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I’ve always relied on calendar-based applications and they’ve always worked for me. In this context, how can DigiFarmz add value to my operation?

Calendar-based applications are attractive to farmers because they allow planning operations according to available equipment, emergence timing in each field, and provide flexibility between applications. At harvest, however, the result is often just an average yield that does not necessarily reflect the full productive potential. What makes the system “always seem to work” is the absence of a proper control check, which would expose its limitations. Of course, acceptable yields can be achieved, especially under conditions of low disease pressure.

DigiFarmz specifically addresses the points that calendar-based applications fail to consider:

  1. Location: Application programs are fully customized and aligned with the specific field. The combination of georeferencing and weather data is decisive for estimating disease progress and, therefore, structuring a control program — in terms of number of applications and fungicide options. While the industry suggests national control programs, regionalization is essential to maximize the crop’s yield potential.

  2. Altitude and latitude: These factors define which pathogens are present and how fast they develop. This rate of progress determines how quickly an epidemic can evolve and, consequently, how a proper control program should be structured.

  3. Climate variability: Weather conditions vary across regions, fields, months, and even days. This variability directly impacts the success of a program — from product selection to number of applications, timing, and intervals between sprays. Weather influences not only pathogens (weeds, insects, diseases) but also the crop itself, affecting both productive capacity and vulnerability. The more precise the program, the lower the sanitary impact.

  4. Cultivar: The chosen variety directly impacts productivity and pathogen dynamics. Productivity is a physiological trait of the plant, but maximizing it requires optimized environments: soils without chemical or physical restrictions, minimal sanitary pressure, optimal solar energy, adequate rainfall, and favorable temperatures. As these factors align, plants express stronger defense mechanisms (structural and biochemical), naturally influencing adjustments to the control program. Each cultivar requires specific fine-tuning, which DigiFarmz incorporates for greater accuracy.

  5. Priority target: Even if farmers correctly identify diseases, DigiFarmz adjusts programs at each application. Depending on climate conditions and crop stage, the primary disease may shift, requiring changes in product choice. For example: rust and powdery mildew are spread by wind, anthracnose by rain splash, while others depend on both rain and wind. As these targets alternate, DigiFarmz ensures programs adapt accordingly.

  6. Fungicide choice and tank mixes: Fungicides act differently depending on their chemical group. Some perform best at specific growth stages or before disease is visible, while others are less effective on established infections. DigiFarmz positions fungicides and tank mixes correctly — whether systemic + systemic or systemic + contact. For example, Chlorothalonil (strong fungicidal action) is better suited for early or late applications in soybeans, while Mancozeb (fungicidal + physiological benefits) shows best results during flowering and early grain filling. DigiFarmz algorithms factor in all these criteria, ensuring precise recommendations.

  7. Correction factors between applications: Unforeseen delays (rain, equipment breakdowns, absent operators) can disrupt schedules. Soybeans can lose 0.8 to 1.2 kg/ha/day if disease is not controlled on time. A 10-day delay could cause up to 20% yield loss — in 1,000 ha with potential of 70 bags/ha, this equals a 14,000-bag reduction. DigiFarmz helps correct intervals and recommend fungicide combinations to minimize damage.

  8. Extreme weather events: Extended drought, prolonged rainfall, and heat extremes can alter suggested programs, prompting DigiFarmz to end a program early or make significant adjustments. Thanks to daily climate data updates, the platform adapts recommendations whenever extreme conditions arise.

It is important to highlight that these factors do not act in isolation, but interact in real farming conditions. This is the key difference between DigiFarmz and other systems. DigiFarmz gathers these variables from its clients and returns personalized, adaptive recommendations. Over time, its algorithms learn from each farm, delivering even more precise and tailored suggestions. In its new version, DigiFarmz will also integrate the crop’s nutritional dynamics, providing clients with both performance highlights and areas needing more attention. The ultimate goal of DigiFarmz is to enable maximum profitability in agricultural operations.