Sugar alcohols-induced oxidative metabolism in cotton callus culture

Sugar alcohols (mannitol and sorbitol) may cause oxidative damage in plants if used in higher concentration. Our present experiment was undertaken to study physiological and metabolic responses in cotton (Gossypium hirsutum L.) callus against mannitol and sorbitol higher doses. Both markedly declined mean values of relative fresh weight growth rates with the increase in their concentration intensities. The overall protein and malonaldehyde (MDA) contents increased in the stressed-shocked cells. Also, the mean values of various antioxidants such as superoxide dismutase (SOD), peroxidase (POD), ascorbate peroxidase (APX) and calalase (CAT) quantitatively improved over their respective controls. As a whole, MDA contents were higher in magnitude than that of different antioxidant enzymes. Also values of relative increase in case of POD were higher as compared to SOD showing the ability of cotton callus culture to scavenge H2O2 produced as a result of the activity of SOD. Our results show that both agents caused greater damage to the membranous structure in comparison to less activation of the antioxidants. As a whole, the overall change regarding fresh weight growth rates was less after 14-day stress regime, while the mean values of the antioxidant enzymes activities were lower after the 28-day stress period. Such decrease conveys the message that less reactive oxygen species (ROS) might have been produced.Keywords: Antioxidants, callus culture, Gossypium hirsutum L., osmotic stress, sugar alcoholsAfrican Journal of Biotechnology Vol. 12(17), pp. 2191-220

Groundnut Entered Post-genome Sequencing Era: Opportunities and Challenges in Translating Genomic Information from Genome to Field

Cultivated groundnut or peanut (Arachis hypogaea) is an allopolyploid crop with a large complex genome and genetic barrier for exchanging genetic diversity from its wild relatives due to ploidy differences. Optimum genetic and genomic resources are key for accelerating the process for trait mapping and gene discovery and deploying diagnostic markers in genomics-assisted breeding. The better utilization of different aspects of peanut biology such as genetics, genomics, transcriptomics, proteomics, epigenomics, metabolomics, and interactomics can be of great help to groundnut genetic improvement program across the globe. The availability of high-quality reference genome is core to all the “omics” approaches, and hence optimum genomic resources are a must for fully exploiting the potential of modern science into conventional breeding. In this context, groundnut is passing through a very critical and transformational phase by making available the required genetic and genomic resources such as reference genomes of progenitors, resequencing of diverse lines, transcriptome resources, germplasm diversity panel, and multi-parent genetic populations for conducting high-resolution trait mapping, identification of associated markers, and development of diagnostic markers for selected traits. Lastly, the available resources have been deployed in translating genomic information from genome to field by developing improved groundnut lines with enhanced resistance to root-knot nematode, rust, and late leaf spot and high oleic acid. In addition, the International Peanut Genome Initiative (IPGI) have made available the high-quality reference genome for cultivated tetraploid groundnut which will facilitate better utilization of genetic resources in groundnut improvement. In parallel, the development of high-density genotyping platforms, such as Axiom_Arachis array with 58 K SNPs, and constitution of training population will initiate the deployment of the modern breeding approach, genomic selection, for achieving higher genetic gains in less time with more precision

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Not AvailableThe Near Infrared Reflectance Spectroscopy (NIRS), a non-destructive and robust tool was calibrated for rapid estimation of moisture content (MC) in whole groundnut kernels. A set of 8 groundnut genotypes were soaked overnight, followed by drying in hot air oven at 60⁰ C. Data were recorded after every 2 hrs drying using a moisture meter followed by scanning in NIRS, till constant MC was obtained. NIR absorption spectral data from 400 to 2500 nm in 2 mm intervals were collected. Modified partial least squares (MPLS) regression was applied to scatter-corrected spectra (SNV and detrend). Calibration equation with high values for the coefficient of determination (R2), the coefficient of determination for cross-validation (1-VR) and low values for the standard error of calibration or standard error of crossvalidation were estimated. Among the various models employed, model 2 with pretreatment 2,4,4,1 was best with an R2 of 0.99 in the calibration set, 1-VR value of 0.99 in the cross-validation set, lowest values for the standard error of calibration (0.33) and standard error of cross-validation (0.55). Calibration equations for moisture content showed a close relationship between NIRS predicted and lab values in this model. Thus, the selected model can act as the best models for prediction of moisture content in groundnut kernels with high accuracy. This study shows the potential of NIRS to predict the moisture content of groundnut seeds as a routine method in breeding programs, processing industries and for farmer’s advice.Not Availabl