Context matters
Abiotic stress changes with the crop, its development and the environment. A signal needs context before it can support an interpretation.
An international research framework
The SMARTExperiment
Intelligent sensing.
Plant-centred research.
Sensor-based monitoring of abiotic stress in agricultural systems. Connecting plant signals, environmental context and comparative research across three countries.
Geographic context03 countries
Natural Earth · geographic base ↗
01 The framework
One scientific question. Multiple environments.
How can plant-centred sensing help us understand abiotic stress across contrasting agroclimatic conditions?
From individual measurements to comparable understanding.
The SMART Experiment is a collaborative research framework in biosystems engineering. Its focus is the relationship between plant responses, atmospheric demand and environmental drivers.
Shared measurement strategies connect research contexts in Chile, the Dominican Republic and the United States. The aim is to distinguish transferable patterns from the effects of a particular crop, site or climate.
Explore the methodological sequence02 International collaboration
Different contexts. A shared framework.
Three complementary research contexts, connected by biosystems engineering and common scientific questions.
The Chilean research context connects biosystems engineering, plant water relations and sensor-based monitoring under Mediterranean conditions.
- Plant water status
- Infrared thermometry
- Field-oriented monitoring
International coordinationFernando Fuentes-Peñailillo
Country roles and reference cities follow the project description. They do not identify verified sensor installations or certify current deployment. UTESA has multiple campuses; the related 2025 paper lists Santiago de los Caballeros.
03 Biosystems engineering
A plant signal is only the beginning.
The scientific rationale joins biology, sensing and intelligent interpretation—not isolated measurements.
The plant is central
Canopy temperature contributes information about plant–atmosphere interactions. It must be interpreted alongside environmental and physiological measurements.
Measurements must be comparable
Consistent protocols and instrument checks support meaningful comparison across locations and agroclimatic conditions.
Intelligence requires validation
Sensor data, models and physiological evidence must be evaluated together. A computed index is not automatically a validated decision.
04 Sensing to interpretation
An integrated research workflow.
Explore the role of measurements, context, shared protocols and analysis. This is a methodological sequence, not a live data pipeline.
01 / Plant-centred signals
Start with the plant.
Infrared thermometry provides a non-contact measure of canopy temperature. Interpreting that signal requires the measurement context—not temperature alone.
Canopy temperature is not, on its own, a diagnosis of water stress.
Measurement / requirementUnit / context
- Canopy temperature
- °C
- Measurement time
- Time zone recorded
- Sensor placement
- Documented geometry
Connects toEnvironmental context
Infrared thermometry · wireless sensor networks · agroclimatic monitoring · water-stress indicators · data-driven analysis · comparative protocols.
05 People & collaboration
Research is a shared endeavour.
Scientific coordination and country collaboration, as described in the project framework.
International coordination
Fernando Fuentes-Peñailillo
Universidad de Talca
ChileResearcher profileInstitutional collaboration
Arturo Bisonó
Universidad Tecnológica de Santiago · UTESA
Dominican RepublicResearcher profileScientific collaboration
Emmanuel Torres
North Carolina State University
United StatesResearcher profile06 Open questions
The questions driving the work.
An explicit research agenda. These are questions to investigate, not conclusions already established by the project.
01Thermal responsesHow do crop thermal responses differ across contrasting agroclimatic environments?
Compare signals with site, crop and atmospheric context, rather than assuming a common temperature threshold.
Methodological context02Transferable patternsCan canopy temperature and environmental variables reveal comparable patterns of abiotic stress?
Examine which relationships transfer between locations and which require local calibration.
Methodological context03Scalable sensingHow can low-cost sensing support international experimental research?
Consider instrument performance, deployment constraints and the comparability of the resulting measurements.
Methodological context04Physiological interpretationHow can plant-centred sensing improve the interpretation of water and heat stress?
Relate sensor signals to independent physiological evidence, not only to model output.
Methodological context05Shared protocolsWhat minimum set of variables supports a comparable stress-monitoring protocol?
Define measurements, units, timestamps and experimental metadata before combining observations.
Methodological context06ResilienceHow can better stress monitoring contribute to climate-resilient crop systems?
Evaluate possible applications through research; the website does not claim measured agronomic impacts.
Methodological contextProgramme logic
A framework for continued research.
Work areas, not a dated completion schedule.
- 01
Frame
Shared questions and experimental context
- 02
Develop
Sensing architectures and measurement protocols
- 03
Compare
Compatible datasets and physiological interpretation
- 04
Share
Research outputs, training and collaboration
07 Intended contribution
Engineering with a scientific purpose.
The project’s intended contributions. No quantitative impact or completed deliverable is implied.
Scientific understanding
Comparative knowledge of crop responses to abiotic stress.
Sensing technology
Evaluation of accessible, scalable monitoring architectures.
Research training
Learning across sensing, plant physiology and data analysis.
Climate resilience
A stronger evidence base for studying crop adaptation.
08 Related scientific evidence
Grounded in published research.
Selected work by members of the collaboration. These publications provide related scientific context; they are not presented as verified deliverables of SMART Experiment.
2025
Remote Sensing · 17(4), 708
Remote Sensing and Soil Moisture Sensors for Irrigation Management in Avocado Orchards: A Practical Approach for Water Stress Assessment in Remote Agricultural Areas
Related work on sensing and water-stress assessment in avocado orchards.
DOI / 10.3390/rs170407082024
Sensors · 24(1), 25
A Smart Crop Water Stress Index-Based IoT Solution for Precision Irrigation of Wine Grape
Related work on wireless infrared sensing and CWSI in grapevine. 2024 journal volume; published online 20 December 2023.
DOI / 10.3390/s24010025Continue the conversation
Better questions.
Shared research.
Connect with the scientific coordinator to discuss experimental collaboration, sensing methods and comparative research in biosystems engineering.
ffuentesp@utalca.clDr. Fernando Fuentes-Peñailillo
Universidad de Talca · Chile