Forecast Spraying & Skip the Calendar Passes

A forecast (or disease-warning) system uses weather — leaf wetness, temperature, rainfall — to predict when infection conditions actually occur, so you spray only ahead of real infection events instead of on a fixed calendar. Many days in a season are not infection-favourable, so a calendar program sprays through dry, low-risk spells unnecessarily. Targeting sprays to the infection periods typically removes several passes while still protecting the crop.

It varies by disease, but published trials commonly show 30–50% fewer sprays than a fixed calendar. For example TOM-CAST cuts tomato and carrot foliar sprays by roughly a third, the Strawberry Advisory System about halves bloom-period sprays, and apple-scab models drop several primary-season cover sprays. This tool reports the saved-spray count and percentage for the specific disease you choose from its reference dataset.

Yes — in the multi-site trials behind these numbers, disease control at the reduced spray count matched the calendar program, because the forecast never skips a spray when infection risk is high; it only removes the unnecessary low-risk passes. The key is that the system delays sprays in dry spells but tightens up under epidemic pressure, so control is maintained, not traded away for savings.

Pick a disease, your area and your cost per fungicide pass, and it returns the calendar spray count, the typical forecast-triggered count, the sprays and percentage saved, the money saved per acre and across your area, and a verdict (big, moderate or marginal saving). It also shows a season timeline of calendar versus forecast spray dates so you can see the difference visually.

Many. This dataset covers potato/tomato late blight (BliteCast), apple scab (Mills/NEWA), tomato and carrot early blight (TOM-CAST), sugarbeet Cercospora leaf spot (BEETcast), grape and onion and cucurbit downy mildews (DMCast, DOWNCAST, CDM ipmPIPE), peanut leaf spot (AU-Pnuts), strawberry botrytis (SAS), wheat Fusarium head blight (FHB risk tool) and potato early blight (P-Day) — each with its calendar versus forecast spray counts.

A DSV is a daily score a model like TOM-CAST assigns from leaf-wetness hours and temperature; the higher the score, the more favourable the day was for infection. You accumulate DSVs and spray when the total crosses a threshold (commonly 15–20 DSV for TOM-CAST), then reset. Because dry days add few or no DSVs, the accumulator naturally spaces sprays out in dry weather — the mechanism behind the spray saving.

Multiply the sprays saved by your cost per fungicide pass (product plus application) and your acreage. If a model saves four passes at $25 per acre on 100 acres, that is $10,000 a season. The tool does this arithmetic for your inputs, showing the saving per acre and total — and the saving recurs every year the model is used, before counting the residue and resistance benefits.

Fewer fungicide passes mean lower residue loads, less selection pressure for fungicide resistance, reduced fuel and labour, and less soil compaction from machinery traffic. Resistance management in particular benefits, because each unnecessary spray adds selection pressure; cutting the low-value calendar sprays preserves the effective life of the fungicide chemistry you rely on for the high-risk infection periods.

The calendar count comes from the disease's typical fixed program in the dataset, and the forecast count is the published trial mid-point. If you run your own decision-support system and know your forecast spray count, you can enter it to compare your real program against the calendar baseline, and the savings recalculate from your number.

If the model saves at least one spray with control maintained — which the tool flags as 'worth it' — and a weather/forecast source is available for your area, it is usually a clear win on cost, residues and resistance. The decision is strongest where calendar programs are spray-heavy (downy mildews, late blight, strawberry botrytis) and weaker where the calendar is already lean. The verdict band makes that call for the disease you pick.

Often not your own — many models run on regional networks (NEWA, ipmPIPE, university DSS portals) that deliver the risk output to you, though an on-farm leaf-wetness and temperature sensor improves local accuracy. The savings in this tool assume you act on a working forecast; the value of installing a sensor is exactly the spray and cost saving shown, weighed against the sensor cost.

No. Forecasting tells you when infection risk is high so you spray at the right time and skip the rest; you still scout to confirm disease presence and the fungicide label remains the legal authority on rate, timing, pre-harvest interval and resistance-group rotation. Use the savings here to justify adopting a model, then operate it alongside scouting and label-compliant product choice.