Diversity assessment of sweetpotato germplasm collections for yield and yield-related traits in western Tanzania

Kagimbo, Filson; Shimelis, Hussein; Sibiya, Julia

doi:10.1080/09064710.2017.1372516

Cited by 10 publications

(7 citation statements)

References 10 publications

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“…These genotypes (G22, G3 and G2) also performed better in four environments namely E2 (SRI), E3 (KATRIN), E4 (SUA) and E6 (Mkuranga). The number of roots per plant in the selected clones is higher than some sweet potato landrace varieties and improved genotypes currently cultivated in Tanzania (Kagimbo et al., 2018). Marked differences in root number may be attributed to genotypic variations.…”

Section: Resultsmentioning

confidence: 82%

“…These planting materials are mostly infected by SPVD causing devastating yield losses under severe epidemics (Rahma et al, 2015(Rahma et al, , 2018. This necessitates the need to develop high and stable yielding and SPVD resistant genotypes for sustainable production and productivity of the crop in Tanzania (Gibson et al, 2000;Ngailo et al, 2016;Kagimbo et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Genotype-by-environment interaction of newly-developed sweet potato genotypes for storage root yield, yield-related traits and resistance to sweet potato virus disease

Ngailo

Shimelis

Sibiya

et al. 2019

Heliyon

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Genotype-by-environment interaction analysis is key for selection and cultivar release, and to identify suitable production and test environments. The objective of this study was to determine the magnitude of genotype-by-environment interaction (GEI) for storage root yield, yield-related traits and sweet potato virus disease (SPVD) resistance among candidate sweet potato genotypes in Tanzania. Twenty-three newly bred clones and three check varieties were evaluated across six diverse environments using a randomized complete block design with three replications. The Additive Main Effect and Multiplicative Interaction (AMMI) and genotype and genotype-by-environment (GGE) biplot analyses were used to determine GEI of genotypes. Genotype, environment and GEI effects were highly significant ( P ≤ 0.01) for the assessed traits. Further, AMMI analysis of variance revealed highly significant ( P ≤ 0.001) differences among genotypes, environments and G × E interaction effects for all the studied traits. Both AMMI and GGE biplot analyses identified the following promising genotypes: G2 (Resisto × Ukerewe), G3 (Ukerewe × Ex-Msimbu-1), G4 (03-03 x SPKBH008), G12 (Ukerewe × SPKBH008) and G18 (Resisto × Simama) with high yields, high dry matter content and SPVD resistance across all test environments. The candidate genotypes are recommended for further stability tests and release in Tanzania or similar environments.

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Section: Resultsmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Genotype-by-environment interaction of newly-developed sweet potato genotypes for storage root yield, yield-related traits and resistance to sweet potato virus disease

Ngailo

Shimelis

Sibiya

et al. 2019

Heliyon

Self Cite

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“…There have been many recent studies on the genetic diversity of sweetpotato collection around the world, including Africa (Elameen et al, 2008;Kagimbo et al, 2018;Ngailo et al, 2016;Selaocoe et al, 2019;Tumwegamire et al, 2011;Zawedde et al, 2015), Asia (Fajardo et al, 2002;He et al, 2006;Luo et al, 2016;Rahajeng and Rahayuningsih, 2017;Soegianto et al, 2011;Su et al, 2017;Zhang et al, 2014) , 2008;Zhang et al, 2000), and North America (Jarret and Austin, 1994;Rodriguez-Bonilla et al, 2014;Wadl et al, 2018). From these studies, it has been generally accepted that there is an abundance of genetic diversity in sweetpotato germplasm collections worldwide (Gichuki et al, 2003;Gr€ uneberg et al, 2015;Su et al, 2017;Wadl et al, 2018;Yang et al, 2015); however, smaller geographic collections may show a narrower range of genetic diversity due to inbreeding or other factors (Elameen et al, 2008;Hao et al, 2007;Meng et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Phenotypic Variation in Leaf Morphology of the USDA, ARS Sweetpotato (Ipomoea batatas) Germplasm Collection

Jackson¹,

Harrison²,

Jarret³

et al. 2020

horts

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During 2012–14, 737 sweetpotato, Ipomoea batatas (L.) Lam. (Convolvulaceae), plant introduction (PI) accessions from the U.S. Department of Agriculture, Agricultural Research Service (USDA, ARS) sweetpotato germplasm collection were evaluated for several phenotypic leaf and plant characteristics, and a photographic record of each accession was made. Data were prepared for placement in the USDA, ARS Germplasm Resources Information Network (GRIN) database and the sweetpotato ontology. The parameters recorded for each genotype were canopy coverage, vine length, general leaf outline, leaf lobing, shape of the central leaf lobe, number of leaf points, leaf petiole length, leaf width, leaf length, leaf width × length, and leaf width/length (aspect ratio). The data indicate that there is wide genetic diversity for vegetative phenotypic characteristics within the USDA, ARS sweetpotato germplasm collection. This study provides important phenotype information for the USDA, ARS sweetpotato collection that has been lacking and can be used for curation of the collection and by researchers and breeders working with this important global food crop.

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“…It is a prerequisite for conservation and utilization of plant genetic resources (Mason et al, 2017). Morphological characterization can also be useful in selection of parents for breeding (Orobiyi et al, 2017;Kagimbo et al, 2017). Therefore, there is a need to assess the diversity of any crop prior to selection and crossing to better utilize the resources in any breeding program.…”

Section: Discussionmentioning

confidence: 99%

Morphological characterization of blackberry (Rubus subgenus Rubus Watson) genetic resources in Kenya

Ochieng¹,

Gesimba²,

Oyoo³

et al. 2019

Afr. J. Plant Sci.

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The variation of morphological and physiological traits of blackberry (Rubus subgenus Rubus Watson) is vital for successful breeding of the fruit crop. The objective of this study was to characterize blackberry accessions in-situ using morphological descriptors in Kenya. Each blackberry accession was nested within its county of collection. A phylogenetic tree was then constructed using the Gower's coefficient which clustered the accessions into two classes; I and II consisting of 1 and 89 accessions, respectively. The clustering of accessions did not show an association between the origin of collection and the accessions. Principal Component Analysis (PCA) revealed ten axes of which seven had a cumulative variation of 96.30% with the first two axes having a discriminatory variance of 52.71%. This suggests that variables identified in this study could be used to differentiate blackberry accessions morphologically. This study demonstrated that the number of internodes per average growing shoots, thorniness of the plant and length of internode were associated with the first axis with Eigenvalue of 27.79%. Plant thorniness was also associated with the second axis with Eigenvalue of 24.92%. These results suggest that there exists qualitative and quantitative variation among blackberry accessions in Kenya that can be utilized in breeding.

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Diversity assessment of sweetpotato germplasm collections for yield and yield-related traits in western Tanzania

Cited by 10 publications

References 10 publications

Genotype-by-environment interaction of newly-developed sweet potato genotypes for storage root yield, yield-related traits and resistance to sweet potato virus disease

Genotype-by-environment interaction of newly-developed sweet potato genotypes for storage root yield, yield-related traits and resistance to sweet potato virus disease

Phenotypic Variation in Leaf Morphology of the USDA, ARS Sweetpotato (Ipomoea batatas) Germplasm Collection

Morphological characterization of blackberry (Rubus subgenus Rubus Watson) genetic resources in Kenya

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