Electrochemical detection of tryptophan in pineapple fruit using a green and chemically synthesized PANI/CuO nanocomposite modified electrode
Why this work is in the frame
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Bibliographic record
Abstract
This study investigated the electrochemical detection of Tryptophan (Trp) in pineapple using a glassy carbon electrode (GCE) modified with nanocomposites of green and chemically synthesized copper oxide-polyaniline (PANI/CuOgrn and PANI/CuOchm). Given the properties of PANI/CuOgrn and PANI/CuOchm that have never been applied in the detection of Trp, it indicates that the development of a highly sensitive and selective sensing platform for Trp-is necessary. Such a platform would take advantage of high electric conductivity, larger surface area, and improved catalytic activity of the nanocomposites. PANI/CuOgrn and PANI/CuOchm nanocomposites were formed by doping polyaniline (PANI) with green and chemically synthesized copper oxide (CuO) nanoparticles. Using Debye-Scherrer the particle sizes of PANI/CuOgrn and PANI/CuOchm were found to be 15 nm and 13 nm, respectively. Through cyclic voltammetry (CV) and square wave voltammetry (SWV), the electrochemical behaviour of CuOch, CuOgrn, PANI/CuOchm, and PANI/CuOgrn electrodes was studied, with the focus on comparing the nanocomposites for tryptophan (Trp) catalysis. GCE-PANI/CuOchm showed a higher current response of 3.2 μA than GCE-PANI/CuOgrn. SWV was used to determine Trp, with the linear range of 5.11 μM to 25.85 μM and limit of detection (LOD) values of 3.947 and 2.037 μM for GCE-PANI/CuOchm, and 3.434 and 2.427 μM for GCE-PANI/CuOgrn. The GCE-PANI/CuOchm electrode achieved a recovered percentage of 96 % to 109 %, with an average RSD value of 18.3 (n=3), while the GCE-PANI/CuOchm electrode achieved a percentage recovery of 85 % to 103 % with an RSD value of 12.7 (n=3). The high recovery percentages for both electrodes confirm their dependability in detecting Trp. The high concentration of Trp-in the fruit and the electrode's sensitivity to identifying Trp-in actual sample analysis may account for the high recovery percentage observed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it