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Enregistrement W2520338494 · doi:10.25675/3.021553

Evaluating genetic mechanisms and performance characteristics of alternative oilseed crops for on-farm biofuel production in Colorado

2015· dissertation· en· W2520338494 sur OpenAlexaboutno aff
Brian Campbell

Notice bibliographique

RevueDigital Collections of Colorado (Colorado State University) · 2015
Typedissertation
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueNitrogen and Sulfur Effects on Brassica
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBiofuelProduction (economics)AgroforestryAgricultural engineeringEnvironmental scienceAgronomyEngineeringBiotechnologyWaste managementBiologyEconomics

Résumé

récupéré en direct d'OpenAlex

Dryland winter wheat (Triticum aestivum) cropping systems dominate most of the agricultural landscape in Colorado’s semi-arid eastern plains. Since this area’s climate is characterized by frequent heat and drought, it is important to maximize water use efficiency to make agricultural lands as productive as possible. Adding a spring crop in rotation with winter wheat intensifies the rotation, increasing water use efficiency by up to 37%. Recent research has explored further intensifying this rotation by adding an oilseed crop into a wheat – spring crop – fallow rotation during the fallow period. Ideally, the oilseed crop acts as a cover crop for part of the season and leaves enough time at the end of the season to regenerate water in the soil profile before planting wheat in the fall. The oil from this crop can be used to produce on-farm biofuels, offsetting petroleum diesel costs without displacing high-value food crops. Additionally, the meal from this crop acts as a value-added byproduct by providing feed for livestock. Since traditional oilseeds such as soybean (Glycine max) and rapeseed (Brassica napus) do not perform well in Colorado, several alternative oilseeds have been tested to assess whether they can fill this niche. Camelina (Camelina sativa) has shown great potential, with high oil content and inherent resistance to many biotic and abiotic stressors. Other potential oilseeds include Brassica juncea and Brassica carinata, but both of these species have exhibited longer life cycles and lower yields than camelina. A major challenge to camelina production in Colorado is a susceptibility to heat stress during reproductive periods. Both short periods of intense heat stress and longer periods of mild heat stress can cause floral and seed abortion, resulting in reduced yield. In the current study, a quantitative trait locus (QTL) approach is used to identify heat and drought tolerance mechanisms and yield components, explore the extent of pleiotropy, epistasis, and linkage, and identify promising lines for study or production. Genetic resources for camelina are becoming more readily available and a newly developed genetic map with improved marker density was used for QTL discovery. Replicated field trials were performed during the 2014 growing season in Fort Collins and Greeley, Colorado, under differential irrigation treatments at each site to collect phenotypic data on a variety of traits. Sixteen new QTL were discovered from this data, along with nine QTL using data from Colorado trials of the same population in 2009 and 2010 performed by Enjalbert (2011). Seven QTL were discovered for yield, however, no QTL were found in more than two environments, indicating a lack of stable QTL for this trait. This was in contrast to results from Enjalbert (2011) where stable QTL for yield across environments were detected using the original, mainly AFLP generated, genetic map by Gehringer et al. (2006). This underscores the high amount of variation that can be caused by environment. QTL for other traits, such as plant height and days to flowering, were detected that were more robust, however, no QTL were detected with either data set that spanned more than three environments. Two loci were identified that affected multiple traits, supplying evidence of either pleiotropy or close linkage of genes. Several RIL performed well in multiple environments, indicating potential for production in Colorado, however, these lines were not in common with previous studies, so further trials will be needed to confirm consistently stable yields. In addition to the camelina QTL study, a two-year variety trial of Brassica carinata was performed in Fort Collins, CO during the 2013 and 2014 growing seasons under limited and full irrigation. Collaboration with the private Canadian oilseed company Agrisoma Biosciences spurred interest in reevaluating the potential of this alternative oilseed in Colorado cropping systems. Agrisoma Biosciences developed early flowering and early maturing germplasm that performs well in the Canadian prairie and is interested in testing their germplasm in new regions with potential for production. The company provided six lines for the trial, five experimental lines and one commercial check cultivar. Mean flowering time was over 13 days longer than previously tested African accessions that had been deemed too late flowering to be competitive in Colorado’s climate. Mean yields were low as well, at 669 kg ha⁻¹. The commercial check cultivar, A100, outperformed all of the experimental lines, with a mean yield of 1081 kg ha⁻¹ across environments. With a wide margin between the other lines and A100, this commercial cultivar was clearly more successful than any of the experimental lines. However, yields of this one cultivar were not sufficiently impressive to recommend on-farm testing of the crop.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,096
Score d'incertitude au seuil0,190

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,016
Tête enseignante GPT0,258
Écart entre enseignants0,242 · 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 source (Gemma direct ou Codex distillé), 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
Publié2015
Routes d'admission1
Résumé présentoui

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Même revueDigital Collections of Colorado (Colorado State University)Même sujetNitrogen and Sulfur Effects on BrassicaTravaux en français237 207