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SENSITIVITY EVALUATION OF 1,8-CINEOLE AGAINST Pseudocercospora fijiensis CAUSING BLACK SIGATOKA LEAF SPOT OF CAVENDISH BANANA

Authors: Carizza Alagano; Suarez, Geneva; Navasca, Abbeah Mae; Corcolon, Benny; Faustino, Mary Ann; Batac, Rene; Searle, Martin;

SENSITIVITY EVALUATION OF 1,8-CINEOLE AGAINST Pseudocercospora fijiensis CAUSING BLACK SIGATOKA LEAF SPOT OF CAVENDISH BANANA

Abstract

Black Sigatoka remains to be the most costly disease of banana accounting to about 35% of the production cost. Management of the disease entails application of registered fungicides following an efficient and effective spray program in order to manage the risk of resistance. A wide selection of fungicides is very ideal, however, through the years, only few products are being positioned for Black Sigatoka management thus increasing the chance of Pseudocersopora fijiensis to develop resistance. In these situations, inclusion of resistance-breakers in the spray program becomes imperative in banana plantations. 1,8- cineole is known to degrade cell walls of fungi causing their lysis and death. With the aim to add novel products in the spray program, efficacy of 1,8-cineole against P. fijiensis was determined in vitro following the method set by Fungicide Resistance Action Committee (FRAC

Keywords

Black Sigatoka, Pseudocercospora fijiensis, Cavendish Banana

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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