9 research outputs found

    Simple sequence repeat (SSR)-based genetic variability among peanut genotypes different in specific leaf weight and relative water content

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    The objective of this study was to compare if simple sequence repeat (SSR) markers could correctly identify peanut genotypes with difference in specific leaf weight (SLW) and relative water content (RWC). Four peanut genotypes and two water regimes (FC and 1/3 available water; 1/3 AW) were arranged in factorial randomized complete block design with six replications. The data were recorded for specific leaf weight (SLW) and relative water content (RWC), and 256 SSR markers were used to detect genetic difference. 89 SSR markers could detect polymorphism among peanut genotypes (48.9%). The numbers of alleles ranged from 1 to 6 with a mean of 2.7 alleles per locus. The polymorphic information content (PIC) values varied from 0.38 to 0.75 with a mean of 0.48. The genetics relationship among peanut genotypes was estimated. KK 4 was clustered distinct from the others genotypes, whereas ICGV 98324 and ICGV 98303 were grouped in the same cluster furthest from the KK 4. The results from this study could be useful as a source of variation for development of mapping population for drought tolerance in peanut breeding program.Keywords: Drought, water regime, polymorphism, genetic relationship, SSR markersAfrican Journal of Biotechnology Vol. 12(26), pp. 4053-4064, 26 June, 201

    Evaluation of ten peanut genotypes for resistance to Peanut bud necrosis virus (PBNV)

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    Reactions of peanut genotypes to Peanut bud necrosis virus (PBNV) under sap-inoculation and natural field conditions may be different. Ten peanut genotypes (KK 60-3, KKU 72-1, KKU 72-2, Luhua 11, Tainan 9, JL 24, IC 10, IC 34, ICGV 86031 and ICGV 86388) were evaluated for their reactions to PBNV under field conditions in Thailand in 2001. The objectives of this study were (i) to determine breeding potential of the selected peanut genotypes in terms of PBNV disease resistance, and (ii) to explore the usefulness of disease incidence, disease score and area under disease progress curve (AUDPC) as the assessments of resistance for effectively discriminating susceptible and resistant genotypes of peanut. Significant differences were found between susceptible and resistant peanut genotypes as identified by disease incidence, disease score and AUDPC. Disease score and AUDPC tended to be equally effective and slightly better than disease incidence in identifying peanut genotypes resistant to PBNV. None of the resistance parameters could differentiate genotypes in the resistant group. IC 10, IC 34, ICGV 86031 and ICGV 86388 were identified as good sources of PBNV resistance. Among susceptible genotypes, KK 60-3 was more resistant than the others and could be used as a parent in peanut breeding programs

    Heritability and phenotypic correlation of resistance to Peanut bud necrosis virus (PBNV) and agronomic traits in peanut

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    Peanut bud necrosis virus (PBNV) is a potential threat to peanut production in Thailand. Therefore, the improvement of peanut lines, which are resistant to PBNV and maintain acceptable agronomic traits, is important. The objective of this study was to estimate broad sense heritability and phenotypic correlation in 16 crosses of the F2 populations derived from cross of four resistant parents with four large-seeded peanut cultivars. A randomized complete block design with four replications was used. Peanut bud necrosis disease (PBND) incidence, PBND score and agronomic data were recorded. Estimates of heritability for PBND score on F2 individual plants were low at 60 days after sowing (DAS) and seemed to be improved at 70 DAS. Estimates of heritability for agronomic traits varied over crosses and traits and were generally low. However, high heritability estimates were observed for 100 seed weight in cross KKU 72-1 × IC 10 and for shelling percentage in crosses KKU 72-1 × IC 34 and Luhua 11 × ICGV 86388. High positive correlation coefficients were found among PBND score, PBND incidence and area under disease progress curve (AUDPC) but all PBNV resistance parameters had low correlation with all agronomic traits. High positive correlation coefficients were found among pod weight per plant, pod number per plant and seed weight per plant. Because of low heritability estimates for PBNV resistance and agronomic traits, selection among individual plants in the F2 generation will be ineffective. Selection should be carried out in advanced generations or on the progeny performance as family mean basis

    Relationships between Nutrient Uptake and Nitrogen Fixation with Aflatoxin Contamination in Peanut under Terminal Drought

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    Terminal drought greatly enhanced Aspergillus flavus Link infection (AI) and aflatoxin contamination (AC) in peanut. Identification of new surrogate traits which have an association with AC may be effective to improve peanut varieties with reduced AI and AC. The objective of this work was to examine the relationships of nutrient uptake and N2-fixation (NF) with AC in peanut in a terminal drought condition. Five peanut varieties were tested in well-watered (WW) and terminal drought (TD) conditions (1/3 available water (AW) from R7 (7th reproductive growth stage; beginning of pod maturity stage)). Data were collected for nutrient uptake (nitrogen, phosphorus, potassium, calcium, magnesium), nodule dry weight (NDW), and NF. AI and AC were also examined. Nutrient uptake, NDW, and NF had negative and significant correlations with AI and AC in the TD condition. Negative and significant correlations of the drought tolerance index of nutrient uptake, NDW, and NF with AI and AC were also observed in the TD condition. The results showed that the ability to maintain nutrient uptake and NF in TD might be a mechanism of tolerance to AI and AC. Moreover, due to their negative impacts on AI and AC, nutrient uptake and NF could be used as selection traits for resistance to AI and AC in peanut in TD

    Additional file 1: of ESAP plus: a web-based server for EST-SSR marker development

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    Supplementary materials. Lists of in-house Shell script in ESAP Plus. Nine in-house Shell scripts including: (1) est1_formatting.sh, (2) est2_length_N.sh, (3) est3_vector.sh, (4) est4_lowcom.sh, (5) est5_est_clustering_cdhitest.sh, (6) est5_est_clustering_tgicl.sh, (7) est6_ssr_misa.sh, (8) est6_ssr_repeatmasker.sh, and (9) est7_primer.sh. Format: The above shell scripts were compressed in one zip file. (ZIP 10 kb

    Additional file 2: Table S1. of ESAP plus: a web-based server for EST-SSR marker development

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    A list of 15 SSR primers used to amplify DNA fragments by PCR reaction with genomic DNAs extracted from 15 sugarcane cultivars. (DOCX 15 kb
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