Evaluation of Different Starches as Gelling Agents for Micropropagation of Potato
Bibliographic record
Abstract
Unavailability of clean planting material is a major constraint of potato production in Eritrea. In vitro multiplication is proved to be a reliable solution; however, due to high media cost and initial investment, its use has been limited. The current study was carried out to evaluate the effectiveness of three starches (corn, potato and barley) of both laboratory and commercial grades as agar substitute, for micropropagation of potato. Single nodes of potato were sub-cultured into a fresh modified Murashige and Skoog (MS) medium supplemented with sucrose (3% w/v) and gelled with 50 g/l of six types of starches in addition to 7 g/l of agar as a control. Gelling agents used showed a highly significant difference in all measured parameters. The pH of all starch based media increased by 0.23-1.3 units during the culture time except the control media which decreased by 0.4 units. Similarly EC showed a decreasing trend in all gelling agents. In most of the measured physical parameters such as plant height, root length, fresh weight and dry weight three starch based media namely laboratory grade potato, commercial corn and laboratory corn showed better results compared to the control media. Survival of in vitro plantlets ranged between 85 and 90% after acclimatization. Both laboratory and commercial grade starch based media resulted in cost reduction of 15-22% and 61-66%, respectively. This implies that using both corn and potato starches can be reliable and cost effective gelling agents for micropropagation of potato.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".