Logistic models for estimating epidemic increase rates of blueberry foliar diseases, based on meteorological and leaf senescence variables

Alternaria tenuissima is one of the most important pathogens on blueberry (Vaccinium corymbossum) in Argentina, causing leaf spots, twig blight and fruit rot. The severity of leaf spots caused by A. tenuissima was estimated in crops located in San Pedro, Gualeguaychú and Concordia (Argentina), during spring and summer of 2008 and 2009. Each linearised disease progress curve (3-4 observations per crop cycle) adjusted to Logistic and Gompertz epidemiological models (R2 greather than 0.77 to 0.98) for Concordia and San Pedro. Every 14 days, epidemic daily increase rate (DI) was estimated from disease epidemic curves. DI values were binary categorized according to median values (DI=0.04253) for the 36 severity percentages estimated every 14 days, into severe (DI greather or equal than 0.04253), and slight to null (DI less than 0.04253). Also, DI values were ordinally categorized into severe (DI greather or equal than 0.0962 (80 percent percentile), moderate: DI less than 0.0962 and greather or equal than 0.04253) and slight to null (DI less than 0.04253). We tried to explain the variability in DI levels by means of meteorological variables and a factor related to the degree of leaf senescence (LS), processed during the 14-day period prior to each estimated increase value within each disease progress curve. Simple weather variables, such as the number of days with minimum temperature less than 17°C (dMT) and mean minimum temperature (MMT), and the interaction MMTxRF (rain frequency) enhanced the highest Kendall correlation coefficients with LS factor (rK greather than 0.55). The best logistic regression model of binary response, that integrated LS, RF and the interaction MMTxRF, showed a prediction accuracy of 97 percent. Among ordinal response models, the bivariate one that integrated LS factor and the interaction MMTxRF was chosen (92 percent prediction accuracy). These results add information for the development of a predictive system for blueberry leaf diseases, in a context of sustainable crop health management.

Bibliographic Details

Main Authors:	Moschini, Ricardo, Wright, Eduardo Roberto, Bombelli, Enrique Carlos, López, María Virginia, Canavesi, Guillermo Luis, Pagano, M., Eizaguirre, Leandro, Barberis, Guillermo, Fabrizio, María del Carmen, Rivera, Marta Carolina
Format:	Texto biblioteca
Language:	eng
Subjects:	ALTERNARIA TENUISSIMA, ARGENTINA, VACCINIUM CORYMBOSSUM, ALTERNARIA, VACCINIUM, ,
Online Access:	http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46522 http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber= http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=
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