Evolution of a Weather-Based Peanut Leaf Spot Spray Advisory in North Carolina

Bailey, Jack E.; Johnson, G. L.; Tóth, Štefan

doi:10.1094/pd-78-0530

Cited by 17 publications

(19 citation statements)

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“…Knowing the economics of fungicide application and the negative impact of fungicides on the environment, many scientists have tried to find ways to reduce fungicide use. Several methods have been used to time fungicide applications; e.g., increasing the interval between sprays by a fixed number of days (every 15 or 21 days), fungicide application according to plant development stage, and use of advisory systems (2,(4)(5)(6)9,13,17,20,23).…”

Section: Discussionmentioning

confidence: 99%

“…The most effective viable system is use of a weather-based advisory developed in the United States to help farmers time fungicide applications (2,10,14). Proper timing of fungicide application reduces the number of applications.…”

Section: Discussionmentioning

confidence: 99%

“…However, a limited number of fungicide applications could substantially increase pod yield. To reduce the number of fungicide applications, approaches such as disease prediction models for alerting farmers to spray have been developed (2). Our objectives were to identify the best combination of timing and number of fungicide applications in relation to cultivars to achieve best pod yield.…”

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confidence: 99%

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Rational Use of Fungicide Applications to Maximize Peanut Yield Under Foliar Disease Pressure in West Africa

2000

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Waliyar, F., Adamou, M., and Traoré, A. 2000. Rational use of fungicide applications to maximize peanut yield under foliar disease pressure in West Africa. Plant Dis. 84:1203-1211.Foliar diseases caused by Cercospora arachidicola, Cercosporium personatum, and Puccinia arachidis are major constraints to peanut production in the world. Fungicides are among the most efficient available control methods. Field trials were conducted in 1991 and 1992 in Benin and Niger, West Africa, to evaluate the cost effectiveness of fungicide application timings and frequencies on four peanut cultivars. A combination of four timings (40, 55, 70, and 85 days after sowing) was scheduled. Early (causal organism, C. arachidicola) and late (caused by C. personatum) leaf spot were prevalent in both years, but late leaf spot was the more economically important disease as shown by high values of area under the disease progress curve. Application of fungicide reduced late leaf spot incidence and increased pod yield. Pod yield responded to an interaction of number and timing of fungicide applications. With appropriate timing two or three fungicide applications were enough to significantly increase pod yield. Properly timed fungicide sprays can result in substantial monetary gains for peanut farmers in West Africa.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Rational Use of Fungicide Applications to Maximize Peanut Yield Under Foliar Disease Pressure in West Africa

2000

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“…A simplifiedversion of the PSC advisory was used in this study because of its history of success in North Carolina and daily advisories could be calculated quickly without the aid of a computer (4). Briefly, daily infection indices from 0 to 3, where O=upfavorable and 3=very favorable, were obtained from the PSC nomogram using the period of RH ~9 5 % and the minimum T during the period as input variables.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of a Weather-Based Spray Advisory for Management of Early Leaf Spot of Peanut in Oklahoma1

et al. 1994

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A simplified version of the weather-based advisory program developed by Pawin, Smith, and Crosby (PSC) for scheduling fungicide sprays for management of early l e d spot (Cercospora arachidicoh Hori) of peanut (Arachis hypogea L.) was evaluated under various productions systems in Oklahoma from 1990-1992. Over eight trials with spanish cultivars, the number of sprays per season averaged 5.7 for the 14-d schedule and 4.0 for the advisory program. Final disease incidence (symptomatic and defoliated leaflets) with the fungicide chlorothalonil (1.26 k@a) averaged 15% for the 14-d schedule, 34% for the advisoryprogram, and 77% for the control. However, disease incidence (75%) and defoliation (!jO%) approached unacceptable levels on the Spanish cultivars in some trials. In six trials with runner cultivars, the number of sprays averaged 6.7 for the 14-d schedule and 4.7 for the advisory program. Final disease incidence with chlorothalonil on the runner cultivars averaged 5% for the 14-d schedule, 14% for the advisory program, and 68% in the control. Yields did not differ in any of the 14 trials between the advisory and 14-d programs using chlorothalonil. Yields averaged 3015,3003, and2303 kg/ha for Spanish cultivars and 4108, 3855, and 3066 kg/ha for runner cultivars with the 14-d schedule, advisory program, and control, respectively. The advisory program was effective in irrigated trials where weather stations were deployed either under or outside the influence of irrigation. The fungicides tebuconazole at 0.14 k@a and propiconazole at 0.13 kg/ ha generally provided better leaf spot control with the advisory program than chlorothalonil. The post-infection activity of these fungicides was observed in one trial and probably accounts for their improved performance. Yields were reduced and leafspot incidence was high where tank mixes of benomyl(O.28 kg/ha) or thiophanatemethyl (0.38 k@a) plus mancozeb (1.68 kg/ha) were used with the advisory program. Area under the disease progress curve, leaf spot incidence, and defoliation in the controls were lower for runner than for Spanish cultivars at sites where both market types were planted in adjacent trials. Fungicides applied according to the advisory program provided better leaf spot control on the runner cultivars. Results showed the need for a weather-based advisory which allows greater levels of leafspot control on Spanish cultivars than the PSC advisory.'Approved for publication by the Director, Oklahoma Agric. Exp. Stn. This study was funded in part by Hatch project

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“…Weather variables including temperature, rainfall, and relative humidity, have been tested and reported on extensively in many disease studies (Bailey et al, 1994;Nokes and Young, 1991;Wharton et al, 2008;Olatinwo et al, 2008Olatinwo et al, , 2009Olatinwo et al, , 2010. In some studies, individual computer programs have been developed based on various weather parameters to make predictions, while others studies have incorporated computer programs into commercial advisory equipment (Cu and Phipps, 1993;Grichar et al, 2005;Boyle, 1965, 1966;Linvill and Drye, 1995;Parvin et al, 1974;Shew et al, 1988;Wu et al, 1999).…”

Section: Weather Factors and Derived Variablesmentioning

confidence: 99%