Near-infrared reflectance spectroscopy prediction of neutral detergent-soluble carbohydrates in timothy and alfalfa
Bibliographic record
Abstract
Carbohydrates in forage crops can be divided into neutral detergent-insoluble fiber and neutral detergent-soluble carbohydrates (NDSC); the latter includes organic acids (OA), total ethanol:water-soluble carbohydrates (TESC), starch, and neutral detergent-soluble fiber (NDSF). The accurate and efficient estimation of NDSC in forage crops is essential for improving the performance of dairy cattle. In the present study, visible and near-infrared reflectance spectroscopy (NIRS) were applied to evaluate the feasibility of predicting OA, TESC, starch, NDSF, NDSC, and all related constituents used to calculate these 5 carbohydrate fractions in timothy and alfalfa. Forage samples (n = 1,008) of timothy and alfalfa were taken at the first and second harvests at 2 sites in 2007; samples were dried, ground, and then scanned (400 to 2,500 nm) using an NIRSystems 6500 monochromator. A calibration (n = 60) and a validation (n = 15) set of samples were selected for each species and then chemically analyzed. Concentrations of TESC and NDSC in timothy, as well as starch in alfalfa, were successfully predicted, but many other carbohydrate fractions were not predicted accurately when calibrations were performed using single-species sample sets. Both sets of samples were combined to form new calibration (n = 120) and validation (n = 30) sets of alfalfa and timothy samples. Calibration and validation statistics for the combined sets of alfalfa and timothy samples indicated that TESC, starch, and NDSC were predicted successfully, with coefficients of determination of prediction of 0.92, 0.89, and 0.93, and a ratio of prediction to deviation (RPD) of 3.3, 3.1, and 3.6, respectively. The NDSF prediction was classified as moderately successful The NIRS prediction of OA was unsuccessful All related constituents were predicted successfully by NIRS except ethanol-insoluble residual OM, with Our results confirm the feasibility of using NIRS to predict NDSC, its fractions, and other related constituents, except for OA and ethanol-insoluble residual OM, in timothy and alfalfa forage samples.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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 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".