Published

2025-09-01

Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria

Selección de múltiples características de genotipos de trigo harinero (Triticum aestivum L.) bajo condiciones semiáridas en Argelia

DOI:

https://doi.org/10.15446/rfnam.v78n3.117143

Keywords:

Agronomic traits, ANOVA, Correlation, LSI, MGIDI, Wheat (en)
Características agronómicas, ANOVA, Correlación, LSI, MGIDI, Trigo (es)

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The selection of high-yielding bread wheat (Triticum aestivum L.) genotypes with superior agronomic traits is critical for improving productivity in semi-arid regions like Algeria. To address national reliance on wheat imports and enhance local production, a preliminary yield trial was conducted in Constantine (36°16′ N, 6°40′ E) during the 2018–2019 cropping season. A total of 112 bread wheat genotypes, including local and international entries and five local checks, were evaluated using an augmented design with four blocks. Significant variability was detected among genotypes and checks for most traits, confirming the presence of exploitable genetic diversity. Phenotypic correlations showed that grain yield was positively associated with spike density (r=0.463) and thousand-kernel weight (r=0.557), while it was negatively correlated with days to heading (r=-0.293), indicating the advantage of early heading under drought conditions. Using the Least Significant Increase (LSI) method, genotypes G29, G38, and G9 were found to be significantly earlier than several local checks, while G65 outperformed at least one check across all traits. In parallel, the Multi-Trait Genotype-Ideotype Distance Index (MGIDI) enabled the identification of 17 high-performing genotypes such as G60, G41, G65, and G111 alongside two superior local checks (C3 and C4). These genotypes combine favorable traits and are promising candidates for inclusion in breeding programs targeting yield stability and stress resilience. Overall, the study provides valuable insights into trait associations and highlights elite genetic materials suitable for advancing wheat improvement efforts in challenging semi-arid environments.

La selección de genotipos de trigo harinero (Triticum aestivum L.) de alto rendimiento con rasgos agronómicos superiores es fundamental para mejorar la productividad en regiones semiáridas como Argelia. Para reducir la dependencia nacional de las importaciones de trigo y aumentar la producción local, se llevó a cabo un ensayo preliminar de rendimiento en Constantina (36°16′ N, 6°40′ E) durante la temporada agrícola 2018–2019. Se evaluaron un total de 112 genotipos de trigo harinero, incluidos materiales locales e internacionales y cinco testigos locales, utilizando un diseño aumentado con cuatro bloques. Se detectó una variabilidad significativa entre genotipos y testigos para la mayoría de los rasgos, lo que confirma la presencia de diversidad genética aprovechable. Las correlaciones fenotípicas mostraron que el rendimiento en grano se asoció positivamente con la densidad de espigas (r=0,463) y el peso de mil granos (r=0,557), mientras que se correlacionó negativamente con los días hasta el espigado (r=-0,293), lo que indica la ventaja de un espigado temprano en condiciones de sequía. Utilizando el método de Least Significant Increase (LSI), se encontró que los genotipos G29, G38 y G9 fueron significativamente más precoces que varios testigos locales, mientras que G65 superó al menos a un testigo en todos los rasgos. Paralelamente, Multi-trait genotype-ideotype distance index (MGIDI) permitió la identificación de 17 genotipos de alto rendimiento tales como G60, G41, G65 y G111, junto con dos testigos locales superiores (C3 y C4). Estos genotipos combinan características favorables y son candidatos prometedores para ser incluidos en programas de mejora enfocados a la estabilidad del rendimiento y la resiliencia al estrés. En general, el estudio proporciona información valiosa sobre las asociaciones entre rasgos y destaca materiales genéticos élite adecuados para avanzar en los esfuerzos de mejora del trigo en entornos semiáridos desafiantes.

References

Arain SM, Sial MA, Jamali KD and Laghari KA (2018) Grain yield performance, correlation, and cluster analysis in elite bread wheat (Triticum aestivum L.) lines. Acta Agrobotanica 71(4): 1747. https://doi.org/10.5586/aa.1747

Aravind J, Mukesh Sankar S, Wankhede DP and Kaur V (2023) augmentedRCBD: analysis of augmented randomised complete block designs (Version 0.1.5.9000) [R package]. https://aravind-j.github.io/augmentedRCBD/

Bekkis S, Benmehaia AM and Kaci A (2023) Price Transmission in the wheat market in Algeria: Threshold cointegration approach. International Journal of Food and Agricultural Economics 11(1): 17–32. https://ideas.repec.org/a/ags/ijfaec/330862.html

Djoudi MBI, Cheniti K, Guendouz A and Louahdi N (2024) Modeling the grain yield loss and quality assessment of some durum wheat (Triticum durum Desf.) genotypes under semi-arid conditions. Revista Facultad Nacional de Agronomía Medellín 77(1): 10563–10572. https://doi.org/10.15446/rfnam.v77n1.108026

Djuric N, Prodanovic S, Brankovic G, Djekic V, Cvijanovic G et al (2018) Correlation-regression analysis of morphological-production traits of wheat varieties. Romanian Biotechnological Letters 23(2): 13457-13465. https://www.researchgate.net/publication/324824808

Federer WT (1956) Augumented (or Hoonuiaku) design. Hwaaiian Planters Record 55: 191-208.

Federer WT (1961) Augmented designs with one-way elimination of heterogeneity. Biometrics 17(3): 447–473. DOI: https://doi.org/10.2307/2527837

Fellahi Z, Hannachi A, Bouzerzour H and Boutekrabt A (2013) Correlation between traits and path analysis coefficient for grain yield and other quantitative traits in bread wheat under semi-arid conditions. Journal of Agriculture and Sustainability 3 (1): 16–26. https://infinitypress.info/index.php/jas/article/view/96 DOI: https://doi.org/10.1155/2013/201851

Frih B, Oulmi A, Guendouz A and Benkadja S (2022) Evaluation of grain yield performance of seven (Triticum durum Desf.) genotypes grown under semi-arid conditions during two crop seasons in the eastern of Algeria. Agricultural Science and Technology 14(3): 26–31. https://doi.org/10.15547/ast.2022.03.033

Hannachi A and Fellahi Z (2023) Efficiency of index-based selection for potential yield in durum wheat [Triticum turgidum (L.) ssp. turgidum convar. durum (Desf.) Mackey] lines. Italian Journal of Agronomy 18(1): 2182. https://doi.org/10.4081/ija.2023.2182

Hasan FU, Sari S, Zubair A and Carsono N (2020) New promising rice genotypes of SP87-1-1-2 and SP73-3-17 adaptive to lowland and medium land. Planta Tropika 8(1). https://doi.org/10.18196/pt.2020.110.21-32

Khodarahmi M, Soughi H, Shahbazi K, Jafarby J and Khavarinejad MS (2023) Trends in important agronomic traits, grain yield and its components in bread wheat cultivars released in northern warm and humid climate of Iran, 1968–2018. Cereal Research Communications 51(4): 1003-1014. https://doi.org/10.1007/s42976-023-00353-x

Kumar A, Sharma PC, Singh R and Kumari J (2018) Bread wheat germplasm evaluation for soil moisture stress tolerance under rainfed condition. International Journal of Bio-resource and Stress Management 9(6): 754–761. DOI: https://doi.org/10.23910/IJBSM/2018.9.6.1926a

Kumar P, Solanki YPS Singh V and Kiran (2020) Genetic variability and association of morpho physiological traits in bread wheat (Triticum aestivum L.). Current Journal of Applied Science and Technology 39(35): 95-105. https://doi.org/10.9734/cjast/2020/v39i3531059

Lamara A, Fellahi Z, Hannachi A and Benniou R (2022) Assessing the phenotypic variation, heritability and genetic advance in bread wheat (Triticum aestivum L.) candidate lines grown under rainfed semi-arid region of Algeria. Revista Facultad Nacional de Agronomía Medellín 75(3): 10107–10118. https://doi.org/10.15446/rfnam.v75n3.100638

Mamun AA, Islam MM, Adhikary SK and Sultana MS (2022) Resolution of genetic variability and selection of novel genotypes in EMS induced rice mutants based on quantitative traits through MGIDI. International Journal of Agriculture and Biology 28(2): 100–112.

Mustikarini ED, Prayoga GI, Santi R, Yesi and Sari NPE (2023) Potential of Upland Rice Promising Lines in Acid Dry Land at Two Different Seasons. AGRIVITA Journal of Agricultural Science 45(1): 31–37. https://doi.org/10.17503/agrivita.v45i1.3750

Olivoto T and Lúcio AD (2020) metan: An R package for multi‐ environment trial analysis. Methods in Ecology and Evolution 11(6): 783–789. https://doi.org/10.1111/2041-210x.13384

Olivoto T and Nardino M (2021) MGIDI: toward an effective multivariate selection in biological experiments. Bioinformatics 37(10): 1383–1389. https://doi.org/10.1093/bioinformatics/btaa981

Olivoto T, Diel MI, Schmidt D and Lúcio AD (2022) MGIDI: a powerful tool to analyze plant multivariate data. Plant Methods 18:121. https://doi.org/10.1186/s13007-022-00952-5

ONS - Office Nationale des Statistiques (2023a) Collections Statistiques: Evolution des échanges extérieurs de marchandises de 2017 à 2022 (233). https://www.ons.dz/spip.php?rubrique315

ONS - Office Nationale des Statistiques (2023b) La Production Agricole Campagne 2020/2021 (990). https://www.ons.dz/IMG/pdf/ProdAgricol2020_2021.pdf

Pour-Aboughadareh A and Poczai P (2021) A dataset on multi-trait selection approaches for screening desirable wild relatives of wheat. Data in Brief 39: 107541. https://doi.org/10.1016/j.dib.2021.107541

Pour-Aboughadareh A, Sanjani S, Nikkhah-Chamanabad H, Mehrvar M R, Asadi A and Amini A (2021) Identification of salt tolerant barley genotypes using multiple-traits index and yield performance at the early growth and maturity stages. Bulletin of the National Research Centre 45(1): 117. https://doi.org/10.1186/s42269-021-00576-0

R Core Team (2024) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/

Romena MH, Najaphy A, Saeidi M and Khoramivafa M (2022) Identification of superior wheat genotypes using multiple-trait selection methods based on agronomic characters and grain protein content under rain-fed conditions. Genetika 54(1): 15-26. https://doi.org/10.2298/gensr2201015r

Sivakumar U and Kumar A (2023) Genetic variability, heritability, and genetic advance analysis in bread wheat (Triticum aestivum L.). The Pharma Innovation Journal 12(8): 800-804.

Tutiempo Network SL (2024) Climate Constantine – climate data (station 604190), 2018 and 2019. https://fr.tutiempo.net/climat/ws-604190.html

Ullah MI, Mahpara S, Bibi R et al (2021) Grain yield and correlated traits of bread wheat lines: Implications for yield improvement. Saudi Journal of Biological Sciences 28(10): 5714–5719. https://doi.org/10.1016/j.sjbs.2021.06.006

Venske E, dos Santos RS, Busanello C, Gustafson P and Costa de Oliveira A (2019) Bread wheat: a role model for plant domestication and breeding. Hereditas 156(1): 16 https://doi.org/10.1186/s41065-019-0093-9

How to Cite

APA

LADOUI, K. K., YAHIAOUI, S., MEFTI, M., BENBELKACEM, A., OUAKKAL, M. & DJENADI, C. (2025). Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria. Revista Facultad Nacional de Agronomía Medellín, 78(3), 11191–11201. https://doi.org/10.15446/rfnam.v78n3.117143

ACM

[1]
LADOUI, K.K., YAHIAOUI, S., MEFTI, M., BENBELKACEM, A., OUAKKAL, M. and DJENADI, C. 2025. Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria. Revista Facultad Nacional de Agronomía Medellín. 78, 3 (Sep. 2025), 11191–11201. DOI:https://doi.org/10.15446/rfnam.v78n3.117143.

ACS

(1)
LADOUI, K. K.; YAHIAOUI, S.; MEFTI, M.; BENBELKACEM, A.; OUAKKAL, M.; DJENADI, C. Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria. Rev. Fac. Nac. Agron. Medellín 2025, 78, 11191-11201.

ABNT

LADOUI, K. K.; YAHIAOUI, S.; MEFTI, M.; BENBELKACEM, A.; OUAKKAL, M.; DJENADI, C. Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria. Revista Facultad Nacional de Agronomía Medellín, [S. l.], v. 78, n. 3, p. 11191–11201, 2025. DOI: 10.15446/rfnam.v78n3.117143. Disponível em: https://revistas.unal.edu.co/index.php/refame/article/view/117143. Acesso em: 18 mar. 2026.

Chicago

LADOUI, Khaoula Khadidja, Samia YAHIAOUI, Mohammed MEFTI, Abdelkader BENBELKACEM, Meriem OUAKKAL, and Chafika DJENADI. 2025. “Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria”. Revista Facultad Nacional De Agronomía Medellín 78 (3):11191-201. https://doi.org/10.15446/rfnam.v78n3.117143.

Harvard

LADOUI, K. K., YAHIAOUI, S., MEFTI, M., BENBELKACEM, A., OUAKKAL, M. and DJENADI, C. (2025) “Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria”, Revista Facultad Nacional de Agronomía Medellín, 78(3), pp. 11191–11201. doi: 10.15446/rfnam.v78n3.117143.

IEEE

[1]
K. K. LADOUI, S. YAHIAOUI, M. MEFTI, A. BENBELKACEM, M. OUAKKAL, and C. DJENADI, “Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria”, Rev. Fac. Nac. Agron. Medellín, vol. 78, no. 3, pp. 11191–11201, Sep. 2025.

MLA

LADOUI, K. K., S. YAHIAOUI, M. MEFTI, A. BENBELKACEM, M. OUAKKAL, and C. DJENADI. “Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria”. Revista Facultad Nacional de Agronomía Medellín, vol. 78, no. 3, Sept. 2025, pp. 11191-0, doi:10.15446/rfnam.v78n3.117143.

Turabian

LADOUI, Khaoula Khadidja, Samia YAHIAOUI, Mohammed MEFTI, Abdelkader BENBELKACEM, Meriem OUAKKAL, and Chafika DJENADI. “Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria”. Revista Facultad Nacional de Agronomía Medellín 78, no. 3 (September 1, 2025): 11191–11201. Accessed March 18, 2026. https://revistas.unal.edu.co/index.php/refame/article/view/117143.

Vancouver

1.
LADOUI KK, YAHIAOUI S, MEFTI M, BENBELKACEM A, OUAKKAL M, DJENADI C. Multi-trait selection of bread wheat (Triticum aestivum L.) genotypes under semi-arid conditions in Algeria. Rev. Fac. Nac. Agron. Medellín [Internet]. 2025 Sep. 1 [cited 2026 Mar. 18];78(3):11191-20. Available from: https://revistas.unal.edu.co/index.php/refame/article/view/117143

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