
LXVI SIGA Annual Congress
Climate-smart plants to feed the future
Bari, 5-8 September 2023
Session 1 – Omics to study and use genetic resources in plant breeding
Session 2 – Breeding for resilience: addressing climate change in plant genetics
Session 3 – Innovative methods and tools in plant genetics and breeding
Session 4 – Underground genetics: roots and their interactions
Session 5 – Exploring the plant epigenomes
Session 6 – Fruit and forest trees genomics, genetics and breeding
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Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti |
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Dipartimento di Scienze Agrarie, Alimenti, Risorse Naturali e Ingegneria |
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Under the patronage of: |
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With the support of: |
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Programme
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TUESDAY, SEPTEMBER 5th
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| 13:00 – 14:30 | Registration | |
| 14:30 – 14:50 | Opening ceremony Chairpersons: Filippone E., Ricciardi L., Lotti C.Welcome addresses by Institutional and Local Authorities |
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| 14:50 – 15:00 | Communication from EIT-FOOD Projectmanager at UNIBA De Ruggeri B. EIT Food: Innovation for a healthy and sustainable food system |
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| 15:00 – 16:45 | Session 1 – Omics to study and use genetic resources in plant breeding Chairpersons: Ambrosone A., Mazzucotelli E. |
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| 15:00 – 15:30 | Invited Lecture Iorizzo M. Omics approach to uncover the origin of high carotenoid orange carrots |
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| 15:30 – 15:45 | Forestan C., Bozzoli M., Maccaferri M., Tuberosa R., Mazzucotelli E., Desiderio F., Faccioli P., Cattivelli L., Ens J., Sharpe A., Pozniak C., Chawla H., Walkowiak S., Pirona R., Ceriotti A., Morgante M., Masci S., Sestili F., Giuliano G., Gadaleta A., Pè M.E., Pecchioni N., Bassi F.M., Distelfeld A., Rusholme-Pilcher R., Hall A., Swarbreck D., Spannagl M., Navratilova P., Šimková H., Silvestri M., Zastrow-Hayes G., Llaca V., Fengler K., The Svevo Platinum Consortium, The Tetraploid Wheat Pangenome Consortium Upgrading the Durum wheat Genomic Resources: from the Platinum-quality Svevo genome assembly and annotation to the tetraploid wheat pangenome |
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| 15:45 – 16:00 | Miculan M., Zuccolo A., Fabbian L., Zhou Y., Rivera L.F., Copetti D., Talag J.D., McNally K., Henry A., Wing R.A. Disentangling the genome wide contribute of structural variations to drought stress resistance in the model species Oryza sativa |
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| 16:00 – 16:15 | Gabelli G., Palumbo F., Boni A.G., Ferrari G., Beretta M., Barcaccia G. Deciphering the recombination spots scenario in a MAGIC population of cultivated and wild tomato |
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| 16:15 – 16:30 | Tripodi P., Beretta M., Peltier D., Kalfas I., Vasilikiotis C., Laidet A., Briand G., Aichholz C., Zollinger T., van Treuren R., Scaglione D., Goritschnig S. Development and application of single primer enrichment technology (SPET) SNP assay for population genomics analysis and candidate gene discovery in lettuce |
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| 16:30 – 16:45 | Gaccione L., Toppino L., Sulli M., Tumino G., Alonso D., Aprea G., Tassone M.R., Boyaci H.F., Lin Y., Lanteri S., Prohens J., Portis E., Rotino G.L., Giuliano G., Barchi L. Genome-wide association study for agronomically relevant traits and fruit quality-related metabolites in a worldwide eggplant core collection |
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| 16:45 – 17:15 | Coffee Break and Poster Viewing | |
| 17:15 – 18:45 | Session 1 – (cont.) | |
| 17:15 – 17:30 | Americo S., Ferrari G., Desiderio F., Guerra D., Beretta M., Lo Piero A.R., Sicilia A., Morelli G., Cattivelli L., D’Orso F. Unveiling the position and effects on salt stress resilience of wild S. pennellii genome in S. pennellii x S. lycopersicum introgression lines through integrated DNA and RNA sequencing approach |
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| 17:30 – 17:45 | Tafuri A., Pirona R., Fricano A., Mazzucotelli E., Cagliani L.R., Gasser M., Giordano M., Zuccaro M., Ravaglia S., Consonni R., Thomas A., Gilardi F., Ceriotti A., Baldoni E. Metabolite characterization of durum wheat grain for association studies: exploring the natural variation of free asparagine content |
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| 17:45 – 18:00 | Delvento C., Arcieri F., Marcotrigiano A.R., Guerriero M., Fanelli V., Dellino M., Curci P.L., Bouwmeester H., Lotti C., Ricciardi L., Pavan S. High-density linkage mapping and genetic dissection of resistance to broomrape (Orobanche crenata Forsk.) in pea (Pisum sativum L.) |
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| 18:00 – 18:15 | Bono G.A., Giaume F., Vicentini G., Mineri L., Betagnon G., Fornara F., Brambilla V. Molecular control of flowering at the rice shoot apex |
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| 18:15 – 18:30 | Foresti C., Amato A., Fattorini C., D’Incà E., Vitulo N., Zenoni S. NACs intra-family hierarchical regulatory network orchestrating grape berry ripening |
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| 18:30 – 18:45 | General discussion | |
| 19:00 – 20:30 | Welcome Cocktail | |
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WEDNESDAY, SEPTEMBER 6th
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| 09:00 – 10:45 | Session 2 – Breeding for resilience: addressing climate change in plant genetics Organized by Next Generation SIGA Chairpersons: Broccanello C., Di Marsico M. |
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| 09:00 – 09:30 | Invited Lecture Dixon L. Adapting cereal development to changing climates |
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| 09:30 – 09:45 | Persello A., Rotasperti L., Torricella V., Ballabio F., Betti A., Tadini L., Camilloni C., Hansson M., Rossini L., Horner S.D., Salvi S., Pesaresi P. Pale-green crops for a new sustainable agriculture |
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| 09:45 – 10:00 | Bubici G., Batelli G., Cellini F., Costa A., De Palma M., Grillo S., Melillo M.T., Petrozza A., Prigigallo M.I., Ruocco M., Sportelli G., Stavolone L., Summerer S., Veronico P., Cillo F. A phenomics approach to drought and pathogen responses in a tomato genotype collection |
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| 10:00 – 10:15 | De Sario F., Liu C., Bozzoli M., Forestan C., Ratti C., Bruschi M., Novi J.B., Campana M., Sciara G., Ormanbekova D., Corneti S., Confortini A., Viviani A., Stefanelli S., Giulini A., Bardelli T., Novarina E., Gadaleta A., Mazzucotelli E., Desiderio F., Viola P., Invernizzi C., Oliveri F., Mastrangelo A.M., Marone D., Roncallo P., Bassi F., Perovic D., Cattivelli L., Tuberosa R., Maccaferri M. The Global Durum Genomic Resource in use: a collaborative genomics initiative to leverage genetic resources for increasing and characterizing the breeding value of durum varieties |
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| 10:15 – 10:30 | Colanero S., Martignago D., Loukili I., Sutti A., Landoni B., Cioffi S., Bosc A., Tonelli C., Galbiati M., Conti L. Engineering water use in tomato by generating SlMyb60 mutants using a CRISPR-Cas9- based approach |
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| 10:30 – 10:45 | General Discussion | |
| 10:45 – 11:15 | Coffee Break and Poster Viewing | |
| 11:15 – 13:15 | Session 3 – Innovative methods and tools in plant genetics and breeding Chairpersons: Lotti C., Pavan S. |
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| 11:15 – 11:45 | Invited Lecture Bai Y. Impaired plant susceptibility genes in resistance breeding: from concept to cultivars |
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| 11:45 – 12:00 | Bettinelli P., Bianco L., Fontana P., Moser M., Pindo M., Nicolini D., Costantini L., Stefanini M., Hausmann L., Vezzulli S. Black rot resistance of grapevine: from organ-specific QTL mapping to the sequencing of the donor towards candidate gene identification |
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| 12:00 – 12:15 | Li R., Cui L., Martina M., Moglia A., Bracuto V., Meijer-Dekens F., Wolters A.A., Bai Y., Acquadro A. Less is more: CRISPR/Cas9-based mutations in DND1 gene enhance tomato resistance to powdery mildew with low fitness costs |
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| 12:15 – 12:30 | Caproni L., Altman T., Ferguson J., Heuermann M., Kromdijk J., Pè M.E., Dell’Acqua M. Combining phenomics approaches from pot to plot to identify candidate genes for photosynthesis improvement in the multi parent MAGIC maize population |
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| 12:30 – 12:45 | Bozzoli M., Bruschi M., Fanelli Carvalho H., Isidro y Sánchez J., Ruggeri M., Meriggi D., Manstretta V., Bartoccetti E., Sgrelli S., Meriggi P., Tuberosa R., Maccaferri M. INNOVAR project: developing high-throughput phenotyping and genetic methods and technologies to improve accuracy in agriculture and in wheat varietal registration protocols |
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| 12:45 – 13:00 | Michelotti V., Rossi R., Crosatti C., Mica E., Guerra D., Colombo M., Masiero S., Radchuk V., Cattivelli L., Battaglia R. Sporophytic control of male fertility, the role of the SWEET4 gene in barley |
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| 13:00 – 13:15 | General Discussion | |
| 13:15 – 13:30 | EUCARPIA: current progressive future opportunity for plant breeding Ercolano M.R. |
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| 13:30 – 14:30 | Lunch Break | |
| 14:30 – 16:30 | Session 4 – Underground genetics: roots and their interactions In memory of Marina Tucci Chairpersons: Beretta M., Salvi S. |
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| 14:30 – 15:00 | Invited Lecture Laplaze L. Targeting root traits to improve tolerance to vegetative drought episodes in pearl millet (Pennisetum glaucum L.) |
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| 15:00 – 15:15 | Puglisi D., Carletti G., Delbono S., Cattivelli L., Fricano A. Shovelomics and clear pot analyses highlight extensive natural genetic variation for root system architecture in barley |
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| 15:15 – 15:30 | Daddiego L., Bianco L., Alagna F., Lopez L., Panara F., Fantini E., Facella P. Differential expression patterns of cryptochrome and circadian clock genes between roots and leaves in Medicago truncatula |
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| 15:30 – 15:45 | Scintu D., Shtin M., Svolacchia N., Sabatini S., Dello Ioio R., Di Mambro R. Exploring root programmed cell death as a mechanism for heat stress resilience |
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| 15:45 – 16:15 | Invited Lecture Pieterse C.M.J. The root microbiome and plant immunity |
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| 16:15 – 16:30 | General Discussion | |
| 16:30 – 17:00 | SIGA Young Research Award 2023 Dedicated to Francesco D’Amato and Gian Tommaso Scarascia Mugnozza Chairpersons: Filippone E., Rosellini D. |
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| Rotasperti L. The barley mutant happy under the sun 1 (hus1): An additional contribution to pale green crops |
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| Iohannes S.D. Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates |
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| Award ceremony | ||
| 17:00 – 17:45 | Coffee Break and Poster Viewing | |
| 17:45 – 19:30 | SIGA General Assembly | |
| THURSDAY, SEPTEMBER 7th | ||
| 09:00 – 10:15 | Session 5 – Exploring the plant epigenomes Chairpersons: Comino C., Varotto S. |
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| 09:00 – 09:30 | Invited Lecture Zilberman D. Long-term epigenetic inheritance and phenotypic diversity in natural populations |
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| 09:30 – 09:45 | Bevilacqua I., Moffa L., Varotto S., Chitarra W., Nerva L. Harnessing genome editing to elucidate the role of histone variant H2A.Z in grapevine |
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| 09:45 – 10:00 | Liva M., Magris G., Di Gaspero G., Schwope R., Catacchio C.R., Daponte A., Ventura M., Morgante M. Analysis of genetic and epigenetic structure and variability of grapevine centromeres through the use of long read sequencing and T2T assemblies |
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| 10:00 – 10:15 | General Discussion | |
| 10:15 – 11:30 | Coffee Break and Poster Viewing | |
| 11:30 – 12:30 | Session 6 – Fruit and forest trees genomics, genetics and breeding Chairpersons: Giannino D., Montemurro C. |
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| 11:30 – 12:00 | Invited Lecture Gonzalez Martinez S. Population vulnerability of a keystone Mediterranean tree under future climate – an ecological genomics approach |
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| 12:00 – 12:15 | Garosi C., Vettori C., Bajc M., Kraigher H., Westergren M., Dovč N., Damjanić R., Sever K., Breznikar A., Gregoric A., Lanšćak M., Ivankovic M., Bogunović S., Paffetti D. Genome-wide SNP association analysis reveals genomic signature of local adaptation in European beech (Fagus sylvatica L.) |
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| 12:15 – 12:30 | Alicandri E., Sebastiani B., Paolacci A.R., Sorgonà A., Manti F., Bosignore C.P., Badiani M., Ciaffi M. Terpenoids and the expression of terpene synthase genes are coherently and selectively modulated in Calabrian pine (Pinus nigra subs. laricio) in response to pine processionary moth (Thaumetopoea pityocampa) infestation |
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| 13:00 – 14:30 | Lunch Break | |
| 14:30 – 17:15 | Session 6 – (cont.) | |
| 14:30 – 15:00 | Invited Lecture Decroocq V. Genetic diversity and use of stone fruit tree wild relatives for a more sustainable fruit production |
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| 15:00 – 15:15 | Cominelli E., Beritognolo I., Cardoni S., Forti C., Cherubini M., Leonardi L., Leone P.A., Sparvoli F., Biffani S., Stella A., Toschi I., Cesari V., Chiozzotto R., Cirilli M., Pozzi C., Mattioni C. Chestnut cultivation development in Lombardy: leveraging native genetic resources in two pilot areas |
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| 15:15 – 15:30 | Costa F., Busatto N., Sayantan P., Vittani L., Populin F., Khomenko I., Biasioli F., Vrhovsek U., Aharoni A., Zanella A. System genetics approach disclosed the genetic architecture of the chilling injury disorder superficial scald in apple |
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| 15:30 – 15:45 | Simoni S., Castellacci M., Usai G., Giordani T., Natali L., Cavallini A., Besnard G., Mascagni F. Genomic dynamics of olive trees in the Mediterranean basin: insights from the repetitive component evolution |
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| 15:45 – 16:00 | Bonghi C., Canton M., Joseph J., Marconi G., Forestan C., Varotto S. The bud peach dormancy dilemma |
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| 16:00 – 16:15 | da Silva Linge C., Baccichet I., Chiozzotto R., Gasic K., Fu W., Byrne D., Rawandoozi Z., Worthington M., Bassi D., Cirilli M., Hardner C., Rossini L. Unlocking genetic diversity for peach fruit acidity through global GWAs and genomic prediction-based selection |
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| 16:15 – 16:30 | Michelotti V., Gentile A., Scortichini M., Lucioli S., Caboni E., Tacconi G. Applyication of a CRISPR/CAS9 vector in A. chinensis var. chinensis to induce Pseudomonas syringae pv. actinidiae resistance/tolerance |
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| 16:30 – 16:45 | Sicilia A., Villano C., Di Serio E., Aversano R., Ferlito F., Nicolosi E., Lo Piero Angela R. Transcriptome analysis reveals plasticity of gene expression in wine grape cultivars grown at different latitudes in southern Italy |
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| 16:45 – 17:00 | Bolognesi G., Crespan M., Broccanello C., Delfino P., Mora R., Marini M., Gardiman M., Giust M., Tomasi D., Bellin D. Genome wide association analysis of phenology related traits in Vitis vinifera L. |
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| 17:00 – 17:15 | General Discussion | |
| 17:15 – 17:45 | Coffee Break and Poster Viewing | |
| 17:45 – 19:45 | Parallel Poster Sessions | |
| 20:30 | Social Event (Sala Zonno, Molo S. Nicola 3, Bari) | |
| FRIDAY, SEPTEMBER 8th | ||
| 09:30 – 12:15 | Session 7 – Updates and upgrades in genome editing Chairpersons: Lanubile A., Nigro D. |
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| 09:30 – 10:00 | Invited Lecture Cereseto A. Expanding the genome editing toolbox by unlocking RNA guided nucleases using massive metagenomic data |
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| 10:00 – 10:15 | Vicentini G., Bertagnon G., Giaume F., Fornara F., Brambilla V. Controls of stem elongation by the flowering pathway in rice |
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| 10:15 – 10:30 | Vaccino P., Sansoni F., Volante A., Zampieri E., Salvi S., Camerlengo F., Pierbattista S., Valè G., Crosatti C., Toppino L., Bono G.A., Fornara F., Pecchioni N. A new rice plant ideotype through genome editing: the SUSRICE project |
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| 10:30 – 10:45 | Maioli A., De Marchi F., Valentino D., Gianoglio S., Patono D., Miloro F., Bai Y., Comino C., Lanteri S., Lovisolo C., Acquadro A., Moglia A. New insights on the role of SlDMR6-1 in drought avoidance in tomato |
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| 10:45 – 11:00 | Nicolia A., D’Agostino N., Tamburino R., Festa G., Sannino L., Aufiero G., Paparo R., Arimura S., Scotti N., Cardi T. Molecular and phenotypic characterization of potato plants edited in the mitochondrial genome by mitoTALEN and mitoTALECD approaches |
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| 11:00 – 11:15 | Salvagnin U., Giacomelli L., Scintilla S., Rouppe van der Voort J., Zeilmaker T., Moser C. Reduced susceptibility to downy mildew of DMR6 gene-edited grapevine plants and development of DNA-free edited mutants |
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| 11:15 – 11:30 | Moffa L., Bevilacqua I., Pagliarani C., Gambino G., Perrone I., Velasco R., Lovisolo C., Nerva L., Chitarra W. Improving grape resilience to drought exploiting the CRISPR/Cas technology: functional characterization of the target gene through Spray Induced Gene Silencing (SIGS) |
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| 11:30 – 12:00 | Invited Lecture Granell A. Genome editing for better, healthier tomatoes |
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| 12:00 – 12:15 | General Discussion | |
| 12:15 – 12:30 | Closing Ceremony Chairpersons: Filippone E., Salvi S. |
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Keywords index
| A | |
| ABA | 7.08 |
| ABA/drought | 6.25 |
| abiotic stress | 2.03, 2.07, 2.42, 6.03 |
| abiotic stress response | 1.30, 2.46 |
| abiotic stresses | 2.49 |
| abiotic tolerance | 4.13 |
| abiotic/biotic stress | 6.26 |
| abscisic acid | 2.05 |
| abscisic acid-stress-ripening | 2.13 |
| accessions | 2.14 |
| adaptation | 2.01, 6.02, 6.13 |
| agri-photovoltaic | 2.02 |
| Agrobacterium-mediated transformation | 6.24 |
| agrobiodiversity | 1.22 |
| agrofood systems | 1.21 |
| agroforestry | 4.23 |
| alfalfa | 3.11 |
| Algeria | 2.31 |
| alien species | 1.27 |
| allele mining | 6.19 |
| allele variation | 1.34 |
| allergens | 1.71 |
| almond | 6.19, 6.20 |
| anther | 6.27, 7.29 |
| Anthesis | 1.34 |
| anthesis control | 1.37 |
| anthocyanins | 1.59, 1.61, 1.62, 1.66, 2.41 |
| antifungal compounds | 2.39 |
| antinutritional molecules | 1.67 |
| antioxidant compounds | 4.10 |
| AP2/ERF | 6.10 |
| apple | 1.73, 6.06 |
| apple scab | 6.15 |
| Apulia | 6.32 |
| Arabidopsis | 1.34 |
| Arabidopsis thaliana | 5.05 |
| ascorbic acid | 7.25 |
| ASR | 2.13 |
| AT4G08850 | 1.36 |
| autopolyploidy | 2.40 |
| B | |
| B-glucan content | 1.54 |
| backcross inbred lines | 1.45 |
| bacterial community | 4.23 |
| barley | 1.41, 2.02, 2.19, 2.20, 3.01, 3.20, 4.02 |
| barley cultivars | 4.18 |
| barley mutants | 2.21 |
| base editing | 7.06 |
| bean | 2.08 |
| belowground traits | 4.02 |
| beneficial fungi | 4.09 |
| berry ripening | 1.11 |
| berry texture | 6.28 |
| bioactive compounds | 1.55, 1.66 |
| bioactive molecules | 1.70 |
| biochar | 4.10 |
| bioclimatic evaluation | 2.31 |
| biodiversity | 1.19, 2.14, 2.31, 2.36, 4.24, 6.33 |
| biodiversity conservation | 2.34 |
| biofortification | 7.21, 7.22 |
| bioinformatics | 4.22, 6.14 |
| biostimulant | 4.16 |
| biostimulants | 4.08 |
| biotic stress | 2.03, 2.42, 6.24 |
| biotic stress resistance | 7.30 |
| black scurf | 2.39 |
| Blumeria graminis | 1.45 |
| Brachypodium | 1.56 |
| Brassica napus | 3.08 |
| Brassica oleracea | 1.23 |
| bread wheat | 2.11, 2.12, 3.21 |
| breeding | 1.09, 2.22, 2.32, 3.07, 6.19, 7.29 |
| breeding for resilience | 2.10 |
| breeding strategy | 3.11 |
| broccoli-raab | 1.37 |
| broomrape | 1.09 |
| BSA-seq | 2.48 |
| Budbreak | 5.07 |
| C | |
| calli | 7.27 |
| callus culture | 1.64 |
| Camelina sativa | 2.32 |
| candidate genes | 1.05, 1.56 |
| candidate genes association analysis | 6.03 |
| cannabinoids | 1.63, 1.68 |
| Cannabis sativa L. | 1.60 |
| CAPS markers | 3.14 |
| Capsicum annum L. | 1.52 |
| Capsicum annuum | 1.65, 3.14 |
| carboxylesterase | 2.43 |
| carotenoid genetics | 1.01 |
| carpel development | 7.09 |
| cauliflower | 3.07 |
| CBCA | 1.68 |
| cell suspension culture | 3.21 |
| cell wall | 1.16, 6.28 |
| cellular agriculture | 1.70 |
| cellulose | 1.16 |
| centromeres | 5.03 |
| cereal | 3.23 |
| chemical characterization | 1.53 |
| chemical treatment | 3.25 |
| chicory | 1.36 |
| ChIP-Seq | 1.15, 5.09, 5.10 |
| Chromatin Immunoprecipitation | 3.10 |
| chromosome engineering | 3.15 |
| Cichorium endivia | 1.35 |
| Cime di Rapa | 1.34 |
| Circadian clock | 4.03 |
| cis-regulatory elements | 2.27 |
| cisgenesis | 7.02, 7.30 |
| cisgenesis and genome editing | 7.31 |
| Citrus | 5.06 |
| Citrus rootstock | 2.30 |
| citrus varieties | 7.31 |
| Cleaved Amplified Polymorphic Sequences (CAPS) | 3.13 |
| climate adaptation | 6.03 |
| climate change | 2.06, 2.18, 2.35, 5.07, 6.18 |
| climate resilience | 2.23 |
| climate services | 2.24 |
| cold | 5.06 |
| combined assembly | 3.31 |
| commmon bean (Phaseolues vulgaris L.) | 1.51 |
| common bean | 1.21 |
| comparative transcriptomics | 1.50 |
| conservation | 6.33 |
| cosmetics | 1.70 |
| cotton | 2.51 |
| cover crop | 2.32 |
| cowpea | 2.23 |
| CPVO | 2.08 |
| CRE | 6.23 |
| CRE-LOX system | 3.18 |
| CRISPR | 7.02, 7.09 |
| CRISPR-Cas9 | 1.61, 7.10 |
| CRISPR-dCas9 | 3.10 |
| CRISPR/Cas | 5.02 |
| CRISPR/Cas9 | 2.22, 3.03, 6.10, 6.25, 6.28, 7.16, 7.17, 7.20, 7.21, 7.22, 7.23, 7.24, 7.25 |
| crocins | 7.15 |
| crop genetics | 2.24 |
| crop yield | 2.21 |
| crossing over | 3.15 |
| Crossing over | 1.04 |
| cryptochromes | 4.03 |
| Cucumis melo L. | 3.27 |
| culm morphology | 2.20 |
| cultivar evaluation | 2.06 |
| cutin | 6.15 |
| Cynara cardunculus L. var. scolymus | 2.38 |
| D | |
| D27 | 2.45 |
| D27-like genes | 2.45 |
| DAP-seq | 1.11, 1.15, 6.27 |
| DAPC | 1.17 |
| DAPseq | 6.23 |
| ddRAD | 1.20 |
| ddRAD seq | 1.27 |
| ddRAD-seq | 1.19 |
| ddRADseq | 1.25 |
| defatted seed meals | 2.11 |
| defoliation | 6.04 |
| Denaturing gradient gel electrophoresis | 3.27 |
| differential allelic expression | 6.21 |
| digital canopy model | 3.06 |
| digitalization | 3.17 |
| Disease Evaluation | 1.42 |
| disease resistance | 1.45 |
| Distinctiness-Uniformity-Stability (DUS) | 2.04 |
| divergent loci | 1.20 |
| DMR6 | 7.23 |
| DNA fingerprinting | 6.34 |
| DNA methylation | 5.03, 5.05, 5.07 |
| DNA-free genome editing | 7.27, 7.28 |
| DND1 gene | 3.03 |
| domestication | 2.51 |
| dormancy | 6.18 |
| dosage | 7.12 |
| doubled haploids | 3.07 |
| downy mildew | 7.07 |
| DOWNY MILDEW RESISTANCE 6 | 7.05 |
| drought | 1.30, 2.13, 2.37, 2.40, 3.23, 4.13, 4.20, 5.08, 5.09, 7.08 |
| drought stress | 1.03, 1.47, 2.17, 2.30, 2.43, 2.45, 2.47, 4.16, 5.10, 7.05 |
| drought tolerance | 2.05, 2.49 |
| duckweed | 3.26 |
| durum wheat | 1.02, 1.08, 1.17, 1.29, 1.47, 1.54, 1.58, 2.14, 2.15, 2.16, 2.17, 3.17, 3.18, 3.20, 7.11 |
| durum wheat breeding line | 1.55 |
| durum wheat landraces | 1.18 |
| E | |
| ecophysiological measurements | 7.05 |
| ecotypes | 1.24 |
| editing | 3.08 |
| eggplant | 1.61, 7.24 |
| electromagnetic waves | 5.05 |
| elicitation | 1.63, 1.65 |
| embriogenic calli | 7.26 |
| embryogenic calli | 6.24, 7.29 |
| enviroment adaptation | 2.10 |
| enzymatic-browning | 1.72 |
| EPFL9 | 6.25 |
| epicuticular waxes | 2.17 |
| epigenetic | 5.06 |
| epigenetic memory | 5.10 |
| epigenetics | 5.05 |
| epigenome | 5.02, 5.04 |
| eQTL | 1.13 |
| essential oils | 1.37 |
| EST-SSR | 1.25 |
| ethylene | 6.16 |
| ethylene responsive factors | 7.20 |
| evolution | 3.12 |
| F | |
| Fagus sylvatica | 6.03 |
| Fagus sylvatica L. | 6.14 |
| fertilization strategies | 2.12 |
| fig tree | 6.21 |
| fingerprinting | 1.22 |
| firmness | 7.18 |
| fitness costs | 3.03 |
| flooding | 2.40 |
| florigens | 7.09 |
| flower | 6.27 |
| flower development | 3.01 |
| flowering | 1.10, 1.35, 7.10 |
| flowering time | 1.33, 3.16 |
| food security | 4.01 |
| food traceability | 3.13 |
| forage quality | 2.06 |
| forest genetic resources | 6.13 |
| forest trees | 6.01 |
| forward genetic | 2.02 |
| forward reverse genetic approaches | 3.25 |
| free asparagine | 1.08 |
| fruit and plant morphological traits | 6.05 |
| fruit antioxidants | 7.20 |
| fruit morphology | 3.13 |
| fruit nutritional analyses | 6.05 |
| fruit quality | 5.04, 6.06 |
| fruit softening | 7.18 |
| fruit traits and diseases | 7.31 |
| FTIR | 2.52 |
| functional food | 1.62 |
| functional genomics | 1.32, 1.50, 3.20 |
| Furovirus | 2.15 |
| Fusarium | 1.44 |
| Fusarium foot rot | 2.14 |
| Fusarium verticilliodes | 2.36 |
| G | |
| GA signalling | 7.10 |
| gas exchange | 7.08 |
| Gbs | 1.53 |
| GBS | 1.20 |
| Gene Coexpression Networks | 3.16 |
| gene duplication | 7.12 |
| gene editing | 2.43, 7.07 |
| gene expression | 1.34, 1.64, 1.72, 2.26, 3.22 |
| gene network | 2.44 |
| gene regulation | 1.15, 3.10 |
| gene-expression-profile | 1.48 |
| genetic analyses | 2.08 |
| genetic and phenotypic characterizations | 6.17 |
| genetic characterization | 2.35 |
| genetic diversity | 1.18, 2.10, 2.38, 3.16, 6.05, 6.13, 6.22 |
| genetic evaluation | 6.33 |
| genetic fingerprinting | 1.27 |
| genetic maps | 6.16 |
| genetic markers | 1.35, 6.22 |
| genetic offset | 6.01 |
| genetic resources | 1.25, 1.43, 1.57, 2.04, 2.37 |
| genetic transformatio | 3.26 |
| genetic variability | 1.24, 1.53, 2.34, 3.09, 6.20 |
| genome assembly | 1.02 |
| genome editing | 1.49, 2.17, 7.02, 7.04, 7.11, 7.17, 7.18, 7.20, 7.21, 7.22, 7.23, 7.24, 7.25, 7.26, 7.29 |
| genome evolution | 6.07 |
| Genome Wide Association Studies | 6.09 |
| Genome Wide Association Studies (GWAS) | 1.51 |
| Genome Wide Association Study | 1.03 |
| genome-wide | 1.16 |
| Genome-Wide Association Studies | 4.02 |
| Genome-Wide Association Study | 1.08, 4.12 |
| genomic diversity | 1.05 |
| genomic library preparation | 1.12 |
| genomic prediction | 4.02 |
| genomic selection | 3.11 |
| genomics | 1.07, 2.23, 3.05, 6.01, 6.02 |
| genotype diversity | 1.67 |
| genotype x environment | 2.28 |
| genotypes | 2.09 |
| genotyping | 1.26, 2.48 |
| genotyping arrays | 3.05 |
| Genotyping by Sequencing | 3.28 |
| Genotyping-by-Sequencing | 3.11 |
| Genotyping-by-sequencing (GBS) | 1.23 |
| germplasm bank | 2.35 |
| germplasm resources | 4.14 |
| Global genomic prediction | 6.09 |
| Glutamate 1-semialdehyde aminotransferase | 7.13 |
| Glutathione S-transferases | 2.47 |
| glycaemic index | 1.55 |
| glycaemic load | 1.55 |
| Goldenbraid | 7.16 |
| Gossypium | 2.51 |
| GPAT6 | 6.15 |
| grain colors | 1.59 |
| Grain number increase | 1.39 |
| Grain protein content | 1.58 |
| grain quality | 1.56, 1.57 |
| grain yield | 1.32, 3.19 |
| Grain yield potential | 1.39 |
| grapevine | 1.11, 1.15, 2.25, 2.26, 3.10, 4.21, 5.03, 6.24, 6.25, 6.26, 7.07, 7.08 |
| grapevine drought stress | 2.29 |
| grapevine rootstocks | 2.29 |
| gravitropism | 4.19 |
| GRF gene family | 3.20 |
| GST | 2.49 |
| Guignardia bidwellii | 3.02 |
| GWAS | 1.05, 1.06, 1.40, 1.42, 1.43, 2.04, 2.10, 2.15, 2.18, 2.20, 3.05, 4.18, 6.12, 6.22 |
| GxE interaction | 6.11 |
| H | |
| haplotype | 4.14 |
| haplotype blocks | 1.28 |
| haplotypes | 3.05 |
| hazelnut (Corylus avellana L.) | 6.22 |
| health-promoting effects | 1.59 |
| healthy diet | 1.69 |
| heat and water-deficit | 2.16 |
| Heat Stress | 2.37 |
| Heat Stress (HS) | 4.04 |
| Helianthus annuus L. | 5.09 |
| hemicellulose | 1.16 |
| hemp | 1.63, 1.68 |
| hereditability | 5.04 |
| heritability | 1.40 |
| heterozygosity | 6.21 |
| Hierarchical intra-family network | 1.11 |
| high intensity light | 7.19 |
| high pigment tomato mutant | 7.19 |
| high resolution melting | 1.26 |
| high temperature | 2.50 |
| high temperatures | 2.44 |
| high throughput phenotyping | 3.04 |
| high throughput sequencing | 1.12 |
| high throughput SNP genotyping | 3.17 |
| high-throughput genotyping | 1.05 |
| high-throughput phenotyping | 4.09 |
| histone modifications | 5.09, 5.10, 6.08 |
| histone variant | 5.02 |
| holobiont | 4.08 |
| hologenome | 4.24 |
| homologous recombination | 7.13 |
| Hordeum vulgare | 1.42, 4.17 |
| hormones | 6.08 |
| hormones signalling | 2.26 |
| HPLC-MS/MS | 1.60 |
| HTP | 3.06 |
| hus1 | 2.19 |
| HvPDIL5-1 gene | 7.11 |
| hydroponic cultivation | 1.51 |
| I | |
| improving photosynthesis | 2.19 |
| in vitro culture | 1.66 |
| in vitro digestibility | 1.67 |
| in vitro propagation | 1.22 |
| InDel | 2.44 |
| inflorescence architecture | 1.32 |
| Infra-Red Gas Analyser | 2.29 |
| INNOVAR | 2.04 |
| integrated omics | 4.08 |
| Intelligent Collection | 1.21 |
| interaction | 6.29 |
| internode elongation | 1.10 |
| interspecific hybrids | 3.31 |
| Introgression Lines | 1.07 |
| inversion | 3.15 |
| Ion Torrent | 6.14 |
| Iron oxide magnetic nanoparticles | 3.30 |
| isolated microspore culture | 3.07 |
| ITS | 3.27 |
| J | |
| juvenile stage | 1.68 |
| K | |
| K-seq protocol | 1.22 |
| KASP | 2.18, 6.34 |
| Keracyanin | 1.60 |
| kernel development | 3.01 |
| kernel taste | 6.19 |
| kiwifruit | 6.10 |
| L | |
| laccase | 2.52 |
| landrace | 1.19, 2.33 |
| landraces | 1.25, 2.34 |
| landscape genomics | 2.33, 6.13 |
| late/post-ripening | 6.26 |
| legumes | 2.09 |
| lentil | 2.09 |
| lettuce | 1.05, 4.10, 7.25 |
| light | 4.03 |
| linkage map | 2.25 |
| local biodiversity | 6.17 |
| local varieties | 1.23, 1.52 |
| lodging | 2.20 |
| long reads | 5.03 |
| long-read sequencing | 1.03 |
| low oxygen | 1.73 |
| Lycopersicon esculentum | 1.49 |
| lysin motif receptor-like kinase | 6.29 |
| M | |
| MAGIC | 3.24 |
| MAGIC population | 1.04, 1.14, 3.04 |
| maize | 1.33, 1.56, 2.33, 2.37 |
| maize germplasm | 2.36, 4.20 |
| maize landraces | 1.53 |
| Maize traditional varieties | 2.35 |
| male fertility | 7.06 |
| male sterility | 3.29, 7.17 |
| Malus | 7.30 |
| Malus domestica | 1.72 |
| Manihot esculenta | 1.48 |
| mapping | 1.09 |
| Marker-Assisted Breeding | 3.02 |
| Marker-Assisted Selection | 1.39, 2.22, 3.14, 6.19, 6.30 |
| marker-free | 7.31 |
| MAS | 7.29 |
| MATE | 1.60 |
| MCSeEd | 5.06 |
| MDIS1 INTERACTING RECEPTOR LIKE KINASE 2 | 1.36 |
| MdPPO | 1.72 |
| Medicago sativa | 2.07, 3.11, 7.13 |
| Medicago truncatula | 4.03 |
| Mediterranean Basin | 1.69, 6.33 |
| medium | 7.14 |
| meristem manipulation | 3.26 |
| metabarcoding | 4.23 |
| metabolic engineering | 1.65 |
| metabolomics | 1.08, 1.69 |
| metagenomics | 4.21 |
| methyl-jasmonate | 1.64 |
| methylome | 6.08 |
| microbial breeding | 4.24 |
| microbiome | 2.36 |
| microbiomes | 4.09 |
| microplastics | 2.52 |
| micropropagation | 7.14 |
| microsatellite markers | 6.20 |
| microsatellite transferability | 6.17 |
| microvine | 7.26 |
| mineral nutrition | 2.12 |
| miPEPs | 5.08 |
| miRNAs | 2.28 |
| MitoTALECD | 7.06 |
| MitoTALEN | 7.06 |
| molecular breeding | 3.28, 6.06 |
| molecular markers | 2.32, 2.38 |
| mono- and di-terpene synthase genes | 6.04 |
| mono- and di-terpenoids | 6.04 |
| morphological characterization | 2.35 |
| morphological descriptors | 1.17, 1.21 |
| morphological traits | 2.38 |
| mountain environment | 2.08 |
| mozambique | 2.24 |
| multi-locus GWAS | 1.28 |
| multiomics | 4.22 |
| multiple stress | 1.49 |
| multivariate data analysis | 1.52 |
| mutants | 4.17 |
| MYB108A | 6.27 |
| MYB90 | 2.41 |
| mycorrhizal root colonization | 4.10 |
| N | |
| NAC | 1.15 |
| NAC transcription factors | 1.11 |
| NAC61 | 6.26 |
| nanopriming | 3.30 |
| Near Infrared Spectroscopy | 2.06 |
| New breeding technology | 7.30 |
| New Plant Breeding Techniques (NPBTs) | 7.15 |
| NGS | 6.27 |
| NGS (next generation sequencing) | 1.22 |
| NGS analysis | 6.07 |
| Nicotiana benthamiana | 7.15 |
| Nicotiana tabacum | 2.47 |
| Nitrate Uptake | 3.22 |
| nitrogen absorption | 7.04 |
| Nitrogen Use Efficiency (NUE) | 3.22 |
| NMR | 1.52 |
| Non Photochemical Quencing (NPQ) | 2.21 |
| novel food | 1.71 |
| NPBTs | 7.02 |
| nutraceuticals | 1.52 |
| nutrient accumulation | 2.12 |
| nutritional values | 2.38 |
| O | |
| oilseed crop | 2.32 |
| Olea europaea | 1.64 |
| Olea evolution | 6.07 |
| oleaster | 2.31, 6.33 |
| olive | 6.32 |
| omic analysis | 1.35 |
| omics | 1.37 |
| omics approach | 1.46 |
| omics data integration | 1.50 |
| orange carrot | 1.01 |
| ornamental plants | 3.28 |
| Orobanchaceae | 4.07 |
| Oryza sativa | 1.03, 7.04 |
| Oxford Nanopore Techonology sequencing | 1.14 |
| P | |
| P-spline | 3.06 |
| pale mutants | 2.19 |
| pale-green | 2.02 |
| PAMPs | 6.29 |
| Pan-genome | 1.14 |
| pangenome | 1.02 |
| panicle development | 1.10 |
| paralog compensation | 7.12 |
| parasitic weeds | 2.45 |
| participatory methods | 2.24 |
| pasta supply chain | 3.17 |
| Pea | 1.09 |
| peach | 6.18 |
| pear | 6.16 |
| Pectate Lyase | 6.28 |
| PEG | 2.30 |
| pepper | 3.24 |
| PGPM | 4.10, 4.16 |
| PGPR | 4.06 |
| PGRFA | 2.08 |
| phased genome | 6.21 |
| phasiRNAs | 2.28 |
| Phelipanche ramosa | 4.07 |
| phenological traits | 2.09 |
| phenology | 6.12 |
| phenomics | 2.03, 3.05 |
| phenotype | 6.22 |
| phenotypic characterization | 7.28 |
| phenotypic plasticity | 2.51 |
| phenotypic prediction | 6.01 |
| phenotyping | 1.26, 2.25, 2.50, 3.23 |
| photoperiod | 2.01, 6.08 |
| photoprotection | 2.21 |
| photosynthesis | 1.41, 2.02, 2.21, 3.04, 7.15 |
| Photosynthesis-related traits | 1.14 |
| phycoremediation | 2.52 |
| Phyllosticta ampelicida | 3.02 |
| phyllotaxis | 3.08 |
| phylogenesis and evolution | 3.22 |
| Phylogenetic analysis | 6.29 |
| phylogeny | 3.29 |
| phytic acid | 2.34 |
| phytohormone | 4.04 |
| phytohormones | 1.30 |
| Phytophthora capsici | 3.14 |
| pigmented maize | 1.66 |
| pigmented mandarin-like hybrids | 3.31 |
| Pinus nigra subsp. laricio (Poiret) Maire | 6.04 |
| plant | 2.09 |
| plant breeding | 1.41 |
| plant cell cultures | 1.70 |
| plant development | 1.30 |
| plant genetic resources | 1.40, 6.34 |
| plant genomics | 6.14 |
| plant genotyping | 1.12 |
| plant growth regulators | 7.14 |
| plant growth-promoting rhizobacteria | 2.42 |
| plant metabolism | 3.21 |
| plant metabolites | 4.11 |
| plant phenotyping | 2.03, 2.29 |
| plant protection | 2.39 |
| plant regeneration | 7.27 |
| plant variety protection | 1.28 |
| plant-microbe interactions | 2.42 |
| plant-microbiome interaction | 4.22 |
| ploidy analysis | 3.28 |
| pollen development | 2.41 |
| pollen‒stigma recognition | 1.36 |
| polygalacturonase 2a (PG2a) | 7.16 |
| polymorphism | 1.19 |
| polyphenols | 1.46, 1.65, 1.72 |
| polyploid | 1.24 |
| polyploidy | 2.07, 2.51 |
| population analysis | 2.33 |
| population genetics | 3.12, 6.01 |
| population genomics | 1.01 |
| population studies | 1.12, 1.13 |
| postharvest | 1.73, 6.06 |
| postzygotic barrier | 1.31 |
| potato | 1.46 |
| potato chondriome | 7.06 |
| powdery mildew | 3.03 |
| powdery mildew candidate genes | 1.45 |
| PREMATURE INTERNODE ELONGATION 1 (PINE1) | 7.03 |
| Programmed Cell Death (PCD) | 4.04 |
| protein content | 1.67 |
| protoplast | 7.07, 7.27, 7.28 |
| protoplasts | 3.10, 7.26 |
| Prunus | 6.02 |
| Prunus persica | 6.09 |
| Prunus species | 6.17 |
| Pseudomonas syringae pv. actinidiae | 6.10 |
| purple durum wheat | 1.59 |
| PVDC | 2.52 |
| Q | |
| QTL | 1.33, 1.40, 1.44, 6.16 |
| QTL mapping | 1.58, 3.04, 3.19 |
| QTLs | 2.25 |
| quality | 1.29 |
| Quantitative Trait Nucleotide | 1.28 |
| R | |
| rDNA | 3.27 |
| ready-to-eat | 3.31 |
| recombination | 1.04 |
| redundancy | 7.12 |
| regeneration | 7.14, 7.31 |
| regulation of gene expression | 1.30 |
| remote sensing | 1.26 |
| resequencing | 1.06, 3.24 |
| resiliance | 6.32 |
| resilience | 2.33, 2.37 |
| resilience traits | 4.14 |
| resistance | 1.09, 1.44, 2.14, 2.15, 6.30 |
| resistance genes | 3.12 |
| resistant source | 2.11 |
| resistant starch | 1.55 |
| responsive backup circuits | 7.12 |
| RGA | 4.19 |
| rhizosphere microbiome | 4.22 |
| rice | 1.10, 1.32, 1.56, 2.23, 7.10 |
| rice blast | 2.22 |
| rice flowering | 7.03 |
| rice genetics | 7.09 |
| ripening | 2.26 |
| RNA sequencing | 1.13 |
| RNA-seq | 1.47, 2.30, 3.30, 5.07, 6.31 |
| RNAseq | 1.61, 6.11 |
| RNP complex | 7.17 |
| Rocket salad | 1.27 |
| Rogosija | 1.18 |
| root | 4.04, 4.12, 4.19, 7.04 |
| root anatomy | 4.01 |
| root and epicotyl development | 4.11 |
| root architecture | 4.01, 4.01, 4.13, 4.19 |
| root system architecture | 4.02, 4.14, 4.15 |
| root system architecture RSA | 4.20 |
| root system traits | 4.18 |
| root transcriptomic | 4.22 |
| roots | 1.66 |
| RT-qPCR | 1.68 |
| rucola | 3.25 |
| rust diseases | 2.11 |
| S | |
| Saccharum spontaneum | 1.24 |
| saffron hydroponics | 1.69 |
| salinity | 2.13, 2.40, 4.13 |
| salinity stress | 2.07 |
| salt stress | 1.07, 2.47, 4.06 |
| salt stress mitigation | 2.46 |
| salt stress tolerance | 1.51 |
| salt tolerance | 2.06 |
| San Marzano landrace | 7.19 |
| SBCMV | 2.15 |
| SCOT markers | 1.27 |
| seasonal-transition | 1.48 |
| secondary metabolites | 1.64 |
| seed development | 1.31 |
| seed-nanoparticle interactions | 3.30 |
| seedlessness | 6.30 |
| seedling | 2.50 |
| selection | 1.01 |
| selection criteria | 4.20 |
| selective sweeps | 1.06 |
| self-incompatibility | 1.36, 3.29 |
| sexual polyploidization | 2.07 |
| shelf-life | 7.18 |
| shoort and long read sequencing | 1.02 |
| Sicilian landraces | 1.29 |
| Single Nucleotide Polymorphism (SNP) | 3.13 |
| Single Nucleotide Polymorphism (SNPs) | 6.03 |
| Single Nucleotide Polymorphisms | 6.12 |
| Single Nucleotide Polymorphisms (SNPs) | 6.14 |
| SiO2 nanoparticles | 2.46 |
| site-directed mutagenesis | 7.13 |
| Small RNA-seq | 2.28 |
| smallholders | 2.24 |
| SNP | 1.25, 1.26, 1.53, 2.18, 2.44, 6.34 |
| SNP array | 1.18 |
| SNP genotyping | 1.29, 3.02 |
| SNP markers | 1.20 |
| SNPs | 1.23, 3.27 |
| soil compaction | 4.18 |
| soil health | 4.15 |
| Soil-borne pathogens | 3.14 |
| Soil-borne viruses | 7.11 |
| Solanaceae | 7.17, 7.21 |
| Solanum lycopersicum | 1.04, 2.03, 2.05, 2.42, 2.47, 2.49, 3.16, 4.09, 5.10, 7.20 |
| Solanum lycopersicum L. | 3.13, 7.05 |
| Solanum melongena | 1.06, 7.23 |
| Solanum pennellii | 4.07 |
| Solanum tuberosum | 2.39 |
| somaclone regeneration | 3.09 |
| somatic embryogenesis | 3.09, 7.28 |
| source-sink | 3.01 |
| spike development | 3.19 |
| Spike fertility | 1.38 |
| spike-related traits | 3.19 |
| sRNAs | 5.08 |
| SSR | 2.31 |
| SSR genotyping | 3.28 |
| SSR markers | 1.24 |
| starch mutants | 3.21 |
| stem elongation | 7.03, 7.10 |
| stem gibberellin sensitivity | 7.03 |
| stem rust | 1.43 |
| stigma position | 2.48 |
| stilbenoid metabolism | 6.26 |
| Stomata formation | 6.25 |
| stomatal closure | 2.05 |
| stone fruit tree | 6.02 |
| straw biomass | 2.19 |
| straw quality | 1.41 |
| stress combination | 2.16 |
| stress memory | 5.09 |
| stress resilience | 1.50, 5.02 |
| stress resistance | 2.36 |
| stress tolerance | 2.16, 7.23 |
| stress-response | 1.48 |
| Strigolactones | 2.43, 2.45, 4.07, 4.17 |
| Structural Variants | 1.14 |
| structural variation | 1.03 |
| style exertion | 2.48 |
| Sun Black genotype | 1.62 |
| superficial scald | 1.73, 6.16 |
| susceptibility genes | 7.05 |
| sustainability | 4.11, 4.18, 7.04 |
| sustainable agriculture | 2.34, 4.12, 4.15, 4.16 |
| sustainable biotechnology | 3.09 |
| Sustainable Forest Management | 6.13 |
| sweet chestnut | 6.05 |
| SWEET genes | 3.01 |
| system genetics | 6.06 |
| T | |
| T. molitor | 1.71 |
| T2T assembly | 5.03 |
| Tarocco orange | 3.31 |
| TEA | 2.22, 7.14 |
| temperature | 2.01 |
| terpenoids | 1.65 |
| Tetraploid Wheat collection | 1.54 |
| TFBS | 6.23 |
| thaumatin-like proteins (TLPs) | 7.16 |
| Thaumetopoea pityocampa (Denis & Schiffermüller 1775) | 6.04 |
| thermotolerance | 2.25 |
| tiller angle | 1.10 |
| tilling | 4.19 |
| TILLING | 2.20 |
| titratable acidity | 6.09 |
| tomato | 1.07, 2.43, 2.46, 2.48, 2.50, 3.12, 3.15, 4.06, 4.08, 5.04, 7.02, 7.22 |
| tomato allergens | 7.16 |
| tomato landraces | 7.18 |
| tomato peels | 1.62 |
| tomato resistance | 3.03 |
| tomato waste | 1.62 |
| tomato wild relatives | 2.49 |
| Ton1 | 3.18 |
| traceability | 1.29, 3.17 |
| trade-off | 4.24 |
| traditional variety | 7.19 |
| transcription factors | 1.59, 1.60, 2.26, 3.16 |
| transcriptome | 1.02, 1.49, 2.30, 6.08, 6.11, 6.31 |
| transcriptome analysis | 1.63 |
| transcriptomics | 1.07, 1.73, 2.46, 4.21, 6.18 |
| translational science | 1.41 |
| transpiration efficiency | 4.01 |
| transposable elements | 1.33 |
| triploid block | 1.31 |
| Triticum aestivum | 1.40, 1.42 |
| Triticum dicoccum | 1.38 |
| Triticum durum | 1.42 |
| Triticum turgidum | 1.38, 4.14 |
| Triticum turgidum ssp. dicoccoides | 1.45 |
| Triticum turgidum subsp. durum | 3.22 |
| Tropomyosin | 1.71 |
| TRV | 7.24 |
| U | |
| UAV | 3.06 |
| UPOV protocol | 1.28 |
| UPOV traits | 1.17 |
| useful alleles | 1.57 |
| UV stress | 2.40 |
| V | |
| Venturia inaequalis | 6.15 |
| VIGE | 7.24 |
| Vitamin D | 7.21 |
| Vitis spp | 3.02 |
| Vitis vinifera | 2.27, 2.28, 5.07, 6.12, 6.28, 6.29, 7.28 |
| Vitis vinifera clones | 1.20 |
| Vitis vinifera L. | 6.11, 7.27 |
| VviAGL11 | 7.26 |
| W | |
| water deprivation | 1.46 |
| water scarcity | 4.09 |
| water stress | 2.27 |
| water use efficiency | 4.11 |
| WCGNA | 6.11 |
| wheat | 1.43, 1.44, 2.01, 2.13, 3.06, 4.12, 4.15 |
| wheat improvement | 1.39 |
| whole grain content | 1.08 |
| wild emmer | 1.43 |
| wild emmer wheat | 2.10 |
| wild introgressions | 2.16 |
| wild relatives | 3.12 |
| wild species | 2.44 |
| Wolffia globosa | 3.26 |
| X | |
| Xylella fastidiosa | 6.31 |
| xyloglucan endotransglucosylase/hydrolase | 1.16 |
| Y | |
| YFP | 6.15 |
| yield | 3.08, 3.18, 3.20 |
| yield-related traits | 1.58 |
| Z | |
| Zea mays L. | 1.19 |
| zeaxanthin | 7.15 |
| 5 | |
| 5-azacytidine | 5.06 |













