LXIX SIGA Annual Congress
Genetic blueprints for next generation crops
08-11 September 2026
Keywords index
| - | |
| -omics analysis | 4.02 |
| A | |
| ABI5 INTERACTING PROTEINs | 7.06 |
| abiotic | 6.07 |
| abiotic stress | 5.08, 5.14, 5.17, 5.18, 5.19, 6.20, 7.12 |
| abscisic acid | 7.06 |
| Aegilops | 4.04 |
| agrivoltaics | 6.15 |
| Agrobacterium rhizogenes | 3.07 |
| agrobiodiversity | 5.12, 5.51, 8.13 |
| agrobiodiversity conservation | 4.11 |
| agroecosystems | 1.07 |
| agroforestry | 3.13 |
| agronomic management | 4.07 |
| agronomic trait loci | 6.13 |
| alfalfa | 6.10 |
| alien gene transfer | 5.17, 5.19 |
| alien introgression | 5.14 |
| Allele Specific PCR (ASP) | 1.12 |
| allelic variation | 5.39 |
| Allium cepa L | 5.53 |
| allometric allocation | 2.03 |
| almond | 1.05, 5.25, 7.03 |
| altered gravity | 2.22 |
| AM fungi | 7.14 |
| anther indehiscence | 2.09 |
| anthesis | 2.29 |
| anthocyanin pigmentation | 2.15 |
| anthocyanins | 4.15, 4.19, 6.09 |
| antioxidant activity | 5.52 |
| antioxidant response | 6.03 |
| apomixis | 2.10 |
| apospory | 3.09 |
| apple | 2.25 |
| apricot | 5.24 |
| Arabidopsis thaliana | 2.29 |
| ARF | 2.13 |
| Artificial Intelligence | 3.16, 8.03 |
| arundamine | 4.17 |
| Atropa belladonna | 6.20 |
| auxin | 2.13 |
| B | |
| barley | 2.11, 3.19, 5.01, 5.48 |
| barley landraces | 5.39 |
| barley mutants | 3.21 |
| bell pepper | 2.08 |
| berry ripening | 6.04 |
| berry texture | 5.05 |
| beta-carotene | 5.22 |
| beta-glucan | 4.04 |
| bi-parental mapping | 3.18 |
| bioactive compounds | 4.06 |
| biodiversity | 5.20, 5.28 |
| biofortification | 4.03 |
| biosynthetic pathway | 4.17 |
| biotic stress | 5.08, 5.13 |
| biparental linkage analysis | 3.12 |
| blood orange | 4.15, 6.05 |
| Brassica rapa subsp. sylvestris | 2.29 |
| brassinosteroid signalling | 2.02 |
| brassinosteroids | 2.12, 2.16 |
| bread wheat | 8.01 |
| breeding | 1.11, 3.18, 3.20, 5.11, 5.20, 8.04 |
| broccoli rabe | 8.11 |
| broccoli-raab landraces | 5.21 |
| broomrape | 5.22 |
| browning | 4.13 |
| BSAseq | 6.14 |
| C | |
| Camelina sativa | 4.09 |
| candidate genes | 5.29, 5.42 |
| Cannabis sativa | 5.26, 8.04 |
| Cannabis sativa L. | 5.50 |
| canopy architecture | 2.04 |
| Capsicum annuum | 5.23 |
| Capsicum annuum var. glabriusculum | 5.56 |
| carbon remobilisation | 5.14 |
| carotenoid cleavage dioxygenases | 6.24 |
| carotenoids | 4.08 |
| Cas9/RNP complex | 2.25 |
| cellular plasticity | 2.27 |
| characterization | 5.11, 5.15 |
| Chardonnay | 2.07 |
| chickpea | 7.19 |
| chlorogenic acid | 4.13 |
| chromatin remodeling | 6.17 |
| chromosome-level de novo genome assembly | 1.10 |
| Cichorium spp | 2.24 |
| cisgenesis | 2.28, 3.08 |
| Citrus | 4.19 |
| Citrus limon | 5.38 |
| Citrus sinensis | 4.15, 6.05 |
| climate adaptation | 3.04, 5.47 |
| climate change | 5.20 |
| climate resilience | 1.07, 8.03 |
| clinostat | 2.22 |
| CoCas9 | 8.07 |
| cold | 4.19 |
| cold storage | 4.15 |
| coleoptile length | 2.21 |
| common bean (Phaseolus vulgaris L.) | 5.03 |
| comparative genomics | 6.11, 6.12 |
| complementation test | 4.10 |
| complex plant genomes | 5.44 |
| composite cross-population | 5.36 |
| computational genomics | 3.05 |
| conservation | 5.15 |
| conservation genetics | 8.14 |
| core collection | 5.04 |
| CRISPR | 8.07 |
| CRISPR-Cas | 4.18 |
| CRISPR-Cas9 gene editing | 2.04 |
| CRISPR/Cas | 2.20, 3.06 |
| CRISPR/Cas system | 2.18 |
| CRISPR/Cas9 | 2.05, 2.08, 2.15, 2.16, 3.07, 8.04 |
| crop improvement | 5.01 |
| crop modelling | 3.11 |
| crop stress detection | 8.03 |
| crop wild relatives | 5.09, 6.09 |
| Cucumis melo | 1.09 |
| Cucurbita maxima | 4.08 |
| Cucurbita pepo | 3.01 |
| curcumin | 4.12 |
| cuticle | 7.16 |
| Cynara cardunculus subsp. scolymus (L.) | 5.12 |
| D | |
| DArT array | 5.55 |
| ddPCR | 8.17 |
| ddRADseq | 5.53 |
| de novo domestication | 1.05 |
| deep learning | 3.05, 3.15, 3.16, 6.01 |
| development | 2.23 |
| differentially expressed genes (DEGs) | 6.08 |
| digital phenotyping | 3.14 |
| disease resistance | 1.03, 3.12, 3.15, 5.45 |
| disease resistance genes | 5.57 |
| Dittrichia viscosa | 4.06 |
| diversity | 1.08 |
| DNA barcoding | 1.12 |
| DNA integrity | 5.27 |
| DNA methylation | 8.02 |
| DNA methylome | 6.21 |
| DNA-free genome editing | 2.17, 2.25 |
| domesticated emmer | 1.03 |
| domestication | 6.09 |
| double-pruning | 8.06 |
| Downy Mildew Resistance 6 | 8.10 |
| DRO1 | 7.07 |
| drought | 5.48, 6.07, 7.16, 7.18 |
| drought adaptation | 5.49, 7.12 |
| drought priming | 8.15 |
| drought resilience | 5.34, 7.15 |
| drought stress | 5.32, 5.39, 6.18, 7.08, 7.19, 8.10 |
| drought stress memory | 6.02, 6.17 |
| drought tolerance | 1.03, 5.07, 5.18, 5.19, 5.29, 7.09 |
| dual-RNAseq | 1.13 |
| Duplex-Specific Nuclease (DSN) | 5.44 |
| durable resistance | 3.08 |
| durum wheat | 2.16, 2.19, 3.03, 3.04, 3.08, 3.15, 4.07, 4.14, 5.08, 5.13, 5.35, 5.45, 5.49, 5.55, 6.23, 7.12, 8.16 |
| E | |
| E3 ubiquitin ligase | 7.09 |
| eco-physiology | 8.15 |
| ecogeographic sampling | 5.09 |
| EGFP transient expression | 2.17 |
| eggplant | 4.13 |
| electromagnetic waves | 8.01 |
| embryogenic callus | 2.17 |
| embryogenic niches | 2.27 |
| EMS mutations | 3.01 |
| enzyme discovery | 4.02 |
| epigenetic signature | 8.15 |
| epigenetics | 6.02, 6.07, 6.17, 6.18 |
| Eragrostis tef | 1.04 |
| Eruca sativa | 1.10 |
| ex situ conservation | 5.12, 8.14 |
| explainable AI | 6.01 |
| Extracellular vesicles | 6.19 |
| F | |
| feruloyl esterase | 8.12 |
| Ficus carica | 5.06 |
| Flavescence dorée | 2.07 |
| FLC gene | 4.09 |
| floral transcriptomics | 6.12 |
| floret development | 2.03 |
| floret fertility | 2.03 |
| flower and fruit development | 3.01 |
| flowering time | 4.09 |
| frost resistance | 5.30 |
| fruit | 2.23 |
| fruit morphology | 5.10 |
| fruit pigmentation | 8.09 |
| fruit quality | 3.01, 5.06, 5.23, 5.36 |
| FST | 5.55 |
| full length cDNA sequencing. | 7.04 |
| functional foods | 4.08 |
| functional genomics | 5.03, 6.25 |
| functional variant prioritization | 6.13 |
| fungal diseases | 3.08 |
| Fusarium Head Blight | 6.23 |
| G | |
| G × E Interaction | 3.20 |
| GA sensitivity | 2.21 |
| GATA7-like genes | 2.16 |
| GBLUP | 3.20 |
| gene bank | 5.15 |
| gene editing | 4.03, 8.10 |
| gene expression | 5.27, 7.17 |
| gene identification | 5.01 |
| gene innovation | 1.02 |
| gene regulatory network | 6.04 |
| Genebanks | 5.31 |
| genetic architecture | 3.03, 5.47 |
| genetic characterization | 5.12, 8.08 |
| genetic diversity | 4.11, 5.01, 5.02, 5.24, 5.25, 5.41, 5.55, 6.11, 8.14 |
| genetic resistance | 3.02, 5.33 |
| genetic resource | 5.30 |
| genetic resources | 1.07, 5.15, 5.31, 5.54 |
| genetic traceability | 5.50 |
| genetic transformation | 2.10 |
| Genetics | 7.01 |
| genome analysis | 8.18 |
| genome assembly | 1.09 |
| genome editing | 2.07, 2.08, 2.14, 2.15, 2.28, 3.17, 7.07 |
| Genome Sequencing | 6.14 |
| Genome-Wide Association Studies (GWAS) | 5.18 |
| Genome-Wide Association Study | 5.06, 5.08, 5.56, 6.05 |
| Genome-Wide Association Study (GWAS) | 3.04 |
| genomic diversity | 5.51 |
| genomic prediction | 3.11, 3.20 |
| genomic selection | 5.30 |
| genomics | 1.05, 3.19, 6.06 |
| genotype × environment | 4.07 |
| Genotype × environment interaction | 3.04 |
| genotype–environment association | 5.37 |
| genotyping | 5.44 |
| Genotyping-by-Sequencing (GBS) | 3.12 |
| germplasm characterization | 5.09, 5.33 |
| germplasm collection | 8.11 |
| germplasm univocal identification | 3.10 |
| Gibberellins (GA) | 2.29 |
| glossy | 7.16 |
| gluten peptides | 4.07 |
| GMO quantification | 8.17 |
| grain legumes | 5.30 |
| grain number | 2.03 |
| grain yield | 2.03, 2.19 |
| grape pomace biochar | 8.16 |
| grapevine | 2.25, 6.04, 7.14 |
| grapevine canopy management | 8.06 |
| grapevine defense | 6.25 |
| grapevine genomics | 5.51 |
| grapevine rootstock / 110R | 5.29 |
| graph | 6.01 |
| graph-based genomics | 1.11 |
| GREAT Atlas | 6.12 |
| GRF4-GIF1 | 3.17 |
| group testing | 8.17 |
| growth rate | 2.19 |
| gummosis | 5.38 |
| GWAS | 3.02, 4.05, 4.07, 4.12, 5.11, 5.35, 5.47, 5.48, 7.01, 8.08 |
| H | |
| HAIKU1 (IKU1) | 2.05 |
| hairy roots | 2.18, 4.06, 8.07 |
| halophyte | 1.12 |
| haplotype | 1.04, 5.40 |
| haplotype mining | 5.32 |
| haplotype sharing | 5.33 |
| haplotype-aware variant analysis | 5.29 |
| HD-ZIP I transcription factors | 2.23 |
| HD-ZIP II transcription factors | 2.18 |
| heat stress | 6.16 |
| Helianthus annuus L. | 3.09 |
| hemotype variation | 4.05 |
| hemp | 2.20 |
| Hieracium | 2.10 |
| High-resolution melting (HRM) | 2.05 |
| high-throughput methodology | 3.16 |
| high-throughput phenotyping | 5.30, 5.41, 5.48 |
| histone modifications | 6.03 |
| historic mutants | 5.01 |
| Hordeum vulgare | 2.04, 7.09 |
| host-pathogen interactions | 5.57 |
| hybrid capture sequencing | 5.40 |
| I | |
| imaging | 5.43 |
| immune receptors | 3.05 |
| in vitro cultures | 4.06 |
| in vitro micropropagation | 5.57 |
| in vitro regeneration | 2.10, 2.24 |
| indole alkaloids | 4.17 |
| insect resistance mechanism | 8.19 |
| intercropping | 8.13 |
| Interkingdom plant–microbe signalling | 6.19 |
| Intra-cultivar variability | 5.51 |
| introgression lines | 2.13 |
| invasive species | 4.17 |
| Italian varieties | 5.26 |
| J | |
| jasmonic acid | 3.06 |
| jasmonic acid signaling | 8.19 |
| K | |
| k-mer | 1.04 |
| KASP | 4.05, 5.26 |
| KASP marker | 2.21 |
| knockout | 3.07 |
| Kompetitive Allele-Specific PCR (KASP) | 5.35 |
| L | |
| landraces | 4.10, 4.11, 5.12, 5.28, 7.10 |
| landscape genomics | 5.34, 5.37 |
| late blight | 1.13 |
| lateral organ development | 6.22 |
| lateral root cap | 2.02, 2.12 |
| leaf angle | 2.26 |
| leaf erectness | 2.04 |
| leaf vein transparency | 3.14 |
| Lens culinaris | 5.04, 5.37 |
| lettuce | 2.06, 2.18 |
| light acclimation | 6.15 |
| lignin and cellulose biosynthesis | 2.28 |
| lignin biosynthesis | 2.09 |
| linkage maps | 3.18 |
| lipidome | 3.06 |
| lipoxygenase | 3.06 |
| local adaptation | 5.34, 5.37 |
| local varieties | 5.53 |
| Long shelf-life (LSL) | 8.05 |
| long-read transcriptomics | 4.04 |
| LYCOPENE β-CYCLASE 2 (LCYb2) | 2.05 |
| M | |
| machine learning | 3.04, 7.01 |
| MAGIC | 5.13 |
| MAGIC maize | 5.43 |
| MAGIC population | 3.11, 5.23 |
| maize | 2.26, 3.11, 5.28, 5.31, 5.54, 7.10, 7.16 |
| Malayan kumquat | 2.15 |
| male sterility | 2.09 |
| mapping by sequencing | 7.11 |
| mapping population | 3.14, 7.08 |
| Marker selection | 3.10 |
| Marker-Assisted BackCrossing | 3.21 |
| Marker-assisted breeding | 5.45 |
| Marker-assisted selection | 3.02 |
| marker-free vector | 2.15 |
| maternal-excess endosperm | 8.02 |
| maturity date | 6.06 |
| Medicago sativa | 8.17 |
| Mediterranean environments | 2.21 |
| Mesorhizobium | 7.19 |
| metabolic engineering | 4.18 |
| metabolites | 1.13 |
| metabolomic analysis | 6.20 |
| metabolomic profiling | 5.21 |
| metal transporter | 7.05 |
| metal-tolerant species | 7.05 |
| micronutrient homeostasis | 7.05 |
| microRNAs | 6.03 |
| miRNA | 4.12 |
| miRNA-seq | 6.19 |
| miRNAs | 4.15 |
| mitotic cell cycle | 2.02 |
| molecular markers | 3.09, 5.36 |
| molecular traceability | 3.10 |
| MTP1 | 7.05 |
| multi-mapping population | 5.10 |
| multi-omics | 6.02, 6.10, 6.17, 7.19 |
| multi-omics integration | 6.25, 7.13 |
| multi-trait GWAS | 3.03 |
| Multiparental mapping population | 5.46 |
| multiparental population | 5.11 |
| mutant | 2.26, 3.19, 5.22 |
| mutant population | 7.06 |
| MYB60 | 7.17 |
| mycorrhization | 6.24 |
| mycotoxins | 5.52 |
| N | |
| NAC | 6.06 |
| NAC factors | 6.04 |
| NAM RILs | 5.47 |
| National Coordination Center for Conservation of the PGRFA | 5.15 |
| natural variation | 5.32 |
| New genomic techniques | 2.24 |
| New genomics techniques | 1.06 |
| new serotonergic drugs | 4.17 |
| Next Generation Sequencing | 5.44 |
| NIR analysis | 4.14 |
| nitrogen | 7.01, 7.02, 7.10 |
| nitrogen fertilization | 5.28 |
| Non-integrative DNA delivery | 2.05 |
| novel nuclease | 8.07 |
| NRT1.1B | 7.07 |
| NUE | 7.02, 7.07, 7.10, 7.15 |
| nutrients uptake | 7.11 |
| nutritional composition | 4.14 |
| nutritional quality | 5.52 |
| O | |
| oilseed crop | 4.09 |
| Olea europaea | 3.12, 5.33, 5.57 |
| olive | 4.02, 8.08 |
| ONT | 1.10 |
| ONT sequencing | 4.05, 5.46 |
| Organogenesis | 2.24 |
| orthology | 6.12 |
| Oryza sativa | 7.18 |
| Oryza sativa ssp. indica | 7.15 |
| Oryza sativa ssp. japonica | 7.15 |
| outcrossing species | 5.53 |
| Outlier SNP | 5.16 |
| P | |
| P. coccineus | 4.11 |
| PacBio | 1.10 |
| Paclobutrazol (PAC/PBZ) | 2.29 |
| pale green | 3.19 |
| pangenome | 1.03, 1.04, 1.08, 5.02, 6.01 |
| pangenome graph | 5.32 |
| pangenome-based breeding | 6.13 |
| pangenomics | 5.46 |
| pantranscriptome | 5.02 |
| participatory plant breeding | 5.36 |
| Paspalum simplex | 8.02 |
| peach | 6.06 |
| Phaseolus vulgaris L. | 6.22 |
| phenotypic absorbance spectra data | 8.11 |
| phenotypic characterization | 8.11 |
| phenotypic diversity | 5.04 |
| phenotypic field data | 8.11 |
| phenotypic plasticity | 5.39 |
| phenotyping | 5.10, 5.27, 5.38, 6.18 |
| Phosphorus | 7.01 |
| photosynthesis | 3.19 |
| phylogenetic analysis | 2.14 |
| phylogenomics | 1.09 |
| physiological adjustments | 6.21 |
| physiological profiling | 7.03 |
| phytic acid | 4.03 |
| phytocannabinoids | 2.20, 8.04 |
| phytohormone signaling | 6.25 |
| Phytophthora infestans | 8.10 |
| pigmentation | 4.19 |
| Pisum sativum | 6.24 |
| plant architecture | 2.16, 2.26, 2.28 |
| plant breeding | 3.09, 4.08 |
| plant cell cultures | 4.16 |
| plant development | 2.18 |
| plant disease resistance | 3.05 |
| plant genetic resources | 5.04 |
| plant growth-promoting bacteria | 7.12, 7.13 |
| plant growth-promoting microorganisms | 8.16 |
| plant metabolic engineering | 4.16 |
| plant molecular farming | 8.12 |
| plant phenomics | 3.15 |
| plant phenotyping | 3.16 |
| plant regeneration | 2.06, 2.14, 2.27 |
| plant tissue architecture | 2.27 |
| plant tissue culture | 2.10 |
| plants memory | 8.01 |
| plant–microbe interactions | 7.13 |
| plastid transformation | 8.12 |
| pleiotropy | 3.03 |
| pollen germination | 2.22 |
| polyploid wheat | 6.11 |
| polyploidy | 3.09 |
| poplar | 2.28 |
| population genomics | 5.09, 5.21, 6.11, 8.18 |
| population structure | 5.25, 5.37, 5.56, 8.14 |
| pre-breeding | 5.04, 5.21, 5.23, 5.32 |
| prebreeding | 5.31, 5.54 |
| precision agriculture | 8.03 |
| precision breeding | 6.01 |
| Presence/Absence Variants | 5.06 |
| priming | 6.18 |
| protein hydrolysates | 7.04 |
| proteomic | 7.02 |
| proteomics | 6.19 |
| protoplast regeneration | 2.17 |
| protoplasts | 2.24, 2.25 |
| Prunus dulcis | 5.25 |
| Prunus persica L. Batsch | 3.18 |
| pseudogamy | 8.02 |
| PSY1 | 3.07 |
| pumpkins | 4.08 |
| Q | |
| qPCR | 8.17 |
| QTL mapping | 4.04, 5.05, 5.10, 5.43, 5.45, 6.23, 8.05, 8.09 |
| QTLs | 5.38 |
| Quantitative trait loci (QTL) | 5.35 |
| Quantitative traits | 5.46 |
| R | |
| radial growth | 2.12 |
| recalcitrance | 2.08, 8.04 |
| Recombinant Imbred Lines | 7.08 |
| Recombinant Inbred Intercross (RIX) | 3.11 |
| Recombinant Inbred Lines | 6.14 |
| reduced soil fertility | 8.16 |
| regeneration | 2.20 |
| regulatory networks | 2.27 |
| remote sensing | 5.11, 8.03 |
| repeat depletion | 5.44 |
| reproductive development | 6.12 |
| resilience to multiple stress factors | 1.06 |
| Resistance genes | 6.14 |
| Rht25 | 5.40 |
| rice (Oryza sativa) | 5.18 |
| Ricinus communis | 6.13 |
| RNA-seq | 2.09, 5.38, 5.42, 6.08, 6.15, 6.18, 6.22, 6.23 |
| RNA-seq transcriptomics | 6.20 |
| RNASeq | 6.14 |
| RNAseq | 6.05, 8.06 |
| root anatomy | 5.41 |
| root development | 2.12 |
| root hair | 7.11 |
| root microbiota | 7.15 |
| root phenotyping | 5.17 |
| root system architecture | 5.19, 5.41, 5.49 |
| Root System Architecture (RSA) | 5.39 |
| root traits | 5.08 |
| root-associated microbes | 7.14 |
| roots | 5.54 |
| S | |
| Salicornia | 1.12 |
| salinity | 5.18, 7.04 |
| salinity stress | 6.03, 6.10 |
| salt stress | 6.08 |
| salt tolerance | 5.17 |
| salt-response | 5.42 |
| Sarcocornia | 1.12 |
| Scanning Electron Microscopy | 7.11 |
| sea rocket | 5.42 |
| secondary metabolism | 4.13, 4.16 |
| secondary metabolite | 4.02 |
| seed development | 2.11, 5.05 |
| seed priming | 7.04 |
| seed quality | 1.07, 7.18 |
| seedling emergence | 7.18 |
| seeds | 7.18 |
| selection signature | 2.19 |
| selection signatures | 5.55 |
| selective sweeps | 5.56 |
| self-compatibility | 1.05 |
| semi-dwarf | 2.21 |
| Septoria tritici blotch | 3.15 |
| sequence classification | 3.05 |
| Silymarin biosynthesis | 4.05 |
| Single nucleotide polymorphism | 5.16 |
| smart canopy | 3.21 |
| SmHQT | 4.13 |
| SNP | 4.12, 5.24 |
| SNP linkage map | 6.23 |
| SNP panel optimization | 3.10 |
| SNPs | 5.26 |
| soil microbiome | 3.13 |
| soil–plant molecular crosstalk | 8.16 |
| Solanaceae | 7.02 |
| Solanum lycopersicum | 3.14, 6.21 |
| Solanum lycopersicum L. | 8.05, 8.10 |
| Solanum melongena | 2.09, 6.09, 7.08, 8.09 |
| somaclonal variation | 5.29 |
| somatic embryogenesis | 1.06 |
| Sorghum bicolor | 5.52 |
| Southern green stink bug | 8.19 |
| soybean | 7.17 |
| space agriculture | 2.22 |
| spatial genetic structure | 5.53 |
| SPET | 5.24 |
| SPET genotyping | 5.05 |
| Spike fertility | 4.14, 5.14 |
| SSR markers | 4.11, 8.14 |
| stomata | 5.43, 5.48, 7.16, 7.17 |
| storage proteins | 5.52 |
| Streptomyces violaceoruber | 7.13 |
| stress adaptation | 6.21 |
| strigolactones | 6.24 |
| structural variants | 5.46, 6.05, 6.06 |
| structural variation | 1.11 |
| structural variations | 6.09 |
| subspecies | 1.08 |
| SULTR | 4.03 |
| summer truffle | 8.18 |
| susceptibility genes | 2.08 |
| sustainability | 8.13 |
| sustainable agriculture | 4.03, 7.04, 7.13 |
| sustainable production | 4.06 |
| sustainable viticulture | 6.15 |
| Sweet basil | 2.14 |
| symbiosis | 7.14 |
| SynCom | 7.14 |
| T | |
| TALE | 2.06 |
| taxonomy | 8.13 |
| teff pangenome | 1.11 |
| temporal dynamics | 3.13 |
| terpenes | 2.20 |
| tetraploid wheat | 5.02, 5.40, 5.41 |
| tetraploidy | 6.10 |
| thermophilic enzyme production | 8.12 |
| thermotolerance | 6.16 |
| thousand-seed weight | 4.09 |
| TILLING | 2.04, 6.22, 7.11 |
| TILLING-by-Sequencing | 3.01 |
| ToBRFV | 3.02 |
| tomato | 2.13, 2.23, 3.07, 4.18, 5.22, 5.36, 6.02, 6.07, 6.17, 8.07 |
| tomato (Solanum lycopersicum) | 6.16 |
| tomato hybrids | 3.20 |
| tomato landraces | 8.19 |
| transcriptional memory | 6.07 |
| transcriptional networks | 6.25 |
| transcriptional regulation | 2.06 |
| transcriptional remodelling | 8.06 |
| transcriptome | 3.06, 8.02 |
| transcriptome analysis | 6.16 |
| transcriptome reprogramming | 6.21 |
| transcriptomic | 7.02, 7.10 |
| transcriptomic landscape | 7.12 |
| transcriptomic profiling | 8.19 |
| transcriptomics | 4.19, 6.02, 6.24, 7.03, 7.06 |
| transgenerational stress effects | 8.01 |
| transposable element exaptation | 1.02 |
| transposable elements | 5.06 |
| trascriptome reprogramming | 8.15 |
| Triticum aestivum | 1.08 |
| Triticum durum | 5.14, 5.17 |
| Triticum durum Desf. | 6.08 |
| Triticum monococcum | 5.09 |
| Tuber aestivum | 8.18 |
| turmeric | 4.12 |
| U | |
| UAV-based phenotyping | 5.07 |
| underutilized crops | 1.09 |
| underutilized legumes | 1.07 |
| untargeted metabolomics | 4.16 |
| uORFs | 2.23 |
| V | |
| vanillin | 4.16 |
| variant calling optimization | 5.03 |
| varietal identification | 5.50 |
| vegetable melons | 1.09 |
| veins | 5.43 |
| VIGE | 3.17 |
| vitamin A deficiency | 4.10 |
| Vitamin D | 4.18 |
| Vitis vinifera | 2.07, 5.05, 6.15 |
| Vitis vinifera L | 5.16 |
| volatile organic compounds | 5.23 |
| volatilome | 5.27 |
| W | |
| water deficit | 7.03 |
| water use efficiency | 7.09 |
| WGCNA | 4.18, 6.20 |
| WGS | 8.08 |
| wheat | 3.17, 4.04, 5.42 |
| wheat breeding | 1.08 |
| wheat genome evolution | 1.02 |
| white grain sorghum | 5.20 |
| White maize | 4.10 |
| Whole Genome Sequencing (WGS) | 5.50 |
| whole-genome duplication | 6.10 |
| whole-genome resequencing | 5.56 |
| whole-genome sequencing | 5.26 |
| Whole-genome sequencing (WGS) | 5.03 |
| Whole-Genome Sequencing (WGS) | 6.22 |
| wild beet germplasm | 5.07 |
| wild emmer | 1.03 |
| wild relatives | 1.05 |
| wild species | 1.13 |
| WOX | 2.06, 2.14 |
| WUE | 7.07 |
| X | |
| Xylella fastidiosa | 2.17, 5.33, 5.57, 8.08 |
| Y | |
| y1 | 4.10 |
| yeast two hybrid | 7.06 |
| yellow rust resistance | 5.35 |
| yield components | 3.03 |
| yield improvement | 5.47 |
| yield-related traits | 8.09 |
| 6 | |
| 60K Almond SNP Array | 5.25 |
| 9 | |
| 90K SNP array | 4.14 |