Bibliographic record
Abstract
Pakistan exports wheat to many countries. Therefore, post-harvest activities for analyzing good quality of wheat in a scientific manner duly approved by ISO are prerequisite. To meet the challenges of competition in the foreign market, particularly from the long established export giants like USA, Canada, Australia and France this has become essential for all the wheat exporters to establish quality control system. In present study stored wheat grains were randomly sampled. Each sample was divided in to three portions for their complete survey of moisture status, fungal flora and aflatoxin contamination. The moisture content of all samples was found less than 12%. All these samples were found positive for fungal contamination when analyzed by plating under unsterilized and sterilized (with 1 % chlorox) conditions on moistened filter paper, Czepaks agar and Aspergillus flavus and A. parasiticus Agar medium (AFPA). A total number of 30 species of fungi viz., A. candidus, A. flavus, A. fumigatus, A. parasiticus, A. niger, A. restrictus, A. sulphurus, A. sydowi, Alternaria alternata, A. brassicae, A. humicola, A. solani, Rhizopus oryzae, R. spp., R. stolonifer, Acremonium spp., Geotrichum candidum, Mucor heimalis, M. spp., Cochliobolus lunatus, Fusarium spp., F. culmorum, Rhizoctonia, Curvularia lunata, Cladosporium herbarum, Penicillium frequentus, Botrytus spp., Nigrospora spp., Humicola, Helminthosporium spp. were isolated. A. flavus and A parasiticus population ranged from 0 - 5.4 CFU/10 seeds and 0 - 5.0 CFU/ 10 seeds respectively. AFPA proved excellent in the isolation of A. flavus and A. parariticus strains. None of the samples was found aflatoxin contaminated when analyzed by ELIZA technique. The efficiency of ELIZA confirmed by the percent recovery of aflatoxin from positive and spiked controls and samples was found hundred percent.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".