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Record W3024022018 · doi:10.1038/s41598-020-63925-5

Effect of water soluble humic acid applied to potato foliage on plant growth, photosynthesis characteristics and fresh tuber yield under different water deficits

2020· article· en· W3024022018 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth Enhancement Techniques
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Natural Science Foundation of China
KeywordsTranspirationPhotosynthesisStomatal conductanceWater-use efficiencyAgronomyHumic acidBiomass (ecology)Abiotic componentSoil waterShootPhotosynthetic capacityGrowing seasonField capacityBiocharHorticultureWater useChemistryBiologyBotanyIrrigationEcology

Abstract

fetched live from OpenAlex

Abstract Water scarcity is the main limiting factor in agricultural crop production in arid and semi-arid areas in northern China. Humic acid could improve the plant resistance to mitigate the abiotic drought damages, which is a potential strategy to improve the crop production in these regions. An experiment to investigate the effect of water soluble humic acid on plant growth, photosynthesis characteristics and fresh tuber yield of potato under different water deficits was carried out under greenhouse conditions in 2014 and 2015. Treatments included foliar application of fresh water (FW), humic acid diluted with water 500 times (HA) and control (CK), and the water deficits included 45%, 60% and 75% of the field water holding capacity. The HA treatment showed highly significant ( P ≤ 0.01) effect on dry biomass, root/shoot ratio and photosynthesis parameters, improved the dry biomass above ground (DM-AG) by 14.12–36.63%, 11.62–36.26% and 7.85–20.85% over the whole growing season at water deficits of 45%, 60% and 75% of the field water holding capacity respectively in 2014 and 2015; decreased the root/shoot (R/S) ratio in the early growing season and increased the R/S ratio in the later growing season; showed an improved effect on leaf soil plant analysis development (SPAD), photosynthesis rate (Pn) and stomatal conductance (Gs) and decreased transpiration rate (Tr) and intercellular CO 2 concentration (Ci) compared with the control. HA usually showed a better effect on photosynthesis parameters in 60% of the field water holding capacity than 45% and 75% except on Pn. Compared with control, HA increased fresh tuber yield by 34.47–63.48%, 35.95–37.28% and 23.37–27.15% at 45%, 60% and 75% of the field water holding capacity respectively. HA enhanced the potato plant growth, and improved photosynthesis parameters and fresh tuber yield under different water deficits under green house conditions, and represents an opportunity to improve crop production and sustainability of agriculture in arid and semiarid regions.

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.

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)0.001
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 score0.002
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.201
Teacher spread0.184 · 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