Yield prediction of experimental plots based on the harvest of specific fruit clusters for selection of fresh market tomato hybrids

Abstract

The objective of this study was to propose models based on the harvest of specific fruit clusters to estimate the plot yield of trials containing fresh market tomato hybrids. Three experiments were conducted at the Experimental Station of Syngenta Crop Protection in the municipality of Holambra, state of São Paulo, Brazil, in 2016 and 2017. The experimental design was randomized complete blocks with 12 genotypes (experiments 1 and 3) and 13 genotypes (experiment 2), with 4 replicates and 10 plants per plot. Multiple linear regression models were fitted (stepwise method) with experiment 1 data (cross-validation), the best models were selected (higher adjusted R²) and then tested with experiments 2 and 3 data by mean of absolute percentage error (MAPE), for the traits mean weight of marketable fruit per plant A (MWA), AA (MWAA), AAA (MWAAA), AA and AAA (MW23A), and the ratio between the market weight and the number of marketable fruits (MFW). The models with four fruit clusters (2, 3, 6 and 9) showed the best balance between prediction capacity and the number of fruit clusters to harvest. The traits MWAA, MW23A and MFW generated reliable predictions, with MAPE approximately 5%. The multiple linear regression can be used to estimate the plot yield what, in the last instance, contributes to the reduction of the costs to conduct fresh market tomato hybrids