Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis

Badu‐Apraku, B.; Oyekunle, M.; Ofori, Kwadwo; Osuman, Alimatu Sadia; Ado, S. G.; Coulibay, N.; Yallou, C. G.; Abdulai, Mashark Seidu; Boakyewaa, Gloria Adu; Didjeira, A.

doi:10.1017/s0021859611000761

Cited by 72 publications

(58 citation statements)

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“…This result is in agreement with the findings of earlier workers (BaduApraku et al 2003;Sabaghnia et al 2008;Moghaddam and Pourdad 2009). The high proportion of 63.5% contributed by environments to the total variation in grain yield, 32.8% contributed by GEI and low (3.5%) contribution by genotypes fall within the range reported by earlier workers (Fakorede and Adeyemo 1986;Badu-Apraku et al 2003, 2011aMohammadi et al 2009). However, the contribution of locations to the environmental variation is much higher than the effect of years and location × year interactions.…”

Section: Discussionsupporting

confidence: 93%

“…This result is in agreement with the finding of Oyekunle and BaduApraku (2014), who reported that savannas of West Africa have the greatest potential for maize production and productivities. The identification of Zaria as an outstanding location for identifying superior genotypes in the present study is consistent with the findings of earlier workers (Badu-Apraku et al 2011a, b) …”

Section: Cereal Research Communications 45 2017supporting

confidence: 93%

“…It is planted on an estimated area of 5.8 million hectares in Nigeria with an annual production of 10.8 million tons in 2014 (FAOSTAT 2016). Maize accounts for about 15% of the total calorific intake of the rural dwellers (Badu-Apraku et al 2011a). The demand for maize has considerably increased due to its potential usefulness as food, livestock feed and raw materials for industrial products.…”

Section: Introductionmentioning

confidence: 99%

“…Changes in environments affect both crop growth and grain yield due to significant genotype × environment interactions (GEI) (Reddy et al 2011;Xu et al 2013). Results of multi-location trials (MET) have demonstrated the existence of GEI (Fakorede and Adeyemo 1986;Badu-Apraku et al 2003, 2011a. The presence of a significant GEI complicates the selection of superior cultivars and the best testing sites for identifying superior and stable genotypes.…”

Section: Introductionmentioning

confidence: 99%

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Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis

Oyekunle

Menkir²,

Mani

et al. 2017

Cereal Research Communications

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Genotype × environment interactions complicate selection of superior genotypes for narrow and wide adaptation. Eighteen tropically-adapted maize cultivars were evaluated at six locations in Nigeria for 2 yrs to (i) identify superior and stable cultivars across environments and (ii) assess relationships among test environments. Environment and genotype × environment interactions (GEI) were significant (P < 0·05) for grain yield. Environments accounted for 63.5% of the total variation in the sum of squares for grain yield, whereas the genotype accounted for 3.5% and GEI for 32.8%. Grain yield of the cultivars ranged from 2292 kg ha -1 for DTSTR-W SYN2 to 2892 kg ha -1 for TZL COMP4 C3 DT C2 with an average of 2555 kg ha -1 . Cultivar DT SYN2-Y had the least additive main effect and multiplicative interaction (AMMI) stability value of 7.4 and hence the most stable but low-yielding across environments. AMMI biplot explained 90.5% and classified cultivars and environments into four groups each. IWD C3 SYN F3 was identified as the high-yielding and stable cultivar across environments. ZA15, ZA14, BK14, BK15 and IL15 had environment mean above the grand mean, while BG14, BG15, LE14, LE15, IL14, LA14 and LA15 had mean below the grand mean. ZA, BK, BG, LE and LA were found to be consistent in ranking the maize cultivars. However, Zaria, Birnin Kudu, and Ilorin were identified as the best test locations and could be used for selecting the superior maize cultivars. The identified high-yielding and stable cultivar could be further tested and promoted for adoption to contribute to food insecurity in Nigeria.

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Section: Discussionsupporting

confidence: 93%

Section: Cereal Research Communications 45 2017supporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis

Oyekunle

Menkir²,

Mani

et al. 2017

Cereal Research Communications

Self Cite

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“…However, in the present study (Chapter 4) yield and stover quality attributes were influenced more by environmental effects (year and site) than by the G or G x E and M effects (Tables 4.2 and 4.5, Chapter 4). This is in accord with other multi-environmental trials which have commonly shown that the environmental effects on GY are larger than the G or G x E effects (Badu-Apraku et al, 2012;Beyene et al, 2013;DeLacy et al, 1996;Makumbi et al, 2015). For factors under farmer control, there was substantial variation among genotypes (P<0.01) for yields (t/ha) of TB, grain and stover (Tables 4.3 and 4.4, Chapter 4).…”

Section: Survey Approaches In Avoiding Survey Biasessupporting

confidence: 86%

Options for improving the yield and nutritive value of maize and grain legume residues for ruminants in East African farming systems

Dejene¹

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The role and importance of livestock in smallholder crop-livestock systems and the importance of crop residues (CR) as ruminant feedstuffs in such systems are well established. The effects of genotype (G), environment (E) and crop management (M) factors on yields of grain and CR and the nutritive value of the CR of maize (Zea mays) and common bean (Phaseolus vulgaris) were investigated in an East African context. Genotype effects were examined in early and medium maturing (EM and MM, respectively) maize hybrids and popular varieties of common bean. Environment was examined at three sites for maize in the 2013 and 2014 cropping seasons and at four sites for common bean in 2013. Management effects examined were plant density (D) (5 and 7 plants/m 2 ), height of cutting at harvest in maize, and harvest at early and final seed maturity in common bean. Quality attributes (nitrogen (N), neutral detergent fibre (NDF) and acid detergent fibre (ADF) contents and dry matter digestibility (DMD)) were analysed using near infrared spectroscopy (NIRS) and calibrations expanded and validated with reference samples of CR representing the experimental sample set.There was substantial variation (P<0.05 to P<0.0001) among maize genotypes in yields of grain and stover and quality of stover as a feedstuff. Dual purpose genotypes were identified but G x E interactions for some yield and quality attributes showed that the variation among genotypes can depend on environment. In general the higher D increased yields of grain by 9-15% and stover by 21-31%, but had only minor effects on stover quality attributes. Year (Y) x density (D), G x E and G x D interactions were observed for some of the yield and stover attributes.High cutting height of maize (two internodes below the lowest ear) allowed harvest of most of the stover (on average 63-72% in EM and MM genotypes, respectively) as feedstuff while leaving stubble in the field available for other uses. This is established practice by farmers in some regions. The amount and quality as a feedstuff of the upper and lower stover components varied (P<0.01) among genotypes. N and DMD were 0.05-0.09% and 1.7-3.6%, respectively higher (P<0.0001) in the upper fraction of the stover than in whole stover. Thus evaluation and estimation of the amount and quality of maize stover available as a feedstuff should consider harvest at high cutting height to increase quality. G x E interactions were observed in yield and in some stover attributes in the upper and lower fractions, but these were not consistent.ii Common bean varieties varied (P<0.05 to P<0.0001) in yields of seed and haulm and in the nutritive value of haulm fractions (leaf, stem and pod wall) when harvested at seed maturity. There was extensive leaf loss at seed maturity which decreased haulm quality.Seed and haulm yields were correlated (r=0.87). Seed yield was generally not related to haulm quality as N% or DMD%. The variation in yield and haulm feedstuff quality was also examined in common bean varieties harvested at early se...

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Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

et al. 2023

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The occurrence of the genotype × environment (G × E) interaction is one of the main factors that hinder the selection of adapted and stable genotypes. The genotype and G × E interaction (GGE) biplot methodology is an efficient process to detect corn (Zea mays L.) hybrids for silage and, consequently, will help in the recommendation of new and more stable hybrids in different environments in breeding programs. In this sense, this study aimed to evaluate and select corn hybrids for silage that simultaneously combine high yield and stability in different environments in the state of Rio de Janeiro, Brazil, via GGE biplot. Eleven corn hybrids, eight precommercial topcrosses and three commercial controls, were evaluated at three sites (Campos dos Goytacazes, Cambuci, and Itaocara, Rio de Janeiro) during two seasons: the 2017-2018 season and 2018-2018 off-season. The experiments were designed in completely randomized blocks with three replications. Individual and joint analyses of variance were performed and, after detecting significant interaction between genotype and environment, the adaptability and phenotypic stability of corn genotypes for silage were analyzed using the GGE biplot methodology. The GGE biplot analysis was efficient in interpreting the data and represented 83.68% of the total variation in the first two principal components. The use of the GGE biplot method allowed the recommendation of more productive, stable, and responsive hybrids for the state of Rio de Janeiro. The hybrid UENF MS2208 is indicated for cultivation in the state of Rio de Janeiro for combining high green biomass yield and stability. INTRODUCTIONCorn (Zea mays L.) is a crop that has importance in the socioeconomic, environmental, and cultural spheres worldwide and also in Brazil. It mainly is due to its potential use in human and animal food and biofuel production among others AEC, average environment coordinate; G × E, genotype × environment interaction; GGE, genotype and genotype × environment interaction; GMY, green biomass yield.

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Performance of extra-early maize cultivars based on GGE biplot and AMMI analysis

Cited by 72 publications

References 33 publications

Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis

Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis

Options for improving the yield and nutritive value of maize and grain legume residues for ruminants in East African farming systems

Adaptability and stability of corn hybrids for silage via genotype and genotype × environment interaction biplot

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