Model‐based evaluation of climate change impacts on rice grain quality in the main European rice district

Abstract

Abstract Crop simulation models are used to forecast the impacts of climate change on yield levels and to identify adaptation strategies. Nevertheless, crop quality has been almost neglected in available studies, despite its relevance on the economic and nutritional value of agricultural products. We present here a modeling study to evaluate the future trends of rice quality in the main European rice district, placed in Northern Italy. A rice growth model was coupled with a library of models of rice milling and cooking suitability, using current farmer management and baseline/future climatic scenarios as input for the simulations. Four general circulation models (NOResm, MIROC‐ESM, HadGEM2‐ES, and GISS‐ES) and two CO2 representative concentration pathways (2.6, 8.5) were used to generate 20‐year future climatic data centered on 2030 and 2070. Spatially distributed simulations were run at 2 × 2 km spatial resolution considering a Japonica (Loto) and a Tropical Japonica (Gladio) rice cultivar. The results depicted an overall decline in rice quality, especially for Loto (−5% of milling suitability considering GISS‐ES‐2.6 in all time frames; −8% in 2030 and −20% in 2070 under HadGEM2‐ES‐8.5). While the revenues of millers are expected to decrease of about 50 € t−1 in 2030 and 100 € t−1 in 2070 for Loto, minor changes are projected on Gladio milling and cooking suitability, except in the worst scenario in 2070 (−10 to −5% of cooking suitability, corresponding to −30 to −72 € t−1). Despite the need of reducing models uncertainty, this study provides variety‐specific indications on rice grain quality ready‐to‐use for crop specialists, farmers, and millers and that could raise the interest of different stakeholders of the agri‐food sector, including food scientists, geneticists, and policy makers.

Keywords

• amylose
• chalky grains
• cooking suitability
• global warming
• milling quality
• proteins