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.

Meta-analytic models were used to summarize and assess the heterogeneity in the relationship between soybean yield (Y, kg/ha) and rust severity (S, %) data from uniform fungicide trials (study, k) conducted over nine growing seasons in Brazil. For each selected study, correlation (k=231) and regression (k=210) analysis for the Y-S relationship were conducted and three effect-sizes were obtained from these analysis: Fisher's transformation of the Pearson's correlation coefficient (Zr) and the intercept (β0) and slope (β1) coefficients. These effect-sizes were summarized through random-effect and mixed-effect models, with the latter incorporating study-specific categorical moderators such as disease onset time (DOT) (70%, moderate=>40 and ≤70%, and low=≤40% S the check treatment), and growing season. The overall mean for r- (back-transformed Z-r) was -0.61, based on the random-effects model. DOT and DP explained 14 and 25%, respectively, of the variability in Z-r. Stronger associations (r-=-0.87 and -0.90) were estimated by mixed-effects models for the Zr data from studies with highest DP (DP>70%) and earliest rust onset (DOT0.73 pp/%(-1)) were estimated for studies with DOT70%; the latter possibly due to high fungicide efficacy when DP is low, thus leading to higher yield differences between fungicide-protected and nontreated plots. The critical-point meta-analytic models can provide general estimates of yield loss based on a composite measure of disease severity. They can also be useful for crop loss assessments and economic analysis under scenarios of varying DOT and weather favorableness for epidemic development.

O objetivo do trabalho foi avaliar o efeito de quatro tratamentos de sementes: água (T1), carbendazim + thiram (T2), fipronil + tiofanato metílico + piraclostrobina (T3) e abamectina + thiamethoxam + fludioxonil + mefenoxan + thiabendazole (T4) sobre parâmetros de crescimento de plantas de soja submetidas a dois regimes hídricos (presença e ausência de estresse hídrico) estabelecidos logo após a emergência das plântulas. O experimento foi conduzido em casa de vegetação e campo. Na casa de vegetação, nos tratamentos sem estresse hídrico, foram feitas quatro irrigações por dia e, nos tratamentos com estresse hídrico, foi realizada uma irrigação a cada três dias. Neste ensaio, foi avaliada a estatura de plantas, comprimento radicular, volume radicular, massa seca da parte aérea, massa seca radicular e área foliar. No ensaio de campo, o estresse hídrico foi estabelecido pela construção de túneis baixos de polietileno que impediram o fornecimento de água pela irrigação e chuva. No campo, foram avaliados estatura de planta, teor relativo de clorofila, emergência, ataque de lagarta-elasmo e rendimento de grãos. Nos dois ambientes, as plantas foram mantidas sob estresse até 28 dias após a emergência. Em casa de vegetação, todos os parâmetros foram influenciados pelo tratamento de sementes na presença e ausência de estresse hídrico. No campo, o tratamento com fipronil + tiofanato metílico + piraclostrobina (T3) e abamectina + thiamethoxam + fludioxonil + mefenoxan + thiabendazole (T4) proporcionaram maior estatura de planta e teor relativo de clorofila em ambos os regimes hídricos e maior emergência e rendimento de grãos em plantas sem e com restrição hídrica, respectivamente. Conclui-se que o tratamento de sementes com esses produtos promove alterações benéficas nas plantas, aumentando sua tolerância ao estresse hídrico, com efeito positivo sobre o rendimento de grãos da soja.

Tar spot of corn has been a major foliar disease in several Latin American countries since 1904. In 2015, tar spot was first documented in the United States and has led to significant yield losses of approximately 4.5 million t. Tar spot is caused by an obligate pathogen, Phyllachora maydis, and thus requires a living host to grow and reproduce. Due to its obligate nature, biological and epidemiological studies are limited and impact of disease in corn production has been understudied. Here we present the current literature and gaps in knowledge of tar spot of corn in the Americas, its etiology, distribution, impact and known management strategies as a resource for understanding the pathosystem. This will in tern guide current and future research and aid in the development of effective management strategies for this disease.

Field trials were conducted in 17 U.S. states to evaluate the effects of quinone outside inhibitor (QoI) and demethylation inhibitor (DMI) fungicide programs on Fusarium head blight index (IND) and deoxynivalenol (DON) toxin in wheat. Four DMI-only treatments applied at Feekes 10.5.1, five QoI-only treatments applied between Feekes 9 or Feekes 10.5, three QoI+DMI mixtures applied at Feekes 10.5, and three treatments consisting of a QoI at Feekes 9 followed by a DMI at Feekes 10.5.1 were evaluated. Network meta-analytical models were fitted to log-transformed mean IND and DON data and estimated contrasts of log means were used to obtain estimates of mean percent controls relative to the nontreated check as measures of efficacy. Results from the meta-analyses were also used to assess the risk of DON increase in future trials. DMI at Feekes 10.5.1 were the most effective programs against IND and DON and the least likely to increase DON in future trials. QoI-only programs increased mean DON over the nontreated checks and were the most likely to do so in future trials, particularly when applied at Feekes 10.5. The effects of QoI+DMI combinations depended on the active ingredients and whether the two were applied as a mixture at heading or sequentially. Following a Feekes 9 QoI application with a Feekes 10.5.1 application of a DMI reduced the negative effect of the QoI on DON but was not sufficient to achieve the efficacy of the Feekes 10.5.1 DMI-only treatments. Our results suggest that one must be prudent when using QoI treatments under moderate to high risk of FHB, particularly where the QoI is used without an effective DMI applied in combination or in sequence.