AGRICULTURE · FIELD DIAGNOSTICS

See more. Measure more.

Intelligent Material turns a familiar field assay into a quantitative plant-health measurement: collect the sample, capture the target, read the optical signal and compare it with a calibrated baseline.

AGRICULTURE DIAGNOSTICSSample → assay → digital signal → baseline
THE DIFFERENCE

Not just positive or negative.

A conventional field strip is often treated as a visual screen. The IMS approach is designed around a machine-readable signal that can be calibrated against target concentration.

Once an assay is calibrated with a standard curve and reference method, the same optical reader can support repeat measurements: plant-to-plant, block-to-block, before/after treatment, or across a growing season.

A field test becomes data.

Intelligent Material reporters can be coupled to target-specific assay chemistry. The reader measures the optical response rather than asking the user to judge the darkness of a line.

Signal intensity, and where useful temporal response, can be used as quantitative dimensions. That creates a path toward standard curves, thresholds and longitudinal baselines.

The assay chemistry changes by target. The reader architecture can remain substantially the same.

FIELD WORKFLOW

From a leaf to a number.

The exact sample preparation and assay format are target dependent, but the architecture is straightforward.

1
SAMPLE

Collect plant material.

Leaf, stem, root, twig sap or another validated sample is placed into a simple extraction workflow.

2
CAPTURE

Bind the target.

Target-specific capture chemistry retains the pathogen marker or plant-health analyte inside the assay.

3
LABEL

Add Intelligent Material.

Functionalized Intelligent Material binds to the captured target and becomes the optical reporter.

4
READ

Excite with NIR.

A compact reader excites the material and measures a low-background optical response, including time-domain information where useful.

5
QUANTIFY

Compare with baseline.

The calibrated signal is translated into a concentration, relative disease burden, threshold or trend for the validated assay.

QUANTIFICATION

Make disease management measurable.

The important change is not merely faster detection. It is repeatable numerical information that can be compared over time.

ILLUSTRATIVE DISEASE SIGNALBASELINE → TREND → THRESHOLD
ACTION THRESHOLDBASELINEFOLLOW-UP
Illustrative only. The relationship between optical signal and biological concentration must be established for each target through assay development, standard curves and validation against an appropriate reference method.
1 readerA common optical architecture can support multiple target-specific cartridges.
NumericMachine-read results instead of subjective visual interpretation.
BaselineEstablish a local reference and compare later measurements with it.
TrendTrack whether a measured target is rising, falling or remaining stable.
CITRUS GREENING
HLB
quantified.

IMS previously developed the agriculture diagnostic architecture around the goal of a rapid field assay that could correlate optical signal with HLB abundance rather than simply report presence or absence.

A useful model for plant disease diagnostics.

The earlier citrus program was built around conjugated nanocrystal reporters, a compact infrared reader, a standard curve and comparison against laboratory reference methods.

That same architecture is applicable to other plant-health targets when suitable capture reagents, sample preparation and validation are developed.

✓Field-oriented assay format rather than a fixed laboratory workflow.
✓Quantitative standard curve instead of visual line interpretation alone.
✓Repeat measurements that can establish local baselines and trends.
✓Potential multiplexing through engineered optical identities and assay design.
ASSAY TARGETS

One platform. Different plant-health questions.

These are examples of plant pathogens that fit the field-diagnostic model. Each requires its own target-specific assay development and validation; the advantage is that the underlying Intelligent Material reader platform can be reused.

Citrus

Citrus greening · HLB

Quantitative field monitoring of a validated HLB target and comparison with a calibrated baseline.

Oomycete

Phytophthora spp.

Potential rapid screening across relevant plant tissues using target-specific capture chemistry.

Virus

Potato virus Y · PVY

Potential in-field viral detection with a quantitative optical readout rather than a visual line alone.

Bacteria

Ralstonia solanacearum

Potential field assay for bacterial wilt targets using the same reader and a dedicated cartridge.

Fireblight

Erwinia amylovora

Potential orchard screening for Fireblight with repeatable machine-read results.

Target examples describe development opportunities, not claims that every listed assay has already been developed or validated by IMS.
CUSTOM AGRICULTURE ASSAYS

Bring us the plant-health target.

IMS can work with assay-development, agricultural, university and instrument partners to pair target-specific biology with Intelligent Material reporters and quantitative optical readout.

Develop an agriculture assay →