Combining ability analysis of common bean (Phaseolus vulgaris L) genotypes for resistance to bean fly (Ophiomyia spp.), and grain yield and component traits

Nkhata, Wilson; Shimelis, Hussein; Melis, Rob; Chirwa, Rowland; Mzengeza, Tenyson; Mathew, Isack; Shayanowako, Admire

doi:10.1007/s10681-021-02833-9

Cited by 14 publications

(24 citation statements)

References 41 publications

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“…High-yielding combinations may also be identified by using either more-traditional crossbreeding methods [57,[69][70][71], or more-recently, molecular markers [41,72,73] or even near-infrared spectroscopy (NIRS) [74]. Molecular marker assisted breeding efforts of Raatz et al [75] characterised 708 bean varieties, landraces, and breeding lines using Single Nucleotide Polymorphism genotyping markers.…”

Section: Breeding For Increased Yield and Qualitymentioning

confidence: 99%

Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review

et al. 2022

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Common bean (Phaseolus vulgaris L.) is the most important legume for human consumption worldwide and an important source of vegetable protein, minerals, antioxidants, and bioactive compounds. The N2-fixation capacity of this crop reduces its demand for synthetic N fertilizer application to increase yield and quality. Fertilization, yield, and quality of common bean may be optimised by several other agronomic practices such as irrigation, rhizobia application, sowing density, etc. Taking this into consideration, a systematic review integrated with a bibliometric analysis of several agronomic practices that increase common bean yield and quality was conducted, based on the literature published during 1971–2021. A total of 250 publications were found dealing with breeding (n = 61), sowing density and season (n = 14), irrigation (n = 36), fertilization (n = 27), intercropping (n = 12), soilless culture (n = 5), tillage (n = 7), rhizobia application (n = 36), biostimulant/biofertilizer application (n = 21), disease management (n = 15), pest management (n = 2) and weed management (n = 14). The leading research production sites were Asia and South America, whereas from the Australian continent, only four papers were identified as relevant. The keyword co-occurrence network analyses revealed that the main topics addressed in relation to common bean yield in the scientific literature related to that of “pod”, “grain”, “growth”, “cultivar” and “genotype”, followed by “soil”, “nitrogen”, “inoculation”, “rhizobia”, “environment”, and “irrigation”. Limited international collaboration among scientists was found, and most reported research was from Brazil. Moreover, there is a complete lack in interdisciplinary interactions. Breeding for increased yield and selection of genotypes adapted to semi-arid environmental conditions combined with the suitable sowing densities are important agronomic practices affecting productivity of common bean. Application of fertilizers and irrigation practices adjusted to the needs of the plants according to the developmental stage and selection of the appropriate tillage system are also of high importance to increase common bean yield and yield qualities. Reducing N-fertilization via improved N-fixation through rhizobia inoculation and/or biostimulants application appeared as a main consideration to optimise crop performance and sustainable management of this crop. Disease and weed management practices appear neglected areas of research attention, including integrated pest management.

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Section: Breeding For Increased Yield and Qualitymentioning

confidence: 99%

Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review

et al. 2022

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“…There are many publications that reported the results of evaluation of gene action and combining ability in very different crops. For example in rice (Ambikabathy et al, 2021;Del Águila & da Silva, 2021;Gaballah et al, 2022), maize (Yu et al, 2020;Coelho, 2021;Sabitha et al, 2021), sweet corn (Khan et al, 2020), cowpea (Owusu et al, 2020), papaya (Vettorazzi et al, 2021), cotton (Giri et al, 2021;Mudhalvan et al, 2021), eggplants (Datta et al, 2021), groundnut (Daudi et al, 2021), common bean (Nkhata et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Elucidation of gene action and combining ability for productive tillering in spring barley

Hudzenko

Поліщук

Лысенко

et al. 2022

Regul. Mech. Biosyst.

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The purpose of the present study is to identify breeding and genetic peculiarities for productive tillering in spring barley genotypes of different origin, purposes of usage and botanical affiliation, as well as to identify effective genetic sources to further improving of the trait. There were created two complete (6 × 6) diallel crossing schemes. Into the Scheme I elite Ukrainian (MIP Tytul and Avhur) and Western European (Datcha, Quench, Gladys, and Beatrix) malting spring barley varieties were involved. Scheme II included awnless covered barley varieties Kozyr and Vitrazh bred at the Plant Production Institute named after V. Y. Yuriev of NAAS of Ukraine, naked barley varieties Condor and CDC Rattan from Canada, as well as awned feed barley variety MIP Myroslav created at MIW and malting barley variety Sebastian from Denmark. For more reliable and informative characterization of barley varieties and their progeny for productive tillering in terms of inheritance, parameters of genetic variation and general combining ability (GCA) statistical analyses of experimental data from different (2019 and 2020) growing seasons were conducted. Accordingly to the indicator of phenotypic dominance all possible modes of inheritance were detected, except for negative dominance in the Scheme I in 2020. The degree of phenotypic dominance significantly varied depending on both varieties involved in crossing schemes and conditions of the years of trials. There was overdominance in loci in both schemes in both years. The other parameters of genetic variation showed significant differences in gene action for productive tillering between crossing Schemes. In Scheme I in both years the dominance was mainly unidirectional and due to dominant effects. In the Scheme II in both years there was multidirectional dominance. In Scheme I compliance with the additive-dominant system was revealed in 2019, but in 2020 there was a strong epistasis. In Scheme II in both years non-allelic interaction was identified. In general, the mode of gene action showed a very complex gene action for productive tillering in barley and a significant role of non-genetic factors in phenotypic manifestation of the trait. Despite this, the level of heritability in the narrow sense in both Schemes pointed to the possibility of the successful selection of individuals with genetically determined increased productive tillering in the splitting generations. In Scheme I the final selection for productive tillering will be more effective in later generations, when dominant alleles become homozygous. In Scheme II it is theoretically possible to select plants with high productive tillering on both recessive and dominant basis. In both schemes the non-allelic interaction should be taken into consideration. Spring barley varieties Beatrix, Datcha, MIP Myroslav and Kozyr can be used as effective genetic sources for involvement in crossings aimed at improving the productive tillering. The results of present study contribute to further development of studies devoted to evaluation of gene action for yield-related traits in spring barley, as well as identification of new genetic sources for plant improvement.

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“…Nkhata et al [49], Ojwang et al [71], Keller et al [6] and Liu et al [85] also observed two subpopulations (Andean and Mesoamerican gene pools) in their GWAS studies.…”

Section: Population Structure and Linkage Disequilibrium Analysismentioning

confidence: 93%

“…the proportion of missing data per marker was 7% (mean call rate of 93%, ranging from 81 to 100%). The entire data set of SNP markers was filtered in TASSEL v5.2 [66] to remove SNP loci with unknown physical positions on the common bean genome, monomorphic SNPs, and SNP markers with more than 20% missing data and minor allele frequency (MAF) of less than 5% (<0.05) threshold [15,49,67]. A final total of 9370 (38%) DArTseq SNPs distributed across the 11 chromosomes were retained after filtering for use in association analysis and population structure analysis via principal component analysis (PCA).…”

Section: Statistical Analysis Of Phenotypic Datamentioning

confidence: 99%

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Identification of genomic regions of dry bean (Phaseolus vulgarisL.) associated with agronomic and physiological traits under drought stressed and well-watered conditions using genome-wide association study

Mutari

Sibiya

Shayanowako

et al. 2022

Preprint

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Understanding the genetic basis of traits of economic importance under drought stress (DS) and well-watered (NS) conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgaris L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An Andean and Mesoamerican diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stress (DS) and well-watered (NS) conditions for two successive seasons. Agronomic and physiological traits, viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the AMDP was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under DS. Population structure analysis revealed two sub-populations, which correspond to the Andean and Mesoamerican gene pools. Markers explained 0.08 – 0.10, 0.22 – 0.23, 0.29 – 0.32, 0.43 – 0.44, 0.65 – 0.66 and 0.69 – 0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under DS conditions. For NS, R2 varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10-03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across DS and NS conditions. Most of the identified genes had known biological functions related to regulating the response to moisture stress. The findings provide new insights into the genetic architecture of moisture stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.

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Combining ability analysis of common bean (Phaseolus vulgaris L) genotypes for resistance to bean fly (Ophiomyia spp.), and grain yield and component traits

Cited by 14 publications

References 41 publications

Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review

Agronomic Practices to Increase the Yield and Quality of Common Bean (Phaseolus vulgaris L.): A Systematic Review

Elucidation of gene action and combining ability for productive tillering in spring barley

Identification of genomic regions of dry bean (Phaseolus vulgarisL.) associated with agronomic and physiological traits under drought stressed and well-watered conditions using genome-wide association study

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