Development of culture medium for high density micropropagation of potato plants in vitro
Bibliographic record
Abstract
All commercial seed potatoes start off as small plantlets grown in tissue culture, and in vitro clonal micropropagation is the only way to ensure a constant supply of certified virus-free plants. Selecting the correct culture medium is one of the most important steps in developing a useful protocol for successful growth and propagation of plant species in vitro. In Alberta, all commercial tissue culture labs rely on the classic Murashige and Skoog (MS) medium to clonally propagate potato plants in vitro. Although MS composition is widely used as a standard growth medium, the nutrients it supplies may not be optimal for plant growth on an industrial scale. To meet the growers’ demand for seed potatoes, commercial producers have to grow plants at 4–10 times higher densities than those in research laboratories. The resulting plants are often of poor quality and exhibit reduced survival rate after being transferred to the greenhouse, thereby causing serious economic losses for the industry. Hence, the composition of MS medium likely requires major modifications to improve its efficiency for commercial use, particularly when potato plants are grown in culture vessels at high density and suboptimal culture conditions. The aim of this study was to evaluate the effects of additional MS nutrients on shoot quality and to determine the most critical culture medium components for improved plant growth response in potato. A factorial approach was used to test combinations of five nutrient factors: 1) NH4NO3, 2) KNO3, 3) mesos (CaCl2, KH2PO4 and MgSO4), 4) micronutrients (B, Cu, Co, I, Mn, Mo, Zn, Fe), and 5) source of carbohydrates. Each factor varied over a range of concentrations, added to MS medium. In total, 25 medium compositions were tested. The effects of these treatments on plant quality, such as shoot length, leaf size and color, were determined. An increase of mesos and micronutrients to concentrations four times higher than in the original MS medium was found to be the most significant factor associated with plant quality, multiplication and shoot length in all plants. This optimized growth medium can be used to produce higher quality potato plants in vitro. *Indicates presenter
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".