Affiliation:
1. Universidade Federal de Minas Gerais
Abstract
Abstract
Through the use of computational systems, it is possible to employ a wide range of statistical techniques, available as open-source code, to perform various assessments in plants. This study aims to demonstrate the application of image analysis in the context of evaluating root nodules in chickpea plants, aiming to standardize a methodology. The research was conducted in the field, where roots were collected, cleaned, and photographed in a studio using a camera with ISO320, SPEED 1/1500 F1.5 M0.6, WB490K. Image analyses were carried out using R software. Parameters related to roots and nodules were obtained, including root area (cm2), nodule area (cm²), the percentage of nodules in relation to roots, and the number of nodules. Comparing the method with conventional approaches showed efficiency, highlighting the effectiveness of this tool for the intended purpose. It is concluded that the use of the developed methodology can be successfully applied to the analysis of nodules and root systems, providing the evaluation of various parameters with precision, reducing labor costs, and saving time.
Publisher
Research Square Platform LLC
Reference6 articles.
1. Use of satellite remote sensing data for crop disease management: a review;ANWAR S;Remote Sens,2020
2. AZEVEDO AM, ExpImage. Tool For Analysis of Images in Experiments. CRAN package repository. 2023 https://CRAN.R-project.org/package=ExpImage.
3. WEITZ, AND JONATHAN P. LYNCH. Image-Based High-Throughput Field Phenotyping of Crop Roots;BUCKSCH A;Plant Physiol,2014
4. MOREIRA, I. B. Image processing as to important tool for artificial intelligence in the seed sector;DE MESQUITA PINHEIRO R;Revista Agrária Acadêmica,2022
5. Artificial intelligence (AI) in agriculture;DHARMARAJ V;Int J Curr Microbiol Appl Sci,2018