Phenotypic variability in Italian rice germplasm
Introduction
After the tremendous increases reached during the green revolution, the yields of the primary cereal crops - rice, wheat and maize - are now stagnating (Brisson et al., 2010; Lobell et al., 2011; Van Wart et al., 2013). New strategies are needed to assist breeding programs to further enhance crop productivity, especially in light of the detrimental impacts of climatic changes on food security and on the environmental sustainability of cropping systems (Bocchiola, 2015; Diffenbaugh and Giorgi, 2012). Among the available technologies, plant breeding is regarded as one of the critical strategies to sustain agricultural production and implement effective adaptation strategies (Zaidi et al., 2019). Plant breeding is indeed an expensive, time consuming and labour-intensive activity (Acquaah, 2012), which is limited by constraints like the narrowed genetic diversity and the poor adaptability of available genotypes across environments. Scientists are thus developing new techniques to speed up and lessen the economic burden of standard breeding programs like rapid generation advance (Lenaerts et al., 2019), speed breeding (Watson, 2018), genetic editing (Song et al., 2016), ideotype breeding (Martre et al., 2015), and crop simulation modelling (Eeuwijk et al., 2019; Hammer et al., 2016). All these techniques rely on a thorough knowledge of the accessible genetic variability and of the complex relationships between the crop traits of interest. Notably, the adoption of crop simulation modelling to support plant breeding programs (Boote et al., 2001; Chenu et al., 2011) should account for the known physiological limits and the correlations and compensatory effects among traits (Picheny et al., 2017). However, the costs associated with the characterisation of available germplasm through field experiments often impede the collection of exhaustive datasets needed for such activities (Nwachukwu et al., 2016).
These considerations also apply to rice agriculture in Italy, where there is a long history of cultivation and vast biodiversity of genotypes (Mongiano et al., 2018). Since the 1990s, the rice sale price has fallen considerably due to the competition exerted by developing countries (Food and Agriculture Organization, 2012). Moreover, the EU Common Agricultural Policy endorsed a progressive reduction of the subsidies granted to rice growers aiming at more equable income support to farmers regardless of the cultivated crops (European Parliament, 2010). Rice cultivation in Europe is also in the spotlight for ecological issues like groundwater pollution, high greenhouse gases emissions (mostly methane, W. Kim et al., 2018), and land degradation (Blengini and Busto, 2009), although it provides socio-economic benefits like water catchment (e.g. rice paddies used as floodplains) and the creation of habitats for waterbirds in lowland areas like, e.g., in the Italian Po valley (Fasola et al., 1996; Longoni, 2010). Apart from the ecological benefits, the environmental costs of rice cultivation and the use of prime agricultural land must be at least justified by its economic return, while actively fostering the reduction of the impacts of these agroecosystems (Sheehy and Agric, 2011).
The availability of phenotypic characterisations of the accessible germplasm is of paramount importance for the development of new improved rice varieties, which could bolster the rice systems towards greater economic and environmental sustainability. To date, assessments of the phenotypic variability found in the rice germplasm of Italy are lacking or involve a limited set of crop traits (Faivre-Rampant et al., 2010; Mongiano et al., 2018). To bridge this gap, we analysed fourteen key crop traits related to phenology, development, plant and grain biometrics, and biomass accumulation in a sample of 40 rice cultivars, selected to be representative of the whole phenotypic variability of the Italian varietal landscape. The aims of this study were a) to broaden the knowledge about the variability of yield-related traits, b) to investigate the between-traits relationships, and c) to highlight the patterns of similarities among Italian rice cultivars.
Section snippets
Plant material
The 40 rice cultivars were chosen from a collection of 351 genotypes, which were characterised for seven crop traits in a previous study (Mongiano et al., 2018) – i.e., duration of vegetative and reproductive stages, culm and panicle length, caryopses length, width, and weight. The cultivar selection was performed via Kennard-Stone algorithm (Kennard and Stone, 1969) to obtain a sample maximising the variance of known traits and including genotypes at the tails of the distributions. We assumed
Traits variability
The summary statistics of the distributions of the fourteen yield-related traits and Yield, regarding the 40 Italian rice cultivars are reported in Table 2. A boxplot representation of these data, divided by the two experimental seasons, is available in Supplementary Figure S3.
The thermal requirements to reach the main phenological stages (Heading - GDDflo, and Maturity - GDDmat) showed medium-low relative variation (CVs of 8.9 % and 6.6 %, respectively). We observed more significant variations
Portraying the phenotype space of the panel
We selected a panel of 40 cultivars from 351 Italian genotypes which were characterised in a previous study for phenology (days to heading and days to maturity), culm and panicle length, thousand seeds weight, caryopsis width and length (Mongiano et al., 2018). The variability found in the 40 Italian rice cultivars was considerable for all the analysed traits and consistent with published data (Faivre-Rampant et al., 2010; Katsura et al., 2007; Samonte et al., 2001, 1998; Volante et al., 2017).
Conclusion
Italian rice germplasm is a precious reservoir of genetic variability, accumulated throughout the twentieth century until today by the synergistic efforts of farmers, breeders, and scientists, further demonstrated by the high phenotypic variability found within this representative panel of cultivars.
The study analysed the ranges of variation of critical yield-related traits in Italian rice cultivars and shed lights on their associations. Results further reinforced the concept that neither
Declaration of Competing Interest
All data generated or analysed during this study are included in this published article and its supplementary information files. The authors declare no conflicts of interest. This research has been hosted in the experimental fields of CREA-DC as part of a collaboration with the University of Milan for the PhD of Gabriele Mongiano and did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
CRediT authorship contribution statement
Gabriele Mongiano: Conceptualization, Data curation, Investigation, Formal analysis, Methodology, Software, Validation, Visualization, Writing - original draft, Writing - review & editing. Patrizia Titone: Supervision, Project administration, Writing - review & editing. Simone Pagnoncelli: Investigation. Davide Sacco: Investigation. Luigi Tamborini: Funding acquisition, Supervision, Project administration. Roberto Pilu: Supervision, Writing - review & editing. Simone Bregaglio:
Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgements
The authors thanks Dr Sofia Fregonara for her invaluable help in the field and laboratory activities.
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