Evaluation of X‐Ray Fluorescence Spectroscopy as a Tool for Nutrient Analysis of Pea Seeds
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT This research was conducted to evaluate the utility and reliability of X‐ray fluorescence (XRF) spectroscopy to analyze macro‐ (K and Ca) and micronutrients (Mn, Fe, Cu, Zn, and Se) in pea ( Pisum sativum L.) seeds. The pea seed samples were ground into flour and pelleted to collect the XRF spectra. Seventy‐three pea seed samples were selected to cover the expected concentration ranges for each element to develop calibration curves by correlating the XRF results with atomic absorption spectroscopy (AAS). The XRF results were validated by a systematic comparison of data obtained from AAS on a set of 80 additional and independent pea seed samples. Element concentrations were also predicted using the fundamental parameter approach collectively for 153 samples. For all the calibration curves, the R 2 value was >0.8, except for K (0.54). For Mn, Fe, Cu, Zn, and Se, the XRF predictions were similar to AAS measurements at a 95% confidence level. Similar results were obtained with the fundamental parameter approach except for Fe for which significant bias of ∼6 mg kg −1 was calculated. Except for K, R value for all the validation curves was >0.85. Thus, the results obtained using XRF and the fundamental parameter approach were statistically not different from the AAS method. This study demonstrated that the XRF technique is a fast and reliable, nondestructive, and noninvasive analytical tool for mineral analysis, particularly for transition metals, does not produce waste, and requires no chemical reagents.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it