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Background: Yellow mosaic disease (YMD) caused by Mungbean Yellow Mosaic Virus (MYMV) is one of the most destructive biotic constraints for production in urdbean. Development and introduction of resistant cultivars with high seed yield is considered as the most economical and eco-friendly option to manage YMD, for which understanding the gene action controlling the inheritance of different traits along with YMD resistance is an important requirement. Methods: Material comprised of four diverse genotypes (TU 94-2, PU 31, IPU 94-1 and LBG 623), six F1s, six BC1s and six BC2s and six F2s. These six generations of all the six crosses were evaluated for various yield related traits in rabi, 2020-21 and phenotyped for YMD in summer, 2021 at Lam, Guntur, Andhra Pradesh which is hotspot for YMD. Result: Inadequacy of additive-dominant model for all most all traits including YMD except for test weight was observed. It was found that, [l] type of non-allelic interaction was observed to be predominant for majority of the traits. Further, the existence of duplicate type of epistasis in the inheritance was evident at least in few crosses for all the traits (except days to maturity). The duplicate epistasis will reduce the variation in F2 and subsequent generations, thereby hinder the pace of the progress through selection.

Lung Cancer is a dangerous disease which is caused by consumption of tobacco and other pollutants it is very hard to predict. But in this era of technology, prediction of lung cancer is possible with the help of machine learning and deep learning algorithms. According to the surveys the survival rate of patients that are affected by cancer is very low, it is because of lack of prediction of cancerous cells in earlier phase. In this Project we use CT(Computed Tomography) scan images of malignant, benign and normal cases are taken in the dataset to classify them as cancerous and non-cancerous images with the help of CNN family Algorithm, i.e, Inception V3 Algorithm. The CT scan images are preprocessed with the help of image preprocessing techniques such as image warping and image cropping. After the preprocessing of the CT images the images are processed with Inception V3 Algorithm, the image dataset is trained under Inception V3 Algorithm of deep learning technique and under the range of 10 epochs the best accuracy the algorithm has provided is 97%. Many Machine Learning Algorithms are used to classify the images such as SVM, CNN, etc. But under deep learning technique the inception V3 algorithm has provided the best accuracy so far. Keywords— CT Scan Images, CNN Algorithm, Cancer Nodules, Malignant cases, Benign Cases, Normal Cases, Inception V3 Algorithm, SVM Algorithm, Image Warping and Image Cropping.

The physiological workload is a personal monitoring device that allows one to measure one’s heart rate in real-time or record the heart rate for later analysis. It is important to note that heart rate fluctuates easily and is affected by multiple elements such as work, stress, hydration, nutrition, smoking, caffeine, exercise, and health conditions. In the current study, the heart rates of two different sector female workers were assessed i.e., weeding activity under agricultural sector and packaging activity under industrial sector. An exploratory research design was adopted to conduct the study in which heart rate monitor was used to assess physiological workload of the workers. Weeding and packaging are two different activities that require different levels of energy expenditure, different working postures, and physical resources. The findings showed that the cost of physiological workload was more for weeding activity compared to packaging activity which implies that weeding activity is laborious.

Forty black gram [Vigna mungo (L.) Hepper] genotypes were evaluated using principal component analysis to estimate the extent of genetic diversity for ten different yield and its component traits. The first three principal components viz., PC I, PC II and PC III with eigen values more than one contributed around 80% of the variability for the genotypes studied. PC I contributed 46.834% towards variability and the traits responsible for its contribution are viz., number of clusters per plant, grain yield per plant, number of branches per plant and number of seeds per pod. The second axis (PC II) contributed 18.951% variability and variation at this axis is due to the accumulated genetic variation of traits viz., days to 50% flowering, days to maturity, grain yield per plant and number of clusters per plant. While PC III and PC IV accumulated 13.807% and 5.765% respectively. Therefore on a cumulative note, first four axes contributed about 85.357% of total variance among 10 characters for all the forty genotypes under study. In the current investigation, four lines (TU 94-2, PU 31, IPU 94-1 and LBG 623) are identified from the depicted 2D & 3D figures as diverse genotypes, which may yield transgressive segregants or heterotic F1s based on nature of gene action of the trait in question.

Restricted selection was used for estimating the genetic advance of yield and nutritional components viz., days to 50% flowering, plant height, panicle length, productive tillers per plant, days to maturity, test weight, protein, carbohydrate, calcium, iron, zinc, copper, manganese, phosphorus and grain yield per plant. The genetic advance of all the fifteen characters under study was estimated by assigning equal economic weights to all characters as well as by using inverse of means as their economic weights. In both cases, the trait plant height recorded maximum estimate of genetic advance in 11 out of 15 cases. The main outcome of the present study is the occurrence of similar trend in the both cases i.e., by assigning equal economic weights and using inverse of means of respective characters as economic weights. This indicates that both ways of assigning weights were equal effective and will result in similar conclusions.

The 2013 curriculum which focuses on improving scientific literacy, assessment is an integral part of the science learning process. However, based on the results of measurements carried out by PISA (Program for International Student Assessment), Indonesian scientific literacy is still relatively low. This study aims to produce an assessment instrument based on scientific literacy on the excretory system and respiratory system material. This research is Research and Development using the Plomp development model which consists of the initial investigation stage, the development stage or the prototyping stage, and the assessment stage. The subjects of the small-scale research product test were 9 students, and the field trial was 32 students. The results showed that the average value of the logical validity of the instrument was 87,23% which was declared very valid and the empirical validity value was 80,00%. The results of the practicality test of the assessment instrument by teachers scored 89,52% and by students 88,43%. The reliability of the scientific literacy-based assessment instrument shows a very high category with a reliability value of 0,93, 80 % questions with moderate difficulty criteria and 66,00% questions with good discriminating power. So, it can be concluded that the scientific literacy-based assessment instrument for the excretory system and respiratory system material can be declared very valid, very practical, and the reliability of the questions is very high.

The study was conducted to explore the effect of selected preservation treatments on the quality of Statice flower in floral freeze dryer. Preservation of flowers in freeze drying process retains its pigment (colour) and structural parts (cells) and thus remains as fresh bloom for years. Prior to freeze drying process, flowers were treated with set of chemical compounds for retaining the inherent qualities in preserved flowers. The qualitative characteristics of flowers were evaluated by expert panel. Flowers treated with a chemical compound that had a blend of exchange medium colour preservatives, colour fixatives, buffers, modifiers, pH regulator, and shatter resistant compound (Ethyl vinyl acetate) resulted in flower that was closer to natural.

Sixty greengram germplasm lines were subjected to multivariate analysis through Mahalanobis’ D2 statistics (Tocher’s method) and 60 genotypes were grouped into nine clusters. Cluster III was the largest with 19 genotypes, followed by cluster I having 17 genotypes, cluster II and VII with eight genotypes, cluster V having 5 genotypes and clusters IV, VI, VIII and IX were solitary clusters. The maximum inter-cluster distance was between cluster VIII and IV, followed by cluster VIII and V. It shows that there is wide genetic diversity between the clusters. On the basis of divergence between clusters, superior F1s or their transgressive segregants can be obtained by crossing between the genotypes belonging to cluster VIII and cluster IV and also between genotypes belonging to cluster VIII and cluster V which are having maximum inter cluster distance between them. Further such genotypes from above clusters which are having better per se are to be considered for hybridization programme.