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Record W7105994941 · doi:10.7939/83222

Effects of Humalite Soil Amendment on Mitigating Drought Stress in Canola (Brassica napus L.)

2025· dissertation· en· W7105994941 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth Enhancement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaAbiotic componentCrop yieldCropDrought toleranceCroppingGreenhouseAbiotic stressMoisture stress

Abstract

fetched live from OpenAlex

Canola is one of the dominant revenue-generating crops globally. Since it was bred in the 1970s, it quickly became the third most grown oilseed crop after palm and soybean, partially due to its favorable fatty acid profiles. Drought stress is recognized as one of the most significant abiotic stressors among varying crop productions globally, where ongoing climate change has profoundly increased extreme weather incidents in croplands. In Canada, the vast majority of canola production occurs in the Canadian Prairies, where the limited water availability and increasing drought events often restrict its production. Due to its significant share of the economy in the Canadian Prairies, it is critical to seek strategies to mitigate the impact of drought stress on canola cropping systems. Humic substances have been recognized for promoting effects on soil health and bio-stimulatory effects on plant growth, with some evidence of improved overall plant stress tolerance. Humic substances have been reported to interact with plant hormone signaling pathways, particularly those that play critical roles in regulating plant growth and responses to abiotic stresses. Humalite is a naturally occurring humate material rich in humic acids exclusively deposited in southern Alberta, Canada. Its capability in improving soil organic carbon and nitrogen availability makes it a promising option for enhancing drought tolerance in canola cropping systems. In this study, we evaluated the effects of humalite on canola vegetative growth, photosynthetic and physiological traits, seed yield and oil quality parameters, as well as stress indicators, under varying moisture conditions and different growth stages. In this study, two different greenhouse studies wereconducted: (i) drought stress imposed at\nthe vegetative growing stage, and (ii) drought stress imposed at the flowering till pod filling stage. In both studies, canola was grown in pots under greenhouse conditions with four different humalite rates (0, 400, 800, and 1600 kg ha-1), maintained at 80% and 30% field capacities (well-watered control and drought-stressed condition, respectively). Results indicated that drought stress in both trials significantly reduced canola performance on the tested parameters. Under well-watered conditions, humalite-supplied plants at 400 kg ha-1 demonstrated significantly improved photosynthesis (13%), shoot dry weights (14%) and root dry weights (31%), biomass water-use efficiencies (11%), seed numbers (14%), and oil yields per plant (13%). With drought stress imposed during the vegetative growth stage, 400 kg ha-1 of humalite supply improved photosynthesis (54%), transpiration (82%), and stomatal conductance (194%), while reducing intrinsic water-use efficiency (-17%). With drought stress imposed during flowering and pod filling stage, 400 kg ha-1 of humalite improved seed numbers (29%), seed weights per plant (27%), oil yields per plant (32%), and harvest index (14%), with reduced stearic acid (-5%), free fatty acids (-61%), and glucosinolates (-17%). These research findings highlight the potential of humalite as a soil amendment to improve canola growth and yields, particularly under moisture-deficient conditions, and provide insights into sustainable agricultural practices.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.837

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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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