Development of a warning system for wheat blast caused by Pyricularia grisea

Wheat (Triticum aestivum L.) blast caused by Pyricularia grisea is a new disease in Brazil and no resistant cultivars are available. The interactions between temperature and wetness durations have been used in many early warning systems. Hence, growth chamber experiments to assess the effect of different temperatures (10, 15, 20, 25, 30 and 35ºC) and the duration of spike-wetness (0, 5, 10, 15, 20, 25, 30, 35 and 40 hours) on the intensity of blast in cultivar BR23 were carried out. Each temperature formed an experiment and the duration of wetness the treatments. The highest blast intensity was observed at 30°C and increased as the duration of the wetting period increased while the lowest occurred at 25°C and 10 hours of spike wetness. Regardless of the temperature, no symptoms occurred when the wetting period was less than 10 hours but at 25°C and a 40 h wetting period blast intensity exceeded 85%. These variations in blast intensity as a function of temperature are explained by a generalized beta model and as a function of the duration of spike wetness by the Gompertz model. Disease intensity was modeled as a function of both temperature and the durations of spike wetness and the resulting equation provided a precise description of the response of P. grisea to temperatures and the durations of spike wetness. This model was used to construct tables that can be used to predict the intensity of P. grisea wheat blast based on the temperatures and the durations of wheat spike wetness obtained in the field.

Weather based warning systems for bean angular-leaf-spot and anthracnose

Data available in the literature were used to develop a warning system for bean angular leaf spot and anthracnose, caused by Phaeoisariopsis griseola and Colletotrichum lindemuthianum, respectively. The model is based on favorable environmental conditions for the infectious process such as continuous leaf wetness duration and mean air temperature during this subphase of the pathogen-host relationship cycle. Equations published by DALLA PRIA (1977) showing the interactions of those two factors on the disease severity were used. Excell spreadsheet was used to calculate the leaf wetness period needed to cause different infection probabilities at different temperature ranges. These data were employed to elaborate critical period tables used to program a computerized electronic device that records leaf wetness duration and mean temperature and automatically shows the daily disease severity value (DDSV) for each disease. The model should be validated in field experiments under natural infection for which the daily disease severity sum (DDSS) should be identified as a criterion to indicate the beginning and the interval of fungicide applications to control both diseases.

Weather requirements and rain forecast to time fungicide application for Fusarium head blight control in wheat

The aim of this study was to determine the minimum conditions of wetness duration and mean temperature required for Fusarium head blight infection in wheat. The weather model developed by Zoldan (2008) was tested in field experiments for two wheat cultivars grown in 2005 (five sowing dates) and 2006 (six sowing dates) in 10 m² plots with three replicates. The disease was assessed according to head incidence (HI), spikelet incidence (SI), and the interaction between these two methods was called head blight severity (HBS). Starting at the beginning of anthesis, air temperature and head wetness duration were daily recorded with an automatic weather station. With the combination of these two factors, a weather favorability table was built for the disease occurrence. Starting on the day of flowering beginning (1 - 5% fully exserted anthers), the sum of daily values for infection favorability (SDVIF) was calculated by means of a computer program, according to Zoldan (2008) table. The initial symptoms of the disease were observed at 3.7% spikelet incidence, corresponding to 2.6 SVDFI. The infection occurs in wheat due to rainfall which results in spike wetting of > 61.4 h duration. Rainfall events forecast can help time fungicide application to control FHB. The name of this alert system is proposed as UPF-scab alert.

Influence of temperature and leaf wetness duration in the severity of Cercospora leaf spot of beet

ABSTRACT In the present study, the influence of temperature (15, 20, 25, 30 and 35°C) and leaf wetness period (6, 12, 24 and 48 hours) on the severity of Cercospora leaf spot of beet, caused by Cercospora beticola, was studied under controlled conditions. Lesion density was influenced by temperature and leaf wetness duration (P<0.05). Data were subjected to nonlinear regression analysis. The generalized beta function was used for fitting the disease severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Cercospora leaf spot. The response surface resultant of the product of the two functions was expressed as ES = 0.0001105 * (((x-8)2.294387) * ((36-x)0.955017)) * (0.39219/(1+25.93072 * exp (-0.16704*y))), where: ES represents the estimated severity value (0.1); x, the temperature (ºC) and y, the leaf wetness duration (hours). This model should be validated under field conditions to assess its use as a computational forecast system for Cercospora leaf spot of beet.

Development of a weather-based model for Botrytis leaf blight of onion

ABSTRACT In the present study, onion plants were tested under controlled conditions for the development of a climate model based on the influence of temperature (10, 15, 20 and 25°C) and leaf wetness duration (6, 12, 24 and 48 hours) on the severity of Botrytis leaf blight of onion caused by Botrytis squamosa. The relative lesion density was influenced by temperature and leaf wetness duration (P <0.05). The disease was most severe at 20°C. Data were subjected to nonlinear regression analysis. Beta generalized function was used to adjust severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Botrytis leaf blight. The response surface obtained by the product of two functions was expressed as ES = 0.008192 * (((x-5)1.01089) * ((30-x)1.19052)) * (0.33859/(1+3.77989 * exp (-0.10923*y))), where ES represents the estimated severity value (0.1); x, the temperature (°C); and y, the leaf wetness (in hours). This climate model should be validated under field conditions to verify its use as a computational system for the forecasting of Botrytis leaf blight in onion.

Effects of global climate changes on geographical distribution patterns of economically important plant species in cerrado

Different climate models, modeling methods and carbon emission scenarios were used in this paper to evaluate the effects of future climate changes on geographical distribution of species of economic and cultural importance across the Cerrado biome. As the results of several studies have shown, there are still many uncertainties associated with these projections, although bioclimatic models are still widely used and effective method to evaluate the consequences for biodiversity of these climate changes. In this article, it was found that 90% of these uncertainties are related to methods of modeling, although, regardless of the uncertainties, the results revealed that the studied species will reduce about 78% of their geographic distribution in Cerrado. For an effective work on the conservation of these species, many studies still need to be carried out, although it is already possible to observe that climate change will have a strong influence on the pattern of distribution of these species.

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Harrod sob análise: path-dependence, tempo histórico e mudança estrutural endógena

Harrod under analysis: path-dependence, historic time and endogenous structural change. The article aims to demonstrate how the Harrod's approach (1937, 1938, 1948) can offer theoretical elements to form a complex, historicists and non-determinist view of the economic system. The relaxation of the constant warranty rate hypothesis make possible the system suffers endogenous qualitative change. It results in the notion of path-dependence and historic time. By the endogenization of the expectations and the existence of turn-points mechanisms, this approach allows a synthesis between non-convergency and economic regulation.