Crop disease forecasting models, spore traps, pheromone and smart pest traps and field diagnostics — spray when risk is real instead of calendar-based fungicide and insecticide programmes

Replaces (partial): calendar-based spray programmes · Scope: potato, grape, apple, cereals, vegetables, orchards · Evidence: high (decision support), medium (automated spore traps)

The chemical problem#

• Many farms spray protectant fungicides every 7–10 days “just in case”, and insecticides on fixed dates, regardless of real infection or pest pressure.
• With protectants like mancozeb and chlorothalonil leaving the EU market, every remaining spray has to count.
• EU law already requires integrated pest management (Directive 2009/128/EC): monitoring and thresholds before treatment.

Product overview#

1. Disease forecasting models — weather-driven infection-risk models (late blight, apple scab, grapevine downy/powdery mildew, septoria, fusarium) delivered as apps or advisory services.
2. Spore traps — air samplers that catch fungal spores; with qPCR or image analysis they detect inoculum before symptoms appear.
3. Pheromone and smart traps — lure traps for moths and fruit flies, increasingly with cameras and automatic counting (links to A37).
4. Field and lab diagnostics — molecular plant-pathogen tests (PCR, LAMP, ELISA) for seed, planting material and outbreaks.
5. Remote sensing — satellite and drone imagery to target scouting.

Active ingredient / Composition#

• Information: weather data, models, trap counts, pathogen DNA tests. Inputs are sensors, traps, lures, reagents and software.

Key facts#

Advantages#

• Fewer sprays for the same protection → lower cost, fewer residues.
• Better timing makes each spray (biological or chemical) more effective.
• Monitoring data documents IPM compliance for buyers and regulators.
• Makes biological products viable: they work best when applied at the right moment.

Mode of action#

• Models calculate infection periods from leaf wetness, temperature and humidity; sprays are applied only before or just after a risk period.
• Spore traps measure the presence of inoculum; no inoculum, no spray.
• Trap counts compared with thresholds trigger treatment only when needed.

Application#

Limitations#

• Models must be validated for local climate and varieties.
• Requires weather stations, trap maintenance and farmer trust.
• Advisory services in many regions are weak; smallholders need cooperative or input-dealer support.
• Some pathogens and pests lack validated models.

Evidence of displacement — D2: measurable displacement (minority share)#

Assessment (hand-reviewed): Adjacent: biocontrol-based IPM on >90% of Dutch greenhouse tomato, cucumber and pepper; threshold-based programmes cut insecticide applications by 44% vs calendar spraying (multi-country meta-analysis, peer-reviewed). Automated-trap adoption: market research only.

Figures found (verified as quoted, but the assessment above explains why they do not count as displacement evidence for this substitution):

• displacement — In New Zealand autumn-sown wheat trials, IPM-managed crops achieved a 50% reduction in insecticide applications compared to conventional crops with no significant yield or disease differences. (New Zealand, 2008-2010; peer-reviewed: exa.ai)
• displacement — In Western Europe, almost 50% of the apple and pear acreage is managed under an Integrated Fruit Production (IFP) program. (Western Europe, 2015; peer-reviewed: mdpi.com)
• displacement — The adoption of Integrated Fruit Production (IFP) in larger areas has led to a 30% decrease in conventional pesticide application. (Western Europe, 1991-2015; peer-reviewed: mdpi.com)
• displacement — In the Netherlands, IPM based on biological control is used on over 90% of greenhouse tomato, cucumber, and sweet pepper production. (The Netherlands, 2011; peer-reviewed: pmc.ncbi.nlm.nih.gov)

Industry pioneers — companies that commercialised this substitution#

Suppliers — real products and services (from the vendor index)#

Active vendors whose own card shows pest-monitoring traps, disease/pest early-warning services or plant-pathogen diagnostics.

Government funding signals#

Scanned 2026-10-01 (OpenAIRE + NSF); candidates reviewed by hand.

Signal: Weak. “Spore trap” returned mostly unrelated awards; relevant hits were Czech MSM LD15046 (detection and early warning for Gibberella circinata) and LD12031 (Dothistroma distribution). The late-blight scan also surfaced Czech MZE QJ1210305 (integrated late-blight management with prediction). Decision support is funded mostly through national extension services.

Scientific evidence#

• Gent DH, Mahaffee WF, McRoberts N, Pfender WF (2013). The use and role of predictive systems in disease management. Annual Review of Phytopathology 51: 267–289.
• West JS, Kimber RBE (2015). Innovations in air sampling to detect plant pathogens. Annals of Applied Biology 166: 4–17.
• Pertot I, Caffi T, Rossi V, et al. (2017). A critical review of plant protection tools for reducing pesticide use on grapevine and new perspectives for the implementation of IPM in viticulture. Crop Protection 97: 70–84.

Bioeconomy value#

Information is the input that makes every biological product work better. Traps, lures and diagnostics are sold through the same distributors as biopesticides, so this collection adds a monitoring line to the crop-protection catalogue.

Cross-links: A37 pheromones; A16 late blight; A19 apple scab; SG01 resistant varieties; DX01 livestock diagnostics.