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Record W7081965120 · doi:10.25675/3.04139

Assessing the impact of hop latent viroid (HLVD) on hemp (Cannabis sativa) and exploring mitigation strategies

2024· other· en· W7081965120 on OpenAlexaboutno aff

Bibliographic record

VenueColorado State University · 2024
Typeother
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsCannabis sativaUnicornCultivarYield (engineering)AgricultureHop (telecommunications)Crop

Abstract

fetched live from OpenAlex

The emergence of hop latent viroid (HLVd) in the hemp (Cannabis sativa L. <0.3% THC) and marijuana (C. sativa >0.3% THC) industries poses a significant threat to agricultural production. Since its first identification in California in 2019, HLVd has spread across the U.S. and Canada, causing substantial yield losses due to its ability to severely disrupt crop development. Mechanically transmitted through propagation, pollen, seed, and water, HLVd is challenging to control; and its impact on emerging crops like hemp is of particular concern. The overarching goal of this thesis was to determine the impact of HLVd on hemp quality and yield and to apply new knowledge and practices to manage HLVd, reducing losses in the hemp and marijuana industries in the U.S. and worldwide. Two objectives achieved this goal: 1) assess the impact of HLVd on the growth and yield of two hemp cultivars, NWG 2463 (dual-purpose fiber grain) and Unicorn (CBD), and 2) determine the effect of chemical elicitors in reducing HLVd infection levels and symptom development. HLVd infection did not impact overall yield metrics—such as biomass, flower, or seed yield—in either the dual-purpose cultivar NWG 2463 or the CBD cultivar Unicorn under the conditions of this study. However, HLVd-symptomatic plants in the CBD Unicorn cultivar exhibited significant reductions in cannabinoid levels, specifically THCA and CBLA: CBCA. These findings highlight the critical risks that HLVd presents to producers relying on consistent cannabinoid profiles. RT-qPCR analysis indicated that specific chemical elicitors may reduce HLVd levels in the CBD Unicorn cultivar, with 1-Triacontanol (TRIA) showing a marginally significant reduction in viroid titers compared to its ethanol (EtOH) control (p = 0.07), and Kinetin demonstrating a trend toward significance against its potassium hydroxide (KOH) control (p = 0.08). Beyond potential viroid reduction, chemical elicitors such as salicylic acid (SA), brassinolides (BR), and 6-benzylaminopurine (BAP) significantly increased biomass and flower production in the CBD Unicorn cultivar infected with HLVd. However, SA, BR, TRIA, chlormequat chloride (CCC), and methyl jasmonate (MeJA) also reduced key cannabinoid levels, notably THC and CBD, highlighting the complexity of using chemical elicitors in viroid-infected plants. The observed trade-off between enhanced plant growth and reduced cannabinoid content suggests that, although chemical elicitors may offer potential as part of an integrated management strategy, their application must be carefully optimized to avoid unintended crop losses. This research provides critical insights into the broader agricultural implications of HLVd on hemp production and highlights the need for refined viroid management practices. The potential impact of HLVd on hemp emphasizes the urgency of developing targeted strategies that balance yield improvement with cannabinoid preservation, thereby safeguarding the financial viability of hemp cultivation in the face of viroid challenges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.595
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.257
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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