Repeatability coefficient estimates and optimum number of harvests in graft/rootstock combinations for 'tahiti' acid lime

Abstract

Combining longitudinal data and statistical models from perennial crops enabled us to estimate the optimum number of measures (harvests), implying accurate discrimination of superior genotypes in those crops. Herein, the goal of this study was to determine the optimum number of harvests based on yield traits and recommend a superior graft/rootstock combination (GRC) for Citrus latifolia Tanaka. Twenty-four GRCs of 'Tahiti' acid lime were evaluated from July 2017 to August 2018 for fruit yield per plant (FYP), number of fruits per plant (NFP), and longitudinal (LFD) and transversal fruit diameter (TFD). The experimental design was a randomized complete block with 4 replications. The experimental unit consisted of three individuals, totalling 244 individuals. The GRCs were composed of (i) two hybrids that were used as rootstock, citrumelo ‘Swingle’ (Citrus paradisi x Poncirus trifoliata) and cintrandarin ‘Riverside’ (Citrus sunki x Poncirus trifoliata); and (ii) 12 different C. latifolia genotypes that were used as grafts: Bello Fruit, Eledio, Iconha, Itarana, Santa Rosa, Bearss lime, CNPMF 01, CNPMF 02, CNPMF 2001, CNPMF 5059, BRS Passos, and Persian 58. Mixed models were employed to estimate the variance components. The optimum number of harvests was determined based on selective efficiency values above 0.9. The estimated repeatability coefficients presented values of 0.14 (LFD), 0.16 (TFD), 0.36 (FYP), and 0.38 (NFD). Based on the results, four harvests were able to choose genotypes based on FYP and NFP, whereas LFD and TFD were considered inefficient traits for recommending superior GRCs.

Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

“…Furthermore, models with significant genetic parameters are the most suitable for estimating variance components and predicting genotypic values for each trait. The deviance analysis using the likelihood ratio test to evaluate the significance of the genotypic effects is indicated for the analysis of mixed models with unbalanced data (Malikouski et al., 2021). In this study, this analysis revealed the existence of variability among the evaluated hybrids; that is, its effects explain part of the total variation, which demonstrates the possibility of obtaining genetic gains through direct selection in all evaluated traits and, therefore, the recommendation of superior genotypes.…”

Number of harvest years and selection for productivity, witches’ broom resistance, stability, and adaptability in cacao

“…According to Resende and Alves (2020) and considering the average values, NHF, DBW, and FI showed median repeatability, and NWBF had high values of this parameter. Medium to high values for this coefficient denote good genotypes' ability to perform similarly over time (Ferreira et al., 2021; Malikouski et al., 2021). This was attested by analyzing the pairwise genotypic correlations between harvest years, high for all traits.…”

The technology life cycle of Persian lime. A patent based analysis

“…Because of its wide range of applications, the majority of the Persian lime literature focuses on findings that improve, analyze, or observe the traits, parameters and functional aspects of the fruit and its derivatives [ 27 , 28 , 29 ]. For example, research is being conducted on plant development nutrients and compounds [ 30 , 31 ], weed management [ 32 ], harvesting [ 33 ], and protection and preservation [ 34 , 35 ]. Some studies are even held in specific countries due to their unique growth features (for example Egypt [ 28 ], Mexico [ 36 ], or Brazil [ 37 ]).…”