Data di Pubblicazione:
2000
Citazione:
Estimating germination of Plasmopara viticola oospores by means of neural networks / A. Vercesi, C. Sirtori, A. Vavassori, E. Setti, D. Liberati. - In: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING. - ISSN 0140-0118. - 38:1(2000), pp. 109-112. [10.1007/BF02344698]
Abstract:
Neural networks are trained to estimate the germination percentages of
Plasmopara viticola oospores, overwintered in natural conditions in two viticultural
areas in northern Italy, by using climatic (temperature and rainfall) data, as well as
the previous germination measurement, as input variables. The 288 available
patterns consist of a set of selected independent variables associated with the
corresponding germination percentage. All 12 networks investigated converge to a
non-linear relationship between the selected independent variables and oospore
germination. The highest correlation coefficient (equal to 0.83) between the real
and estimated germination percentages is obtained by considering, as input to the
network, the climatic data (both temperature and rainfall) recorded during the 40
days before sampling and the germination percentage assessed in the germination
assay carried out immediately before the present sampling.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Neural networks; Oospore germinability forecasting; Plasmopara viticola
Elenco autori:
A. Vercesi, C. Sirtori, A. Vavassori, E. Setti, D. Liberati
Link alla scheda completa: