Lazar 1997 model
The Lazár 1997 model is a mathematical description of chlorophyll a fluorescence induction in plants, built to capture how herbicides alter the fluorescence transient. It represents photosystem II as a network of fifteen redox and protonation states whose interconversions reproduce the characteristic rise of the fluorescence signal.
By blocking electron transport at specific steps, PSII-targeting herbicides reshape this transient, and the model allows their effect on the fluorescence induction curve to be studied in silico.
Analyses
Simulation
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Model Details
Review and edit model structure, biological variables, and kinetic parameters.
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Generated LaTeX Code
\begin{align*}
\frac{d y1}{dt} &= k10 \cdot y3 + y1 \cdot (- k1 - k17) + k16 \cdot y11 \cdot y9 \\
\frac{d y2}{dt} &= k1 \cdot y1 + k11 \cdot y4 + k7 \cdot y3 - y2 \cdot (k23 + k6) + k22 \cdot y12 \cdot y9 \\
\frac{d y3}{dt} &= k6 \cdot y2 - y3 \cdot (k10 + k2 + k7) \\
\frac{d y4}{dt} &= k2 \cdot y3 + k9 \cdot y5 - y4 \cdot (k11 + k8) \\
\frac{d y5}{dt} &= k13 \cdot y7 + k8 \cdot y4 - y5 \cdot (k12 + k3 + k9) \\
\frac{d y6}{dt} &= k19 \cdot y8 + k3 \cdot y5 - k18 \cdot y6 \\
\frac{d y7}{dt} &= k12 \cdot y5 - y7 \cdot (k13 + k14 + k4) + k15 \cdot y10 \cdot y11 \\
\frac{d y8}{dt} &= k18 \cdot y6 + k4 \cdot y7 - y8 \cdot (k19 + k20) + k21 \cdot y10 \cdot y12 \\
\frac{d y9}{dt} &= k17 \cdot y1 + k23 \cdot y2 + k24 \cdot y10 - y9 \cdot (k25 + k16 \cdot y11 + k22 \cdot y12) \\
\frac{d y10}{dt} &= k14 \cdot y7 + k20 \cdot y8 + k25 \cdot y9 - y10 \cdot (k24 + k15 \cdot y11 + k21 \cdot y12) \\
\frac{d y11}{dt} &= k14 \cdot y7 + k17 \cdot y1 - y11 \cdot (k15 \cdot y10 + k16 \cdot y9) \\
\frac{d y12}{dt} &= k20 \cdot y8 + k23 \cdot y2 - y12 \cdot (k21 \cdot y10 + k22 \cdot y9) \\
\frac{d y13}{dt} &= - k6n \cdot y13 \\
\frac{d y14}{dt} &= k6n \cdot y13 \\
\frac{d y15}{dt} &= 0
\end{align*}Fit to data
Fit settings
| Setting | Value |
|---|---|
| Fit backend | |
| Function evaluations per progress update | |
| Maximum total function evaluations | |
| Stop once residual norm reaches |
Curriculum learning (advanced)
Every bar shares one fixed step budget. Drag a divider to move a cutoff, drag a bar's top edge (or focus it and use the arrow keys) to change its share — the final stage isn't draggable, it always gets whatever's left. Double-click a bar or use its + to split it, use a divider's × (or Delete/Backspace while it's focused) to remove it.
| Stage | Data cutoff | Iteration budget |
|---|---|---|
| 1 (final) | full data | 1000 iterations (runs to convergence within this) |
Data
Plot options
| Parameter | Fit | Log-space | Initial guess / fixed value | Fitted value |
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| k1 | — | |||
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| k6 | — | |||
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| k10 | — | |||
| k11 | — | |||
| k12 | — | |||
| k13 | — | |||
| k14 | — | |||
| k15 | — | |||
| k16 | — | |||
| k17 | — | |||
| k18 | — | |||
| k19 | — | |||
| k20 | — | |||
| k21 | — | |||
| k22 | — | |||
| k23 | — | |||
| k24 | — | |||
| k25 | — | |||
| k6n | — | |||
| p | — |