Distribution of Elements in Potato (Solanum tuberosum L.) Tubers and Their Relationship to After-cooking Darkening
Bibliographic record
Abstract
The hypothesis of this study was that the concentration and the spatial distribution of elements in potato tubers could be used to predict after-cooking darkening (ACD), one of the most important undesirable potato traits with respect to tuber quality. The objective was to identify the elements (plant nutrients) whose content may relate to the severity of potato ACD. This study used induced coupled argon plasma spectrometry and a variable pressure scanning electron microscope equipped with energy-dispersive x-ray spectrometry to measure these elements. A total of 14 elements were studied [phosphorus (P), calcium, magnesium (Mg), potassium (K), sulfur (S), iron (Fe), copper, sodium (Na), zinc (Zn), boron (B), manganese, aluminum (Al), silicon (Si), chlorine (Cl)] in two potato cultivars with various fertilization regimes. Some elements such as P, Mg and K, S, Zn, and Cl had higher concentrations at the center of the tuber compared with the distal ends, whereas others such as calcium (Ca) showed a decrease from stem end to bud end of the tubers. The concentrations of Na, Fe, Al, and Si were greater near the distal ends of the tuber and decreased toward the center of the tuber. Copper (Cu) and B showed no distribution pattern from the stem to the bud end. When segment element concentrations were compared with their degree of ACD, the elements most strongly correlated with ACD severity were P ( r = 0.590), S ( r = 0.530), Ca ( r = –0.388), Cu ( r = 0.382), and Mg ( r = 0.338). Predictor models for the severity of ACD had R 2 values in the range of 0.398 to 0.480 depending on the data sets used. Phosphorus, Ca, and in one case Cu, were selected as the best element subset to predict the degree of ACD severity. This study elucidates details of tuber element composition and distribution and also provides a useful method to predict the severity of ACD or other tuber qualities. Such predictive models have a strong potential to help the potato processing industry in predicting the occurrence of ACD and in developing agronomic treatments to minimize ACD.
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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 | 0.000 | 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 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".