Target spot, caused by the fungus Corynespora cassiicola, has become a serious foliar disease in soybean production in the Brazilian Cerrado. Information in the literature regarding the biochemical defence responses of soybean to C. cassiicola infection is rare. Therefore, the objective of this study was to determine the biochemical features associated with soybean resistance to target spot. The activities of chitinases (CHI), b-1-3-glucanases (GLU), phenylalanine ammonia-lyases (PAL), peroxidases (POX), polyphenol oxidases (PPO) and lipoxygenases (LOX), as well as the concentrations of total soluble phenolics (TSP) and lignin-thioglycolic acid (LTGA) derivatives, were determined in soybean leaves from both a resistant (FUNDACEP 59) and a susceptible (TMG 132) cultivar. The target spot severity, number of lesions per cm 2 of leaflet and area under the disease progress curve were significantly lower for plants from cv. FUNDA-CEP 59 compared to plants from cv. TMG 132. The GLU, CHI, PAL, POX and PPO activities and the concentration of LTGA derivatives increased significantly, whereas LOX activity decreased significantly on the leaves infected by C. cassiicola. Inoculated plants from cv. FUNDACEP 59 showed a higher PPO activity and concentrations of TSP and LTGA derivatives at 4 and 6 days after inoculation compared to plants from cv. TMG 132. In conclusion, the results of this study demonstrated that the defence-related enzyme activities increased upon C. cassiicola infection, regardless of the basal level of resistance of the cultivar studied. The increases in PPO activity and concentrations of TSP and LTGA derivatives, but lower LOX activity, at early stages of C. cassiicola infection were highly associated with soybean resistance to target spot.
Considering the importance of target spot, caused by the fungus Corynespora cassiicola, to reduce soybean yield in Brazil and that more basic information regarding the soybean-C. cassiicola interaction is needed, the present study aimed to investigate whether the cellular damage caused by C. cassiicola infection could activate the antioxidant system and whether a more efficient antioxidant system could be associated with an increase in soybean resistance to target spot. The activities of the antioxidant enzymes superoxide dismutase, catalase, peroxidase, ascorbate peroxidase, glutathione peroxidase, glutathione reductase, glutathione S-transferase as well as the concentrations of ascorbate (AsA), hydrogen peroxide (H2O2), superoxide (O2•-), and malondialdehyde (MDA) were measured in soybean plants from two cultivars differing in resistance to the pathogen. The number of lesions per square centimeter was significantly reduced by 14% in plants from cultivar Fundacep 59 compared with plants from cultivar TMG 132. The area under the disease progress curve was significantly lower, by 15%, in plants from Fundacep 59 than in plants from TMG 132. Generally, antioxidant enzyme activities and AsA concentration significantly increased in response to C. cassiicola infection in plants from both cultivars, however more prominent increases were recorded for plants from Fundacep 59. The concentrations of MDA, H2O2, and O2•- also increased, particularly for plants from TMG 132. The results from this study highlight the importance of a more efficient antioxidative system in the removal of reactive oxygen species generated in soybean plants during C. cassiicola infection, contributing to the resistance to target spot.
Spatial variation is a recurrent issue in field trials and can cause obstacles in terms of genetic selection. Analyses that account for spatial variation within location can lead breeders to predict genetic values accurately across locations in multi-environment trials (METs). The present study aims to fit spatial models for analyzing soybean [Glycine max (L.) Merr.] seed composition traits using a two-stage analysis pipeline and to assess its efficiency relative to a single-stage analysis setting. Seed protein content (SPC), seed oil content (SOC), and seed storage protein content (SSP) data were collected from 283 soybean genotypes tested in four environments (C1, C2, V1, and V2). In Stage 1 of the two-stage analysis, a randomized complete block (RCB) design model as well as four two-dimensional first-order (AR1 ⊗ AR1) spatial models were fit in each dataset to determine the most suitable model for genetic prediction. Predicted genetic values were used as input data for Stage 2. The most used spatial model [5] in Stage 1 of this study had accommodated local and global residuals. The autocorrelation estimates depicted spatial trends, especially in terms of rows, while column autocorrelation coefficients were low for C1 and C2 because of the limited number of blocks and their short length. Broad-sense heritability, mean accuracy, and selection gains were greater for all traits in the two-stage analysis than in the single-stage analysis. The two-stage analysis leveraged the spatial model fitting in the Stage 1 and proved to be advantageous for soybean seed composition breeding.
Spatial trends represent an obstacle to genetic evaluation in maize breeding. Spatial analyses can correct spatial trends, which allow for an increase in selective accuracy. The objective of this study was to compare the spatial (SPA) and non-spatial (NSPA) models in diallel multi-environment trial analyses in maize breeding. The trials consisted of 78 inter-populational maize hybrids, tested in four environments (E1, E2, E3, and E4), with three replications, under a randomized complete block design. The SPA models accounted for autocorrelation among rows and columns by the inclusion of first-order autoregressive matrices (AR1 ⊗ AR1). Then, the rows and columns factors were included in the fixed and random parts of the model. Based on the Bayesian information criteria, the SPA models were used to analyze trials E3 and E4, while the NSPA model was used for analyzing trials E1 and E2. In the joint analysis, the compound symmetry structure for the genotypic effects presented the best fit. The likelihood ratio test showed that some effects changed regarding significance when the SPA and NSPA models were used. In addition, the heritability, selective accuracy, and selection gain were higher when the SPA models were used. This indicates the power of the SPA model in dealing with spatial trends. The SPA model exhibits higher reliability values and is recommended to be incorporated in the standard procedure of genetic evaluation in maize breeding. The analyses bring the parents 2, 10 and 12, as potential parents in this microregion.
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