Multi-attribute responses of maize inbred lines across managed environments

D'andrea, Karina Elizabeth; Otegui, Marı́a Elena; Vega, Abelardo J. de la

doi:10.1007/s10681-007-9567-3

Cited by 18 publications

(10 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For modern varieties of the most intensively-cultivated grain crops, including rice19, wheat20, barley ( Hordeum vulgare )21, and maize22, HI values range from 0.4 to 0.6323. Genetic and agronomic improvements have greatly increased the yield potential of Glycine max (soybean), which is associated with an increase in HI from around 0.35 to 0.533.…”

Section: Discussionmentioning

confidence: 99%

A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus

Xiao

Jian

et al. 2016

Sci Rep

View full text Add to dashboard Cite

Harvest index (HI), the ratio of seed mass to total biomass of the aboveground plant parts, is an important trait for harvestable yield of crops. Unfortunately, HI of Brassica napus is lower than that of other economically important crops. To identify candidate genes associated with high HI, a genome-wide association study of HI and four HI-related traits was conducted with 520 B. napus accessions cultivated in both Yunnan and Chongqing. We detected 294 single nucleotide polymorphisms significantly associated with the abovementioned traits, including 79 SNPs that affected two or more traits. Differentially expressed genes between extremely high- and low-HI accessions were identified in 8 tissues at two cultivated regions. Combination of linkage disequilibrium and transcriptome analyses revealed 33 functional candidate genes located within the confidence intervals of significant SNPs associated with more than one trait, such as SHOOT GRAVITROPISM 5 (Bna.SGR5), ATP-CITRATE LYASE A-3 (Bna.ACLA-3) and CAROTENOID CLEAVAGE DIOXYGENASE 1 (Bna.CCD1), their orthologs in the Arabidopsis thaliana have been shown to play key roles in photosynthesis, inflorescence, and silique development. Our results provide insight into the molecular mechanisms underlying establishment of high-HI B. napus and lay a foundation for characterization of candidate genes aimed at developing high-HI B. napus varieties.

show abstract

Section: Discussionmentioning

confidence: 99%

A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus

Xiao

Jian

et al. 2016

Sci Rep

View full text Add to dashboard Cite

show abstract

“…[3]). The phenotypic observation of measured trait Y ijk on genotype i in replicate k of environment j was modeled as follows (D'Andrea et al, 2008):

Y_{i j k} = μ {+ G}_{i} {+ E}_{j} {+ (R/E)}_{j k} {+ (GE)}_{i j} + ε_{i j k}

where μ is the general mean, G is the effect of the i th genotype, E is the effect of the j th experiment (environment), R is the effect of the k th replicate nested in the environment, GE is the G × E interaction effect, and ε is the residual error. Genotype and G × E interaction effects were treated as random, while E and R effects were treated as fixed (Alvarez Prado et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

Contribution of Reserves to Kernel Weight and Grain Yield Determination in Maize: Phenotypic and Genotypic Variation

et al. 2016

View full text Add to dashboard Cite

Maize (Zea mays L.) kernel weight (KW) and grain yield depend on plant growth during active grain filling and reserves use. The objective of our study was to analyze the phenotypic and genotypic variation in these traits in a family of recombinant inbred lines (RIL). In two field experiments we measured plant grain yield (PGY) and its components (KW and kernel number per plant, KNP), biomass production per plant and per kernel during active grain filling, and apparent reserves use (ARU) per plant (ARUP, difference between PGY and plant biomass production during active grain filling) and per kernel (ARUK, difference between KW and plant biomass production per kernel during active grain filling). Heritability (h2) and phenotypic plasticity were computed for all traits. Large differences were always evident among genotypes, but phenotypic plasticity was (i) low for KW and plant biomass at R2 and physiological maturity; (ii) intermediate for KNP and PGY; and (iii) high for plant growth, plant growth per kernel after R2, and ARUs. Traits with highest h2 were KW (0.70), KNP (0.61), and ARUP (0.59). Final KW was related to plant growth per kernel (r2 = 0.64; P < 0.001) but not to ARUK, and ARUP was driven (r2 ≥ 0.49; P < 0.001) by KNP. Because of its positive relationship with KNP (main determinant of PGY), high h2 and high phenotypic plasticity, breeding must consider the increase in ARUP for improving grain yield, an objective that needs to be coupled with large reserves accumulation before silking to avoid the risk of lodging.

show abstract

“…In general, to obtain a correct assessment in an integrated descriptive study, the appropriate method should take several variables into account together (D'Andrea et al, 2008). This approach is especially valuable in observational studies, in which total control is never possible (White, 1993).…”

Section: Multivariate Analysismentioning

confidence: 99%

Univariate and multivariate analysis on processing tomato quality under different mulches

Moreno

Mancebo

Tarquis

et al. 2014

Sci. agric. (Piracicaba, Braz.)

View full text Add to dashboard Cite

The use of eco-friendly mulch materials as alternatives to the standard polyethylene (PE) has become increasingly prevalent worldwide. Consequently, a comparison of mulch materials from different origins is necessary to evaluate their feasibility. Several researchers have compared the effects of mulch materials on each crop variable through univariate analysis (ANOVA).However, it is important to focus on the effect of these materials on fruit quality, because this factor decisively infl uences the acceptance of the fi nal product by consumers and the industrial sector. This study aimed to analyze the information supplied by a randomized complete block experiment combined over two seasons, a principal component analysis (PCA) and a cluster analysis (CA) when studying the effects of mulch materials on the quality of processing tomato (Lycopersicon esculentum Mill.). The study focused on the variability in the quality measurements and on the determination of mulch materials with a similar response to them. A comparison of the results from both types of analysis yielded complementary information. ANOVA showed the similarity of certain materials. However, considering the totality of the variables analyzed, the fi nal interpretation was slightly complicated. PCA indicated that the juice color, the fruit fi rmness and the soluble solid content were the most infl uential factors in the total variability of a set of 12 juice and fruit variables, and CA allowed us to establish four categories of treatment: plastics (polyethylene -PE, oxo-and biodegradable materials), papers, manual weeding and barley (Hordeum vulgare L.) straw. Oxobiodegradable and PE were most closely related based on CA.

show abstract

Multi-attribute responses of maize inbred lines across managed environments

Cited by 18 publications

References 44 publications

A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus

A combination of genome-wide association and transcriptome analysis reveals candidate genes controlling harvest index-related traits in Brassica napus

Contribution of Reserves to Kernel Weight and Grain Yield Determination in Maize: Phenotypic and Genotypic Variation

Univariate and multivariate analysis on processing tomato quality under different mulches

Contact Info

Product

Resources

About