Wheat grain biofortification for essential amino acids

Loro, Murilo Vieira; Carvalho, Ivan Ricardo; Filho, Alberto Cargnelutti; Hoffmann, Jéssica Fernanda; Kehl, Kassiana

doi:10.1590/s1678-3921.pab2023.v58.02860

Cited by 5 publications

(5 citation statements)

References 37 publications

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“…For that, the REML/BLUP methodology has helped to select genotypes in crops such as soybeans (PRADEBON et al, 2023;KEHL et al, 2022;KNEBEL et al, 2021), wheat (LORO et al, 2023), white oats (SCHMIDT et al, 2023) and corn (CARVALHO et al, 2017). This methodology makes it possible to estimate variance components and genetic parameters that indicate the proportion of the phenotype that is determined by the genetic makeup.…”

Section: Port Et Almentioning

confidence: 99%

Early selection of resilient progenies to seed yield in soybean populations

Port,

Carvalho,

Pradebon

et al. 2024

Cienc. Rural

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This study carried out early selection of soybean progenies that are productive and resilient to environmental conditions. The experiment took place at the Genetic Breeding Program of UNIJUI (University of the Northwest of the State of Rio Grande do Sul), located in Ijuí - RS, Brazil. The experiment used augmented blocks design with interim checks. The regular treatments correspond to 24 soybean F2 populations and the common treatments were 18 commercial checks, arranged in four replications. At full physiological maturity, in each experimental unit, five plants were randomly collected to obtain seed weight per plant (SWP, g). The Jinks and Pooni methodology was used to calculate the probability of extracting superior lineages from the evaluated populations. The best control and promising cultivars to compose the parent bank are BMX FORÇA RR, FUNDACEP 66 RR and TMG 7062 IPRO. Jinks and Pooni’s methodology identified populations IRC001, IRC002, IRC017, IRC019, IRC028, IRC030, IRC032, IRC033, IRC035, IRC036, IRC039 and IRC040 as having high potential for extraction of superior lineages.

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Section: Port Et Almentioning

confidence: 99%

Early selection of resilient progenies to seed yield in soybean populations

Port,

Carvalho,

Pradebon

et al. 2024

Cienc. Rural

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“…Most plant breeders use classical stability indexes like deviation from regression, regression, and mean to select the most stable genotype [56,57]. However, these statistical tools are insufficient to detect the weaknesses and strengths of genotypes and to select individuals with desired average performance and stability [58]. The MGIDI is a sophisticated quantitative genetic technique used to exploit desired accessions in all crop species [59] and is free from multi-collinearity problems [60].…”

Section: Treatment Combination and Genotypes Selection Using The Mgidimentioning

confidence: 99%

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

et al. 2023

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Climate change has affected the food supply chain and raised serious food concerns for humans and animals worldwide. The present investigation aimed to assess the effect of environmental factors along with three different levels of cutting (i.e., cutting 1, 2, and 3 at the vegetative, budding, and flowering stages, respectively) and spacing (i.e., 21, 23, and 26 cm) on quinoa biomass and quality to select the most suitable accessions. This experiment was repeated for two years using a split–split plot experimental design. The cutting × genotype × year and cutting × space × genotype interactions were significant for most quinoa morphological traits (except for leaf area and intermodal distance), where the maximum growth in number of leaves/plant (NoL), plant height (PH), fresh weight (FW), number of branches/plant (Br), and dry weight (DW) were observed during the second growing season. Cutting and spacing levels also showed significant effects on morphological and quality traits of quinoa. Among the different levels of cutting and spacing, cutting level 3 and spacing level 2 were more effective across both years at gaining maximum biomass and quality traits such as crude fat (CF) and crude protein (CP). According to the MGIDI, only two accessions (R3 and R9) fared better in both growing seasons, and selected accessions had positive morphological and quality traits. There were moderately significant negative correlations between PH, NoL, LA, FW, and DW and anti-quality traits such as neutral detergent fiber (NDF) and acid detergent fiber (ADF), indicating that an increase in biomass decreased the concentrations of ADF and NDF in both stem and leaves. A comparison with oat accessions (G3 and G7) revealed that quinoa has higher CP and CF and lower NDF than oats in both stems and leaves (except for ADF). In conclusion, the combination of cutting level 3 and spacing level 2 (23 cm) is more suitable to obtain high-quality quinoa forage with maximum biomass production. Furthermore, the MGIDI is a useful tool for breeders to select genotypes based on their mean performance, stability, and desired traits.

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“…Wheat (Triticum aestivum L.) is widely used in human food and has important functional properties in its grains (LORO et al, 2023). Developing and selecting superior genotypes has been efficient in increasing the nutritional quality of grains (SZARESKI et al, 2019;SEGATTO et al, 2022;SEGATTO et al, 2023) and production performance (SILVA et al, 2015), in order to meet the demand for wheat grains.…”

Section: Introductionmentioning

confidence: 99%

Partial correlations between production traits and grain protein in wheat

Trivisiol,

Cargnelutti Filho,

Facco

et al. 2024

Rev. Caatinga

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The objective of this study was to check whether there are linear relations between production traits and grain protein in early-, medium- and late-cycle wheat. Data from 204 competition trials of wheat genotypes conducted in the states of Rio Grande do Sul and Paraná were used, 78 trials with early-cycle, 34 with medium -cycle and 92 with late-cycle genotypes. The trials were conducted in a randomized block design, with 149 early-cycle, 95 medium-cycle and 193 late-cycle genotypes being evaluated from 2015 to 2019. Three production traits (grain yield, in kg ha-1, thousand-grain weight, in g, and hectoliter weight, in kg hL-1) and grain protein, in %, were evaluated. Scatter plots were created and the partial correlation coefficients between these four traits were calculated, based on 4330, 2497 and 4714 observations, referring to the early, medium and late cycles, respectively. There are linear relations between production traits and grain protein in early-, medium- and late-cycle wheat. Early- and late-cycle wheat genotypes show a negative correlation between grain yield and grain protein. Medium-cycle wheat genotypes show no correlation between grain yield and grain protein. Selection of wheat genotypes with higher grain yield and hectoliter weight can be carried out indirectly by means of thousand-grain weight.

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Wheat grain biofortification for essential amino acids

Cited by 5 publications

References 37 publications

Early selection of resilient progenies to seed yield in soybean populations

Early selection of resilient progenies to seed yield in soybean populations

Multi-Trait Selection of Quinoa Ideotypes at Different Levels of Cutting and Spacing

Partial correlations between production traits and grain protein in wheat

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