PSVIII-19 Predict Indigestible Fiber Fraction of Barley Plant Silage by Using non-Destructive Mid-IR vs Near-IR Spectroscopic Techniques
Bibliographic record
Abstract
Abstract The objective of this study was to reveal the potential of using Fourier transform mid-infrared (FTIR) and near infrared (NIR) spectroscopy as tools for the determination of indigestible neutral (NDF) fraction (iNDF) of barley plant silage. A total of 48 barley plant silage samples collected from different farms in Western Canada provinces were analyzed for iNDF. Reference values were matched with NIR and FTIR spectra. Spectral data processing (pretreatments) included first derivative (FD), standard normal variate (SNV), multiplicative scattering correction (MSC), second derivative (SD) and orthogonal signal correction (OSC). Prediction equations were obtained from each model using an external validation set. The determination coefficient of external validation (R2P) of iNDF was 0.62 for FTIR, while 0.41 for NIR and the corresponding ratio performance deviation (RPD) were 1.69 and 1.38 in FTIR and NIR, respectively. Results from this research showed the high potential of applying infrared molecular spectroscopy for the examination of forage plant fiber digestibility. More studies are needed to improve the accuracy and performance of FTIR and NIR spectroscopies in predicting the iNDF of barley plant silage samples.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".