Production viability index for annual agricultural crops

CONTEXT

In the face of intensifying challenges for sustainable food production, well-planned agricultural development is crucial to mitigate climate impacts and manage blue water demands. Tools and methodologies that support public policy for sustainable regional growth are essential, especially in regions lacking hydroclimatic data, which complicates the use of simulation models for efficient water management. An effective tool should identify areas most suitable for rainfed and irrigated agriculture, optimizing planting dates, crop types, and rotations.

OBJECTIVE

To develop an index to assess the most suitable areas, inside regions, for developing rainfed and irrigated annual crops.

METHODS

The proposed Production Viability Index (PVI) combines ISDIA (Irrigated Agriculture Suitability Indicator) and ISDRA (Rainfed Agriculture Suitability Indicator) to represent suitability for irrigated and rainfed agriculture. Each indicator comprises five sub-indicators reflecting plant characteristics, soil, climate, and water availability in crop production. A Python routine was developed to calculate the PVI, which was then used to assess soybean production suitability across 204 million hectares in Brazil's Cerrado (Brazilian savannah), the country's second-largest biome. Three planting dates (September 15, October 15, and November 15) were simulated, evaluating the Cerrado's suitability and identifying the best planting date per area.

RESULTS AND CONCLUSIONS

The PVI for Annual Crops proves to be a valuable tool for agricultural planning, enabling the identification of areas with varying suitability for sustainable agricultural development. Based on factors such as climate, soil, plant characteristics, and water availability, the PVI is not intended to determine if a crop can be produced in a specific area but rather to identify locations with greater cultivation potential across different periods and crop types. Results highlight suitability variations throughout the months, underscoring the need for dynamic planning that accounts for seasonality and regional characteristics. Consequently, the PVI significantly supports managers and agricultural planners in developing adaptive strategies, maximizing agricultural productivity and resilience across diverse agro-ecological contexts.

SIGNIFICANCE

This work's primary contribution is the development of an index to classify areas within regions based on rainfed and irrigated agriculture potential, relying on basic, accessible data sets for soil, climate, water, and plant information. These findings aid planners in identifying the most suitable areas for sustainable agricultural expansion, enhancing annual crop production while mitigating water use conflicts.