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Record W2342835087 · doi:10.14288/1.0086125

Effects of CO₂ enrichment and potassium supply on growth and inorganic nutrition of chrysanthemum (Dendranthema grandiflora Tzvelev)

2008· article· en· W2342835087 on OpenAlexaff
Juan C. Hoyos

Bibliographic record

VenuecIRcle (University of British Columbia) · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPotassiumHorticultureChemistryCut flowersBiologyBotany

Abstract

fetched live from OpenAlex

Beyond the effects of photosynthesis, plant responses to CO₂ enrichment are modified by secondary environmental factors and internal processes, including mineral relations and carbon partitioning. Leaf abnormalities sometimes develop under long-term CO₂ enrichment, and previous research has correlated them with altered nutrient requirements and distribution. To explore the roles of CO₂ enrichment on the development of leaf abnormalities, three experiments were performed on chrysanthemum (Dendranthema grandiflora Tzvelev) plants cv 'Envy'. CO₂ enrichment and K+ supply effects on growth, carbon partitioning, and the inorganic nutrient contents in plants were studied. CO₂ enrichment increased plant dry mass, mainly due to increased leaf dry mass. In CO₂ enriched plants, increased leaf area of branch leaves resulted in an increase in total leaf area. There was no significant further increase above 1200A L L⁻¹ CO₂. Leaf starch concentration was increased by CO₂ enrichment, although there was no evidence of excessive starch accumulation. CO₂ enrichment did not have a significant effect on the leaf concentrations of sucrose, glucose, fructose or protein. Total leaf content of inorganic nutrients was not changed by CO₂ enrichment. CO₂ enrichment decreased the starch-corrected concentrations of some nutrients in leaves borne on main stems. That change was significant for K, Ca and Mn, and also for the ratio of Mn to Zn. In leaves borne on the lower part of branches, CO₂ enrichment induced a slight reduction in N concentration. Interactions between CO₂ enrichment and K supply on the nutrient relations of plants were seldom detected. Increasing K limited leaf dry mass accumulation and leaf area production, reduced nutrient concentrations, and induced leaf chlorosis. The interpretation of K effects was restricted by the possible detrimental effect of acetic acid. This negative effect was probably enhanced by daily drifts in the pH of nutrient solutions. Both acetic acid additions and the size of pH drifts increased with increasing K supply. A possible beneficial effect of Na, when K supply was low, further confounded the interpretation of K supply effects. Interveinal chlorosis appeared on both the upper most leaves of main stems and the lower leaves borne on branches, after one week of CO₂ enrichment. It was more pronounced in the latter. Leaf chlorosis decreased toward the bottom of main stems, and toward the top of branches. Increasing K supply enhanced chlorosis in both CO₂ enriched and unenriched plants. No relationship was detected between leaf chlorosis and leaf starch concentration or leaf temperature. Reduced leaf concentration of Mn coupled with alterations in the Mn to Zn ratio, and the appearance and distribution of symptoms, suggest that Mn deficiency played a role in the induction of chlorosis by CO₂ enrichment. However, other nutrients, such as K or N, or non-nutritional factors could be involved in the disorder. These studies confirmed that CO₂ enrichment reduces leaf nutrient concentration and makes plants more susceptible to nutrient stresses. The importance of inorganic nutrition in the regulation of plant responses to CO₂ enrichment was also verified.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.914
Threshold uncertainty score0.995

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 head0.137
Teacher spread0.133 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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