A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping

Abstract

The development of high-throughput field phenotyping, which uses modern detection technologies and advanced data processing algorithms, could increase productivity and make in-field phenotypic evaluation more efficient by collecting large amounts of data with no or minimal human assistance. Moreover, high-throughput plant phenotyping systems are also very effective in selecting crops and characterizing germplasm for drought tolerance and disease resistance by using spectral sensor data in combination with machine learning. In this study, an affordable high-throughput phenotyping platform (phenomobile) aims to obtain solutions at reasonable prices for all the components that make up it and the many data collected. The goal of the practical innovation in field phenotyping is to implement high-performance precision phenotyping under real-world conditions at accessible costs, making real-time data analysis techniques more user-friendly. This work aims to test the ability of a phenotyping prototype system constituted by an electric phenomobile integrated with a MAIA multispectral camera for real in-field plant characterization. This was done by acquiring spectral signatures of F1 hybrid Elisir (Olter Sementi) tomato plants and calculating their vegetation indexes. This work allowed to collect, in real time, a great number of field data about, for example, the morphological traits of crops, plant physiological activities, plant diseases, fruit maturity, and plant water stress.