Analysis of Ergot (Claviceps purpurea) Alkaloids in Grain and Effect on Cow-Calf Performance
Bibliographic record
Abstract
Ergot contamination of cereal crops and grasses has been of increasing concern for both grain and animal producers.The overall objective was to examine ergot contamination from an analytical, regulatory and biological perspective.The objectives of the first study were to determine the correlation between number of ergot sclerotia and weight compared to the total ergot alkaloid concentration, to evaluate the effect of particle size (PS) on ergot alkaloid analysis and to determine the impact of sample volume on analytical variability.This study demonstrated that correlations existed between both ergot sclerotia count and weight compared to the total alkaloid concentration (P's < 0.001) but did not exist for either, at ergot alkaloid concentrations below 350 g/kg (P = 0.956 and 0.769 respectively).This study also determined that a finer grind (PS = 192 m) produced a lower variability (P = 0.041) than a coarser grind (PS = 516 m).The coefficient of variation (CV) was also numerically reduced as sample volume increased (97% CV for 75 mL to 64% CV for 1000 mL; mean of all concentrations) but increased as sample concentration declined (17% CV for 81678 g/kg to 284% for 35 g/kg; mean of all sample volumes).An analytical approach with fine grinding of a minimum sample volume of 1000 mL (if not the entire sample available) should be used to assess ergot contamination to reduce variability.The objective of the second study was to determine if the percentages of individual ergot alkaloids were similar across different cereal grains collected from across Western Canada over different years.Ergocristine was the predominant alkaloid accounting for half of the total alkaloids in all grain types.Ergocornine (6% 1; P = 0.201), ergocristine (48% 2; P = 0.939), ergocryptine (17% 2; P = 0.302) and ergosine (5% 0.5; P = 0.239) were of similar proportions in barley (n = 39), rye (n = 7), triticale (n = 9) and wheat (n = 94).However, small differences were found between grain types for both ergometrine and ergotamine (P = 0.027 and 0.011 respectively).There were no yearly alkaloid proportion differences between the six alkaloids in barley and wheat 2015/2016 samples (P = 0.969, 0.680, 0.572, 0.080, 0.119 and 0.189 for ergocornine, ergocristine, ergocryptine, ergometrine, ergosine and ergotamine respectively).However, ergocornine was higher in wheat (P = 0.017) and ergometrine was higher in barley (P = committee members Dr.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".