Response of Four Potato (Solanum Tuberosum L.) Varieties to Four Nano Fertilizers
Bibliographic record
Abstract
Abstract A field experiment was conducted at vegetable field, Department of Plant Production, Technical Agricultural College, Mosul, Iraq during spring season of 2020, to investigate the response of four potato varieties (Arizona, Florice, Laperla, Montreal) to four Nano fertilizers Kind (K, B. Zn, Fe 2 gm. L.−1) with recommend dosage of NPK as well as the recommend dosage of NPK 20:20:20 at 600 Kg.ha−1 as control. The four potato varieties were sown on 26 February in loamy soil at drip irrigation system T-tap. Nano fertilizers were spraying at 2 gm. L.−1 constriction three times in the season. The treatments were arranged in factorial experiment in split plot with in randomized complete block design with three replicates. The results showed Montreal variety give the higher value of average tuber weight (82.022 gm.), total and marketable yield of plant (1048.3, 1007.8 gm.), total and marketable yield of hectare ( 58.241,55.993 ton.ha.−1), dry matter and starch in tuber( 21.877 %, 15.500%). Spraying with four Nano fertilizers kind increase significantly all the parameters of yield and quality compared with control treatment an Zn nano give the higher value of number of tubers per plant (15.177), plant yield (1150.6 gm.), total yield (63.925 ton.ha.−1 ) and marketable yield (61.106 ton.ha.−1) while the higher value of dry matter (22.062 %), starch (15.667 %) an TSS (5.571%) was from K nano.
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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) | 0.001 | 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".