An Integrated Genetic,Physical and Transcript Map of Homoeologous Chromosomes 12 and 26 in Upland Cotton(Gossypium hirsutum L.)

While Upland cotton(Gossypium hirsutum L.) represents 95% of the world production,its genetic improvement is hindered by the shortage of effective genomic tools and resources.The

Toward Development of a Whole-genome, BAC/BIBAC-based Integrated Physical/Genetic Map of the Cotton Genome Using the Upland Genetic Standard TM-1: BAG and BIBAC Library Construction, SSR Marker Development, and Physical/Genetic Map Integration

Integrative physical mapping is the centerpieceof and essential for advanced genomics research.Upland cotton(Gossypium hirsutum L.)geneticstandard line TM-1 is used as the referencegenotype to develop a whole-genome,BAC/BIBAC-based integrated physical/genetic map ofthe cotton genome.From the TM-1 line we haveconstructed two BAC libraries with HindIII

Cotton Germplasm: Resources and Tools for Characterization

Future improvement of cotton has met newchallenges that require integrated tools tocharacterize existing genetic resources.Fragmentary data and information on germplasmcharacterization need to be coordinated into anintegrated whole.The four domesticated species(G.hirsutum,G.barbadense,G.arboreum。

Toward Development of a Whole-genome, BAC/BIBAC-based IntegratedPhysical/Genetic Map of the Cotton Genome Using the Upland Cotton Genetic Standard TM-1: BAC Fingerprinting and Physical Map Contig Construction

We are developing a whole-genome,BAC/BIBAC-based integrated physical/genetic map ofthe cotton(Gossypium hirsutum L.)genomeusing its genetic standard line TM-1 as thereference genotype.Whole-genome physicalmaps integrated with genetic maps will providerevolutionized tools and platforms for all kindsof genomics researeh,including large-scale

Image dehazing based on dark channel prior and brightness enhancement for agricultural monitoring

Obtaining clear and true images is a basic requirement for agricultural monitoring.However,under the influence of fog,haze and other adverse weather conditions,captured images are usually blurred and distorted,resulting in the difficulty of target extraction.Traditional image dehazing methods based on image enhancement technology can cause the loss of image information and image distortion.In order to address the above-mentioned problems caused by traditional image dehazing methods,an improved image dehazing method based on dark channel prior(DCP)was proposed.By enhancing the brightness of the hazed image and processing the sky area,the dim and un-natural problems caused by traditional image dehazing algorithms were resolved.Ten different test groups were selected from different weather conditions to verify the effectiveness of the proposed algorithm,and the algorithm was compared with the commonly-used histogram equalization algorithm and the DCP method.Three image evaluation indicators including mean square error(MSE),peak signal to noise ratio(PSNR),and entropy were used to evaluate the dehazing performance.Results showed that the PSNR and entropy with the proposed method increased by 21.81%and 5.71%,and MSE decreased by 40.07%compared with the original DCP method.It performed much better than the histogram equalization dehazing method with an increase of PSNR by 38.95%and entropy by 2.04%and a decrease of MSE by 84.78%.The results from this study can provide a reference for agricultural field monitoring.

Opening Remarks:Perspectives of the International Cotton Genome Initiative

Thanks go to our hosts,the organizers,sponsors,and all participants who have put in great efforts to making the 2008 Research Conference of the International Cotton Genome Initiative(ICGI,

Map-based cloning of a recessive gene v_1 for virescent leaf expression in cotton(Gossypium spp.)

Background： Virescence, as a recognizable phenotype available for research on chloroplast development and in the early development stage of cotton, is not only photosynthesis but also for heterosis exploitation in cotton Methods： In current study, for fine mapping of virescent-1 （V1） in cotton, three populations with a total of 5 678 individuals were constructed using T582 which has the virescent trait. Tobacco rattle virus, TRV1 and TRV2 （pYL156）, were used as vectors for the virus-induced gene silencing （VlGS） assay. Results： The V1 gene was fine-mapped to a 20 kb interval on chromosome 20 of tetraploid cotton. We identified only one candidate gene with four single nucleotide polymorphisms between parents, among which the single nucleotide polymorphism at the position of 1 082 base pair caused the change of amino acid residue from Arg （3-79） to Lys （]-582）. The relative expression of the candidate gene in virescent plants was extensively lower than that in normal plants. Nullification of the gene by VlGS significantly turned the green leaf of normal cotton plants into yellow. We named this candidate gene as GhRVL. Conclusions： This study will facilitate the further research on virescent formation, and will be useful for breeding of hybrid cottons.

Laboratory evaluation of the GreenSeeker^(TM) handheld optical sensor to variations in orientation and height above canopy

Handheld optical sensors recently have been introduced to the agricultural market.These handheld sensors are able to provide operators with Normalized Difference Vegetative Index(NDVI)data when cloud cover prevents acquisition of satellite or aerial images.This research addressed the sensitivity of the GreenSeeker handheld optical sensor to changes in orientation and height above a ryegrass canopy.Planter boxes were oriented both parallel and perpendicular to the light beam from the sensor head and heights of 30.5 cm(12”),61.0 cm(24”),91.5 cm(36”),122 cm(48”)and 152 cm(60”)were tested.Results indicated that the sensor was highly sensitive(P<0.0001)to both height above canopy and orientation of the sensor relative to the target.Operators should follow manufacturer’s recommendations on operating height range of 81-122 cm and orient the sensor head in-line with the target to obtain maximum signal response.