Newly established bermudagrass response to topramezone and photosystem II-inhibitor herbicides Raphael M. Negrisoli, D. Calvin Odero Weed Technology, 2024 Bermudagrass is the most troublesome and difficult-to-control perennial grass weed in Florida sugarcane. Once established, it may be effectively controlled only during the sugarcane fallow period using a combination of nonselective herbicides and tillage. Options for selective management of bermudagrass that escape sugarcane fallow period management programs must be evaluated to mitigate its progressive increase as the crop cycle increases from plant cane to ratoon crops. Greenhouse and field studies were conducted in Belle Glade, Florida, from 2017 to 2018, to determine the response of newly established bermudagrass from sprigs with stolons to two or three sequential applications of topramezone (25 and 50 g ha−1) every 14 d, and combinations of topramezone (25 and 50 g ha−1) with herbicides that inhibit photosystem II (PS II) such as atrazine (2,240 g ha−1), ametryn (440 g ha−1), and metribuzin (2,240 g ha−1). Two or three sequential applications of topramezone with a cumulative total of 75 to 100 g ha−1 provided >93% bermudagrass control 42 d after the first sequential application under greenhouse and field conditions. These treatments exhibited 12% chance of survival 70 d after the first sequential application. There was an additive effect of PS II-inhibitor herbicides on bermudagrass control in mixtures with topramezone. The mixture of topramezone (50 g ha−1) with metribuzin and atrazine provided more than 87% and 92% bermudagrass control under greenhouse and field conditions, respectively, 42 d after treatment. Bermudagrass treated with topramezone (50 g ha−1) in a mixture with metribuzin exhibited 23% chance of survival 70 d after treatment. The results show good efficacy of sequential topramezone applications every 14 d or in a mixture with the PS II-inhibitor herbicides atrazine and metribuzin for control of newly established bermudagrass that typically escape control measures during the sugarcane fallow management period.
Effect of dew and spray volume on the efficacy of control of asulam on fall panicum (Panicum dichotomiflorum) Alex G. Rodriguez, D. Calvin Odero, Raphael M. Negrisoli Zuckerindustrie, 2023 Asulam controls fall panicum (Panicum dichotomiflorum Michx.), the most troublesome annual grass weed in Florida sugarcane. This study was conducted to evaluate the effect of dew on asulam efficacy on fall panicum control when applied using different spray volumes. Fall panicum 30 cm tall with 0, 50, and 100% dew on leaves equivalent to no dew, moderate dew, and heavy dew, respectively, were treated with asulam at 3,700 g ha–1 using spray volumes of 94, 140, 187, and 281 L ha–1. Fall panicum control was rated 28 days after treatment, and aboveground biomass was harvested immediately. The presence or absence of dew and spray volume did not significantly influence asulam efficacy on fall panicum control and aboveground biomass accumulation. Fall panicum was controlled from 89% to 94% at the different dew levels and spray volumes. Heavy dew did not diminish the performance of asulam. The presence of dew on fall panicum foliage probably hydrated the cuticle and aided water-soluble asulam to remain in solution for a longer period, thereby enhancing uptake. The water-holding capacity of fall panicum foliage with the heavy dew and spray volumes was probably not exceeded, resulting in no runoff and no subsequent reduction of control. These results indicate that dew deposition under Florida conditions has no effect on asulam efficacy on fall panicum 30 cm tall or less when applied at commonly used spray volumes of 140 and 187 L ha–1.
Soybean rust detection and disease severity classification by remote sensing Matheus Mereb Negrisoli, RaphaelMereb Negrisoli, FlavioNunes da Silva, Lucasda Silva Lopes, Franciscode Sales de Souza Júnior, Edivaldo Domingues Velini, Caio Antonio Carbonari, Sergio Augusto Rodrigues, Carlos Gilberto Raetano Agronomy Journal, 2022 The detection and monitoring of soybean rust (SBR) through remote sensing is promising because of the importance of the crop and the aspects of the disease. We evaluated the effects of different levels of SBR severity on soybean [Glycine max (L.) Merr.] leaflets reflectance aiming for the construction of a disease classification model. Leaflet reflectance was evaluated on two cultivars (susceptible and partially resistant) at four disease severity levels: healthy, low, moderate, and high. Leaflets were collected in the field and taken to the laboratory for spectral evaluation through the spectrophotometer UV 2700 coupled with Integrating Sphere Attachment ISR‐603, in the range of 270–1000 nm. The feasibility of using a collection of vegetation indices (VIs) and data dimensionality reduction through multiple factor analysis (MFA) was evaluated, and a classification model was constructed. Ten algorithms were assessed based on precision, sensibility, and accuracy parameters, using 80% of the dataset as training data and 20% as testing dataset. The visible range and red edge region contributed more significantly to the disease prediction and classification model. The MFA performed satisfactorily in the dimensionality reduction and unveiled the effect of specific wavelengths on the classification of each class. Most of the VIs studied had high correlation performance across the severity classes. Classification accuracy and precision were >70% for all models. Linear support vector machine with the collection of VIs achieved the best results. This study provides a practical path for developing a detection model to be integrated into SBR management programs.
Impact of Fungicide Application Timing Based on Soybean Rust Prediction Model on Application Technology and Disease Control Matheus Mereb Negrisoli, Flávio Nunes da Silva, Raphael Mereb Negrisoli, Lucas da Silva Lopes, Francisco de Sales Souza Júnior, Bianca Rezende de Freitas, Edivaldo Domingues Velini, Carlos Gilberto Raetano Agronomy, 2022 The application of remote sensing techniques and prediction models for soybean rust (SBR) monitoring may result in different fungicide application timings, control efficacy, and spraying performance. This study aimed to evaluate the applicability of a prediction model as a threshold for disease control decision-making and to identify the effect of different application timings on SBR control as well as on the spraying technology. There were two experimental trials that were conducted in a 2 × 4 factorial scheme: 2 cultivars (susceptible and partially resistant to SBR); and four application timings (conventional chemical control at a calendarized system basis; based on the prediction model; at the appearance of the first visible symptoms; and control without fungicide application). Spray deposit and coverage at each application timing were evaluated in the lower and upper region of the soybean canopy through quantitative analysis of a tracer and water-sensitive papers. The prediction model was calculated based on leaf reflectance data that were collected by remote sensing. Application timings impacted the application technology as well as control efficacy. Calendarized system applications were conducted earlier, promoting different spray performances. Spraying at moments when the leaf area index was higher obtained poorer distribution. None of the treatments were capable of achieving high spray penetration into the canopy. The partially resistant cultivar was effective in holding disease progress during the crop season, whereas all treatments with chemical control resulted in less disease impact. The use of the prediction model was effective and promising to be integrated into disease management programs.
Sugarcane response and fall panicum (Panicum dichotomiflorum) control with topramezone and triazine herbicides Raphael M. Negrisoli, D. Calvin Odero, Gregory E. MacDonald, Brent A. Sellers, H. Dail Laughinghouse Weed Technology, 2020 Field studies were conducted on organic soils in Belle Glade, FL, in 2016 to 2017 to evaluate sugarcane tolerance and fall panicum control with topramezone applied alone or in combination with triazine herbicides (atrazine, metribuzin, ametryn). Treatments included topramezone (25 and 50 g ai ha−1) applied alone or in combination with atrazine (2,240 g ai ha−1), metribuzin (2,240 g ai ha−1), and ametryn (440 g ha−1) on four plant cane varieties to evaluate tolerance, and on second ratoon fields to determine efficacy on fall panicum control. Topramezone applied alone had no effect on sugarcane chlorophyll fluorescence (i.e., the ratio of variable fluorescence to maximum fluorescence), total chlorophyll, and carotenoid 7 to 28 d after treatment (DAT), suggesting sugarcane tolerance. Significant reduction of these parameters occured 7 to 14 DAT when topramezone (50 g ai ha−1) was applied with ametryn or metribuzin; however, reductions were not detected thereafter, indicating recovery. Sugarcane yield was not affected by topramezone applied alone or in combination with the triazine herbicides. Topramezone (50 g ai ha−1) plus metribuzin resulted in acceptable control of fall panicum (84%) with limited to no regrowth of meristematic tissue at sugarcane canopy closure, equivalent to 56 to 70 DAT. These results indicate that when sequential applications of topramezone, applied alone or in combination with these triazine herbicides, are required for efficacious weed control, topramezone applications alone can be made after 7 d, whereas the combinations can be made after 14 or 21 d, depending on sugarcane sensitivity.
