0470 The effect of sorting wheat or barley, based on the predicted CP of individual seeds, on physical characteristics and in vitro dry matter digestibility
Bibliographic record
Abstract
Nutrient values are based on sample averages, ignoring variability among seeds. The objective of this experiment was to determine if fractions obtained by separating kernels based on predicted CP (PCP) have different physical characteristics and DM digestibility (DMD). Second, we determined if grinding method and intensity influence digestibility of each fraction. The BoMill TriQ (TriQ), which uses near infrared transmittance spectroscopy (NIT), was used to separate individual kernels based on PCP. In the first study, the TriQ was used to sort 6 wheat sources into 10 fractions. Sixty kernels from each fraction were randomly chosen for measurement of length, width, height, area, geometric mean diameter, perimeter, sphericity, color, and mass. Data were analyzed using a mixed model with the fixed effect of fraction. Physical characteristics were similar among fractions (P > 0.10), except color, where lower PCP content had greater L* (54.12 vs. 50.95; P < 0.05). In the second study, 2 fractions [high CP (HCP) vs. low CP (LCP)] were produced from 5 sources of wheat and barley. The unsorted grain and each fraction were ground through a hammer mill (0.188 or 0.375 mm screens) or a roller mill to produce coarse and finely ground treatments. The roller mill was adjusted to produce samples with a similar processing index (wt/v) to the hammer mill. In vitro DMD and total gas production (TGP) were determined after a 12-h incubation. Data were analyzed independently by grain source including the effect of fraction, grinder, degree of processing, and interactions. The TGP (ml) and DMD (%) were similar among fractions (P > 0.10). The TGP and DMD of barley ground using a hammer mill was greater (P < 0.10) than when processed using a roller mill (59.4 ± 2.0 and 24.0 ± 2.0; 41.8 ± 1.0 and 24.0 ± 1.0, respectively) and a similar response was observed for wheat (P < 0.10; 63.8 ± 1.4 and 27.8 ± 1.5; 42.3 ± 0.8 and 26.3 ± 0.8, respectively). Increasing the degree of processing increased TGP (P < 0.10; 47.4 ± 2.0 and 35.9 ± 2.0; 48.9 ± 1.5 and 42.7 ± 1.4, respectively) and DMD (P < 0.10; 36.2 ± 1.0 and 29.6 ± 1.0; 36.4 ± 0.8 and 32.2 ± 0.8, respectively) of barley and wheat. Sorting individual seeds for PCP produces fractions with comparable physical characteristics, DMD, and in vitro TGP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".