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Maize

Maize, also known as corn, is a cereal grain that is widely cultivated globally.
It is a staple food crop and a versatile ingredient used in a variety of food and industrial products.
Maize is an important source of carbohydrates, protein, vitamins, and minerals, making it a nutritionally valuable crop.
The plant is characterized by its large ears, which contain rows of kernels that can be consumed fresh, dried, or processed.
Maize has a rich history of cultivation and is a significant contributor to food security and the global economy.
Reserchers continute to study maize to optimize its yield, nutritional profile, and resiliance to environmental stressors.

Most cited protocols related to «Maize»

1
Maize and Barley Genotyping Protocol
Analyses of the 86 bp sequencing reads were based upon the unfiltered qseq files, since the filtering process that produces fastq files sometimes discarded good reads that aligned perfectly to the reference genome for at least 64 bases. Starting with the qseq files from a flow cell, we first filtered for reads that (1) perfectly matched one of the barcodes and the expected four-base remnant of the ApeKI cut site (CWGC), (2) were not adapter/adapter dimers, and (3) contained no “Ns” in their first 72 bases. These reads were sorted into separate files according to their barcode, with the barcode removed and the remainder of the sequence trimmed to 64 bases (including the initial CWGC). If either the full ApeKI site (from partial digestion or chimera formation) or the first 8 bases of common adapter (from ApeKI fragments less than 64 bases) were detected within 64 bases, the read was truncated appropriately and then filled to 64 bases with polyA.
For maize, subsequent filtering of the reads was then done in two different ways, depending on our purpose. To generate a reference set of 64 base sequence tags to be included in a presence/absence genotype table, only reads with a minimum Q-score of 10 across the first 72 bases) and that occurred at least twice were kept. We opted to use this somewhat low-stringency minimum Q-score cutoff to maximize the number of useful sequence tags. Sequence tags containing random sequencing errors should not occur multiple times in multiple samples and should not map genetically, so they should be filtered out in subsequent steps. To this set of reference tags, the expected 64 base tags from an in silico ApeKI digest of the maize reference genome, B73 RefGen v1 [21] (link), were added (with fragments shorter than 64 bases filled with polyA, as above). To fill in the observed counts in the genotype table, a second pass across the reads for each DNA sample was performed. In this second pass, 64 base reads were counted for each sample (and the count added to the genotype table) if they perfectly matched one of the reference tags, regardless of their minimum Q score. The resulting genotype table was then filtered to remove tags that occurred in 10 or fewer DNA samples; this should remove most of the sequencing errors. For barley, the absence of a reference genome prevented anchoring reads to a physical map. Sequence reads were simply filtered for unique 64 base sequence reads that were present in five or more lines and these were mapped genetically as described below.
All maize and barley sequences were submitted to the National Center for Biotechnology Information (NCBI) Short Read Archive (study SRP004282.1).
Elshire R.J., Glaubitz J.C., Sun Q., Poland J.A., Kawamoto K., Buckler E.S, & Mitchell S.E. (2011). A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species. PLoS ONE, 6(5), e19379.
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Publication 2011
Base Sequence Cells Chimera Digestion Genome Genotype Hordeum vulgare Maize Physical Examination Poly A
2
Genetic Mapping of DNA Sequence Tags
Presence/absence scores for each tag were used in a binomial test of segregation versus an independent framework map. For maize, this framework map consisted of 644 SNPs genetically mapped in the maize nested association mapping (NAM) population [29] (link) and then genotyped in the IBM population. The binomial segregation test filtered for sequence tags that co-segregated with only one of the two parental alleles at a given SNP. For each SNP marker, the two possible parental sources of a tag were each tested in turn. A “success” was recorded when a tag co-occurred in a RIL with the SNP allele from its presumed parental source, otherwise a “failure” was recorded. The binomial sample size was the number of RILs in which the tag was present and the SNP was not missing or heterozygous. For maize, tests were only performed if the sample size was at least 10. The probability of success was defined as the proportion of the RILs that contained the SNP allele being tested. For maize, a threshold p-value of 0.001 was considered significant for directed tests versus the physically closest SNP, or 0.0001 for elsewhere in the genome.
For barley, mapping was conducted using flanking SNPs and a threshold of p<0.0001 for the binomial test. In practice, a sequence tag was mapped in barley only if it always co-occurred with one SNP allele and never the other.
In maize only, biallelic GBS markers were identified as follows. Pairs of tags that aligned to exactly the same unique position and strand in the maize reference genome (B73 RefGen v1) and that also co-segregated with the physically closest SNP (p<0.001) were merged into a single, biallelic marker. These markers were then re-tested for co-segregation with the physically closest SNP using Fisher's Exact Test (p<0.001). Biallelic GBS markers that passed the latter test were then incorporated into a high density, framework map and ordered according to their positions in the reference genome. To determine how many of the remaining presence/absence GBS tags could be genetically mapped in maize, the binomial test of segregation was repeated versus this high density framework map, with a threshold of p<0.0001.
Software for the sequence filtering and the mapping analysis was written in Java and is available on SourceForge (http://sourceforge.net/projects/tassel/). This software is part of the TASSEL package but is not currently implemented in the TASSEL GUI.
Elshire R.J., Glaubitz J.C., Sun Q., Poland J.A., Kawamoto K., Buckler E.S, & Mitchell S.E. (2011). A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species. PLoS ONE, 6(5), e19379.
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Publication 2011
Alleles Genome Heterozygote Hordeum Maize Parent Strains Tassel
3
CRISPR/Cas9 Transformation of Maize
The CRISPR/Cas9 binary vector pBUE-2gRNA-ZH was transformed into Agrobacterium strain EHA105, and Agrobacterium-mediated method was used to transform immature embryos of B73 maize at China Agricultural University Transgenic Facility Center. The genomic DNA was extracted from 20 transgenic seedlings and the PCR fragment, primers and reactions were the same as those described above. For restriction enzyme digestion analysis, about 500 ng purified PCR products from each reaction was digested overnight with XcmI or SphI in a 20-μL reaction volume. For sequencing analysis, the PCR products from two representative transgenic seedlings were cloned into the cloning vector pCBC and positive clones were sequenced using the T7 primer.
Xing H.L., Dong L., Wang Z.P., Zhang H.Y., Han C.Y., Liu B., Wang X.C, & Chen Q.J. (2014). A CRISPR/Cas9 toolkit for multiplex genome editing in plants. BMC Plant Biology, 14, 327.
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Publication 2014
Agrobacterium Animals, Transgenic Clone Cells Cloning Vectors Clustered Regularly Interspaced Short Palindromic Repeats Digestion Embryo Genome Maize Oligonucleotide Primers Restriction Mapping S-pentachlorobuta-1,3-dien-yl-cysteine Seedlings Sequence Analysis Strains
4
Quantifying Gene Completeness Using Asmgene
BUSCO24 (link) is a popular tool for evaluating gene completeness. It is very helpful for new species, but is underpowered for species with high-quality reference genomes. For example, BUSCO reports that the completeness of GRCh38 is only 94.8%, lower than the 95.2% percent completeness of the male HG002 hifiasm assembly (Supplementary Table 5).
In order to quantify gene completeness more accurately, we used the paftools script from the minimap2 package22 (link) to calculate the asmgene scores. Unlike BUSCO, asmgene relies on a reference genome. It uses minimap2 to align EnsEMBL cDNAs (v99 for human and mouse and v47 for maize) to a reference genome or an assembly. For each transcript, asmgene records a hit if the transcript is mapped at ≥99% identity (≥97% for non-human species due to their higher diversity) over ≥99% of the transcript length. A transcript is considered to be single-copy (SC) if it has only one hit; otherwise it is considered to be multi-copy (MC). The asmgene script chooses the longest transcript to represent a gene. In Table 1 and 2, percent “Complete” equals |{SCorMCinASM}∩{SCinREF}|/|{SCinREF}|, where {SCinREF} denotes the set of genes single-copy in the reference genome and {SCorMCinASM} denotes the union sets of single- and multi-copy genes in the assembly. Similarly, percent “Duplicated” equals |{MCinASM}∩{SCinREF}|/|{SCinREF}|. In Table 2, percent “Multi-copy gene retained” is calculated by |{MCinASM}∩{MCinREF}|/|{MCinREF}|.
Cheng H., Concepcion G.T., Feng X., Zhang H, & Li H. (2021). Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nature methods, 18(2), 170-175.
Publication 2021
DNA, Complementary Genes Genes, vif Genome Homo sapiens Maize Males Mice, House Multiple Birth Offspring
5
Structural Variant Detection in Maize Genomes
Leaves were used to prepare high molecular mass DNA and optical genome maps were constructed as described above for B73. Structural variant calls were generated based on alignment to the reference map B73 v4 chromosomal assembly using the multiple local alignment algorithm (RefSplit)32 (link). A structural variant was identified as an alignment outlier32 (link),49 (link), defined as two well-aligned regions separated by a poorly aligned region with a large size difference between the reference genome and the map or by one or more unaligned sites, or alternatively as a gap between two local alignments. A confidence score was generated by comparing the non-normalized P values of the two well-aligned regions and the non-normalized log-likelihood ratio50 (link) of the unaligned or poorly aligned region. With a confidence score threshold of 3, RefSplit is sensitive to insertions and deletions as small as 100 bp (events smaller than 1 kb are generally compound or substitution and include label changes, not just spacing differences) and other changes such as inversions and complex events which could be balanced. Insertion and deletion calls were based on an alignment outlier P-value threshold of 1 × 10−4. Insertions or deletions that crossed gaps in the B73 pseudomolecules, or that were heterozygous in the optical genome maps, were excluded. Considering the resolution of the BioNano optical map, only insertion and deletions larger than 100 bp were used for subsequent analyses. To obtain high-confidence deletion sequences, sequencing reads from the maize HapMap2 project8 (link) for Ki11 and W22 were aligned to our new B73 v4 reference genome using Bowtie2 (ref. 51 (link)). Read depth (minimum mapping quality >20) was calculated in 10-kb windows with step size of 1 kb. Windows with read depth below 10 in Ki11 and 20 in W22 (sequencing depths for Ki11 and W22 were 2.32× and 4.04×, respectively) in the deleted region were retained for further analysis.
Jiao Y., Peluso P., Shi J., Liang T., Stitzer M.C., Wang B., Campbell M.S., Stein J.C., Wei X., Chin C.S., Guill K., Regulski M., Kumari S., Olson A., Gent J., Schneider K.L., Wolfgruber T.K., May M.R., Springer N.M., Antoniou E., McCombie W.R., Presting G.G., McMullen M., Ross-Ibarra J., Dawe R.K., Hastie A., Rank D.R, & Ware D. (2017). Improved maize reference genome with single-molecule technologies. Nature, 546(7659), 524-527.
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Publication 2017
6H,8H-3,4-dihydropyrimido(4,5-c)(1,2)oxazin-7-one BP 100 Chromosomes Deletion Mutation Gene Deletion Genome Heterozygote Inversion, Chromosome Maize Vision

Most recents protocols related to «Maize»

1
Microbial Seed Treatments for Enhanced Crop Performance
Not available on PMC !

Example 2

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiably higher biomass than the control corn plants.

The biomass from the treated plants may be about 1-10% higher, 10-20% higher, 20-30% higher, 30-40% higher, 40-50% higher, 50-60% higher, 60-70% higher, 70-80% higher, 80-90% higher, or more.

The biomass from the treated plants may equate to about a 1 bushel per acre increase over the controls, or a 2 bushel per acre increase, or a 3 bushel per acre increase, or a 4 bushel per acre increase, or a 5 bushel per acre increase, or more.

In some aspects, the biomass increase is statistically significant. In other aspects, the biomass increase is not statistically significant, but is still quantifiable.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the with the agricultural composition will exhibit a quantifiable and superior ability to tolerate drought conditions and/or exhibit superior water use efficiency, as compared to the control corn plants.

The drought tolerance and/or water use efficiency can be based on any number of standard tests from the art, e.g leaf water retention, turgor loss point, rate of photosynthesis, leaf color and other phenotypic indications of drought stress, yield performance, and various root morphological and growth patterns.

A. Seed Treatment with Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the isolated microbe as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the isolated microbe applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

B. Seed Treatment with Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as a seed coating to seeds of corn (Zea mays). Upon applying the microbial consortium as a seed coating, the corn will be planted and cultivated in the standard manner.

A control plot of corn seeds, which did not have the microbial consortium applied as a seed coating, will also be planted.

It is expected that the corn plants grown from the seeds treated with the seed coating will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

C. Treatment with Agricultural Composition Comprising Isolated Microbe

In this example, an isolated microbe from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

D. Treatment with Agricultural Composition Comprising Microbial Consortia

In this example, a microbial consortium, comprising at least two microbes from Tables 1-3 will be applied as an agricultural composition, administered to the corn seed at the time of sowing.

For example, it is anticipated that a farmer will apply the agricultural composition to the corn seeds simultaneously upon planting the seeds into the field. This can be accomplished, for example, by applying the agricultural composition to a hopper/bulk tank on a standard 16 row planter, which contains the corn seeds and which is configured to plant the same into rows. Alternatively, the agricultural composition can be contained in a separate bulk tank on the planter and sprayed into the rows upon planting the corn seed.

A control plot of corn seeds, which are not administered the agricultural composition, will also be planted.

It is expected that the corn plants grown from the seeds treated with the agricultural composition will exhibit a quantifiable and superior ability to utilize nitrogen, as compared to the control corn plants.

The nitrogen use efficiency can be quantified by recording a measurable change in any of the main nitrogen metabolic pool sizes in the assimilation pathways (e.g., a measurable change in one or more of the following: nitrate, nitrite, ammonia, glutamic acid, aspartic acid, glutamine, asparagine, lysine, leucine, threonine, methionine, glycine, tryptophan, tyrosine, total protein content of a plant part, total nitrogen content of a plant part, and/or chlorophyll content), or where the treated plant is shown to provide the same or elevated biomass or harvestable yield at lower nitrogen fertilization levels compared to the control plant, or where the treated plant is shown to provide elevated biomass or harvestable yields at the same nitrogen fertilization levels compared to a control plant.

The inoculants were prepared from isolates grown as spread plates on R2A incubated at 25° C. for 48 to 72 hours. Colonies were harvested by blending with sterile distilled water (SDW) which was then transferred into sterile containers. Serial dilutions of the harvested cells were plated and incubated at 25° C. for 24 hours to estimate the number of colony forming units (CFU) in each suspension. Dilutions were prepared using individual isolates or blends of isolates (consortia) to deliver 1×105 cfu/microbe/seed and seeds inoculated by either imbibition in the liquid suspension or by overtreatment with 5% vegetable gum and oil.

Seeds corresponding to the plants of table 15 were planted within 24 to 48 hours of treatment in agricultural soil, potting media or inert growing media. Plants were grown in small pots (28 mL to 200 mL) in either a controlled environment or in a greenhouse. Chamber photoperiod was set to 16 hours for all experiments on all species. Air temperature was typically maintained between 22-24° C.

Unless otherwise stated, all plants were watered with tap water 2 to 3 times weekly. Growth conditions were varied according to the trait of interest and included manipulation of applied fertilizer, watering regime and salt stress as follows:

    • Low N—seeds planted in soil potting media or inert growing media with no applied N fertilizer
    • Moderate N—seeds planted in soil or growing media supplemented with commercial N fertilizer to equivalent of 135 kg/ha applied N
    • Insol P—seeds planted in potting media or inert growth substrate and watered with quarter strength Pikovskaya's liquid medium containing tri-calcium phosphate as the only form phosphate fertilizer.
    • Cold Stress—seeds planted in soil, potting media or inert growing media and incubated at 10° C. for one week before being transferred to the plant growth room.
    • Salt stress—seeds planted in soil, potting media or inert growing media and watered with a solution containing between 100 to 200 mg/L NaCl.

Untreated (no applied microbe) controls were prepared for each experiment. Plants were randomized on trays throughout the growth environment. Between 10 and 30 replicate plants were prepared for each treatment in each experiment. Phenotypes were measured during early vegetative growth, typically before the V3 developmental stage and between 3 and 6 weeks after sowing. Foliage was cut and weighed. Roots were washed, blotted dry and weighed. Results indicate performance of treatments against the untreated control.

TABLE 15
StrainShootRoot
Microbe sp.IDCropAssayIOC (%)IOC (%)
Bosea thiooxidans123EfficacyEfficacy
overall100%100%
Bosea thiooxidans54522WheatEarly vigor - insol P30-40 —
Bosea thiooxidans54522RyegrassEarly vigor50-60 50-60 
Bosea thiooxidans54522RyegrassEarly vigor - moderate P0-100-10
Duganella violaceinigra111EfficacyEfficacy
overall100%100%
Duganella violaceinigra66361TomatoEarly vigor0-100-10
Duganella violaceinigra66361TomatoEarly vigor30-40 40-50 
Duganella violaceinigra66361TomatoEarly vigor20-30 20-30 
Herbaspirillum huttiense222Efficacy—
overall100%
Herbaspirillum huttiense54487WheatEarly vigor - insol P30-40 —
Herbaspirillum huttiense60507MaizeEarly vigor - salt stress0-100-10
Janthinobacterium sp.222Efficacy—
Overall100%
Janthinobacterium sp.54456WheatEarly vigor - insol P30-40 —
Janthinobacterium sp.54456WheatEarly vigor - insol P0-10—
Janthinobacterium sp.63491RyegrassEarly vigor - drought0-100-10
stress
Massilia niastensis112EfficacyEfficacy
overall80%80%
Massilia niastensis55184WheatEarly vigor - salt stress0-1020-30 
Massilia niastensis55184WinterEarly vigor - cold stress0-1010-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress20-30 20-30 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress10-20 10-20 
wheat
Massilia niastensis55184WinterEarly vigor - cold stress<0<0
wheat
Novosphingobium rosa211EfficacyEfficacy
overall100%100%
Novosphingobium rosa65589MaizeEarly vigor - cold stress0-100-10
Novosphingobium rosa65619MaizeEarly vigor - cold stress0-100-10
Paenibacillus amylolyticus111EfficacyEfficacy
overall100%100%
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Paenibacillus amylolyticus66316TomatoEarly vigor10-20 10-20 
Paenibacillus amylolyticus66316TomatoEarly vigor0-100-10
Pantoea agglomerans323EfficacyEfficacy
33%50%
Pantoea agglomerans54499WheatEarly vigor - insol P40-50 —
Pantoea agglomerans57547MaizeEarly vigor - low N<00-10
Pantoea vagans55529MaizeEarly vigor<0<0
(formerly P. agglomerans)
Polaromonas ginsengisoli111EfficacyEfficacy
66%100%
Polaromonas ginsengisoli66373TomatoEarly vigor0-100-10
Polaromonas ginsengisoli66373TomatoEarly vigor20-30 30-40 
Polaromonas ginsengisoli66373TomatoEarly vigor<010-20 
Pseudomonas fluorescens122Efficacy—
100%
Pseudomonas fluorescens54480WheatEarly vigor - insol P>100 —
Pseudomonas fluorescens56530MaizeEarly vigor - moderate N0-10—
Rahnella aquatilis334EfficacyEfficacy
80%63%
Rahnella aquatilis56532MaizeEarly vigor - moderate N10-20 —
Rahnella aquatilis56532MaizeEarly vigor - moderate N0-100-10
Rahnella aquatilis56532WheatEarly vigor - cold stress0-1010-20 
Rahnella aquatilis56532WheatEarly vigor - cold stress<00-10
Rahnella aquatilis56532WheatEarly vigor - cold stress10-20 <0
Rahnella aquatilis57157RyegrassEarly vigor<0—
Rahnella aquatilis57157MaizeEarly vigor - low N0-100-10
Rahnella aquatilis57157MaizeEarly vigor - low N0-10<0
Rahnella aquatilis58013MaizeEarly vigor0-1010-20 
Rahnella aquatilis58013MaizeEarly vigor - low N0-10<0
Rhodococcus erythropolis313Efficacy—
66%
Rhodococcus erythropolis54093MaizeEarly vigor - low N40-50 —
Rhodococcus erythropolis54299MaizeEarly vigor - insol P>100 —
Rhodococcus erythropolis54299MaizeEarly vigor<0<0
Stenotrophomonas chelatiphaga611EfficacyEfficacy
60%60%
Stenotrophomonas chelatiphaga54952MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga47207MaizeEarly vigor<0 0
Stenotrophomonas chelatiphaga64212MaizeEarly vigor0-1010-20 
Stenotrophomonas chelatiphaga64208MaizeEarly vigor0-100-10
Stenotrophomonas chelatiphaga58264MaizeEarly vigor<0<0
Stenotrophomonas maltophilia612EfficacyEfficacy
43%66%
Stenotrophomonas maltophilia54073MaizeEarly vigor - low N50-60 —
Stenotrophomonas maltophilia54073MaizeEarly vigor<00-10
Stenotrophomonas maltophilia56181MaizeEarly vigor0-10<0
Stenotrophomonas maltophilia54999MaizeEarly vigor0-100-10
Stenotrophomonas maltophilia54850MaizeEarly vigor 00-10
Stenotrophomonas maltophilia54841MaizeEarly vigor<00-10
Stenotrophomonas maltophilia46856MaizeEarly vigor<0<0
Stenotrophomonas rhizophila811EfficacyEfficacy
12.5%37.5%
Stenotrophomonas rhizophila50839MaizeEarly vigor<0<0
Stenotrophomonas rhizophila48183MaizeEarly vigor<0<0
Stenotrophomonas rhizophila45125MaizeEarly vigor<0<0
Stenotrophomonas rhizophila46120MaizeEarly vigor<00-10
Stenotrophomonas rhizophila46012MaizeEarly vigor<0<0
Stenotrophomonas rhizophila51718MaizeEarly vigor0-100-10
Stenotrophomonas rhizophila66478MaizeEarly vigor<0<0
Stenotrophomonas rhizophila65303MaizeEarly vigor<00-10
Stenotrophomonas terrae221EfficacyEfficacy
50%50%
Stenotrophomonas terrae68741MaizeEarly vigor<0<0
Stenotrophomonas terrae68599MaizeEarly vigor<00-10
Stenotrophomonas terrae68599Capsicum *Early vigor20-30 20-30 
Stenotrophomonas terrae68741Capsicum *Early vigor10-20 20-30 

The data presented in table 15 describes the efficacy with which a microbial species or strain can change a phenotype of interest relative to a control run in the same experiment. Phenotypes measured were shoot fresh weight and root fresh weight for plants growing either in the absence of presence of a stress (assay). For each microbe species, an overall efficacy score indicates the percentage of times a strain of that species increased a both shoot and root fresh weight in independent evaluations. For each species, the specifics of each independent assay is given, providing a strain ID (strain) and the crop species the assay was performed on (crop). For each independent assay the percentage increase in shoot and root fresh weight over the controls is given.

US11871752B2. Agriculturally beneficial microbes, microbial compositions, and consortia (2024-01-16). BIOCONSORTIA, INC. [US]. Inventors: Peter Wigley [NZ], Susan Turner [US], Caroline George [NZ], Thomas Williams [US], Kelly Roberts [US], Graham Hymus [US], Kelvin Lau [NZ].
Full text: Click here
Patent 2024
Ammonia Asparagine Aspartic Acid Biological Assay Bosea thiooxidans Calcium Phosphates Capsicum Cells Chlorophyll Cold Shock Stress Cold Temperature Crop, Avian Dietary Fiber DNA Replication Droughts Drought Tolerance Embryophyta Environment, Controlled Farmers Fertilization Glutamic Acid Glutamine Glycine Growth Disorders Herbaspirillum Herbaspirillum huttiense Leucine Lolium Lycopersicon esculentum Lysine Maize Massilia niastensis Methionine Microbial Consortia Nitrates Nitrites Nitrogen Novosphingobium rosa Paenibacillus Paenibacillus amylolyticus Pantoea agglomerans Pantoea vagans Phenotype Phosphates Photosynthesis Plant Development Plant Embryos Plant Leaves Plant Proteins Plant Roots Plants Polaromonas ginsengisoli Pseudoduganella violaceinigra Pseudomonas Pseudomonas fluorescens Rahnella Rahnella aquatilis Retention (Psychology) Rhodococcus erythropolis Rosa Salt Stress Sodium Chloride Sodium Chloride, Dietary Stenotrophomonas chelatiphaga Stenotrophomonas maltophilia Stenotrophomonas rhizophila Stenotrophomonas terrae Sterility, Reproductive Strains Technique, Dilution Threonine Triticum aestivum Tryptophan Tyrosine Vegetables Zea mays
2
Modeling Resistance Evolution in Bt Crops
Not available on PMC !

Example 10

The model demonstrates that resistance evolves first to Intacta soy when mating disruption is used on corn, but resistance evolves first to Cry1A.105+Cry2Ab2 corn when mating disruption is used in conjunction with the Intacta soy (FIG. 9A-9B).

The Intacta soy is a high dose single gene product (the Bt toxin kills 95% of larvae on it), while the corn actually has two low dose events (each kills 85% of the larvae developing on it).

In many of the model simulations, durability is increased from 1 to 2 years, which may be an artifact of the base simulation having too little refuge present. It is hypothesized that if more refuge is added to the model, or unsprayed refuge is added, or more genes in each product are added, then the MD would increase durability from 10 to 20 years. In each case MD has doubled durability.

US11856951B2. Method for managing resistance to insecticidal traits and chemicals using pheromones (2024-01-02). Provivi, Inc. [US]. Inventors: John B. Schoper [US], Pedro Coelho [US], Christopher Wheeler [US].
Full text: Click here
Patent 2024
Bacillus thuringiensis Toxins Larva Maize Proteins
3
Corn and Soy Resistance Evolution
Not available on PMC !

Example 9

MD can be thought of as an additional mode of action and thus corn and soy with Cry1A.105+Cry2Ab2 would have two modes of action, while fields with mating disruption (Cry1A.105+Cry2Ab2+MD) would have 3 modes of action. It is known that having single gene traits in place when releasing dual gene traits can lead to more rapid resistance evolution. This normally would not be as much of a problem with 2 and 3 modes of action, but refuge size is minimal in this model, and the two gene corn and soy without mating disruption drives the entire system towards rapid resistance evolution (FIG. 8).

US11856951B2. Method for managing resistance to insecticidal traits and chemicals using pheromones (2024-01-02). Provivi, Inc. [US]. Inventors: John B. Schoper [US], Pedro Coelho [US], Christopher Wheeler [US].
Full text: Click here
Patent 2024
Biological Evolution Genes Maize
4
Enhancing Corn Plant Properties
Not available on PMC !

Example 7

To produce corn plants or plant parts thereof which comprise enhanced agronomic, insecticidal, or herbicidal properties, corn plants containing event MON 87411 can be crossed with corn plants containing potentially any other corn event or combination thereof and phenotypes evaluated to determine the resulting properties of the progeny plants. As a non-limiting example, MON 87411 can be crossed with corn plants including one or more combinations, of the following: DAS-59122-7; MIR604; MON 89034; MON 87411; MON 87427; TC1507; 5307; DAS-06275-8; BT176; BT11; and MIR162.

US11859198B2. Corn event MON 87411 (2024-01-02). Monsanto Technology LLC [US]. Inventors: Wen C. Burns [US], Catherine A. Chay [US], Cheryl L. Cloninger [US], Mingqi Deng [US], Stanislaw Flasinski [US], Kunsheng Wu [US].
Full text: Click here
Patent 2024
Herbicides Insecticides Maize Phenotype Plants Zea mays
5
Heifer Feed Intake Monitoring
Two heifer development pens (N = 63 per pen) were utilized at the CGREC for a 2-week training period where one MCCC unit was placed in each dry lot pen. A portion of the heifer development ration (corn silage) was placed into the feed bins and heifer intake was monitored. Only heifers with a history of feed consumption from the feeders were selected as experimental units for this experiment.
McCarthy K.L., Underdahl S.R., Undi M, & Dahlen C.R. (2023). Using precision tools to manage and evaluate the effects of mineral and protein/energy supplements fed to grazing beef heifers. Translational Animal Science, 7(1), txad013.
Full text: Click here
Publication 2023
Maize Menstruation Disturbances Silage

Top products related to «Maize»

1
Trizol reagent by Thermo Fisher Scientific
Sourced in United States, China, Japan, Germany, United Kingdom, Canada, France, Italy, Australia, Spain, Switzerland, Netherlands, Belgium, Lithuania, Denmark, Singapore, New Zealand, India, Brazil, Argentina, Sweden, Norway, Austria, Poland, Finland, Israel, Hong Kong, Cameroon, Sao Tome and Principe, Macao, Taiwan, Province of China, Thailand
TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
2
Rneasy plant mini kit by Qiagen
Sourced in Germany, United States, United Kingdom, Netherlands, China, Japan, Canada, Spain, France, Australia, Italy, India, Sweden
The RNeasy Plant Mini Kit is a laboratory equipment designed for the isolation and purification of total RNA from plant tissues and cells. It utilizes a silica-membrane-based technology to efficiently capture and purify RNA molecules, enabling subsequent analysis and downstream applications.
3
Trizol by Thermo Fisher Scientific
Sourced in United States, Germany, China, Japan, United Kingdom, Canada, France, Italy, Spain, Australia, Switzerland, Belgium, Denmark, Netherlands, India, Ireland, Lithuania, Singapore, Sweden, Norway, Austria, Brazil, Argentina, Hungary, Sao Tome and Principe, New Zealand, Hong Kong, Cameroon, Philippines
TRIzol is a monophasic solution of phenol and guanidine isothiocyanate that is used for the isolation of total RNA from various biological samples. It is a reagent designed to facilitate the disruption of cells and the subsequent isolation of RNA.
4
Hiseq 2000 by Illumina
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The HiSeq 2000 is a high-throughput DNA sequencing system designed by Illumina. It utilizes sequencing-by-synthesis technology to generate large volumes of sequence data. The HiSeq 2000 is capable of producing up to 600 gigabases of sequence data per run.
5
Hiseq 2500 by Illumina
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The HiSeq 2500 is a high-throughput DNA sequencing system designed for a wide range of applications, including whole-genome sequencing, targeted sequencing, and transcriptome analysis. The system utilizes Illumina's proprietary sequencing-by-synthesis technology to generate high-quality sequencing data with speed and accuracy.
6
Maizesnp50 beadchip by Illumina
Sourced in United States
The MaizeSNP50 BeadChip is a high-throughput genotyping platform designed for genetic analysis of maize (corn) samples. It enables the simultaneous detection and interrogation of thousands of single nucleotide polymorphisms (SNPs) across the maize genome. The BeadChip provides a comprehensive and efficient tool for researchers to conduct genetic studies, trait mapping, and marker-assisted breeding in maize.
7
Sas 9 by SAS Institute
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SAS 9.4 is an integrated software suite for advanced analytics, data management, and business intelligence. It provides a comprehensive platform for data analysis, modeling, and reporting. SAS 9.4 offers a wide range of capabilities, including data manipulation, statistical analysis, predictive modeling, and visual data exploration.
8
Agilent 2100 bioanalyzer by Agilent Technologies
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The Agilent 2100 Bioanalyzer is a lab instrument that provides automated analysis of DNA, RNA, and protein samples. It uses microfluidic technology to separate and detect these biomolecules with high sensitivity and resolution.
9
Sodium hydroxide (naoh) by Merck Group
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Sodium hydroxide is a chemical compound with the formula NaOH. It is a white, odorless, crystalline solid that is highly soluble in water and is a strong base. It is commonly used in various laboratory applications as a reagent.
10
Rnaprep pure plant kit by Tiangen Biotech
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The RNAprep Pure Plant Kit is a laboratory equipment product designed for the isolation and purification of total RNA from a variety of plant samples. It utilizes a silica-based membrane technology to efficiently capture and purify RNA molecules.

More about "Maize"

Maize, also known as corn, is a versatile cereal grain that is widely cultivated globally.
It is a staple food crop and a key ingredient in a variety of food and industrial products.
Maize is an important source of carbohydrates, protein, vitamins, and minerals, making it a nutritionally valuable crop.
The maize plant is characterized by its large ears, which contain rows of kernels that can be consumed fresh, dried, or processed.
Maize has a rich history of cultivation and is a significant contributor to food security and the global economy.
Researchers continue to study maize to optimize its yield, nutritional profile, and resilience to environmental stressors.
Techniques like TRIzol reagent, RNeasy Plant Mini Kit, and the MaizeSNP50 BeadChip are used to extract and analyze maize RNA and genomic data.
Software tools like SAS 9.4 and the Agilent 2100 Bioanalyzer help researchers process and interpret their findings.
In addition to food applications, maize is also used in the production of biofuels, animal feed, and industrial products.
Sodium hydroxide is sometimes used in the processing of maize to produce high-fructose corn syrup and other corn-derived ingredients.
PubCompare.ai's AI-driven protocol comparisons can enhance maize research by helping scientists identify the best methods and products from the literature, pre-prints, and patents.
This ensures reproducibility and accuracy in maize optimization studies, unlocking the full potential of this versatile and important crop.