I.F. Beloti, G.M. Maciel, R.B.A. Gallis, R.R. Finzi, A.A. Clemente, A.C.S. Siquieroli, F.C. Juliatti
Published: August 30, 2020
Genet. Mol. Res. 19(3): GMR18598
DOI: https://doi.org/10.4238/gmr18598
Cite this Article:
I.F. Beloti, G.M. Maciel, R.B.A. Gallis, R.R. Finzi, A.A. Clemente, A.C.S. Siquieroli, F.C. Juliatti (2020). Low-altitude, high-resolution aerial imaging for field crop phenotyping in summer squash (Cucurbita pepo). Genet. Mol. Res. 19(3): GMR18598. https://doi.org/10.4238/gmr18598
About the Authors
I.F. Beloti, G.M. Maciel, R.B.A. Gallis, R.R. Finzi, A.A. Clemente, A.C.S. Siquieroli, F.C. Juliatti
Corresponding Author
I.F. Beloti
Email: agroifb@gmail.com
ABSTRACT
The culture of summer squash (Cucurbita pepo) has great socioeconomic importance worldwide. Characterization of C. pepo germplasm has been predominantly performed by field evaluations, which is very time consuming. Thus, the validation of new techniques capable of optimizing time for the field germplasm selection process would be useful. We evaluated agronomic potential and genetic dissimilarity of C. pepo germplasm and gathered data to determine whether aerial images obtained by drone imaging could assist in the selection of vegetative vigor; this is the first such analysis for this crop. Sixty-five genotypes belonging to the vegetable germplasm bank of the Federal University of Uberlândia were evaluated, with three replications in a randomized block design. The variables evaluated were: production per plant, number of fruits per plant, leaf temperature, precocity, and the indexes SPAD (Soil Plant Analysis Development), LAI (Leaf Area Index), NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge Index) the last three variables were obtained using drone imaging. Genetic divergence analysis was performed with multivariate techniques using generalized Mahalanobis distance and UPGMA clustering. Hybrid performance was compared by the Scott-Knott test. UPGMA clustering showed considerable genetic diversity, with the formation of 12 distinct groups. The largest relative contribution was from the leaf area index in the discrimination of the genotypes, demonstrating high efficiency in the validation of the image phenotyping technique. Eight genotypes stood out for yield, fruit number, precocity and high leaf area index, NDVI and NDRE values. The use of image phenotyping using NDVI and NDRE sensors was efficient to identify C. pepo genotypes that differed in plant vigor.
Keywords: Drone, Genetic dissimilarity, Geotechnology, Leaf area index, NDRE, NDVI.