GestHerb: design of a digital tool for monitoring weed seedlings in fields

Abstract

Developing decision support systems to help farmers and technicians achieve greater efficiency in weed management is one of the pillars of integrated weed management programs. Greater efficiency is achieved by applying a control measure when most seedlings have already emerged. Having a tool that indicates when this moment is would be of great help to the technician or farmer. In this paper we present an application for mobile and desktop that predicts the field emergence of various winter and summer species based on daily precipitation and temperature data collected from weather stations. Based on these data the program calculates for the selected species the onset of emergencies and elaborates the curve of emergencies, indicating the percentage of seedlings with respect to the expected total for the year. When 90% or a given value set by the user is reached, the system generates a warning for quick action. For the calculations, a hydrothermal model that considers air temperature and water content of the soil is applied. Soil moisture is estimated daily from a water balance based on precipitation, evapotranspiration and water storage capacity of the soil according to its texture. The emergence pattern is fitted with a Gompertz model.