Hybrid Programming Research Articles

Genetic diversity study in soybean [Glycine max L. Merrill] based on agro- morphological characters

Using Mahalanobis D2statistics, the level of genetic diversity among soybean genotypes based on 12 agro-morphological traits was investigated in this study. A total of 100 soybean genotypes were grouped into six clusters. Cluster I had the maximum number of genotypes (53 genotypes), followed by cluster II (37 genotypes), cluster III (6 genotypes), clusters IV and V (1 genotype each), cluster VI (2 genotypes). Clusters I and VI had the greatest inter-cluster distance (117618.10). Intra-cluster distance ranged between 0.00 and 9830.83. The biggest contribution to total divergence came from character plot yield (25.0 %). Cluster VI had the highest cluster mean values for yield and its component traits. Based on inter-cluster distance, cluster mean values, and mean per se performance, it is recommended to utilize genotypes of cluster I and cluster VI, I and III, III and IV, II and VI, respectively, for future hybridization programs to develop high yielding genotypes. Keywords: soybean, clusters, genetic diversity

Multivariate analysis based prediction of phenotypic diversity associated with yield and yield component traits in germplasm lines of rice (Oryza sativa L.)

An investigation was conducted with 217 germplasm lines of rice to estimate potential variation among rice genotypes. Multivariate analyses viz., PCA and cluster analysis to assess genetic diversity were performed on seven agronomic traits. For the evaluated traits in the lines of germplasm, box plots and normal probability plots displayed substantial estimates of variability. PCA showed that PC1 and PC2 represented 46.15 per cent of variation. PC1 was responsible for the most variance (24%) for four characters, followed by PC2 (22.15%) for three parameters. Filled grain number per panicle, single plant yield, plant height and thousand grain weight were identified as vital traits contributing to variability. Based on agglomerative hierarchical cluster analysis, the germplasm lines were grouped into five clusters, which explained a lot of variation in the traits. The study identified that plant height and 1000 grain weight have the greatest impact on variation. The genotypes viz., WGL 1063, RNR 26085, OR 2511-3, Swarna, KNM 7123, WGL 1063, MGD-101, IVT MS-6130, IVT IM-4231, IVT IME-3948 and IVT NPT-6303 were found to be the best performing genotypes for the traits panicle length, plant height and single plant yield, which can be used in hybridisation programme to improve these traits. Keywords: Rice, Box plot, diversity, germplasm, principal components and variability

A novel cluster-specific analysis framework for demand-side management and net metering using smart meter data

Demand-side management (DSM) and net metering (NM) plays a critical role in managing the energy imbalance by supervising the customer behavioural patterns. The availability of fine-grained energy consumption information from the smart meter empowers the energy policy-makers to design realistic DSM and NM plans with a detailed analysis of usage patterns, dynamics, and characteristics. This paper presents a novel cluster-specific analysis framework to examine trends in residential electricity consumption to understand their potential for participating in energy efficiency, demand response, and net metering programs. In this process, the proposed framework utilises the Hierarchical clustering on energy usage patterns of residential consumers of Kolkata, India to obtain the representative profiles. Further, six different load shape characteristics are proposed to semantically analyse the clustered profiles for understanding the underlying diversity in consumption behaviour. Moreover, a novel statistical approach is incorporated into the proposed framework to evaluate the electricity consumption of every customer based on the number of peaks in a day, solar size required, and consumption during solar generation hours. The findings emphasise the critical nature of examining consumption habits in order to execute rational and productive decisions for the residential sector The scalability experiment demonstrates the effectiveness of the proposed framework. The cluster-specific analysis thus recommends power utilities in categorising the groups to participate in the demand-side management, net metering, and hybrid programs based on their respective potential. This would also help utilities in better planning for future electricity needs with an increase in renewable energy sources. • A framework for determining the potential of customers for DSM & NM is proposed. • Practical analysis of load profiles using distinct characteristics is presented. • The number of peaks per day & usage during PV generation hours are key parameters. • The implications for DSM & NM are presented for customer recruitment process.

Germplasm Evaluation, Genetic Variability, Heritability, Genetic Advance, and Character Analysis in Scented and Non-Scented Rice (Oryza sativa L.) Under Irrigated Conditions

Eighty-nine germplasm of rice (Oryza sativa L.) along with four checks were evaluated in a well-prepared field to assess the genetic variability, heritability, and genetic advance for different characters under irrigated conditions in Augmented Block Design. In this study, the analysis of variance revealed highly significant or significant for all the 13 characters except non–significant for 1000- grain weight. High and moderate broad sense heritability was recorded for all the characters except 1000-grain weight, days to maturity, days to 50 % flowering, and spikelet fertility which showed low heritability. Genetic advance in percent of mean recorded high and moderate for all the characters except 1000-grain weight, days to 50 % flowering, number of fertile spikelet per panicle, and spikelet fertility which had the low genetic advance. The phenotypic and genotypic coefficient of variation was recorded higher for flag leaf area and moderate for harvest index, days to maturity, and L/B ratio. Non- hierarchical Euclidean analysis grouped the eighty-nine germplasm into eight clusters and this study showed the existence of wide genetic diversity within Oryza sativa germplasm. Among the eight clusters, the highest number of genotypes were present in cluster III which contained 23 entries, followed by cluster IV and cluster VII with 14 and 11entries, respectively. While least no genotypes were present in cluster VIII contained only 4 genotypes. The highest intra-cluster distance was observed in cluster II (3.664) while the lowest was in cluster V (2.327). In the case of inter-cluster distance, the highest value was observed between cluster VIII and cluster II (5.698) while the lowest value was observed between V and III clusters (2.808). The genotypes present in the diverse clusters may serve as parental material for the hybridization program which will lead to the isolation of desirable sergeants for developing high-yielding rice varieties under irrigated conditions.

A Hybrid Dynamic Method for Conflict-Free Integrated Schedule Optimization in U-Shaped Automated Container Terminals

Automated guided vehicles (AGVs) in the U-shaped automated container terminal travel longer and more complex paths. The conflicts among AGVs are trickier. The scheduling strategy of the traditional automated container terminal is difficult to be applied to the U-shaped automated container terminal. In order to minimize the handling time of all tasks and avoid AGV conflicts simultaneously in the U-shaped automated container terminal, this paper establishes a hybrid programming model for conflict-free integrated scheduling of quay cranes, AGVs, and double-cantilever rail cranes in the unloading process. It consists of a discrete event dynamic model and a continuous time dynamic model. An improved genetic seagull optimization algorithm (GSOA) is designed. A series of numerical experiments are conducted to verify the effectiveness and the efficiency of the model and the algorithm. The results show that the proposed method can simultaneously realize the AGVs collision avoidance and multi-equipment integrated scheduling optimization in the U-shaped automated container terminal.

Combining Ability and Heterosis of QPM Hybrids for Yield, Qualitative and Quantitative Traits under Heat stress in Different Environments

With increasing climate change relates to rise in mercury causing heat stress in maize. Heat stress tolerance has appeared to be one of the foremost trait to overcome this situation. Relative magnitude of variances depicted additive and non-additive gene action for the expression of these characters were more extrusive for all the traits studied. GCA and SCA both showed huge collaboration with climate for all the characteristics. Parents NBPGR-36548 (P4), VL-153237 (P5) and BHU QPM-2 (P2) were found to be good general combiners for grain yield per plant, chlorophyll content, oil content and starch content. Indicating that they could be good parental lines in hybridization programs. The scope of heterosis communicated by various crosses was from 0.71 % (P2 X P6) to 45.11% (P5 X P6) in E1, from 0.42% (P1 X P7) to 5.69% (P1 X P8) in E2 and 18.92% (P4 X P8) in E3. The better performing five crosses P5 X P7, P5 X P6, P4 X P8, P5 X P9 and P4 X P5. Crosses between good x average, average x average and good x good shows greater economic heterosis and exhibited high SCA effects for yield under HS. These best Hybrids showed no side effects of leaf firing, tassel blast, root lodging and no severe loss of yield in the present investigation. These crosses additionally should be assessed further multi location in enormous scope.

Pilot development and feasibility of telehealth Community Reinforcement and Family Training (CRAFT) for early psychosis and substance use

Substance use is associated with poor outcomes for individuals with early psychosis. Community Reinforcement and Family Training (CRAFT) is an evidence-based approach that helps families to reduce substance use, engage in treatment, and improve family wellbeing, but it has not yet been studied for psychosis and substance use. The present study aimed to develop and evaluate a telehealth intervention utilizing CRAFT for families experiencing early psychosis and substance use. Twenty family members completed six to eight telehealth sessions of CRAFT adapted for early psychosis (CRAFT-EP). Participants completed an assessment battery at baseline, mid- and post-intervention, a three-month follow-up, surveys after each session, and a focus group to measure mean percentage of sessions completed, mean program satisfaction ratings, telehealth preference, and qualitative feedback. Participants had 100% session completion, and program satisfaction was at or near excellent for 99% of sessions. Half of participants preferred a primarily virtual hybrid program, whereas 45% preferred exclusively virtual visits. Communication was the most helpful topic, and participants requested additional written examples and resources. CRAFT-EP is feasible and acceptable to serve as the active intervention in a pilot randomized controlled trial comparing treatment as usual plus CRAFT-EP to treatment as usual.

Heterogeneous Big Data Parallel Computing Optimization Model using MPI/OpenMP Hybrid and Sensor Networks

For the heterogeneous big data parallel computing model, two levels of parallelism between nodes are not considered, resulting in low efficiency of heterogeneous big data parallel computing and bandwidth to send and receive information, high communication overhead, long model running time and small computational volume. In the paper, we propose an optimization model of heterogeneous big data parallel computing based on a hybrid Multi Point Interface (MPI)/Open Multi-Processing (OpenMP) and Sensor Networks. First, the processor characteristics of heterogeneous big data architecture is analyzed, the parallel tasks among processors are divided, collect the heterogeneous big data to be computed and cluster them, and use the processing results as the input items of the model. Then, a parallel load balancing mechanism is established to optimally divide the parallel computing load of heterogeneous big data, and a parallel computing optimization program is written by combining the hybrid programming mode of MPI and OpenMP and using the hybrid MPI/OpenMP, and finally, the parallel computing optimization of heterogeneous big data is realized by optimizing the parallel communication and determining the model parameters. The results show that the proposed model has a communication bandwidth of 510Mbps, a computational volume of 1.16GB, a model runtime of 24s, and an improved network bandwidth utilization of 93%, which can effectively reduce the communication overhead, and improve the efficiency of parallel computing and bandwidth sending and receiving information in sensor networks, and shorten the model running time.

Response on Phenological, Fruiting Behaviour and Growth Characteristics of F1 Candidates Rootstock Seedlings of Peach [Prunus persica (L.) Batsch

Aim: The aim of present study was to evaluate the flowering and fruiting behaviour of different variety of peach, plum along with growth characteristics of their F1 hybrids and identification hybrid rootstocks for future genetic improvement.
 Study Design: The experiment was designed in Randomized Block Design Factorial with three replications.
 Place and Duration of Study: Rootstock hybridization programme were carried out at main fruit research station Punjab Agricultural University, Ludhiana, Punjab during 2016-17 and 2017-18.
 Methodology: Rootstock hybridization programme were carried out with three varieties two peach namely Sharbati and Flordaguard and one plum Kala amritsari and study the phenological, fruiting behavior and growth performance of seedlings of parents and F1 hybrids.
 Results: Higher days from full bloom to maturity take by Sharbati × Flordaguard (129.4 Days) and minimum in Kala amritsari × Flordaguard (111.1 Days). For completion of stratification seeds of Sharbati and Sharbati × Flordaguard took maximum days for stratification (90-105 Days and 30-105 Days, respectively) and minimum in Flordaguard (30-60 Days). Seed germination % higher in Flordaguard (97.15%) and minimum in Sharbati × Kala amritsari (70.81%). Pollen viability in stored and fresh pollen was highest in Flordaguard (96.26 and 97.58%), while, minimum in Sharbati (90.89% and 96.60%). Leaf colour values (L, a, b, chroma and hue) maximum were in Sharbati and minimum in Flordaguard and leaf colour values of both hybrids, were as Flordaguard. Maximum chlorophyll (SPAD units) were recorded in Flordaguard × Sharbati (42.87) which was at par with the SAPD values of Sharbati × Flordaguard. Leaves of Flordaguard and both the hybrids showed dark reddish green colour on upper and light reddish green in lower side of leaves. Seedlings of Sharbati, Sharbati × Flordaguard and Flordaguard × Sharbati showed better growth characteristics as compares to seedlings of Flordaguard.
 Conclusion: The advance candidate hybrid rootstocks may be useful for further exploitation for genetic improvement and development of rootstock with good nursery characters.

How PMHNP Program Directors Facilitate Psychotherapeutic Skill Acquisition.

The use of psychotherapy has a long history within psychiatric-mental health nurse practitioner (PMHNP) practice. Underutilization of psychotherapy in practice has potentially led to a reduced emphasis in the PMHNP curriculum. To date, no national survey has solely evaluated how PMHNP programs ensure psychotherapy skill acquisition. Survey the PMHNP programs within the United States on how psychotherapy skill acquisition is achieved, including (a) psychotherapeutic curricular content; (b) psychotherapy related clinical practicum hours, including simulation and preceptor-delivered hours; and (c) student interest in psychotherapy skills. Three rounds of e-mail invitations were sent to all PMHNP programs within the United States. Descriptive statistics and reflective thematic analysis were used to examine survey content. There were 39 (27%) respondents, representing the U.S. regions equally. The most common forms of psychotherapy taught were cognitive-behavioral and motivational interviewing. The content was most often delivered through a hybrid program (65.8%). Psychotherapy clinical hours most often used in psychology and social work were varied (0-720, SD 132.9) and were usually (63.89%) separate from other clinical hours. Qualitative responses focused on increased emphasis on the use of psychotherapy within PMHNP programs and the need to develop competency checklists for psychotherapy skill acquisition to use with simulation. This survey reported on both similarities and differences in how PMHNP programs ensure student competency in the skill acquisition of psychotherapy. While this article focuses on what skills are needed in psychotherapy education, direction on how programs deliver this content to their students to ensure this skill will be retained in practice is a critical next step.

Principal component analysis for yield and its attributing characters of pearl millet (Pennisetum glaucum [L.] R.Br.)

An experiment was conducted at Agricultural Research Station, Navgaon (Alwar) during kharif season of 2019 to study the genetic divergence among 31 genotypes of pearl millet based on quantitative data of grain yield and its nine component traits using hierarchical cluster and principal component analysis (PCA). Principal Component Analysis (PCA) indicated that three components with eigen values more than one accounted for about 73.35% of the total variation among nine quantitative characters responsible for seed yield in pearl millet genotypes. The principal components PC1, PC2 and PC3 contributed about 37.44%, 22.63% and 13.28%, respectively to the total variation. The first principal component exhibited high positive loading for grain yield, stover yield, plant height, spike length, spike thickness and 1000-grain weight which contributed more to the diversity. The second principal component showed high loading for days to 50% flowering, days to maturity and 1000-grain weight. Cluster analysis grouped the genotypes into five clusters indicated that grain yield, stover yield, 1000-grain weight and days to maturity contributed maximum towards genetic divergence. The grouping patterns of genotypes in principal component analysis and cluster analysis were almost in agreement with each other with minor deviations. The maximum inter cluster distance between genotypes of cluster V and III with cluster II, indicate that genotypes included in these clusters have high heterotic response and produce better seggregants of used in Pearl millet hybridization programme.

Runko: Modern multiphysics toolbox for plasma simulations

runko is a new open-source plasma simulation framework implemented in C++ and Python. It is designed to function as an easy-to-extend general toolbox for simulating astrophysical plasmas with different theoretical and numerical models. Computationally intensive low-level kernels are written in modern C++ taking advantage of polymorphic classes, multiple inheritance, and template metaprogramming. High-level functionality is operated with Python scripts. The hybrid program design ensures good code performance together with ease of use. The framework has a modular object-oriented design that allows the user to easily add new numerical algorithms to the system. The code can be run on various computing platforms ranging from laptops (shared-memory systems) to massively parallel supercomputer architectures (distributed-memory systems). The framework supports heterogeneous multiphysics simulations in which different physical solvers can be combined and run simultaneously. Here, we showcase the framework’s relativistic particle-in-cell (PIC) module by presenting (i) 1D simulations of relativistic Weibel instability, (ii) 2D simulations of relativistic kinetic turbulence in a suddenly stirred magnetically-dominated pair plasma, and (iii) 3D simulations of collisionless shocks in an unmagnetized medium.

Parallelization of Array Method with Hybrid Programming: OpenMP and MPI

For parallelization of applications with high processing times and large amounts of storage in High Performance Computing (HPC) systems, shared memory programming and distributed memory programming have been used; a parallel application is represented by Parallel Task Graphs (PTGs) using Directed Acyclic Graphs (DAGs). For the execution of PTGs in HPC systems, a scheduler is executed in two phases: scheduling and allocation; the execution of the scheduler is considered an NP-complete combinatorial problem and requires large amounts of storage and long processing times. Array Method (AM) is a scheduler to execute the task schedule in a set of clusters; this method was programmed sequentially, analyzed and tested using real and synthetic application workloads in previous work. Analyzing the proposed designs of this method in this research work, the parallelization of the method is extended using hybrid OpenMP and MPI programming in a server farm and using a set of geographically distributed clusters; at the same time, a novel method for searching free resources in clusters using Lévy random walks is proposed. Synthetic and real workloads have been experimented with to evaluate the performance of the new parallel schedule and compare it to the sequential schedule. The metrics of makespan, waiting time, quality of assignments and search for free resources were evaluated; the results obtained and described in the experiments section show a better performance with the new version of the parallel algorithm compared to the sequential version. By using the parallel approach with hybrid programming applied to the extraction of characteristics of the PTGs, applied to the search for geographically distributed resources with Lévy random walks and applied to the metaheuristic used, the results of the metrics are improved. The makespan is decreased even when the loads increase, the times of the tasks in the waiting queue are decreased, the quality of assignments in the clusters is improved by causing the tasks with their subtasks to be assigned in the same clusters or in cluster neighbors and, finally, the searches for free resources are executed in different geographically distributed clusters, not sequentially.

Genetic Diversity Analysis for Yield and Morpho-physiological Traits in Elite Rice (Oryza sativa L.) Genotypes under Semi-dry System Through D2 Statistics

Genetic divergence is a useful tool for choosing the parents to employ in a hybridization program. The current study was conducted at Agricultural College, Aswaraopet, Telangana, to evaluate genetic diversity among 30 rice genotypes during Kharif 2021 using D2 analysis under a semi-dry system. Based on the analysis, thirty genotypes were divided into ten clusters based on D2 values. Cluster II was found largest with twelve genotypes followed by cluster I with ten genotypes and clusters III, IV, V, VI, VII, VIII, IX, and X had one genotype each, indicating that there was a sizable amount of variation among the genotypes. Cluster II (284.13) had the highest intra-cluster D2 value, followed by cluster I. (242.63) while the highest inter-cluster distance was found between Cluster VIII and IV (1503.42) followed by cluster VI and IV (1316.83), cluster VI and III (1316.15), cluster IX and IV (1303.55), cluster VIII and X (1261.09), cluster VIII and IX (1132.95), V and III (1113.91), and cluster VII and V (1101.7) suggesting that crosses involving lines from these clusters would produce wider and more desirable recombination. The average inter-cluster distance for Cluster VIII and VI was the lowest (231.01), followed by Cluster IX and X (394.3) and Cluster III and IV (397.72). The genotypes of these clusters have the most gene complexes, as shown by the shortest inter-cluster distance. The findings revealed that root biomass contributed the most to genetic divergence (24.59 percent), ranking first followed by total biomass (21.60%), root length (17.70%) and grain yield/plant (14.02%), culm strength (8.04%), plant height (5.74%), 1000 grain weight (4.36 %). The traits viz., root biomass, total biomass, root length, grain yield/plant, and culm strength contributed 85.95% of the total deviation and need to be exploited to develop varieties suitable for the semi-dry system in rice. The genotypes BPT 5204, WGL 697, RNR 21278, RNR 28361, WGL 915, PR 126, and JGL 28545 were to be better for further hybridization programs to develop varieties for the semi-dry system.

Evaluation of The Instructor-Student Interaction in Online Classes: Instructors’ Perspective

Due to the COVID-19 pandemic, the learning process shifted from face-to-face learning to online learning as schools and universities were closed almost worldwide. After the pandemic restrictions, it seems that many educational institutions continue to offer online courses as an alternative to face-to-face classes, or they have begun to implement hybrid programs in which the students have both face-to-face and online courses. With the shift from face-to-face to online learning, the learning process has been affected negatively from different perspectives with varying degrees; however, the interaction between instructors and students has become more challenging to pursue at expected levels. Students tend to avoid interacting for many different reasons in the online learning process, or the instructors have some obstacles to a sound interaction with their students. By exploring the experiences and perceptions of the English language instructors, this descriptive study aimed to examine the perceptions of instructors regarding teacher-student interaction in online classes, the challenges faced by the practitioners, and their suggestions for course designers, policymakers and other related stakeholders. The researchers employed a qualitative research approach. The participants were 17 instructors working at the school of foreign languages at a state university. Semi-structured interviews were conducted to collect the qualitative data. The data was analysed by following the content analysis procedures. The findings reported insights into the interaction issues in online classes; the instructors had negative perceptions of the interaction in online classes due to the challenges they faced. In the light of the qualitative data, the present research offers valuable suggestions for decision-makers and practitioners, such as taking the participation of the learners into consideration in assessments and providing in-service training programs for EFL instructors.

Principle Component Analysis and Diversity Studies in Sunflower Lines (Helianthus annuus)

Background: Sunflower crop being a highly cross pollinated with high yield potential, can be grown in all seasons with its suitability in variety of inter and series cropping systems due to its photo insensitive nature and can be adapted to a variety of environmental conditions also. So keeping in mind of its potential and future use, research was conducted with available lines to study PCA and its diversity that might be used in hybridization programmes. Methods: The 45 lines of sunflower were grown in a randomised block design with three replications at the Research Farm, Department of Genetics and Plant Breeding, College of Agriculture, Vijayapur during summer 2018-19 for study on principal component analysis and diversity analysis. Result: At the genotypic stage, the analysis of variance showed highly significant variations among the genotypes for all of the characters. Whereas Divergence analysis using principal component analysis and hierarchical cluster analysis has been shown to be effective in determining which genetically distant parents should be used for hybridization. Divergence in genotypes were divided into nine major groups or clusters and out of nine components, four components had more than one eigen value (Table-2). The first principal component explained 33.40 per cent of total variation, while the second, third, fourth, fifth, sixth, seventh, eighth and ninth principal components explained 23.30, 14.10, 11.19, 6.30, 4.90, 3.60, 1.90 and 0.60 per cent, respectively.

Embracing brain and behaviour: Designing programs of complementary neurophysiological and behavioural studies

AbstractNeuroIS—the methods and knowledge of neuroscience applied to the information systems (IS) domain—has become an established research field within the IS discipline. A key advantage of NeuroIS is its ability to provide insights into human cognition beyond those obtained using behavioural techniques alone. Nevertheless, in neuroscience, there is renewed interest in examining behaviour together with neurophysiological methods to better inform our understanding of neural processes. In this research opinion article, we argue that in the field of NeuroIS, there is an opportunity for hybrid programs of study that combine neurophysiological and behavioural methods in a complementary manner. We outline four strategies for designing complementary neurophysiological and behavioural experiments in a research program: (1) observe the relationship between neural processes and behavioural change; (2) combine neurophysiological and behavioural methods to enhance internal, external, and ecological validity; (3) extend, rather than replicate, experiments based on theory; and (4) use neurophysiological and behavioural experiments together to evaluate IT artefact design. By applying these strategies, researchers can more effectively design programs using complementary neurophysiological and behavioural methods, which, in turn, can help to provide richer insights into the phenomena under study as well as accelerate the advancement of IS knowledge.

Genetic Diversity and Correlation Coefficient Studies in Muskmelon (Cucumis melo L.)

Background: Genetic diversity provides opportunity for plant breeders to develop new and improved cultivars with desirable characteristics, which include both farmer-preferred traits (yield potential and large seed, etc.) and breeder preferred traits (pest and disease resistance and photosensitivity, etc.). Yield being a complex quantitative character, direct selection for yield may not result in successful improvement. Information on character association and direct and indirect effects of component traits on yield would greatly help in formulating the selection criteria and using them effectively in crop improvement programme. Therefore present study was aimed to evaluate genetic diversity in 25 muskmelon genotypes. Methods: 25 muskmelon genotypes were evaluated at Dr. Y.S.R Horticultural University, College of Horticulture, Anantharajupeta, during 2017-2018 in randomized block design with three replications. Genetic diversity among genotypes was estimated using Mahalanobis D2 statistics. Result: Cluster analysis revealed distinctive clustering pattern and grouped the genotypes in to seven clusters. cluster II was the largest comprising of eight genotypes, while cluster III, IV, VI, VII consist of only one genotype. Cluster VII and IV were found to be considerably different from the rest of the clusters. Genotypes falling in these clusters which are genetically more diverse, can be exploited in a hybridization programmes. Genetic variability in terms of correlation analysis were studied for yield and yield attributing traits. Fruit yield had a positive correlation with fruit volume, fruit diameter, number of fruits per plant, fruit weight and flesh thickness. While it had a negative correlation with days to appearance of first pistillate flower and days to first fruit harvest.

Genetic diversity using principal component analysis and hierarchical cluster analysis in rice

A set of 100 germplasm lines with four checks viz., BPT-5204, PSB-68, Siri1253 and MGD-101 were evaluated in augmented block design during Kharif 2020. The observations were documented for 5 quantitative traits viz., days to 50% flowering, panicle length, number of panicles per square meter, 1000 grain weight and grain yield by principal component analysis and cluster analysis to determine the relationship and genetic divergence among the individuals. The cumulative variance of 55.60% was explained by 1st two principal components (PC1 and PC2) with eigen values greater than 1. Component 1 with variance of 32.10% had contribution from days to 50% flowering, panicle length, panicles per square meter and grain yield while principal component 2 accounting 23.50% total variability has contribution from days to 50% flowering and panicles per square meter. The remaining variability of 17.68%, 16.10% and 10.60% was consolidated in PC3, PC4 and PC5. Results from cluster analysis grouped 100 germplasm lines into four clusters with minimum individuals constituted in cluster 1 and maximum individuals were found in cluster 4. The lines in cluster 1 (2.62) showed maximum divergence followed by cluster 3 (2.23). The maximum inter cluster Euclidean distance was observed between clusters 2 and cluster 3 followed by cluster 1 and cluster 2 giving a scope for selection of parents for hybridization programme from these clusters to realize high genetic variation and novel combinations for yield increment.

Unravelling the G × E interactions using AMMI biplot for phenology and agro-morphological traits in linseed (Linum usitatissimum L.)

In the present study, additive main effects and multiplicative interactions (AMMI) biplot analysis was used to identify stable genotypes for days to flowering, maturity, plant height and number of branches per plant to dissect GEI in linseed. Trials were conducted in randomized complete block design with two replications over three consecutive years(2016-17, 2017-18 and 2018-19). ANOVA analysis revealed genotype and G×E interaction effects contributed significant sumofsquare for days to flower (97.31% and 0.56%); days to maturity (89.27% and 8.90%); plant height (98.29% and 0.70%) and number of branches per plant (86.40% and 2.41%respectively). The dissection of GE interaction for all the traits was mostly explained by the first and second principal component axis (IPCA1 and IPCA2). The SSI statistic fully sync with the results of the AMMI1 biplot analysis for all the traits of top ranked genotypes across the environments. Results of genotypes stability in AMMI1 and AMMI2 biplot analyses were shown differential response with some exceptions that indicates the different sets of genes were responsible for the cumulative expression of traits under study. In the present study environments imposed variable effects with few exceptions towards the genotype stability in both AMMI1 and AMMI2 analysis models for all the traits studied. Hence, the desirable genotypes identified in linseed for phenology and agro-morphological traits could be utilized in hybridization program and varietal recommendation under semi-arid conditions.