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Manual phenotyping (MP) methodology forpapaya breeding demands intensive labor and is time-consuming. This study aimed to validate a low-cost image-based phenotyping (IBP) methodology of fruit traits to speed up the process in breeding program. Two groups of 50 fruits of the 'THB' at the zero-maturitystage were used. The fruits were sliced longitudinally and half part of the fruit was scanned in Flat-bed Scanner to obtain the digital image. In the first group, the length and diameter of fruits were measured by image processing (IP) using a two-bit binary imageand the ovarian cavity length, ovarian cavity diameter, thickness pulp were measured by image analysis (IA) in RGB format using the straight tool of ImageJ software. Thetraits were measured by digital caliper. The fruit mass(FM)was measured by analytical scale and de fruit volume (FV) was estimated using the water desplacement method (WDM). The second group was used to estimate the FV and FMthrough IP and MP. The trait averages were estimated using IBP, similar to thoseaverages measured manually. The coefficients of variation estimated by IBP were low compared to the measurement by MP, indicating that this methodology is more accurate. The Bland-Altman approach showed agreement between the FV obtained by the WDM and IP. Since the IBP is about four times quicker and less-dependent on labor, it is expected to be incorporated to papaya breeding as a way to increase the number of accessed (being evaluated) genotypes and, consequently, increasing the genetic gains.

Image-based phenotyping of morpho-agronomic traits in papaya fruits (Carica papaya L. THB var.)