Assessment of the influence of soil inoculation on changes in the adaptability of maize hybrids
Bibliographic record
Abstract
Abstract The aim of this paper is to present the results of the field trial carried out to collect and assess data on the interaction of maize ( Zea mays L) genotypes and beneficial microorganisms. The small plot field trial consisting of untreated control plots and plots treated with biostimulants was conducted in three consecutive years (2019, 2020 and 2021). Yield is a particularly important trait from the aspect of maize breeding as well as maize production; therefore, the present study focused more closely on how it was influenced by the biostimulant treatments. The level of grain yield, grain moisture content at harvest and grain dry-matter content were observed and recorded as the components of yield. The nutritional value of kernels was also tested, and protein, oil and starch contents were analysed as the most important components of this trait. The results reflected that the treatment with biostimulants constituted from beneficial microorganisms can be listed among the factors influencing the grain yield, in addition to the seasonal effect, the genotype and the nutrient supply of the soil. The treatment with biostimulants, even on its own among the factors, had an impact on the quantity and components of yield, and on the characteristics determining the kernel nutritional value. The interaction between the genotypes and the interacting microorganisms is of specific importance. The most spectacular result was attained with the application of one of the biostimulants leading to elevated grain yield in 75% of the maize genotypes in the study, along with a kernel nutritive value equal to the control group over all of the three years of the trial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".