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◆ Field Crops Research2026-02-20· Context (archaeology)

Evaluation and optimization of wheat and maize national variety evaluation systems in Europe

Jip J. C. Ramakers, Waqas Ahmed Malik, Claude Welcker, Boris Parent, Daniela Bustos-Korts, Nadir Abu-Samra Spencer, Harimurti Buntaran, Xinxin Chen, Damien Eylenbosch, C. Flamm, Christophe Grizeau, Juan M. Herrera, Jürg Hiltbrunner, Vladimíra Horáková, Lilia Levy Häner, Fabien Masson, Joke Pannecoucque, Márton Pécs, Marek Povolný, Philipp Starnberger, Margot Visse‐Mansiaux, Tiziana Vonlanthen, Cécile Collonnier, François Laurens, Pierre Martre, Hans‐Peter Piepho, Fred A. van Eeuwijk

原始摘要(英文原文)· Original abstract
Context and objective To facilitate sustained productivity gains in wheat and maize across Europe, we analysed a long-term (2003–2018) European Value for Cultivation and Use (VCU) dataset to quantify genotypic (G) and genotype-by-environment interaction (GEI) variation and to assess variety-testing precision for grain yield. Methods Mixed-model analyses were applied to partition genetic and environmental sources of yield variation across European VCU networks in seven countries and to estimate variety-comparison precision (LSDs) and annual genetic trends for both crops. Results Across Europe, G and GEI variances were comparable, explaining in total 10–29 % of total phenotypic variance in wheat and 8–29 % in maize. LSDs ranged 0.29–0.56 t ha⁻¹ and 0.38–0.81 t ha⁻¹ , respectively. Genetic trends ranged 0.45–1.81 % yr⁻¹ for wheat and 0.90–1.31 % yr⁻¹ for maize. Testing precision allowed effective comparison of wheat and maize varieties differing by 2.7–10.5 and 3.3–6.4 release years, respectively, aligning with typical breeding turnover rates. Stronger GEI was associated with larger genetic trends in maize yield, whereas in wheat, observed trends were substantially smaller than the maximum potential implied by GEI magnitudes. Combining data from national VCU networks improved precision and allowed for efficient comparison of varieties not jointly tested. Conclusions European VCU networks are well-optimized for the number of testing locations given national evaluation periods (2–3 years). Strengthening connections among national VCU networks could further improve precision, while integrating environmental and genetic information would enable a predictive testing system, accelerating breeding progress and the development of resilient varieties. Significance This first pan-European appraisal of current VCU testing efficiency for two major crops provides a quantitative basis for optimizing variety evaluation across Europe.
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