Relationship between concentration of isoflavones in soybean grain and potassium fertilization
Bibliographic record
Abstract
Soybean grain contains isoflavones that may prevent various human diseases. Previous studies in Canada found that K fertilization and high grain K concentration can result in increased isoflavones concentration in grain, but effects were inconsistent across sites and soil-test K (STK) levels. The objective of this study was to assess (1) effects of K fertilization on the concentration of isoflavones and K in soybean grain and (2) relationships between soybean grains K concentration, isoflavone concentration, and yield. The study was based on analyses of grain collected from selected treatments and years of six Iowa long-term experiments that investigated effects of K fertilization and placement methods on soybean yield. Four experiments evaluated K placement methods for no-till soybean in rotation with corn (Zea mays, L.) from 1994 to 2001 at Iowa research farms located near Nashua, Kanawha, Lewis, and Sutherland. Two experiments evaluated broadcast K rates from 1976 until 2001at research farms near Ames and Kanawha. Grain samples were collected from two replications of three treatments from 17 site-years. Treatments selected from the placement trials were a control (no K) and 66 kg ha-1 yr-1 broadcast or deep-banded 15-20 cm depth, although at (two sites) Kanawha and Nashua grain also was collected from plots receiving 33 kg K ha-1 yr-1. Treatments selected from the other trials were a control and 67 or 100 kg K ha-1 yr -1. Soil samples were collected before planting soybean from the control plots for STK analyses. Grain was analyzed for concentration of K and 12 isoflavones. Potassium fertilization did not increase (P ≤ 0.05) grain yield, K concentration, or isoflavones concentration at sites where STK was above optimum for soybean. However, it increased grain K concentration and uptake consistently and yield and isoflavones concentration less consistently in other sites with STK Low or Optimum for soybean. On average across responsive sites, K fertilization increased K uptake 20%, yield 11%, K concentration 10%, and total isoflavones 6%. Isoflavones response to K was explained by response of total daidzein and genistein (total glycitein did not respond). Relationships between STK, concentration of K and isoflavones in grain, and grain yield often were positive and significant within sites but seldom across sites. Potassium fertilization increased yield and isoflavones concentrations only when STK was below optimum levels for crops but did not increase yield or isoflavones concentrations in high-testing soils. Relationships within and across locations indicated that the concentration of isoflavones in grain decreased or was unrelated with grain K concentration. Therefore, grain K concentration alone is not a good index of potential effects of K fertilization on isoflavones concentration in soybean grain.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".