Genotype by environment interactions for seed yield and oil content in sunflower (H. annuus L.) using AMMI model

Marinković, Radovan; Jocković, Milan; Marjanović-Jeromela, Ana; Jocić, Siniša; Ćirić, Mihajlo; Balalić, Igor; Sakač, Zvonimir

doi:10.2298/hel1154079m

Cited by 10 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…G × E interactions correspond to significant changes in the relative performance of the genotypes when they are evaluated in different environments. Such interactions could be substantial in sunflower crop as their contribution to total yield variance may range from 5 to 20 % (far less than the E contribution but generally more than the G contribution) (de la Vega et al, 2001;Foucteau et al, 2001;Marinković et al, 2011). Large and regional G × E interactions complicate selection for broad adaptation (de la Vega, 2012) but identifying specifically adapted genotypes could be promoted in advisory systems to optimize locally the variety choice (Jeuffroy et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

A model-based approach to assist variety evaluation in sunflower crop

Casadebaig

Mestries

Debaeke

2016

European Journal of Agronomy

View full text Add to dashboard Cite

Assessing the performance and the characteristics (e.g. yield, quality, disease resistance, abiotic stress tolerance) of new varieties is a key component of crop performance improvement. However, the variety testing process is presently exclusively based on experimental field approaches which inherently reduces the number and the diversity of experienced combinations of varieties x environmental conditions in regard of the multiplicity of growing conditions within the cultivation area. Our aim is to make a greater and faster use of the information issuing from these trials using crop modeling and simulation to amplify the environmental and agronomic conditions in which the new varieties are tested. In this study, we present a model-based approach to assist variety testing and implement this approach on sunflower crop, using the SUNFLO simulation model and a subset of 80 trials from a large multi-environment trial (MET) conducted each year by agricultural extension services to compare newly released sunflower hybrids. After estimating parameter values (using plant phenotyping) to account for new genetic material, we independently evaluated the model prediction capacity on the MET (model accuracy was 54.4 %) and its capacity to rank commercial hybrids for performance level (Kendall's $\tau$ = 0.41, P < 0.01). We then designed a numerical experiment by combining the previously tested genetic and new cropping conditions (2100 virtual trials) to determine the best varieties and related management in representative French production regions. We suggest that this approach could find operational outcomes to recommend varieties according to environment types. Such spatial management of genetic resources could potentially improve crop performance by reducing the genotype-phenotype mismatch in farming environments.Comment: 25 pages, 10 figure

show abstract

Section: Introductionmentioning

confidence: 99%

A model-based approach to assist variety evaluation in sunflower crop

Casadebaig

Mestries

Debaeke

2016

European Journal of Agronomy

View full text Add to dashboard Cite

show abstract

“…Previously in sun ower, Genotype × Environment interaction studies were carried out majorly through AMMI (Marinković et al, 2011;Khomari et al, 2017) and GGE (Genotype main effect (G) plus genotype by environment interaction (GE)) biplot analysis (Pourdad et al, 2013;Ansarifard et al, 2020;Shojaei et al, 2022). The weighted average of absolute scores (WAASB) stability index, a best linear unbiased prediction-based mixed model that takes in to account all the IPCAs, has been used in stability analysis.…”

Section: Duscussionmentioning

confidence: 99%

WAASB-based stability analysis and validation of sources resistant to Plasmopara halstedii race-100 from the sunflower working germplasm for the semiarid regions of India

Dudhe

Jadhav

Sujatha

et al. 2023

Genet Resour Crop Evol

View full text Add to dashboard Cite

In sun ower, stable performance in a semi-arid region is an essential factor for obtaining high and stable seed as well as oil yield. Therefore, efforts were made to evaluate 28 sun ower genotypes including USDA, USA, France collection and germplasm maintained at ICAR-IIOR, Hyderabad under four semi-arid locations of India during 2021-2022. Screening of the selected genotypes for Sun ower Downy Mildew (SDM) which is important disease and cause losses upto 100% incited by Plasmopara halstedii race-100 in India was undertaken during previous years (2017-20) and validation experiment was conducted during 2021. WAASB (Weighted Average of Absolute Scores) and Multi-Trait Stability Index (MTSI) adopted for stability analysis. The analysis of variance from AMMI showed highly signi cant effects of the climate, genotypes, and their interaction. Only 56.13% which is lesser than 60% of total GEI variation was explained by rst two PCs indicating the complexity of GEI and suitability of WAASB statistics. Based on WAASB study most stable genotypes identi ed for yield were GMU-494, LTRR-341, EC-601901 and GMU-481and GMU-494 for oil content. Based on WAASBY scores most stable genotype identi ed for yield were GMU-770 (96.76) and EC-178168-2 (96.53) and for oil content , EC-601901(91.30). Simultaneous selection index MTSI has been employed for selecting high yielding genotypes with medium to high oil content. MTSI index identi ed ideal genotype EC-198078 which is closer to hypothetical ideotype with least MTSI index coupled with high WAASBY score and resistant reaction to SDM. Population structure based on 20 SSR markers depicted the change of Delta (k) value (k = 4) which suggests the four populations within the collection of 28 sun ower germplasm accessions. Based on multiple year screening we have identi ed and validated 10 resistance sources and three new sources of resistance to SDM for semi-arid region. Identi ed stable genotypes coupled with SDM resistance could be useful for the development of inbreds or can be used to develop superior populations in sun ower.

show abstract

“…Such relationships between the cultivation environment and fatty acids composition have not been reported previously for noug. However, the genotype and environment, as well as their interactions, are well known to influence most components in plants [37,38], and the effects on the content of total lipids and fatty acids have been previously reported, e.g., in sunflower (Helianthus annuus L.), which is the closest crop to noug [39][40][41].…”

Section: Quantity and Quality Of Lipidsmentioning

confidence: 99%

Nutritional Profile of the Ethiopian Oilseed Crop Noug (Guizotia abyssinica Cass.): Opportunities for Its Improvement as a Source for Human Nutrition

Tsehay

Ortíz

Geleta

et al. 2021

Foods

View full text Add to dashboard Cite

The aim of this study was to evaluate the potential of noug as a source for human nutrition. Diverse noug genotypes were evaluated for their content and/or composition of total lipids, fatty acids, proteins, and minerals using standard methods. The total lipid content (32.5–45.7%) and the proportion of an essential fatty acid, linoleic acid (72.2–77.8%), were high in noug, compared to other oilseed crops. The proportion of oleic acid, a monounsaturated fatty acid, was low in noug (5.2–9.2%). The breeding objective of increasing the oleic acid level in the highland, where noug is mainly cultivated, was limited, as the content of this acid was low in this environment. The seed protein concentration (25.4–27.5%) and mineral content were mainly affected by the cultivation environment, as the high temperature increased the amount of protein, whereas the soil condition was a major factor in the variation of the mineral content. Thus, noug is a unique crop with a high seed oil content, of which a high proportion is linoleic acid. With the exception of the seed oleic acid content, when grown in low-altitude areas, the genotypic variation contributes less than the cultivation environment to the nutritional attributes of noug. Hence, high-oleic-acid noug for lowland production can be targeted as a breeding goal.

show abstract

Genotype by environment interactions for seed yield and oil content in sunflower (H. annuus L.) using AMMI model

Cited by 10 publications

References 5 publications

A model-based approach to assist variety evaluation in sunflower crop

A model-based approach to assist variety evaluation in sunflower crop

WAASB-based stability analysis and validation of sources resistant to Plasmopara halstedii race-100 from the sunflower working germplasm for the semiarid regions of India

Nutritional Profile of the Ethiopian Oilseed Crop Noug (Guizotia abyssinica Cass.): Opportunities for Its Improvement as a Source for Human Nutrition

Contact Info

Product

Resources

About