A SiPM-Enabled Portable Delayed Fluorescence Photon Counting Device: Climatic Plant Stress Biosensing
Bibliographic record
Abstract
A portable and sensitive time-resolved biosensor for capturing very low intensity light emission is a promising avenue to study plant delayed fluorescence. These weak emissions provide insight on plant health and can be useful in plant science as well as in the development of accurate feedback indicators for plant growth and yield in applications of agricultural crop cultivation. A field-based delayed fluorescence device is also desirable to enable monitoring of plant stress response to climate change. Among basic techniques for the detection of rapidly fluctuating low intensity light is photon counting. Despite its vast utility, photon counting techniques often relying on photomultiplier tube (PMT) technology, having restricted use in agricultural and environment measurements of plant stress outside of the laboratory setting, mainly due to the prohibitive cost of the equipment, high voltage nature, and the complexity of its operation. However, recent development of the new generation solid-state silicon photomultiplier (SiPM) single photon avalanche diode array has enabled the availability of high quantum efficiency, easy-to-operate, compact, photon counting systems which are not constrained to sophisticated laboratories, and are accessible owing to their low-cost. In this contribution, we have conceived, fabricated and validated a novel SiPM-based photon counting device with integrated plug-and-play excitation LED, all housed inside a miniaturized sample chamber to record weak delayed fluorescence lifetime response from plant leaves subjected to varying temperature condition and drought stress. Findings from our device show that delayed fluorescence reports on the inactivation to the plant's photosystem II function in response to unfavorable acute environmental heat and cold shock stress as well as chronic water deprivation. Results from our proof-of-concept miniaturized prototype demonstrate a new, simple and effective photon counting instrument is achieved, one which can be deployed in-field to rapidly and minimally invasively assess plant physiological growth and health based on rapid, ultra-weak delayed fluorescence measurements directly from a plant leaf.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".