Productivity Insights: Optimizing Crop Management

Armosys, through the ARMOSA simulation model, provides services capable of identifying, via advanced simulations, the most effective agricultural management strategies with the aim of enhancing crop productivity.

Beyond crop yield, the ARMOSA model allows the evaluation of several key agronomic and environmental indicators, such as nitrate leaching, N₂O emissions, and the effects of crop residues from different cropping systems on soil organic carbon dynamics. This integrated approach enables farmers and advisors to assess not only productivity, but also the environmental performance and long-term sustainability of agricultural systems.

Maintaining a good average level of productivity while reducing the use of inputs – particularly mineral nitrogen fertilizers, but also soil tillage operations and irrigation water – allows farmers to lower production costs and, at the same time, reduce the environmental impact of their activities.

By integrating key management information (such as crop rotations, type and amount of fertilizer applied, tillage operations, and irrigation management), the Armosa model can start from a conventional management scenario and develop a set of alternative scenarios. These scenarios, tailored to the specific needs of each farm, make it possible to optimize the management of the entire crop rotation, identifying solutions that are both more efficient and more sustainable.

An application example

A farm aims to identify the optimal nitrogen fertilization strategy to maintain an average annual wheat grain yield of approximately 5 t ha⁻¹.

The conventional management consists of an application of 150 kg N ha⁻¹ of ammonium nitrate, split into two applications.

Kg N ha⁻¹	Year	Crop	Dose 1 (kg N ha⁻¹, period)	Dose 2 (kg N ha⁻¹, period)	Average year yield (t ha⁻¹)
180 AN	10	Wheat	70, october	110, march	4.969
150 AN	10	Wheat	50, october	100, march	4.968
120 AN	10	Wheat	50, october	70, march	4.968
100 AN	10	Wheat	40, october	60, march	4.929
80 AN	10	Wheat	30, october	50, march	4.216

The simulations show that reducing nitrogen fertilization from 150 to 100 kg N ha⁻¹ results in a very similar average wheat yield. A significant yield reduction is observed only when fertilization decreases to 80 kg N ha⁻¹.

These results allow farmers to reduce nitrogen inputs while maintaining adequate yields, achieving significant economic savings and improving the environmental sustainability of agricultural activities. In particular, a more efficient input management contributes positively to indicators such as the Soil Health Index.

Optimization of application timing

Another key strength of the Armosa model is its ability to identify the optimal timing of fertilization, precisely defining both application dates and doses in order to maximize yield.

Still considering wheat, the optimization of a total dose of 100 kg N ha⁻¹ of ammonium nitrate was simulated.

Kg N ha⁻¹	Year	Crop	Dose 1 (kg N ha⁻¹, period)	Dose 2 (kg N ha⁻¹, period)	Dose 3 (kg N ha⁻¹, period)	Average year yield (t ha⁻¹)
100 AN	10	Wheat	40, october	60, march		4.929
100 AN	10	Wheat	30, october	40, january	30, march	4.936
100 AN	10	Wheat	30, october	40, january	30, april	4.931
100 AN	10	Wheat	50, october	30, january	20, april	4.874

Among the four simulated scenarios, the second one proves to be the most performant. This information represents a valuable decision-support tool for farmers, enabling them to plan fertilization operations more efficiently, reduce waste, and maximize productivity.

In addition to optimizing timing, the Armosa model also allows the comparison of different fertilizer types, both mineral and organic, applied at the same dose and application dates. This makes it possible to evaluate how different nutrient sources affect crop yield, nutrient availability, and environmental indicators such as leaching and greenhouse gas emissions, supporting more informed choices in fertilizer management.

The value of the Armosys service

The true value of the ARMOSA simulation model lies in its ability to transform complex data into clear and reliable operational decisions. Farmers are no longer forced to rely solely on standard practices or past experience; instead, they can anticipate the effects of their management choices, significantly reducing technical and economic risk.

Through simulations, different management scenarios can be compared before being implemented in the field, allowing the selection of strategies that ensure the best balance between productivity, costs, and environmental sustainability. This approach is particularly strategic in an agricultural context increasingly affected by climate variability, rising input costs, and stricter regulatory constraints.

Armosys does not simply provide a simulation model, but a comprehensive decision-support service, designed to guide farmers toward more efficient, informed, and resilient management practices. A tool that enhances today’s agricultural production and helps build the sustainable agriculture of tomorrow, grounded in solid scientific principles.