Selection For Crop Improvement Research Articles

Assessment of Genetic Diversity Using Metroglyph Analysis in Rice (Oryza sativa L.) Germplasm

The present investigation was carried out to assess the genetic variability parameters, metroglyph analysis in 31 rice genotypes for 13 quantitative traits during Kharif,2022 season at Field experimentation center, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Uttar Pradesh using Randomized Block Design with three replications. Analysis of variance indicated high significant differences among the genotypes for all the traits. Considerable variability existed in the genotypes for all the characters studied. These were the genotypes with high mean values in desirable direction i.e., From the present investigation it is concluded that among 31 genotypes of rice, VASUMATHI showed Early flowering (80 days), and had characters like Early maturity (113days), DRR DHAN-38 showed high Plant height (155.8 cm), PUSA BASMATHI-1 showed high Panicle length (28.8 cm), NAGARJUNA is showing both high Biomass (69.3 g), and Grain Yield per Plant (39.7 g). Highest GCV were depicted for Grain Yield per Plant, Biological Yield per hill, Number of Spikelet’s per panicle, Number of Panicles per hill, Number of Tillers per Hill, and Flag Leaf Width. The highest Heritability was observed for Number of Tillers per hill, Number of Spikelet’s per Panicle, Grain yield per plant, Number of Panicles per hill, Biological Yield per Hill and Flag Leaf Width and Highest genetic advance as a percentage of mean except Plant height, Grain yield per plant, Biological yield per hill, Number of spikelet’s per panicle, Number of panicles per hill, Number of total tillers, Flag leaf width and harvest index. A scatter diagram was created for 31 genotypes that formed five complexes with 13,9,4,4 and 1 genotype in each complex. The genotypes Nagarjuna, Jarva and NDR-359, which have a high index score and fall into various clusters, can be utilized as parents in hybridization to get the most variety in character combinations. This character should be given due consideration during selection for crop improvement.

Assessment of Genetic Diversity of Rice (Oryza sativa L.) under Prayagraj Agro-climatic Conditions

The goal of the current study was to assess the genetic variability parameters and genetic diversity in 40 rice genotypes for 13 quantitative traits in the Kharif, 2022 Season at the field experimentation center, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology and Sciences, Uttar Pradesh. Analysis of variance indicated highly significant differences among the genotypes for all the traits. Considerable variability existed among the genotypes for all the characters studied. It is concluded that among 40 genotypes of rice, Nellore Dhanyarasi showed early flowering (77 days), IR-64 had characters like early maturity (108 days), high grain yield per plant is seen in Shuats Dhan-6 (62.1 g), JHARA SEL showed high plant height (185 cm) and high biomass is seen in Shuats Dhan-6 (123.6 g), Swathi showed high panicle length (43.7 cm). Highest GCV and PCV were depicted for grain yield per plant, biological yield, harvest index and number of spikelets per panicle. The highest heritability was observed for Grain Yield per Plant followed by Harvest Index, Flag Leaf length, Biological Yield and Number of Spikelets per Panicle. The Genetic Advance in per cent of mean is high for grain yield per plant, biological yield, harvest index and number of Spikelets per Panicle. Based on D2 values, 40 genotypes grouped into 7 clusters. Among 7 clusters, cluster I had a greater number of genotypes (26) followed by cluster II (8), III (2), IV, V, VI andVII (1) genotype each. Cluster VI and cluster III (365.72) followed by cluster VII and cluster V (363.6), were most diverse from each other and the genotypes included in these clusters provide a broad spectrum of variability in segregation and may be used as parents in the future hybridization programme to develop desirable genotypes for grain yield improvement in rice genotypes. The trait Grain yield per hill had maximum contribution towards to genetic divergence followed by biological yield, Harvest Index, Test Weight. Therefore, all these characters should be given due consideration during selection for crop improvement.

Genetic Variability and Path Analysis for Yield and Grain Yield Component Characters in Rice (Oryza sativa L.) Genotypes

The present investigation consists of 21 genotypes of Rice including one check, which were grown under the Field Experiment Centre of the Department of GPB, SHUATS, Prayagraj during Kharif 2021 following Randomized Block Design with three replications. Analysis of variance among 21 genotypes showed significant difference for all the characters studied. Based on the mean performance, genotypes NUMALI followed by KALINGA and MTU-1155 were identified as suitable genotypes with highest grain yield per hill. High estimates of PCV, GCV, heritability coupled with high genetic advance as percent of mean were recorded for grain yield per hill, biological yield and flag leaf length indicating that these characters could be used as selection for crop improvement. Biological yield and harvest index showed positive significant association and recorded high positive direct effect on grain yield per hill at both the genotypic and phenotypic levels. These characters such as biological yield, and harvest index should be given prior consideration during selection for grain yield improvement in rice.

Adaptability Study of Yield and Yield Related Trait Performance of Improved Bread Wheat (Triticum aestivum L.) Varieties in North Shewa Zone Oromia, Ethiopia

Bread Wheat (Triticum aestivum L.) is an important cereal crop, which receives the most attention of specialists in plant breeding and production as worldwide. The Knowledge of the interaction between genotypes and environment with yield and yield components is a key aspect of effective selection in crop improvement. Therefore, the objective of this study was: to identify Adaptable bread wheat variety/ies with high level of grain yield and yield stability across locations. The study used 16 bread wheat released varieties, against local check at Fitche Agricultural Research Center (FiARC) in 2020-2022 cropping season. Ten important agronomic traits data were evaluated. Analysis of variance noticed significant difference, among varieties in both separated and combined analysis of variance. The combined ANOVA and the additive main effects and multiplicative interactions (AMMI) analysis for grain yield across environments exhibited significantly affected by environments, which explained 76.6% of the total variation. The genotype and genotype environmental integration were significant and accounted for 8 and 13.1%, respectively. Principal component (PCA) 1 and 2 accounted for 6.5 and 3.5% of the GEI, respectively, with a total of 10% variation. Generally, Sanete and Dandaa varieties were identified for yielding ability and stability, and recommended for the study area and similar agro-ecologies.

Appraisal of Buckwheat (Fagopyrum esculentum L.) Genotypes for Growth, Yield, Yield Attributes, Seed and Seedling Characteristics under Prayagraj Agro-Climatic Conditions

Buckwheat is referred as poor man’s food because it has good fibre, carbohydrates and essential amino acids. So, it must be made as an integral crop in agriculture production system. For this purpose, production is to be improved through development and breeding of new varieties. So, an experiment was conducted by using 26 buckwheat genotypes to evaluate them under Prayagraj agro-climatic conditions during 2021-22 to study growth, yield and yield attributes. The field experiment was conducted in randomized block design (RBD) with three replications and lab experiments were conducted in complete randomized design (CRD) with four replications. During the field experiment all genotypes showed wide variations among them for both growth and yield attributing traits. Among twenty-five genotypes, IC 108508 produced highest yield plot-1 (405g) followed by IC 26755 (315g), IC 37275 (299.3g) and IC 107575 (277.3g) higher yield than check PRB 1 (208.3 g). These genotypes also showed high to moderate values for growth and yield attributes. Therefore, these genotypes can be suggested for cultivation under Prayagraj agro-climatic conditions. Under laboratory study, it was observed that IC 42412 performed better for germination percent (97%), seedling length (27.9cm), fresh weight (1.05g), dry weight (0.303 g), vigour index I (2703), vigour index II (29.39), viability percent (99%) and electrical conductivity (0.22dsm-1). The highest protein content (14.1g%) was recorded in IC 24300 genotype. Therefore, IC 42412 can be considered as physiologically potential genotype. Through correlation and path analysis it was clear that number of seeds plant-1, inflorescence length, economic yield, number of inflorescence plant-1 and days to maturity may be considered for selection in crop improvement. Through this study it was concluded that IC 108508, IC 26755, IC 37275, IC 107575 and IC 42412 can be used for further breeding programs.

Diversity in Root Architecture of Durum Wheat at Stem Elongation under Drought Stress

Durum wheat is a major crop in the Mediterranean basin, where water deficit is the most important factor affecting its production. Under drought conditions, the root system has a crucial role in crop productivity as a water and nutrition supplier. The aim of the study was to analyze root system diversity in six contrasting durum wheat accessions, including two hydric stress-tolerant genotypes, and to evaluate root traits using the high-throughput phenotyping scanner Win-RHIZO in order to determine the main traits to be used in breeding programs. Six durum wheat accessions were subjected to two drought events under greenhouse conditions from the seedlings stage (BBCH12) for 49 days. Root phenotyping data were validated with results from plants grown in the rainfed field. This study highlighted a great variability among the analyzed genotypes in terms of development, distribution, and architecture of the root system under difficult environments, underlining a good resilience to climate change. Interestingly, the two hydric stress-tolerant genotypes, Cham1 and J. Khetifa, showed different root system ideotypes and rooting patterns under drought conditions. The late flowering landrace J. Khetifa (as also genotypes; Pelsodur and Vulci) showed a steep and long root system ideotype that led to the maintaining of the highest root biomass, length, and volume under drought conditions, while the early flowering genotype Cham1 (as also genotype; Sebatel) was distinguished by a wider root system ideotype, and by increasing the root volume in the topsoil as a strategy to tolerate drought. Moreover, a significant positive correlation was obtained between the root angle of plants grown under greenhouse conditions and plants from the field. Our results demonstrated that screening plant roots in early stages grown under greenhouse conditions using high-throughput phenotyping systems can speed up the selection for crop improvement and future drought stress breeding programs.

Genetic variability, heritability for quantitative traits in upland rice (Oryza sativa L.) genotypes

The present investigation consists of 34 genotypes with one local check (NDR-359) grown at field experimentation centre at the Department of Genetic and Plant Breeding, SHIATS, Allahabad evaluated for thirteen quantitative characters. All the genotypes differed significantly with respect to all the quantitative traits. High to moderate estimates of GCV and PCV were found for number of panicle per plant, number of tiller per plant, plant height and number of spikelet’s per panicle, indicating these traits could be use for selection in crop improvement. Plant height, number of spikelet’s per panicle, test weight and flag leaf length exhibited high values for broad sense heritability. Number of spikelet’s and plant height showed highest genetic advance coupled with high heritability, which is also exhibited by number of panicle per plant, number of tillers per plant and plant height suggesting pre dominance of additive gene action in the expression of these traits.

Multi-Location Evaluation of Yield and Yield Related Trait Performance in Bread Wheat Genotypes at Western Oromia, Ethiopia

Wheat (<i>Triticum aestivum</i> L.) is an important cereal crop, which receives the most attention of specialists in plant breeding and production worldwide. Knowledge of the interaction between genotypes and environment with yield and yield components is a principal aspect of effective selection in crop improvement. Therefore, the objective of this study was: to identify bread wheat genotypes with high level of grain yield and yield stability and insect pest tolerant across locations. The study used 15 bread wheat genotypes, against one local and two standard checks (Liban and Kingbird) at Haro Sabu Agricultural Research Center (HSARC) in 2017-2018 cropping season. Ten agronomic traits and four economically important disease reaction data were evaluated. Analysis of variance detected significant difference, among genotypes in both separated and combined analysis of variance. The combined ANOVA and the additive main effects and multiplicative interactions (AMMI) analysis for grain yield across environments exhibited significantly affected by environments, which explained 65.06% of the total variation. The genotype and genotype environmental interation were significant and accounted for 13.34 and 9.44%, respectively. Pricipal component (PCA) 1 and 2 accounted for 7.88 and 1.15% of the GEI, respectively, with a total of 9.03% variation. Generally, G6 and G3 were identified as ideal genotypes for yielding ability and stability, tolerant to diseases and use as parents in future breeding programs.

Assessment of genetic variability, correlation and path analysis for yield and related traits in elite rice (Oryza sativa L.) germplasm

Studies on genetic variability, heritability, genetic advance and correlation coefficient analysis and path analysis. Analysis of variance among 26 elite rice germplasm showed highly significant differences for all the characters under study indicated the presence of a substantial amount of genetic variability. Higher estimates of GCV and PCV were for number of panicles per plant followed by number of tillers per plant followed by spikelets per panicle indicating that these characters could be used as selection for crop improvement. High heritability coupled with high genetic advance is recorded for number of spikelets per plant. Correlation study revealed that Grain yield per plant showed the high significant positive correlation with number of tillers per plant, number of panicles, panicle length, number of grains per panicle, biological yield showed positive significant correlation at phenotype and genotypic levels. Path coefficient analysis revealed that days to 50% flowering, plant height, number of tillers per plant, number of panicles per plant, flag leaf length, number of grains per panicle, biological yield and harvest index has positive direct effect on grain yield per plant.

Study of genetic variability and heritability of yield and its components in forage sorghum (Sorghum bicolor L. Moench)

The present investigation was undertaken by using ten lines and four testers and their forty F1 made with the parents of forage sorghum genotype of diverse origin, which were grown in a Completely Randomized Block Design (CRBD) with three replications during kharif season 2017 & 2018 were evaluated for eleven characters to study genetic variability, heritability and genetic advance. The ‘analysis of variance’ revealed highly significant differences among the genotypes for all the characters i.e. days to 50% flowering, plant height, leaf length, leaf breadth, internode length, stem girth, leaves per plant, leaf area, leaf stem ratio, total soluble solids and green fodder yield per plant, which indicated that wide spectrum of variability among the genotypes. The highest genotypic coefficient of variation (GCV) & phenotypic coefficient variation (PCV) was observed for leaf stem ratio, indicates that these attributes could be used as a selection for crop improvement. On the basis of high estimates of heritability coupled with high genetic advance was expressed as per cent of mean were observed for leaf breadth, leaf area, leaf stem ratio and green fodder yield per plant indicating a predominance of additive gene effects and possibilities of effective selection for the improvement of these characters.

Genetic variability, heritability and genetic advance study in bread wheat (Triticum aestivum L.)

The present investigation consists of seventeen Wheat genotypes and the experiment was conducted during Rabi-2016- 2017 and 2017–2019 in Randomized Block Design with three replications. The experiment consisted of 17 parents (13 lines and 4 testers) and 52 F1s developed from line x tester mating design (13 x 4). The data were recorded on 14 quantitative characters (12 agronomical and 2 quality characters) viz; days to 50% flowering, days to maturity, plant height (cm), spike length (cm), spikelets per spike, productive tillers per plant, grains per spike, flag leaf area (cm2), biological yield per plant (g), grain yield per plant (g), harvest index (%), 1000 grain weight (g), gluten content (%) and ash content (%). The data were recorded for 15 quantitative characters to study genetic variability, heritability and genetic advance. On the basis of mean performance, high Plant height was exhibited by different genotypes. Analysis of variance among 17 genotypes showed significant differences for all traits studied. Highest genotypic coefficient of variation (GCV) & phenotypic coefficient variation (PCV) was observed for Grain Yield/Plant followed by Plant Height, Harvest Index and Ash Content indicating that these characters could be used as selection for crop improvement. On the basis of high estimates of heritability coupled with high genetic advance was observed for Plant Height, Biological Yield/Plant, Harvest Index and Grain Yield/Plant indicating predominance of additive gene effects and possibilities of effective selection for the improvement of these characters.

English

Barley is recognized as one of the oldest cereal crop in Ethiopia grown for various uses. The knowledge of the association between various yield components and yield is paramount important for effective selection in crop improvement. The present study was to determine the interrelationship and direct and indirect effects of yield component traits on grain yield of Ethiopian landraces barley for further breeding activities of yield improvement. One hundred barley landraces were laid out in 10 x 10 simple lattice design with two replications in 2017 main cropping season at Mata sub site of Haro-Sabu Agricultural Research Center (HSARC). The analysis of variance revealed highly significant (p≤ 0.01) to low significant (p ≤ 0.05) difference for all the characters. Sixteen parameters were evaluated to assess the inter relationship among yield and yield-related agronomic characters and their effect on grain yield. Grain yield showed positive and significant genotypic correlations with grain weight per spike (rg = 0.36), spike weight per plant (rg = 0.38), 1000-seed weight (rg = 0.66), biological yield (rg = 0.83), awn length (rg = 0.34) and plant height (rg = 0.23). The result revealed that biological yield, 1000-seed weight, productive tillers per plant and grain weight per spike were the most important yield components as they exerted positive direct effect on grain yield as well as positive genetic association with each other explaining the existence of significant correlation. This suggests that simultaneous improvement in these characters might be possible. Keywords: Barley, phenotypic association, genotypic association, direct and indirect effects.

Genetic diversity and association mapping of Ethiopian and exotic finger millet accessions

Combining morphological and molecular data to identify genetic variation and marker–trait association is one of the most important prerequisites for genomics-assisted selection in crop improvement. To this end, a total of 138 finger millet (Eleusine coracana subsp. coracana) accessions including five improved varieties were evaluated to assess the genetic variation and population structure and undertake association mapping. These accessions were basically collected from Ethiopia (96), Eritrea (8), Kenya (7), Zambia (9) and Zimbabwe (13). Finger millet accessions were evaluated in the field for 10 important agronomic traits and also characterised using a set of 20 microsatellite markers. Mean polymorphism information content of 0.61 was observed from a total of 222 alleles with an average of 11.1 alleles per microsatellite locus. About 61% of alleles detected were rare (&lt;5%) and specific allele amplification was observed in 34 accessions. Both weighted neighbour-joining based clustering using molecular data and hierarchical clustering using phenotypic trait data grouped the 138 accessions into four major clusters that were not entirely based on their geographical origins. Genome-wide association studies depicted 16 significant (P &lt; 0.01) associations between 13 microsatellite markers and six agronomic traits. Our results reveal a unique abundance of rare alleles in finger millet and highlight the need for more careful selection of genome-wide association studies in the future in order to capture the contribution of rare alleles to important agronomic traits.

A Hypomethylated population of Brassica rapa for forward and reverse Epi-genetics

BackgroundEpigenetic marks superimposed on the DNA sequence of eukaryote chromosomes provide agility and plasticity in terms of modulating gene expression, ontology, and response to the environment. Modulating the methylation status of cytosine can generate epialleles, which have been detected and characterised at specific loci in several plant systems, and have the potential to generate novel and relatively stable phenotypes. There have been no systematic attempts to explore and utilise epiallelic variation, and so extend the range of phenotypes available for selection in crop improvement. We developed an approach for generating novel epialleles by perturbation of the DNA methylation status. 5- Azacytidine (5-AzaC) provides selective targeting of 5mCG, which in plants is associated with exonic DNA. Targeted chemical intervention using 5-AzaC has advantages over transgenic or mutant modulation of methyltransferases, allowing stochastic generation of epialleles across the genome.ResultsWe demonstrate the potential of stochastic chemically-induced hypomethylation to generate novel and valuable variation for crop improvement. Systematic analysis of dose–response to 5-AzaC in B. rapa guided generation of a selfed stochastically hypomethylated population, used for forward screening of several agronomic traits. Dose–response was sigmoidal for several traits, similar to that observed for chemical mutagens such as EMS. We demonstrated transgenerational inheritance of some phenotypes. BraRoAZ is a unique hypomethylated population of 1000 E2 sib lines. When compared to untreated controls, 5-Aza C-treated lines exhibited reduced immuno-staining of 5mC on pachytene chromosomes, and Methylation Sensitive Amplified Polymorphism (MSAP) profiles that were both divergent and more variable. There was coincident phenotypic variation among these lines for a range of seed yield and composition traits, including increased seed protein content and decreased oil content, as well as decreased erucic acid and corresponding increases in linoleic and/or palmitic acid. Each 5-AzaC-treated line represents a unique combination of hypomethylated epialleles.ConclusionsThe approach and populations developed are available for forward and reverse screening of epiallelic variation and subsequent functional and inheritance studies. The generation of stochastically hypomethylated populations has utility in epiallele discovery for a wide range of crop plants, and has considerable potential as an intervention strategy for crop improvement.

Application of Artificial Neural Network in Genomic Selection for Crop Improvement

With important progress in marker technologies,marker-assisted selection(MAS) has been used broadly for the crop improvement.Biparental populations are designed for the detection of quantitative trait loci(QTLs),but their application is re-tarded.The association mapping(AM) is applied directly to natural populations,which has been proposed to mitigate the lack of relevance of biparental populations in QTL identification.Many QTLs are identified by the two methods,which have encouraged genetic improvement of crop.However,they are using significant thresholds to identify QTL from estimated means that estimated effects are biased.Therefore,small-effect QTLs cannot be identified and missed entirely,while lots of traits of crop are controlled by those small-effect QTLs.Genomic selection(GS) has been proposed to make good for these deficiencies.Genomic selection predicts the breeding values of lines in a population by analyzing their phenotypes and high-density marker scores,and by includ-ing all markers in the model,and benefits from unbiased estimation of all chromosome segment effects,even when they are small.The GS incorporates all marker information in the prediction model,which avoids biased marker effect estimates and captures more of the variation from small-effect QTLs.Furthermore,markers carry information on the relatedness among lines,which contributes to prediction accuracy.Such accuracies are sufficient to select parents strictly on the basis of marker scores even for traits such as yield,tolerance to abiotic stress.From the view of perspective of the products from plant breeding,the genomic selection would greatly accelerate the breeding cycle,and enhance annual gains.GS would develop a prediction model from training population,genotyped and phenotyped,by estimated the markers effects.Then GS model would take genotypic data from candidate population to predict genomic estimated breeding values(GEBV),and there are some methods used for GS model,such as best linear unbiased prediction(BLUP),ridge regression BLUP(RR-BLUP),and Bayesian linear regression(BLR).These models are well used for crop genomic selection breeding.However,all the models are developed based on line or regression,while the relationships of genetic sites in life are not non-line or regression.The neural network was introduced to genomic selec-tion in crop improvement in this study.The crop genomic selection model was optimized by non-linear model system.Therefore,the high efficient genomic selection system was established,and the prediction results were compared with these of other linear models,such as RR-BLUP,BLR.In wheat genetic data simulation,the correlation coefficient between the true breeding value of unphenotyped experimental lines and that predicted by genomic selection based on the neural network reached 0.6636,while that of RR-BLUP,BLR and BLR with pedigree information was 0.6422,0.6294,and 0.6573,respectively.Meanwhile,the best predic-tion was 0.8379,which indicated the genomic selection based on the neural network is superior to those of other linear regression models.This level of accuracy was sufficient for selecting for agronomic performance using marker information alone.Such se-lection would substantially accelerate the breeding cycle,and enhance gains per unit time.Therefore,this research showed that GS has more potential for incorporating it into breeding schemes.

Screening of barley landraces by direct selection for crop improvement

Barley (Hordeum vulgare L.) landraces display a high degree of variability in morphological and developmental traits, in disease resistance, and in protein content. Representatives of 29 barley landraces from southeast Turkey were collected from farmers’ fields, for a total of 800 accessions. The objectives of this study were to characterize these accessions over four years for morphological and agronomical traits to be used for future selection and breeding program. The observed variation between landraces was very large for all traits. In the first year of testing the accessions showed average grain yields ranging from 197–2225 kg ha−1. After three years of selection, promising accessions were tested at two different geographical regions and using two different irrigation methods. One line was identified which significantly out-yielded the local landrace in all of the testing years and had a higher average yield than the check genotypes.

Evaluating Plant Breeding Strategies by Simulating Gene Action and Dryland Environment Effects

Functional genomics is the systematic study of genome‐wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM‐Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this space using a quantitative genetics model of a plant breeding program (QU‐GENE) to simulate recurrent selection. Complex epistatic and gene × environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe‐Terminal drought environment type, late genotypes were favored in the Mild‐Terminal and Midseason drought environment types. In the Severe‐Terminal environment, there was an interaction of the stay‐green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene × gene × environment interactions will challenge the application of genomics and marker‐assisted selection in crop improvement for dryland adaptation.

Optimizing RAPD Markers for Ginseng Genomic DNA Analysis

Random amplified polymorphic DNA (RAPD) may have utility as genetic markers facilitating selection in ginseng crop improvement. This experiment determined chemical buffer and root tissue-type combinations that yield repeatable bands. The results allow further experiments using RAPD markers for estimating the genetic distance between ginseng landraces, selection for crop improvement, and extensive fingerprinting for use in determining the origin of tissue samples. This experiment determined mean band yields for all combinations of dry, fresh, and powdered root with cetyltrimethylammonium bromide, potassium/sodium ethyl xanthogenate, and urea buffers. The buffers were applied in replication to the tissue-types with other extraction protocol factors constant. Replications were amplified four times with four different primers using constant PCR and agarose gel electrophoretic protocols. Distinct bands were counted in each replication, and the summation of the replication repeats considered an observation. Least squares means for several response variables were analyzed. The most significant difference found was between buffers. The buffers ctab and urea were productive, and the pex was not. Significant difference was found when buffers were crossed with tissue. The applications of urea to fresh root, ctab to dry root, urea to dry root, and ctab to powdered root were productive. Based on these results we conclude 1) urea and ctab are productive when applied to all tissue-types, 2) dry root, which is easily collected and stored, yields sufficient DNA for analysis, and 3) powdered root, often the form of commercial products that might be tested for genetic origin, will yield sufficient DNA for analysis.

Sporophytic and gametophytic heat shock protein synthesis in Sorghum bicolor

The general characteristics of the heat-shock response in the sporophytic and gametophytic phases of Sorghum bicolor, a species well adapted to tropical environments, are examined. At the sporophytic level, heat shock protein (HSP) synthesis in sorghum is still induced after an extreme (well over 50°C) or prolonged heat stress: the so-called late HSPs are first induced after 14 h continuous exposure at 45°C, and persist up to at least 28 h shock. A normal protein pattern is not resumed, as is the case in most organisms. In contrast to plant species typical of temperate climates, sorghum pollen also retains the capability to synthesize HSPs in post-germinative stages. In addition to several classic HSPs, those synthesized in all sporophytic tissues, some gametophyte specific heat inducible polypeptides are expressed in both immature and germinating pollen. Taking into account the likely role of HSPs in cellular thermo-protection, these data support the hypothesis that acquisition of themotolerance shows between species variability, in relation to climatic adaptation. In addition, the results concerning HSP synthesis in the male gametophyte suggest the possible use of gametophytic selection in crop improvement for thermotolerance.

STUDIES ON GENETIC DIVERGENCE AND REACTION TO IRON CHLOROSIS IN AEROBIC RICE (ORYZA SATIVA L.) ON VERTISOLS IN MAHARASTRA

The present study was carried out to study the genetic parameters for yield, yield contributing, quality and nutritional characters along with reaction of genotypes against iron chlorosis in vertisols. The experiment consisted of 50 promising genotypes along with standard checks viz., Basmati-370, Parag and Avishkar were grown in randomized block design with three replications. The analysis of variance revealed that all the characters under study. Different genotypes showed some degrees of tolerance to iron chlorosis. And, some other characteristics like number of effective tillers per plant, number of filled grains per panicle, number of unfilled grains per panicle, gel consistency, flag leaf area, straw yield, grain yield per plot and grain yield per plant showed high estimates of phenotypic coefficient of variation, high heritability with high genetic advance. All characters which exhibited high estimates of both genotypic and phenotypic variance coupled with high heritability and high genetic advance can be employed for simple selection for crop improvement. Furthermore, variation in such characters are result of additive gene effects and can be explored and studied for potentialities of being used as parents in breeding program for improvement for particular traits.