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Record W4403130228 · doi:10.3390/horticulturae10101063

Impact of Nitrogen Limitation, Irrigation Levels, and Nitrogen-Rich Biostimulant Application on Agronomical and Chemical Traits of Hydroponically Grown Cichorium spinosum L.

2024· article· en· W4403130228 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

VenueHorticulturae · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth Enhancement Techniques
Canadian institutionsMcGill University
FundersHorizon 2020 Framework ProgrammeEuropean Commission
KeywordsCichoriumNitrogenIrrigationStratum spinosumAgronomyChemistryBiologyHorticultureBotany

Abstract

fetched live from OpenAlex

This study investigates the effects of nitrogen fertilization, irrigation, and biostimulant application on the growth and nutrient composition of Cichorium spinosum L. The experimental design included two nitrogen rates (NR100 and NR30, 100% and 30% of plant requirements), two irrigation levels (WA100 and WA50, 100% and 50% of water availability,), and foliar application of a nitrogen-rich biostimulant (BS and NoBS, biostimulated or not biostimulated). In comparison to NR100, NR30 reduced agronomical parameters leaf number, leaf area, leaf fresh, and dry weight by 13.53%, 24.93%, 20.76%, and 15.00%, respectively, whereas dry matter content was increased by 7.64%. WA50 also resulted in reduction in the agronomical characteristics by 8.62%, 7.19%, 5.53%, and 5.26, respectively, whereas the dry matter content was not affected. BS positively affected the agronomical characteristics by 7.49%, 8.01%, 7.18%, and 5.56, respectively, whereas the dry matter content was not affected. The effects of nitrogen rates and water availability suggest the more pronounced impact of nitrogen compared to water stress on the agronomical characteristics. Biostimulant application partially mitigated the effects of NR30 but was ineffective against WA50. The nutrient content of the leaves was also affected. NR30 reduced leaf nitrate, calcium, and zinc content, but increased iron, manganese, and copper concentrations. WA50 altered magnesium and zinc levels: it increased the former and decreased the latter. The interaction between nitrogen and water stress notably affected the plants’ calcium content, which was higher under the NR100 x WA50 treatment. These findings provide significant insights into the perlite-based cultivation of C. spinosum L., and its resilience against drought stress. Moreover, the beneficial effects of sufficient nitrogen rates on leaf fresh weight of Cichorium spinosum L. outline the importance for improving nutrient solution management schemes. Biostimulant application demonstrated promising results and could, after further research, become a viable solution for maintaining optimal yields under nitrogen stress.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.271

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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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