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> Phenomena > Biologic Function > Germination

Germination

Germination is the process by which a plant emerges from a seed and begins to grow.
This complex biological process involves the activation of enzymes, the mobilization of stored nutrients, and the expansion of the embryo.
Germination is influenced by a variety of factors, including temperature, moisture, light, and the presence of dormancy-breaking chemicals.
Understanding the mechanisms of germination is crucial for optimizing seed viability, crop production, and ecological restoration efforts.
Researchers can utilize AI-driven tools like PubCompare.ai to identify the most effective protocols and methods for enhancing germination reproducibility and accuracy, ultimately driving their experminets forward with confidence.

Most cited protocols related to «Germination»

1
Sequencing and Assembly of Rice Genome
The IRGSP clone and PCR sequences of the O. sativa (japonica group, cultivar Nipponbare) genome deposited in the International Nucleotide Sequence Databases as of 25 February 2010 were used in construction of the MTP. In addition, sequence reads generated by the Syngenta rice genome sequencing project (Goff et al. 2002 (link)) were assembled and used to extend contigs.
For the next-generation DNA sequencing of an NIAS individual, total genomic DNA was prepared from nuclei isolated from Nipponbare rice young leaves (two weeks after germination) using the CTAB method (Murray and Thompson 1980 (link)). The DNA samples were fragmented by a nebulizer or Branson Sonifier 250 (Danbury, CT). Sequencing libraries were constructed following the protocols with Illumina Genomic DNA Sample Preparation Kit and Roche GS DNA Library Preparation Kit, respectively. Illumina genome sequencing was performed by Illumina Genome Analyzer II/IIx with the Illumina version 2 sequencing kit. GS-FLX genome sequencing was performed using the Roche GS LR70 Sequencing Kit. The sequence reads are available at the DDBJ Sequence Read Archive (DRA000651).
For the CSHL individual, ~5 μg of Nipponbare rice genomic DNA was used as input for standard Illumina libraries. The DNA was sheared by adaptive focused acoustics using the Covaris (Woburn, MA) instrument and end-repaired using T4 DNA polymerase, Klenow fragment, and T4 polynucleotide kinase. Fragments were then treated with Klenow fragment (3’ - 5’ exonuclease) to add a single 3’ deoxyA overhang and ligated to standard paired-end Illumina adapters. Qiagen (Valencia, CA) columns were used for purification between steps. The fragments were size-selected at ~225 bp (including adapters) using agarose gel electrophoresis. The actual insert size excluding adapters was ~150 bp. The library was then PCR amplified using Phusion DNA polymerase in HF buffer for 14 cycles and quantified using the Agilent BioAnalyzer (Santa Clara, CA). All libraries were normalized to 10 nM before loading on the Illumina sequencers. Production sequencing was performed using Illumina GAIIx instruments with paired-end modules using the Illumina version 3 sequencing kits. The library was sequenced with 76 bp paired-end read lengths. Sequence data was processed using the Illumina GAPipeline v1.1 and v1.3.2 (Firecrest/Bustard v1.9.6 and Firecrest/Bustard v1.3.2). The sequence reads are available at the Sequence Read Archive of NCBI (SRX032913).
Syngenta rice genome sequences (Goff et al. 2002 (link)) were filtered by using IRGSP rice genomic sequences with similarity searches. The filtered sequences were then assembled; 50 large Syngenta contigs (between 4 kb and 40 kb), a total of 748 kb were used for potential gap filling.
Kawahara Y., de la Bastide M., Hamilton J.P., Kanamori H., McCombie W.R., Ouyang S., Schwartz D.C., Tanaka T., Wu J., Zhou S., Childs K.L., Davidson R.M., Lin H., Quesada-Ocampo L., Vaillancourt B., Sakai H., Lee S.S., Kim J., Numa H., Itoh T., Buell C.R, & Matsumoto T. (2013). Improvement of the Oryza sativa Nipponbare reference genome using next generation sequence and optical map data. Rice, 6, 4.
Publication 2013
3'-5'-Exonucleases A-748 Acclimatization Acoustics Buffers Cell Nucleus Cetrimonium Bromide Clone Cells DNA-Directed DNA Polymerase DNA Library DNA Polymerase I Electrophoresis, Agar Gel Genome Germination Nebulizers Oryza sativa Polynucleotide 5'-Hydroxyl-Kinase
2
Rice Protoplast Isolation and Transformation
Our protoplast isolation protocol was based on the protocol for maize protoplasts provided online by J. Sheen's laboratory with several changes. Rice seeds were grown as stated above. Between 7 and 14 days post germination, plants were ~4–8 inches tall. Leaf and stem tissue was cut into 0.5 mm pieces using very sharp razors. Tissue was immediately incubated in enzyme solution (0.6 M mannitol, 10 mM MES (pH 5.7), 1.5% Cellulase RS, 0.75% Macerozyme, 0.1% BSA, 1 mM CaC12, 5 mM β-mercaptoethanol and 50 μg/ml carbenicillin) for 4 h in the dark under gentle shaking (40 rpm). After incubation, protoplasts were passed through a 35 μm nylon mesh filter. One volume of W5 solution (154 mM NaCl, 125 mM CaC12, 5 mM KC1, 2 mM MES (pH 5.7)) was added and the solution was centrifuged for 5 minutes at 1500 rpm to pellet the protoplasts. Cells were re-suspended in Mmg solution [13 (link)] (0.6 M mannitol, 15 mM MgC12, 4 mM MES (pH 5.7)) for PEG-mediated transformation at 106 cells/ml. Cells were quantified using a hemocytometer. For transformation, 40% PEG (0.6 M mannitol, 100 mM CaC12, 40% v/v PEG 3350) was added to the protoplasts for 15 minutes. Cells were washed 1× with 10 volumes of W5 and then re-suspended in incubation solution (0.6 M mannitol, 4 mM MES (pH 5.7), 4 mM KC1). Cells were incubated at 28°C in the dark overnight.
Bart R., Chern M., Park C.J., Bartley L, & Ronald P.C. (2006). A novel system for gene silencing using siRNAs in rice leaf and stem-derived protoplasts. Plant Methods, 2, 13.
Publication 2006
2-Mercaptoethanol Carbenicillin Cells Cellulase Enzymes Germination isolation Maize Mannitol Nylons Oryza sativa Plant Embryos Plant Leaves Plants polyethylene glycol 3350 Precursor T-Cell Lymphoblastic Leukemia-Lymphoma Protoplasts Sodium Chloride Stem, Plant Tissues
3
Botrytis cinerea Infection of Tomato Leaves
Tomatoes (S. lycopersicum) cv. Jinpeng 1 were used as host plants; they were grown in a greenhouse at a 16-h day/8-h night cycle, at 22–28°C. At the age of 6 weeks, plants were inoculated using a solution containing B. cinerea conidia (2 × 106 spores ml−1), 5 mM glucose, and 2.5 mM KH2PO4. The inoculation solution was applied to both leaf surfaces using a soft brush. After inoculation, the plants were kept at 100% relative humidity to ensure spore germination. The B. cinerea- and mock-inoculated leaves were harvested at 5 time points (0 days, 0.5 days, 1 days, 3 days, and 7 days) after treatment, in 3 biological replicates. We found that the B. cinerea spores appeared on the leaves at 7 dpi. The 7-dpi leaves of B. cinerea-infected (TD7d) and control (TC7d) plants were sent to BGI (Shenzheng, China) for the deep sequencing of sRNAs. The samples were frozen in liquid nitrogen and stored at −70°C for the studies of transcript expression.
Total RNAs were extracted from leaf tissues using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), followed by RNase-free DNase treatment (Takara, Dalian, China). Their concentrations were quantified using a NanoDrop ND-1000 spectrophotometer.
Jin W, & Wu F. (2015). Characterization of miRNAs associated with Botrytis cinerea infection of tomato leaves. BMC Plant Biology, 15, 1.
Publication 2015
Biopharmaceuticals Conidia Deoxyribonucleases Endoribonucleases Freezing Germination Glucose Humidity Lycopersicon esculentum Nitrogen Plant Leaves Plants RNA Spores Tissues trizol Vaccination
4
Optimizing Arabidopsis Growth Conditions
After stratification of the seeds at 2°C for 5 days or vernalization at 2°C for 6 weeks on wet filter paper and in darkness, plants of Arabidopsis (Columbia) were grown in 8-h SDs or 16-h LDs. The photon flux density was 120 (HL) or 50 μmol.m-2.s-1 (LL) PAR (Very High Output fluorescent tubes; Sylvania, Zaventem, Belgium) and the temperature was 20°C. Relative humidity – which is critical for the success of germination and seedling establishment – was set optimally at 70%.
Tocquin P., Corbesier L., Havelange A., Pieltain A., Kurtem E., Bernier G, & Périlleux C. (2003). A novel high efficiency, low maintenance, hydroponic system for synchronous growth and flowering of Arabidopsis thaliana. BMC Plant Biology, 3, 2.
Publication 2003
Arabidopsis Darkness Germination Humidity Plant Embryos Plants Strains
5
Isolation of Anaerobic Gut Bacteria
Fresh faecal samples were obtained from six consenting healthy adult human donors (1 faecal sample per donor: minimum 0.5 g) and were placed in anaerobic conditions within 1 h of passing to preserve the viability of anaerobic bacteria. All sample processing and culturing took place under anaerobic conditions in a Whitley DG250 workstation at 37 °C. Culture media, PBS and all other materials that were used for culturing were placed in the anaerobic cabinet 24 h before use to reduce to anaerobic conditions. The faecal samples were divided in two. One part was homogenized in reduced PBS (0.1 g stool per ml PBS) and was serially diluted and plated directly onto YCFA7 (link) agar supplemented with 0.002 g ml−1 each of glucose, maltose and cellobiose in large (13.5 cm diameter) Petri dishes. This sample was also subjected to metagenomic sequencing to profile the entire community. The other part was treated with an equal volume of 70% (v/v) ethanol for 4 h at room temperature under ambient aerobic conditions to kill vegetative cells. Then, the solid material was washed three times with PBS and it was eventually resuspended in PBS. Plating was performed as described earlier.
For the ethanol-treated samples, the medium was supplemented with 0.1% sodium taurocholate to stimulate spore germination. Colonies were picked 72 h after plating from Petri dishes of both ethanol-treated and non-ethanol-treated conditions harbouring non-confluent growth, (that is, plates on which the colonies were distinct and not touching). The colonies that were picked were re-streaked to confirm purity. No statistical methods were used to predetermine sample size. The experiments were not randomized. The investigators were not blinded to allocation during experiments and outcome assessment.
Browne H.P., Forster S.C., Anonye B.O., Kumar N., Neville B.A., Stares M.D., Goulding D, & Lawley T.D. (2016). Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation. Nature, 533(7604), 543-546.
Publication 2016
Adult Agar Bacteria, Aerobic Bacterial Viability Cellobiose Cells Donors Ethanol Feces Germination Glucose Hyperostosis, Diffuse Idiopathic Skeletal Maltose Metagenome Spores Taurocholic Acid, Monosodium Salt Tissue Donors

Most recents protocols related to «Germination»

1
Overexpression of Ceres cDNA 12723147 Confers Drought Tolerance
Not available on PMC !

Example 6

Ceres cDNA 12723147 encodes an Arabidopsis putative aldo/keto reductase. Ectopic expression of Ceres cDNA 12723147 under the control of the CaMV35S promoter induces the following phenotypes:

    • Germination on high concentrations of polyethylene glycol (PEG), mannitol and abscissic acid (ABA).
    • Continued growth on high concentration of PEG, mannitol and ABA.
      Generation and Phenotypic Evaluation of T1 Lines Containing 35S::cDNA 12723147.

Wild-type Arabidopsis Wassilewskija (WS) plants were transformed with a Ti plasmid containing cDNA 12723147 in the sense orientation relative to the CaMV35S constitutive promoter. The Ti plasmid vector used for this construct, CRS338, contains PAT and confers herbicide resistance to transformed plants. Ten independently transformed events were selected and evaluated for their qualitative phenotype in the T1 generation. No positive or negative phenotypes were observed in the T1 plants.

Screens of Superpools on High PEG, Mannitol, and ABA as Surrogate Screens for Drought Tolerance.

Seeds from 13 superpools (1,200 T2 seeds from each superpool) from the CaMV35S or 32449 over-expression lines were tested on 3 drought surrogate screens (high concentrations of PEG, mannitol, and ABA) as described above. T3 seeds were collected from the resistant plants and analyzed for resistance on all three surrogate drought screens.

Once cDNA 12723147 was identified in resistant plants from each of the three surrogate drought screens, the five individual T2 events containing this cDNA (SR01013) were screened on high PEG, mannitol, and ABA to identify events with the resistance phenotype.

Superpools (SP) are referred to as SP1, SP2 and so on. The letter following the hyphen refers to the screen (P=PEG, M=mannitol, and A=ABA) and the number following the letter refers to a number assigned to each plant obtained from that screen on that superpool. For example, SP1-M18 is the 18th plant isolated from a mannitol screen of Superpool 1.

Qualitative and Quantitative Analysis of 2 Independent Events Representing 35S::cDNA 12659859 (SR01010) on PEG, Mannitol and ABA

To identify two independent events of 35S::cDNA 12659859 showing PEG, mannitol, and ABA resistance, 36 seedlings from each of two events, SR01013-01 and -02 were screened as previously described. BastaR segregation was assessed to verify that the lines contained a single insert segregating in a 3:1 (R:S) ratio as calculated by a chi-square test (Table 6-1). Both lines (01 and 02) segregated for a single insert in the T2 generation (Table 1)

TABLE 6-1
BastaR segregation for SR01013 individual events
Probability
EventResistantSensitiveTotalof Chi-test*
SR01013-01305350.14323
SR01013-02306360.24821
SR01013-01-3341360.00248**
SR01013-02-2320320.00109**
*Chi-test to determine whether actual ratio of resistant to sensitive differs form the expected 3:1 ratio.
**Significantly different than a 3:1 (R:S) ratio

Lines SR01013-01 and -02 were chosen as the two events because they had a strong and consistent resistance to PEG, mannitol and ABA. The controls were sown the same day and in the same plate as the individual lines. The PEG (Tables 6-2 and 6-3), mannitol (Tables 6-4 and 6-5) and ABA (Tables 6-6 and 6-7) segregation ratios observed for SR01013-01 and -02 are consistent with the presence of single insert as demonstrated by chi-square, similar to what we observed for BastaR resistance (Table 6-1).

The progeny from one resistant T2 plant from each of these two events were tested in the same manner as the T2. Resistance to PEG, mannitol and ABA was also observed in the T3 generation. Taken together, the segregation of resistant seedlings containing cDNA 12723147 from two events on all three drought surrogate screens and the inheritance of this resistance in a subsequent generation, provide strong evidence that cDNA 12723147 when over-expressed can provide tolerance to drought.

TABLE 6-2
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-01T2 containing 35S::cDNA 12723147 on PEG.
Probability
EventObservedExpectedχ2of Chi-Test
PEG Resistant22270.9260.054
PEG Sensitive1492.778
36363.704

TABLE 6-3
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on PEG.
Probability
EventObservedExpectedχ2of Chi-Test
PEG Resistant26270.037.700
PEG Sensitive109.111
3636.148

TABLE 6-4
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-01 T2 containing 35S::cDNA 12723147 on mannitol.
Probability
EventObservedExpectedχ2of Chi-Test
Mannitol Resistant2827.037.700
Mannitol Sensitive89.111
3636.148

TABLE 6-5
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on mannitol.
Probability
EventObservedExpectedχ2of Chi-Test
Mannitol Resistant18273.0005
Mannitol Sensitive1899
363612

TABLE 6-6
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on ABA.
EventObservedExpectedχ2Probability
ABA Resistant1324 5.0427.098
ABA Sensitive19 815.125
323220.167

TABLE 6-7
Chi-square analysis assuming a 3:1 (R:S) ratio for progeny of
SR01013-02 T2 containing 35S::cDNA 12723147 on ABA.
EventObservedExpectedχ2Probability
ABA Resistant1324 5.0427.098
ABA Sensitive19 815.125
323220.167
FIG. 5 provides the results of the consensus sequence (SEQ ID NOs: 178-200) analysis based on Ceres cDNA 12723147.

US11859195B2. Nucleotide sequences and polypeptides encoded thereby useful for modifying plant characteristics (2024-01-02). CERES, INC. [US]. Inventors: Cory Christensen [US], Nestor Apuya [US], Kenneth A. Feldmann [US].
Patent 2024
14-3-3 Proteins Abscisic Acid Aldo-Keto Reductase Arabidopsis CERE Cloning Vectors Consensus Sequence DNA, Complementary Droughts Drought Tolerance Ectopic Gene Expression Germination Herbicide Resistance Mannitol Pattern, Inheritance Phenotype Plant Embryos Plants Plant Tumor-Inducing Plasmids Polyethylene Glycols Seedlings
2
Seed Germination Inhibition Assay
The assay was performed according to the Italian Environmental
Agency guidelines.29 Briefly, seeds of L. sativum and S. lycopersicum not treated with fungicides were preliminary checked for vitality
in distilled water in the dark at 25 ± 1 °C (germination
rates >90%). Crude extracts were tested at six doses (100, 30,
15,
7.5, 3.75, and 1.8% v/v), and distilled water was used as negative
control. Three replicates per treatment were arranged by wetting a
Whatman no. 1 filter paper with 2 mL of each solution. Ten seeds for
each replicate were distributed on the filter and incubated at 25
± 1 °C in the dark for 72 h (L. sativum) or 144 h (S. lycopersicum). At the
end of the incubation time, complete sprouts (≥1 mm) and root
lengths were evaluated to calculate the germination index (GI) using
the eq. , where St and Sc are the mean number of germinated seeds in
treatments and control samples, respectively, and Lt and Lc are the mean root
length of treatments and control samples, respectively. Results were
expressed as GI ± standard deviation (SD). The statistical correlation
between groups was analyzed by Student’s t-test.
Bulgari D., Alias C., Peron G., Ribaudo G., Gianoncelli A., Savino S., Boureghda H., Bouznad Z., Monti E, & Gobbi E. (2023). Solid-State Fermentation of Trichoderma spp.: A New Way to Valorize the Agricultural Digestate and Produce Value-Added Bioproducts. Journal of Agricultural and Food Chemistry, 71(9), 3994-4004.
Publication 2023
Biological Assay Complex Extracts DNA Replication Germination Industrial Fungicides Plant Embryos Strains Student
3
Spectral Effects on Lettuce and Tomato Growth
Red oak leaf lettuce (Lactuca sativa) was grown with adjustments made to the height of the growth boxes so that each treatment received similar light intensity in addition to the consistent height, variable intensity setup previously described (Ravishankar et al., 2021 (link)). Eight lettuce plants from each treatment were harvested at 21 days post germination (transplant stage) and the remaining eight plants from each treatment at 35 days post germination (harvest stage). Four plants from each harvest per box were used for biomass measurements, while the remaining four were used for tissue sampling. Tomato plants (Solanum lycopersicum cv. Moneymaker) were grown under these conditions with modifications. Seeds were sown on rockwool and germinated in the same growth chamber with metal halide and incandescent lighting to approximate natural sunlight. Eight seedlings of uniform size and age were selected and transplanted into individual blocks of larger rockwool and moved inside the treatment boxes with nearly 100% OSC roof coverage. Tomato plants were harvested after flowering, 30 days past the two-leaf stage when plants were moved under the filters.
The growth boxes were covered with either an OSC filter, a clear glass or a shaded control on top to simulate a greenhouse roof. The positions of the rockwool blocks were rotated to avoid positional light effects as in the lettuce experiment. The consistent light intensity between treatments allowed for comparison of the influence of the light spectra on plant physiology. The results of these experiments were compared to the previously reported experimental design where all filters were positioned at a consistent height to model the roof of a greenhouse and therefore produce different TPFD due to the differences in filter transmission. Five replications of the lettuce experiment with consistent light intensity were conducted. One replication was conducted of both tomato experiments, using consistent and variable light intensity. Lettuce light conditions were measured as previously reported. Reported percent colors for tomato were measured using a spectrophotometer (Black Comet-SR, Stellar Net, Inc., USA) except the high light control treatment, which was assumed to have the percent colors of the low light control. PPFD was measured using a quantum sensor (LI-190R, LI-COR, Inc., USA) and TPFD was calculated from PPFD and percent colors.
Charles M., Edwards B., Ravishankar E., Calero J., Henry R., Rech J., Saravitz C., You W., Ade H., O’Connor B, & Sederoff H. (2023). Emergent molecular traits of lettuce and tomato grown under wavelength-selective solar cells. Frontiers in Plant Science, 14, 1087707.
Publication 2023
Comet Assay DNA Replication Germination Incandescence Lactuca sativa Light Lycopersicon esculentum Metals Plant Embryos Plant Leaves Plant Physiological Phenomena Plants Seedlings Sunlight Tissues Transmission, Communicable Disease
4
Evaluating Plant Growth Metrics in Lettuce and Tomato
Measurements of fresh weight, dry weight, leaf area and leaf number were collected as previously described at Day 21 and Day 35 after germination for lettuce and at Day 30 for tomato (Ravishankar et al., 2021 (link)). The 21-day early harvest corresponds to the age when young lettuce is typically transplanted. Both fresh and dry weights are above ground measurements that do not include root tissue. Dry weight was measured after leaves were dried at 65°C for three days. Leaf area was measured by leaf meter (LI-3000, LI-COR, Inc., USA) and summed per plant. Leaf number was also summed by plant and excluded any emerging leaves less than 1 cm in length. Additional measurements were taken of the tomato plants. Height was measured from the top of the rockwool block to the highest point of the plant. Visible flower buds and open flower buds were recorded per plant after initiation of flowering and at harvest. The number of leaflets was counted per plant. Height and leaf number were collected for all eight plants in each treatment. All other biomass measurements were collected for the four tomato plants per treatment not used for tissue sampling.
Charles M., Edwards B., Ravishankar E., Calero J., Henry R., Rech J., Saravitz C., You W., Ade H., O’Connor B, & Sederoff H. (2023). Emergent molecular traits of lettuce and tomato grown under wavelength-selective solar cells. Frontiers in Plant Science, 14, 1087707.
Publication 2023
Germination Lactuca sativa Lycopersicon esculentum Plant Leaves Plant Roots Plants Tissues
5
Bacterial Inoculation and Rice Seedling Evaluation
The bacterial strain used in this study, except those referenced in Fig. 6, Supplementary Figs. S1 and S11, was B. glumae MAFF301682 (MAFF designates strains from the culture collection of the National Agriculture and Food Research Organization (NARO) Genebank, formerly the culture collection of the Ministry of Agriculture, Forestry and Fisheries, Japan). Bacterial inocula were incubated on Luria–Bertani (LB) media with 2% agar at 28 °C for 4 days and then suspended in sterilized, deionized water at a concentration of 108 CFU/ml. The rice seeds were sterilized by soaking in a chlorine bleach solution (available chlorine 2.5%) for 30 min, rinsed carefully with sterilized water, and then soaked in sterilized water for 3 days in a plant growth chamber at 28 °C. The sterilized seeds were subsequently placed in a freshly prepared bacterial suspension and held under vacuum (0.2 MPa) for 3 min. The inoculated seeds were dried for 2 h, sown in sterilized soil (Bonsol No. 2, Sumitomo Kagaku Kougyo, Osaka, Japan) and incubated in a growth chamber at 28 °C with 80% humidity under a 14-h photoperiod. The disease symptoms were measured 8 days after sowing on a scale of 1–3, where 1 = no symptoms, 2 = sheaths with reddish-brown lesions (mild infection), and 3 = necrotic seedlings or seeds that did not germinate (severe infection). The BSR severity was calculated from these scores as follows: BSRseverity%=N3-N1-N2/2×100/N3, where N1 = number of seedlings with a score of 1, N2 = number of seedlings with a score of 2, and N3 = number of seeds per replication. There were three or four replications per inoculation. As a control, we germinated uninoculated seeds and confirmed that the average germination rate was > 90%. The bacterial strain for evaluation of resistance to bacterial seedling blight was B. plantarii MAFF301723. The method for inoculating seeds was the same as that used for B. glumae. Five inoculated seeds and 95 uninoculated seeds were sown in sterilized soil in the same cell tray, and the disease severity of B. plantarii (Fig. 6) was calculated as described above. The bacterial strain shown in Supplementary Fig. S11 was B. glumae MAFF302744, and the panicle disease severity assay was conducted according to a previously described metohd53 (link).
Mizobuchi R., Sugimoto K., Tsushima S., Fukuoka S., Tsuiki C., Endo M., Mikami M., Saika H, & Sato H. (2023). A MAPKKK gene from rice, RBG1res, confers resistance to Burkholderia glumae through negative regulation of ABA. Scientific Reports, 13, 3947.
Publication 2023
Agar ARID1A protein, human Bacteria Biological Assay Cells Chlorine DNA Replication Food Germination Humidity Infection Necrosis Oryza sativa Plant Development Plant Embryos Strains Vaccination Vacuum

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1
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More about "Germination"

Germination is a crucial process in the life cycle of plants, where seeds undergo a complex series of biological and physiological changes to sprout and begin growing.
This key event, also known as seed emergence or seedling development, involves the activation of enzymes, the mobilization of stored nutrients, and the expansion of the embryo.
The germination process is influenced by a variety of environmental factors, including temperature, moisture, light, and the presence of dormancy-breaking chemicals.
Understanding the mechanisms of germination is essential for optimizing seed viability, crop production, and ecological restoration efforts.
Researchers can utilize advanced tools like PubCompare.ai to identify the most effective protocols and methods for enhancing germination reproducibility and accuracy.
This AI-driven platform allows users to locate the best germination-related protocols from literature, pre-prints, and patents, enabling them to make informed decisions and drive their experiments forward with confidence.
When conducting germination studies, researchers may employ various laboratory techniques and materials, such as Whatman No. 1 filter paper, Whatman filter paper, TRIzol reagent, RNeasy Plant Mini Kit, Phytagel, DNeasy Plant Mini Kit, and statistical analysis software like SAS 9.4.
Microscopy techniques, including the BX51 microscope and Eclipse 80i, may also be utilized to observe and analyze the germination process.
By leveraging the insights and capabilities provided by PubCompare.ai, researchers can optimize their germination experiments, enhance reproducibility, and ultimately drive their research forward with greater confidence and success.