Co-Authors:
Cochavi, A., Department of Phytopathology and Weed Research, Newe Ya’ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel, R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agricultural, Food and Environmental Sciences, The Hebrew University of Jerusalem, Rehovot, Israel
Rubin, B., R. H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agricultural, Food and Environmental Sciences, The Hebrew University of Jerusalem, Rehovot, Israel
Achdari, G., Department of Phytopathology and Weed Research, Newe Ya’ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
Eizenberg, H., Department of Phytopathology and Weed Research, Newe Ya’ar Research Center, Agricultural Research Organization, Ramat Yishay, Israel
Abstract:
Carrot, a highly profitable crop in Israel, is severely damaged by Phelipanche aegyptiaca parasitism. Herbicides can effectively control the parasite and prevent damage, but for optimal results, knowledge about the soil–subsurface phenological stage of the parasite is essential. Parasitism dynamics models have been successfully developed for the parasites P. aegyptiaca, Orobanche cumana, and Orobanche minor in the summer crops, tomato, sunflower, and red clover, respectively. However, these models, which are based on a linear relationship between thermal time and the parasitism dynamics, may not necessarily be directly applicable to the P. aegyptiaca–carrot system. The objective of the current study was to develop a thermal time model to predict the effect of P. aegyptiaca parasitism dynamics on carrot growth. For development and validation of the models, data was collected from a temperature-controlled growth experiment and from 13 plots naturally infested with P. aegyptiaca in commercial carrot fields. Our results revealed that P. aegyptiaca development is related to soil temperature. Moreover, unlike P. aegyptiaca parasitism in sunflower and tomato, which could be predicted both a linear model, P. aegyptiaca parasitism dynamics on carrot roots required a nonlinear model, due to the wider range of growth temperatures of both the carrot and the parasite. Hence, two different nonlinear models were developed for optimizing the prediction of P. aegyptiaca parasitism dynamics. Both models, a beta function model and combined model composed of a beta function and a sigmoid curve, were able to predict first P. aegyptiaca attachment. However, overall P. aegyptiaca dynamics was described more accurately by the combined model (RMSE = 14.58 and 10.79, respectively). The results of this study will complement previous studies on P. aegyptiaca management by herbicides to facilitate optimal carrot growth and handling in fields infested with P. aegyptiaca. © 2016 Cochavi, Rubin, Achdari and Eizenberg.
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