Onion (Allium cepa L.) is grown worldwide for its fleshy bulbs which are used as food and medicinal purposes. In Egypt, onion is the 2nd major export crop after cotton. Downy mildew of onion, caused by Peronospora destructor (Berk.)Casp. is considered one of the most destructive disease of onion and has a wide geographical distribution includes Egypt. P. destructor is a polycyclic pathogen: many infection cycles can follow one another during an onion-growing season. When weather conditions are favourable, the fungus can complete its cycle in a short time and the disease can cause severe yield losses and affect negatively the Egyptian national income. Therefore disease management relies on routine applications of both protectant and eradicant fungicides (4-6 sprays) throughout the season but maintaining control in the life of the crop and timing applications effectively is difficult. In addition, reducing fungicide applications on onions is extremely desirable for the environment and consumer. A computerized forecasting model for onion downy mildew named by the author (ODM-Cast) was developed and field validated during 2006/2007 and 2007/2008 onion growing seasons in a disease hot spot cultivation site with a susceptible cultivar(Giza 20) and downy mildew disease severity was confirmed by the visual presence of leaves typical symptoms on onion plants in untreated plots. An advanced wireless telemetry Agro-weather station (Adcon A733 AddWave) which established within the crop canopy was used for monitoring the weather microelements such as: air temperature, relative humidity, leaf wetness, precipitation, global radiation and wind speed 24 hour a day. The results showed that ODM-Cast forecast model successfully indicated the disease daily infection potential and reduced the number of sprays in both years compared with the time table fundamental sprays in both 2006/2007 and 2007/2008, respectively. The basic roles of system analysis for model development and validation are discussed in details .

Tomato (Lycopersicon esculentum Mill.) is considered one of the main vegetable cash crop for both local consumption and exportation in Egypt. The most important disease infect tomato plants is early blight caused by Alternaria solani which also attacks several nightshade crops including potato and eggplant. Under favourable weather conditions the disease cycle takes about one week.This rapid reproduction cycle can expand the disease so rapidly and completely defoliate tomato plants causing a severe losses in yield. Therefore, a 7-10 day spray schedule with protecting fungicides is a traditional and effective system to control tomato early blight. Consumer concern about agro-chemical residues is strong in Egypt, and particularly relevant for fresh consumed products, including tomato. This consumer concern for food safety and the environment has lead to certified schemes for good agricultural practices such as disease forecast. A computerized forecast model named by the authors (TEB-Cast) is an integral linking based on short term observations over several tomato growing seasons , analyzing the correlation between 24 hour microclimate data collected throughout real time automatic Agroweather station (Adcon Telemetry A733 AddWave) , was evaluated and validated under both computer lab. (workstation) and open field in 2005 and 2006 growing seasons .The results indicated that TEB-Cast forecast model correctly timed the first spray and the disease daily infection potential and significantly reduced the number of sprays compared with the routine schedule fungicide applications in both 2005 and 2006 growing seasons respectively. The basic roles of system analysis for model evaluation and validation are discussed in details.