-Brazil has the largest commercial beef
Brachiaria humidicola (Rendle) Schweick. is a warm-season grass commonly used as forage in the tropics. Accessions of this species were collected in eastern Africa and massively introduced into South America in the 1980s. Several of these accessions form a germplasm collection at the Brazilian Agricultural Research Corporation. However, apomixis, ploidy, and limited knowledge of the genetic basis of this germplasm collection have constrained breeding activities. The objectives of this work were to identify genetic variability in the Brazilian B. humidicola germplasm collection using microsatellite markers and to compare the results with information on the following: (1) collection sites of the accessions; (2) reproductive mode and ploidy levels; and (3) genetic diversity revealed by morphological traits. The evaluated germplasm population is highly structured into four major groups. The sole sexual accession did not group with any of the clusters. Genetic dissimilarities did not correlate with either geographic distances or genetic distances inferred from morphological descriptors. Additionally, the genetic structure identified in this collection did not correspond to differences in ploidy level. Alleles exclusive to either sexual or apomictic accessions were identified, suggesting that further evaluation of the association of these loci with apospory should be carried out.
Resumo -O objetivo deste trabalho foi parametrizar e avaliar o modelo DSSAT/Canegro para cinco variedades brasileiras de cana-de-açúcar. A parametrização foi realizada a partir do uso de dados biométricos e de crescimento das variedades CTC 4, CTC 7, CTC 20, RB 86-7515 e RB 83-5486, obtidos em cinco localidades brasileiras. Foi realizada análise de sensibilidade local para os principais parâmetros. A parametrização do modelo foi feita por meio da técnica de estimativa da incerteza de probabilidade generalizada ("generalized likelihood uncertainty estimation", Glue). Para a avaliação das predições, foram utilizados, como indicadores estatísticos, o coeficiente de determinação (R 2 ), o índice D de Willmott e a raiz quadrada do erro-médio (RMSE). As variedades CTC apresentaram índice D entre 0,870 e 0,944, para índice de área foliar, altura de colmo, perfilhamento e teor de sacarose. A variedade RB 83-5486 apresentou resultados similares para teor de sacarose e massa de matéria fresca do colmo, enquanto a variedade RB 86-7515 apresentou valores entre 0,665 e 0,873, para as variáveis avaliadas.Termos para indexação: Saccharum, biometria, calibração, modelagem, validação. Parameterization and evaluation of the DSSAT/Canegro model for Brazilian sugarcane varietiesAbstract -The objective of this work was to parameterize and to evaluate the DSSAT/Canegro model for five Brazilian sugarcane varieties. The parameterization was done using biometric and growth data from the varieties CTC 4, CTC 7, CTC 20, RB 86-7515, and RB 83-5486, obtained in five Brazilian locations. Local sensitivity analysis was performed for the main parameters. Model parameterization was done using the generalized likelihood uncertainty estimation (Glue) method. The predictions were evaluated using the coefficient of determination (R²), Willmott's D-index, and the root mean square error (RMSE) as statistical indexes. CTC varieties showed D values ranging from 0.870 to 0.944 for leaf area index, stalk height, tillering, and sucrose content. The RB 83-5486 variety showed similar results for sucrose content and fresh matter mass of stalks, whereas the RB 86-7515 variety showed values ranging from 0.665 to 0.873 for all variables analyzed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.