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Copyright of Anbar Journal of Agricultural Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study assessed genetic variability among oat genotypes for twelve traits, including yield. Significant differences were found across all traits, with high heritability and genetic advance for the number of effective tillers, 1000-seed weight, and grain yield. Hierarchical clustering using morphometric traits grouped the genotypes into four distinct clusters. We identified 665 potential microsatellites using 1000 contigs from NCBI and designed possible primer pairs to develop PCR-based markers in orphan crop like oats. Validation with a panel of 31 diverse genotypes revealed that seven of ten newly developed markers detected expected alleles, with four being polymorphic. Additionally, eight reported SSRs were used to assess genotypic differences. The markers showed a mean allele richness of 2.86 (range: 2-4) and a mean polymorphism information content (PIC) of 0.37 (range: 0.15-0.96). Cluster analysis indicated three distinct clusters with a mean dissimilarity of 0.54, demonstrating the markers’ effectiveness for genetic diversity assessment and breeding.

A half diallel crossing was carried out between six Inbreeds of maize according to the second Griffing method. The genotypes (parents and the hybrids resulting from them) were planted during the spring and fall seasons of 2022 using a randomized complete block design (R.C.B.D) with three replicates to study genetic and phenotypic correlations and their variations and the path coefficient for traits (number of silking days, plant height, leaf area, number of ears, number of rows per ear, number of grains per row, weight of 500 grains, and grain yield per plant). Analysis of Variance showed highly significant differences between the genotypes for all the studied traits for the fall and spring seasons of 2020. The results indicated that the values of the phenotypic variation coefficient were close to the values of the genetic variation coefficient for most traits. Accordingly, the genotype can be studied by taking phenotypic data, and such traits can be considered as a selection index for improving this crop. The brant yield was (0.874 and 0.6 the number of rows per ear, as they reached (0.691, 0.498, and 0.671) for the spring season, respectively, and (0.701, 0.516, and 0.689) for the fall of rows per ear in breeding programs to increase yields in yellow maize.

Abstract High signal-to-noise ratio (SNR) seismic waveform data are conductive to various studies in seismology. Seismic denoising aims to enhance SNR by eliminating additive noise through signal processing while preserving important features of the seismic signal. Conventional parametric seismic denoising methods often require selecting appropriate parameters to achieve optimal results, which may be limiting when dealing with various types and scales of seismic data. Here, we develop an adaptive parameter-free denoising method by combining general cross-validation (GCV) thresholding and pixel connectivity in synchrosqueezed (SS) domain. In this denoising framework, the synchrosqueezed continuous wavelet transform (SS-CWT) is first applied to obtain a high-resolution time–frequency representation. Then, the GCV approach, which allows for choosing the (nearly) optimal threshold without relying on any prior knowledge about the noise level, is employed to attenuate most of the low-energy noise. After that, the relatively isolated high-energy residual noise remaining in the SS-CWT spectrum is removed using pixel connectivity thresholding. Finally, the inverse SS-CWT is applied to the thresholded spectrum to obtain the denoised seismic record. As the thresholds for GCV and pixel connectivity are derived from the spectrum characteristics of the data being analyzed, the proposed denoising approach is highly adaptive and parameter-free. We demonstrate the effectiveness and versatility of the proposed denoising framework using synthetic data and real seismic data from diverse monitoring scenarios, including land, ocean, and emerging distributed acoustic sensing (DAS). The results indicate that the method is a stable and efficient tool for seismic data denoising. Graphical Abstract

High signal-to-noise ratio (SNR) seismic waveform data are conductive to various studies in seismology. Seismic denoising aims to enhance SNR by eliminating additive noise through signal processing while preserving important features of the seismic signal. Conventional parametric seismic denoising methods often require selecting appropriate parameters to achieve optimal results, which may be limiting when dealing with various types and scales of seismic data. Here, we develop an adaptive parameter-free denoising method by combining general cross-validation (GCV) thresholding and pixel connectivity in synchrosqueezed (SS) domain. In this denoising framework, the synchrosqueezed continuous wavelet transform (SS-CWT) is first applied to obtain a high-resolution time–frequency representation. Then, the GCV approach, which allows for choosing the (nearly) optimal threshold without relying on any prior knowledge about the noise level, is employed to attenuate most of the low-energy noise. After that, the relatively isolated high-energy residual noise remaining in the SS-CWT spectrum is removed using pixel connectivity thresholding. Finally, the inverse SS-CWT is applied to the thresholded spectrum to obtain the denoised seismic record. As the thresholds for GCV and pixel connectivity are derived from the spectrum characteristics of the data being analyzed, the proposed denoising approach is highly adaptive and parameter-free. We demonstrate the effectiveness and versatility of the proposed denoising framework using synthetic data and real seismic data from diverse monitoring scenarios, including land, ocean, and emerging distributed acoustic sensing (DAS). The results indicate that the method is a stable and efficient tool for seismic data denoising. [ABSTRACT FROM AUTHOR]

Foxtail millet (Setaria italica (L.) Beauv) is one of the earliest cultivated millet for grain, hay and silage. There is wide genetic diversity available in foxtail millet and characterization of available germplasm is a pre-requisite for the genetic improvement of any crop. Keeping the above fact in view 30 foxtail germplasm lines were evaluated during kharif 2020 and 2021 for morphological traits, stover yield, dry fodder yield and seed yield under rainfed conditions of Haryana. The results (based on pooled data of two years) revealed that enough variability was present among germplasm lines for further exploitation. High heritability and positive correlation was reported between traits like plant height, leaf length, leaf stem ratio, stover yield, grain yield etc. Principal component analysis also revealed that PC1, PC2, PC3, PC4 and PC5 contributed for 31.8%, 15.05%, 12.31%, 11.43% and 10.14%, respectively to the total variation. Five foxtail accessions viz., SEA8, SEA12, SEA48, SEJ184 and SEA37 were identified promising for yield and related traits under rainfed conditions of Haryana.

A panel of 25 nutmeg genotypes were evaluated at the Horticulture Research Station, Pechiparai, Kanyakumari district from 2019 to 2022 for the pattern of genetic divergence and relationship among them based on seven morphological traits by cluster and path analysis. Notable difference was observed for yield characteristics of genotypes, in which the genotype MF-4 was observed to record high plant height, stem girth, leaf length and fruit production. Genetic variability analysis revealed that traits such as stem girth, number of fruits and mace yield/tree were found to possess high genotypic coefficient of variation along with high heritability and genetic advance as percent of mean which implied that these traits had higher variability among the studied genotypes. The 25 genotypes were grouped in to four clusters based on cluster analysis. Path analysis revealed that traits such as number of fruits, single fruit weight and plant height had a favourable direct impact on the mace yield. These traits might be used as selection indicators in future breeding programmes.

An investigation was carried out with 101 finger millet genotypes for assessment of genetic variability and heritability in four environments during Kharif 2021. Variation due to genotypes for all the traits under study was found significant suggesting high amount of variability among different genotypes for different traits providing ample scope for selection and further evaluation as well as improvement in the seed yield and its component traits. Grain yield per plant (g) had moderate heritability estimates along with high genetic advance expressed as per cent of mean which implied that the character is controlled by genes having additive nature. High heritability combined with high genetic advance expressed as per cent of mean was noted for the characters viz., main ear head length, finger length, 1000-seed weight, protein content, calcium content, iron content and zinc content. Simple selection for such characters would be rewarding.

The experiment was conducted during September, 2023 to February, 2024 at the Department of Biochemistry, Anand Agricultural University, Anand, Gujarat, India. Total 28 genotype originating from a cross between a little leaf resistance parent AB 15-06 (S. melongena) and a susceptible parent GRB 5 (S. melongena). Disease incidence recorded from 14 each of highly resistant and susceptible genotypes and their parents AB 15-06 (Resistance against little leaf disease) and GRB 5 (Susceptible against little leaf disease) were selected for biochemical attributes comprised of chlorophyll (0.73-0.98 mg g-1), moisture (76.77-97.43%), phenol (0.43-3.26 mg g-1), total soluble sugar (2.36-4.57 mg g-1), membrane injury (24.56-69.87%). Correlation analysis of biochemical characters like chlorophyll and moisture were observed negatively correlated with disease incidence while rest of biochemical parameters total soluble solids, membrane injury and phenol content were positively correlated. Membrane injury (0.254), moisture (0.026), TSS (0.030), and phenol content (0.016) showed positive skewness whereas chlorophyll (-1.318), membrane injury (-1.540), moisture (-1.543), total soluble sugar (-1.160) and phenol content (-1.626) detected negative kurtosis. GCV, PCV and heritability analysis for all biochemical characters recorded were chlorophyll (36.46%, 36.5% and 99.82%), membrane injury (61.52%, 61.96% and 98.59%), moisture (7.55%, 8.73% and 13.44%), total soluble sugar (99.39%) and phenol content (46.76%, 46.83% and 99.67%). [ABSTRACT FROM AUTHOR]

The present research was conducted to examine different parameters of variability, correlations, and path coefficients associated with yield and yield-related traits in aerobic rice. The analysis of variance indicated noteworthy variations among the genotypes for all the traits investigated. Among them, flag leaf area and alkali spreading value showed high PCV and GCV. Except for days to fifty per cent flowering, days to maturity, and amylose content, the remaining traits demonstrated substantial heritability combined with high genetic advance as percentage of mean. The correlation analysis revealed significant positive association between grain yield per plant and several traits, namely effective tillers per plant, test weight, chlorophyll content, and length breadth ratio. Traits such as test weight, effective tillers per plant, and flag leaf area showed a positive direct effect on grain yield per plant. Therefore, it is crucial to give priority to traits that exhibit significant positive correlations and substantial direct effects during selection process. This approach will yield rewarding results in the development of high-yielding cultivars suitable for aerobic conditions.

Citrus is an economically important fruit crop with a long history of cultivation worldwide, and many citrus varieties are grown extensively in Morocco, both for domestic consumption and export. Nevertheless, the genetic diversity of this genus in Morocco has not been reported upon. Our objective was to explore phenotypic variations in grapefruit and pomelo genotypes for targeted breeding, enhancing key traits, and identifying opportunities for genetic improvement. We emphasize practical implications and outline future research directions for developing improved citrus varieties. This present study physiochemically analyzes eight grapefruit (Citrus paradisi) and two pomelo (Citrus maxima) cultivars to assess the genetic variability of these fruits' physicochemical characteristics. The results revealed significant variance among the genotypes for all traits. For example, the phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) for all the traits. Moreover, a high degree of heritability was recorded for seed number, β-carotene, vitamin C, juice yield (%), total soluble solids, titratable acidity, maturity index, fruit diameter, and fruit weight, whereas limited heritability was observed for fruit length, peel thickness, and segment number per fruit. The high genetic advance scores corresponded to the high degree of heritability estimates for seed number per fruit, β-carotene, juice yield, and vitamin C, suggesting the existence of additive genetic effects. Our principal component analysis (PCA) identified four components with cumulative variance of 93.20%, while hierarchical cluster analysis grouped the collection into five clusters. In conclusion, phenotypic distinctions among grapefruit and pomelo genotypes reveal opportunities for genetic enhancement through selection or hybridization. Varied traits, including seed count, vitamin C, beta-carotene, and juice yield, across genotypes suggest potential avenues for targeted breeding and practical applications in diverse citrus varieties. [ABSTRACT FROM AUTHOR]

In the present paper, we prove a new theorem, resulting in an update formula for linear regression model residuals calculating the exact k-fold cross-validation residuals for any choice of cross-validation strategy without model refitting. The required matrix inversions are limited by the cross-validation segment sizes and can be executed with high efficiency in parallel. The well-known formula for leave-one-out cross-validation follows as a special case of the theorem. In situations where the cross-validation segments consist of small groups of repeated measurements, we suggest a heuristic strategy for fast serial approximations of the cross-validated residuals and associated Predicted Residual Sum of Squares ( $PRESS$ ) statistic. We also suggest strategies for efficient estimation of the minimum $PRESS$ value and full $PRESS$ function over a selected interval of regularisation values. The computational effectiveness of the parameter selection for Ridge- and Tikhonov regression modelling resulting from our theoretical findings and heuristic arguments is demonstrated in several applications with real and highly multivariate datasets.

The present investigations were carried out on fifty three rice genotypes to select the better lines for yield traits in randomized block design with three replications during kharif 2023. The variance studies showed significant variations among all the genotypes, suggesting significant genetic variation in the material. The phenotypic coefficient of variation (PCV) was higher than genotypic coefficient of variation (GCV) for all the traits. The yield traits which showed high values for genetic advance as per cent of mean along with high heritability were number of unfilled grains per panicle followed by number of filled grains per panicle, number of total grains per panicle, grain yield per plant, number of panicles per plant, number of total tillers per plant, harvest index, test weight, plant height, biological yield per plant and panicle length, revealing the prevalence of additive gene action, thus providing scope for further improvement through selection. [ABSTRACT FROM AUTHOR]

This study was aimed to identify efficiency of recurrent selection program to improve maize population. This program was applied to var. Buhooth 106 with var. 5012 Using RGCA with the inbred Zm7 for the production of RSCA. The recurrent selection program was implemented for four consecutive seasons (2020 - 2021) at the Fields Station of the College of Agriculture - University of Anbar. In the spring season 2020, 100 top crosses were obtained from both varieties and progeny. During the fall season 2020, an experiment was carried out to compare the top crosses of each variety RGCA and RSCA using a 10 × 10 partially balanced lattice design.. Six genotypes from each genetic population as well as Buhooth 106 and 5012 and Zm7 inbreds). The genotype-S1-2 RSCA achieved the lowest female flowering period for females 61.50 days, the highest number of rows per ear 17.80 rows, and the highest grain yield 177.82 g. The genotype-S1-3 RSCA achieved the highest leaf area 0.593 m² and the highest number of kernels per row 43.11 kernel. The broad sense heritability of the traits of the number of rows and the number of kernels in the row and the yield of the plant reached 53.23%, 73.85% and 41.94%, respectively, and high genetic advance for kernels per row and grain yield of 4.79 and 15.52 respectively. [ABSTRACT FROM AUTHOR]

The global surface mass variations obtained by the Gravity Recovery and Climate Experiment (GRACE) satellite Level-2 products show significant north-south strip noise, which seriously affects the estimation of regional surface mass variations. Most existing filtering methods are based on the processing of spherical harmonic basis functions to remove stripes. However, because spherical harmonic basis functions are only orthogonal globally, they may not be orthogonal in regions, which hinders the effective constraint of quality changes in specific regions. Therefore, this paper converts the spherical harmonic base of GRACE Level-2 to the Slepian base of the interested region and truncates it based on the Shannon number of the region. Even though the signals are concentrated in the region, there are still many stripes present. In order to remove the stripes, it is necessary to introduce the regularization and consider the statistical information of the spherical harmonic coefficient. The Tikhonov regularization matrix of the Slepian coefficient is obtained, combined with a power-law model to construct the prior covariance matrix of the signal and the optimal regularization coefficient is selected by using the generalized cross-validation (GCV) method, which is represented as the statistically optimal Slepian method (SO-Slepian) in this study. The results show that the ability of SO-Slepian and decorrelation and denoising Kernel (DDK) filtering with the same regularization parameters as SO-Slepian to remove stripes and retain signals in the selected region is comparable. The line chart comparing the differences between SO-Slepian and DDK not only demonstrates the close similarity in results between SO- Slepian and traditional DDK filtering in the regional domain but also emphasizes the logical application of regularization during the Slepian modeling stage. It further supports the rationality of developing a regularization scheme for GRACE data processing based on Slepian. [ABSTRACT FROM AUTHOR]

Background: Canna lily (Canna indica L.) is an edible herbaceous perennial plant in which flowers and rhizomes were commonly used as a food additive and its potentiality was not fully utilized in India. To stun these hindrances, morphological characterizations are needed to determine the genetic variability to improve flower quality and rhizome yield in canna lily. Methods: In the present research, a field experiment was conducted during 2022-2023 in Botanical Garden, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu. Twelve accessions were investigated by using a randomized block design with 3 replications. All the observations for 23 quantitative traits were carried out at 0.05 and 0.01 probability. Result: A wide range of genetic variability was observed, a high genetic coefficient of variation ranged from 8.49 to 75.62% and a phenotypic coefficient of variation ranged from 8.83 to 76.50% was observed in 20 traits except in days to fist bloom, rhizome diameter, number of nodes per rhizome. High heritability coupled with high genetic advance as a percent of mean was observed for 21 traits except in days to fist bloom and number of nodes per rhizome. Character association analysis revealed that stem diameter and inflorescence length showed highly significant and positively correlated with flower yield and rhizome yield per plant. Path analysis specified that the number of leaves per clump had a very high and positive direct effect on fresh flower yield per plant. [ABSTRACT FROM AUTHOR]

A novel, genetically-stabilized type 2 oral polio vaccine (nOPV2), developed to assist in the global polio eradication program, was recently the first-ever vaccine granted Emergency Use Listing by the WHO. Lot release tests for this vaccine included-for the first time to our knowledge-the assessment of genetic heterogeneity using next-generation sequencing (NGS). NGS ensures that the genetically-modified regions of the vaccine virus genome remain as designed and that levels of polymorphisms which may impact safety or efficacy are controlled during routine production. The variants present in nOPV2 lots were first assessed for temperature sensitivity and neurovirulence using molecular clones to inform which polymorphisms warranted formal evaluation during lot release. The novel use of NGS as a lot release test required formal validation of the method. Analysis of an nOPV2 lot spiked with the parental Sabin-2 strain enabled performance characteristics of the method to be assessed simultaneously at over 40 positions in the genome. These characteristics included repeatability and intermediate precision of polymorphism measurement, linearity of both spike-induced and nOPV2 lot-specific polymorphisms, and the limit-of-detection of spike-induced polymorphisms. The performance characteristics of the method met pre-defined criteria for 34 spike-induced polymorphic sites and 8 polymorphisms associated with the nOPV2 preparation; these sites collectively spanned most of the viral genome. Finally, the co-location of variants of interest on genomes was evaluated, with implications for the interpretation of NGS discussed.

Nonparametric regression approaches are used when the shape of the regression curve between the response variable and the predictor variable is assumed to be unknown. Nonparametric excess regression has high flexibility. A frequently used nonparametric regression approach is a truncated spline that has excellent ability to handle data whose behavior is variable at certain sub-intervals. The aim of this study was to obtain the best model of multivariable nonparametric regression with linear and quadratic truncated spline approaches using Generalized Cross Validation (GCV) and Unbiased Risk (UBR) methods and to find out the factors influencing stunting prevalence in Indonesia in 2021. The data used are the prevalence of stunting as a response variable and the predictor variable used by the percentage of infants receiving Exclusive breastfeeding for 6 months, the percentage of households with proper sanitation, the percentage of toddlers receiving Early Childhood Cultivation (IMD), the percentage of the poor population, and the percentage of pregnant womenIt's a risk. Results show that the best linear and quadratic nonparametric spline truncated regression model in modeling the stunting prevalence is linear truncated spline using the GCV method with three knot points. This model has the minimum GCV value of 7.29 with MSE value of 1.82. Factors influencing the incidence of stunting in Indonesia in 2021 include the percentage variable of infants receiving Exclusive breastfeeding for 6 months, the percentage of households with proper sanitation, the percentage of poor people, and the percentage of pregnant women at risk of KEK.

Vaksinasi adalah proses pemberian vaksin pada tubuh manusia yang bertujuan untuk meningkatkan kekebalan tubuh secara aktif terhadap suatu penyakit dan tidak menjadi sumber penularan penyakit tersebut. Vaksinasi massal merupakan sebuah keharusan yang harus dipenuhi untuk menanggulangi permasalahan wabah Covid-19 yang melanda seluruh dunia termasuk Indonesia. Pada tahun 2021 pelaksanaan vaksinasi Covid-19 di Jawa timur baru mencapai 50% dari total sasaran yang divaksin. Kekebalan imunitas tercapai ketika 70% penduduk telah divaksin. Sementatra ini pelaksanaan program vaksinasi pemerintah sudah mencapai pada vaksin dosis kedua. Berdasarkan uraian tersebut peneliti bertujuan untuk membandingkan pemodelan jumlah penduduk yang telah divaksin dosis pertama dan kedua menggunakan metode deret Fourier Birespon dengan Fungsi Tren. Kriteria kebaikan model yang digunakan adalah nilai GCV dan MSE terkecil, serta nilai koefisien determinasi tertinggi. Model yang diperoleh dalam penelitian ini adalah model dengan basis sinus cosinus. Model tersebut mempunyai nilai GCV dan MSE lebih kecil dibandingkan nilai GCV dan MSE pada basis cosinus dan sinus. Koefisien determinasi model tersebut sebesar menunjukkan nilai yang besar. Vaccination is a process carried out by the human body that aims to increase the body's active immunity against a disease so that people who are vaccinated will not get sick. The Covid-19 outbreak hit the whole world, including Indonesia. Currently, the implementation of the Covid-19 vaccination in East Java has only reached 50% of the total target being vaccinated. The requirement to achieve immunity must be that 70% of the population has been vaccinated. Based on this description, the researcher aims to compare the modeling of the population that has been vaccinated with the first and second doses using the Fourier series bi-response method with a trend function. The criteria for the goodness of the model in this study used small GCV and MSE values and a high coefficient of determination. The model has smaller GCV and MSE values ​​than the cosine and sine basis. The coefficient of determination of the model shows a large value.

Understanding the character of genetic variability and diversity is crucial to enhancing selection efficiency in plant breeding programs. This study aimed to estimate the magnitude of genetic variability and diversity among 64 accessions based on quantifiable characteristics to provide valuable information for breeding programs and conservation. The 64 accessions were evaluated in the two locations using an 8x8 lattice design. Analysis of variance showed a significant difference among the tested accessions for the characters studied, indicating the presence of variability and the possibility of character selection and improvement. The highest genotypic coefficient of variation revealed for the aboveground biomass, storage root yield, and storage root number indicates that the possibility of selection of those characters might be effective for their improvement. High heritability along with high genetic advance as a percent of the mean was observed for number of storage roots, length of storage roots, storage root yield, aboveground biomass, and harvest index, suggesting the existence of additive gene effects. The first three principal components explained 49 % of the total variation, with PC I accounting for 22.5 %, PC II for 15.6 %, and PC III for 10.9 % of the total variation. The 64 accessions were grouped into five clusters, and the number of accessions in each cluster was varied from 3 in cluster V to 31 in cluster II. The maximum inter-cluster diversity was found between IV and V (82.60), while cluster V (6.12) had the highest intra-cluster diversity. Accessions G8, G16, G40, G43, G46, G53, and G57 have been identified as the best candidates for the breeding program in terms of storage root yield. The various analyses performed in the present study confirmed the presence of wide variability & diversity among accessions, which could be used to develop cassava cultivars with optimal storage root yield through effective selection.

A study was carried out to understand the genetic variability and trait association in a set of 30 naturally coloured cotton hybrids along with their parents (five colour cotton and six white cotton parents). The Analysis of Variance revealed the significance of the mean square for most of the traits studied. The phenotypic coefficient of variation was more than that of the genotypic coefficient of variation for all the traits. High PCV and GCV were recorded for the traits number of monopodia and single plant yield. The heritability and genetic advance as percentage of mean (GAM) were high for the traits plant height, number of monopodia, number of bolls per plant, single boll weight, bundle strength, fibre fineness and single plant yield. The Number of sympodia, number of bolls per plant and boll weight were observed to have significant genotypic and phenotypic correlation with single plant yield, while upper half mean length was observed to have significant genotypic and phenotypic correlation with bundle strength and fibreelongation. Path analysis revealed that seed index and ginning out turn recorded very high direct effect with single plant yield. [ABSTRACT FROM AUTHOR]

The landraces of rice provide a wide range of genetic variations and environmental adaptation and act as excellent genetic resources for crop improvement. Natural germplasm that has been maintained through conservation is in desperate need of rigorous investigation in order to uncover new genes or alleles to introduce into rice breeding programmes. Given this context, an investigation was done to determine the degree of genetic divergence and variability across 31 rice landraces for various productivity, physiological, and grain quality traits. On evaluation of the mean performance of landraces and the influence of characters in genetic divergence resulted in the identification of better landraces viz., Vellaikuruvikar, Karupu Kavuni, Kichidi Samba and Athur Kichadi which are better for both grain yield and quality traits that can be used to create better recombinants, by hybridization. These gene pools could be used in selective breeding to significantly enhance the agronomic characters. Out of 20 traits that were investigated,15 traits viz., height of the plant, productive tillers per plant, length of panicle, spikelets per panicle, filled grains per panicle, grain yield per plant, seedling root to shoot ratio, harvest index, head rice recovery, length of the kernel, length to breadth ratio of kernel, breadth of kernel after cooking, length to breadth ratio of kernel after cooking, gelatinization temperature and aroma were noted for high heritability and genetic advancement suggesting that additive gene action predominates, there by opening up a wide range of opportunities for these traits to be improved through simple phenotypic selection.

Little millet is one of the underutilized crops among the cereals, which is being cultivated by farmers of tribal agriculture. The landraces under cultivation possess excellent variability presenting good opportunities for selection. In view of this, the current study was carried out with 17 little millet landraces for 10 quantitative and nine qualitative traits. The study revealed the preponderance of additive gene action for all the 10 traits and hence effective selection could be done for their improvement. Higher to moderate ranges for PCV and GCV with minimum ECV for genetic variability for all the traits were observed. Among the nine qualitative traits, there were significant variations observed for inflorescence shape and panicle compactness. Hence, these traits could be utilized as major DUS descriptors in differentiating the little millet landraces in future. Further the PCA analysis exhibited three reliable principal components contributing to an overall variation of 74.54%. The traits such as days to 50% flowering, peduncle length and flag leaf length were the major positive contributors for variability across all the eigen vectors. These traits were found to exhibit a higher variability among the population and thus a rewarding selection and hybridization for improving these traits could be effected in future breeding programs. Among all the landraces and varieties chittan samai, perunsamai, ATL 1, CO 4 (samai), paakulam karunjamai and vellai samai could be further identified as desirable donors for improving the yield parameters in little millet breeding programs in future.

Thirty advanced lines of wheat obtained from Borlaug Institute for South Asia (BISA), Ludhiana, Punjab were evaluated in a Randomized Block Design (RBD) with three replications for yield and its contributing characters at Agriculture Research Farm, Department of Genetics and Plant Breeding, School of Agriculture, Lovely Professional University, Phagwara, Punjab, India during rabi 2021-2022. Genetic variability, heritability and genetic advance per cent of the meanand analysis of variance were carried out for 14 traits. The mean sum of square (MSS) due to genotypes was highly significant for all the fourteen traits. Grain yield per plant exhibited the highest phenotypic coefficient of variation (PCV) followed by harvest index, the number of spikes per plant, the number of tillers per plant and biological yield per plant. Genotypic coefficient of variation (GCV) was found to be highest for grain yield per plant followed by harvest index, the number of spikes per plant, the number of tillers per plant and biological yield per plant. Very high heritability estimates were associated with high estimates of genetic advance for the number of tillers per plant, the number of spikes per plant, biological yield per plant, harvest index, grain yield per plant, chlorophyll content, and flag leaf area which revealed the presence of additive gene effects, showing the efficiency of selection method of breeding for improving these attributes in wheat.

Twenty bacterial wilt resistant lines including recently developed lines at CSKHPKV, Palampur (08) were studied to ascertain the extent of genetic variability, the type and magnitude of correlation between component characters & marketable yield, as well as the direct and indirect impacts of every character on marketable yield. For all variables except plant survival, analysis of variance exhibited significant differences across genotypes. Phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) values for lycopene content (80.581%, 80.148%), titrable acidity (73.666%, 71.219%), marketable yield / plant (53.953%, 52.598%), marketable fruits / plant (34.994%, 34.050%), gross yield / plant (34.094%, 30.553%), average weight of fruit (30.558%, 29.13%), locules / fruit (28.549%, 25.050%), and ascorbic acid (23.641%, 20.919%) respectively, were found high across different parameters of variability. Marketable yield / plant (95.043%, 45.633%), marketable fruits/plant (94.68%, 68.252%), titrable acidity (93.467%, 48.838%), average weight of fruit (90.877%, 57.206%), gross yield / plant (80.305%, 56.402%), ascorbic acid (78.295%, 38.130%), and locules / fruit (76.985%, 45.276%) were found with high heritability and high genetic advance. Marketable yield / plant was significantly and positively associated with average weight of fruit (0.734, 0.795), gross yield / plant (0.774, 0.853), marketable fruits / plant (0.734, 0.742), pericarp thickness (0.693, 0.806), ascorbic acid (0.381, 0.469), titrable acidity (0.347, 0.364) and locules/fruit (0.284, 0.345) at both phenotypic as well as genotypic levels, respectively. Path coefficient analysis showed that marketable fruits / plant (0.589, 0.608), gross yield / plant (0.278, 0.617) and average weight of fruit (0.382, 0.182) are the three main parameters that had the greatest positive direct impact on marketable yield / plant at the phenotypic and genotypic levels, respectively. [ABSTRACT FROM AUTHOR]

Sixty-nine cultivars of rice were examined for fourteen biometrical characteristics to study the degree of genetic divergence, heritability and genetic gain as a percentage of mean, character relationship and path coefficient analysis. Yield per plant reported the highest estimate of PCV and GCV followed by the total effective tillers per plant, hundred seed weight, number of filled seeds per panicle and flag leaf length indicating that these traits may be given importance while exercising selection. Plant height, panicle length, total tillers, total effective tillers per plant, flag leaf length, grain length, grain L/B ratio, the number of filled seeds per plant, hundred seed weight and yield per plant exhibited remarkable genetic gain and high heritability, implying a predominance of additive gene action. Hence, genetic advancement through simple selection would be more beneficial. Among the yield traits examined, days to 50% flowering, total tillers per plant, the number of effective tillers per plant, flag leaf breadth, the number of filled seeds per panicle, and hundred-seed weight recorded a positive significant correlation with direct effects on yield per plant asserting that these traits were the most efficient and promising selection criteria.

Genetic variability for plant type and seed yield components among 318 recombinant inbred lines of Pigeonpea [Cajanus cajan (L) Millspaugh] was studied during the Kharif season of 2017-18 and 2018-19. The characters studied include plant height, the number of primary branches, the number of secondary branches, days to flowering, and days to maturity, the number of pods per plant, the number of seeds per pod, pod bearing length and branching angle with the main axis. Significant genetic variability was observed among the recombinant inbred lines. Remarkable genotypic differences were found for many of the traits under study. The recombinant inbred line population studied under two environments showed less genotype and environment interaction. The difference between the phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) is less indicating high heritability of the traits under study and control of additive gene action. The genetic advance over the percentage of the mean was also high for all the traits under study. From the study, it was inferred that genotypes with determinate plant types with a greater number of pod and primary branches early flowering and early maturing with high seed weight and acute branching angle play a significant role in enhancing the yield.