Rapid production of multiple shoots from cotyledonary node explants of an elite cotton (Gossypium hirsutum L.) variety

In vitro sprouting and simultaneous elongation of multiple shoots were achievedby culturing cotyledonary node explants of an elite cotton (Gossypium hirsutum L.)variety (NC-601), on Murashige and Skoog basal medium containing N6-Benzylaminopurine, 6- Furfurylaminopurine and Thidiazuron in combination with 1-Naphthaleneacetic acid. A combination of N6-Benzylaminopurine (1.5mg/l) and 1-Naphthaleneacetic acid (0.5mg/l) was found most effective for producing maximumnumber (10.31±0.22) of multiple shoots per explant. Although the explants of differentsets of seedlings could produce multiple shoots, the explants derived from the 15-day oldseedlings show maximum response compared to 5- and 10-day old nodal explants.Furthermore, maximum frequency (82.6%) of rooting was observed in the elongatedshoots when cultured on the half-strength MS medium containing Indole-3-butyric acid.Regenerated plants could survive upto 95 to 100% under the glass house conditions.Following this procedure, plants were obtained within a period of 12 to 15 weeks. Normalflowering and boll formation were observed in regenerated plants similar to that ofcontrol plants obtained through seed germination

Data Migration from On- Premises to Cloud Platform: Key Considerations

In today’s IT world, organizations look up different opportunities to build a strong IT- infrastructure for long-term benefits. With growing business needs, companies across multiple sectors are transitioning from an on-premises environment to cloud, irrespective of the size. The migration to cloud gives leverage to share the resources and allow businesses to virtually access high power computing and storage capacity which optimizes the agility, scalability and cost compared to that of on-site infrastructure. Cloud migration processes can be executed in different ways. It is not necessary that the implementation requires transferring all the organization’s data to the cloud in a single operation. Depending on the organization’s business and technical requirements, the migration process is carried out iteratively. Cloud technology refers to both hardware and software services that are accessible over the internet offered by a cloud service provider. Whereas, in on-premises systems, the IT infrastructure has built in local storage and a physical data warehouse, and the company gets complete ownership of the servers. There are many factors that an organization should take into consideration when deciding to move to the cloud. Encircling all considerations is the critical need to lay a solid foundation for strategically implementing the process. In my paper, I am going to elaborate on: ‘What critical factors to be considered by an organization for successfully implementing cloud migration process of their data assets’

Weapon Detection In Surveillance Camera Images

Now a days, Closed Circuit Television (CCTV) cameras are installedeverywhere in public places to monitor illegal activities like armedrobberies. Mostly CCTV footages are used as post evidence after theoccurrence of crime. In many cases a person might be monitoringthe scene from CCTV but the attention can easily drift on prolongedobservation. Eciency of CCTV surveillance can be improved by in-corporation of image processing and object detection algorithms intomonitoring process.The object detection algorithms, previously implemented in CCTVvideo analysis detect pedestrians, animals and vehicles. These algo-rithms can be extended further to detect a person holding weaponslike rearms or sharp objects like knives in public or restricted places.In this work the detection of weapon from CCTV frame is acquiredby using Histogram of Oriented Gradients (HOG) as feature vector andarticial neural networks performing back-propagation algorithm forclassication.As a weapon in the hands of a human is considered to be greaterthreat as compared to a weapon alone, in this work the detection ofhuman in an image prior to a weapon detection has been found advan-tageous. Weapon detection has been performed using three methods.In the rst method, the weapon in the image is detected directly with-out human detection. Second and third methods use HOG and back-ground subtraction methods for detection of human prior to detectionof a weapon. A knife and a gun are considered as weapons of inter-est in this work. The performance of the proposed detection methodswas analysed on test image dataset containing knives, guns and im-ages without weapon. The accuracy rate 84:6% has been achievedby a single-class classier for knife detection. A gun and a knife havebeen detected by the three-class classier with an accuracy rate 83:0%

Development of Transgenic Cotton Lines Expressing <i>Allium sativum</i> Agglutinin (ASAL) for Enhanced Resistance against Major Sap-Sucking Pests

<div><p>Mannose-specific <i>Allium sativum</i> leaf agglutinin encoding gene (<i>ASAL</i>) and herbicide tolerance gene (<i>BAR</i>) were introduced into an elite cotton inbred line (NC-601) employing <i>Agrobacterium</i>-mediated genetic transformation. Cotton transformants were produced from the phosphinothricin (PPT)-resistant shoots obtained after co-cultivation of mature embryos with the <i>Agrobacterium</i> strain EHA105 harbouring recombinant binary vector pCAMBIA3300-<i>ASAL</i>-<i>BAR</i>. PCR and Southern blot analysis confirmed the presence and stable integration of <i>ASAL</i> and <i>BAR</i> genes in various transformants of cotton. Basta leaf-dip assay, northern blot, western blot and ELISA analyses disclosed variable expression of <i>BAR</i> and <i>ASAL</i> transgenes in different transformants. Transgenes, <i>ASAL</i> and <i>BAR</i>, were stably inherited and showed co-segregation in T₁ generation in a Mendelian fashion for both PPT tolerance and insect resistance. <i>In planta</i> insect bioassays on T₂ and T₃ homozygous <i>ASAL</i>-transgenic lines revealed potent entomotoxic effects of ASAL on jassid and whitefly insects, as evidenced by significant decreases in the survival, development and fecundity of the insects when compared to the untransformed controls. Furthermore, the transgenic cotton lines conferred higher levels of resistance (1–2 score) with minimal plant damage against these major sucking pests when bioassays were carried out employing standard screening techniques. The developed transgenics could serve as a potential genetic resource in recombination breeding aimed at improving the pest resistance of cotton. This study represents the first report of its kind dealing with the development of transgenic cotton resistant to two major sap-sucking insects.</p></div

Effect of ASAL on the fecundity of jassid and whitefly insects.

<p>(A) Total number of nymphs produced by three pairs of adult jassid insects fed on untransformed control and transgenic plants were counted and plotted on the graph. (B) Total number of nymphs produced by five pairs of adult whitefly insects fed on untransformed control and transgenic plants were counted and plotted on the graph. UC: untransformed control plants. NC_3-1-8, NC_9-1-15, NC_12-1-11 and NC_16-1-6: Different Transgenic cotton lines expressing ASAL. Bioassays were carried out with five replications and were repeated thrice. Differences between control and transgenic plants were significant at p<0.0001. Bars indicate mean ± SE.</p

Jassid and whitefly bioassays on homozygous transgenic plants of cotton.

<p>(A) 45-day old transgenic lines along with untransformed control plant infested with jassid. (B) 45-day old transgenic lines along with untransformed control plant infested with whitefly. UC: untransformed control plants showing susceptibility against jassid and whitefly infestation with complete damage (4 on a 1 to 4 scale). NC_3-1-8, NC_9-1-15, NC_12-1-11 and NC_16-1-6: Transgenic cotton lines expressing ASAL showing significant resistance (1 to 2 on a 1 to 4 scale) against jassid and whitefly infestation with minimal plant damage.</p

Basta treated leaves of cotton transformants showing tolerance to the herbicide.

<p>UC: Untransformed control leaf showing damage to the herbicide. 1–9: Leaves of different cotton transformants showing tolerance to the herbicide.</p

Northern and western blot analyses for the expression pattern of transgenes in transgenic cotton lines.

<p>(A) RNA probed with <i>ASAL</i> coding sequence. (B) RNA probed with <i>BAR</i> coding sequence. (C) Protein extracts from cotton plants treated with anti-ASAL antibodies. Lane UC: Samples from untransformed control plants. Lanes NC3, NC5, NC9, NC10, NC12 and NC16: Samples from different transgenic lines. Ethidium bromide stained 28S RNA band is shown under northern blots for amount of RNA loading.</p

Southern blot analyses of transgenic cotton plants.

<p>(A) Restriction map of T-DNA region of pCAMBIA3300 containing <i>ASAL</i> and <i>BAR</i> expression units. (B) Genomic DNA digested with EcoRI and probed with <i>ASAL</i> coding sequence. (C) Genomic DNA digested with HindIII and probed with <i>BAR</i> coding sequence. Lane UC: DNA from untransformed control plant. Lanes NC3, NC5, NC9, NC10, NC12 and NC16: DNA from different transgenic lines.</p