Generic Paddy Plant Disease Detector (GP2D2): An Application of the Deep-CNN Model

Rice is the primary food for almost half of the world’s population, especially for the people of Asian countries. There is a demand to improve the quality and increase the quantity of rice production to meet the food requirements of the increasing population. Bulk cultivation and quality production of crops need appropriate technology assistance over manual traditional methods. In this work, six popular Deep-CNN architectures, namely AlexNet, VGG-19, VGG-16, InceptionV3, MobileNet, and ResNet-50, are exploited to identify the diseases in paddy plants since they outperform most of the image classification applications. These CNN models are trained and tested with Plant Village dataset for classifying the paddy plant images into one of the four classes namely, Healthy, Brown Spot, Hispa, or Leaf Blast, based on the disease condition. The performance of the chosen architectures is compared with different hyper parameter settings. AlexNet outperformed other convolutional neural networks (CNNs) in this multiclass classification task, achieving an accuracy of 89.4% at the expense of a substantial number of network parameters, indicating the large model size of AlexNet. For developing mobile applications, the ResNet-50 architecture was adopted over other CNNs, since it has a comparatively smaller number of network parameters and a comparable accuracy of 86.1%. A fine-tuned ResNet-50 architecture supported mobile app, “Generic Paddy Plant Disease Detector (GP2D2)” has been developed for the identification of most commonly occurring diseases in paddy plants. This tool will be more helpful for the new generation of farmers in bulk cultivation and increasing the productivity of paddy. This work will give insight into the performance of CNN architectures in rice plant disease detection task and can be extended to other plants too

Novel SSR Markers for Polymorphism Detection in Pigeonpea (Cajanus spp.)

With an objective to expand the repertoire of molecular markers in pigeonpea (Cajanus cajan), 36 microsatellite or simple sequence repeat (SSR) loci were isolated from a SSR-enriched genomic library. Primer pairs were designed for 23 SSR loci, of which 16 yielded amplicons of expected size. Thirteen SSR markers were polymorphic amongst 32 cultivated and eight wild pigeonpea genotypes representing six Cajanus species. These markers amplified a total of 72 alleles ranging from two to eight alleles with an average of 5.5 alleles per locus. The polymorphic information content for these markers ranged from 0.05 to 0.55 with an average of 0.32 per marker. Phenetic analysis clearly distinguished all wild species genotypes from each other and from the cultivated pigeonpea genotypes. These markers should be useful for genome mapping, trait mapping, diversity studies and assessment of gene flow between populations in pigeonpea

A PROSPECTIVE CONSIDERATIONS AND COMPARATIVE EFFICACY BETWEEN IVABRADINE VS BETA BLOCKERS IN SOUTH INDIAN ACUTE CORONARY SYNDROME PATIENTS

Objectives: the objective of this study was to assess the role of heart rate in acute coronary syndrome with reduced ejection fraction, to assess contraindications for beta blockers, to assess the tolerability between Ivabradine and Beta-Blockers, to assess efficacy between Ivabradine and Beta Blockers, to assess patient condition according to NYHA classification. Methods: A Prospective observational study was conducted for a duration of6 months Study population includes 100 patients in which Group A-50, Group B-50. We were selected the subjects according to inclusion and exclusion criteria. The patients were classified in one of four categories based on their symptoms in regards to normal breathing and varying degrees in shortness of breath by using (The New York Heart Association) NYHA Classification. Results: Majority of the patients were in age group between (55-64)(32%) years of age are highly affected with ACS. Prevalence of ACS is high in Rural (56%). Both drugs decreased the mean heart rate to 89.97±10.27 (Group-A) versus 86.76±13.14 (Group-B) beats per minute (P=0.24). The result obtained are clinically and statistically significant with statistical significance at P>0.05. Conclusion:  In the present study we considered and compared the efficacy between Ivabradine and Beta Blockers in south Indian acute coronary syndrome patients shows Ivabradine is as effective as betablockers in reduction of heart rate.   &nbsp

Raman spectroscopy studies of oral cancer

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Lectindb: a plant lectin database

Lectins, a class of carbohydrate-binding proteins, are now widely recognized to play a range of crucial roles in many cell–cell recognition events triggering several important cellular processes. They encompass different members that are diverse in their sequences, structures, binding site architectures, quaternary structures, carbohydrate affinities, and specificities as well as their larger biological roles and potential applications. It is not surprising, therefore, that the vast amount of experimental data on lectins available in the literature is so diverse, that it becomes difficult and time consuming, if not impossible to comprehend the advances in various areas and obtain the maximum benefit. To achieve an effective use of all the data toward understanding the function and their possible applications, an organization of these seemingly independent data into a common framework is essential. An integrated knowledge base (Lectindb, http://nscdb.bic.physics.iisc.ernet.in) together with appropriate analytical tools has therefore been developed initially for plant lectins by collating and integrating diverse data. The database has been implemented using MySQL on a Linux platform and web-enabled using PERL-CGI and Java tools. Data for each lectin pertain to taxonomic, biochemical, domain architecture, molecular sequence, and structural details as well as carbohydrate and hence blood group specificities. Extensive links have also been provided for relevant bioinformatics resources and analytical tools. Availability of diverse data integrated into a common framework is expected to be of high value not only for basic studies in lectin biology but also for basic studies in pursuing several applications in biotechnology, immunology, and clinical practice, using these molecules

Genomic designing for biotic stress resistance in sugarcane.

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Raman spectroscopy studies for diagnosis of cancers in human uterine cervix

Cancer of uterine cervix is one of the leading cancers among women in both developed and developing countries. Optical spectroscopy methods mostly Fourier transform infrared (FTIR) and fluorescence have widely been used to diagnose cervix cancer using cells as well as tissues. Raman spectra of normal and malignant tissues were recorded in fingerprint region. Normal cervix tissues are characterized by strong, broad amide I, broader amide III and strong peaks at 853 and 938 cm-1 which can be attributed to structural proteins such as collagen. Prominent features of malignant tissue spectra with respect to normal tissue are-relatively weaker and sharper amide I, minor red shift in ΔCH2 and sharper amide III which indicate the presence of Deoxyribonucleic acid (DNA), lipids and non-collagenous proteins. In order to develop highly objective discrimination methods, very elaborate data analysis was carried out using Principal Components Analysis (PCA). Standard sets for normal and malignant were prepared and tested retrospectively and prospectively. Several parameters such as (scores of factor, Mahalanobis distance and spectral residuals) were explored for discrimination and very clean clustering of normal and malignant spectra was achieved. A multiparametric approach (limit test) combining all the above discrimination parameters was also considered, in order to develop unambiguous discrimination. This analysis has produced very high, 99.5%, sensitivity and specificity. Results obtained in this study thus validate Raman spectroscopy methods for discrimination of normal and malignant tissues in cervical cancers