Grain quality in the Broadbalk Wheat Experiment and the winter North Atlantic Oscillation

Atkinson, Mark; Kettlewell, P. S.; Poulton, P. R.; Hollins, P. D.

doi:10.1017/s0021859608007958

Cited by 35 publications

(20 citation statements)

References 26 publications

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“…Selection of suitable parents with desirable traits and making crosses among them is an important way for increased production . Local cultivars were survived from past years until now, expected to contribute in new practices of agriculture and eff ects of climate changes which have adverse impacts on production, quality and security of human foods (Parry et al, 2004;Atkinson et al, 2008). Unless, local cultivars are not known by high grain yield, adaptability is their benefi ts for direct use by farmers or as potential plant materials in breeding programs.…”

Section: Introductionmentioning

confidence: 99%

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Janmohammadi¹,

Sabaghnia²,

Nouraein³

2014

Acta Univ. Agric. Silvic. Mendelianae Brun.

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Development of new bread wheat cultivars needs effi cient tools to monitor trait association in a breeding program. This investigation was aimed to characterize grain yield components and some agronomic traits related to bread wheat grain yield. The effi ciency of a breeding program depends mainly on the direction of the correlation between diff erent traits and the relative importance of each component involved in contributing to grain yield. Correlation and path analysis were carried out in 56 bread wheat genotypes grown under fi eld conditions of Maragheh, Iran. Observations were recorded on 18 wheat traits and correlation coeffi cient analysis revealed grain yield was positively correlated with stem diameter, spike length, fl oret number, spikelet number, grain diameter, grain length and 1000 seed weight traits. According to the variance infl ation factor (VIF) and tolerance as multicollinearity statistics, there are inconsistent relationships among the variables and all traits could be considered as fi rst-order variables (Model I) with grain yield as the response variable due to low multicollinearity of all measured traits. In the path coeffi cient analysis, grain yield represented the dependent variable and the spikelet number and 1000 seed weight traits were the independent ones. Our results indicated that the number of spikelets per spikes and leaf width and 1000 seed weight traits followed by the grain length, grain diameter and grain number per spike were the traits related to higher grain yield. The above mentioned traits along with their indirect causal factors should be considered simultaneously as an eff ective selection criteria evolving high yielding genotype because of their direct positive contribution to grain yield.

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Section: Introductionmentioning

confidence: 99%

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Janmohammadi¹,

Sabaghnia²,

Nouraein³

2014

Acta Univ. Agric. Silvic. Mendelianae Brun.

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“…Local varieties and landraces were survived from ancient years until now, expected to contribute in new practices of agriculture (sustainable or organic farming) and effects of climate changes which have adverse impacts on food production [1], food quality [2] and food security [3]. Also, the high protein content of wheat grain makes it important source of human nutrition and social economy.…”

Section: Introductionmentioning

confidence: 99%

Multienvironmental evaluation of wheat landraces by GGE Biplot Analysis for organic breeding

Koutis¹,

Mavromatis²,

Baxevanos³

et al. 2012

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This study was conducted to determine the performance of wheat landraces cultivated under organic conditions and to analyze their stability across diverse environments. Six wheat landraces with specific characteristics (high protein content, drought tolerance, stay green) were tested under organic growing environment. The experiments were applied in three locations (Larisa (LAR), Thessaloniki (THES), Kilkis (KIL)) for three growing seasons. The role of specific agronomic traits (stay green, lodging) and their correlation with yield components were analyzed. Stability and genotypic superiority for grain yield were determined using ANOVA and genotype × environment (GGE) biplot analysis. Furthermore, the interrelationships among wheat traits and genotype-by-trait using regression analysis, coefficient of variation and (GT)-biplot technique were studied. Significant differences were found in yield among wheat landraces tested, and also in yield components, as related to specific traits expressed into organic environment. Best varieties in terms of yield were Skliropetra and M. Argolidas, characterized by lowest weight of 1000 grains, large number of spikes per m 2 meter and the highest number of grains per spike as compared to the other landraces. The statistical model GGE biplot provides useful information for experimentation of wheat landraces when grown under organic environment. It identifies clearly the ideal and representative environment for experimentation and underlines the effect of specific traits for each wheat cultivar on yield performance and stability across environments.

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“…Many studies have demonstrated a relationship between wheat grain quality (Hagber falling number, specific weight and protein concentration) in the UK and the winter NAO (Kettlewell et al 1999;Wanner et al 2001;Hurrell et al 2003;Atkinson et al 2005Atkinson et al , 2008. According to Kettlewell et al (2003) the winter NAO has an effect on cumulative precipitation in summer in England and Wales and, consequently, on wheat quality, while Colman (1997) suggested an association between SST and NAO in the UK.…”

Section: Introductionmentioning

confidence: 99%

The influence of climate on durum wheat quality in Tuscany, Central Italy

et al. 2010

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Climate and meteorological conditions greatly affect agricultural activities, modifying plant responses and determining the quantity and the quality of production. In this respect, the aim of this research was to analyze the quality of winter durum wheat (Triticum turgidum L. var. durum), in terms of protein content through the use of meteorological information. Meteorological conditions were described utilizing both local weather station data (air temperature, cumulated precipitation) and large-scale information available freely on the internet, such as geopotential height (GPH), sea surface temperature (SST), and the North Atlantic Oscillation (NAO) index. The analysis was carried out for the period 1997-2009 in the Tuscany region, Central Italy. Grain protein was positively correlated with air temperature during the February to June period, and negatively with cumulative precipitation during the entire period from November to June. Protein content was also negatively correlated with 500 hPa GPH over Gibraltar and North-Western Africa during the March to June period and with the SST of the Atlantic Ocean south-west of the Canary Islands during the January to June period. Finally, with regard to the NAO, winter durum wheat quality was positively correlated with the specific index for several months, in particular during the winter period. These results demonstrate that precipitation and air temperature over the production area represent two crucial variables driving the vegeto-productive responses of winter durum wheat. On the other hand, the use of large-scale meteorological information showed great potential from the perspective of a local quality forecast system setup.

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Grain quality in the Broadbalk Wheat Experiment and the winter North Atlantic Oscillation

Cited by 35 publications

References 26 publications

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Path Analysis of Grain Yield and Yield Components and Some Agronomic Traits in Bread Wheat

Multienvironmental evaluation of wheat landraces by GGE Biplot Analysis for organic breeding

The influence of climate on durum wheat quality in Tuscany, Central Italy

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