Application of advanced synchrotron radiation-based Fourier transform infrared (SR-FTIR) microspectroscopy to animal nutrition and feed science: a novel approach
Bibliographic record
Abstract
Synchrotron radiation-based Fourier transform IR (SR-FTIR) microspectroscopy has been developed as a rapid, direct, non-destructive and bioanalytical technique. This technique, taking advantage of synchrotron light brightness and a small effective source size, is capable of exploring the molecular chemistry within the microstructures of a biological tissue without the destruction of inherent structures at ultraspatial resolutions within cellular dimensions. This is in contrast to traditional 'wet' chemical methods, which, during processing for analysis, often result in the destruction of the intrinsic structures of feeds. To date there has been very little application of this technique to the study of feed materials in relation to animal nutrient utilisation. The present article reviews four applications of the SR-FTIR bioanalytical technique as a novel approach in animal nutrition and feed science research. Application 1 showed that using the SR-FTIR technique, intensities and the distribution of the biological components (such as lignin, protein, lipid, structural and non-structural carbohydrates and their ratios) in the microstructure of plant tissue within cellular dimensions could be imaged. The implication from this study is that we can chemically define the intrinsic feed structure and compare feed tissues according to spectroscopic characteristics, functional groups, spatial distribution and chemical intensity. Application 2 showed that the ultrastructural-chemical makeup and density of yellow- and brown-seeded Brassica rape could be explored. This structural-chemical information could be used for the prediction of rapeseed quality and nutritive value for man and animals and for rapeseed breeding programmes for selecting superior varieties for special purposes. More research is required to define the extent of differences that exist between the yellow- and brown-seeded Brassica rape. Application 3 showed with the SR-FTIR technique that chemical differences in the ultrastructural matrix of endosperm tissue between Harrington (malting-type) and Valier (feed-type) barley in relation to rumen degradation characteristics could be identified. The results indicated that the greater association of the protein matrix with the starch granules in the endosperm tissue of Valier barley may limit the access of ruminal micro-organisms to the starch granules and thus reduce the rate and extent of rumen degradation relative to that of Harrington barley. It is the first time that the microstructural matrix in the endosperm of barley has been revealed by using the SR-FTIR technique, which makes it possible to link feed intrinsic structures to nutrient utilisation and digestive behaviour in ruminants. Application 4 showed with the SR-FTIR technique that the chemical features of various feed protein (amide I) secondary structures (such as feather, wheat, oats and barley) could be quantified. With a multi-component fitting program (Lorentz function), the results showed feather containing about 88% beta-sheet and 4% alpha-helix, barley containing about 17% beta-sheet and 71% alpha-helix; oats containing about 2% beta-sheet and 92% alpha-helix; and wheat containing about 42% beta-sheet and 50% alpha-helix. The relative percentage of the two may influence protein value. A high percentage of beta-sheet may reduce the access of gastrointestinal digestive enzymes to the protein structure. Further study is required on feed protein secondary structures in relation to enzyme accessibility and digestibility. In conclusion, the SR-FTIR technique can be used for feed science and animal nutrition research. However, the main disadvantage of this technique is the requirement for a special light source; a synchrotron beam.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".