Fluorescence quantum yield of natural dye extracted from Tradescantia pallida purpurea as a function of the seasons: Preliminary bioapplication as a fungicide probe for necrotrophic fungi.

In this work, over the course of four seasons (12 months), we have monitored the fluorescence quantum efficiency (η) from two sets (S1 and S2) of fresh natural dye extracts from the leaves of Tradescantia pallida purpurea. The natural dye was extracted in aqueous solutions from leaves collected from regions with a predominance of shade (S1) and sun (S2) during the day. The thermo-optical parameter fractional thermal load (φ) was measured using conical diffraction (CD) patterns caused by thermally driven self-phase modulation, for η determination in both sets of solutions. Fluorescence measurements corroborate the CD results, and the η values are, on average, slightly higher (~ 11%) in the summer than in the other seasons for both sets of samples (S1 and S2). In addition, the experimental results are presented using natural dye extracted from Tradescantia pallida purpurea as a fungicide probe in Fusarium solani, Sclerotinia sclerotiorum, and Colletotrichum gloeosporioides fungi. The promising fungicide results obtained for the aqueous natural dye extract were compared with those obtained for other natural dyes and fungi. The fungi tested are of the necrotrophic group and constitute important pathosystems in Brazil, causing diseases in several crops that synthetic fungicides often cannot control or do so with low efficiency.

Performance and Profitability of Fungicides for Managing Soybean White Mold: A 10-Year Summary of Cooperative Trials.

White mold, caused by Sclerotinia sclerotiorum, is a yield-limiting disease of soybean in Brazil. Uniform fungicide trials have been conducted annually since 2009. Data from 74 cooperative field trials conducted over a 10-year period were assembled. We selected five fungicides applied two times around flowering: dimoxystrobin plus boscalid (DIMO+BOSC), carbendazim plus procymidone (CARB+PROC), fluazinam (FLUZ), fluopyram (FLUO), and procymidone (PROC). For comparison, thiophanate-methyl (TMET) applied four times was also included as a low-cost treatment. Network models were fitted to the log of white mold incidence (percentages) and log of sclerotia mass data (grams/hectare) and to the nontransformed yield data (kilograms/hectare) for each treatment, including the untreated check. Back-transformation of the meta-analytic estimates indicated that the lowest and highest mean (95% confidence interval [CI]) percent reductions in incidence and sclerotia mass were 54.2 (49.3 to 58.7) and 51.6% (43.7 to 58.3) for TMET and 83.8 (79.1 to 87.5) and 87% (81.9 to 91.6) for CARB+PROC, respectively. The overall mean (95% CI) yield responses ranged from 323 kg/ha (247.4 to 400.3) for TMET to 626 kg/ha (521.7 to 731.7) for DIMO+BOSC, but the variance was significantly reduced by a binary variable (30% threshold) describing disease incidence in the untreated check. On average, an increment of 352 kg/ha was estimated for trials where the incidence was >30% compared with the low-disease scenario. Hence, the probability of breaking even on fungicide costs for the high-disease scenario was >65% for the more effective, but more expensive fungicide (FLUZ) than TMET. For the low-disease scenario, profitability was less likely and depended more on variations in fungicide cost and soybean price.

Meta-Analytic Modeling of the Decline in Performance of Fungicides for Managing Soybean Rust after a Decade of Use in Brazil.

An apparent decline of fungicide performance for the control of soybean rust in Brazil has been reported but the rate at which it has occurred has not been formally quantified. Control efficacy and yield response to three fungicides applied as single active ingredients (a.i.)-azoxystrobin (AZOX), cyproconazole (CYPR), and tebuconazole (TEBU)-and four applied as mixtures-AZOX+CYPR, picoxystrobin + CYPR, pyraclostrobin + epoxiconazole, and trifloxystrobin + prothioconazole (TRIF+PROT)-were summarized using network meta-analytic models fitted to mean severity and yield data from 250 trials (10-year period). The effect of year was tested on both variables in a meta-regression model. Overall control efficacy ranged from 56 to 84%; the three single-a.i. fungicides performed the poorest (56 to 62%). Yield increase for single-a.i. fungicides was as low as 30% but ranged from 47 to 65% for the premixes. Significant declines in both variables were detected for all fungicides except TRIF+PROT. For TEBU, control efficacy (yield response) declined the most: 78% (18%) to 54% (8%) from 2004-05 to 2013-14. The recent surge of resistant populations of Phakopsora pachyrhizi to both demethylation inhibitor and quinone outside inhibitor fungicides is likely the driving force behind a significant decline after 4 years of fungicide use.

Genome-wide association mapping of resistance to a Brazilian isolate of Sclerotinia sclerotiorum in soybean genotypes mostly from Brazil.

BACKGROUND: Sclerotinia Stem Rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is ubiquitous in cooler climates where soybean crops are grown. Breeding for resistance to SSR remains challenging in crops like soybean, where no single gene provides strong resistance, but instead, multiple genes work together to provide partial resistance. In this study, a genome-wide association study (GWAS) was performed to dissect the complex genetic architecture of soybean quantitative resistance to SSR and to provide effective molecular markers that could be used in breeding programs. A collection of 420 soybean genotypes were selected based on either reports of resistance, or from one of three different breeding programs in Brazil, two commercial, one public. Plant genotype sensitivity to SSR was evaluated by the cut stem inoculation method, and lesion lengths were measured at 4 days post inoculation. RESULTS: Genotyping-by-sequencing was conducted to genotype the 420 soybean lines. The TASSEL 5 GBSv2 pipeline was used to call SNPs under optimized parameters, and with the extra step of trimming adapter sequences. After filtering missing data, heterozygosity, and minor allele frequency, a total of 11,811 SNPs and 275 soybean genotypes were obtained for association analyses. Using a threshold of FDR-adjusted p-values <0.1, the Compressed Mixed Linear Model (CMLM) with Genome Association and Prediction Integrated Tool (GAPIT), and the Fixed and Random Model Circulating Probability Unification (FarmCPU) methods, both approaches identified SNPs with significant association to disease response on chromosomes 1, 11, and 18. The CMLM also found significance on chromosome 19, whereas FarmCPU also identified significance on chromosomes 4, 9, and 16. CONCLUSIONS: These similar and yet different results show that the computational methods used can impact SNP associations in soybean, a plant with a high degree of linkage disequilibrium, and in SSR resistance, a trait that has a complex genetic basis. A total of 125 genes were located within linkage disequilibrium of the three loci shared between the two models. Their annotations and gene expressions in previous studies of soybean infected with S. sclerotiorum were examined to narrow down the candidates.