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A generalized phenological model for durum wheat: application to the Italian peninsula.

Authors :
Di Paola, Arianna
Ventura, Francesca
Vignudelli, Marco
Bombelli, Antonio
Severini, Maurizio
Source :
Journal of the Science of Food & Agriculture; 8/30/2020, Vol. 100 Issue 11, p4093-4100, 8p
Publication Year :
2020

Abstract

BACKGROUND: A likely increasing demand for varieties mixtures, landraces and genetic diversity in cropping systems will underpin calls for models able to generalize phenological development at the species level, at the same time as providing the expected range of phenological variability. In the present article, we aimed to obtain a generalized phenological model of durum wheat (Triticum durum, Desf.). RESULTS: Using a large phenological dataset embracing field data collected under different sowing dates, varieties and locations over the Italian peninsula, we searched for the phenophases enabling the best linear approximations between developmental rates and air temperature, aiming to minimize the residual variability from drivers other than temperature, as genetic and environmental diversity. The developmental rates of the resulting phases were then examined with respect to the mean daylength to determine possible additional relations with photoperiod. If a correlation with daylength was also present, the developmental rate is calibrated by multiple linear regression, or otherwise by simple linear regression of temperature. The resulting calibration, tested on an independent data subset, confirms that the model is able to generalize wheat development over the Italian peninsula with high accuracy (mean absolute error =3–8 days; r2 = 0.75–0.98), regardless of the wheat variety. CONCLUSION: The generalized phenological model is potentially suitable for many agro‐ecological and large‐scale applications. It is hoped that the model will aid in situations where phenological observations to parameterize a model are still lacking, as is probably the case for landraces and underutilized crop varieties. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00225142
Volume :
100
Issue :
11
Database :
Complementary Index
Journal :
Journal of the Science of Food & Agriculture
Publication Type :
Academic Journal
Accession number :
144455433
Full Text :
https://doi.org/10.1002/jsfa.9864