Design of electronic devices for monitoring climatic variables and development of an early warning system for the avocado wilt complex disease.

Highlights • AWC is the most important disease in this crops and present high relation with climatic variables. • Electronic devices were designed for quantification of climatic variables in avocado production systems. • An app was developed with three functions: (ii) early warning system for AWC, (ii) diagnosis of AWC, and (iii) management practices of AWC. Abstract Quantification of climatic variables such as precipitation and temperature and determination of their interactions inside the soil profile is very important in avocado systems as a tool for prompt and appropriate management of several aspects of crop production such as the avocado wilt complex (AWC). Commercial electronic devices are very expensive, with close code, difficult to integrate to an open code system and present the disadvantage that are made and calibrated for different conditions and usually, most epidemiological models are not suitable for the Colombian conditions. The aim of this work was to design a low cost electronic device for the collection and transmission of climatic variables including moisture and temperature from inside the soil profile. As a complement, a mobile application was designed with three functions. (i) Available information in real time, which may be used as an early warning system for the AWC. (ii) Diagnosis of causal agents based on patterns associated with image processing, (a) decomposition of RGB color and comparison of images of plants diseased based on a machine learning algorithm, and (b) a key for identification of diseased plants based on different symptoms, was incorporated. (iii) Management of AWC. We evaluated the capacity of the system to quantify the values of different environmental variables, prediction of early warning system of AWC, and diagnosed strategy for management of AWC, based on a correlation model with the real data taken in avocado fields. The low cost electronic device showed a correlation higher than 90% compared with data obtained from traditional climatic stations and standard methods of soil analysis. In addition, the early warning system achieved a prediction higher than 70% of the variables associated with AWC, whose values increased when the prediction was corroborated with the diagnostic system. [ABSTRACT FROM AUTHOR]