LXVII SIGA Annual Congress
“Expanding frontiers in crop genetics”
10-13 September 2024
Session 1 – Single cell -omics, innovative interactomics and beyond
Session 2 – Plant developmental genetics to improve our crops
Session 3 – Understanding and improving nutrition and health-related traits of crops
Session 4 – Coping with environmental challenges: from genetics to phenomics
Session 5 – Plant genetics strategies against biotic challenges for agroinnovations
Session 6 – Breeders’ toolbox for plant improvement
Session 7 – Getting to the field: plant genetics for the seed and nursery sector
Mini session – Fruit tree genomics and breeding
Workshop – Social impact of plant biotechnologies: challenges and opportunities
| Organised by: |
|
 Dipartimento di Scienze e Tecnologie Agro-Alimentari |
|
 Centro di Ricerca Cerealicoltura e Colture Industriali |
|
Under the patronage of: |
|
 |
|
 |
|
 |
|
 |
|
 |
|
With the support of: |
|
| Dipartimento di Scienze e Tecnologie Agro-Alimentari |
|
| Centro di Ricerca Cerealicoltura e Colture Industriali |
|
 |
|
 | |
 | |
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
Programme
|
TUESDAY, SEPTEMBER 10th
|
|
| 13:00 – 14:30 | Registration |
| 14:30 – 15:00 | Opening ceremony Chairpersons: Silvio Salvi, Roberto Tuberosa, Nicola PecchioniWelcome addresses by Institutional and Local Authorities Maurizio Martina, Food and Agriculture Organization of the United Nations (FAO), Deputy Director-General Valtiero Mazzotti, Emilia-Romagna Region, General Directorate of Agriculture Luca Fontanesi, University of Bologna, Rector Delegate for Competitive Research |
| 15:00 – 17:00 | Session 1 – Single cell -omics, innovative interactomics and beyond Chairpersons: Riccardo Aiese Cigliano, Elisabetta Frascaroli |
| 15:00 – 15:30 | Invited Lecture Stefania Giacomello – KTH Royal Institute of Technology (SE) A journey in plant spatial transcriptomics and beyond |
| 15:30 – 15:45 | Laezza C., D’Amelia V., Kang M., Caputi L., O’Connor S.E., Rigano M.M. Unveiling hidden diversity: single-cell multi-omics reveals heterogeneous metabolite production in Annurca callus cultures |
| 15:45 – 16:00 | Busatto N., Populin F., Vittani L., Zanella A., Stefan S., Komhenko I., Masuero D., Vrhovsek U., Costa F. Transcriptome and metabolic analysis reveal the impact of static and dynamic low oxygen regimes on postharvest storage of ‘Granny Smith’ apples |
| 16:00 – 16:15 | Riccucci E., Mbebi A., Razaghi-Moghadam Z., Tong H., Caproni L., Royles J., Burnett A., Aguilera M. M. P., Kromdijk J., Dell’Acqua M., Nikoloski Z. Reconstructing the maize leaf Regulatory Network from eQTL mapping associations |
| 16:15 – 16:30 | Magnanimi F., Testone G., Sobolev A., Scioli G., Pin L., Aturki Z., Pajoro A., Serino G., Giannino D. Lavender essential oil treatment can delay anthesis in Brassicaceae plants by targeting hormone and primary metabolism gene networks |
| 16:30 – 16:45 | Cappetta E., Del Regno C., Ceccacci S., Monti M.C., Conte M., D’Anna C., Alfieri M., Vietri M., Costa A., Leone A., Ambrosone A. Unveiling adaptive molecular mechanisms through comparative proteomics of potato cell responses to acute or stepwise water deficit |
| 16:45 – 17:00 | Martini D., Paini M., Limongi A.R., Angheben L., Esposito A., Delledonne M. Highly contiguous de novo assembly of plant genomes with Nanopore sequencing |
| 17:15 – 17:45 | Keynote Talk Edward Buckler – Cornell University (USA) From climate change to AI: Improving agriculture by learning from global biological diversity |
| 17:45 – 18:40 | Poster viewing (Sessions 1, 2 and 3, even numbers) |
| 18:40 – 19:30 | Poster viewing (Sessions 1, 2 and 3, odd numbers) |
| 19:30 – 20:45 | Welcome Cocktail offered by CORTEVA AGRISCIENCE ITALIA SRL |
|
WEDNESDAY, SEPTEMBER 11th
|
|
| 09:00 – 10:45 | Session 2 – Plant developmental genetics to improve our crops Chairpersons: Vittoria Brambilla, Lucio Conti |
| 09:00 – 09:30 | Invited Lecture Keisuke Nagai – Nagoya University Elucidation of the flooding tolerance mechanism through internode elongation in rice |
| 09:30 – 09:45 | Bono G.A., Giaume F., Mineri L., Betti C., Brambilla V., Fornara F. Exploring the function of rice florigenic proteins during inflorescence development |
| 09:45 – 10:00 | Castorina G., Domergue F., Consonni G. Genetically regulated cuticle composition affects the permeability of juvenile leaves and prevents seedling water loss in maize |
| 10:00 – 10:15 | D’Attilia C., Camerlengo F., Frittelli A., Palombieri S., Fratini C., Masci S., Sestili F. Modulating grain size of durum wheat (Triticum durum spp.) via TON1B overexpression |
| 10:15 – 10:30 | Tassinari A., Forestan C., Urbany C., Li K., Giuliani S., Sangiorgi G., Presterl T., Ouzunova M., Landi P., Tuberosa R., Salvi S. Fine mapping and positional cloning of a major root system architecture QTL in maize |
| 10:30 – 10:45 | De Vivo M., Bertolotti G., Damato P., Scintu D., Novak O., Amati S., Dello Ioio R. Identification of a tight link between root anatomy and compact soil penetration |
| 10:45 | SOCIETA’ PRODUTTORI SEMENTI Short Presentation |
| 11:00 – 11:30 | Coffee Break and Poster Viewing (Sessions 4 and 5, even numbers) |
| 11:30 – 13:15 | Session 3 – Understanding and improving nutrition and health-related traits of crops Chairpersons: Stefania Masci, Angelo Santino |
| 11:30 – 12:00 | Invited Lecture Fred Brouns – Maastricht University (NL) Nutrition and health-related traits of crops: is developing “safe and healthy wheat for all” an opportunity or utopia? |
| 12:00 – 12:15 | Orasen G., Mica E., Lucchini G., Negrini N., Nocito F.F., Baldoni E., Tondelli A., Sacchi G.A., Valè G. A genome wide association study of the grain ionome trait in rice Oryza sativa subsp. japonica under two diverse water management systems |
| 12:15 – 12:30 | Toccaceli M., Marinelli A., Ballabio F., Bassolino L., Pacifico D., Parisi B., Nicoletti F., Lo Scalzo R., Camilloni C., Mandolino G., Petroni K. Upland pigmented potatoes as valuable functional foods with anti-inflammatory properties: an insight into bioactive compounds interaction |
| 12:30 – 12:45 | Warren F. Manipulating carbohydrate biosynthesis in crops: targeting the gut microbiome |
| 12:45 – 13:00 | Frittelli A., Palombieri S., Quagliata G., Masci S., Botticella E., Astolfi S., De Vita P., Volpato M., Sestili F. Development and characterization of durum wheat lpa mutants by modulating the accumulation of phytic acid |
| 13:00 – 13:15 | Nigro D., Sgaramella N., Pasqualone A., Signorile M.A., Laddomada B., Sonnante G., Blanco E., Simeone R., Blanco A. Genetics of flavonoid content in pigmented durum wheat grains |
| 13:30 – 15:00 | Lunch Break |
| 14:30 – 16:30 | Session 4 – Coping with environmental challenges: from genetics to phenomics Chairpersons: Pasquale Tripodi, Michela Janni |
| 15:00 – 15:30 | Invited Lecture Fabio Fiorani – Forschungszentrum Jülich GmbH (DE) Phenotyping applications for shoot and root traits |
| 15:30 – 15:45 | Dimattia B.G., Righi A., Bettuzzi M., Koestel J., Morigi M.P., Salvi S., Hernandez Soriano M.C., Tuberosa R., Maccaferri M., Bittelli M. Use of X-Ray tomography to investigate the impact of wheat cultivars on soil morphology |
| 15:45 – 16:00 | Sillo F., Salon C., Montesano V., Summerer S., Petrozza A., Conte A., Bergese F., Jeudy C., Balestrini R. Root phenotyping in different bread wheat genotypes provides a tool to assess phosphorus-deficiency tolerance |
| 16:00 – 16:15 | Graci S., Aiese Cigliano R., Francesca S., Rigano M.M., Barone A. Identification of candidate genes for the heat stress response of a thermotolerant tomato genotype |
| 16:15 – 16:30 | Capasso G., Ruggiero A., Cirillo V., Esposito S., Esposito Se., Grillo S., Batelli G. Enzymatic modifications and stress memory in tomato: focus on the ROS scavenging machinery in a recurrent drought stress experiment |
| 16:30 – 16:45 | Ricci D., Fabene E., Lobato Gòmez M., Presa S., Al-Babili S., Granell A., Rodriguez P.L., Locato V., De Gara L., Demurtas O., Diretto G. Physiological effects of beta-apo-11-carotenal and Zaxinone apocarotenoids in Solanum lycorpersicum |
| 16:45 – 17:00 | Castellacci M., Usai G., Vangelisti A., Simoni S., Natali L., Cavallini A., Mascagni F., Küden A., López-Corrales M., Domínguez G., Baraket G., Giordani T. Exploiting the genetic diversity of the fig tree to discover molecular markers associated to morphological and abiotic stress-related traits |
| 17:00 – 17:15 | Franguelli N., Cavalli D., Notario T., Pecetti L., Crosta M., Annicchiarico P. Assessing frost tolerance in white lupin and pea: a methodological study to implement a high-throughput phenotypic platform |
| 17:15 | KWS Short Presentation |
| 17:30 – 18:10 | Fruit tree genomics and breeding – Invited minisession Dedicated to Claudio Moser Chairpersons: Laura Rossini, Stefano Tartarini |
| 17:30 – 17:50 | Giulia Malacarne – Fondazione Edmund Mach (IT) Gene functional studies and gene editing at work to improve the sustainability of viticulture |
| 17:50 – 18:10 | Maria J. Aranzana – Centre for Research in Agricultural Genomics (CRAG) – Research Institute of Agriculture, Food Research and Technology (IRTA) (ES) The use of genetic diversity, genomics and AI models for apple breeding |
| 18:15 – 18:45 | Coffee Break and Poster Viewing (Session 4 and Session 5, odd numbers) |
| 18:45 – 20:00 | SIGA General Assembly |
| THURSDAY, SEPTEMBER 12th | |
| 09:00 – 10:30 | Session 5 – Plant genetics strategies against biotic challenges for agroinnovations Chairpersons: Clizia Villano, Luca |
| 09:00 – 09:30 | Invited Lecture Sebastian Schornack – Cambridge University (UK) Exploiting conserved development regulators to achieve oomycete pathogen resistance in monocots and dicots |
| 09:30 – 09:45 | Negrini F., Sunico V., Higuera J.J., Sabbadini S., Mezzetti B., Caballero J.L., Baraldi E., Karas M. Suitability of the Md-MYB10 reporter gene to generate intragenic strawberry varieties resistant to fungal pathogens |
| 09:45 – 10:00 | D’Amelia V., Villano C., Piccinelli A.L., Docimo T., Esposito S., Ruocco M., Monti M.M., Staiti A., Aversano R., Carputo D. Guardians of resilience: Anthocyanins impact on potatoes against Rhizoctonia solani |
| 10:00 – 10:15 | de Sario F., Benbernou R., Ntakirutimana F., Lapalu N., GIE Blé Dur, Ammar K., Mazzucotelli E., Prodi A., Novi B.J., Confortini A., Desiderio F., Bozzoli M., Stefanelli S., Tuberosa R., Suffert F., Maccaferri M., Marcel T.C. Genetics and genomics of the wheat-Zymoseptoria tritici pathosystem: novel resistance gene loci in wheat and insights from pathogenicity factors |
| 10:15 – 10:30 | Magris G., Zelasco S., Salimonti A., Forgione I., Sirangelo T.M., Carbonell Bejerano P., Weigel D., Bagnaresi P., Di Gaspero G., Scalabrin S., Scaglione D., Usai G., Mascagni F., Natali L., Cavallini A., Marchese A., Marra F.P., Mulas M., Medda S., Muleo R., Baldoni L., Perri E., Cattivelli L., Carbone F., Morgante M. Olive genome analysis for understanding genetic and genomic variation linked to disease and other important agronomic traits |
| 10:30 – 10:40 | APSOVSEMENTI Short Presentation |
| 10:40 – 11:45 | Coffee Break and Poster Viewing (Session 6) |
| 11:45 – 12:45 | Session 5 – cont. |
| 11:45 – 12:00 | Bevilacqua I., Moffa L., Narduzzo A., Varotto S., Perrone I., Gambino G., Pagliarani C., Balestrini R., Chitarra W., Nerva L. Exploring the impact of NPR3 gene silencing on grapevine defense responses and arbuscular mycorrhizal symbiosis establishment |
| 12:00 – 12:15 | Zenoni S., Fasoli M., Bertini E., D’Incà E., Zattoni S., Cattaneo L., Lissandrini S., Ciffolillo C., Polverari A., Tornielli G.B. DNA-Free genome editing confers disease resistance in grapevine |
| 12:15 – 12:30 | Arcieri F., Giudice G., Haider I., Delvento C., Guerriero M., Schilder M., Giancaspro A., Bouwmeester H., Lotti C., Ricciardi L., Pavan S. Resistance mechanisms to Orobanche crenata in pea (Pisum sativum L.): beyond strigolactones |
| 12:30 – 12:45 | Milani A., Di Vita N., Ottaviani F., Moffa L., Nerva L., Chitarra W., Scarabel L., Varotto S., Panozzo S. Herbicidal dsRNA discovery by using virus-induced gene silencing (VIGS) in weeds |
| 13:00 – 14:30 | Lunch Break |
| 14:30 – 16:15 | Session 6 – Breeders’ toolbox for plant improvement organized by Next Generation SIGA Chairpersons: Chiara Delvento, Antonio Lippolis |
| 14:30 – 15:00 | Invited Lecture Julia Engelhorn – Max Planck Institute for Plant Breeding Research (DE) Towards a cis-code: Identification of functional cis-regulatory variants at unprecedented scale |
| 15:00 – 15:15 | Ciacciulli A., Augugliaro M., Licciardello C. A PCR-based pipeline for integrating molecular tools into marker-free constructs |
| 15:15 – 15:30 | Puglisi D., Afshari-Behbahanizadeh S., Angione G., Colella I., Fania F., Spadanuda P., Esposito S., De Vita P. Allelic combinations of Vrn, Ppd and Rht genes improve genome-enabled prediction models in durum wheat |
| 15:30 – 15:45 | Farooq M.A., Zeng X., Forestan C., Bruschi M., Bozzoli M., Makhoul M., Snowden R.J., Ober E., Pinto F., Reynolds M., Salvi S., Maccaferri M., Tuberosa R. Dissecting the tetraploid wheat root growth angle QTLome: A key component of drought stress resilience |
| 15:45 – 16:00 | Toppino L., Gattolin S., Molesini B., Tassone M.R., Castelli A., Pennisi F., Azzimonti M.T., Pandolfini T., Rotino G.L. Inactivation of smelAUCSIA genes through CRISPR/Cas9 induces parthenocarpy in eggplant |
| 16:00 – 16:15 | Lippolis A., Dechesne A., Laurice P., Trindade L.M. High-throughput seed quality analysis in faba bean: leveraging Near-InfraRed Spectroscopy (NIRS) data and statistical methods |
| 16:15 | CORTEVA AGRISCIENCE ITALIA SRL Short Presentation |
| 16:25 – 17:00 | Coffee Break and Poster Viewing (Sessions 7 and 8) |
| 17:00 – 19:00 | Workshop – Social Impact of plant biotechnologies: challenges and opportunities Chairpersons: Domenica Nigro, Nicola Pecchioni |
| 17:00 – 17:30 | Invited Talk Agnes Ricroch – Paris-Saclay University (FR) Agricultural applications of new genomic techniques and their international regulations |
| 17:30 – 18:00 | Invited Talk Inez Hortense Slamet – IRRI (FR) Biotechnology for sustainable farming and healthier communities |
| 18:00 – 19:00 | Round table “Impatto sociale delle biotecnologie vegetali: sfide e opportunità” Discussant: Anna MeldolesiParticipants Agostino Macrì – Unione Nazionale Consumatori (UNC) Silvia Giuliani – Assosementi Vittoria Brambilla – Università degli Studi di Milano Luca De Carlo – Senatore della Repubblica Amedeo Alpi – Accademia dei Georgofili Nicola Lucifero – Università degli Studi di Firenze Daniele Rossi – COPA COGECA Research and InnovationBiotechnology for sustainable farming and healthier communities |
| 20:30 | Social Event (The Sidney Hotel) |
| FRIDAY, SEPTEMBER 13th | |
| 09:30 – 10:15 | SIGA Young Researcher Award Dedicated to: Alessandro Bozzini, Luigi Monti, Mirella Sari Gorla Chairpersons: Silvio Salvi, Daniele Rosellini |
| Gomez-Alvarez E.M. The inability of barley to germinate after submergence depends on hypoxia-induced secondary dormancy |
|
| Del Regno C. An integrated multilevel approach unveils complex seed−nanoparticle interactions and their implications for seed priming |
|
| Giaume F. Two florigens and a florigen-like protein form a triple regulatory module at the shoot apical meristem to promote reproductive transitions in rice |
|
| Award ceremony | |
| 10:15 – 12:15 | Session 7 – Getting to the field: plant genetics for the seed and nursery sector Chairpersons: Silvia Giuliani, Roberto Tuberosa |
| 10:15 – 10:45 | Invited Lecture Dirk Inzé – Ghent University (BE) Multiplex gene editing for tackling complex traits in crops |
| 10:45 – 11:00 | Balconi C., Galaretto A., Malvar R.A., Nicolas S.D., Redaelli R., Andjelkovic V., Revilla P., Bauland C., Gouesnard B., Butron A., Torri A., Barata A.M., Kravic N., Mendes-Moreira P., Murariu D., Šarčević H., Schierscher-Viret B., Vincent M., Zanetto A., Kessel B., Madur D., Mary-Huard T., Pereira A., Placinta D.D., Strigens A., Charcosset A., Goritschnig S. European public-private partnership exploring maize diversity to identify promising genetic resources for pre-breeding |
| 11:00 – 11:15 | Maccaferri M., Mazzucotelli E., Forestan C., Bozzoli M., Muhammad Awais F., Desiderio F., Mastrangelo A. M., Marone D., Gadaleta A., Viola P., Invernizzi C., Goudemand E., Devaux P., Pirona R., Ceriotti A., Curci P.L., Sonnante G., Masci S., Sestili F., Morgante M., Giuliano G., Fengler K., Llaca V., Zastrow-Eyes G., Ammar K., Faris J., Xu S., Varshney R., Walkowiak S., Chawla H.S., Sharpe P., Silvestri M., Spannagl M., Hall A., Bassi F.M., Pozniak C., Cattivelli L., Salvi S., Tuberosa R. The collaborative genomics tools developed by the Durum Wheat community: from the Platinum-Quality Svevo RefSeq v2.0 to the Global Durum Genomic Resource and the tetraploid wheat pangenome pyramid |
| 11:15 – 11:30 | Faccini N., Baronchelli M., Tagliaferri I., Reggiani F., Corvi C., Pagani D., Alberici R., Povesi A., Fricano A., Gianinetti A., Cattivelli L., Tondelli A. Public-private partnerships to support the Italian small grain cereal sector |
| 11:30 – 11:45 | Metelli G., Bonarrigo M., Blasi E., Marucci A., Sestili F., Masci S. Traceability in the Italian pasta supply chain via SNPs analysis: high-throughput SNP-based approach for the traceability in the Italian pasta supply chain |
| 11:45 – 12:00 | Martina M., Gianoglio N., Barchi L., Gaccione L., Milanesi C., Acquadro A., Portis E. Pepper breeding: Genomic profiling of MAGIC parental lines through public-private partnerships |
| 12:00 – 12:15 | Belcapo S., Rethoré E., Desiderio F., Guerra D., Nguema-Ona E., Ezquer I. Uncovering seed biology traits of new hybrids of interest in wheat |
| 12:15 – 12:30 | Closing Ceremony Chairpersons: Silvio Salvi, Stefania Masci |
Keywords index
| A | |
| ABA | 4.06 |
| abiotic stress | 2.29, 2.32, 2.36, 2.51, 2.63, 6.30 |
| Abiotic stress | 2.30, 4.05, 4.26, 8.10 |
| Abiotic stress response | 1.11 |
| Abiotic stresses | 4.01 |
| Abscisic acid | 2.34 |
| abscisic acid | 6.35 |
| acetogenic bacteria | 8.01 |
| Aegilops caudata | 2.24, 3.07 |
| AFLP | 6.19 |
| agrobiodiversity | 6.08, 6.09, 7.15 |
| agrofood system | 2.74 |
| Agronomic practices | 4.39 |
| AI-based breeding | 9.02 |
| AI-powered phenotyping | 4.17 |
| Alfa-mannosidase | 3.14 |
| Alfalfa | 4.13 |
| alien gene transfer | 6.30 |
| allele mining | 2.54 |
| allele-specific expression | 3.08 |
| Almond | 6.47 |
| Almond; Microsatellites; Phenotypic descriptors; Biodiversity safeguard; Marche region | 8.17 |
| AMF | 5.12 |
| AMF responsiveness | 4.29 |
| anthesis control | 1.05 |
| anthocyanins | 2.36, 3.01, 3.11 |
| Anthocyanins | 3.15 |
| Anti-inflammatory | 3.03 |
| antiflorigens | 2.02 |
| antioxidants | 8.14 |
| Apical meristem | 2.53 |
| Apocarotenoids | 4.06 |
| Apomixis | 6.18 |
| apple | 1.02, 1.03 |
| Apple | 3.10, 6.37 |
| apple breeding | 5.15 |
| apple tree | 8.19 |
| Apricot | 3.12 |
| Apulia region | 5.20 |
| Arabidopsis | 2.21, 2.33, 4.31, 4.45 |
| Arabidopsis thaliana | 2.39, 2.63 |
| arbuscular mycorrhizal fungi | 1.10, 4.14, 4.19 |
| arbuscular mycorrhizal fungi (AMF) | 5.06 |
| Aroma | 6.13 |
| artificial intelligence | 10.01 |
| Artificial intelligence | 4.23 |
| Association analysis | 6.44 |
| association studies | 1.13 |
| Asteraceae | 2.25 |
| Asymmetric cell division | 2.39 |
| ATAC-seq | 4.38 |
| ATI | 3.20 |
| Atropa belladonna | 2.51 |
| Auxin | 2.53 |
| auxin | 2.25 |
| awn | 2.23 |
| B | |
| baby fruits | 6.50 |
| Bacteria | 1.01 |
| Bacterial endophytes | 4.21, 4.44 |
| Barcoding | 4.21, 8.12 |
| barley | 2.44, 2.49, 5.01, 6.33 |
| Barley | 2.20, 2.40, 2.46, 4.17, 6.38 |
| Base Editing | 6.41 |
| bayesian statistics | 6.06 |
| beans | 2.37 |
| Bidnija olive grove | 8.18 |
| Bio-hydrogen | 8.02 |
| bioactive compounds | 2.64, 3.09, 5.12 |
| Biochemical analysis | 2.10 |
| Biocontrol agent | 5.26 |
| Biodiveresity | 8.12 |
| biodiversity | 2.78, 3.13, 7.10, 8.18 |
| Biodiversity | 2.10, 5.28, 8.15 |
| bioenergy | 4.36 |
| biofertilizer | 4.12 |
| Biofortification | 3.05 |
| Biogenic volatile organic compounds | 2.53 |
| Bioinformatic tools | 1.07 |
| biopesticides | 7.09 |
| biostimulant | 2.16 |
| Biostimulant | 2.56 |
| Biostimulants | 2.15, 2.50 |
| biostimulants | 2.63, 4.31, 4.34, 7.12 |
| Biotic stress | 2.68, 5.29 |
| Biotic Stress | 5.14 |
| biotic stresses | 5.31 |
| biotic/abiotic stress | 2.37 |
| Bisulfite sequencing | 3.15 |
| Blood orange | 3.15 |
| Brassica oleracea | 6.10 |
| Brassica spp. | 7.14 |
| Brassicaceae | 1.05, 2.45, 7.09 |
| Brassinosteroid | 2.70 |
| Bread and durum wheat | 2.61 |
| bread wheat | 4.03 |
| Breeding | 6.44, 7.04 |
| breeding | 2.37, 2.73, 2.78, 4.34, 6.23, 6.28, 6.45, 6.46, 6.51, 7.06 |
| Breeding strategies | 6.17 |
| Brix degree | 8.13 |
| broccoli | 6.10 |
| broccoli-raab | 6.24 |
| Bronze tomato | 3.18 |
| Broomrape | 5.08 |
| BSA | 2.44 |
| BSAseq | 6.23 |
| BSMV | 5.32 |
| Budbreak | 2.09 |
| C | |
| callus | 4.09 |
| callus cultures | 1.02 |
| Camelina | 2.18 |
| Candidare genes | 4.04 |
| candidate gene | 8.07 |
| candidate genes | 4.19, 4.47 |
| Candidate genes | 4.49 |
| Cannabis | 6.31 |
| CAPFITOGEN tools | 2.76 |
| Capsicum annuum | 3.21, 7.06 |
| Capsicum annuum L. | 2.10 |
| Carbohydrate quality | 3.04 |
| carbon accumulation | 6.30 |
| Cardamine hirsuta | 2.39 |
| carotenoid content | 3.17 |
| Cas9 orthologs | 6.41 |
| CBF Genes | 2.20 |
| cell wall | 9.01 |
| cellular level phenotyping | 4.16 |
| Characterization | 2.67 |
| characterization | 2.74 |
| chemotype | 3.13 |
| chestnut | 5.17 |
| chestnut micropropagation | 7.11 |
| Chilling Injuries | 2.41 |
| ChIP-seq | 4.35 |
| ChIP-Seq | 4.25 |
| Chromosome engineering | 6.40 |
| chromosome-scale genome assembly | 5.12 |
| circadian clock | 2.55 |
| Circular economy | 5.13 |
| cistrome | 4.11 |
| citrus | 6.02 |
| Citrus limon | 5.26 |
| Climate change | 2.22, 2.70 |
| Climate variability | 4.23 |
| CO2 reductase | 8.01 |
| Cold | 3.15 |
| Cold Acclimation | 2.20, 4.15 |
| Cold stress | 4.15 |
| Colonization | 4.22 |
| Commercial variety | 4.35 |
| Common bean | 8.09 |
| common wheat | 6.45 |
| compact soil | 2.06 |
| Complementarity analysis | 2.76 |
| Conservation | 2.28 |
| conservation | 7.15 |
| conservative agriculture | 2.62 |
| constant light | 2.55 |
| Core collections | 2.67 |
| corky root rot | 5.22 |
| coronatine | 2.26 |
| cortex | 2.06 |
| Cortex | 2.39 |
| cover crop | 2.18 |
| CRF transcription factors | 1.11 |
| Crispr-Cas | 6.20 |
| Crispr-Cas9 | 2.73 |
| CRISPR-Cas9 | 1.08 |
| CRISPR-cas9 | 5.33 |
| CRISPR/Cas9 | 2.34, 2.53, 2.68, 5.06, 5.22, 5.28, 5.32, 6.12, 6.40, 6.43, 6.48 |
| CRISPR/Cas9 platform for plants | 6.41 |
| CRISPR/Cas9 system | 5.07 |
| CrisprCas9 | 2.70 |
| crop improvement | 7.01 |
| crop protection | 5.09 |
| Crop yield improvement | 4.26 |
| Crops | 2.40 |
| cross populations | 4.48 |
| cross-species analyses | 2.08 |
| crude protein yield | 6.14 |
| cryptochromes | 6.24 |
| CslF6 gene | 3.07 |
| Cucurbita spp. | 5.23 |
| Cucurbitaceae | 5.29 |
| culm morphology | 2.44, 2.46 |
| Curly leaf | 4.15 |
| cuticle | 2.03, 4.33, 9.01 |
| CWR | 2.76 |
| Cynara cardunculus var. altilis | 5.12 |
| cytokinin | 4.31 |
| cytokinins | 2.25 |
| D | |
| D27-likes | 2.34 |
| DArTseq | 3.13 |
| Dasypyrum villosum | 3.07 |
| ddRAD-seq | 3.09 |
| De novo assembly | 1.07, 4.13 |
| Deasease resistance | 5.16 |
| decreased irrigation | 2.16 |
| defense | 9.01 |
| development | 2.72 |
| developmental plasticity | 2.65 |
| Developmental trajectories | 1.12 |
| Diagnostic markers | 2.61 |
| Diatoms | 8.02 |
| differential DNA methylation | 3.08 |
| differentially expressed genes | 5.25 |
| Digitaria exilis | 7.08 |
| Diplotaxis tenuifolia | 2.71, 6.15 |
| Disease resistance | 5.30 |
| DNA editing | 4.49 |
| DNA methylation | 3.15, 8.13, 8.19 |
| DNA-free genome editing | 5.27 |
| Domestication history | 6.51 |
| Dormancy | 2.17 |
| Double Haploids | 2.46 |
| Drought | 2.21 |
| drought | 2.03, 2.47, 2.54, 4.11, 4.24, 4.34 |
| Drought Resilience | 6.04 |
| drought resistance | 4.33 |
| Drought stress | 4.05, 4.44 |
| drought stress | 2.32, 2.66, 4.14, 4.25, 4.41, 6.01, 6.35 |
| Drought Stress | 4.27 |
| drought tolerance | 4.19 |
| Drought tolerance | 2.52, 4.40 |
| drought-stress response | 4.38 |
| Durium wheat | 6.49 |
| durum wheat | 2.62, 2.72, 3.01, 4.09, 6.03, 6.33, 8.07 |
| Durum Wheat | 6.04, 8.10 |
| Durum wheat | 2.70, 2.77, 3.05, 3.20, 4.23, 7.05 |
| DUS and VCU | 6.39 |
| Dwarf 27 | 2.34 |
| Dwarfing genes | 2.52 |
| dynamic response | 4.20 |
| E | |
| ecotype | 6.09 |
| ecotypes | 6.08 |
| efficiency | 8.16 |
| eggplant | 6.23 |
| Eggplant | 6.12 |
| Electric field | 5.33 |
| elicitors | 2.26 |
| endoplasmic reticulum | 2.27 |
| Environmental plastic pollution | 4.30 |
| environmental stresses | 7.07 |
| Epigenetic | 2.09 |
| epigenetic changes | 8.19 |
| epigenetic mechanisms | 4.38 |
| Eragrostis curvula | 6.18 |
| Eragrostis tef | 6.29 |
| ERF | 2.28 |
| Erysiphe necator | 5.21 |
| essential oils | 1.05 |
| ethylene | 2.29 |
| European olive oils | 8.05 |
| EVA collection | 4.37 |
| evaluation network | 7.02 |
| evo-devo | 2.06 |
| evolutionary genetics | 5.05 |
| EVOO | 8.03 |
| expression Quantitative Trait Loci mapping | 1.04 |
| F | |
| faba bean | 6.06 |
| Ficus carica | 4.07 |
| fig tree | 3.08 |
| fine-mapping | 6.46 |
| fingerprinting | 6.08 |
| Fire blight | 4.08 |
| Firmness | 6.22 |
| Flavonoids | 3.03, 3.21 |
| FLC gene | 2.18 |
| Flooding | 2.28 |
| Flooding tolerance | 2.01 |
| Flooding Tolerance | 4.18 |
| florigens | 2.02 |
| flower fertility | 2.02 |
| Flower organ identity | 2.33 |
| Flower organ polarity | 2.33 |
| flowering | 4.34, 6.24 |
| Flowering | 2.09, 2.21, 6.47 |
| flowering time | 2.18, 6.15 |
| foliar disease | 5.24 |
| fonio | 7.08 |
| Food security | 2.04 |
| Freezing | 4.15 |
| Frost Resistance | 2.20 |
| Frost tolerance | 4.01 |
| Fructans | 3.20 |
| fruit and plant morphological traits | 7.11 |
| fruit chemical composition analyses | 7.11 |
| fruit color | 3.11 |
| Fruit development | 4.39 |
| fruit genomics | 9.02 |
| fruit quality | 6.05, 6.16 |
| Fruit quality | 6.37 |
| Fruit softening | 6.22 |
| fruit traits | 4.07 |
| Fruit tree breeding | 9.02 |
| functional phenotyping | 4.20 |
| functional genomics | 6.33 |
| fungal diseases | 5.19 |
| fungi | 5.31 |
| fungi infection | 6.45 |
| Fusarium Ear Rot | 5.16 |
| Fusarium graminearum | 5.13 |
| Fusarium resistance | 8.07 |
| Fusarium verticillioides | 5.10, 5.11, 5.13 |
| G | |
| GAD1 gene | 2.23 |
| Gas exchanges | 4.28 |
| GC/MS | 3.18 |
| gene coexpression network | 2.72 |
| Gene editing | 7.01 |
| gene editing | 5.17, 6.05, 9.01 |
| Gene expression | 2.12 |
| GENE EXPRESSION | 2.58 |
| gene expression | 2.08 |
| Gene expression regulation | 1.12 |
| Gene network | 1.12 |
| Gene Regulation | 1.08 |
| Gene Regulatory Network | 1.04, 2.65 |
| Gene regulatory network | 6.35 |
| Gene silencing | 2.38 |
| Gene-Targeting | 6.41 |
| genetic adaptation | 10.01 |
| genetic analysis | 3.17 |
| genetic divergence | 2.31 |
| genetic diversity | 4.07, 5.05, 6.08, 6.27, 6.28, 7.02, 7.03, 7.11 |
| Genetic diversity | 2.48, 6.17 |
| genetic engineering | 2.04 |
| genetic improvement | 3.09, 5.31 |
| genetic linkage map | 8.07 |
| genetic potential | 2.24 |
| genetic resources | 2.37, 2.74, 4.46, 8.18 |
| Genetic resources | 2.67 |
| Genetic variability | 2.40 |
| genetic variability | 3.02, 4.11, 8.11, 9.02 |
| Genetica Diversity | 3.12 |
| Genome editing | 5.11, 6.20, 6.43, 6.48, 8.02 |
| Genome Editing | 2.70, 6.22 |
| genome editing DNA-free | 5.07 |
| genome sequencing | 1.13 |
| Genome sequencing | 1.07 |
| Genome wide association mapping | 2.48 |
| Genome Wide Association Study GWAS | 6.04 |
| Genome-wide association studies | 5.30 |
| Genomic approaches | 6.21 |
| genomic prediction | 6.03 |
| genomic regions | 5.24 |
| genomic selection | 6.14 |
| genomic selection in plant breeding | 6.34 |
| genomics | 6.39 |
| Genomics | 4.04, 6.32 |
| Genotype | 6.38 |
| genotypic variation | 3.06 |
| Genotyping | 2.10, 5.20 |
| genotyping | 8.18 |
| Genotyping-by sequencing | 2.31 |
| germination parameters | 2.14 |
| Germplasm | 6.44 |
| germplasm | 8.11 |
| Germplasm bank | 6.21 |
| germplasm characterization | 6.25 |
| Germplasm collection | 3.10 |
| Germplasm Collection | 3.12 |
| global warming | 4.48 |
| glucoraphanin | 2.26 |
| glucosinolates | 7.09 |
| Glutathione pathway | 2.13 |
| Glutathione S-transferases | 4.41 |
| glycoalkaloids | 3.16 |
| Grafting | 8.13, 8.19 |
| grain protein content | 3.06 |
| Grain size | 2.04 |
| grain size-related traits | 4.47 |
| grain weight | 4.47 |
| grain yield | 6.14 |
| Grapevine | 1.08, 2.73, 4.39, 5.27 |
| grapevine | 5.06, 9.01 |
| Grapevine physiology | 4.27 |
| Grapevine Rootstocks | 4.27 |
| graph pangenome | 6.11 |
| gravitropism | 2.49 |
| Green Revolution | 2.52 |
| greenhouse | 2.07 |
| greenhouse gas emissions | 10.01 |
| GRF gene family | 6.33 |
| Growth habit | 2.61 |
| growth progression | 4.32 |
| Gut microbiome | 3.04 |
| GW analysis | 2.62 |
| GWAS | 2.21, 2.46, 4.01, 4.22, 4.36, 4.37, 5.04, 6.11, 6.39, 6.45, 6.47, 6.49 |
| gwas | 4.07 |
| GxE | 8.10 |
| H | |
| Halophytes | 4.21 |
| haplotype diversity | 7.03 |
| haplotype-phased genome | 3.08 |
| HD-Zip II | 2.33 |
| HDCR | 8.01 |
| Health | 3.04 |
| Health-promoting pigments | 3.21 |
| heat stress | 2.71, 4.42 |
| Heat stress | 4.04 |
| Heavy metals | 2.12 |
| Helianthus annuus L. | 4.38 |
| Hemp | 2.17 |
| hemp | 2.35, 6.26 |
| herbicidal RNAi | 5.09 |
| herbicide resistance | 5.09 |
| heterosis | 7.07 |
| High-throughput | 7.05 |
| high-throughput phenotyping | 6.06 |
| high-throughput screening | 8.01 |
| Highthrouput Plant Phenotyping | 4.27 |
| histone modification | 2.64 |
| histone modifications | 4.25 |
| Historical Italian rice varieties | 2.23 |
| holobiont | 2.16 |
| Hordeum vulgare | 2.42, 2.43 |
| hormones | 2.25 |
| HS-SPME | 2.35 |
| Human health | 2.12 |
| hybrids | 7.07 |
| hydrogen | 8.01 |
| Hydrolase enzymes | 4.30 |
| Hydroponic culture | 3.14 |
| Hypoxia | 2.01 |
| I | |
| iMAGIC | 6.38 |
| in situ conservation | 2.76 |
| In vitro regeneration | 5.33 |
| in vitro regeneration | 6.12 |
| in vivo monitoring | 4.20 |
| In-vitro | 2.32 |
| INCREASE | 2.78 |
| Indigenous crops | 6.25 |
| inflorescence development | 2.02 |
| ink disease | 5.17 |
| intragenic | 5.02 |
| Introgression Lines | 6.32 |
| invasive species | 2.51 |
| inversion | 6.40 |
| ionome | 3.02 |
| Italian maize inbred lines | 2.48 |
| J | |
| jasmonic acid | 2.29 |
| Jordan | 2.37 |
| K | |
| KASP | 7.13 |
| Kernel | 6.47 |
| Kernel traits | 6.44 |
| kernels | 3.02 |
| Kiwifruit | 2.09 |
| Kosakonia sacchari | 4.22 |
| L | |
| Lactuca sativa | 6.43 |
| landrace | 6.10 |
| Landrace | 4.35 |
| landrace diversity | 6.24 |
| landraces | 3.17 |
| Landraces | 2.37, 6.07, 7.14 |
| Landscape-genomics | 6.07 |
| large genomes | 1.13 |
| Lateral Root | 2.05 |
| Lazio germplasm | 7.14 |
| lead-free perovskite | 2.07 |
| Leaf erectness | 2.42 |
| leaf permeability | 2.03 |
| leafy crops | 2.25 |
| legume crops | 2.37 |
| Legumes | 4.01 |
| legumes | 2.78 |
| lemon | 5.31 |
| lentil | 2.74, 2.78 |
| Lentil | 2.67 |
| Lentil genotypes | 2.66 |
| Lettuce | 2.56 |
| lettuce | 1.10 |
| Linkage Mapping Population | 5.04 |
| lipoxygenase | 5.10 |
| Local accessions | 8.15 |
| local genotype preservation | 6.27 |
| Local Germplasm | 8.04 |
| lodging | 2.44, 2.46 |
| Long reads | 1.07 |
| long-read sequencing | 7.03 |
| Long-reads | 1.09 |
| Low coverage sequencing | 1.09 |
| low oxygen | 1.03 |
| LRD gene expression | 2.54 |
| Lunar | 4.45 |
| M | |
| machine learning | 6.06 |
| macroelements | 4.36 |
| MAGIC | 4.33, 7.06 |
| MAGIC maize population | 5.16 |
| MAGIC population | 4.24, 4.32, 7.10 |
| maize | 2.03, 4.11, 4.24, 4.32, 5.10, 7.01, 7.02, 7.09, 10.01 |
| Maize | 2.05, 6.07 |
| maize leaf transcripts | 1.04 |
| Malsecco | 5.31 |
| Mapping by sequencing | 4.40 |
| marker | 6.26 |
| Marker Assisted Selection (MAS) | 5.14 |
| marker-assisted backcross | 6.36 |
| markers | 4.42 |
| MAS | 5.15 |
| MCSeEd | 8.13 |
| MCSeEd genotyping | 6.17 |
| Medicago sativa | 6.20 |
| Melatonin | 2.30 |
| memory acquisition | 2.57 |
| Metabarcoding | 4.28 |
| metabolic activity | 4.16 |
| Metabolic Engineering | 2.59 |
| metabolic engineering | 3.18 |
| Metabolite profiling | 3.10 |
| metabolomic analysis | 2.51 |
| Metabolomics | 4.10, 6.32 |
| Metagenomics | 4.44 |
| Microalgae | 2.50, 4.30, 8.02 |
| microbial consortia | 1.10 |
| Microbiome | 1.01, 6.52 |
| microbiome | 9.02 |
| Microbiota | 4.45 |
| Microelements | 3.05 |
| Microsatellite | 6.42 |
| microsatellite markers | 8.05 |
| microtom | 7.12 |
| Mildew | 4.08 |
| milk thistle | 3.13 |
| Mimosa pudica | 2.57 |
| minor cereals | 7.08 |
| miR156 | 2.36 |
| mixed-linkage glucan | 3.07 |
| modern breeding | 2.71 |
| Molecular Biology | 1.08 |
| Molecular biology of plant development | 2.19 |
| molecular characterization | 6.19 |
| Molecular markers | 6.42, 7.14 |
| molecular tools | 6.50 |
| Molecular validation | 2.52 |
| morphological characterization | 3.17 |
| multi parental cross design | 6.16 |
| multi-environment trial | 2.62 |
| Multigenic family | 2.56 |
| Multiparental maize population | 1.04 |
| multiparental population | 6.28 |
| mutagenesis | 8.09 |
| mutants | 2.43 |
| Mycotoxigenic fungi control | 5.13 |
| mycotoxins | 7.09 |
| N | |
| NaDES | 3.16 |
| nanofertilizers | 3.19 |
| nanomaterials | 8.06 |
| NASA | 4.45 |
| NB-LRR proteins | 5.23 |
| necrotrophic fungi | 5.03 |
| Nested Association Mapping (NAM) | 6.29 |
| Network analyses | 1.11 |
| New Plant Breeding Techniques | 5.21 |
| Next-Generation Sequencing (NGS) | 6.48 |
| NGS (next generation sequencing) | 6.08, 6.09 |
| NGT | 5.02, 6.02 |
| Nicotiana tabacum | 4.41 |
| NIR spectroscopy | 6.06 |
| Nitrate | 2.77 |
| Nitrogen | 6.52 |
| Nitrogen efficiency | 10.01 |
| Nitrogen use efficiency | 8.08 |
| Non-Photochemical Quenching (NPQ) | 8.16 |
| NUE | 2.77, 6.36 |
| NUS | 7.08 |
| nutritional profile | 6.19 |
| O | |
| oilseed crop | 2.18 |
| Olea europaea | 2.55 |
| Olive | 5.20, 8.03, 8.04 |
| olive | 5.05 |
| Olive tree | 4.19 |
| Oltrepò pavese | 8.04 |
| omics | 1.05, 2.16 |
| Omics | 2.41, 5.29 |
| Omics Analyses | 6.04 |
| omics data | 4.46 |
| Omics data integration | 4.35 |
| Online database | 6.21 |
| ONT | 2.21 |
| orphan crops | 7.08 |
| Oryza sativa | 4.22 |
| Oryza sativa ssp. indica | 6.36 |
| Oryza sativa ssp. japonica | 6.36 |
| osmotic stress | 2.64 |
| Osmotic stress | 2.15 |
| Oxford Nanopore sequencing | 5.12 |
| Oxford Nanopore Technology | 6.29 |
| oxidative stress | 3.16 |
| Oxidative stress | 1.11, 4.05 |
| oxylipins | 5.10 |
| P | |
| P. tracheiphilus | 5.26 |
| Pale-green | 2.40 |
| pan di zucchero | 2.16 |
| Pan-cistrome | 6.01 |
| Pan-Genome | 6.18 |
| Pangenome | 6.29 |
| pangenome pyramid | 7.03 |
| parthenocarpy | 6.23 |
| Parthenocarpy | 6.05 |
| Partial Redundancy Analysis | 6.07 |
| partnership | 7.06 |
| Pathogen resistance | 6.22 |
| pathogen resistance | 5.07 |
| Pathogenicity Test | 5.04 |
| PCD | 2.71 |
| PDO | 8.05 |
| Pea | 5.08 |
| Peach | 1.09 |
| Peanut | 6.51 |
| pear | 6.16 |
| Peas | 3.04 |
| pedigree based analysis | 6.16 |
| pepper | 3.09 |
| Pepper | 4.37 |
| Perennial wheats | 4.12 |
| Perennial wheats lines | 4.10 |
| PGI | 8.05 |
| PGP traits | 4.12 |
| PGPB | 2.47 |
| PGPM | 1.10 |
| PGPR | 4.28 |
| Phaseolus vulgaris L. | 6.19 |
| pheno-morphological traits | 6.03 |
| phenolamides | 5.03 |
| phenolic acids | 3.16 |
| phenology | 4.48 |
| Phenology | 4.39 |
| phenomics | 4.32, 6.39 |
| Phenotype | 6.38 |
| Phenotype Microarray | 4.16 |
| Phenotypic data | 4.23 |
| phenotypic parameters | 4.19 |
| phenotypic profiling | 6.25 |
| phenotypic selection | 6.14 |
| phenotypic traits | 7.02 |
| phenotyping | 4.42, 7.10 |
| Phenotyping | 2.10, 2.38, 4.01, 4.40 |
| PHENOTYPING | 2.58 |
| phosphorous | 4.03 |
| Phosphorus use efficiency | 8.08 |
| Photoprotection | 4.26 |
| photosynthesis | 4.33, 8.14 |
| Photosynthesis | 2.40, 4.26 |
| photosynthesys | 8.16 |
| Photosystem II(ΦPSII) | 6.38 |
| Phycoremediation | 4.30 |
| physico-chemical features | 6.27 |
| Physiological parameters | 8.08 |
| Phytic acid | 3.05 |
| Phytocannabinoids | 6.31 |
| Phytohormones | 2.01, 2.53 |
| Phytophthora | 5.01 |
| Pinot Noir | 4.44 |
| Pisum sativum | 6.14 |
| PIWI | 5.19 |
| Plant biology | 2.19 |
| Plant bioreactors | 3.14 |
| Plant biostimulants | 2.45 |
| plant breeding | 2.24, 4.46 |
| Plant Breeding | 5.14 |
| Plant breeding | 3.21 |
| plant cells | 4.16 |
| plant development | 2.75, 4.34 |
| plant evolution | 2.65 |
| Plant exudates | 4.10 |
| plant genetic resources | 6.45, 7.13 |
| plant growth promoting microorganisms | 8.06 |
| plant growth-promoting bacteria | 8.11 |
| plant nutrition | 4.03 |
| Plant physiology | 2.19 |
| Plant protection | 2.38 |
| Plant sensing | 2.38 |
| plant signaling | 2.63 |
| Plant-Microbe Interactions | 4.18 |
| plant-microbe interactions | 5.01 |
| Plant-rooting | 2.45 |
| Plasmid synthesis | 6.02 |
| Ploidy | 6.18 |
| Pochonia chlamydosporia | 5.18 |
| Podosphaera xanthii | 5.29 |
| Polycomb Repressive Complex 2 | 4.15 |
| Polyethylene terephthalate (PET) degradation | 4.30 |
| Polymorphism Information Content | 6.42 |
| polyphenols | 5.19 |
| Polyploidy | 4.13 |
| poplar | 2.11 |
| Poplar | 2.13 |
| population structure | 7.03 |
| post-harvest | 1.03 |
| Postharvest | 2.41, 6.37 |
| potato | 2.36 |
| Potato | 3.03 |
| potato (Solanum tuberosum) | 1.06 |
| potato peels extracts | 3.16 |
| PPOs | 2.47 |
| pre-breeding | 6.30 |
| prebreeding | 7.02 |
| predictive ability | 6.03 |
| Predictive models | 4.23 |
| preserving local varieties | 6.19 |
| Primary metabolites | 3.10 |
| Prime Editing | 6.41 |
| priming | 4.09 |
| Priming | 2.17, 2.30, 2.57 |
| Private alleles | 8.03 |
| proteomics | 1.06 |
| Protoplast | 5.33 |
| protoplast regeneration | 5.07 |
| Protoplasts | 1.08, 5.27 |
| protoplasts | 4.16, 6.12 |
| Protoplasts isolation | 5.28 |
| Prunus armeniaca | 6.46 |
| Prunus persica | 2.41 |
| PRX | 2.56 |
| Public-Private Partnership | 7.04 |
| pyrenocheta | 5.22 |
| Q | |
| QTL | 2.05 |
| QTL analysis | 4.49, 5.24 |
| QTL mapping | 3.01, 4.32, 4.48, 5.16, 5.30, 6.16 |
| quality | 3.09 |
| quantitative trait loci | 6.28 |
| quantitative traits | 7.01 |
| R | |
| R-genes | 5.23 |
| Reactive Oxygen Species | 2.17 |
| Recombinant hybrids | 5.16 |
| recombinant inbred lines (RIL) | 8.16 |
| Recombinant Inbred Lines (RIL) | 2.32 |
| Redox modifications | 4.05 |
| reduced fertilization | 4.14 |
| reference genome | 5.05 |
| Reference genomes | 2.61 |
| Regolith | 4.45 |
| regulatory network | 1.06 |
| reporter gene | 5.02 |
| reserve remobilisation | 6.30 |
| Resilience | 2.22, 6.07 |
| resilience | 4.24 |
| resistance | 5.02, 5.24 |
| Resistance | 5.08 |
| Resistant genes | 5.29 |
| restriction-free | 6.02 |
| reugularized linear regression | 1.04 |
| rhizosphere | 4.12 |
| Rhizosphere | 4.21, 6.52 |
| Rhizosphere environment | 4.10 |
| Rhizosphere Microbial Communities | 4.18 |
| ribonucleoproteins | 6.12 |
| rice | 2.02 |
| Rice | 2.01, 2.28, 3.02, 6.13, 8.11 |
| Rice domestication | 2.23 |
| Rice Seedling Establishment | 4.18 |
| RISOLO project | 2.23 |
| RKN | 5.18 |
| RNA seq | 8.14 |
| RNA Sequencing | 2.22, 4.27 |
| RNA sequencing | 5.25 |
| rna-seq | 1.03 |
| RNA-seq | 1.11, 2.08, 3.18 |
| RNA-Seq | 2.45, 2.77, 4.13 |
| RNA-Sequencing | 5.10 |
| RNAseq | 4.09, 4.28, 4.35, 5.26 |
| rocket | 2.26 |
| Root System Architecture | 2.05 |
| root angle | 2.49 |
| root architecture | 2.43, 2.49, 2.54, 4.31 |
| root development | 2.06, 2.39 |
| Root Growth Angle RGA | 6.04 |
| Root hair mutants | 4.40 |
| root meristem | 2.06 |
| root microbiota | 6.36 |
| root phenotypic plasticity | 4.29 |
| root phenotyping | 4.03 |
| root resistance | 5.01 |
| Root System Architecture | 4.02 |
| root traits | 4.03 |
| roots | 4.43 |
| rootstock effect | 8.19 |
| ROS | 2.15 |
| RT-qPCR | 2.35 |
| Rubus idaeus | 3.11 |
| rucola | 6.15 |
| S | |
| saccharification | 4.36 |
| Salicornia | 8.12 |
| Salinity | 2.37, 2.50 |
| salt stress | 4.07, 4.41, 7.12, 8.06 |
| Salt stress | 2.13, 2.30, 4.37 |
| Secondary metabolites | 3.10 |
| seed | 6.26, 7.15 |
| seed development | 7.07 |
| seed germination | 2.11, 4.42 |
| seed priming | 2.11, 2.14 |
| Seed priming | 2.15, 2.45 |
| Seed purity | 6.42 |
| seedlessness | 2.73 |
| selective sweeps | 7.06 |
| Senescence | 2.68 |
| Sequencing | 1.01 |
| sequencing | 6.51 |
| sequencing project | 6.09 |
| serotonin (SER) | 2.60 |
| Serotonin (SER) | 2.59 |
| Short-reads | 1.09 |
| Sicilian conservation varieties | 3.20 |
| signalling | 2.65 |
| Silerncing | 4.08 |
| silymarin | 3.13 |
| Single Nucleotide Polimorphysms (SNPs) | 7.05 |
| Single nucleus ATAC-seq | 1.12 |
| Single-cell RNA-seq | 1.12 |
| single-cell technology | 1.02 |
| site-directed mutagenesis | 6.20 |
| SLP9 | 2.36 |
| Small grain cereals | 7.04 |
| SNP | 6.10, 7.13 |
| SNP markers | 2.31 |
| SNPs | 3.01, 6.17, 6.25, 6.27 |
| Soil | 6.52 |
| Soil Health | 4.02 |
| soil moisture | 2.14 |
| Solanum commersonii | 2.68 |
| Solanum incanum | 6.11 |
| Solanum insanum | 6.11 |
| Solanum lycopersicum | 2.37, 2.59, 2.60, 4.25, 4.41 |
| Solanum lycopersicum L. | 2.07 |
| Solanum melongena | 6.05, 6.11 |
| Solanum tuberosum | 2.68, 5.03, 8.14 |
| solar panels | 2.07 |
| Somatic embryogenesis | 5.27, 5.33 |
| sowing-by-season combinations | 6.03 |
| Soybean | 2.15 |
| Spatial Transcriptomics | 1.01 |
| speed breeding | 2.66 |
| spermidine | 2.11 |
| SPET | 3.12, 7.10 |
| Spike Fertility | 6.49 |
| Spike shape | 6.49 |
| spray-induced gene silencing | 5.17 |
| SSR | 7.14, 8.10, 8.15 |
| SSR markers | 5.15, 5.20, 8.03, 8.04 |
| stem cell maintenance | 2.65 |
| Stem elongation | 2.01 |
| Stilbenes | 5.21 |
| stomata | 2.27, 4.33 |
| Stomatal density | 2.69, 4.17 |
| Stomatal index | 2.69 |
| strawberry | 5.02 |
| stress | 2.57, 2.72 |
| stress biomarker | 2.64 |
| stress memory | 4.25 |
| stress response mechanisms | 1.06 |
| stress transcriptional memory | 4.38 |
| Strigolactones | 2.34, 2.43, 5.08 |
| Structural variants | 1.09 |
| Submergence | 2.28, 4.18 |
| sugar metabolism | 3.08 |
| Superficial Scald | 6.37 |
| superficial scald | 1.03 |
| susceptibility genes | 5.01 |
| Susceptibility genes | 4.08, 5.28 |
| sustainability | 8.14 |
| sustainable agriculture | 5.06 |
| sustainable viticulture | 5.07 |
| sweet chestnut | 7.11 |
| Symbiotic microorganisms | 4.22 |
| SynCom | 4.28 |
| system biology | 3.19 |
| Systemic Acquired Resistance (SAR) | 5.06 |
| T | |
| T. turgidum ssp. durum | 2.04 |
| target RNA-sequencing | 2.55 |
| targeted-RNAseq | 2.47 |
| Taxonomy | 8.12 |
| TEA | 6.26, 6.35, 6.40 |
| Technological quality | 3.20 |
| teff | 4.11 |
| Teff breeding | 6.29 |
| Temperature-related plasticity | 5.04 |
| terpene synthases | 2.35 |
| Terpens | 6.31 |
| terpens | 6.31 |
| tetraploid wheat | 2.47, 4.29 |
| THC | 6.26 |
| THCA | 6.31 |
| Theobroma cacao L | 6.17 |
| Therapeutic products | 3.14 |
| TILLING | 2.42, 2.44, 2.58, 3.05 |
| TILLING by sequencing | 8.09 |
| TILLING population | 4.40 |
| TILLmore | 2.69 |
| Tissue | 1.01 |
| tobacco | 5.03 |
| tolerance | 2.66 |
| Tomato | 2.12, 2.50, 4.04, 4.06, 5.14, 6.22, 6.32, 8.13 |
| tomato | 2.32, 4.20, 5.22, 6.27, 7.10, 7.12, 7.15, 8.06, 8.16 |
| Tomato Brown Rugose Fruit Virus (ToBRFV) | 5.14 |
| tomato fruits | 2.07 |
| Tomato landraces | 4.05 |
| tomato wild species | 6.40 |
| Ton1b gene | 2.04 |
| Traceability | 7.05, 8.03 |
| traceability | 8.05 |
| Transcription factor footprinting | 6.01 |
| transcription factors | 2.26, 2.35 |
| Transcription factors | 5.03, 5.11 |
| transcription regulation | 2.29 |
| Transcriptional factors | 3.21 |
| transcriptome | 2.57, 3.11 |
| Transcriptomic | 2.09 |
| transcriptomics | 2.72 |
| Transcriptomics | 4.39, 5.18, 6.32 |
| translational biology | 2.71 |
| translational research | 2.33 |
| transposon | 3.11 |
| transposons | 5.23 |
| tri-trophic system | 5.18 |
| triterpenic acids | 1.02 |
| Triticum aestivum | 6.44 |
| Triticum germplasm | 6.21 |
| Triticum turgidum | 3.06, 4.47 |
| Triticum turgidum ssp. durum | 4.36 |
| tropane alkaloids | 2.51 |
| Tryptamine (TAM) | 2.59 |
| tryptamine (TAM) | 2.60 |
| tryptamine 5-hydroxylase | 2.60 |
| tryptophan decarboxylase | 2.60 |
| Tryptophan decarboxylase (TDC) | 2.59 |
| V | |
| VAMP-Associated Protein | 2.27 |
| Varietal characterization | 6.13 |
| Varietal identification | 6.42 |
| Venturia inaequalis | 5.15 |
| Vernalization | 2.20, 2.61 |
| Viability | 2.17 |
| VIGE | 6.43 |
| Viral Vector | 6.43 |
| Vitis vinifera | 5.19, 5.21, 5.27, 5.28 |
| VOCs | 2.58, 4.12, 4.31 |
| W | |
| Walnut | 8.15 |
| Wastewater | 2.12 |
| water | 3.02 |
| Water deficit | 4.13 |
| water deficit | 2.08 |
| water deficit tolerance | 1.06 |
| water loss | 2.03 |
| water scarcity | 4.20 |
| water stress | 1.10 |
| Water stress | 8.08 |
| Water Use Efficiency | 2.69 |
| weed control | 5.09 |
| WGCNA | 5.26 |
| WGS | 6.47 |
| wheat | 2.24, 4.14, 6.39, 7.07, 7.12 |
| Wheat | 3.04, 3.07, 4.02, 6.52, 8.08 |
| Wheat breeding | 6.48 |
| Wheat diseases | 5.32 |
| whole genome sequencing | 6.24, 8.09 |
| wild wheat relatives | 2.54 |
| WinRHIZO | 4.29 |
| WRKY125 | 5.11 |
| WUE | 4.17 |
| X | |
| X-Ray CT | 4.02 |
| xenobiotic detoxification | 2.63 |
| Xylella | 5.05 |
| Xylella fastidiosa | 5.20, 5.25, 8.18 |
| Y | |
| yellow index | 3.06 |
| Yellow rust | 5.30 |
| yield | 6.33 |
| yield traits | 6.28 |
| Yield-related traits | 4.04 |
| Z | |
| Zaxinone | 4.06 |
| zea mays | 3.19 |
| Zea mays | 5.11 |
| Zea mays L. | 3.17 |
| Zymoseptoria tritici | 5.04 |
| β | |
| β-apo-11-carotenal | 4.06 |
| “ | |
| “Mugnoli” | 6.10 |
| 1 | |
| 16S rRNA | 4.21 |
| 9 | |
| 90k SNP array | 6.49 |