Phenotypic variability in Italian rice germplasm

TL;DR

This study characterizes phenotypic variability in Italian rice germplasm, identifying three genotype groups with distinct yield strategies and highlighting the importance of balanced source-sink traits for high yield.

Contribution

It introduces a novel classification of Italian rice cultivars based on yield-related phenotypic traits, aiding future rice breeding strategies.

Findings

High phenotypic variation observed across traits.

Three genotype groups with different yield strategies identified.

Balanced source-sink ratio correlates with higher yield.

Abstract

Plant breeding is one of the key strategies for further enhancement of crop yields; however, effective breeding strategies require phenotypic characterisation of the available germplasm. This study sought to characterise the phenotypic expression of fourteen crop traits related to phenology, plant architecture, and yield in a panel of 40 cultivars selected to represent the phenotypic variability present in Italian rice germplasm during a two-season field experiment. The observed range of phenotypic variation was high for many traits (coefficients of variation ranging from 5.9\% to 45.4\%) including yield (mean: 6.47 t ha\textsuperscript{-1}; CV: 15.4\%; min: 2.19 t ha\textsuperscript{-1}; max: 8.95 t ha\textsuperscript{-1}), and multiple strong associations emerged in all the analysed traits. Cluster analysis extracted three groups of genotypes characterised by alternative yield strategies, i.e. "high-tillering", "early maturing", and "increased source-sink". Our findings highlight that rice yield decrease when one strategy is overemphasised. In contrast, the highest-yielding genotypes have a balanced ratio between sink and source organs, along with a proportional duration of vegetative and reproductive phases. This study depicts the phenotypic variability in Italian rice cultivars and proposes a novel classification based on yield-related traits which could be of use in multiple rice breeding applications.