NIEZBĘDNIK · MY FIELD · A FREE TOOL FOR THE FARMER
The agronomic decision engine institutions pay for. Free for the farmer.
Behind a simple screen — "when to spray, when to enter the field" — runs an engine built on the same science institutions pay for: 130+ peer-reviewed agronomic models, dozens of satellite streams fused into one view, decisions computed for your specific parcel, hourly, across the whole season. It is not a skin over a weather forecast. It is a system.
130+peer-reviewed agronomic models — disease, pest and growth — each grounded in published epidemiology, not a lookup table
50+crops — cereals, oilseed rape, root crops, legumes, orchards, vegetables — each with its own thresholds
dozensof satellite streams fused into a single picture of your field
hourlyspray windows and alerts computed per parcel, not for a whole region
01 · WHAT THE SYSTEM DECIDES FOR YOU
Most "farming apps" show you weather and NDVI. Niezbędnik makes decisions — 60+ distinct ones, each for a specific parcel and its growth stage:
Spray windows — hourlyWind, humidity, vapour-pressure deficit, dew, drift risk — it points to a 2–4 hour window, not just "today is fine".
Disease riskSeptoria, fusarium, late blight, mildew, phoma — infection models computed from leaf-wetness hours and BBCH stage.
Pest flightsFlight phenology on temperature sums — when aphids, pollen beetle or corn borer will actually appear.
Field trafficabilityWhether the soil will carry a machine today — and how many days until it dries, if no rain falls.
Water balance and irrigationAn FAO-56 root-zone model — how much water is really left, and when to irrigate.
Frost and heat stressDamage threshold tied to crop stage, plus cold-air drainage from local terrain.
Drought — composite indicesSPI, NDVI anomalies, soil moisture and gravimetry — an alarm only when several sources agree.
Nitrogen and soilNitrogen nutrition index, Nmin, liming, organic carbon — a rate based on data, not habit.
Crop rotationCarry-over disease risk from the previous crop, nitrogen credit after legumes, active-substance rotation.
Yield and qualityYield forecast (growth model + NDVI assimilation), falling number, protein, lodging risk from radar.
Harvest windowGrain moisture from a drying curve, plus a 5-day forecast of dry days.
Compliance and insurancePre-harvest intervals, treatment records, flags relevant to claims — ready for inspection.
Many of these modules are sold as separate, paid products elsewhere. Here there are 60+ of them — in one free tool.
PER PARCEL · HOURLY · NO CHARGE TO THE FARMER
02 · CROPS — EACH WITH ITS OWN THRESHOLDS
One crop is not one model. Wheat, oilseed rape, potato, pea, apple, onion — each has its own phenology, its own diseases, its own pests and its own thresholds. The system does not lay one lookup table over everything: for each crop group it computes the risks that genuinely apply to it, at the BBCH stage matched to its variety and sowing date.
CEREALS
Wheat · barley · rye · triticale · oats
Septoria, fusarium head blight (DON risk), mildew, rusts, tan spot — infection windows tied to heading stage and leaf-wetness hours. Nitrogen and growth-regulator thresholds per stage.
OILSEED RAPE
Winter and spring rape
Phoma stem canker, sclerotinia stem rot, dark leaf spot; pollen beetle and weevil flights computed on temperature sums. The flowering window drives protection timing.
ROOT CROPS
Potato · sugar beet
Late blight (BLITECAST / Hutton model), early blight, Colorado beetle; cercospora leaf spot and ramularia in beet. Irrigation thresholds during tuber and root set.
LEGUMES
Pea · field bean · soybean · lupin
Ascochyta, downy mildew, aphids; plus a nitrogen credit for the next crop in the rotation. High drought sensitivity during flowering.
ORCHARDS
Apple · pear · cherry
Apple scab (Mills model, wetness hours), fire blight, codling moth on temperature sums. Blossom frost risk computed per phenological stage.
VEGETABLES
Onion · carrot · brassicas
Onion downy mildew, carrot alternaria, root flies; precise irrigation thresholds and narrow spray windows with drift control.
The same weather event means something different for each crop — and the system tells them apart. Rain at wheat heading is a fusarium risk; the same rain at rape flowering is a sclerotinia risk; in the orchard it is a scab window. Computed for your parcel and its crop — not for a region, not for a municipality.
03 · SCIENCE UNDERNEATH — NOT GUESSWORK
The difference between an "app" and a system is measurable here. Each recommendation rests on a peer-reviewed publication and is calibrated to the Polish agricultural climate. These are not thresholds copied from a leaflet — they are mechanistic models, the same families science uses:
DISEASE EPIDEMIOLOGY
Infection models, not lookup tables
Septoria, fusarium head blight, late blight, sclerotinia, phoma — each with its own infection window, latency period and wetness kinetics. Built on established phytopathology literature.
PLANT GROWTH
Growth model + data assimilation
A physical development and biomass model corrected on the fly by satellite NDVI — a filter joins physics with observation, so the growth stage does not drift away from reality.
WATER BALANCE
Root zone, day by day
A full soil-water model with effective rainfall, crop- and stage-dependent evaporation, and capillary rise from groundwater — across eight soil-texture classes.
The model families this builds on (publicly citable method families, without disclosing our implementation):
Septoria — Lovell / ShawFusarium DON — Birr 2020Late blight — BLITECAST / Hutton
Growth — WOFOST + EnKFWater — FAO-56Soil carbon — RothCTemperature sums — GDD phenology
04 · DATA FROM ACROSS THE SKY — FUSED INTO ONE FIELD
A single sensor lies: cloud blocks the optics, radar sees no colour, microwaves see no leaf. So we do not look with one eye — we fuse dozens of streams and weight them by uncertainty, so each covers the weakness of the others:
OPTICAL + RADAR + THERMAL
The field seen through and through
Optical (condition, vegetation indices), SAR radar (lodging, mowing, moisture — through cloud), thermal (water stress before the eye can see it). Together — a picture no single satellite gives.
WATER — FROM LEAF TO AQUIFER
The whole water column
Root-zone moisture from microwaves, surface water from the balance, deep water from gravimetry. We combine it with a local model — from dew on the leaf to the reserve underground.
Every stream is fitted to your parcel — the weather point nearest its centre, terrain from a local DEM, the boundary from the land register. Not a "region", not a "municipality" — a specific field.
05 · WHY IT CAN BE FREE
Commercial agricultural intelligence of this class typically costs tens of euros per hectare per year — and it tends to reach large farms and corporations. We give the core to the farmer free of charge, and that is not charity but architecture:
Real fields test our models better than any laboratory. Each season of a farmer's decisions — what worked, what did not — helps calibrate the same models before they reach paying clients: insurers, banks, commodity firms. The farmer's free use is part of our validation. That is what lets us give it away.
What "free" means for you: the tool costs you nothing, and aggregated, anonymized field outcomes feed back into model validation. We do not sell your individual records; what flows back is the pooled signal of whether a model's call matched what happened in the field.
We are not aware of another company giving the farmer a system of this depth at no charge — not because it is cheap, but because the engine earns its keep elsewhere.
FARMER PAYS ZERO · MODELS LEARN ON REAL FIELDS · INSTITUTIONAL CLIENTS PAY FOR THE MATURE MODEL
06 · NOT A SKIN — A SYSTEM
ENGINEERING SCALE
A decision system, not a screen
130+ peer-reviewed agronomic models and 60+ per-parcel decisions, all curated rather than generated — recomputed per parcel across the full season, not a static dashboard.
WORKS IN THE FIELD
Offline-first; localisation in preparation
Works with no signal — the treatment log and field notes sync once back online. Per-country localisation: weather, crop calendars, language. A release is in preparation for 8+ European countries (roadmap, not yet live everywhere).
EXPLAINABLE
Every alert explains itself
We show the sources, the confidence and the reason for escalation (e.g. lodging from radar raises fusarium risk). An alert appears only when the cost of treatment is below the expected loss — an economic threshold, not panic.
What we are careful about. These are models, and models can be wrong. Satellite passes are missed under persistent cloud; sensor fusion narrows but does not erase uncertainty; phenology and disease thresholds are calibrated to a region and can drift for an unusual season or a new variety. We surface confidence alongside every call and flag when an input is stale or missing rather than guessing. The system supports a decision — it does not replace the agronomist on the ground.
Three sentences for the editor
1. Not a weather app — a decision system. 130+ peer-reviewed agronomic models and 60+ decisions, computed per parcel, hourly.
2. A tool of this class, given to the farmer at no charge. We can do it because real fields help validate our models for paying institutional clients — free use is part of the engine, not a cost.
3. Part of a larger Earth-observation system. Niezbędnik and My Field share an engine with products for banks, insurers and local government — the same science, a different screen.
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