Variation In Estimates Research Articles

Estimation of Genetic Variability, Correlaton for Yield and Yield Compoments in Rice (Oryza sativa L.)

The present study consists of 23 rice genotypes including one check variety that were evaluated at Field Experimentation Centre of the Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (Allahabad), U.P. to study genetic variability, correlation and path coefficient for 13 quantitative characters. The experiment was conducted by using Randomized Block Design with three replications during Kharif -2021. Observation recorded to study the genetic variability parameters, correlation coefficient and path coefficient for yield and its attributing traits. On the basis of mean performance BPT-3291 was found to be superior in grain yield per hill followed by, SIGNET-5455, KSR-140 and RNR-15048 showed higher yield over the check (NDR359). High to moderate estimates of GCV and PCV were recorded for number of spikelets per panicle followed by number of tillers per hill, harvest index, biological yield, grain yield per hill, flag leaf width, test weight and number of panicles per hill. Grain yield indicated significant positive correlation with plant height followed by tillers per hill, panicles per hill, biological yield and harvest index in terms of phenotypic correlation coefficient whereas in terms of genotypic coefficient it showed positive and significant correlation. Path coefficient analysis showed positive significant direct effects on Biological Yield, Harvest Index and Number of Spikelets per Panicle at genotypic level whereas it showed positive and significant direct effect for days to fifty percent flowering, plant height, flag leaf width, number of panicles, test weight, biological yield, and harvest index at phenotypic level. Thus, these traits are identified as the efficient and potential for indirect selection for the improvement of rice productivity in the present experimental materials.

Estimates of genetic variability, inter character association and path analysis in turmeric over environments

Pooled data of 27 traits, including quantitative and qualitative, from 15 turmeric varieties grown in three locations over two years were used to estimate the genetic parameters of variability and path analysis. High genotypic coefficient of variation (GCV) combined with high phenotypic coefficient of variation (PCV) was observed for collar girth, length of mother rhizome, number of mother rhizomes, weight of mother rhizome, weight of primary rhizome, number of secondary rhizomes, primary rhizome inter-nodal length, bisdemethoxycurcumin (BDMC), demethoxycurcumin (DMC), curcumin (CUR) and yield. High heritability coupled with high genetic advance as per cent mean (GAM) was recorded for plant height, number of shoots, leaf petiole length, leaf length, collar girth, length of mother rhizome, girth of mother rhizome, primary rhizome inter-nodal length, dry recovery, oleoresin, BDMC, DMC and curcumin. Correlation coefficients showed that yield was significantly associated with collar girth, weight of mother rhizome, number of primary rhizomes, weight of primary rhizome and number of secondary rhizomes. Path coefficient analysis at phenotypic level revealed that, positive direct effect was high for length of mother rhizome followed by number of mother rhizomes, weight of primary rhizome and curcumin content. The study confirmed that characters such as weight of mother rhizome, girth of mother rhizome, weight of primary rhizomes, number of primary rhizomes and curcumin content can be relayed upon to form selection criteria in turmeric.

Spatiotemporally variable incident light, leaf photosynthesis, and yield across a greenhouse: fine-scale hemispherical photography and a photosynthesis model

Although greenhouse agriculture can generate high crop yields, they vary due to spatiotemporal differences in incident light and photosynthesis. To elucidate these dynamics, multipoint analysis of hemispheric images and a photosynthesis model were used to visualize the spatiotemporal distribution of photosynthetic photon flux density (PPFD) and leaf photosynthetic rate (A) and compared these with strawberry fruit yield in a greenhouse. This method enabled successful estimation of spatiotemporal variability in PPFD and A with relative root mean square errors of 4.4% and 11.0%, respectively. PPFD, captured at ca. 2 m resolution, varied diurnally and seasonally based on sun position and external light intensity. A showed less spatial variability, because it is reduced by physical and physiological mechanisms in the leaves at excessive leaf temperatures and becomes saturated at high PPFD. Yield spatial variability was better explained by A than by PPFD. The association between A and yield weakened over the cultivation period (R2 declined from 46% in winter to 12% in spring), thus suggesting that, over the cultivation period, factors such as photoassimilate availability replaced A as the primary limiting factor. The proposed method can be directly applied to other types of greenhouses, and the findings may facilitate spatiotemporal optimization in crop production, improving precision greenhouse agriculture.

Third Dose of the BNT162b2 Vaccine Results in Sustained High Levels of Neutralizing Antibodies Against SARS-CoV-2 at 6 Months Following Vaccination in Healthy Individuals.

Third Dose of the BNT162b2 Vaccine Results in Sustained High Levels of Neutralizing Antibodies Against SARS-CoV-2 at 6 Months Following Vaccination in Healthy Individuals.

Statistically rigorous, model-based inferences from maps

Statistically rigorous inferences in the form of confidence intervals for map-based estimates require model-based inferential methods. Model-based mean square errors (MSE) incorporate estimates of both residual variability and sampling variability, of which the latter includes population unit variance estimates and pairwise population unit covariance estimates. Bootstrapping, which can be used with any prediction technique, provides a means of estimating the required variances and covariances.The objectives of the study were to to demonstrate a method for estimating the sampling variability, Var̂samμ̂, that can be used with all prediction techniques, to develop an efficient method that map makers can use to disseminate metadata that facilitates calculation of Var̂samμ̂ for arbitrary subregions of maps, and to estimate the individual contributions of sampling variability and residual variability to the overall standard error of the prediction of the population mean.The primary results were fourfold: (i) map makers must provide metadata that facilitate estimation of population unit variances and covariances for arbitrary map subregions, (ii) bootstrapping was demonstrated as an effective means of estimating the variances and covariances, (iii) the very large matrix of pairwise population unit covariances can be aggregated into a much smaller matrix that can be readily communicated by map makers to map users, and (iv) MSEs that include only estimates of residual variability and/or estimates of population unit variances, but not estimates of the pairwise population unit covariances, grossly under-estimate the actual MSEs.

Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2

Abstract. The Antarctic marginal ice zone (MIZ) is a highly dynamic region where sea ice interacts with ocean surface waves generated in ice-free areas of the Southern Ocean. Improved large-scale (satellite-based) estimates of MIZ extent and variability are crucial for understanding atmosphere–ice–ocean interactions and biological processes and detection of change therein. Legacy methods for defining the MIZ are typically based on sea ice concentration thresholds and do not directly relate to the fundamental physical processes driving MIZ variability. To address this, new techniques have been developed to measure the spatial extent of significant wave height attenuation in sea ice from variations in Ice, Cloud and land Elevation Satellite-2 (ICESat-2) surface heights. The poleward wave penetration limit (boundary) is defined as the location where significant wave height attenuation equals the estimated error in significant wave height. Extensive automated and manual acceptance/rejection criteria are employed to ensure confidence in along-track wave penetration width estimates due to significant cloud contamination of ICESat-2 data or where wave attenuation is not observed. Analysis of 304 ICESat-2 tracks retrieved from four months of 2019 (February, May, September and December) reveals that sea-ice-concentration-derived MIZ width estimates are far narrower (by a factor of ∼ 7 on average) than those from the new technique presented here. These results suggest that indirect methods of MIZ estimation based on sea ice concentration are insufficient for representing physical processes that define the MIZ. Improved large-scale measurements of wave attenuation in the MIZ will play an important role in increasing our understanding of this complex sea ice zone.

Assessment of Variability, Heritability and Genetic Advance in 20 Genotypes of Gladiolus (Gladiolus grandiflorus L.)

This study was undertaken to find out the estimates of genetic variability, analysis of variance, genetic parameters viz GCV, PCV, heritability and genetic advance among different flower traits between 20 genotypes of gladiolus. The experiment was repeated three times by using RBD (Randomized block design) at crop research centre, Department of Genetics and Plant Breeding, School of Agriculture, ITM University, Gwalior, Madhya Pardesh. Analysis of variance indicated highly significant difference for all the trait among 20 genotypes. The estimate of heritability varied from 92% to 42%. The highest heritability was estimated in broad sense was observed for the character leaf area (92.01%) and lowest for weight of daughter corms (42%). The genetic advance expressed as percent of mean ranged from 7.65% to 55.82%. The highest of genetic advance as percentage of mean was recorded for no. of shoots per corm (55.82%) and lowest for spike initiation (7.65). Environmental coefficient of variance (ECV) ranged from (2.72 to 37.13). the highest ECV was recorded for the character weight of daughter of corms (37.13) and lowest for days to spike initiation (2.72). Key words: Gladiolus, GCV, PCV, Heritability, Genetic Advance as percentage of mean

Performance, Heritability and Correlation Studies on Maize (Zea Mays L) Genotypes Under Irrigated Condition in Central Sudan

These experiments were conducted in two different sites to study the genetic variability and the mean performance of the elite different origin maize genotypes under irrigated condition in central of the Sudan on rainy season 2014. The experiments were arranged in randomize complete block design in three replicates, the data were collected on days to 50% tasseling and silking, plant and ear height, ear length and diameter and grain yield. The analysis of variance for each site and a cross sites showed a significant variability among tested genotypes for grain yield, days to 50% tasseling and silking, plant and ear height, ear length and diameter. Also, significant different were observed for genotypes, site and a cross site for most of studied traits such as for grain yield, days to 50% tasseling and silking, plant and ear height, ear length and diameter. The combined results for genotypic coefficients of variability and broad sense heritability estimates grain yield, ear length and ear diameter varied significantly among the tested genotypes.

Genetic Diversity For Zinc , Iron and Yeild Contributing Characters in Pearl Millet [Pennisetum glaucum (L.) R.Br.] Genotypes

The most widely grown drought-tolerant warm-season coarse grain cereal, Pearl Millet [Pennisetum glaucum (L.) R.Br.] is grown on almost 26 million ha. Pearl Millet is India's fourth most extensively and widely produced food crop. This study aims for estimation of genetic variability among fifty-two genotypes of Pearl Millet were grown at Bajra Research Scheme, College of Agriculture, Dhule, (MS) during Kharif, 2020, in a Randomized Block Design with three replications. The maximum inter-cluster distance (D2) were observed between clusters VI and VII (23.06) and cluster minimum between II and III (8.23). The significant differences due to genotypes with high range (D2) value clearly indicated the presence of adequate diversity among genotypes studied. Among the genotypes divergence contributed maximum (41.63%) to iron content, followed by plant height (19.23%), panicle girth (15.16%), test weight (6.86%), days to flowering (5.13%), yield per plant (4.15%), panicle length (4.00%), and zinc content (3.39%)etc. Hence, this traits suggested important indices for selection of superior genotypes of pearl millet in breeding programs.

Multiple Lines of Evidence for Estimating NSZD Rates Overlying a Shallow LNAPL Source Zone

AbstractQuantitative methods of monitoring natural source zone depletion (NSZD) via biodegradation of petroleum hydrocarbons (PHC) are required to investigate source zone longevity and guide long‐term management of PHC impacted sites. Vadose zone NSZD processes can be monitored using analysis of surficial CO2 effluxes, soil‐gas gradients, and thermal gradients. This study describes an applied research and development program conducted at a former refinery site over a 4‐year period (2015 to 2019) on quantitative technologies for evaluation of NSZD of PHC light nonaqueous phase liquid (LNAPL) present within a shallow soil zone. A multiyear study using discrete CO2 efflux measurements from dynamic closed chambers was compared with estimates obtained using static traps and continuous monitoring using forced diffusion (FD) technology. Thermistor strings along a transect were used to monitor hourly thermal gradients and assess NSZD rates using the temperature gradient method. Discrete soil‐gas data were used to quantify the vertical oxygen gradient to estimate NSZD rates using the concentration gradient method (CGM). Results of discrete and continuous monitoring methods provide estimates of monthly NSZD rates that range seasonally from 80 to 1300 US gal/acre/year using radiocarbon corrected CO2 efflux method for decane (C10H22) equivalent, 120 to 1600 US gal/acre/year using CGM (for wet to dry conditions) and 400 to 2000 US gal/acre/year using the temperature gradient method. Both seasonal temperature and precipitation fluctuations contribute to variability in rates. Continuous methods are shown to provide for improved resolution of temporal variability and seasonal estimates, although discrete methods provide for improved spatial quantification.

Spatial and temporal variations of rainfall erosivity in the middle Yellow River Basin based on hourly rainfall data

Understanding spatial and temporal variations in rainfall erosivity is essential for estimating the variability in soil erosion. However, rainfall erosivity in the middle Yellow River Basin is usually calculated based on daily rainfall data, which fails to consider the impact of the changing rainfall intensity at the subdaily scale. In this study, we collected hourly rainfall data from 355 meteorological stations within and around the region to calculate rainfall erosivity during 1960–2017. We found that the rainfall erosivity calculated based on hourly data had much larger variability than that calculated based on daily data, and the calculated spatial and temporal variability were substantially different in periods when the rainfall intensity was highly variable. Based on our new estimation, we found that the spatial distribution of rainfall erosivity was highly heterogeneous, with high erosivity values in the Loess Regions and Rocky Mountain Regions with high soil erodibility and low erosivity values in the Aeolian Regions and Soft Sandstone Regions with low soil erodibility. This heterogeneity was mainly due to the distinct spatial distribution patterns of rainfall amount and rainfall intensity. Although the long-term increasing trend of rainfall erosivity was statistically insignificant from 1960 to 2017, its rate of increase was higher than that of the annual rainfall amount. Decadal changes showed a slight decrease from the 1960 s to the 1980 s and an increase since the 1990 s, which was substantially different from the decadal changes in the annual rainfall amount. These differences in temporal variability were mainly caused by the contribution of changing rainfall intensity, which was greater in the Aeolian Regions and Soft Sandstone Regions than in the other subregions. Our study highlighted the importance of considering the changing rainfall intensity at a subdaily scale in semiarid and semihumid climate zones and provided the first estimation of the long-term variability in rainfall erosivity based on hourly rainfall data in this region.

Estimation of variability in soil water content in a forested critical-zone experimental catchment in Eastern China

Knowledge of soil water content (SWC) dynamics within soil profiles is crucial for the effective management of water and soil resources. This study aims to clarify the temporal variability and stability of SWC in a forested critical-zone experimental catchment, and further to improve the understanding of the temporal and spatial distribution of soil water in a typical hilly catchment in eastern China. The selected Nandadish (NDD) catchment covering 0.79 ha was instrumented with 34 SWC monitoring sites using Frequency Domain Reflectometry. The consecutive high-resolution monitoring data of soil water at different depths of the sites were collected from January 2017 to December 2019. The results showed that the SWC of the shallow layer (0–30 cm) had the strongest variability over time during the three hydrologic years. The interannual variability of SWC showed the opposite regularity with that of the seasonal variability. Specifically, the spatial variability of SWC in the dry years was greater than that in wet years; whilst the temporal stability of SWC in dry seasons was greater than that in rainy seasons. Precipitation and temperature were the two dominant factors influencing the temporal variation of SWC. Precipitation controlled the interannual variation of SWC, while temperature controlled the seasonal variation of SWC. Additionally, soil water had high temporal stability throughout the observation period in NDD catchment, and the most representative point was located at a relatively flat and central place, which can be used to simulate the variability of SWC under different rainfall conditions in the study area. The temporal stability of SWC patterns was controlled by topography, geographic location, throughfall, and the groundwater level in the study area, which was characterized by sloping terrain and forested cover. This research provides scientific bases for the optimum design of ground sampling, and the temporal and spatial prediction for soil moisture in a typical eastern hilly area with forest land uses.

Sex Differences in Estimates of Cardiac Autonomic Function Using Time Domain based Method of Heart Rate Variability: Effects of Oral Capsaicin

Heart rate variability (HRV) estimates autonomic nervous system (ANS) influence on the heart and is sex‐specific. Sensory afferents exhibit sex‐specificity; although, there is a paucity of data on the potential effects of Capsaicin, an agonist for transient receptor potential vanilloid channel‐1 (TRPV1), on cardiac ANS activity and if the effect is sex‐dependent. Given the predictive nature of HRV on risk of developing hypertension, understanding the sex differences in factors governing HRV is paramount.PURPOSETherefore, this study sought to determine the sex‐specificity in the effect of capsaicin on cardiac autonomic function estimated through HRV. It was hypothesized that females would have lower HRV than the age‐matched males and that capsaicin could attenuate these sex differences.METHODSHRV was measured in 38 young males (M: n=25) and females (F: n=13), in a blinded crossover design, after acute ingestion of placebo or capsaicin capsules. Resting measurements of HR, RR interval, root mean square of successive differences (RMSSD), natural log‐transformed RMSSD (LnRMSSD), standard deviation of n‐n intervals (SDNN), number of pairs of successive n‐n intervals that differ by more than 50 msec (NN50), and percent NN50 to total n‐n intervals (PNN50) were obtained using standard techniques.RESULTSUnder placebo, males had significantly lower minimum HR (M: 49±9.7 vs. F: 58±16 beats/min, p=0.038, d=‐0.738) and significantly higher NN50 (M: 141±118 vs. F: 33±23, p=0.003, d=‐0.129) than females. There was a main effect of sex on HR (M: 59±9.3 vs. F: 65±12 beats/min, p=0.036, η2=0.098), minimum HR (M: 47±8.3 vs. F: 56±12 beats/min, p=0.014, η2=0.124), and NN50 (M: 177±143 vs. F: 29±17, p<0.001, η2=0.249). There was a significant interaction of sex and treatment (p=0.02, η2=0.027) for RMSSD, where males increased (Placebo: 78±55 vs. Capsaicin: 91±64 ms), and females decreased (Placebo: 105±83 vs. Capsaicin 76±43 ms).CONCLUSIONThis study recapitulates previously documented sex differences in HR and HRV. Acute ingestion of capsaicin increased RMSSD in men, but decreased RMSSD in women, suggesting a sexual dimorphism in parasympathetic response, perhaps due to differences in TRPV1‐sensitive afferents or sensitivity. The physiological ramifications of these findings, specifically in the regulation of blood pressure and ultimately cardiovascular disease risk remain to be explored, especially in the transition to menopause in women.

Estimating rainfall depth from satellite-based soil moisture data: A new algorithm by integrating SM2RAIN and the analytical net water flux models

Sparse distribution of rain gauge networks challenges the estimation of rainfall variability over space and time. The SM2RAIN algorithm was developed to estimate rainfall from the knowledge of soil moisture (SM) by inverting the soil‐water balance equation. The algorithm was simplified by neglecting the contribution of evapotranspiration and surface runoff rate during the rainfall event. A recent study developed an analytical model to estimate the net water flux (NWF) from SM data via inversion of analytical Warrick’s equation. In this study, the SM2RAIN-NWF algorithm was developed by integrating the SM2RAIN algorithm and the NWF model to improve the accuracy of rainfall estimation. The applicability of the SM2RAIN-NWF algorithm was evaluated based on observed rainfall data in the Lake Urmia basin, Iran. Satellite SM data was obtained from the Advanced Microwave Scanning Radiometer 2 (AMSR2). The algorithm calibrated based on the data from July 3, 2012, to December 31, 2017, was then used to estimate rainfall for two years extending from January 2018 to December 2019. Estimated rainfall through SM2RAIN-NWF algorithm improved compared to SM2RAIN by 14% and 37.4% increase in the average values of correlation coefficient (R) and Nash–Sutcliffe (NS), and 11.5% decrease in the Percentage Root Mean Square Error (PRMSE) over the calibration period. Validating the estimated rainfall showed a considerable improvement in the performance of the SM2RAIN-NWF algorithm compared to the SM2RAIN algorithm by 8.6% and 30.4% increase in the average values of R and NS, and 13.4% decrease in the PRMSE. It was also found that the SM2RAIN-NWF algorithm contributes to the improvement of error indices in rainfall estimation and simulates the rainfall variation trend in a better fashion than the SM2RAIN algorithm.

Characterization of population variability of 1,3-butadiene derived protein adducts in humans and mice

1,3-butadiene is a known human carcinogen and a chemical to which humans are exposed occupationally and through environmental pollution. Inhalation risk assessment of 1,3-butadiene was completed several decades ago before data on molecular biomarkers of exposure and effect have been reported from both human studies of workers and experimental studies in mice. To improve risk assessment of 1,3-butadiene, the quantitative characterization of uncertainty in estimations of inter-individual variability in cancer-related effects is needed. For this, we ought to take advantage of the availability of the data on 1,3-butadiene hemoglobin adducts, well established biomarkers of the internal dose of the reactive epoxides, from several large-scale human studies and from a study in a Collaborative Cross mouse population. We found that in humans, toxicokinetic uncertainty factor for 99th percentile of the population ranged from 3.27 to 7.9, depending on the hemoglobin adduct. For mice, these values ranged from less than 2 to 7.51, depending on the dose and the adduct. Quantitative estimated from this study can be used to reduce uncertainties in the parameter estimates used in the models to derive the inhalation unit risk, as well as to address possible differences in variability in 1,3-butadiene metabolism that may be dose-related.

Comparison of classical tumour growth models for patient derived and cell-line derived xenografts using the nonlinear mixed-effects framework

In this study we compare seven mathematical models of tumour growth using nonlinear mixed-effects which allows for a simultaneous fitting of multiple data and an estimation of both mean behaviour and variability. This is performed for two large datasets, a patient-derived xenograft (PDX) dataset consisting of 220 PDXs spanning six different tumour types and a cell-line derived xenograft (CDX) dataset consisting of 25 cell lines spanning eight tumour types. Comparison of the models is performed by means of visual predictive checks (VPCs) as well as the Akaike Information Criterion (AIC). Additionally, we fit the models to 500 bootstrap samples drawn from the datasets to expand the comparison of the models under dataset perturbations and understand the growth kinetics that are best fitted by each model. Through qualitative and quantitative metrics the best models are identified the effectiveness and practicality of simpler models is highlighted

Downscaling Satellite-Based Estimates of Ocean Bottom Pressure for Tracking Deep Ocean Mass Transport

Gravimetry measurements from the GRACE and GRACE-Follow-On satellites provide observations of ocean bottom pressure (OBP), which can be differenced between basin boundaries to infer mass transport variability at a given level in the deep ocean. However, GRACE data products are limited in spatial resolution, and conflate signals from many depth levels along steep continental slopes. To improve estimates of OBP variability near steep bathymetry, ocean bottom pressure observations from a JPL GRACE mascon product are downscaled using an objective analysis procedure, with OBP covariance information from an ocean model with horizontal grid spacing of ∼18 km. In addition, a depth-based adjustment was applied to enhance correlations at similar depths. Downscaled GRACE OBP shows realistic representations of sharp OBP gradients across bathymetry contours and strong currents, albeit with biases in the shallow ocean. In validations at intraannual (3–12 month) timescales, correlations of downscaled GRACE data (with depth adjustment) and in situ bottom pressure recorder time series were improved in ∼79% of sites, compared to correlations that did not involve downscaled GRACE. Correlations tend to be higher at sites where the amplitude of the OBP signal is larger, while locations where surface eddy kinetic energy is high (e.g., Gulf Stream extension) are more likely to have no improvement from the downscaling procedure. The downscaling procedure also increases the amplitude (standard deviation) of OBP variability compared to the non-downscaled GRACE at most sites, resulting in standard deviations that are closer to in situ values. A comparison of hydrography-based transport from RAPID with estimates based on downscaled GRACE data suggests substantial improvement from the downscaling at intraannual timescales, though this improvement does not extend to longer interannual timescales. Possible efforts to improve the downscaling technique through process studies and analysis of alongtrack GRACE/GRACE-FO observations are discussed.

Epigenetic patterns in a complete human genome.

The completion of a telomere-to-telomere human reference genome, T2T-CHM13, has resolved complex regions of the genome, including repetitive and homologous regions. Here, we present a high-resolution epigenetic study of previously unresolved sequences, representing entire acrocentric chromosome short arms, gene family expansions, and a diverse collection of repeat classes. This resource precisely maps CpG methylation (32.28 million CpGs), DNA accessibility, and short-read datasets (166,058 previously unresolved chromatin immunoprecipitation sequencing peaks) to provide evidence of activity across previously unidentified or corrected genes and reveals clinically relevant paralog-specific regulation. Probing CpG methylation across human centromeres from six diverse individuals generated an estimate of variability in kinetochore localization. This analysis provides a framework with which to investigate the most elusive regions of the human genome, granting insights into epigenetic regulation.

Genetic variability and multivariate studies on the grain physical properties of rice (Oryza sativa L.) landraces

Thirty rice landraces were evaluated during the 2020 wet season for the estimation of the genetic variability of six grain physical properties, viz. grain length (GL), grain breadth (GB), milled grain length (MGL), milled grain breadth (MGB), milled grain length breadth ratio (MGL/MGB), and 1000-grain weight (TGW), at the Bangladesh Institute of Nuclear Agriculture Substation, Sunamganj, Bangladesh. The relative contribution of these traits to variability was estimated by using principal component analysis (PCA), and the landraces were clustered by using Mahalanobis distance (D2) statistics. The TGW and MGL/MGB ratio exhibited high estimates of the phenotypic coefficient of variation and genotypic coefficient of variation. The high broad-sense heritability and genetic advance of all the traits indicated that the environmental effect had a weak involvement in the expression of these traits. PCA revealed six principal components, among which two were significant and contributed up to 96.9% of the total variance cumulatively. GL, GB, MGL, and TGW contributed to PC1 to create the variation among the landraces, whereas MGL/MGB ratio, GL, and MGL contributed to PC2. The landraces were grouped into six clusters. Cluster analysis revealed that the maximum and minimum intracluster distances were found in cluster III (235.11) and cluster VI (0.00), respectively. The longest intercluster distance was found between clusters IV and VI, and the shortest distance was found between clusters I and III. The maximum mean values for GL and TGW were observed in cluster VI. The mean values for GB and MGB were highest in cluster V, whereas the MGL/MGB ratio and MGL were highest in cluster II. ‘Madhumala’/‘Sada Madhumala’ and ‘Pankhuraj’ could be used in hybridization programs to exploit maximum heterosis for rice grain size and shape and for the direct selection of superior quality traits because these traits are less affected by the environment than other traits.

Estimation of Genetic Variability, Heritability and Genetic Advance in Hybrid RICE (Oryza sativa L.)

The current study was conducted at the Indian Institute of Rice Research (IIRR) to look at the genetic characteristics for quantitative characters in 64 hybrid rice genotypes (Oryza sativa L.). For all of the characters, the analysis of variance indicated significant differences. The characters with the highest phenotypic and genotypic coefficients of variation were productive tillers per plant, filled grains per panicle, and single plant yield (GCV). Plant height, number of productive tillers per plant, number of filled grains per panicle, grain yield per plant, and test weight all had high heritability and genetic advance as a percent of mean, indicating the influence of additive gene action. As a result, simple selection could likely be effective for improving these traits.