High-Throughput Phenotyping for the Evaluation of Agronomic Potential and Root Quality in Tropical Carrot Using RGB Sensors

Fernanda Gabriela Teixeira Coelho, Gabriel Mascarenhas Maciel (), Ana Carolina Silva Siquieroli, Rodrigo Bezerra de Araújo Gallis, Camila Soares de Oliveira, Ana Luisa Alves Ribeiro and Lucas Medeiros Pereira
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Fernanda Gabriela Teixeira Coelho: Postgraduate Program in Agronomy, Institute of Agrarian Sciences, Federal University of Uberlândia, Uberlândia 38410-337, Brazil
Gabriel Mascarenhas Maciel: Institute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, Brazil
Ana Carolina Silva Siquieroli: Institute of Biotechnology, Federal University of Uberlândia, Monte Carmelo 38500-000, Brazil
Rodrigo Bezerra de Araújo Gallis: Institute of Geography, Federal University of Uberlândia, Monte Carmelo 38500-000, Brazil
Camila Soares de Oliveira: Institute of Agrarian Sciences, Federal University of Uberlândia, Monte Carmelo 38500-000, Brazil
Ana Luisa Alves Ribeiro: Postgraduate Program in Agronomy, Institute of Agrarian Sciences, Federal University of Uberlândia, Uberlândia 38410-337, Brazil
Lucas Medeiros Pereira: Postgraduate Program in Agronomy, Institute of Agrarian Sciences, Federal University of Uberlândia, Uberlândia 38410-337, Brazil

Agriculture, 2024, vol. 14, issue 5, 1-15

Abstract: The objective of this study was to verify the genetic dissimilarity and validate image phenotyping using RGB (red, green, and blue) sensors in tropical carrot germplasms. The experiment was conducted in the city of Carandaí-MG, Brazil, using 57 tropical carrot entries from Seminis and three commercial entries. The entries were evaluated agronomically and two flights with Remotely Piloted Aircraft (RPA) were conducted. Clustering was performed to validate the existence of genetic variability among the entries using an artificial neural network to produce a Kohonen’s self-organizing map. The genotype–ideotype distance index was used to verify the best entries. Genetic variability among the tropical carrot entries was evidenced by the formation of six groups. The Brightness Index (BI), Primary Colors Hue Index (HI), Overall Hue Index (HUE), Normalized Green Red Difference Index (NGRDI), Soil Color Index (SCI), and Visible Atmospherically Resistant Index (VARI), as well as the calculated areas of marketable, unmarketable, and total roots, were correlated with agronomic characters, including leaf blight severity and root yield. This indicates that tropical carrot materials can be indirectly evaluated via remote sensing. Ten entries were selected using the genotype–ideotype distance (2, 15, 16, 22, 34, 37, 39, 51, 52, and 53), confirming the superiority of the entries.

Keywords: carrot; image phenotyping; Kohonen map; remote sensing; vegetation indices (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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