ArticleProtoplasma2019
Salt stress in rice: multivariate analysis separates four components of beneficial silicon action.
Article in Protoplasma, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 18 citations in OpenAlex.
- Possible melatonin-induced salt stress tolerance pathway in Phaseolus vulgaris L. using transcriptomic and metabolomic analyses.BMC plant biology · 2024Article
- Exogenous SA Affects Rice Seed Germination under Salt Stress by Regulating NaInternational journal of molecular sciences · 2022Article
- The Ability of Silicon Fertilisation to Alleviate Salinity Stress in Rice is Critically Dependent on Cultivar.Rice (New York, N.Y.) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
How many subcellular targets of the beneficial silicon effect do exist in salt-stressed rice? Here, we investigate the effects of silicon on the different components of salt stress, i.e., osmotic stress, sodium, and chloride toxicity. These components are separated by multivariate analysis of 18 variables measured in rice seedlings (Oryza sativa L.). Multivariate analysis can dissect vectors and extract targets as principal components, given the regressions between all variables are known. Consequently, the exploration of 153 correlations and 306 regression models between all variables is essential, and regression parameters for variables of shoot (silicon, sodium, chloride, carotenoids, chlorophylls a and b, and relative growth rate) and variables of shoot and root (hydrogen peroxide, ascorbate peroxidase (APX), catalase (CAT), fresh weight, dry weight, root-to-shoot ratio) are determined. The regression models [log (y) = y
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.