EVALUATION OF MAIZE SOURCE MATERIAL BY QUALITATIVE GRAIN INDICATORS
Bibliographic record
Abstract
The basis of a complex and long process of creating new maize hybrids is the selection of parent components that can serve as sources of improved biochemical and economically valuable traits. Thus, depending on the peculiarities of the directions of maize grain processing, the production requires hybrids with a high starch content, and in the starch itself – amylose or amylopectin. When used for fodder purposes, high protein content is a must. This distribution of hybrids by areas of use will increase the profitability of production and reduce the cost of final products. The article presents the evaluation results of self-pollinating maize lines collection, which has 38 samples. The collection includes selection samples of the National University of Life and Environmental Sciences of Ukraine, Institute of Plant Breeding. V.Ya. Yuriev NAAS and lines of Canadian and Russian origin which are obtained from the National Center for Plant Genetic Resources of Ukraine. Field research was conducted according to generally accepted methods in the research fields of the Department of genetics, breeding and seed production. prof. M.O. Zelensky National University of Life and Environmental Sciences of Ukraine of the production unit "Agronomic Research Station", which is located in Vasylkiv district of Kyiv region laboratory. The soil of the experimental area is typical, low-humus, coarse-grained-medium-loam chernozem in terms of granulometric composition. Weather conditions were favorable for maize growing. Determination of quality indicators of maize grain was carried out on the «Infratec 1241 Grain Analyzer». The samples were divided into groups according to the content of quality indicators in the grain. In terms of protein content, two groups with high and medium content were formed, and the total variation of the indicator ranged from 10.0 to 13.8%. According to the starch content, the samples were also divided into two groups with very high and high content, and the percentage varied in the range of 66.5-71.8%. The range of oil content in the grain was in the range of 3.0-5.9% and, accordingly, three groups with high, medium and low content were formed. Selected inbred lines according to a set of indicators that serve as analyzers in the scheme of tester crosses to determine the degree of inheritance of specific biochemical traits. Key words: corn, inbred line, hybrid, biochemical parameters, amylose, amylopectin, tester, combination ability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".