Previsão da ocorrência de requeima e alternaria em tomateiro industrial irrigado sob duas condições climáticas e seu custo

• Autor(a) principal: Grimm, Edenir Luis
• Data de Publicação: 2010
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/3580
• topic: Lycopersicon esculentum; Alternaria solani; Phytophthora infestans; Sistemas de previsão; Redução de aplicação; Lycopersicon esculentum; Alternaria solani; Phytophthora infestans; Forecasting systems; Reduction of application; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA

The tomato (Lycopersicon esculentum Mill) is an important crop in the world and an important product for trade "in nature and for industry. The amount of fungicides used in tomato crop for control of diseases is high and contributes significantly to production costs of tomato, besides the high risk of intoxication of the applicator and environmental problems. So, the use of disease forecasting systems based on mathematical models to manage the applications of fungicides for foliar diseases control in tomato may to reduce production costs, by decreasing the number of fungicide applications and machinery operation during the culture cycle. The objective was to test the systems for predicting occurrence of late blight (Phytophthora infestans) and early blight (Alternaria solani) on irrigated tomato under two climatic conditions and estimate the cost of deployment. Three experiments were conducted, the first experiment in the spring of 2007, in Santa Maria - RS. The other two were accomplished in Cristalina - GO. There were two seasons of transplanting (01/04/08 and 03/05/08). Used the hybrid U2006 (UNILEVER), with growth habit determined. The spacing between the rows of plants was 1.3 m between plants in rows of 0,3 m. The randomized block design with three replications was used, each plot of 5,2 m wide, consisting of 4 rows of plants with 5 m long. The systems for predicting disease FAST, to early blight, and Blitecast to late blight were used. Irrigation was performed by spraying in Santa Maria and sprinkler, surface drip and subsurface in Cristalina-GO. The results showed that the use of disease forecasting systems is the most appropriate way to control diseases in tomato, as with the use of disease forecasting systems that can significantly reduce the number of fungicide applications in relation the calendar, based on weekly applications in areas with conditions generally unfavorable to the development of disease. Considering the scenarios of reductions of the number of fungicide applications (30, 43 and 65%), compared to the weekly application, in climatic conditions unfavorable to disease development, it is possible to recover the costs of implementing the system prediction in all scenarios.