Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn

Nardino, Maicon; Baretta, Diego; Carvalho, Ivan Ricardo; Olivoto, Tiago; Follmann, Diego Nicolau; Szareski, VinÃ­cius Jardel; Ferrari, Maurício; Pelegrin, Alan Junior de; Konflanz, Valmor Antônio; Souza, V. Q. de

doi:10.5897/ajar2016.11691

Cited by 15 publications

(3 citation statements)

References 13 publications

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“…Model yang kuat dan akurat diperlukan dalam mengevaluasi percobaan yang kompleks (seperti percobaan multilokasi atau percobaan multi-tahun) sehingga penggunaan model campuran semakin populer dalam program pemuliaan tanaman (Nardino et al, 2016). Hal ini terutama disebabkan oleh adanya efek lokal/tahun yang dianggap sebagai faktor acak dalam banyak kasus, sehingga hasil inferensinya lebih bersifat umum (Piepho et al, 2008).…”

Section: K E K U a T A N A N A L I S I S M O D E L L I N I E R Campuranunclassified

Penerapan Model Linier Campuran Untuk Analisis Data Pada Program Pemuliaan Kelapa Sawit

Ningsih,

Adriwan Siregar,

Yenni

2024

war

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Program pemuliaan kelapa sawit untuk menghasilkan varietas unggul membutuhkan analisis statistik yang efektif. Model Linier Campuran atau Mixed Linear Model (MLM) merupakan pendekatan yang populer untuk menganalisis data pemuliaan. Tulisan ini membahas pentingnya analisis model linier campuran dalam pemuliaan kelapa sawit dan bagaimana metode ini dapat mengatasi kendala dalam pengujian pemuliaan di lapangan. MLM memungkinkan pemodelan efek tetap dan efek acak, mengakomodasi data yang tidak seimbang, serta mengintegrasikan informasi kekerabatan. Selain itu, model ini dapat menangani data yang berkorelasi dan memberikan estimasi yang lebih akurat dan efisien. Implementasi model linier campuran pada resolvable design dan analisis GxE memberikan hasil yang kuat dan dapat diandalkan dalam seleksi varietas kelapa sawit unggul. Dengan menggunakan metode Best Linear Unbiased Prediction (BLUP), data pemuliaan kelapa sawit dapat diolah dengan baik untuk menduga parameter genetik dan memprediksi nilai pemuliaan meskipun data yang digunakan “berantakan“. Penerapan analisis model linier campuran dalam pemuliaan kelapa sawit dapat menjadi alat bantu untuk meningkatkan efisiensi dan keberhasilan percobaan pemuliaan kelapa sawit dalam menghasilkan varietas unggul yang berkelanjutan.

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Section: K E K U a T A N A N A L I S I S M O D E L L I N I E R Campuranunclassified

Penerapan Model Linier Campuran Untuk Analisis Data Pada Program Pemuliaan Kelapa Sawit

Ningsih,

Adriwan Siregar,

Yenni

2024

war

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“…The BLUP has been used in the evaluation of various crops such as rice (53), corn (54), cotton (55) and sugarcane (56) and useful results have been presented. One of the most important advantages of the mentioned method is the accurate estimation of the mean performance of genotypes, especially in LMMs (28,49,57). In addition, when there is a LMM effect in the results, the BLUP allows optimal prediction of random effects (58,59).…”

Section: Table 3 Estimation Of Phenotypic Variance Components Of Whit...mentioning

confidence: 99%

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Rajabi

Saremirad

Rezaei

et al. 2023

Preprint

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Background The methods utilized to analyze genotype by environment interaction (GEI) and assess the stability and adaptability of genotypes are constantly changing and developing. In this study, 13 different sugar beet genotypes were grown in four naturally infected locations over two years. They were also assessed for resistance to Rhizoctonia disease in microplots artificially inoculated with the R133 isolate of Rhizoctonia solani. Results The additive main effect and multiplicative interaction (AMMI) analysis showed that both environment and genotype had significant additive effects, while GEI had a significant multiplicative effect. Further analysis of the interaction effects using IPCs revealed that the first three IPCs were significant. Based on the AMMI1 biplot, Rc3, Rc6, and Rc11 were recognized as the most stable genotypes. The TOPSIS calculated from AMMI statistics identified Rc3 as the most stable genotype. The LMM showed that the genotype and GEI were significant. Based on the best linear unbiased prediction (BLUP), Rc6 had the highest predicted mean white sugar yield (WSY). The obtained TOPSIS from BLUP statistics introduced Rc3 and Rc9 as the most stable genotypes. The WSY and WAASB biplot showed that Rc3, Rc5, and Rc11 had higher WSY in addition to stability. In terms of WAASBY/WSY ratio, BTS233, Rc5, and Rc7 were found to be stable genotypes. The simultaneous ranking and selection of genotypes based on the 50/50 ratio for WAASB and WSY yielded somewhat different results, with Rc3, Rc6, and Rc11 having relatively higher WAASBY values. Conclusion Based on the results, the AMMI alone cannot be successful in analyzing the structure of the LMM. In such a situation, using BLUP can bring better and more reliable results. However, the combination of AMMI power and BLUP prediction accuracy made it possible to investigate the genotypic stability and GEI derived from the LMM, and to reveal a complete view of the GEI of sugar beet product while eliminating the limitations of AMMI. In total, Rc3 followed by Rc6 and Rc11 were recognized as stable genotypes with high WSY. In addition to stability and high WSY, these genotypes also had genetic resistance against R. solani.

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“…The fertilization of 300 kg ha -1 of NPK in the formulation 05-20-20 was applied, and 180 kg ha -1 of nitrogen in the amide form was applied for top dressing, on the stages V4 and V6, following the phenological scale proposed by (Ritchie et al, 1993). The control of invasive plants, insect-pests, and diseases were carried out in a preventive way in order to minimize biotic influences in the experiment (Nardino et al, 2016a).…”

Section: Methodsmentioning

confidence: 99%

Interrelations of Characters and Multivariate Analysis in Corn

Szareski¹,

Carvalho²,

Kehl³

et al. 2018

JAS

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The objective of this work was to evaluate the agronomic performance of corn hybrids, the interrelations of the characters with the grain yield, and to genetically discriminate the corn hybrids by means of the dispersion analysis of the canonical variables. The experiment was conducted in the agricultural crop of 2013/2014, in an area belonging to the Federal University of Santa Maria, Campus of Frederico Westphalen, RS. The experimental design was a randomized block design, with four replications. The treatments were composed of seven maize hybrids with different genetic bases and maturation cycles. The LG 6304 modified simple hybrid has higher grain yield than the others. The characters plant height, spike insertion height and number of grains per row of spike have positive interrelations with grain yield of corn hybrids. Hybrids are not grouped according to the genetic basis and maturation cycle. The canonical variables explain 94.62% of the existing genetic variation, and allows the formation of five groups of maize hybrids.

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Restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) for analyzing the agronomic performance of corn

Cited by 15 publications

References 13 publications

Penerapan Model Linier Campuran Untuk Analisis Data Pada Program Pemuliaan Kelapa Sawit

Penerapan Model Linier Campuran Untuk Analisis Data Pada Program Pemuliaan Kelapa Sawit

Evaluation of resistance and stability of new sugar beet hybrids in field conditions infected with rhizoctonia root and crown rot disease

Interrelations of Characters and Multivariate Analysis in Corn

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