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The GOLPE procedure for predicting olive crop production from climatic parameters
Author(s) -
Clementi Monica,
Clementi Sergio,
Fornaciari Marco,
Orlandi Fabio,
Romano Bruno
Publication year - 2001
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.670
Subject(s) - production (economics) , crop production , variable (mathematics) , selection (genetic algorithm) , crop , agricultural engineering , mathematics , environmental science , computer science , agronomy , engineering , machine learning , biology , agriculture , ecology , economics , mathematical analysis , macroeconomics
This paper reviews the philosophy of the GOLPE procedure, explaining the reasons for the validation criterion and variable selection method used and comparing GOLPE with other regression and variable selection methods. Its application to olive production, for a training set of 16 years, allows one to improve the uncertainty of prediction of the yearly crop production from temperature, rain, heliophany, humidity and wind from 30% to 14% and to indicate the climatic parameters affecting crop production. Copyright © 2001 John Wiley & Sons, Ltd.