Recommendation of Tahiti acid lime cultivars through Bayesian probability models.

Probabilistic models enhance breeding, especially for the Tahiti acid lime, a fruit essential to fresh markets and industry. These models identify superior and persistent individuals using probability theory, providing a measure of uncertainty that can aid the recommendation. The objective of our study was to evaluate the use of a Bayesian probabilistic model for the recommendation of superior and persistent genotypes of Tahiti acid lime evaluated in 12 harvests. Leveraging the Monte Carlo Hamiltonian sampling algorithm, we calculated the probability of superior performance (superior genotypic value), and the probability of superior stability (reduced variance of the genotype-by-harvests interaction) of each genotype. The probability of superior stability was compared to a measure of persistence estimated from genotypic values predicted using a frequentist model. Our results demonstrated the applicability and advantages of the Bayesian probabilistic model, yielding similar parameters to those of the frequentist model, while providing further information about the probabilities associated with genotype performance and stability. Genotypes G15, G4, G18, and G11 emerged as the most superior in performance, whereas G24, G7, G13, and G3 were identified as the most stable. This study highlights the usefulness of Bayesian probabilistic models in the fruit trees cultivars recommendation.

Effect of F1 and F2 generations on genetic variability and working steps of doubled haploid production in maize.

For doubled haploid (DH) production in maize, F1 generation has been the most frequently used for haploid induction due to facility in the process. However, using F2 generation would be a good alternative to increase genetic variability owing to the additional recombination in meiosis. Our goals were to compare the effect of F1 and F2 generations on DH production in tropical germplasm, evaluating the R1-navajo expression in seeds, the working steps of the methodology, and the genetic variability of the DH lines obtained. Sources germplasm in F1 and F2 generations were crossed with the tropicalized haploid inducer LI-ESALQ. After harvest, for both induction crosses were calculated the haploid induction rate (HIR), diploid seed rate (DSR), and inhibition seed rate (ISR) using the total number of seeds obtained. In order to study the effectiveness of the DH working steps in each generation, the percentage per se and the relative percentage were verified. In addition, SNP markers were obtained for genetic variability studies. Results showed that the values for HIR, ISR, and DSR were 1.23%, 23.48%, and 75.21% for F1 and 1.78%, 15.82%, and 82.38% for F2, respectively. The effectiveness of the DH working step showed the same percentage per se value (0.4%) for F1 and F2, while the relative percentage was 27.2% for F1 and 22.4% for F2. Estimates of population parameters in DH lines from F1 were higher than F2. Furthermore, population structure and kinship analyses showed that one additional generation was not sufficient to create new genotype subgroups. Additionally, the relative efficiency of the response to selection in the F1 was 31.88% higher than F2 due to the number of cycles that are used to obtain the DH. Our results showed that in tropical maize, the use of F1 generation is recommended due to a superior balance between time and genetic variability.