No abstract

The monitoring of development of Botrytis cinerea under reduction of pesticide treatments in Macedonian viticulture production is possible only when introducing a disease forecasting model. B.cinerea causes an increase in the number of chemical treatments just before harvest and calls into question the environmental and health value of the product. Therefore, an attempt was made to create a forecasting model for Botrytis which is based on the relationship between relative humidity and the temperature in the vine canopy. The forecasting model for Botrytis was applied at the white varieties Smederevka and Zilavka and based on the data obtained was made ANOVA statistical test which proves the reliability of the model. On the localities, Smilica and Sopot, Kavadarci, Republic of Macedonia, are the experimental fields that were observed for three consecutive years (2017 till 2019).

Impact of disease severity on infected bunches upon a yield of grape variety Vanec, caused by Plasmopara viticola (Berk. & M.A. Curtis) Berl. & De Toni., every year causes damage to the yield of vines by infection the bunches while they are still unripe. It is essential to assess the severity of Downy Mildew in vineyards to predict yield loss accurately. The software platform 'image J' was used to detect and quantify the disease severity by measuring infected berries relative to healthy tissue. Regression analysis was used as a statistical method to predict yield loss. Plasmopara viticola was monitored in 2022 to find a rational solution to build a Yield Loss Forecast Model. The results of theoretical assumptions compared with actual field situations show that Yield Loss Forecasting Model within the allowed statistical range approximately predicts the yield loss of the control variant.