Confirmation of the pleiotropic control of leaflet shape and number of seeds per pod by the &lt;i&gt;Ln&lt;/i&gt; gene in induced soybean mutants

Sayama, Takashi; Tanabata, Takanari; Saruta, Masayasu; Yamada, Testsuya; Anai, Toyoaki; Kaga, Akito; Ishimoto, Masao

doi:10.1270/jsbbs.16201

Cited by 28 publications

(25 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The upper limits for the number of seeds per pod and seed size are determined genetically. However, these two components can still undergo significant changes, thus raising the yield of the genotype (Sayama et al, 2017). These changes in yield can be caused by several factors, such as changes in the environmental elements (relative humidity and air temperature, radiation, precipitation), amount of weeds and pathogens in the crop, agricultural practices, sowing season, maturation group, fertilization (Allen et al, 2017, Cafaro La Menza et al, 2017, among others.…”

Section: Resultsmentioning

confidence: 99%

Productive potential and seed quality of soybean genotypes with different maturity groups

et al. 2019

View full text Add to dashboard Cite

Soybean has economically stood out worldwide. In MATOPIBA region of Brazil (Maranhão, Tocantins, Paiuí e Bahia) it is the most economically important crop with participation in the country’s GDP growth. Due to this great growth economic and the incentive to the production of this oilseed, this study aimed to understand the behavior and physiological quality of soybean genotypes and to determine the productive potential of soybean seeds of different cultivars in the Cerrado of the State of Piauí. To this end, an experiment was carried out at Celeiro Farm, located in Serra do Quilombo, municipality of Monte Alegre do Piauí. Sowing followed the usual standards and was carried out on January 10, 2016. The experiment was set up in a randomized complete block design with four replicates. The treatments consisted of five cultivars of INTACTA RR2 PRO soybean, with different maturity groups: C1: MG 8.6, C2: MG 8.3, C3: MG 8.6.1, C4: MG 7.9 and C5: MG 8.5. The analyzed variables were: plant height, number of nodes, internode length, pod length, number of grains per pod, number of grains per plant, one thousand seed weight, productivity, first germination count, germination, seedling length, germination speed index and seedling dry mass. The results indicated that the best cultivars were: C5:TMG 2185 IPRO for plant height, internode length and pod length, and C4: BÔNUS IPRO for number of grains per pod, number of grains per plant, one thousand seed weight, and productivity. Considering the first count, germination, and germination speed index, the best cultivar was C5.

show abstract

Section: Resultsmentioning

confidence: 99%

Productive potential and seed quality of soybean genotypes with different maturity groups

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The qSw20-1 is closely linked to the Ln locus; whose recessive allele governs narrow leaflet morphology. Previous studies indicated a relationship between small seed and narrow leaflet phenotypes controlled by the Ln locus ( Dinkins et al 2002 , Jeong et al 2011 , Sayama et al 2017 ). ‘Tachinagaha’ is a narrow leaflet cultivar and the small-seeded ln allele at qSw20-1 was certainly derived from this narrow leaflet parent in the NsT-RIL population ( Supplemental Table 5 ).…”

Section: Discussionmentioning

confidence: 99%

“…The narrow leaflet phenotype, controlled by the Ln locus ( Bernard and Weiss 1973 , Jeong et al 2012 ), is associated with both decreased SSW and increased NOP ( Dinkins et al 2002 , Jeong et al 2011 ). The induced mutant line for the Gm-JAG1 ( Glyma20g25000 ) gene clearly demonstrated the increase in NSP compensated reductions of SSW ( Sayama et al 2017 ) . Therefore, it is likely that SSW and other SYCs are regulated by common loci and share regulatory mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Identification and dissection of single seed weight QTLs by analysis of seed yield components in soybean

et al. 2018

Self Cite

View full text Add to dashboard Cite

Single seed weight (SSW), or seed size, is a seed yield components (SYC) in soybean, and it is suggested that the genetic factors regulating SSW are involved in the control of other SYCs. The quantitative trait loci (QTLs) for SSW and their effects on the other SYCs were investigated using a recombinant inbred line population derived from typical small- and large-seeded cultivars that were cultivated in two different environments. QTL analysis detected four environmentally stable QTLs for SSW, two of which coincided with the defined loci, qSw17-1 and Ln. The effects of the other loci, qSw12-1 and qSw13-1, were confirmed by analyzing residual heterozygous line progenies derived from the recombinant population. These four QTL regions were also involved in the control of an additional SYC, namely the large-seeded allele at each locus that reduced either the number of pods per plant or the number of ovules per pod. These results suggest the presence of at least two different regulatory mechanisms for SSW. Isolation of genes responsible for these QTLs provides an important tool in the understanding and utilization of SSW diversity for soybean breeding.

show abstract

“…Description of the individual leaflet elongation model Since the node number estimation is the same as the leaf number estimation in soybean, the leaf area for the whole plant may be calculated by adding estimates of the leaf area at each node. Leaf area of each leaflet may be estimated from the leaflet length because the length and width of a leaflet increase symmetrically (Inaba, 1992), while soybean leaflet shape is genetically controlled (Sawada, 1992;Sayama et al, 2017). Individual leaflet elongation rate is highly correlated with the air temperature (Bunce, 1985).…”

Section: Description Of the Node Number Estimation Modelmentioning

confidence: 99%

Modeling leaf area development in soybean (Glycine max L.) based on the branch growth and leaf elongation

Nakano

Purcell

Homma

et al. 2019

Plant Production Science

View full text Add to dashboard Cite

Several models have been proposed to simulate the leaf area index (LAI) in soybean (Glycine max L.); however, these models do not directly account for the effect of branch growth. Because the increases in branches and branch node vary with plant density, the evaluation of branch growth is necessary for the application of the LAI model at various plant densities. In this study, we developed an LAI model for soybean, considering the branch growth and leaf elongation at each node. To simplify this model, we estimated the rate of branch and branch node increase based on the rate of main stem node increase. Branch growth was assumed to be restricted when the fraction of canopy radiation interception was increased. Moreover, we calculated the leaf area growth at each node based on leaf elongation at each leaflet. This LAI model was validated using the data of different years and plant densities for model calibration, and it estimated the LAI with a root mean square error of 0.76, which accounted for 92% of the variation in the data. Although further evaluation is needed, the LAI model proposed in this study reveals a high potential for accurate estimation of LAI at various plant densities.

show abstract

Confirmation of the pleiotropic control of leaflet shape and number of seeds per pod by the <i>Ln</i> gene in induced soybean mutants

Cited by 28 publications

References 20 publications

Productive potential and seed quality of soybean genotypes with different maturity groups

Productive potential and seed quality of soybean genotypes with different maturity groups

Identification and dissection of single seed weight QTLs by analysis of seed yield components in soybean

Modeling leaf area development in soybean (Glycine max L.) based on the branch growth and leaf elongation

Contact Info

Product

Resources

About