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In order to make more efficient plant breeding and gain in competitiveness, the sector of oil-protein crops decided to intensify agronomic research on sunflower crop. The "Sunflower" Joint Technological Unit (Unite Mixte Technologique (UMT) "Tournesol", in French) was launched in the Toulouse area in 2006, associating closely INRA and Terres Inovia. First focused on improving oil production through an agronomic approach, the UMT was renewed in 2011 with a broader partnership and a more assertive orientation towards the development of decision-making tools. The objective of this paper is to highlight the relevance and productivity of this user-oriented research facility. The main results relate to (i) the co-construction of a simulation model (SUNFLO) that can be parameterized and manipulated by Terres Inovia engineers, (ii) the joint exploration of supra-field scales and new methods for agronomic diagnosis and yield forecasting based on remote sensing, (iii) the tuning and dissemination of operational decision rules, (iv) the production of essential knowledge on emergent and/or damaging fungal diseases, as well as on complex interactions between genotype, environment and crop management. After a concluding symposium in 2016, new requests for sunflower research were formulated by the participants. They also advocated for a diversification of crops to consider in order to better meet the needs of the whole oil-protein sector.; In order to make more efficient plant breeding and gain in competitiveness, the sector of oil-protein crops decided to intensify agronomic research on sunflower crop. The "Sunflower" Joint Technological Unit (Unité Mixte Technologique (UMT) "Tournesol", in French) was launched in the Toulouse area in 2006, associating closely INRA and Terres Inovia. First focused on improving oil production through an agronomic approach, the UMTwas renewed in 2011 with a broader partnership and a more assertive orientation towards the development of decision-making tools. The objective of this paper is to highlight the relevance and productivity of this user-oriented research facility. The main results relate to (i) the co-construction of a simulation model (SUNFLO) that can be parameterized and manipulated by Terres Inovia engineers, (ii) the joint exploration of supra-field scales and new methods for agronomic diagnosis and yield forecasting based on remote sensing, (iii) the tuning and dissemination of operational decision rules, (iv) the production of essential knowledge on emergent and/or damaging fungal diseases, as well as on complex interactions between genotype, environment and crop management. After a concluding symposium in 2016, new requests for sunflower research were formulated by the participants. They also advocated for a diversification of crops to consider in order to better meet the needs of the whole oil-protein sector. Keywords: sunflower / collaborative research / agronomy / decision support / oil concentration Résumé-L'agronomie du tournesol : 10 années de recherche en partenariat dans l'UMT Tournesol à Toulouse. Afin de valoriser les avancées en sélection végétale et de gagner en compétitivité, la filière oléoprotéagineuse a jugé nécessaire d'intensifier la recherche agronomique sur le tournesol. L'Unité Mixte Technologique (UMT) « Tournesol » associant étroitement l'INRA et Terres Inovia a été mise en place en région toulousaine en 2006 à Toulouse. Tout d'abord centrée sur l'amélioration de la production d'huile de tournesol par une approche agronomique, elle a bénéficié d'un partenariat élargi lors de son renouvellement en 2011 affirmant une orientation plus marquée vers le développement d'outils pour la décision. Cet article illustre la pertinence et la productivité de ce dispositif en s'appuyant sur quelques résultats significatifs, en particulier : (i) la co-construction d'un modèle de simulation (SUNFLO) paramétrable et manipulable par les ingénieurs de Terres Inovia, (ii) l'exploration en commun des échelles supra-parcellaires et de la télédétection pour le diagnostic agronomique et la prévision des rendements, (iii) la construction et la diffusion de règles de décision opérationnelles, (iv) la production de connaissances sur des maladies émergentes ou nuisibles, ainsi que sur des interactions complexes entre le génotype, l'environnement et la conduite de culture. À l'issue d'un colloque conclusif en 2016, de nouvelles demandes à la recherche ont été formulées. Elles passent également par une diversification des objets d'étude pour mieux répondre aux besoins de la filière oléoprotéagineuse (the full text is available in French on https://www.ocl-journal.org/10.1051/ocl/2020006/olm). Mots clés : tournesol / recherche collaborative / agronomie / aide à la décision / teneur en huile ☆ Contribution to the Topical Issue "Sunflower / Tournesol".

International audience; Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA) of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS) can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore. GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET) over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%). Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but increased GCA-based prediction ability by 6.4%. Our results show that GS is a major improvement to breeding efficiency compared to the classical GCA modeling when either one or both parents are not well-characterized. This finding could therefore accelerate breeding through reducing phenotyping efforts and more effectively targeting for the most promising crosses.

Premature ripening (PR) is one of the most important fungal diseases in France, responsible for high yield losses in sunflower crop in the main regions of production. Previous results indicated that girdling canker of the stem base, caused by Phoma macdonaldii, was its primary cause. Previous studies have reported the influence of nitrogen and water supply on the incidence and severity of PR but an additional study was required to analyse the effect of plant density on the level of attack for a more comprehensive cultural control of PR. This study supplements the known effects of crop management on sunflower PR and emphasizes the key role of crop canopy in understanding the processes involved in the development of the disease. This morphology could be manipulated through crop management (plant density, N fertilization) and probably breeding.

Premature ripening (PR) induced by Phoma macdonaldii Boerema is one of the most severe and widespread sunflower disease in France. PR could be responsible for the stagnation of seed yields around 2.5 t.ha-1 during the two last decades. As no resistant variety and no fungicide are available, cultural control remains the alternative method to limit yield losses. High N availability, high plant density and water stress after flowering significantly increase the occurrence of PR in sunflower (Seassau et al., 2010). In this paper, simple statistical models are suggested to represent PR incidence as a function of plant nitrogen status, plant population and water stress.