
LXIV SIGA Annual Congress
“Plant genetic innovation for food security in a climate change scenario”
14-16 September 2021
Session 1 – Unlocking the potential of genetic resources
Session 2 – Filling the gap between potential and actual yields: Novel routes to boost crop yield
Session 4 – NGS: Next Generation SIGA
Session 5 – Abiotic stresses and resource use efficiency in a changing climate
Session 6 – Plants as biofactories
Programme
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TUESDAY, SEPTEMBER 14th
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| 09:00 – 09:30 | Opening ceremony
Welcome addresses |
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| 09:30 – 11:00 | Session 1 – Unlocking the potential of genetic resources Chairpersons: Cattivelli L., Marconi G. |
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| 09:30 – 10:00 | Invited Lecture McNally K. Sequencing of diverse rice genomes drives breeding innovation |
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| 10:00 – 10:15 | Tripodi P., Rabanus-Wallace M. T., Barchi L., Kale S., Esposito S., Acquadro A., Schafleitner R., van Zonneveld M., Prohens J., José Diez M., Börner A., Salinier J., Caromel B., Bovy A., Boyaci F., Pasev G., Brandt R., Himmelbach A., Portis E., Finkers R., Lanteri S., Paran I., Lefebvre V., Giuliano G., Stein N. Global range expansion history of pepper (Capsicum spp.) revealed by over 10,000 genebank accessions |
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| 10:15 – 10:30 | Magris G., Jurman I., Fornasiero A., Paparelli E., Schwope R., Marroni F., Di Gaspero G., Morgante M. The genomes of 204 domesticated and wild Vitis vinifera accessions reveal the history and the genetic ancestry of European wine grapes |
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| 10:30 – 10:45 | Maccaferri M., Sciara G., Bozzoli M., Novi J., Campana M., Bruschi M., Forestan C., Ratti C., Prodi A., Invernizzi C., Viola P., Oliveri F., Randazzo B., Goundemand E., Devaux P., Mazzucotelli E., Mastrangelo A., Desiderio F., Bansal U., Bariana H., Ammar K., Cattivelli L., Bassi F., Tuberosa R. Establishment of a global tetraploid wheat collection to facilitate the dissection of the native variation present in the A and B wheat genomes |
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| 10:45 – 11:00 | Barchi L., Rabanus-Wallace M. T., Prohens J., Toppino L., Padmarasu S., Portis E., Rotino G.L., Stein N., Lanteri S., Giuliano G. Genomic insights into the domestication and selection of key agronomic traits in eggplant following improved genome assembly and pan-genome analysis |
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| 11:00 – 12:10 | Break and poster vision | |
| 12:10 – 13:00 | Session 1 – (cont.) | |
| 12:10 – 12:25 | Frugis G., Testone G., Di Vittori V., Paolo D., Liberatore C., Galbiati M., Locatelli F., Cominelli E., Confalonieri M., Rossato M., Delledonne M., Cortinovis G., Bellucci E., Bitocchi E., Rodriguez M., Attene G., Aragao F., Papa R., Sparvoli F. TILLING-by-sequencing and genome editing for the functional validation of candidate domestication genes in common bean (Phaseolus vulgaris L.) |
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| 12:25 – 12:40 | Pavan S., Vergine M., Nicolì F., Sabella E., Aprile A., Negro C., Fanelli V., Savoia M.A., Montilon V., Susca L., Delvento C., Lotti C., Nigro F., Montemurro C., Ricciardi L., De Bellis L., Luvisi A. Screening of olive biodiversity defines genotypes potentially resistant to Xylella fastidiosa |
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| 12:40 – 13:00 | General discussion | |
| 13:00 – 15:00 | Break and poster vision | |
| 15:00 – 19:00 | Online SIGA General Assembly | |
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WEDNESDAY, SEPTEMBER 15th
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| 09:00 – 10:30 | Session 2 – Filling the gap between potential and actual yields: Novel routes to boost crop yield Chairpersons: Tondelli A., Rossini L. |
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| 09:00 – 09:30 | Invited Lecture Tardieu F. Improving yield for suboptimal conditions: making use of alleles for adaptive traits |
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| 09:30 – 09:45 | Rotasperti L., Tadini L., Chiara M., Crosatti C., Guerra D., Tagliani A., Forlani S., Ezquer I., Horner D. S., Rossini L., Tondelli A., Pesaresi P. The barley mutant happy under the sun 1 (hus1): a further step towards a new generation of pale green crops |
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| 09:45 – 10:00 | Miculan M., Nelissen H., Ben Hassen M., Marroni F., Inzè D., Pè M.E., Dell’Acqua M. A forward genetics approach integrating GWAS and eQTL mapping to dissect leaf development in maize (<i>Zea mays</i>) |
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| 10:00 – 10:15 | Crosatti C., Michelotti V., Tafuri A., Gazzetti K., Rossi R., Migliorini C., Guerra D., Cattivelli L., Mica E., Battaglia R. Identification and functional characterization of key genes influencing yield potential in barley |
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| 10:15 – 10:30 | General discussion | |
| 10:30 – 11:00 | Break and poster vision | |
| 11:00 – 12:25 | Session 4 – NGS: Next Generation SIGA Organized by SIGA Young Researchers Chairpersons: D’Amelia V., Delvento C. |
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| 11:00 – 11:10 | Opening Chairperson: Villano C. |
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| 11:10 – 11:40 | Invited Lecture Zhang Y. Tomato as a model plant for studying metabolic regulation |
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| 11:40 – 11:55 | Caproni L., Iohannes S.D., Woldeyohannes A.B., Miculan M., Abate Desta E., Fadda C., Pè M.E., Dell’Acqua M. A data-driven approach harnessing genomic, phenotypic, and bioclimatic diversity reveals climate-driven genomic offset in a collection of Ethiopian teff |
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| 11:55 – 12:10 | Bordignon S., Farinati S., Milani A., Panozzo S., Scarabel L., Varotto S. New insights into an exogenous RNAi-based approach for endogenous genes silencing in plants |
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| 12:10 – 12:25 | Salonia F., Ciacciulli A., Pappalardo H.D., La Malfa S., Licciardello C. Genome editing applied to induce lycopene accumulation in anthocyanin-rich sweet orange varieties |
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| 12:25 – 14:00 | Break and poster vision | |
| 14:00 – 15:00 | Session 4 – (cont) Chairpersons: Castorina G., Forgione I. |
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| 14:00 – 14:30 | Invited Lecture Coupel-Ledru A. Improving water-use efficiency through the temporal and spatial uncoupling between water loss and carbon gain: insights from a combination of high-throughput phenotyping, quantitative genetics and physiology |
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| 14:30 – 14:45 | Foresti C., D’Incà E., Vitulo N., Galli M., Zenoni S. Reconstructing the VviNAC factors intra family regulation network orchestrating the grapevine berry ripening |
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| 14:45 – 15:00 | Puglisi D., Delbono S., Visioni A., Ozkan H., Kara Ä., Casas A. M., Igartua E., Valè G., Lo Piero A.R., Cattivelli L., Tondelli A., Fricano A. Genome-enabled prediction models for grain yield, transpiration rate and below-ground traits using a barley MAGIC population |
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| 15:00 – 15:20 | Break and poster vision | |
| 15:20 – 16:50 | Session 3 – The bright and dark side of seeds: nutritional, antinutritional and functional properties Chairpersons: Janni M., Pedrazzini E. |
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| 15:20 – 15:50 | Invited Lecture Krishnan H. A multifaceted approach to improve the nutritional quality of soybean protein |
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| 15:50 – 16:05 | Sparvoli F., Cominelli E., Liberatore C., Paolo D., Campion B., Nielsen E., Bollini R. Modulation of bioactive compounds in common bean seed: two sides of the same coin |
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| 16:05 – 16:20 | Masci S., Sestili F., Camerlengo F., Neerukonda M., Fayer F., Mansueto P., Carroccio A., Schuppan D. Wheat kernel alpha-amylase/trypsin inhibitor (ATI) gene silencing procedures cause pleiotropic effects and affect ATI pro-inflammatory activity |
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| 16:20 – 16:35 | Farinon B., Costantini L., Molinari R., Di Matteo G., Ferri S., Garzoli S., Mannina L., Mazzucato A., Merendino N. Effect of malting on nutritional, antioxidant, and antinutritional properties of the seeds of two industrial hemp (Cannabis sativa L.) cultivars |
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| 16:35 – 16:50 | General discussion | |
| 16:50 – 17:20 | Break and poster vision | |
| 17:20 – 18:20 | SIGA Young Scientist Award 2021 Chairpersons: Pè M.E., Rosellini D.Castorina G. Drought-responsive ZmFDL1/MYB94 regulates cuticle biosynthesis and cuticle-dependent leaf permeabilityPompili V. Reducedfire blight susceptibility in apple cultivars using a high-efficiency CRISPR/Cas9-FLP/FRT-based gene editing system Zampieri R. |
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| THURSDAY, SEPTEMBER 16th | ||
| 09:00 – 10:30 | Session 5 – Abiotic stresses and resource use efficiency in a changing climate Chairpersons: Lo Piero A.R., Salvi S. |
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| 09:00 – 09:30 | Invited Lecture Tester M. Genomics-driven genetics to support development of saltwater agricultural systems |
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| 09:30 – 09:45 | Baldoni E., Frugis G., Martinelli F., Benny J., Paffetti D., Buti M. Identification of common key genes and regulatory pathways involved in drought tolerance in four Gramineae species through a comparative transcriptomic meta-analysis |
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| 09:45 – 10:00 | Giannino D., Testone G., Sobolev A.P., Mele G., Gonnella M., Giuseppe A., Biancari T. Integrated “omics” of leaf endives stressed by downpour-induced waterlog reveal insights in nutrient variation and molecular aspects of kestose and inulin pathway |
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| 10:00 – 10:15 | Colzi I., Vergata C., Gonnelli C., Cicatelli A., Guarino F., Castiglione S., Aprile A., De Bellis L., Martinelli F. Gaining insight into the molecular and phenotypic effects of transgenerational memory due to chromium stress in plants |
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| 10:15 – 10:30 | Francesca S., Vitale L., Arena C., Olivieri F., Maggio A., Barone A., Rigano M.M. Physiological and genomic characterization of a tomato genotype able to improve resource use efficiency in water-limited conditions |
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| 10:30 – 10:45 | Break and poster vision | |
| 10:45 – 11:45 | Session 5 – (cont) | |
| 10:45 – 11:00 | Ferrari G., Prazzoli L., Beretta M. Expoliting salt stress tolerance in Solanum pennelli introgression lines |
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| 11:00 – 11:15 | Aci M.M., Mauceri A., Abenavoli M.R., Sunseri F., Lupini A. Short-term transcriptome response to low nitrate revealed N-related differentially expressed genes in two NUE-contrasting tomato genotypes |
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| 11:15 – 11:30 | Fasano C., Donald N., Carr C., Herzyk P., Amtmann A., Perrella G. Unravelling the function of the histone deacetylation machinery during stress transcriptional responses in Arabidopsis thaliana |
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| 11:30 – 11:45 | General discussion | |
| 11:45 – 12:00 | Break and poster vision | |
| 12:00 – 14:30 | Interactive Poster Sessions | |
| 14:30 – 16:30 | Sessione 6 – Plants as biofactories Chairpersons: Avesani L., Filippone E. |
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| 14:30 – 15:00 | Invited Lecture Orzaez D. Breeding new tobacco plant biofactories through genome editing and synthetic biology |
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| 15:00 – 15:15 | Maricchiolo E., De Marchis F., Bellucci M., Paolocci F., Cignotti A., Fraternale D., Pallotta M. T., Ballottari M., Perozeni F., Panfili E., Pompa A. Production of bioactive molecules for human health in plant cells: three case studies |
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| 15:15 – 15:30 | Santoni M., Gecchele E., Zampieri R., Gandini D., Thueneman E., Lomonossoff G., Avesani L. Plant virus nanoparticles for molecular diagnostics applications |
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| 15:30 – 15:45 | Ambrosone A., De Palma M., Leone A., Del Gaudio P., Ruocco M., Turiák L., Bokka R., Fiume I., Tucci M., Pocsfalvi G. Plant roots release small extracellular vesicles carrying a molecular toolkit for defence against pathogens |
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| 15:45 – 16:00 | Sevi F., Fiore A., Frusciante S., Romano E., Rambla J. L., Orzaez D., Granell A., Diretto G. Metabolic engineering of curcuminoids in N. benthamiana leaves |
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| 16:00 – 16:15 | Lico C., Tanno B., Marchetti L., Novelli F., Giardullo P., Arcangeli C., Pazzaglia S., Podda M., Santi L., Bernini R., Baschieri S., Mancuso M. Tomato Bushy Stunt Virus nanoparticles as a platform for drug delivery to Shh-dependent medulloblastoma |
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| 16:15 – 16:30 | General discussion | |
| 16:30 – 16:45 | Break | |
| 16:45 – 18:45 | Session 7 – Plant Genetics and Breeding Chairpersons: Zenoni S., Volpi C. |
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| 16:45 – 17:15 | Keynote Lecture “New tools for doubled-haploid production in dicots” Boutilier K. |
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| 17:15 – 17:30 | Carbone F., Scalabrin S., Bagnaresi P., Tacconi G., Salimonti A., Zelasco S., Forgione I., Sirangelo T. M., Desiderio F., Cattivelli L., Morgante M. A new reference genome sequence for cultivated olive tree |
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| 17:30 – 17:45 | Ventimiglia M., Marturano G., Vangelisti A., Usai G., Simoni S., Cavallini A., Giordani T., Natali L., Zuccolo A., Mascagni F. Survey of transposable elements exaptation events in sunflower (Helianthus annuus L.) genome |
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| 17:45 – 18:00 | Acquadro A., Zayas A., Martina M., Polli M.F., Di Nardo G., Comino C., Gilardi G., Martin E., Portis E. BSA-seq analysis reveals genomic regions carrying candidate genes for male sterility phenotype in globe artichoke |
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| 18:00 – 18:15 | Mazzucato A., Picarella M.E., Granell A. A point mutation in the HD-Zip III transcription factor SlCORONA/SlHB15 underlies the phenotype of the parthenocarpic fruit (pat) tomato mutant |
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| 18:15 – 18:30 | Giacomelli L., Scintilla S., Salvagnin U., Zeilmaker T., Dalla Costa L., Malnoy M., Rouppe Van Der Voort J., Moser C. Generation of mildew-resistant grapevine clones via genome editing: potentials and hurdles |
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| 18:30 – 18:45 | Dell’Acqua M., Alem C.G., Nigir B., de Sousa K., Poland J., Kidane Y., Abate E., van Etten J., Fadda C., Pè M.E. Genomics-driven breeding for local adaptation is enhanced by farmers’ traditional knowledge |
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| 18:45 | Poster Awards | |
| 19:00 | Closing of Congress | |
Keywords index
| A | |
| abiotic stress | 1.35, 4.15, 5.06, 5.08, 5.10, 5.21, 7.27 |
| Aegilops tauschii | 7.42 |
| affordable phenotyping | 4.25 |
| Aglianico | 1.29 |
| agricultural waste management | 6.08 |
| agro-food processing | 1.11 |
| agro-morphological traits | 1.30 |
| agrobiodiversity | 1.19, 1.20, 7.15 |
| agronomic improvement | 4.24 |
| agronomic traits | 7.42 |
| alien introgression | 5.16 |
| allele-specific transcriptome analysis | 1.03 |
| alpha-amylase and trypsin inhibitor | 3.03 |
| alpha-amylase inhibitor | 3.02 |
| ALS | 4.04 |
| Amaranthus hybridus | 4.04 |
| AMF colonization | 2.05 |
| ancestral relationship | 7.36 |
| Anemone | 7.11 |
| anthesis | 4.23 |
| anthocyanin | 4.08, 7.41 |
| anti-malarial activity | 6.09 |
| anti-nutritional factors | 3.01 |
| antinutritional compounds | 3.06, 3.09 |
| antinutritional factors | 3.08 |
| antioxidant capacity | 3.04 |
| antioxidant compounds | 4.05 |
| antioxidants | 1.11, 6.02 |
| apple | 4.22 |
| apple-pear hybrid | 7.28 |
| Arabidopsis | 5.19 |
| Artemisia annua | 6.09 |
| artemisinin | 6.09 |
| ascorbic acid | 7.12, 7.24 |
| autochthonous cultivars | 7.33 |
| autoimmune diseases | 6.03 |
| autopolyploidy | 7.25 |
| B | |
| barley | 1.39, 2.02, 4.27, 7.08, 7.44 |
| berry ripening | 4.06 |
| bioactive compounds | 3.09 |
| bioagents | 4.29 |
| bioassays | 4.29 |
| bioavalaibility | 6.11 |
| bioclimatic diversity | 4.03 |
| biodiversity | 3.06 |
| bioinformatic tools | 7.03 |
| bioinformatics | 4.09 |
| biomass accumulation | 2.02 |
| biopharmaceuticals | 6.02 |
| biorefinery | 6.10, 6.12 |
| biotic stress | 1.35, 4.08 |
| biotransformation | 7.09 |
| black lemma and pericarp | 1.39 |
| blast disease | 1.12 |
| blast resistance | 1.12 |
| Botrytis cinerea | 1.27 |
| breeding | 5.16, 7.07, 7.11, 7.21 |
| broccoli sprouts | 6.11 |
| bromatological analyses | 4.12 |
| broomrapes | 7.48 |
| BSA-seq | 7.04 |
| bud dormancy | 4.11 |
| C | |
| Camelina sativa | 4.12 |
| candidate genes | 2.06, 4.15, 7.38 |
| Candidatus liberibacter | 1.21 |
| cannabis | 4.16 |
| CAPS | 7.13 |
| carbohydrate pathways | 3.05 |
| cardoon callus cultures | 6.12 |
| carotenoids | 1.10, 7.40 |
| cell cultures | 6.10 |
| chicory | 7.36 |
| chilling requirement | 4.11 |
| chip | 1.36 |
| chitin receptor | 1.29 |
| chlorophyll content | 2.02 |
| chloroplast-to-nucleus communication | 7.37 |
| chromatin modifications | 4.11 |
| chromium | 5.04 |
| chromosome engineering | 5.15, 5.16 |
| cisgenesis | 7.19 |
| cistrome | 4.28 |
| Citrus | 4.05 |
| climate change | 1.11, 1.37, 2.01, 5.09 |
| climate-driven vulnerability | 4.03 |
| climatic change | 1.34, 5.10 |
| co-expression analysis | 1.38 |
| cold stress | 5.11 |
| combined DNA fingerprint | 7.36 |
| combined stress | 5.05 |
| common bean | 1.30 |
| comparative genomics | 1.27, 5.11 |
| comparative transcriptomics | 5.02 |
| complex traits | 1.25 |
| conservation variety | 1.23 |
| conservative agriculture | 1.33 |
| copper | 6.07 |
| correlation analysis | 7.35 |
| CRISPR-Cas9 gene silencing | 3.03 |
| CRISPR-Cas9-based enrichment | 1.13 |
| CRISPR/Cas9 | 4.05, 4.20, 4.26, 7.18, 7.20, 7.32, 7.43, 7.48 |
| crop protection | 4.29 |
| crop yield | 7.30 |
| Cucumis melo L. | 1.31 |
| Cucurbita maxima | 1.10 |
| Cucurbita pepo | 7.09 |
| culm | 4.27 |
| cultivar-specific genome | 1.13 |
| cultivated cardoon | 5.11 |
| cultivation history | 4.09 |
| Curcuminoids | 6.05 |
| cuticle | 7.49 |
| cv Microtom | 5.14 |
| D | |
| DAP-seq | 4.06, 4.28, 4.30, 4.31 |
| de-novo assembly | 1.13, 7.02 |
| defense responses | 5.13 |
| denaturing gradient gel electrophoresis | 1.31 |
| development | 7.30 |
| diary cow manure | 6.08 |
| diatoms | 6.07 |
| Dioecious | 4.16 |
| Diplotaxis | 7.27 |
| DMR6 | 7.43 |
| DNA markers | 1.07 |
| DNA methylation | 4.08, 4.11, 4.22 |
| DNA-Seq | 1.03 |
| domestication | 1.03, 1.05 |
| domestication genes | 1.06 |
| dormancy | 4.19 |
| downy and powdery mildew | 7.06 |
| downy mildew | 7.18 |
| drought | 5.05, 5.18, 5.20 |
| drought stress | 4.13, 5.06, 5.22 |
| drought tolerance | 5.02, 5.16 |
| drug delivery | 6.11 |
| dsRNAs | 4.04 |
| durum wheat | 1.08, 1.23, 2.08, 3.10, 4.25, 5.10, 5.22, 7.19, 7.22, 7.26, 7.34, 7.45 |
| E | |
| ear prolificacy | 7.16 |
| eggplant | 7.41 |
| Emilia Romagna | 1.18, 1.19 |
| EMS mutagenesis | 1.32 |
| endemic plant | 1.28 |
| endive leaves | 5.03 |
| endoplasmic reticulum | 3.07 |
| environmental sensor | 7.37 |
| environmental stresses | 5.18 |
| epigenetic regulation | 7.41 |
| epigenetics | 4.21, 4.22, 5.04, 5.08, 7.21 |
| ex situ conservation | 1.18 |
| exaptation | 7.03 |
| expression atlas | 4.23 |
| expression Quantitative Trait Loci (eQTL) mapping | 2.03 |
| external factors | 1.38 |
| extracellular vesicles | 6.04 |
| F | |
| False flax | 3.08 |
| FAs | 4.10 |
| fasciation | 7.14 |
| fatty acids | 6.12, 7.47 |
| fertility | 2.07 |
| Ficus carica L. | 1.17 |
| fine mapping | 7.38 |
| flavor | 7.21 |
| flowering | 4.19 |
| food security | 1.09, 1.11, 1.14 |
| food traceability | 7.13 |
| forest trees | 4.15 |
| free asparagine | 1.08 |
| fruit development | 7.05 |
| fruit developmental stages | 7.33 |
| fruit quality | 4.18, 7.24 |
| fruit ripening | 4.31 |
| fruits | 4.05 |
| functional biodiversity | 1.34 |
| functional foods | 3.10 |
| fungal disease | 7.19 |
| Funneliformis mosseae | 2.05 |
| Fusarium | 7.27 |
| Fusarium culmorum | 7.39 |
| G | |
| GBS | 1.16, 4.09, 4.12 |
| GCN | 4.28 |
| gene characterisation | 4.21 |
| gene co-expression network | 5.02 |
| gene co-expression network analysis | 5.07 |
| gene duplication | 1.27 |
| gene editing | 3.08, 7.17 |
| gene espressione regulation | 5.12 |
| gene expression | 4.08, 7.33 |
| gene expression analysis | 4.29 |
| gene knock-out | 7.12 |
| gene regulation | 4.31 |
| gene silencing | 4.04 |
| Genebank | 1.02 |
| genetic characterisation | 1.18, 1.19, 1.20 |
| genetic diversity | 1.01, 1.07, 1.16, 1.23, 1.26, 1.33, 7.42 |
| genetic progress | 2.01 |
| genetic resources | 1.30, 7.40 |
| genetic structure | 4.18 |
| genetic variability | 1.17 |
| genetics | 1.22 |
| genome annotation | 1.17 |
| genome assembly | 1.17 |
| genome editing | 1.06, 1.35, 5.09, 7.06, 7.18, 7.24 |
| genome evolution | 7.03 |
| genome re-sequencing | 7.41 |
| Genome Wide Association Mapping | 1.04 |
| Genome Wide Association Studies (GWAS) | 2.03 |
| Genome Wide Association Study | 4.03 |
| genomic prediction | 2.01, 4.07, 7.29 |
| genomic selection | 7.07, 7.26 |
| genomics | 1.09, 7.04, 7.07 |
| genotype x environment | 1.30 |
| genotyping | 4.16 |
| germplasm | 1.34 |
| germplasm collection | 1.26 |
| Global Durum Panel | 1.08 |
| globe artichoke | 7.04 |
| glutathione transferase | 5.18 |
| GoldenBraid | 4.26 |
| GoldenBraid 3.0 | 4.05 |
| grafted plant | 2.05 |
| grafting | 4.22 |
| grain | 2.07 |
| grain number | 5.16 |
| grain number increase | 2.08 |
| Grain Protein Content | 7.22 |
| grain size | 2.06 |
| grain yield | 2.02, 2.06, 7.26 |
| Gramineae | 5.02 |
| grapevine | 1.36, 1.37, 4.06, 4.28, 4.30, 4.31, 7.46 |
| grapevine flower | 4.23 |
| Greening | 1.21 |
| GRF | 2.04 |
| growth | 4.02 |
| growth promotion | 7.39 |
| GRXs | 1.27 |
| GS/GOGAT cycle | 7.22 |
| GTR transporters | 3.08 |
| GWAS | 1.02, 1.08, 1.09, 1.12, 1.16, 1.24, 1.37, 4.18, 7.29, 7.38, 7.47 |
| H | |
| hairy roots | 7.17 |
| HD-Zip transcription factors | 7.05 |
| heat shock | 5.15 |
| heat stress | 4.25, 5.05, 5.14 |
| Helianthus annuus | 7.03 |
| Hi-C | 7.02 |
| high-density consensus map | 1.36 |
| high-throughput phenotyping | 4.02 |
| Hordeum vulgare | 5.21, 7.08 |
| HRM | 7.28 |
| I | |
| ICP-MS | 6.07 |
| iku1 | 4.26 |
| Illumina | 1.21 |
| in situ and ex situ conservation | 1.20 |
| in situ conservation | 1.19 |
| industrial hempseeds | 3.04 |
| inflorescence | 5.21 |
| Inflorescence Architecture | 7.30 |
| inhibition growth | 6.07 |
| invertase | 7.17 |
| iron starvation | 5.04 |
| ITS | 1.31 |
| J | |
| juvenile and adult leaves | 7.49 |
| K | |
| KASP | 7.38 |
| kernel texture | 3.10 |
| kernerl row number | 7.14 |
| Kunitz-trypsin inhibitor | 3.01 |
| L | |
| L-proline transporter | 5.14 |
| laccase | 2.04 |
| landraces | 1.15, 1.30, 7.45 |
| landscape genomics | 1.14, 4.03 |
| lectins | 3.02 |
| legumes | 1.06, 1.33, 3.02 |
| lignin | 6.10 |
| Lipid Transfer Proteins | 7.23 |
| lipoxygenase | 7.20 |
| local biodiversity safeguard | 7.31 |
| local maize | 1.19 |
| local varieties | 5.17 |
| lodging resistance | 4.27 |
| low phytic acid mutants | 4.13 |
| LysM | 1.29 |
| M | |
| MAGIC | 1.22, 4.07 |
| maize | 1.15, 1.26, 1.34, 4.13, 7.14, 7.16, 7.49 |
| maize germplasm | 1.18 |
| male sterility | 7.04 |
| malt | 3.04 |
| mandarins | 4.26 |
| Marker Assisted Selection | 1.04, 7.46 |
| Marker-Trait Associations | 1.12 |
| MAS | 4.12 |
| MCSeEd | 4.22 |
| Medicago sativa | 7.25 |
| Medulloblastoma Targeting peptides | 6.06 |
| meiosis | 4.21 |
| melatonin | 5.17 |
| meta-analysis | 1.35, 4.15 |
| metabolic characterisation | 1.20 |
| metabolic characterization | 7.40 |
| metabolic engineering | 6.05, 6.09, 6.12 |
| metabolic pathway | 7.35 |
| metabolites | 3.09 |
| metabolomics | 5.22 |
| metagenomics | 1.33 |
| metal hyperaccumulation | 7.10 |
| microarray | 4.14, 7.35 |
| microRNAs | 5.15 |
| microsatellites | 4.16, 7.11, 7.31 |
| miRNA | 6.11, 7.10 |
| modelling | 2.01 |
| molecular diagnostics | 6.03 |
| molecular fingerprinting | 7.33 |
| Monoecious | 4.16 |
| morphological traits | 1.23 |
| mountain environment | 1.15 |
| Mozambique | 1.14 |
| multi-locus GWAS | 1.25 |
| multigenic family | 7.23 |
| multiparental populations | 2.03 |
| mutagenesis | 7.08, 7.32 |
| mutant population | 1.32 |
| mutants | 3.08, 4.21 |
| MYB | 6.10 |
| N | |
| N-forms | 5.19 |
| NAC TFs | 4.06 |
| nanoferitlization | 7.09 |
| Nanopore sequencing | 1.13 |
| nanovescicles | 6.11 |
| Near Isogenic lines | 7.22 |
| necrotics | 7.08 |
| neglected and underutilized crop species | 4.03 |
| New breeding techniques | 4.24 |
| new plant breeding techniques | 7.12 |
| Next generation sequencing NGS | 7.08 |
| NGS-technologies | 4.30 |
| nitrate | 5.07 |
| nitrogen | 4.19 |
| nitrogen recovery | 6.08 |
| Nitrogen Use Efficiency | 5.07, 5.19, 7.22 |
| Non Celiac Wheat Sensitivity | 3.03 |
| NUC | 1.09 |
| nutrient stress | 5.20 |
| nutrition | 1.11, 7.10 |
| nutritional compounds | 3.06 |
| O | |
| Ocimum basilicum cv. FT Italiko | 7.18 |
| oilseed | 7.23 |
| Olea europaea | 7.33 |
| olive | 1.07, 7.02 |
| olive fruit | 4.10 |
| olive oil | 7.47 |
| ornamentals | 7.11 |
| Oryza sativa | 1.01, 5.21 |
| osmotic adjustment | 5.22 |
| ovule development | 7.05 |
| Oxford Nanopore | 1.21 |
| P | |
| P sustainability | 4.13 |
| pan-genome | 1.05 |
| parthenocarpy | 7.05 |
| participatory variety selection | 1.14 |
| pathogen resistance | 7.20 |
| pathology | 7.43 |
| pea | 4.09 |
| peach | 4.19 |
| pedigree method | 1.10 |
| pepper | 1.02, 5.17 |
| Phaseolus vulgaris | 1.06, 1.32 |
| Phelipanche ramosa | 7.48 |
| phenilpropanoids | 4.10 |
| phenology | 7.46 |
| phenols | 7.47 |
| phenomics | 2.01 |
| phenotypic descriptors | 7.31 |
| phenotyping | 1.22, 1.32, 4.21, 7.47 |
| phenylpropanoids | 4.17 |
| photoperception | 4.10 |
| photosynthesis | 2.02 |
| photosynthetic mutants | 7.44 |
| phycoremediation | 6.07, 6.08 |
| phytic acid | 3.02 |
| phytohormones | 5.21 |
| plant | 6.05 |
| plant as biofactories | 6.06 |
| plant bioreactor | 6.02 |
| plant breeding | 1.10, 4.12 |
| plant conservation | 1.28 |
| plant development | 4.17, 5.08 |
| plant growth | 5.13 |
| Plant Molecular Farming | 6.03 |
| plant regeneration | 7.06 |
| plant resistance | 7.46 |
| plant stem cells | 6.02 |
| Plant Virus Nanoparticles | 6.03, 6.06 |
| plant virus nanoparticles drug loading | 6.06 |
| plant-pathogen interactions | 6.04 |
| plant-soil interaction | 5.12 |
| plasticity | 5.12 |
| plastid development | 7.37 |
| plastids | 7.37 |
| PMR4 | 4.20 |
| pointed maize | 1.15 |
| pollen | 7.09 |
| polyphenol content | 7.33 |
| Pomella genovese | 1.20 |
| poplar | 7.29 |
| population genetic structure | 1.28 |
| population genomics | 1.02 |
| PPR | 7.44 |
| Pre Breeding | 1.04 |
| primary metabolites | 7.40 |
| priming | 5.17 |
| proso millet | 1.09 |
| protein body biogenesis | 3.07 |
| protein complex | 5.08 |
| Prunus | 4.24 |
| Prunus dulcis | 7.31 |
| PTR-ToF-MS | 4.18 |
| purple color | 1.38 |
| Q | |
| QTL | 7.14, 7.16, 7.34 |
| QTL cluster | 2.06 |
| QTL mapping | 2.08 |
| QTL/GWAS | 4.02 |
| QTLome | 1.04 |
| quality | 7.21 |
| quantitative trait loci | 4.27 |
| quantitative trait locus | 1.24 |
| Quantitative Trait Nucleotides | 1.25 |
| quinoa | 5.01 |
| R | |
| R | 4.14 |
| rain excess waterlog | 5.03 |
| RAPD | 1.28 |
| rDNA | 1.31 |
| real time PCR | 5.10 |
| Red Sea Farms | 5.01 |
| reference genome | 1.01, 7.02 |
| regulatory network | 4.06 |
| relative water content | 5.22 |
| reproductive level | 5.14 |
| resistance | 1.07, 4.20, 7.06 |
| resistance genes | 1.21 |
| resistance inducers | 4.29 |
| resistance QTL | 7.29 |
| rice | 1.12 |
| RNA-seq | 2.05, 4.11, 4.14, 4.19, 5.03, 5.07, 7.09, 7.25, 7.34, 7.38, 7.41 |
| RNA-sequencing | 1.35 |
| RNAi | 4.04 |
| RNAi gene silencing | 3.03 |
| rocket | 7.27 |
| root architecture | 1.24 |
| root exudate | 6.04 |
| root growth angle (RGA) | 7.34 |
| root system architecture | 4.13 |
| root system traits | 7.42 |
| routes of diversification | 1.02 |
| RRS | 5.05 |
| rye | 7.15 |
| S | |
| salinity tolerance | 5.01 |
| salt | 5.18 |
| salt stress | 5.06, 5.11, 5.13, 7.27 |
| secondary metabolite | 5.12, 7.28 |
| seed | 3.02, 3.06, 3.09, 5.17 |
| seed coating | 7.39 |
| seed development | 3.07 |
| seed size | 2.04 |
| seedless | 4.26 |
| selective sweeps | 1.05, 4.09 |
| seminal root angle | 4.07 |
| seminal root number | 4.07 |
| Seminal root trait | 1.24 |
| Septoria Tritici Blotch | 7.45 |
| sequencing | 1.01 |
| Shiny | 4.14 |
| side effects | 3.05 |
| SlDET1 gene | 7.32 |
| smallholder farming | 7.07 |
| smallholder farming systems | 1.14 |
| SNP | 1.16, 1.36, 7.13, 7.25 |
| SNP-chip | 7.28 |
| SNPs | 1.29, 1.31 |
| soil drench | 5.13 |
| soil-borne cereal mosaic virus | 1.08 |
| Solanaceae | 7.37 |
| Solanum lycopersicum | 5.18, 7.24 |
| Solanum melongena | 1.05 |
| Solanum pennelli | 5.06 |
| Solanum pennelli introgression lines | 7.48 |
| Solanum tuberosum | 4.17 |
| source-sink relation | 2.04 |
| soybean | 3.01 |
| spike | 2.07 |
| spike fertility | 2.08 |
| SSR | 7.28 |
| starch mutants | 3.05, 3.10 |
| STB | 7.45 |
| stomata | 5.09 |
| storage proteins | 3.07, 3.09 |
| straw composition | 1.25 |
| stress memory | 5.04 |
| stress physiology | 5.15 |
| strigolactones | 7.48 |
| structural variation | 1.39 |
| sugar and inulin pathway | 5.03 |
| sulfur assimilatory pathway | 3.01 |
| sunflower | 7.23 |
| susceptibility | 7.43 |
| susceptibility genes | 4.20 |
| sustainability | 3.10, 7.18 |
| sustainable agriculture | 1.34 |
| sustainable production | 6.12 |
| SWEET | 2.04 |
| sweet cherry | 1.16 |
| sweet orange | 4.08 |
| systemin | 5.13 |
| T | |
| targeted RNA | 4.10 |
| targeted-resequencing | 4.25 |
| tau analysis | 4.23 |
| terraced environment | 7.15 |
| Tillering | 7.16 |
| TILLING | 1.32 |
| TILLING-by-sequencing | 1.06 |
| tissues | 1.38 |
| tocopherols | 3.04 |
| tomato | 1.22, 1.27, 2.05, 4.01, 4.20, 5.06, 5.07, 5.20, 7.05, 7.17, 7.21, 7.43 |
| Tomato Bushy Stunt Virus | 6.06 |
| tomato fruit | 7.32 |
| tomato landraces | 7.40 |
| tomato nutritional quality | 7.12 |
| tomatoes | 5.01 |
| TOMRES | 5.20 |
| transcript | 7.35 |
| transcription factor | 5.11 |
| transcription factors | 1.38, 4.30, 5.02, 7.30 |
| transcription regulation | 4.28 |
| transcriptome | 3.05 |
| transcriptomics | 4.14, 5.08, 7.25 |
| transformed plants | 5.14 |
| transgenerational | 5.04 |
| transient expression | 6.09 |
| transpiration | 4.02 |
| transpiration rate | 4.07 |
| transposable elements | 7.03 |
| Trichoderma sp. | 7.39 |
| trichome | 4.17 |
| Triticum turgidum | 1.04 |
| trypsin inhibitors | 3.04 |
| U | |
| untargeted metabolic profiling | 5.03 |
| unwanted variation | 7.35 |
| V | |
| varaison | 1.37 |
| variability | 1.22 |
| virus-like particles | 6.03 |
| Vitis 18KSNPChip | 1.37 |
| Vitis vinifera | 1.03, 5.09, 7.06, 7.20 |
| Vitis18K | 1.36 |
| VOCs | 4.18 |
| VvNAC03 | 4.31 |
| W | |
| water-use efficiency | 4.02 |
| Weighted Gene Co-expression Network Analysis (WGCNA) | 2.03 |
| WGCNA | 4.23, 5.19 |
| wheat | 1.25, 1.33, 2.06, 2.07, 3.03, 3.05, 7.07, 7.15, 7.39 |
| whole genome resequencing | 1.05, 7.42 |
| wild germplasm | 5.15 |
| wild grapevines | 1.29 |
| wild species | 7.24 |
| Woolly Poplar Aphid | 7.29 |
| WRKY | 5.10 |
| WRKY3 | 4.30 |
| X | |
| XP | 7.01 |
| Xylella fastidiosa | 1.07 |
| Y | |
| yellow tomato | 7.13 |
| yield | 5.16 |
| yield increment | 2.08 |
| Z | |
| Zea mays | 2.03, 7.20 |
| zeins | 3.07 |
| ZmFDL1 | 7.49 |
| ZmGL15 | 7.49 |
| Zn homeostasis | 7.10 |
| Zymoseptoria tritici | 7.45 |
| ° | |
| °Brix | 7.17 |
| 1 | |
| 1954 sampling | 1.18 |