| A | |
| ABA | 4.06 |
| abiotic stress | 2.29, 2.32, 2.36, 2.51, 2.63, 6.30 |
| Abiotic stress | 2.30, 4.05, 4.26, 8.10 |
| Abiotic stress response | 1.11 |
| Abiotic stresses | 4.01 |
| Abscisic acid | 2.34 |
| abscisic acid | 6.35 |
| acetogenic bacteria | 8.01 |
| Aegilops caudata | 2.24, 3.07 |
| AFLP | 6.19 |
| agrobiodiversity | 6.08, 6.09, 7.15 |
| agrofood system | 2.74 |
| Agronomic practices | 4.39 |
| AI-based breeding | 9.02 |
| AI-powered phenotyping | 4.17 |
| Alfa-mannosidase | 3.14 |
| Alfalfa | 4.13 |
| alien gene transfer | 6.30 |
| allele mining | 2.54 |
| allele-specific expression | 3.08 |
| Almond | 6.47 |
| Almond; Microsatellites; Phenotypic descriptors; Biodiversity safeguard; Marche region | 8.17 |
| AMF | 5.12 |
| AMF responsiveness | 4.29 |
| anthesis control | 1.05 |
| anthocyanins | 2.36, 3.01, 3.11 |
| Anthocyanins | 3.15 |
| Anti-inflammatory | 3.03 |
| antiflorigens | 2.02 |
| antioxidants | 8.14 |
| Apical meristem | 2.53 |
| Apocarotenoids | 4.06 |
| Apomixis | 6.18 |
| apple | 1.02, 1.03 |
| Apple | 3.10, 6.37 |
| apple breeding | 5.15 |
| apple tree | 8.19 |
| Apricot | 3.12 |
| Apulia region | 5.20 |
| Arabidopsis | 2.21, 2.33, 4.31, 4.45 |
| Arabidopsis thaliana | 2.39, 2.63 |
| arbuscular mycorrhizal fungi | 1.10, 4.14, 4.19 |
| arbuscular mycorrhizal fungi (AMF) | 5.06 |
| Aroma | 6.13 |
| artificial intelligence | 10.01 |
| Artificial intelligence | 4.23 |
| Association analysis | 6.44 |
| association studies | 1.13 |
| Asteraceae | 2.25 |
| Asymmetric cell division | 2.39 |
| ATAC-seq | 4.38 |
| ATI | 3.20 |
| Atropa belladonna | 2.51 |
| Auxin | 2.53 |
| auxin | 2.25 |
| awn | 2.23 |
| B | |
| baby fruits | 6.50 |
| Bacteria | 1.01 |
| Bacterial endophytes | 4.21, 4.44 |
| Barcoding | 4.21, 8.12 |
| barley | 2.44, 2.49, 5.01, 6.33 |
| Barley | 2.20, 2.40, 2.46, 4.17, 6.38 |
| Base Editing | 6.41 |
| bayesian statistics | 6.06 |
| beans | 2.37 |
| Bidnija olive grove | 8.18 |
| Bio-hydrogen | 8.02 |
| bioactive compounds | 2.64, 3.09, 5.12 |
| Biochemical analysis | 2.10 |
| Biocontrol agent | 5.26 |
| Biodiveresity | 8.12 |
| biodiversity | 2.78, 3.13, 7.10, 8.18 |
| Biodiversity | 2.10, 5.28, 8.15 |
| bioenergy | 4.36 |
| biofertilizer | 4.12 |
| Biofortification | 3.05 |
| Biogenic volatile organic compounds | 2.53 |
| Bioinformatic tools | 1.07 |
| biopesticides | 7.09 |
| biostimulant | 2.16 |
| Biostimulant | 2.56 |
| Biostimulants | 2.15, 2.50 |
| biostimulants | 2.63, 4.31, 4.34, 7.12 |
| Biotic stress | 2.68, 5.29 |
| Biotic Stress | 5.14 |
| biotic stresses | 5.31 |
| biotic/abiotic stress | 2.37 |
| Bisulfite sequencing | 3.15 |
| Blood orange | 3.15 |
| Brassica oleracea | 6.10 |
| Brassica spp. | 7.14 |
| Brassicaceae | 1.05, 2.45, 7.09 |
| Brassinosteroid | 2.70 |
| Bread and durum wheat | 2.61 |
| bread wheat | 4.03 |
| Breeding | 6.44, 7.04 |
| breeding | 2.37, 2.73, 2.78, 4.34, 6.23, 6.28, 6.45, 6.46, 6.51, 7.06 |
| Breeding strategies | 6.17 |
| Brix degree | 8.13 |
| broccoli | 6.10 |
| broccoli-raab | 6.24 |
| Bronze tomato | 3.18 |
| Broomrape | 5.08 |
| BSA | 2.44 |
| BSAseq | 6.23 |
| BSMV | 5.32 |
| Budbreak | 2.09 |
| C | |
| callus | 4.09 |
| callus cultures | 1.02 |
| Camelina | 2.18 |
| Candidare genes | 4.04 |
| candidate gene | 8.07 |
| candidate genes | 4.19, 4.47 |
| Candidate genes | 4.49 |
| Cannabis | 6.31 |
| CAPFITOGEN tools | 2.76 |
| Capsicum annuum | 3.21, 7.06 |
| Capsicum annuum L. | 2.10 |
| Carbohydrate quality | 3.04 |
| carbon accumulation | 6.30 |
| Cardamine hirsuta | 2.39 |
| carotenoid content | 3.17 |
| Cas9 orthologs | 6.41 |
| CBF Genes | 2.20 |
| cell wall | 9.01 |
| cellular level phenotyping | 4.16 |
| Characterization | 2.67 |
| characterization | 2.74 |
| chemotype | 3.13 |
| chestnut | 5.17 |
| chestnut micropropagation | 7.11 |
| Chilling Injuries | 2.41 |
| ChIP-seq | 4.35 |
| ChIP-Seq | 4.25 |
| Chromosome engineering | 6.40 |
| chromosome-scale genome assembly | 5.12 |
| circadian clock | 2.55 |
| Circular economy | 5.13 |
| cistrome | 4.11 |
| citrus | 6.02 |
| Citrus limon | 5.26 |
| Climate change | 2.22, 2.70 |
| Climate variability | 4.23 |
| CO2 reductase | 8.01 |
| Cold | 3.15 |
| Cold Acclimation | 2.20, 4.15 |
| Cold stress | 4.15 |
| Colonization | 4.22 |
| Commercial variety | 4.35 |
| Common bean | 8.09 |
| common wheat | 6.45 |
| compact soil | 2.06 |
| Complementarity analysis | 2.76 |
| Conservation | 2.28 |
| conservation | 7.15 |
| conservative agriculture | 2.62 |
| constant light | 2.55 |
| Core collections | 2.67 |
| corky root rot | 5.22 |
| coronatine | 2.26 |
| cortex | 2.06 |
| Cortex | 2.39 |
| cover crop | 2.18 |
| CRF transcription factors | 1.11 |
| Crispr-Cas | 6.20 |
| Crispr-Cas9 | 2.73 |
| CRISPR-Cas9 | 1.08 |
| CRISPR-cas9 | 5.33 |
| CRISPR/Cas9 | 2.34, 2.53, 2.68, 5.06, 5.22, 5.28, 5.32, 6.12, 6.40, 6.43, 6.48 |
| CRISPR/Cas9 platform for plants | 6.41 |
| CRISPR/Cas9 system | 5.07 |
| CrisprCas9 | 2.70 |
| crop improvement | 7.01 |
| crop protection | 5.09 |
| Crop yield improvement | 4.26 |
| Crops | 2.40 |
| cross populations | 4.48 |
| cross-species analyses | 2.08 |
| crude protein yield | 6.14 |
| cryptochromes | 6.24 |
| CslF6 gene | 3.07 |
| Cucurbita spp. | 5.23 |
| Cucurbitaceae | 5.29 |
| culm morphology | 2.44, 2.46 |
| Curly leaf | 4.15 |
| cuticle | 2.03, 4.33, 9.01 |
| CWR | 2.76 |
| Cynara cardunculus var. altilis | 5.12 |
| cytokinin | 4.31 |
| cytokinins | 2.25 |
| D | |
| D27-likes | 2.34 |
| DArTseq | 3.13 |
| Dasypyrum villosum | 3.07 |
| ddRAD-seq | 3.09 |
| De novo assembly | 1.07, 4.13 |
| Deasease resistance | 5.16 |
| decreased irrigation | 2.16 |
| defense | 9.01 |
| development | 2.72 |
| developmental plasticity | 2.65 |
| Developmental trajectories | 1.12 |
| Diagnostic markers | 2.61 |
| Diatoms | 8.02 |
| differential DNA methylation | 3.08 |
| differentially expressed genes | 5.25 |
| Digitaria exilis | 7.08 |
| Diplotaxis tenuifolia | 2.71, 6.15 |
| Disease resistance | 5.30 |
| DNA editing | 4.49 |
| DNA methylation | 3.15, 8.13, 8.19 |
| DNA-free genome editing | 5.27 |
| Domestication history | 6.51 |
| Dormancy | 2.17 |
| Double Haploids | 2.46 |
| Drought | 2.21 |
| drought | 2.03, 2.47, 2.54, 4.11, 4.24, 4.34 |
| Drought Resilience | 6.04 |
| drought resistance | 4.33 |
| Drought stress | 4.05, 4.44 |
| drought stress | 2.32, 2.66, 4.14, 4.25, 4.41, 6.01, 6.35 |
| Drought Stress | 4.27 |
| drought tolerance | 4.19 |
| Drought tolerance | 2.52, 4.40 |
| drought-stress response | 4.38 |
| Durium wheat | 6.49 |
| durum wheat | 2.62, 2.72, 3.01, 4.09, 6.03, 6.33, 8.07 |
| Durum Wheat | 6.04, 8.10 |
| Durum wheat | 2.70, 2.77, 3.05, 3.20, 4.23, 7.05 |
| DUS and VCU | 6.39 |
| Dwarf 27 | 2.34 |
| Dwarfing genes | 2.52 |
| dynamic response | 4.20 |
| E | |
| ecotype | 6.09 |
| ecotypes | 6.08 |
| efficiency | 8.16 |
| eggplant | 6.23 |
| Eggplant | 6.12 |
| Electric field | 5.33 |
| elicitors | 2.26 |
| endoplasmic reticulum | 2.27 |
| Environmental plastic pollution | 4.30 |
| environmental stresses | 7.07 |
| Epigenetic | 2.09 |
| epigenetic changes | 8.19 |
| epigenetic mechanisms | 4.38 |
| Eragrostis curvula | 6.18 |
| Eragrostis tef | 6.29 |
| ERF | 2.28 |
| Erysiphe necator | 5.21 |
| essential oils | 1.05 |
| ethylene | 2.29 |
| European olive oils | 8.05 |
| EVA collection | 4.37 |
| evaluation network | 7.02 |
| evo-devo | 2.06 |
| evolutionary genetics | 5.05 |
| EVOO | 8.03 |
| expression Quantitative Trait Loci mapping | 1.04 |
| F | |
| faba bean | 6.06 |
| Ficus carica | 4.07 |
| fig tree | 3.08 |
| fine-mapping | 6.46 |
| fingerprinting | 6.08 |
| Fire blight | 4.08 |
| Firmness | 6.22 |
| Flavonoids | 3.03, 3.21 |
| FLC gene | 2.18 |
| Flooding | 2.28 |
| Flooding tolerance | 2.01 |
| Flooding Tolerance | 4.18 |
| florigens | 2.02 |
| flower fertility | 2.02 |
| Flower organ identity | 2.33 |
| Flower organ polarity | 2.33 |
| flowering | 4.34, 6.24 |
| Flowering | 2.09, 2.21, 6.47 |
| flowering time | 2.18, 6.15 |
| foliar disease | 5.24 |
| fonio | 7.08 |
| Food security | 2.04 |
| Freezing | 4.15 |
| Frost Resistance | 2.20 |
| Frost tolerance | 4.01 |
| Fructans | 3.20 |
| fruit and plant morphological traits | 7.11 |
| fruit chemical composition analyses | 7.11 |
| fruit color | 3.11 |
| Fruit development | 4.39 |
| fruit genomics | 9.02 |
| fruit quality | 6.05, 6.16 |
| Fruit quality | 6.37 |
| Fruit softening | 6.22 |
| fruit traits | 4.07 |
| Fruit tree breeding | 9.02 |
| functional phenotyping | 4.20 |
| functional genomics | 6.33 |
| fungal diseases | 5.19 |
| fungi | 5.31 |
| fungi infection | 6.45 |
| Fusarium Ear Rot | 5.16 |
| Fusarium graminearum | 5.13 |
| Fusarium resistance | 8.07 |
| Fusarium verticillioides | 5.10, 5.11, 5.13 |
| G | |
| GAD1 gene | 2.23 |
| Gas exchanges | 4.28 |
| GC/MS | 3.18 |
| gene coexpression network | 2.72 |
| Gene editing | 7.01 |
| gene editing | 5.17, 6.05, 9.01 |
| Gene expression | 2.12 |
| GENE EXPRESSION | 2.58 |
| gene expression | 2.08 |
| Gene expression regulation | 1.12 |
| Gene network | 1.12 |
| Gene Regulation | 1.08 |
| Gene Regulatory Network | 1.04, 2.65 |
| Gene regulatory network | 6.35 |
| Gene silencing | 2.38 |
| Gene-Targeting | 6.41 |
| genetic adaptation | 10.01 |
| genetic analysis | 3.17 |
| genetic divergence | 2.31 |
| genetic diversity | 4.07, 5.05, 6.08, 6.27, 6.28, 7.02, 7.03, 7.11 |
| Genetic diversity | 2.48, 6.17 |
| genetic engineering | 2.04 |
| genetic improvement | 3.09, 5.31 |
| genetic linkage map | 8.07 |
| genetic potential | 2.24 |
| genetic resources | 2.37, 2.74, 4.46, 8.18 |
| Genetic resources | 2.67 |
| Genetic variability | 2.40 |
| genetic variability | 3.02, 4.11, 8.11, 9.02 |
| Genetica Diversity | 3.12 |
| Genome editing | 5.11, 6.20, 6.43, 6.48, 8.02 |
| Genome Editing | 2.70, 6.22 |
| genome editing DNA-free | 5.07 |
| genome sequencing | 1.13 |
| Genome sequencing | 1.07 |
| Genome wide association mapping | 2.48 |
| Genome Wide Association Study GWAS | 6.04 |
| Genome-wide association studies | 5.30 |
| Genomic approaches | 6.21 |
| genomic prediction | 6.03 |
| genomic regions | 5.24 |
| genomic selection | 6.14 |
| genomic selection in plant breeding | 6.34 |
| genomics | 6.39 |
| Genomics | 4.04, 6.32 |
| Genotype | 6.38 |
| genotypic variation | 3.06 |
| Genotyping | 2.10, 5.20 |
| genotyping | 8.18 |
| Genotyping-by sequencing | 2.31 |
| germination parameters | 2.14 |
| Germplasm | 6.44 |
| germplasm | 8.11 |
| Germplasm bank | 6.21 |
| germplasm characterization | 6.25 |
| Germplasm collection | 3.10 |
| Germplasm Collection | 3.12 |
| global warming | 4.48 |
| glucoraphanin | 2.26 |
| glucosinolates | 7.09 |
| Glutathione pathway | 2.13 |
| Glutathione S-transferases | 4.41 |
| glycoalkaloids | 3.16 |
| Grafting | 8.13, 8.19 |
| grain protein content | 3.06 |
| Grain size | 2.04 |
| grain size-related traits | 4.47 |
| grain weight | 4.47 |
| grain yield | 6.14 |
| Grapevine | 1.08, 2.73, 4.39, 5.27 |
| grapevine | 5.06, 9.01 |
| Grapevine physiology | 4.27 |
| Grapevine Rootstocks | 4.27 |
| graph pangenome | 6.11 |
| gravitropism | 2.49 |
| Green Revolution | 2.52 |
| greenhouse | 2.07 |
| greenhouse gas emissions | 10.01 |
| GRF gene family | 6.33 |
| Growth habit | 2.61 |
| growth progression | 4.32 |
| Gut microbiome | 3.04 |
| GW analysis | 2.62 |
| GWAS | 2.21, 2.46, 4.01, 4.22, 4.36, 4.37, 5.04, 6.11, 6.39, 6.45, 6.47, 6.49 |
| gwas | 4.07 |
| GxE | 8.10 |
| H | |
| Halophytes | 4.21 |
| haplotype diversity | 7.03 |
| haplotype-phased genome | 3.08 |
| HD-Zip II | 2.33 |
| HDCR | 8.01 |
| Health | 3.04 |
| Health-promoting pigments | 3.21 |
| heat stress | 2.71, 4.42 |
| Heat stress | 4.04 |
| Heavy metals | 2.12 |
| Helianthus annuus L. | 4.38 |
| Hemp | 2.17 |
| hemp | 2.35, 6.26 |
| herbicidal RNAi | 5.09 |
| herbicide resistance | 5.09 |
| heterosis | 7.07 |
| High-throughput | 7.05 |
| high-throughput phenotyping | 6.06 |
| high-throughput screening | 8.01 |
| Highthrouput Plant Phenotyping | 4.27 |
| histone modification | 2.64 |
| histone modifications | 4.25 |
| Historical Italian rice varieties | 2.23 |
| holobiont | 2.16 |
| Hordeum vulgare | 2.42, 2.43 |
| hormones | 2.25 |
| HS-SPME | 2.35 |
| Human health | 2.12 |
| hybrids | 7.07 |
| hydrogen | 8.01 |
| Hydrolase enzymes | 4.30 |
| Hydroponic culture | 3.14 |
| Hypoxia | 2.01 |
| I | |
| iMAGIC | 6.38 |
| in situ conservation | 2.76 |
| In vitro regeneration | 5.33 |
| in vitro regeneration | 6.12 |
| in vivo monitoring | 4.20 |
| In-vitro | 2.32 |
| INCREASE | 2.78 |
| Indigenous crops | 6.25 |
| inflorescence development | 2.02 |
| ink disease | 5.17 |
| intragenic | 5.02 |
| Introgression Lines | 6.32 |
| invasive species | 2.51 |
| inversion | 6.40 |
| ionome | 3.02 |
| Italian maize inbred lines | 2.48 |
| J | |
| jasmonic acid | 2.29 |
| Jordan | 2.37 |
| K | |
| KASP | 7.13 |
| Kernel | 6.47 |
| Kernel traits | 6.44 |
| kernels | 3.02 |
| Kiwifruit | 2.09 |
| Kosakonia sacchari | 4.22 |
| L | |
| Lactuca sativa | 6.43 |
| landrace | 6.10 |
| Landrace | 4.35 |
| landrace diversity | 6.24 |
| landraces | 3.17 |
| Landraces | 2.37, 6.07, 7.14 |
| Landscape-genomics | 6.07 |
| large genomes | 1.13 |
| Lateral Root | 2.05 |
| Lazio germplasm | 7.14 |
| lead-free perovskite | 2.07 |
| Leaf erectness | 2.42 |
| leaf permeability | 2.03 |
| leafy crops | 2.25 |
| legume crops | 2.37 |
| Legumes | 4.01 |
| legumes | 2.78 |
| lemon | 5.31 |
| lentil | 2.74, 2.78 |
| Lentil | 2.67 |
| Lentil genotypes | 2.66 |
| Lettuce | 2.56 |
| lettuce | 1.10 |
| Linkage Mapping Population | 5.04 |
| lipoxygenase | 5.10 |
| Local accessions | 8.15 |
| local genotype preservation | 6.27 |
| Local Germplasm | 8.04 |
| lodging | 2.44, 2.46 |
| Long reads | 1.07 |
| long-read sequencing | 7.03 |
| Long-reads | 1.09 |
| Low coverage sequencing | 1.09 |
| low oxygen | 1.03 |
| LRD gene expression | 2.54 |
| Lunar | 4.45 |
| M | |
| machine learning | 6.06 |
| macroelements | 4.36 |
| MAGIC | 4.33, 7.06 |
| MAGIC maize population | 5.16 |
| MAGIC population | 4.24, 4.32, 7.10 |
| maize | 2.03, 4.11, 4.24, 4.32, 5.10, 7.01, 7.02, 7.09, 10.01 |
| Maize | 2.05, 6.07 |
| maize leaf transcripts | 1.04 |
| Malsecco | 5.31 |
| Mapping by sequencing | 4.40 |
| marker | 6.26 |
| Marker Assisted Selection (MAS) | 5.14 |
| marker-assisted backcross | 6.36 |
| markers | 4.42 |
| MAS | 5.15 |
| MCSeEd | 8.13 |
| MCSeEd genotyping | 6.17 |
| Medicago sativa | 6.20 |
| Melatonin | 2.30 |
| memory acquisition | 2.57 |
| Metabarcoding | 4.28 |
| metabolic activity | 4.16 |
| Metabolic Engineering | 2.59 |
| metabolic engineering | 3.18 |
| Metabolite profiling | 3.10 |
| metabolomic analysis | 2.51 |
| Metabolomics | 4.10, 6.32 |
| Metagenomics | 4.44 |
| Microalgae | 2.50, 4.30, 8.02 |
| microbial consortia | 1.10 |
| Microbiome | 1.01, 6.52 |
| microbiome | 9.02 |
| Microbiota | 4.45 |
| Microelements | 3.05 |
| Microsatellite | 6.42 |
| microsatellite markers | 8.05 |
| microtom | 7.12 |
| Mildew | 4.08 |
| milk thistle | 3.13 |
| Mimosa pudica | 2.57 |
| minor cereals | 7.08 |
| miR156 | 2.36 |
| mixed-linkage glucan | 3.07 |
| modern breeding | 2.71 |
| Molecular Biology | 1.08 |
| Molecular biology of plant development | 2.19 |
| molecular characterization | 6.19 |
| Molecular markers | 6.42, 7.14 |
| molecular tools | 6.50 |
| Molecular validation | 2.52 |
| morphological characterization | 3.17 |
| multi parental cross design | 6.16 |
| multi-environment trial | 2.62 |
| Multigenic family | 2.56 |
| Multiparental maize population | 1.04 |
| multiparental population | 6.28 |
| mutagenesis | 8.09 |
| mutants | 2.43 |
| Mycotoxigenic fungi control | 5.13 |
| mycotoxins | 7.09 |
| N | |
| NaDES | 3.16 |
| nanofertilizers | 3.19 |
| nanomaterials | 8.06 |
| NASA | 4.45 |
| NB-LRR proteins | 5.23 |
| necrotrophic fungi | 5.03 |
| Nested Association Mapping (NAM) | 6.29 |
| Network analyses | 1.11 |
| New Plant Breeding Techniques | 5.21 |
| Next-Generation Sequencing (NGS) | 6.48 |
| NGS (next generation sequencing) | 6.08, 6.09 |
| NGT | 5.02, 6.02 |
| Nicotiana tabacum | 4.41 |
| NIR spectroscopy | 6.06 |
| Nitrate | 2.77 |
| Nitrogen | 6.52 |
| Nitrogen efficiency | 10.01 |
| Nitrogen use efficiency | 8.08 |
| Non-Photochemical Quenching (NPQ) | 8.16 |
| NUE | 2.77, 6.36 |
| NUS | 7.08 |
| nutritional profile | 6.19 |
| O | |
| oilseed crop | 2.18 |
| Olea europaea | 2.55 |
| Olive | 5.20, 8.03, 8.04 |
| olive | 5.05 |
| Olive tree | 4.19 |
| Oltrepò pavese | 8.04 |
| omics | 1.05, 2.16 |
| Omics | 2.41, 5.29 |
| Omics Analyses | 6.04 |
| omics data | 4.46 |
| Omics data integration | 4.35 |
| Online database | 6.21 |
| ONT | 2.21 |
| orphan crops | 7.08 |
| Oryza sativa | 4.22 |
| Oryza sativa ssp. indica | 6.36 |
| Oryza sativa ssp. japonica | 6.36 |
| osmotic stress | 2.64 |
| Osmotic stress | 2.15 |
| Oxford Nanopore sequencing | 5.12 |
| Oxford Nanopore Technology | 6.29 |
| oxidative stress | 3.16 |
| Oxidative stress | 1.11, 4.05 |
| oxylipins | 5.10 |
| P | |
| P. tracheiphilus | 5.26 |
| Pale-green | 2.40 |
| pan di zucchero | 2.16 |
| Pan-cistrome | 6.01 |
| Pan-Genome | 6.18 |
| Pangenome | 6.29 |
| pangenome pyramid | 7.03 |
| parthenocarpy | 6.23 |
| Parthenocarpy | 6.05 |
| Partial Redundancy Analysis | 6.07 |
| partnership | 7.06 |
| Pathogen resistance | 6.22 |
| pathogen resistance | 5.07 |
| Pathogenicity Test | 5.04 |
| PCD | 2.71 |
| PDO | 8.05 |
| Pea | 5.08 |
| Peach | 1.09 |
| Peanut | 6.51 |
| pear | 6.16 |
| Peas | 3.04 |
| pedigree based analysis | 6.16 |
| pepper | 3.09 |
| Pepper | 4.37 |
| Perennial wheats | 4.12 |
| Perennial wheats lines | 4.10 |
| PGI | 8.05 |
| PGP traits | 4.12 |
| PGPB | 2.47 |
| PGPM | 1.10 |
| PGPR | 4.28 |
| Phaseolus vulgaris L. | 6.19 |
| pheno-morphological traits | 6.03 |
| phenolamides | 5.03 |
| phenolic acids | 3.16 |
| phenology | 4.48 |
| Phenology | 4.39 |
| phenomics | 4.32, 6.39 |
| Phenotype | 6.38 |
| Phenotype Microarray | 4.16 |
| Phenotypic data | 4.23 |
| phenotypic parameters | 4.19 |
| phenotypic profiling | 6.25 |
| phenotypic selection | 6.14 |
| phenotypic traits | 7.02 |
| phenotyping | 4.42, 7.10 |
| Phenotyping | 2.10, 2.38, 4.01, 4.40 |
| PHENOTYPING | 2.58 |
| phosphorous | 4.03 |
| Phosphorus use efficiency | 8.08 |
| Photoprotection | 4.26 |
| photosynthesis | 4.33, 8.14 |
| Photosynthesis | 2.40, 4.26 |
| photosynthesys | 8.16 |
| Photosystem II(ΦPSII) | 6.38 |
| Phycoremediation | 4.30 |
| physico-chemical features | 6.27 |
| Physiological parameters | 8.08 |
| Phytic acid | 3.05 |
| Phytocannabinoids | 6.31 |
| Phytohormones | 2.01, 2.53 |
| Phytophthora | 5.01 |
| Pinot Noir | 4.44 |
| Pisum sativum | 6.14 |
| PIWI | 5.19 |
| Plant biology | 2.19 |
| Plant bioreactors | 3.14 |
| Plant biostimulants | 2.45 |
| plant breeding | 2.24, 4.46 |
| Plant Breeding | 5.14 |
| Plant breeding | 3.21 |
| plant cells | 4.16 |
| plant development | 2.75, 4.34 |
| plant evolution | 2.65 |
| Plant exudates | 4.10 |
| plant genetic resources | 6.45, 7.13 |
| plant growth promoting microorganisms | 8.06 |
| plant growth-promoting bacteria | 8.11 |
| plant nutrition | 4.03 |
| Plant physiology | 2.19 |
| Plant protection | 2.38 |
| Plant sensing | 2.38 |
| plant signaling | 2.63 |
| Plant-Microbe Interactions | 4.18 |
| plant-microbe interactions | 5.01 |
| Plant-rooting | 2.45 |
| Plasmid synthesis | 6.02 |
| Ploidy | 6.18 |
| Pochonia chlamydosporia | 5.18 |
| Podosphaera xanthii | 5.29 |
| Polycomb Repressive Complex 2 | 4.15 |
| Polyethylene terephthalate (PET) degradation | 4.30 |
| Polymorphism Information Content | 6.42 |
| polyphenols | 5.19 |
| Polyploidy | 4.13 |
| poplar | 2.11 |
| Poplar | 2.13 |
| population structure | 7.03 |
| post-harvest | 1.03 |
| Postharvest | 2.41, 6.37 |
| potato | 2.36 |
| Potato | 3.03 |
| potato (Solanum tuberosum) | 1.06 |
| potato peels extracts | 3.16 |
| PPOs | 2.47 |
| pre-breeding | 6.30 |
| prebreeding | 7.02 |
| predictive ability | 6.03 |
| Predictive models | 4.23 |
| preserving local varieties | 6.19 |
| Primary metabolites | 3.10 |
| Prime Editing | 6.41 |
| priming | 4.09 |
| Priming | 2.17, 2.30, 2.57 |
| Private alleles | 8.03 |
| proteomics | 1.06 |
| Protoplast | 5.33 |
| protoplast regeneration | 5.07 |
| Protoplasts | 1.08, 5.27 |
| protoplasts | 4.16, 6.12 |
| Protoplasts isolation | 5.28 |
| Prunus armeniaca | 6.46 |
| Prunus persica | 2.41 |
| PRX | 2.56 |
| Public-Private Partnership | 7.04 |
| pyrenocheta | 5.22 |
| Q | |
| QTL | 2.05 |
| QTL analysis | 4.49, 5.24 |
| QTL mapping | 3.01, 4.32, 4.48, 5.16, 5.30, 6.16 |
| quality | 3.09 |
| quantitative trait loci | 6.28 |
| quantitative traits | 7.01 |
| R | |
| R-genes | 5.23 |
| Reactive Oxygen Species | 2.17 |
| Recombinant hybrids | 5.16 |
| recombinant inbred lines (RIL) | 8.16 |
| Recombinant Inbred Lines (RIL) | 2.32 |
| Redox modifications | 4.05 |
| reduced fertilization | 4.14 |
| reference genome | 5.05 |
| Reference genomes | 2.61 |
| Regolith | 4.45 |
| regulatory network | 1.06 |
| reporter gene | 5.02 |
| reserve remobilisation | 6.30 |
| Resilience | 2.22, 6.07 |
| resilience | 4.24 |
| resistance | 5.02, 5.24 |
| Resistance | 5.08 |
| Resistant genes | 5.29 |
| restriction-free | 6.02 |
| reugularized linear regression | 1.04 |
| rhizosphere | 4.12 |
| Rhizosphere | 4.21, 6.52 |
| Rhizosphere environment | 4.10 |
| Rhizosphere Microbial Communities | 4.18 |
| ribonucleoproteins | 6.12 |
| rice | 2.02 |
| Rice | 2.01, 2.28, 3.02, 6.13, 8.11 |
| Rice domestication | 2.23 |
| Rice Seedling Establishment | 4.18 |
| RISOLO project | 2.23 |
| RKN | 5.18 |
| RNA seq | 8.14 |
| RNA Sequencing | 2.22, 4.27 |
| RNA sequencing | 5.25 |
| rna-seq | 1.03 |
| RNA-seq | 1.11, 2.08, 3.18 |
| RNA-Seq | 2.45, 2.77, 4.13 |
| RNA-Sequencing | 5.10 |
| RNAseq | 4.09, 4.28, 4.35, 5.26 |
| rocket | 2.26 |
| Root System Architecture | 2.05 |
| root angle | 2.49 |
| root architecture | 2.43, 2.49, 2.54, 4.31 |
| root development | 2.06, 2.39 |
| Root Growth Angle RGA | 6.04 |
| Root hair mutants | 4.40 |
| root meristem | 2.06 |
| root microbiota | 6.36 |
| root phenotypic plasticity | 4.29 |
| root phenotyping | 4.03 |
| root resistance | 5.01 |
| Root System Architecture | 4.02 |
| root traits | 4.03 |
| roots | 4.43 |
| rootstock effect | 8.19 |
| ROS | 2.15 |
| RT-qPCR | 2.35 |
| Rubus idaeus | 3.11 |
| rucola | 6.15 |
| S | |
| saccharification | 4.36 |
| Salicornia | 8.12 |
| Salinity | 2.37, 2.50 |
| salt stress | 4.07, 4.41, 7.12, 8.06 |
| Salt stress | 2.13, 2.30, 4.37 |
| Secondary metabolites | 3.10 |
| seed | 6.26, 7.15 |
| seed development | 7.07 |
| seed germination | 2.11, 4.42 |
| seed priming | 2.11, 2.14 |
| Seed priming | 2.15, 2.45 |
| Seed purity | 6.42 |
| seedlessness | 2.73 |
| selective sweeps | 7.06 |
| Senescence | 2.68 |
| Sequencing | 1.01 |
| sequencing | 6.51 |
| sequencing project | 6.09 |
| serotonin (SER) | 2.60 |
| Serotonin (SER) | 2.59 |
| Short-reads | 1.09 |
| Sicilian conservation varieties | 3.20 |
| signalling | 2.65 |
| Silerncing | 4.08 |
| silymarin | 3.13 |
| Single Nucleotide Polimorphysms (SNPs) | 7.05 |
| Single nucleus ATAC-seq | 1.12 |
| Single-cell RNA-seq | 1.12 |
| single-cell technology | 1.02 |
| site-directed mutagenesis | 6.20 |
| SLP9 | 2.36 |
| Small grain cereals | 7.04 |
| SNP | 6.10, 7.13 |
| SNP markers | 2.31 |
| SNPs | 3.01, 6.17, 6.25, 6.27 |
| Soil | 6.52 |
| Soil Health | 4.02 |
| soil moisture | 2.14 |
| Solanum commersonii | 2.68 |
| Solanum incanum | 6.11 |
| Solanum insanum | 6.11 |
| Solanum lycopersicum | 2.37, 2.59, 2.60, 4.25, 4.41 |
| Solanum lycopersicum L. | 2.07 |
| Solanum melongena | 6.05, 6.11 |
| Solanum tuberosum | 2.68, 5.03, 8.14 |
| solar panels | 2.07 |
| Somatic embryogenesis | 5.27, 5.33 |
| sowing-by-season combinations | 6.03 |
| Soybean | 2.15 |
| Spatial Transcriptomics | 1.01 |
| speed breeding | 2.66 |
| spermidine | 2.11 |
| SPET | 3.12, 7.10 |
| Spike Fertility | 6.49 |
| Spike shape | 6.49 |
| spray-induced gene silencing | 5.17 |
| SSR | 7.14, 8.10, 8.15 |
| SSR markers | 5.15, 5.20, 8.03, 8.04 |
| stem cell maintenance | 2.65 |
| Stem elongation | 2.01 |
| Stilbenes | 5.21 |
| stomata | 2.27, 4.33 |
| Stomatal density | 2.69, 4.17 |
| Stomatal index | 2.69 |
| strawberry | 5.02 |
| stress | 2.57, 2.72 |
| stress biomarker | 2.64 |
| stress memory | 4.25 |
| stress response mechanisms | 1.06 |
| stress transcriptional memory | 4.38 |
| Strigolactones | 2.34, 2.43, 5.08 |
| Structural variants | 1.09 |
| Submergence | 2.28, 4.18 |
| sugar metabolism | 3.08 |
| Superficial Scald | 6.37 |
| superficial scald | 1.03 |
| susceptibility genes | 5.01 |
| Susceptibility genes | 4.08, 5.28 |
| sustainability | 8.14 |
| sustainable agriculture | 5.06 |
| sustainable viticulture | 5.07 |
| sweet chestnut | 7.11 |
| Symbiotic microorganisms | 4.22 |
| SynCom | 4.28 |
| system biology | 3.19 |
| Systemic Acquired Resistance (SAR) | 5.06 |
| T | |
| T. turgidum ssp. durum | 2.04 |
| target RNA-sequencing | 2.55 |
| targeted-RNAseq | 2.47 |
| Taxonomy | 8.12 |
| TEA | 6.26, 6.35, 6.40 |
| Technological quality | 3.20 |
| teff | 4.11 |
| Teff breeding | 6.29 |
| Temperature-related plasticity | 5.04 |
| terpene synthases | 2.35 |
| Terpens | 6.31 |
| terpens | 6.31 |
| tetraploid wheat | 2.47, 4.29 |
| THC | 6.26 |
| THCA | 6.31 |
| Theobroma cacao L | 6.17 |
| Therapeutic products | 3.14 |
| TILLING | 2.42, 2.44, 2.58, 3.05 |
| TILLING by sequencing | 8.09 |
| TILLING population | 4.40 |
| TILLmore | 2.69 |
| Tissue | 1.01 |
| tobacco | 5.03 |
| tolerance | 2.66 |
| Tomato | 2.12, 2.50, 4.04, 4.06, 5.14, 6.22, 6.32, 8.13 |
| tomato | 2.32, 4.20, 5.22, 6.27, 7.10, 7.12, 7.15, 8.06, 8.16 |
| Tomato Brown Rugose Fruit Virus (ToBRFV) | 5.14 |
| tomato fruits | 2.07 |
| Tomato landraces | 4.05 |
| tomato wild species | 6.40 |
| Ton1b gene | 2.04 |
| Traceability | 7.05, 8.03 |
| traceability | 8.05 |
| Transcription factor footprinting | 6.01 |
| transcription factors | 2.26, 2.35 |
| Transcription factors | 5.03, 5.11 |
| transcription regulation | 2.29 |
| Transcriptional factors | 3.21 |
| transcriptome | 2.57, 3.11 |
| Transcriptomic | 2.09 |
| transcriptomics | 2.72 |
| Transcriptomics | 4.39, 5.18, 6.32 |
| translational biology | 2.71 |
| translational research | 2.33 |
| transposon | 3.11 |
| transposons | 5.23 |
| tri-trophic system | 5.18 |
| triterpenic acids | 1.02 |
| Triticum aestivum | 6.44 |
| Triticum germplasm | 6.21 |
| Triticum turgidum | 3.06, 4.47 |
| Triticum turgidum ssp. durum | 4.36 |
| tropane alkaloids | 2.51 |
| Tryptamine (TAM) | 2.59 |
| tryptamine (TAM) | 2.60 |
| tryptamine 5-hydroxylase | 2.60 |
| tryptophan decarboxylase | 2.60 |
| Tryptophan decarboxylase (TDC) | 2.59 |
| V | |
| VAMP-Associated Protein | 2.27 |
| Varietal characterization | 6.13 |
| Varietal identification | 6.42 |
| Venturia inaequalis | 5.15 |
| Vernalization | 2.20, 2.61 |
| Viability | 2.17 |
| VIGE | 6.43 |
| Viral Vector | 6.43 |
| Vitis vinifera | 5.19, 5.21, 5.27, 5.28 |
| VOCs | 2.58, 4.12, 4.31 |
| W | |
| Walnut | 8.15 |
| Wastewater | 2.12 |
| water | 3.02 |
| Water deficit | 4.13 |
| water deficit | 2.08 |
| water deficit tolerance | 1.06 |
| water loss | 2.03 |
| water scarcity | 4.20 |
| water stress | 1.10 |
| Water stress | 8.08 |
| Water Use Efficiency | 2.69 |
| weed control | 5.09 |
| WGCNA | 5.26 |
| WGS | 6.47 |
| wheat | 2.24, 4.14, 6.39, 7.07, 7.12 |
| Wheat | 3.04, 3.07, 4.02, 6.52, 8.08 |
| Wheat breeding | 6.48 |
| Wheat diseases | 5.32 |
| whole genome sequencing | 6.24, 8.09 |
| wild wheat relatives | 2.54 |
| WinRHIZO | 4.29 |
| WRKY125 | 5.11 |
| WUE | 4.17 |
| X | |
| X-Ray CT | 4.02 |
| xenobiotic detoxification | 2.63 |
| Xylella | 5.05 |
| Xylella fastidiosa | 5.20, 5.25, 8.18 |
| Y | |
| yellow index | 3.06 |
| Yellow rust | 5.30 |
| yield | 6.33 |
| yield traits | 6.28 |
| Yield-related traits | 4.04 |
| Z | |
| Zaxinone | 4.06 |
| zea mays | 3.19 |
| Zea mays | 5.11 |
| Zea mays L. | 3.17 |
| Zymoseptoria tritici | 5.04 |
| β | |
| β-apo-11-carotenal | 4.06 |
| “ | |
| “Mugnoli” | 6.10 |
| 1 | |
| 16S rRNA | 4.21 |
| 9 | |
| 90k SNP array | 6.49 |
