, Caroline A., Rainer Melzer, and Susanne Schilling. 2021. “Timing Is Everything: The Genetics of Flowering Time in Cannabis Sativa.” The Biochemist 43 (3): 34–38. https://doi.org/10.1042/bio_2021_138.
Dufresnes, Christophe, Catherine Jan, Friederike Bienert, Jérôme Goudet, and Luca Fumagalli. 2017. “Broad-Scale Genetic Diversity of Cannabis for Forensic Applications.” PLOS ONE 12 (1): e0170522. https://doi.org/10.1371/journal.pone.0170522.
Eichhorn Bilodeau, Samuel, Bo-Sen Wu, Anne-Sophie Rufyikiri, Sarah MacPherson, and Mark Lefsrud. 2019. “An Update on Plant Photobiology and Implications for Cannabis Production.” Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.00296.
Eric Anderson. 2019. “Industrial Hemp Production in Michigan,” 8.
Farinas, C., and Hand F. Peduto. 2020. “First Report of Golovinomyces Spadiceus Causing Powdery Mildew on Industrial Hemp (Cannabis Sativa) in Ohio.” Plant Disease 104 (10): 2727–7. https://doi.org/10.1094/PDIS-01-20-0198-PDN.
Farmer. 1775. An Essay on the Culture and Management of Hemp: More Particularly for the Purpose of Making Coarse Linens.: [Two Lines in Latin from Virgil]. Annapolis. http://opac.newsbank.com/select/evans/14022.
Faux, A. -M., X. Draye, R. Lambert, R. d’Andrimont, P. Raulier, and P. Bertin. 2013. “The Relationship of Stem and Seed Yields to Flowering Phenology and Sex Expression in Monoecious Hemp (Cannabis Sativa L.).” European Journal of Agronomy 47: 11–22. https://doi.org/10.1016/j.eja.2013.01.006.
Gee. 1767. Considerations on the Expediency of a Bounty Upon Hemp and Flax of Home Growth, &c. &C. [London. http://galenet.galegroup.com/servlet/ECCO?c=1&stp=Author&ste=11&af=BN&ae=T140824&tiPG=1&dd=0&dc=flc&docNum=CW106517206&vrsn=1.0&srchtp=a&d4=0.33&n=10&SU=0LRL+OR+0LRI&locID=cornell.
Giusti, M. Mónica, and Ronald E. Wrolstad. 2001. “Characterization and Measurement of Anthocyanins by UV-Visible Spectroscopy.” Current Protocols in Food Analytical Chemistry 00 (1): F1.2.1–F1.2.13. https://doi.org/10/bmsmfw.
Grassi, Gianpaolo, and John M. McPartland. 2017. “Chemical and Morphological Phenotypes in Breeding of Cannabis Sativa L.” In Cannabis Sativa L. - Botany and Biotechnology, edited by Suman Chandra, Hemant Lata, and Mahmoud A. ElSohly, 137–60. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-54564-6_6.
Grishko, NN and Levchenko, VI and Seletski, VI. 1937. “Question of Sex in Hemp, the Production of Monoecious Forms and of Varieties with Simoultaneous Ripening of Both Sexes.” Vszesoy. Nauchno-Issled. Inst. Konopli, Moskow, Leningrad 5: 73–108.
Hall, Jack, Surya P. Bhattarai, and David J. Midmore. 2012. “Review of Flowering Control in Industrial Hemp.” Journal of Natural Fibers 9 (1): 23–36. https://doi.org/10.1080/15440478.2012.651848.
Hampton, Joe. 2000. Industrial Hemp Investigative and Advisory Task Force Report. State of Illinois. http://hdl.handle.net/2027/uiug.30112032826049.
Haney, Alan, and Benjamin B. Kutscheid. 1975. “An Ecological Study of Naturalized Hemp (Cannabis Sativa L.) in East-Central Illinois.” American Midland Naturalist 93 (1): 1. https://doi.org/10.2307/2424101.
Hanuš, Lumír Ondřej, and Yotam Hod. 2020. “Terpenes/Terpenoids in Cannabis: Are They Important?” Medical Cannabis and Cannabinoids 3 (1): 25–60. https://doi.org/10.1159/000509733.
Hazekamp, A., and J. T. Fischedick. 2012. “Cannabis - from Cultivar to Chemovar.” Drug Testing and Analysis 4 (7-8): 660–67. https://doi.org/10.1002/dta.407.
Hädener, Marianne, Stefan König, and Wolfgang Weinmann. 2018. “Quantitative Determination of CBD and THC and Their Acid Precursors in Confiscated Cannabis Samples by HPLC-DAD.” Forensic Science International 299: 142–50. https://doi.org/10.1016/j.forsciint.2019.03.046.
He, Bingqing, Penglin Shen, Hongjuan Zheng, Yi Chu, Jinqiu Guan, and Lan Li. 2020. “Effects of Different Hormones on Germination and Callus Induction of Hemp Seeds.” IOP Conference Series: Earth and Environmental Science 526: 012043. https://doi.org/10.1088/1755-1315/526/1/012043.
Hillig, Karl W. 2005. “A Combined Analysis of Agronomic Traits and Allozyme Allele Frequencies for 69 Cannabis Accessions.” Journal of Industrial Hemp 10 (1): 17–30. https://doi.org/10.1300/J237v10n01_03.
H M G Van der Werf, W C A van Geel, and M Wijlhuizen. 1995. “Agronomic Research on Hemp in the Netherlands, 1987-1993.” http://druglibrary.net/olsen/HEMP/IHA/iha02107.html.
Hu, Huaran, Hao Liu, and Feihu Liu. 2018. “Seed Germination of Hemp (Cannabis Sativa L.) Cultivars Responds Differently to the Stress of Salt Type and Concentration.” Industrial Crops and Products 123: 254–61. https://doi.org/10.1016/j.indcrop.2018.06.089.
Hu, Jiahuai, Robert Masson, and Laura Dickey. 2020. “First Report of Beet Curly Top Virus Infecting Industrial Hemp (Cannabis Sativa) in Arizona.” Plant Disease. https://doi.org/10/gmtg62.
Humphrey, John R. 1919. Marketing Hemp. Lexington : http://hdl.handle.net/2027/uiug.30112019587614.
Hurgobin, Bhavna, Muluneh Tamiru-Oli, Matthew T. Welling, Monika S. Doblin, Antony Bacic, James Whelan, and Mathew G. Lewsey. 2021. “Recent Advances in Cannabis Sativa Genomics Research.” New Phytologist 230 (1): 73–89. https://doi.org/10.1111/nph.17140.
Hutton, William C., Joel R. Garbow, and Thomas R. Hayes. 1999. “Nondestructive NMR Determination of Oil Composition in Transformed Canola Seeds.” Lipids 34 (12): 1339–46. https://doi.org/10.1007/s11745-999-0487-0.
International Union for the Protection of New Varieties of Plants. 2012. “Guidelines for the Conduct of Tests for Distinctness, Uniformity and Stability.” https://www.upov.int/edocs/tgdocs/en/tg276.pdf.
Jian, Fuji, Md Abdullah Al Mamun, Noel D. G. White, Digvir S. Jayas, Paul G. Fields, and Jennifer McCombe. 2018. “Safe Storage Times of FINOLA® Hemp (Cannabis Sativa) Seeds with Dockage.” Journal of Stored Products Research 83: 34–43. https://doi.org/10.1016/j.jspr.2019.05.013.
Jin, Dan, Shengxi Jin, Yang Yu, Colin Lee, and Jie Chen. 2017. “Classification of Cannabis Cultivars Marketed in Canada for Medical Purposes by Quantification of Cannabinoids and Terpenes Using HPLC-DAD and GC-MS.” Journal of Analytical & Bioanalytical Techniques 08. https://doi.org/10.4172/2155-9872.1000349.
Johnson, Renée. 2018. “Hemp as an Agricultural Commodity.” CRS Report, 47.
Kadie Britt. 2021. “Key Insect and Mite Pests of Cannabis Sativa.” Department of Entomology, University of California, Riverside.
Kovalchuk, I., M. Pellino, P. Rigault, R. van Velzen, J. Ebersbach, J. R. Ashnest, M. Mau, et al. 2020. “The Genomics of Cannabis and Its Close Relatives.” Annual Review of Plant Biology 71 (1): 713–39. https://doi.org/10.1146/annurev-arplant-081519-040203.
Križman, Mitja. 2020. “A Simplified Approach for Isocratic HPLC Analysis of Cannabinoids by Fine Tuning Chromatographic Selectivity.” European Food Research and Technology 246 (2): 315–22. https://doi.org/10.1007/s00217-019-03344-7.
Laverty, Kaitlin U., Jake M. Stout, Mitchell J. Sullivan, Hardik Shah, Navdeep Gill, Larry Holbrook, Gintaras Deikus, et al. 2018. “A Physical and Genetic Map of Cannabis Sativa Identifies Extensive Rearrangements at the THC/CBD Acid Synthase Loci.” Genome Research 29 (1): 146–56. https://doi.org/10.1101/gr.242594.118.
Lisson, S. N., N. J. Mendham, and P. S. Carberry. 2000. “Development of a Hemp (Cannabis Sativa L.) Simulation Model 2.The Flowering Response of Two Hemp Cultivars to Photoperiod.” Australian Journal of Experimental Agriculture 40 (3): 413–17. https://doi.org/10.1071/ea99059.
Lynch, Ryan C., Daniela Vergara, Silas Tittes, Kristin White, C. J. Schwartz, Matthew J. Gibbs, Travis C. Ruthenburg, Kymron deCesare, Donald P. Land, and Nolan C. Kane. 2016. “Genomic and Chemical Diversity in Cannabis.” Critical Reviews in Plant Sciences 35 (5-6): 349–63. https://doi.org/10.1080/07352689.2016.1265363.
Magagnini, Gianmaria, Gianpaolo Grassi, and Stiina Kotiranta. 2018. “The Effect of Light Spectrum on the Morphology and Cannabinoid Content of Cannabis Sativa L.” Medical Cannabis and Cannabinoids 1 (1): 19–27. https://doi.org/10.1159/000489030.
Mah, Lawrence Murphy. 1923. “Hemp. Cannabis Sativa; an Agronomic Study.” PhD thesis, [Berkeley]. http://hdl.handle.net/2027/uc1.b3807516.
Mandolino, G., A. Carboni, S. Forapani, V. Faeti, and P. Ranalli. 1999. “Identification of DNA Markers Linked to the Male Sex in Dioecious Hemp (Cannabis Sativa L.):” Theoretical and Applied Genetics 98 (1): 86–92. https://doi.org/10.1007/s001220051043.
Mandrioli, Mara, Matilde Tura, Stefano Scotti, and Tullia Gallina Toschi. 2018. “Fast Detection of 10 Cannabinoids by RP-HPLC-UV Method in Cannabis Sativa L.” Molecules 24 (11): 2113. https://doi.org/10.3390/molecules24112113.
Marcandier. 1764. A Treatise on Hemp: In Two Parts. Containing I. Its History, ... II. The Methods of Cultivating, Dressing, and Manufacturing It, ... Translated from the French of M. Marcandier, . London: printed for T. Becket,; P. A. de Hondt. http://galenet.galegroup.com/servlet/ECCO?c=1&stp=Author&ste=11&af=BN&ae=T122611&tiPG=1&dd=0&dc=flc&docNum=CW108992661&vrsn=1.0&srchtp=a&d4=0.33&n=10&SU=0LRM&locID=cornell.
McKernan, Kevin J., Yvonne Helbert, Liam T. Kane, Heather Ebling, Lei Zhang, Biao Liu, Zachary Eaton, et al. 2020. “Sequence and Annotation of 42 Cannabis Genomes Reveals Extensive Copy Number Variation in Cannabinoid Synthesis and Pathogen Resistance Genes.” bioRxiv, 2020.01.03.894428. https://doi.org/10.1101/2020.01.03.894428.
McPartland, John M., and Karl W. Hillig. 2003. “The Hemp Russet Mite.” Journal of Industrial Hemp 8 (2): 107–12. https://doi.org/10/b4wzwq.
McPartland, John Michael, Robert Connell Clarke, and David Paul Watson. 2000. Hemp Diseases and Pests: Management and Biological Control : An Advanced Treatise. CABI.
Meijer, E. P. M. de, and K. M. Hammond. 2005. “The Inheritance of Chemical Phenotype in Cannabis Sativa L. (II): Cannabigerol Predominant Plants.” Euphytica 145 (1): 189–98. https://doi.org/10.1007/s10681-005-1164-8.
Meijer, E. P. M. de, and L. C. P. Keizer. 1996. “Patterns of Diversity in Cannabis.” Genetic Resources and Crop Evolution 43 (1): 41–52. https://doi.org/10.1007/BF00126939.
Mishchenko, S. V., and I. M. Lajko. 2016. “Variability of Quantitative Characters of Linear Hemp Hybrids F1-F3 of Mid-Russian and Southern Eco-Geographical Types.” Herald of the Ul’ianovskoj Gorudarstvennoj Sel’skokhoziajstvennoj Akademii, 30–36. https://doi.org/10.18286/1816-4501-2016-2-30-36.
Moon, Youn-Ho, Young-Lok Cha, Ji-Eun Lee, Kwang-Soo Kim, Da-Eun Kwon, and Yong-Ku Kang. 2020. “Investigation of Suitable Seed Sizes, Segregation of Ripe Seeds, and Improved Germination Rate for the Commercial Production of Hemp Sprouts (Cannabis Sativa L.).” Journal of the Science of Food and Agriculture 100 (7): 2819–27. https://doi.org/10.1002/jsfa.10294.
Musio, Salvatore, Jörg Müssig, and Stefano Amaducci. 2018. “Optimizing Hemp Fiber Production for High Performance Composite Applications.” Frontiers in Plant Science 9. https://doi.org/10.3389/fpls.2018.01702.
Nahar, Lutfun, Alev Onder, and Satyajit D. Sarker. 2020. “A Review on the Recent Advances in HPLC, UHPLC and UPLC Analyses of Naturally Occurring Cannabinoids (2010–2019).” Phytochemical Analysis 31 (4): 413–57. https://doi.org/https://doi.org/10.1002/pca.2906.
Pahkala, Katri, Elina Pahkala, and Heidi Syrjälä. 2008. “Northern Limits to Fiber Hemp Production in Europe.” Journal of Industrial Hemp 13 (2): 104–16. https://doi.org/10.1080/15377880802391084.
Palmieri, Sara, Marcello Mascini, Antonella Ricci, Federico Fanti, Chiara Ottaviani, Claudio Lo Sterzo, and Manuel Sergi. 2018. “Identification of Cannabis Sativa L. (Hemp) Retailers by Means of Multivariate Analysis of Cannabinoids.” Molecules 24 (19): 3602. https://doi.org/10.3390/molecules24193602.
Pandohee, Jessica, Brendan J. Holland, Bingshan Li, Takuya Tsuzuki, Paul G. Stevenson, Neil W. Barnett, James R. Pearson, Oliver A. H. Jones, and Xavier A. Conlan. 2015. “Screening of Cannabinoids in Industrial-Grade Hemp Using Two-Dimensional Liquid Chromatography Coupled with Acidic Potassium Permanganate Chemiluminescence Detection.” Journal of Separation Science 38 (12): 2024–32. https://doi.org/https://doi.org/10.1002/jssc.201500088.
Patel, Bhupendra, Daniel Wene, and Zhihua (Tina) Fan. 2017. “Qualitative and Quantitative Measurement of Cannabinoids in Cannabis Using Modified HPLC/DAD Method.” Journal of Pharmaceutical and Biomedical Analysis 146: 15–23. https://doi.org/10.1016/j.jpba.2017.07.021.
Pavlovic, Radmila, Sara Panseri, Luca Giupponi, Valeria Leoni, Cinzia Citti, Chiara Cattaneo, Maria Cavaletto, and Annamaria Giorgi. 2019. “Phytochemical and Ecological Analysis of Two Varieties of Hemp (Cannabis Sativa L.) Grown in a Mountain Environment of Italian Alps.” Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.01265.
Pellati, Federica, Virginia Brighenti, Johanna Sperlea, Lucia Marchetti, Davide Bertelli, and Stefania Benvenuti. 2018. “New Methods for the Comprehensive Analysis of Bioactive Compounds in Cannabis Sativa L. (Hemp).” Molecules 23 (10): 2639. https://doi.org/10.3390/molecules23102639.
Pertwee, Roger. 2014. Handbook of Cannabis. OUP Oxford.
Petit, Jordi, Elma M. J. Salentijn, Maria-João Paulo, Christel Denneboom, Eibertus N. van Loo, and Luisa M. Trindade. 2020. “Elucidating the Genetic Architecture of Fiber Quality in Hemp (Cannabis Sativa L.) Using a Genome-Wide Association Study.” Frontiers in Genetics 11. https://doi.org/10.3389/fgene.2020.566314.
Piluzza, G., G. Delogu, A. Cabras, S. Marceddu, and S. Bullitta. 2013. “Differentiation Between Fiber and Drug Types of Hemp (Cannabis Sativa L.) from a Collection of Wild and Domesticated Accessions.” Genetic Resources and Crop Evolution 60 (8): 2331–42. https://doi.org/10.1007/s10722-013-0001-5.
Pollastro, Federica, Alberto Minassi, and Luigia G. Fresu. 2018. “Cannabis Phenolics and Their Bioactivities.” Current Medicinal Chemistry 25 (10): 1160–85. https://doi.org/10.2174/0929867324666170810164636.
Protti, Michele, Virginia Brighenti, Maria Rita Battaglia, Lisa Anceschi, Federica Pellati, and Laura Mercolini. 2018. “Cannabinoids from Cannabis Sativa L.: A New Tool Based on HPLC–DAD–MS/MS for a Rational Use in Medicinal Chemistry.” ACS Medicinal Chemistry Letters 10 (4): 539–44. https://doi.org/10.1021/acsmedchemlett.8b00571.
Punja, Zamir K., and Janesse E. Holmes. 2020. “Hermaphroditism in Marijuana (Cannabis Sativa L.) Inflorescences – Impact on Floral Morphology, Seed Formation, Progeny Sex Ratios, and Genetic Variation.” Frontiers in Plant Science 11. https://doi.org/10.3389/fpls.2020.00718.
Punja, Zamir K., Gina Rodriguez, and Sarah Chen. 2017. “Assessing Genetic Diversity in Cannabis Sativa Using Molecular Approaches.” In Cannabis Sativa L. - Botany and Biotechnology, edited by Suman Chandra, Hemant Lata, and Mahmoud A. ElSohly, 395–418. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-54564-6_19.
Ranalli, Paolo. 1999. Advances in Hemp Research. New York: Food Products Press.
Razumova, Olga V., Oleg S. Alexandrov, Mikhail G. Divashuk, Tatiana I. Sukhorada, and Gennady I. Karlov. 2016. “Molecular Cytogenetic Analysis of Monoecious Hemp (Cannabis Sativa L.) Cultivars Reveals Its Karyotype Variations and Sex Chromosomes Constitution.” Protoplasma 253 (3): 895–901. https://doi.org/10.1007/s00709-015-0851-0.
Razumova, O. V. 2014. “Using of Sex Linked Dna Markers for Assessment the Quality of Monoecious Hemp Seeds.” https://cyberleninka.ru/article/n/ispolzovanie-polospetsifichnyh-dnk-markerov-dlya-otsenki-kachestva-semyan-odnodomnyh-sortov-konopli-posevnoy.
Reimann-Philipp, Ulrich, Mark Speck, Cindy Orser, Steve Johnson, Aaron Hilyard, Helen Turner, Alexander J. Stokes, and Andrea L. Small-Howard. 2018. “Cannabis Chemovar Nomenclature Misrepresents Chemical and Genetic Diversity; Survey of Variations in Chemical Profiles and Genetic Markers in Nevada Medical Cannabis Samples.” Cannabis and Cannabinoid Research. https://doi.org/10.1089/can.2018.0063.
Ribnicky, David, Alexander Poulev, Slavik Dushenkov, Ilya Raskin, and Cary Leizer. 2000. “The Composition of Hemp Seed Oil and Its Potential as an Important Source of Nutrition.” Journal of Nutraceuticals, Functional & Medical Foods 2 (4): 35–53. https://doi.org/10.1300/J133v02n04_04.
Rongpipi, Sintu, Dan Ye, Enrique D. Gomez, and Esther W. Gomez. 2019. “Progress and Opportunities in the Characterization of Cellulose – an Important Regulator of Cell Wall Growth and Mechanics.” Frontiers in Plant Science 9. https://doi.org/10.3389/fpls.2018.01894.
Russo, Ethan B. 2011. “Taming THC: Potential Cannabis Synergy and Phytocannabinoid-Terpenoid Entourage Effects.” British Journal of Pharmacology 163 (7): 1344–64. https://doi.org/10.1111/j.1476-5381.2011.01238.x.
Rustichelli, C., V. Ferioli, M. Baraldi, P. Zanoli, and G. Gamberini. 1998. “Analysis of Cannabinoids in Fiber Hemp Plant Varieties (Cannabis Sativa L.) by High-Performance Liquid Chromatography.” Chromatographia 48 (3-4): 215–22. https://doi.org/10.1007/BF02467674.
Salentijn, Elma M. J., Jordi Petit, and Luisa M. Trindade. 2019. “The Complex Interactions Between Flowering Behavior and Fiber Quality in Hemp.” Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.00614.
Salentijn, Elma M. J., Qingying Zhang, Stefano Amaducci, Ming Yang, and Luisa M. Trindade. 2015. “New Developments in Fiber Hemp (Cannabis Sativa L.) Breeding.” Industrial Crops and Products, FIBRE CROPS: From production to end use, 68: 32–41. https://doi.org/10.1016/j.indcrop.2014.08.011.
Schaffner, John H. 1921. “Influence of Environment on Sexual Expression in Hemp.” Botanical Gazette 71 (3): 197–219. https://doi.org/10.1086/332818.
Schultz, Carolyn J., Wai L. Lim, Shi F. Khor, Kylie A. Neumann, Jakob M. Schulz, Omid Ansari, Mark A. Skewes, and Rachel A. Burton. 2020. “Consumer and Health-Related Traits of Seed from Selected Commercial and Breeding Lines of Industrial Hemp, Cannabis Sativa L.” Journal of Agriculture and Food Research 2: 100025. https://doi.org/10.1016/j.jafr.2020.100025.
Seed Laboratory Oregon State University. 2018. “AOSCA Testing Rules.” Seed Laboratory. https://seedlab.oregonstate.edu/industrial-hemp.
Sera, Bozena, Iveta Gajdova, Bogdan Gavril, Eugen Hnatiuc, Michal Sery, and Petr Spatenka. 2012. “Hemp (Cannabis Sativa L.) Seeds After Plasma Treatment.” In 2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), 1371–4. Brasov, Romania: IEEE. https://doi.org/10.1109/OPTIM.2012.6231981.
Serkov, V. A. 2015. “Influence of Growth Regulators on Expression of Sex and Formation of a Complex of Useful Traits in Monoecious Hemp Plants.” Estestvennye Nauki: Biologiia (Natural Sciences: Biology) 3 (11). https://doi.org/633.522:631.527.
Serkov, V. A., L. V. Klimova, M. V. Danilov, R. O. Belousov, M. R. Aleksandrova, and O. K. Davydova. 2020. “New Source Material for the Selection of Nonnarcotic Varieties of Seed Hemp.” International Agricultural Journal 2 (374): 75–80. https://doi.org/10.24411/2587-6740-2020-12036.
Shams, Rezvan, Ali Azizi, Javad Hamzei, Alireza Noroozisharaf, Shoeib Moghadam, and Mojtaba Kordrostami. 2020. “Genetic Structure and Diversity of Iranian Cannabis Populations Based on Phytochemical, Agro-Morphological and Molecular Markers.” Industrial Crops and Products 158: 112950. https://doi.org/10.1016/j.indcrop.2020.112950.
Shao, Hong, Shu-Juan Song, and Robert C. Clarke. 2003. “Female-Associated DNA Polymorphisms of Hemp (Cannabis Sativa L.).” Journal of Industrial Hemp 8 (1): 5–9. https://doi.org/10.1300/J237v08n01_02.
Slator, Lionel. 1735. Instructions for the Cultivating and Raising of Flax and Hemp: In a Better Manner, Than That Generally Practis’d in Ireland. Boston: N.E.
Small, Ernest, and Brenda Brookes. 2012. “Temperature and Moisture Content for Storage Maintenance of Germination Capacity of Seeds of Industrial Hemp, Marijuana, and Ditchweed Forms of Cannabis Sativa.” Journal of Natural Fibers 9 (4): 240–55. https://doi.org/10.1080/15440478.2012.737179.
Spitzer-Rimon, Ben, Shai Duchin, Nirit Bernstein, and Rina Kamenetsky. 2019. “Architecture and Florogenesis in Female Cannabis Sativa Plants.” Frontiers in Plant Science 10. https://doi.org/10.3389/fpls.2019.00350.
Stack, George M., Jacob A. Toth, Craig H. Carlson, Ali R. Cala, Mariana I. Marrero‐González, Rebecca L. Wilk, Deanna R. Gentner, et al. 2021. “Season-Long Characterization of High-Cannabinoid Hemp (Cannabis Sativa L.) Reveals Variation in Cannabinoid Accumulation, Flowering Time, and Disease Resistance.” GCB Bioenergy n/a (n/a). https://doi.org/https://doi.org/10.1111/gcbb.12793.
Struik, P. C., S. Amaducci, M. J. Bullard, N. C. Stutterheim, G. Venturi, and H. T. H. Cromack. 1999. “Agronomy of Fibre Hemp (Cannabis Sativa L.) in Europe.” Industrial Crops and Products 11 (2): 107–18. https://doi.org/10.1016/S0926-6690(99)00048-5.
Suriyong, Sangtiwa, Nattasak Krittigamas, Sarita Pinmanee, Adirek Punyalue, and Suchada Vearasilp. 2015. “Influence of Storage Conditions on Change of Hemp Seed Quality.” Agriculture and Agricultural Science Procedia 5: 170–76. https://doi.org/10.1016/j.aaspro.2015.08.026.
Szarka, Desiree, Bernadette Amsden, Julie Beale, Ed Dixon, Christopher L. Schardl, and Nicole Gauthier. 2020. “First Report of Hemp Leaf Spot Caused by a Bipolaris Species on Hemp (Cannabis Sativa) in Kentucky.” Plant Health Progress 21 (2): 82–84. https://doi.org/10.1094/PHP-01-20-0004-BR.
Tang, K., P. C. Struik, X. Yin, C. Thouminot, M. Bjelková, V. Stramkale, and S. Amaducci. 2016. “Comparing Hemp (Cannabis Sativa L.) Cultivars for Dual-Purpose Production Under Contrasting Environments.” Industrial Crops and Products 87: 33–44. https://doi.org/10.1016/j.indcrop.2016.04.026.
Taylor, John. 1620. The Praise of Hemp Seed. https://newcatalog.library.cornell.edu/catalog/12809987.
Thiessen, Lindsey D., Tyler Schappe, Sarah Cochran, Kristin Hicks, and Angela R. Post. 2020. “Surveying for Potential Diseases and Abiotic Disorders of Industrial Hemp (Cannabis Sativa) Production.” Plant Health Progress 21 (4): 321–32. https://doi.org/10.1094/PHP-03-20-0017-RS.
Thiex, Nancy, Harold Manson, Shirley Andersson, and Jan-Åke Persson. 2002. “Determination of Crude Protein in Animal Feed, Forage, Grain, and Oilseeds by Using Block Digestion with a Copper Catalyst and Steam Distillation into Boric Acid: Collaborative Study.” Journal of AOAC International 85 (March): 309–17. https://doi.org/10/gmchr8.
Toth, Jacob A., George M. Stack, Ali R. Cala, Craig H. Carlson, Rebecca L. Wilk, Jamie L. Crawford, Donald R. Viands, et al. 2020. “Development and Validation of Genetic Markers for Sex and Cannabinoid Chemotype in Cannabis Sativa L.” GCB Bioenergy 12 (3): 213–22. https://doi.org/10.1111/gcbb.12667.
Tuma, Jimmie Lee. 1972. “Longevity, Germination, and Emergence of Wild Hemp,(Cannabis Sativa L.).” PhD thesis, Kansas State University.
Turner, Jocelyn C., John K. Hemphill, and Paul G. Mahlberg. 1978. “Quantitative Determination of Cannabinoids in Individual Glandular Trichomes of Cannabis Sativa L. (Cannabaceae).” American Journal of Botany 65 (10): 1103–6. https://doi.org/10.1002/j.1537-2197.1978.tb06177.x.
Unknown. 1720. Reasons for Encouraging the Manufacture of British Sail-Duck, and the Growth of Hemp and Flax in Great-Britain. [London. http://galenet.galegroup.com/servlet/ECCO?c=1&stp=Author&ste=11&af=BN&ae=T017275&tiPG=1&dd=0&dc=flc&docNum=CW106547679&vrsn=1.0&srchtp=a&d4=0.33&n=10&SU=0LRL+OR+0LRI&locID=cornell.
USDA. 2009. Testing Guidelines for Identifying Delta-9 Tetrahydrocannabinol (THC) Concentration in Hemp. Vienna: United Nations.
Vaknin, Yiftach, Miriam Ghanim, Shahar Samra, Levana Dvash, Efrat Hendelsman, Dan Eisikowitch, and Yael Samocha. 2011. “Predicting Jatropha Curcas Seed-Oil Content, Oil Composition and Protein Content Using Near-Infrared Spectroscopy—A Quick and Non-Destructive Method.” Industrial Crops and Products 34 (1): 1029–34. https://doi.org/10.1016/j.indcrop.2011.03.011.
Vavilov, N. I. 1957. “World Resources Leguminous Seed of Cereals, Crops and Flax, and Their Utilization in Plant Breeding.”
Vergara, Daniela, Halie Baker, Kayla Clancy, Kyle G. Keepers, J. Paul Mendieta, Christopher S. Pauli, Silas B. Tittes, Kristin H. White, and Nolan C. Kane. 2016. “Genetic and Genomic Tools for Cannabis Sativa.” Critical Reviews in Plant Sciences 35 (5-6): 364–77. https://doi.org/10.1080/07352689.2016.1267496.
Vergara, Daniela, Ezra L. Huscher, Kyle G. Keepers, Rahul Pisupati, Anna L. Schwabe, Mitchell E. McGlaughlin, and Nolan C. Kane. 2021. “Genomic Evidence That Governmentally Produced Cannabis Sativa Poorly Represents Genetic Variation Available in State Markets.” bioRxiv, 2021.02.13.431041. https://doi.org/10.1101/2021.02.13.431041.
Wang, Yan-Hong, Bharathi Avula, Mahmoud ElSohly, Mohamed Radwan, Mei Wang, Amira Wanas, Zlatko Mehmedic, and Ikhlas Khan. 2018. “Quantitative Determination of δ9-THC, CBG, CBD, Their Acid Precursors and Five Other Neutral Cannabinoids by UHPLC-UV-MS.” Planta Medica 84 (04): 260–66. https://doi.org/10.1055/s-0043-124873.
Weijde, Tim van der, Andres F. Torres, Oene Dolstra, Annemarie Dechesne, Richard G. F. Visser, and Luisa M. Trindade. 2016. “Impact of Different Lignin Fractions on Saccharification Efficiency in Diverse Species of the Bioenergy Crop Miscanthus.” BioEnergy Research 9 (1): 146–56. https://doi.org/10.1007/s12155-015-9669-z.
Werf, H. M. G. van der, W. C. A. van Geel, L. J. C. van Gils, and A. J. Haverkort. 1995. “Nitrogen Fertilization and Row Width Affect Self-Thinning and Productivity of Fibre Hemp (Cannabis Sativa L.).” Field Crops Research 42 (1): 27–37. https://doi.org/10.1016/0378-4290(95)00017-K.
Werf, H. M. G. van der, H. J. Haasken, and M. Wijlhuizen. 1994. “The Effect of Daylength on Yield and Quality of Fibre Hemp (Cannabis Sativa L.).” European Journal of Agronomy 3 (2): 117–23. https://doi.org/10.1016/S1161-0301(14)80117-2.
Williams, D. W., ed. 2019. Industrial Hemp as a Modern Commodity Crop. ASA, CSSA, and SSSA Books. Madison, WI, USA: American Society of Agronomy Crop Science Society of America Soil Science Society of America. https://doi.org/10.2134/industrialhemp.
Wissett, Robert. 1808. A Treatise on Hemp, Including a Comprehensive Account of the Best Modes of Cultivation and Preparation as Practised in Europe, Asia, and America: With Observations on the Sunn Plant of India, Which May Be Introduced as a Substitute for Many of the Purposes to Which Hemp Is Now Exclusively Applied. London: J. Harding.
Yadav, Praduman, and I. Y. L. N. Murthy. 2016. “Calibration of NMR Spectroscopy for Accurate Estimation of Oil Content in Sunflower, Safflower and Castor Seeds.” Current Science 110 (1): 73–76. http://www.jstor.org/stable/24906613.
Zatta, Alessandro, Andrea Monti, and Gianpietro Venturi. 2012. “Eighty Years of Studies on Industrial Hemp in the Po Valley (1930–2010).” Journal of Natural Fibers 9 (3): 180–96. https://doi.org/10.1080/15440478.2012.706439.
Zhang, Qingying, Xuan Chen, Hongyan Guo, Luisa M. Trindade, Elma M. J. Salentijn, Rong Guo, Mengbi Guo, Yanping Xu, and Ming Yang. 2018. “Latitudinal Adaptation and Genetic Insights into the Origins of Cannabis Sativa L.” Frontiers in Plant Science 9. https://doi.org/10.3389/fpls.2018.01876.
Zivovinovic, Sanja, Ruth Alder, Martina D. Allenspach, and Christian Steuer. 2018. “Determination of Cannabinoids in Cannabis Sativa L. Samples for Recreational, Medical, and Forensic Purposes by Reversed-Phase Liquid Chromatography-Ultraviolet Detection.” Journal of Analytical Science and Technology 9 (1): 27. https://doi.org/10.1186/s40543-018-0159-8.