scholarly journals QTL mapping for grain yield and three yield components in a population derived from two high-yielding spring wheat cultivars

2021 ◽  
Author(s):  
Kyle Isham ◽  
Rui Wang ◽  
Weidong Zhao ◽  
Justin Wheeler ◽  
Natalie Klassen ◽  
...  
Keyword(s):  
Grain Yield ◽  
Spring Wheat ◽  
Yield Components ◽  
Heading Date ◽  
Kernel Weight ◽  
Yield Component ◽  
Six Traits ◽  
Component Traits ◽  
Yield Component Traits ◽  
Spikelet Number Per Spike

Abstract Key message Four genomic regions on chromosomes 4A, 6A, 7B, and 7D were discovered, each with multiple tightly linked QTL (QTL clusters) associated with two to three yield components. The 7D QTL cluster was associated with grain yield, fertile spikelet number per spike, thousand kernel weight, and heading date. It was located in the flanking region of FT-D1, a homolog gene of Arabidopsis FLOWERING LOCUS T, a major gene that regulates wheat flowering. Abstract Genetic manipulation of yield components is an important approach to increase grain yield in wheat (Triticum aestivum). The present study used a mapping population comprised of 181 doubled haploid lines derived from two high-yielding spring wheat cultivars, UI Platinum and LCS Star. The two cultivars and the derived population were assessed for six traits in eight field trials primarily in Idaho in the USA. The six traits were grain yield, fertile spikelet number per spike, productive tiller number per unit area, thousand kernel weight, heading date, and plant height. Quantitative Trait Locus (QTL) analysis of the six traits was conducted using 14,236 single-nucleotide polymorphism (SNP) markers generated from the wheat 90 K SNP and the exome and promoter capture arrays. Of the 19 QTL detected, 14 were clustered in four chromosomal regions on 4A, 6A, 7B and 7D. Each of the four QTL clusters was associated with multiple yield component traits, and these traits were often negatively correlated with one another. As a result, additional QTL dissection studies are needed to optimize trade-offs among yield component traits for specific production environments. Kompetitive allele-specific PCR markers for the four QTL clusters were developed and assessed in an elite spring wheat panel of 170 lines, and eight of the 14 QTL were validated. The two parents contain complementary alleles for the four QTL clusters, suggesting the possibility of improving grain yield via genetic recombination of yield component loci.

Genetic analysis of grain yield conditioned on its component traits in rice (Oryza sativa L.)

2008 ◽  
Vol 59 (2) ◽  
pp. 189 ◽  
Author(s):  
G. F. Liu ◽  
J. Yang ◽  
H. M. Xu ◽  
Y. Hayat ◽  
J. Zhu
Keyword(s):  
Grain Yield ◽  
Yield Components ◽  
Genetic Relationships ◽  
Mapping Method ◽  
Yield Component ◽  
Doubled Haploid Population ◽  
Environment Interaction ◽  
Panicle Number ◽  
Component Traits ◽  
Yield Component Traits

Grain yield (GY) of rice is a complex trait consisting of several yield components. It is of great importance to reveal the genetic relationships between GY and its yield components at the QTL (quantitative trait loci) level for multi-trait improvement in rice. In the present study, GY per plant in rice and its 3 yield component traits, panicle number per plant (PN), grain number per panicle (GN), and 1000-grain weight (GW), were investigated using a doubled-haploid population derived from a cross of an indica variety IR64 and a japonica variety Azucena. The phenotypic values collected from 2 cropping seasons were analysed by QTLNetwork 2.0 for mapping QTLs with additive (a) and/or additive × environment interaction (ae) effects. Furthermore, conditional QTL analysis was conducted to detect QTLs for GY independent of yield components. The results showed that the general genetic variation in GY was largely influenced by GN with the contribution ratio of 29.2%, and PN and GN contributed 10.5% and 74.6% of the genotype × environment interaction variation in GY, respectively. Four QTLs were detected with additive and/or additive × environment interaction effects for GY by the unconditional mapping method. However, for GY conditioned on PN, GN, and GW, 6 additional loci were identified by the conditional mapping method. All of the detected QTLs affecting GY were associated with at least one of the 3 yield components. The results revealed that QTL expressions of GY were contributed differently by 3 yield component traits, and provide valuable information for effectively improving GY in rice.

scholarly journals Heterosis and Combining Ability for Grain Yield and Yield Component Traits of Maize in Eastern Ethiopia

2015 ◽  
Vol 3 (2) ◽  
pp. 118-127 ◽  
Author(s):  
Habtamu Zeleke
Keyword(s):  
Grain Yield ◽  
Combining Ability ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Kernel Weight ◽  
Yield Component ◽  
Days To Maturity ◽  
Component Traits ◽  
The Mean ◽  
Yield Component Traits

Combining ability analysis for grain yield and yield component traits in maize were carried out in 8×8 diallel cross. The analysis of variance showed there is highly significant variation between the genotypes for all the traits considered. Year of testing was significant only for days to maturity and grain yield per hectare. The highest percentage of heterosis for grain over the standard varieties (BH 660) was observed by the cross L1 x L4 (29.3%) followed by crosses L1 x L5 (28.3%), L3 x L5 (21.7%) and L1 x L7 (20.8%). Mid-parent heterosis for days to maturity ranged from -2.5 to -23.9%, whereas that of better parent heterosis ranged from 0 to -13% indicating that the hybrids tend to be earlier in maturity than the parents. The mean squares due to GCA for days to maturity, ear diameter, member of kernels per row, 1000 kernel weight and grain yield were significant, indicating the importance of additive genetic variance in controlling these traits. The mean squares due to SCA were also significant for days to maturity, ear length, member of kernels per row and 1000 kernel weight indicating the importance of non-additive genetic variance in controlling these traits. The inbred lines L1, L3, and L4 were good general combiners for grain yield.

Effect of nitrogen, seeding date and cultivar on oat quality and yield in the eastern Canadian prairies

2004 ◽  
Vol 84 (4) ◽  
pp. 1025-1036 ◽  
Author(s):  
William E. May ◽  
Ramona M. Mohr ◽  
Guy P. Lafond ◽  
Adrian M. Johnston ◽  
F. Craig Stevenson
Keyword(s):  
Grain Yield ◽  
Avena Sativa ◽  
Yield Components ◽  
Seed Quality ◽  
Kernel Weight ◽  
Yield Component ◽  
Human Consumption ◽  
Seeding Date ◽  
N Rates

The proportion of oat (Avena sativa L.) being used for race horses and human consumption has increased over the past 15 yr. The objective of this study was to evaluate the effects of N, seeding date and cultivar on grain yield components, grain yield and grain quality of oat under a direct seeding system. Four N rates, three seeding dates and two cultivars were tested at Indian Head, Melfort, and Canora, SK, and Brandon, MB. Yield was more responsive to increasing N rates from 15 and 80 kg ha-1 when oat was seeded in early May versus early June. Panicles plant-1 was the yield component that accounted for most of the yield increase achieved from increasing rates of N, while kernel weight was the yield component that decreased as the rate of N increased. Physical seed quality decreased (plump seed decreased and thin seed increased) with delayed seeding and greater N fertilizer rates. Nitrogen fertilizer and seeding date had a much larger effect on the quality of CDC Pacer than AC Assiniboia. Combining early seeding, appropriate N fertility and well-adapted cultivars should increase the likelihood of optimizing oat yield and quality necessary for high-value markets. Key words: Avena sativa L., yield components, test weight, lodging, plump seed, thin seed

Improving hexaploid spring wheat by introgression of alleles for yield component traits from durum wheat

Crop Science ◽  
2020 ◽  
Vol 60 (2) ◽  
pp. 759-771 ◽  
Author(s):  
Brittney H. Jones ◽  
Nancy K. Blake ◽  
Hwa‐Young Heo ◽  
Jay R. Kalous ◽  
John M. Martin ◽  
...  
Keyword(s):  
Durum Wheat ◽  
Spring Wheat ◽  
Yield Component ◽  
Component Traits ◽  
Yield Component Traits

scholarly journals Synergistic effect of P and K interaction on yield and yield components of mungbean (Vigna radiata (L.) Wilczek) varieties

2021 ◽  
Vol 45 (1) ◽  
Author(s):  
E. M. Abd El Lateef ◽  
Asal M. Wali ◽  
M. S. Abd El-Salam
Keyword(s):  
Synergistic Effect ◽  
Seed Yield ◽  
Yield Components ◽  
Field Experiments ◽  
Fertilizer Application ◽  
Yield Component ◽  
Beneficial Effects ◽  
Yield And Yield Components ◽  
Component Traits ◽  
Yield Component Traits

Abstract Background The relation between the macronutrients P and K seems to be synergistic due to the beneficial effects of the interaction between (P × K) and varies according to the variety used. Therefore, two field experiments were conducted during 2018 and 2019 summer seasons to study the effect of interaction of phosphatic fertilization at 0, 37.5 and 75 kg P2O5 ha−1 and potassic fertilization at 0 and 57.6 kg K2O ha−1 on the yield and yield components of two mungbean varieties, viz. Kawmy-l and V2010, as well as determining the relationship between the two nutrients interaction. Results The results showed that there were varietal differences in yield and yield components regardless fertilizer application. Either phosphatic or potassic fertilization significantly increased mungbean yield and yield components traits. Significant effects due to the interaction (V × P) were reported on yield component traits in both seasons. Furthermore, the triple interaction (V × P × K) indicates that synergistic effect was reported for the two varieties and was more clearer for V2010 where it needed both of P and K nutrients to out yield the greatest seed yield ha−1, while Kawmy-1 gave the greatest seed yield ha−1 without K application. Conclusion It could be concluded from this study that mungbean varieties differ in their response to the synergistic interaction effect of P and K and the combination of 75 kg P2O5 + 57.6 kg K2O is preferable for V2010 and 75 kg P2O5 alone for Kawmy-1 to produce the greatest yield.

scholarly journals DEVELOPMENT AND APPLICATION OF 1536-PLEX SINGLE NUCLEOTIDE POLYMORPHISM MARKER CHIP FOR GENOME WIDE SCANNING OF INDONESIAN RICE GERMPLASM

2013 ◽  
Vol 14 (2) ◽  
pp. 71
Author(s):  
Dwinita W. Utami ◽  
I. Rosdianti ◽  
P. Lestari ◽  
D. Satyawan ◽  
H. Rijzaani ◽  
...  
Keyword(s):  
Molecular Breeding ◽  
Rice Genome ◽  
Heading Date ◽  
Snp Markers ◽  
Yield Component ◽  
Diversity Analysis ◽  
Rice Germplasm ◽  
Genome Wide ◽  
Component Traits ◽  
Yield Component Traits

A successful molecular breeding program requires detailed and comprehensive understanding of the diversity of rice germ-plasm and genetic base of target traits. The objective of this research was to develop the high throughput 1536-SNP chip linked to heading date and yield component traits and used it for genotyping the diverse Indonesian rice germplasm. The genotype data obtained could be used for diversity analysis and genome wide association mapping study. A 1536-SNP genome wide assay was developed using the Illumina’s GoldenGate technology. The SNP markers were selected in the rice genome regions containing heading date and yield component genes or regions where the quantitative trait loci (QTLs) of the two traits were mapped. The developed custom SNP chips were then used for genotyping 467 rice accessions showing diversity in heading dates and yield components. The assay can reliably be used for diversity analysis and mapping genes associated with heading date and yield component traits. For 1536-SNP BIO-RiceOPA-1 custom chip designed, a total of 34.832 SNPs distributed in rice genome particularly in the region of heading date and yield component genes or QTLs were identified. A total of 1536-SNP were selected and confirmed to be used for genotyping analysis. Analysis performance and quality of 1536-SNP BIO-RiceOPA1 showed that 60% (918/1536) of total SNP markers had a good differentiating power in scanning the rice accessions tested (MAF &gt; 0.2). The 1536-SNP genome wide assay Illumina’s GoldenGate designed was useful for diversity analysis and could be used as SNP marker for large scale genotyping in rice molecular breeding involving Indica-Indica, Indica-Japonica and Indica-Tropical Japonica crosses. <br />

Allelic response of yield component traits to resource availability in spring wheat

2020 ◽  
Author(s):  
Brittney H. Jones ◽  
Nancy K. Blake ◽  
Hwa-Young Heo ◽  
John M. Martin ◽  
Jessica A. Torrion ◽  
...  
Keyword(s):  
Spring Wheat ◽  
Resource Availability ◽  
Yield Component ◽  
Component Traits ◽  
Yield Component Traits

scholarly journals Source-sink Relationship and Their Influence on Yield Performance of YAU Promising Rice Lines

2020 ◽  
pp. 124-135
Author(s):  
Myint Aye ◽  
Chan Nyein Thu ◽  
Nyo Mar Htwe
Keyword(s):  
Grain Yield ◽  
Dry Weight ◽  
Yield Component ◽  
Grain Weight ◽  
Yield Performance ◽  
Component Traits ◽  
Yield Component Traits ◽  
Source Sink ◽  
1000 Grain Weight ◽  
Panicle Weight

Fifty YAU promising rice genotypes were used to evaluate source-sink relationship and yield performance in 2017 dry season. The experiment was conducted in the experimental field of Yezin Agricultural University, Nay Pyi Taw, Myanmar. The spacing was 20 cm between row and 20 cm between plants in a randomized complete block design with three replications. The data on physiological traits, yield and yield component traits were collected and analyzed by using STAR and R program. Growth duration1 is positively and significantly correlated with the number of grains panicle-1, filled grains percentage, grain yield, panicle weight, dry weight at heading and harvesting, straw weight and LAI at harvesting, and increase of dry weight from heading to harvesting. Significant positive correlation was found between growth duration2 and decrease of LAI from heading to harvesting indicating that these traits are strongly influenced by source before heading. Significant correlations between yield and physiological and yield component traits were observed except LAI at harvesting and 1000-grain weight. Therefore, yield variation among YAU promising rice lines is more related with source size than with sink size. Decrease of LAI from heading to harvesting and dry weight at maturity exhibited positive direct effect on 1000-grain weight, filled grains percentage and grain number m-2 meaning the relative contribution of source components to the sink. The contribution of the decrease of LAI from heading to harvesting to the grain yield was much higher than that of number of grains, panicle weight and 1000-grain weight. This research finding will be useful for the plant breeder to consider the improvement of yield supporting traits in the breeding program.

Sign in / Sign up

Export Citation Format

Share Document