ICP-OES Determination of Elements in Dorema Aucheri and Suaeda Maritima

Farhadiannezhad, Masumeh; Malaekeh, Seyed Mohammad Ali; Mojaddami, Ayyub; Abbasi, Samaneh; Noorizadeh, Najaf; Chamkouri, Narges

doi:10.5958/0973-9130.2019.00250.0

Cited by 2 publications

(2 citation statements)

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“…Wheat grain yield is determined by the integration of many characteristics that affect plant growth throughout the growing period, and each characteristic changes to a different extent and direction under the effect of environmental factors (SadeghGolMoghadam et al, 2011;Rymuza et al, 2012;Farhadiannezhad et al, 2019). Therefore, toward a clear understanding of the type of plant traits, correlation and path coefficient analysis are logical steps (Kashif & Khaliq, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Indirect selection through traits related to grain yield is among the most important strategies in wheat breeding (Garcia Del Moral et al, 2003). Due to the significant and positive correlation of wheat grain yield with traits such as plant height, spikelets per spike, and spike length, these traits can be used as indirect selection criteria for grain yield improvement (Ohja et al, 2018;Devesh et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Correlation and path coefficient analyses of phenological traits, yield components and quality traits in wheat

Semnaninejad

Ghorban

Rameeh

et al. 2021

Rev. bras. eng. agríc. ambient.

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This study was conducted to characterize the phenological traits, yield components and quality traits affecting wheat grain yield. Three wheat genotypes were evaluated during three planting dates (November 20, December 5, and December 20) and at four seeding densities 300, 350, 400 and 450 seeds per m2 for two years. Multivariate analyses were conducted based on the interaction effects of planting date and seeding density (PS), planting date and genotype (PG) and seeding density and genotype (SG) mean values. The results of correlation analysis showed that grain yield was significantly and positively correlated with biomass yield (0.91**), days to spiking (0.81**), days to anthesis (0.83**), and days to maturity (0.57*) for PS; with biomass yield (0.94**), days to spiking (0.87**), days to anthesis (0.75*), and harvest index (0.83**) for PG; with gluten index (0.73**), harvest index (0.68*), and 1000-grain weight for SG. Path analysis revealed that biomass yield for PS and PG, harvest index for PG and SG, and gluten index for SG exhibited the highest positive direct effect. Stepwise regression analysis also revealed important effect of biomass yield, harvest index, and days to maturity for improving grain yield in different agronomical conditions.

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Section: Introductionmentioning

confidence: 99%