Biology subjects

Rocha, D. J. A.

Publications and source records attributed to Rocha, D. J. A..

3 recordsLinked to original sources

bioRxiv2025

Evaluation of annual ryegrass genotypes for forage yield and blast resistance

The annual ryegrass (Lolium multiflorum Lam.) is a key winter forage, but its productivity is limited by diseases, especially blast, caused by Magnaporthe oryzae (syn. Pyricularia oryzae). This study aimed to evaluate the productive performance and reaction to blast of commercial cultivars and advanced lines of annual ryegrass in two edaphoclimatic environments in Santa Catarina, Brazil: Lages (Cfb climate) and Agronomica (Cfa climate). The experiment utilized a randomized block design with eight genotypes and four replicates. Variables analyzed included dry matter yield and blast severity. A bifactorial analysis of variance (genotype x local) and Spearman correlation were performed. The results revealed a significant genotype x environment (GxA) interaction for both dry matter yield and blast severity, indicating a dependence on local conditions. Blast pressure was drastically higher in Agronomica, which is climatically more favorable to the disease. Annual ryegrass genotypes Altovale and Taio were superior, combining high and stable productivity with low disease severity in both locations. Conversely, the cultivar Ponteio showed high yield only in Lages, suffering a severe reduction and higher susceptibility in Agronomica. Ceronte was the most susceptible genotype, reaching 86.25% severity in Agronomica. The Spearman correlation confirmed a negative and significant impact of blast on forage productivity, with a stronger correlation in Agronomica ({rho} = -0.689) than in Lages ({rho} = -0.497). These findings underscore that the GxA interaction is primarily driven by the differential resistance response to blast. Altovale and Taio are the most recommended options. It is concluded that the selection of ryegrass genotypes must be conducted in the target environment, considering blast as a primary selection factor to ensure the stability and sustainability of forage production in southern Brazil.

genetics↗

bioRxiv2023

Genomic selection for herbage yield in forage oats (Avena sp.)

The study investigated the potential of genomic selection (GS) to accelerate genetic improvement in forage oats (Avena sp.) by predicting herbage yield. The results showed that GS can be an effective tool for predicting herbage yield in forage oats, with prediction accuracies ranging from 0.91 to 0.97. The use of SNP markers for GS in forage oats has several advantages over traditional marker-assisted selection (MAS), including the ability to capture more of the genetic variation for the trait of interest. The accuracy of GS predictions can be further improved by using trait-specific relationship matrices (TGRMs) and genomic information from multiple generations. Key FindingsO_LIGS can be an effective tool for predicting herbage yield in forage oats, with prediction accuracies ranging from 0.91 to 0.97. C_LIO_LIThe use of SNP markers for GS in forage oats has several advantages over traditional MAS, including the ability to capture more of the genetic variation for the trait of interest. C_LIO_LIThe accuracy of GS predictions can be further improved by using TGRMs and genomic information from multiple generations. C_LI ImplicationsO_LIGS can be used to accelerate the development of new forage oat varieties with improved herbage yield. C_LIO_LIGS has the potential to significantly improve the agronomic performance and quality of forage oat varieties. C_LI Future ResearchO_LIDevelop a more structured training population to improve the accuracy of GS predictions. C_LIO_LIIdentify trait-specific relationship matrices (TGRMs) to further improve the accuracy of GS predictions. C_LIO_LIInvestigate the use of genomic information from multiple generations to improve the accuracy of GS predictions. C_LI

genetics↗

bioRxiv2021

SCS313 Serrano, a big trefoil selected for flowering ability and seed production

SCS313 Serrano is a tetraploid cultivar of Lotus uliginosus developed by the Research and Rural Extension Company of Santa Catarina, Brazil, to improve flowering ability and seed production in low-latitude regions. SCS313 Serrano was developed from the selection of individual plants of the cultivar Grasslands Maku. Seeds from the initial breeding population was bulked and used to establish a field trial with spaced plants. The plants were selected and classified as late or early, regarding the beginning of flowering, through visual evaluations based on the time for the beginning of flowering. Selected plants were transplanted to crossing blocks and seed harvested on individual plants; a progeny test was conducted, with four replications, through the establishment of approximately 100 genotypes in a field. This process was repeated for three consecutive cycles of recurrent selection. Considering the mean time for the beginning of flowering and vigor performance, the best five genotypes were selected as parental lines for the synthetic cultivar SCS313 Serrano. A morphological difference between SCS313 Serrano and Grasslands Maku is that SCS313 Serrano has absence of hairs in stems whereas Grasslands Maku has a medium stem hair density. In addition, SCS313 Serrano exhibits profuse flowering ability while Grasslands Maku exhibits very sparse seedhead formation. SCS313 Serrano exhibited good persistence under wet conditions and similar forage yields compared to other lotus commercial cultivars. Thus, SCS313 Serrano is recommended to be used as pasture in mixtures with grass in livestock systems, mainly on wet soils.

plant biology↗