A statistical test is described to verify the characteristics of the biological information contained in the dynamics of the flowering process. The test focuses on interactions between the pollen index and climatic variables to investigate if the biological indicator can synthesise the information of the preflowering phases. The multiple-regression model is built upon two pre-flowering climate macro-indicators extracted by Principal Component Analysis (PCA) and the optimised pollen index is obtained by non-parametric estimation. The empirical analysis is applied to 15 stations located in southern Italy in regions that have a longstanding tradition of olive production. Using the variance explained, we find that an optimised pollen index is fairly well predicted by the pre-flowering climatic data. We conclude that the optimised pollen index makes more parsimonious the modelling for predicting olive production.
Instrumental test to estimate a model of forecast yield: a non-parametric application to the pollen index in South Italy
ORLANDI, Fabio;LANARI, Donatella;PIERONI, Luca;ROMANO, Bruno;FORNACIARI DA PASSANO, Marco
2004
Abstract
A statistical test is described to verify the characteristics of the biological information contained in the dynamics of the flowering process. The test focuses on interactions between the pollen index and climatic variables to investigate if the biological indicator can synthesise the information of the preflowering phases. The multiple-regression model is built upon two pre-flowering climate macro-indicators extracted by Principal Component Analysis (PCA) and the optimised pollen index is obtained by non-parametric estimation. The empirical analysis is applied to 15 stations located in southern Italy in regions that have a longstanding tradition of olive production. Using the variance explained, we find that an optimised pollen index is fairly well predicted by the pre-flowering climatic data. We conclude that the optimised pollen index makes more parsimonious the modelling for predicting olive production.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
