Interpretation of hybrid×sowing date interaction for oil content and oil yield in sunflower

Balalić, Igor; Zorić, Miroslav; Branković, Gordana; Terzić, S.; Crnobarać, Jovan

doi:10.1016/j.fcr.2012.08.005

Cited by 40 publications

(27 citation statements)

References 36 publications

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“…Moreover, solid planting of flax had higher seed oil content than those of intercropping culture. It is apparent that solid planting formed normal environmental conditions for flax growth and development and thereby flax plant maximized the use of natural resources during critical periods of oil yield and its components with the moment of the growth season where more ecological resources are available (Balalic et al, 2012). …”

Section: Effect Of Cropping Systemmentioning

confidence: 99%

Effect of Ridge Width and Cropping System on Productivity and Land Use Efficiency in Faba Bean-Flax Intercrops

Safina

2017

Egypt. J. Agron.

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IntroductionThe rising regard on sustainable agriculture enhances the cultivation of legumes as a tool of environmental optimization of resource use and preferment of pest pliability in cropping systems. It is known that weeds compete with crop plants for light, nutrients, soil moisture and space. Broomrape weed (Orobanche spp.) is root holoparasites that feed off a wide range of the most important legume crops. Furthermore, broomrape seeds to keep you can repeat vital good for 20 years or more in the nonattendance of the host plant (Kebreab & Murdoch, 1999). They act by attaching themselves to the roots of many plant species to obtain nutrients and water from their host. It is known that Orobanche crenata is a main necessity for grain and forage legume on over four Mha of the Mediterranean area (Parker, 2009). Egypt at present satisfies around 70% of its request out of incoming as a result of the effects of competition with other crops, and parasites such as Orobanche (ICARDA, 2017). TWO FIELD experiments were conducted at the Agricultural Experimental Station, Faculty of Agriculture, Cairo University, Giza, Egypt during 2014/2015 and 2015/2016 seasons. The study to investigate the performance of two faba bean varieties, i.e. Giza-843 and Giza-2 when intercropped with flax to productivity, land use efficiency, farmer's benefit and control broomrape in faba bean fields under two ridge widths. The experiment included 8 treatments which were the combination of two ridge widths (60 and 120 cm), two cropping systems (intercropping and solid planting) and two faba bean varieties (Giza-2 and Giza-843). The experimental design was a split-split plot design in randomized complete block arrangement with three replications. The results indicated that increasing ridge width from 60 to 120 cm decreased number of Orobanche crenata m -2 but it increased seed yield of the intercrops plant -1 and ha -1 . Intercropping flax with faba bean decreased number of Orobanche crenata -2 and seed yield plant -1 and ha -1 of both intercrop components. Faba bean cv. Giza-843 recorded the lowest values of number of Orobanche crenata m -2 and the highest values of yield and its attributes compared to Giza-2 variety. Also, faba bean cv. Giza-843 affected negatively seed yield of flax and its attributes. Most of the studied faba bean and flax traits were affected significantly by the interactions. The amount of fatty acids in flax seed was approximately 12.5 to 14.5% saturated (8.3 to 9.2% of palmitic acid and 4.2 to 5.3% of stearic acid) and 81.7 % to 85.2 % unsaturated fatty acids (20.9 to 22.3% of oleic acid, 13.0 to 14.2 % of ώ6 and 47.8 to 48.7% of ώ3). Total unsaturated fatty acids were not affected significantly by ridge width x cropping system x faba bean variety. Land equivalent ratio (LER) ranged from 1.63 for intercropping flax with Giza-2 variety in ridges 60 cm width to 1.86 for intercropping flax with Giza-843 variety in ridges 120 cm width. Land equivalent coefficient (LEC) exceeded 0.25. The dominance analysis proved that faba ...

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Section: Effect Of Cropping Systemmentioning

confidence: 99%

Effect of Ridge Width and Cropping System on Productivity and Land Use Efficiency in Faba Bean-Flax Intercrops

Safina

2017

Egypt. J. Agron.

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“…Biplot analysis was first developed by Gabriel (1971), and it can interpret multiple variables in function of different treatments in the same graphic (Akinwale et al, 2014). GGE biplot has been used to show the performance of sunflower hybrids in different testing environments or sowing dates (Ullah et al, 2007;Balalic et al, 2012;Brankovic et al, 2012). A GGE biplot is used to analyze multi-year data of variety trials, where genotypes vary from year to year, treating each year-location as an environment (Yan, 2014).…”

Section: Introductionmentioning

confidence: 99%

Grouping sunflower genotypes for yield, oil content, and reaction to Alternaria leaf spot using GGE biplot

Leite

Oliveira

2015

Pesq. agropec. bras.

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-The objective of this work was to evaluate the suitability of the multivariate method of principal component analysis (PCA) using the GGE biplot software for grouping sunflower genotypes for their reaction to Alternaria leaf spot disease (Alternariaster helianthi), and for their yield and oil content. Sixty-nine genotypes were evaluated for disease severity in the field, at the R3 growth stage, in seven growing seasons, in Londrina, in the state of Paraná, Brazil, using a diagrammatic scale developed for this disease. Yield and oil content were also evaluated. Data were standardized using the software Statistica, and GGE biplot was used for PCA and graphical display of data. The first two principal components explained 77.9% of the total variation. According to the polygonal biplot using the first two principal components and three response variables, the genotypes were divided into seven sectors. Genotypes located on sectors 1 and 2 showed high yield and high oil content, respectively, and those located on sector 7 showed tolerance to the disease and high yield, despite the high disease severity. The principal component analysis using GGE biplot is an efficient method for grouping sunflower genotypes based on the studied variables.Index terms: Alternariaster helianthi, Helianthus annuus, disease resistance, principal component analysis. Agrupamento de genótipos de girassol quanto à produtividade, ao teor de óleo e à reação à mancha de alternária por GGE biplotResumo -O objetivo deste trabalho foi avaliar a adequação do uso do método multivariado de análise de componentes principais (ACP), com uso do programa GGE biplot, para o agrupamento de genótipos de girassol quanto à sua reação à mancha de alternária (Alternariaster helianthi), e quanto à produtividade e ao teor de óleo. Sessenta e nove genótipos foram avaliados quanto à severidade da doença em campo, na fase de desenvolvimento R3, em sete safras, em Londrina, PR, com uso de uma escala diagramática própria, desenvolvida para esta doença. A produtividade e o teor de óleo também foram avaliados. Os dados foram padronizados com o programa Statistica, e o GGE biplot foi utilizado para ACP e exibição gráfica dos dados. Os dois primeiros componentes principais explicaram 77,9% da variação total. De acordo com o biplot poligonal, obtido com os dois primeiros componentes principais e as três variáveis resposta, os genótipos foram divididos em sete setores. Os genótipos alocados nos setores 1 e 2 apresentaram alta produtividade e alto teor de óleo, respectivamente, e os agrupados no setor 7 apresentaram tolerância à doença e alta produtividade, apesar de elevada severidade da doença. O método de análise de componentes principais com uso do GGE biplot é eficiente para agrupar genótipos de girassol com base nas variáveis estudadas.Termos para indexação: Alternariaster helianthi, Helianthus annuus, resistência a doenças, análise de componentes principais.

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“…They indicate that cultivars planted in later periods are more likely to flower in drought stress periods, penalizing the number of grains per head and grain filling cycle duration (Foucteau et al, 2001). In a more recent study, Balalić et al (2012) identified that the level of rainfall and relative humidity at flowering time were the most important factors in the presence of GEI for a particular year of evaluation. On the other hand, for the remaining years the high levels of precipitation in the vegetative phase generated significant decreases in grain yield and oil concentration.…”

Section: Agronomic and Climatic Factorsmentioning

confidence: 99%

Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency

González-Barrios¹,

Castro²,

Pérez³

et al. 2018

Span. j. agric. res.

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Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars.Additional keywords: genotype by environment interaction; multi-environment trials; sunflower; network efficiency; yield stability. Abbreviations used: CPD (critical percentage difference); GEI (genotype by environment interaction); GGE (genotype plus genotype by environment); LE (La Estanzuela); MET (multi-environment trial); NENSU (National evaluation network of sunflower cultivars of Uruguay); PLS (partial least squares); RCBD (randomized complete block design); YG (Young).

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Interpretation of hybrid×sowing date interaction for oil content and oil yield in sunflower

Cited by 40 publications

References 36 publications

Effect of Ridge Width and Cropping System on Productivity and Land Use Efficiency in Faba Bean-Flax Intercrops

Effect of Ridge Width and Cropping System on Productivity and Land Use Efficiency in Faba Bean-Flax Intercrops

Grouping sunflower genotypes for yield, oil content, and reaction to Alternaria leaf spot using GGE biplot

Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency

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