Boundaries and perspectives from a multi-model study on rice grain quality in Northern Italy
Articolo
Data di Pubblicazione:
2018
Citazione:
Boundaries and perspectives from a multi-model study on rice grain quality in Northern Italy / G. Cappelli, R. Confalonieri, M. Romani, S. Feccia, M.A. Pagani, C. Cappa, S. Bocchi, S. Bregaglio. - In: FIELD CROPS RESEARCH. - ISSN 0378-4290. - 215(2018 Jan), pp. 140-148. [10.1016/j.fcr.2017.10.014]
Abstract:
Grain quality is crucial to meeting market demand and preserve the sustainability of the European rice sector.
However the relationships between agro-meteorological conditions and major features of pre-harvest quality are
not well understood. The evaluation of available models is needed to assess their suitability for predicting grain
quality for different environmental conditions. This study presents a multi-site and multi-year evaluation of 26
models for the simulation of rice grain composition, milling quality and cooking quality, in the main European
rice district (Northern Italy). The analysis was performed using data from 16 sites where the cultivars Loto
(japonica) and Gladio (tropical japonica) were grown in 2011–2014. Model performances denoted models’ ability
to reproduce grain quality variables, with increased modelling efficiencies (EF) from grain composition
(−0.78 < EF < 0.62; median =0.34) to cooking quality (−0.09 < EF < 0.85; median =0.44). In general,
models based on biological parameters (0.18 < EF< 0.85, median =0.52) performed better than those that
include empirical coefficients (−0.78 < EF < 0.80, median =0.29), with the best results achieved for proteins,
breakdown viscosity and pecky grains for Loto cultivar (0.04 < EF < 0.85, median =0.65). The calibration
of cultivar-specific coefficients, led the models based on empirical parameters to the best balance between
goodness-of-fit and complexity, thus resulting as a possible alternative to models using biological
parameters under the explored conditions.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
amylose; milky white grains; milling quality; model comparison; protein; starch viscosity; agronomy and crop science; soil science
Elenco autori:
G. Cappelli, R. Confalonieri, M. Romani, S. Feccia, M.A. Pagani, C. Cappa, S. Bocchi, S. Bregaglio
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