A survey of Canadian dairy nutritionists to assess current trace element formulation practices
Bibliographic record
Abstract
The purpose of this study was to identify current practices and perceptions around trace element feeding for dairy cows through a Canadian dairy nutritionist survey. An online survey with 23 questions was used to collect data from Canadian dairy nutritionists with the help of professional associations and social media. The survey was active from November 2021 to April 2022. The first 7 questions collected descriptive information on respondents, and the subsequent 16 questions focused on trace element feeding. A total of 92 participants from all over Canada filled out the survey, and about 26% of Canadian herds and cows were represented by these respondents. The participants had diverse views on the importance of diet formulations for trace elements to optimize cow health and productivity, with perceptions varying from very important to not important. In comparison, macronutrients and selenium were consistently rated as very important by between 58% and 74% of respondents. Software reference values were used by 54%, 72%, and 73% of participants to estimate trace element concentrations of forages, cereals, and protein sources, respectively, highlighting the importance of regularly updating the feed library of the software. More than 60% of nutritionists participating in this study had intentionally formulated diets above trace element software recommendations, considered mineral interactions occurring in the rumen, and used a trace element source known for its better bioavailability (e.g., organic, chelate) when they formulated diets. Herds with more than 80 cows were more likely to be given trace element supplements known for their greater bioavailability. The most used supplement with enhanced bioavailability was selenium. In addition, different trace element feeding strategies pertaining to different stages of lactation and breeds were reported. This finding can be explained by the absence of clear recommendations on trace element feeding by breed. The participants who adjusted trace element feeding according to the stages of lactation considered the transition period as the most challenging period, and they identified the need for a source of trace element known for its greater bioavailability for this period. Further research should aim to identify environmental risk of trace element overfeeding using the One Health approach. Moreover, strategies to avoid trace element overfeeding should be evaluated.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".