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Enregistrement W2729015700 · doi:10.2134/csa2017.62.0709

HIA Industrial Hemp Conference: Science, Industry, and Policy

2017· article· en· W2729015700 sur OpenAlexaboutno aff
Delyth W. Williams

Notice bibliographique

RevueCSA News · 2017
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueCassava research and cyanide
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSession (web analytics)WitnessEngineeringLibrary scienceManagementPolitical scienceAdvertisingBusinessLaw

Résumé

récupéré en direct d'OpenAlex

Photo courtesy of Jeff Kostuik/Hemp Genetics International This year, CSSA and ASA are partnering with the Hemp Industries Association (HIA) and the University of Kentucky (UK) to host the 2017 HIA Conference in Lexington, KY, 8–11 September. The conference is themed “Share the Vision.” For the first time, the conference program will include concurrent tracks covering diverse topics in science, industry, and policy as related to the evolving industrial hemp (Cannabis sativa L.) industry in the U.S. as well as a moderated session integrating topics and participants from all three perspectives. For complete information, please see: https://thehia.org/event-2535421. The conference begins Friday, 8 September with meetings and events for HIA members only and will include the annual business meeting and other association matters. An all-day hemp farming/processing tour will be provided to conference registrants on Saturday, 9 September. The tour begins with the UK agronomic science industrial hemp research field day at the Agricultural Experiment Station Spindletop Farm in Lexington where lunch will be served on-site. From there, the tour will proceed to a commercial farm in neighboring Clark County to witness large-scale hemp grain harvesting by a standard combine. The last tour stop will be at the Atalo Holdings hemp research campus, also in Clark County. Here participants will witness hemp processing activities as well as learn about hemp food and cannabinoid products, culminating with dinner on-site. Concurrent tracks will begin Sunday morning following a general session for all registrants and will conclude Monday afternoon. Science tracks include presentations on hemp science visions for the future, agronomic science, fiber science, economic science, and hemp food science (human and animal foods). Science-track presentations will focus on current U.S. research and define future research needs. Industry topics include industry vision for the future, industry-wide economics, production industry issues, fiber industry issues, and hemp food industry issues. The policy track will include policy visions for the future, phytocannabinoid policy, national and state-level policy, economics policy, and intellectual property policy as related to hemp genetics. There will also be concurrent scientific poster sessions in conjunction with general exhibitions in the exhibit hall. Members of CSSA and ASA who are involved in industrial hemp research are strongly encouraged to consider presenting posters of their work during these sessions. Hemp was a U.S. commodity crop into the early 20th century and for a brief period during World War II. All species and varieties of Cannabis became schedule 1 controlled substances after the passage of the Controlled Substances Act of 1971. At that time, all GRIN germplasm was destroyed. Hence, excepting feral growth in rural areas that were previously active in hemp production, there are no sources of the old varieties bred in the U.S. and known to be well adapted to local climates and latitudes. Nearly all commercially available varieties originate from the European Union, Canada, Australia, or China. Today, efforts in hemp research are growing rapidly across the U.S. Pilot research programs are provided for in the 2014 farm bill when supported by state-level legislation. All pilot research programs must be administered by either state departments of agriculture or universities. The state department of agriculture administers the entire program in a few states while in other states, individual universities are administering programs. Generally speaking, statewide programs administered by departments of agriculture are broader in scale and scope. This is due to federal requirements regarding the monitoring of and reporting for individual research locations. Program administration becomes more onerous as the number of locations increases. Additionally, many universities are averse to serving in what is essentially a regulatory role for research sites and activities not under their direct control. According to the HIA (http://bit.ly/2rFRqLX), 26 U.S. states have legislation in place providing for pilot research programs, with at least eight additional states considering legislation. Current U.S. research efforts are very diverse. Hemp exhibits strong photoperiodism. As such, the onset of reproductive growth will vary depending both on the latitudes of origin and current production, which will significantly affect yields and harvestability. Basic variety trials are necessary to define which of the currently available, imported varieties will provide economically viable yields while requiring minimum modifications to standard harvesting equipment. Plant breeding efforts are under way to produce lines that are regionally well adapted and high yielding. Molecular biologists are defining inherent genes of strong interest as well as candidate genes for modification. Agricultural engineers are studying the potential of hemp as a feedstock for biofuels and carbonaceous materials. Food and animal scientists are investigating hemp grain as source of nutrition. The pharmaceutical potential of phytocannabinoids is of very strong interest. The science of industrial hemp is in its infancy within the U.S. The 2017 HIA conference will be the best occasion to be exposed to current research efforts with this “new”’ crop as well as an excellent opportunity for networking to define new needs and directions. Consider this: How many opportunities do you get to work with essentially an “unknown” crop that possesses significant potential and has such deep cultural interest?

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,667
Score d'incertitude au seuil0,851

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,124
Tête enseignante GPT0,335
Écart entre enseignants0,212 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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