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Climate resilience is the most concentrated subject in the current scenario for rice improvement. The aerobic system of rice cultivation involving direct seeding with need-based irrigation in non-puddled soil is gaining ground with respect to a current scenario of water scarcity. The selection of lines suitable and stable under aerobic along with irrigated conditions without any yield penalty is one of the focus areas of the breeding programme for resource use efficiency. In the present study, we have screened a panel of 118 rice lines under aerobic i.e. limited water conditions and irrigated conditions at ARS Dhadesugur Karnataka to identify ideal selection indices viz. STI, TOL, SSI, YSI, YR, YI, PYR, MP and GMP for selecting the best high-yielding and stable lines under both rice cultivation methods. The deployment of selection indices here only pertains to finding the differences in yield per plant under aerobic and irrigated conditions. According to the results of multivariate analysis (correlation and PCA), STI, YI, MP and GMP exhibited a strong correlation with YP and YS. Therefore, they appear to be the most effective stress indices for the selection of lines with good yield potential under water-limited and irrigated conditions. These indices serve as valuable selection criteria for the identification of aerobic-tolerant cultivars from both water-limited and normal conditions. These indices identified lines, DB 5 (Swarna × Oryza nivara (IRGC 81848)) and NPK-40 (Swarna × Oryza nivara (IRGC81832)) wild introgression lines. GNV-14-96-1 (BPT-5204 × Nerica line) Advanced breeding line. JBB 631-1 ((Swarna*2/ IRGC 4105) (RP 5405-JBB-631-1-1-1-1-1-1)) Tropical japonica × indica introgression line. KR-209 (Wazuhophek × ISM) and KR-262 (Wazuhophek × ISM) recombinant introgression lines. TI-36 and TI-124 Ethyl Methane Sulfonate (EMS) mutants of BPT-5204. WB-10 (Langphou) and WB-16 (Phouoibi) North-Eastern Landraces were promising for both environments. These lines are suitable because of low grain yield loss under aerobic conditions and can be further considered for cultivation.

Rice lines need to be grown and evaluated for yield under different agro-ecological locations to identify stable and high-yielding lines for deployment in breeding programs. With this aim, a set of rice germplasm was evaluated for G×E in four different environments (E1-Dadesuguru-Wet 2020, E2-ICAR–IIRR-Dry 2019, E3-ICAR–IIRR-Wet 2020, E4-ICAR–IIRR-Dry 2020). The experimental trial was laid out in a randomized complete block (RCB) design with three replications at each location for 118 rice lines. Data on yield per plant was analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI) and Genotype, and Genotype × Environment Interaction (GGE) models. The combined analysis of variance (ANOVA) manifested significant variations for tested genotypes, locations, years, genotype × year, and genotype × location interactions revealing the influence of environmental factors on yield traits. All four environments showed discrimination power, whereas E2 and E3 were found as the representative environment as they fall near the Average-Environment axis (AEA). The AMMI biplot PC1 contributed 79.20% variability and PC2 contributed 15.18% variability. From the GGE biplot analysis, the rice lines Phouren, JBB-631-1, and JBB-1325 were found to be the best and most stable. The rice lines Phouren, PUP-229, and TI-112 were stable in the first sub-group Dhadesugur-Wet 2020 (E1). The rice lines Langphou, and NPK-45 were stable in the second sub-group ICAR-IIRR-Wet 2020 (E3). Environment ICAR-IIRR-Dry 2019 (E2) was the third subgroup and the rice lines Moirangphou-Yenthik and TI-3 topped for the same. The ICAR IIRR-Dry 2020 (E4) environment formed the fourth subgroup where Phouren-Amubi, TI-128 and JBB-1325 topped the season. In conclusion, this study revealed that G × E interactions are significant for yield variation, and its AMMI and biplots analysis are efficient tools for visualizing the response of genotypes to different locations.

Hybrid breeding technology is one of the most feasible options to meet the future food challenges and sustainable agriculture. Genetic diversity studies determine the inherent potential of a cross for heterosis and frequency of desirable recombinants. Optimum parental diversity is required to obtain superior cross combinations in the further generations. Hence, the present study was conducted with 100 maintainer lines of rice hybrids using eighty SSR markers, out of which 16 were found to be polymorphic and 10 were monomorphic. Molecular diversity analysis revealed a total of five clusters at a similarity coefficient 0.73. Sixteen out of 80 markers were found to be polymorphic. The number of alleles per locus ranged from 2 to 8 with an average per locus of 4.5. The PIC values varied widely among SSR loci tested and ranged from a minimum 0.37 (JGT725.2) to maximum 0.76 (RM12424) with an average of 0.61. The highest similarity was observed between TCP 1128 and TCP 1145 whereas the most diverse genotypes were TCP726 and TCP816. The most diverse genotypes could be used as parents in the hybridization experiments.

Soil phosphorus (P) deficiency is one of the major challenges for rice cultivation. The present study was carried out under low soil P condition (available P, < 2 kg ha-1) to study the genetic variability, correlation, path and principal component analysis (PCA) in a set of 40 introgression lines derived from Samba Mahsuri (Oryza sativa ssp. indica) × Oryza rufipogon. High genotypic coefficient of variation and phenotypic coefficient of variation was recorded for productive tillers (PT), seed weight (SW), and grain yield (GY). High heritability coupled with high genetic advance was recorded for plant height (PH), PT, SW, number of spikelets/panicle (SPP), spikelet fertility, and GY. Correlation analysis revealed that grain yield had a significant positive association with PH, PT, panicle length, SPP, and SW. Regression analysis revealed that the grain yield was mainly influenced by PT and SW. This was confirmed by path analysis, wherein PT and SW exerted the highest direct positive effect on grain yield. The PCA revealed that the first two PCs contribute to maximum variability, which together accounted for 60% of the total variability. The traits PT and SW contributed the maximum to load/variance the total variability. Thus, the selection of introgression lines with a greater number of PT and higher SW would be the most appropriate strategy for yield improvement under low soil P condition in rice. Cluster analysis grouped introgression lines along with checks into three clusters. Overall, the study revealed the pattern genetic variability for low P tolerance in the introgression lines. This further helps in designing appropriate breeding strategies for the improvement of rice cultivars for low P tolerance.

Recent predictions on climate change indicate that high temperature episodes are expected to impact rice production and productivity worldwide. The present investigation was undertaken to assess the yield stability of 72 rice hybrids and their parental lines across three temperature regimes over two consecutive dry seasons using the additive main effect and multiplicative interaction (AMMI), genotype and genotype × environment interaction (GGE) stability model analysis. The combined ANOVA revealed that genotype × environment interaction (GEI) were significant due to the linear component for most of the traits studied. The AMMI and GGE biplot explained 57.2% and 69% of the observed genotypic variation for grain yield, respectively. Spikelet fertility was the most affected yield contributing trait and in contrast, plant height and tiller numbers were the least affected traits. In case of spikelet fertility, grain yield and other yield contributing traits, male parent contributed towards heat tolerance of the hybrids compared to the female parent. The parental lines G74 (IR58025B), G83 (IR40750R), G85 (C20R) and hybrids [G21 (IR58025A × KMR3); G3 (APMS6A × KMR3); G57 (IR68897A × KMR3) and G41 (IR79156A × RPHR1005)] were the most stable across the environments for grain yield. They can be considered as potential genotypes for cultivation under high temperature stress after evaluating under multi location trials.

Soil phosphorus (P) deficiency is one of the major challenges for the cultivation of rice worldwide because it limits the growth and productivity of the crop. Therefore, the ability to grow in P-deficit soils is an important trait for rice cultivation. O . rufipogon Griff., a wild relative of rice, is a source of genetic variation for low phosphorus tolerance. The present study was undertaken to identify low P stress-tolerant introgression lines by analysing stress tolerance indices of 40 introgression lines of O. rufipogon. The populations were screened under low soil P and normal soil P plots for two growing seasons. Based on yield under stress and normal conditions, we computed different stress indices, including stress tolerance index (STI), tolerance index, yield reduction ratio (YR), stress susceptibility index, yield stability index (YSI), yield index, per cent yield reduction and geometric mean productivity (GMP). The studies of correlation analysis, principal component analysis and clustering revealed that STI, YSI and GMP were ideal indices for the selection of genotypes that performed well under both stress and normal conditions. Based on these indices, introgression lines (IL-24, IL-29 and IL-32) were identified as promising low P tolerant lines, which exhibited better grain yield under both stress (YS) and normal (YP) conditions. These pre-breeding lines serve as valuable genetic resources for low P tolerance in rice breeding programmes across the world.

The wild species of rice, Oryza rufipogon, is a source of genetic variation for yield-enhancing traits and blast resistance. With the objective to genetically enhance the elite rice cultivar, ‘Samba Mahsuri’, a set of 192 BC2F2 and BC2F3 lines developed from O. rufipogon was characterized for yield-enhancing traits and blast resistance. The study revealed the presence of significant genetic variability and transgressive segregation for productive tillers, spikelets per panicle, and grain yield per plant. The study also identified several introgression lines superior to the recurrent parent for yield enhancing traits and blast resistance. Molecular characterization of 26 blast resistant lines identified multiple blast resistance genes in IL-136 [Pib, Pi9 (t), Pi54, Pi38, Pitp and Pi20(t)], IL-3 [Pib, Pi54, Pi38, Pitp and Pi20(t)], and IL-140 [Pib, Pi9(t), Pi54, Pi38, and Pitp]. Based on the performance of yield-enhancing traits and blast resistance, seven lines (IL-27, IL-28, IL-29, IL-72, IL-139, IL-158 and IL-171) showed merit. Estimation of the recovery of the recurrent parental genome by using 117 polymorphic SSR markers revealed that recurrent-parental genome recovery varied from 54.0 (IL-158) to 92.3% (IL-27). These promising, high-yielding introgression lines with multiple blast-resistance genes can serve as important genetic resources for yield and blast resistance improvement in rice, especially for the southern India.

Nested association mapping (NAM) captures the best features of both linkage and association mapping and enables the high power and high resolution of quantitative trait locus mapping through joint linkage-association analysis. In the current study, NAM population was developed by hybridizing JS 335, a popular variety of central India with 20 diverse soybean genotypes. The parents used in the study have various traits of economic importance such as drought and water-logging tolerance, bacterial pustule and yellow mosaic virus resistance, wider adaptability, resistance to mechanical damage and higher yield potential. High variability in the F2 populations of 20 crosses for grain yield and days to maturity indicated scope for development of high-yielding varieties. Genetic variability studies, correlation, regression, principal component analysis (PCA) and genetic diversity analyses were carried out in 900 NAM-recombinant inbred lines (RILs) derived from 11 crosses. Correlation and regression analysis indicated a significant positive effect of biomass, pods/plant, harvest index, branches/plant, nodes/plant and plant height on grain yield. Genetic diversity analysis grouped 900 NAM-RILs into 10 clusters. PCA revealed first two principal components to explain 63.78% of total variation mostly contributed by grain yield, biomass and number of pods. The inbred lines developed in this study will serve as an elite soybean genetic resource in understanding the genetic architecture underlying different traits of economic significance.

Phosphorus (P) is one of the macro nutrients essential for plant growth and development. Rice (Oryza sativa L.) is sensitive to P starvation and its deficiency influences many key plant functions which results in crop yield penalty. Although the hybrid rice segment is well-known for its yield heterosis, P deficiency and bacterial leaf blight (BLB) diseases are the evident limitations. APMS6B, the female parent of DRRH-3 is susceptible to low P and bacterial blight disease. In the present study, the improvement of APMS6B to P starvation and resistance to bacterial leaf blight (BB) was carried out using marker-assisted backcross breeding (MABB) approach. Kasalath (+ Pup1 QTL) was used as donor and a promising IL (ATR 594-1) at BC1 F4 generation was identified with 81.15% RPGR. Concurrently, this IL was intercrossed with GU-2 (+ Xa21 and Xa38 ). Hybridity of Intercross F1s (ICF1) was confirmed through foreground selection having maximum RPGR (88.29%) and were selfed to produce ICF2. The resultant progenies were phenotyped for BB using Xoo inoculum (IX-020), simultaneously genotyped with gene specific functional SSR markers for Xa21 and Xa38. The identified BB resistant plants were subjected to foreground selection for Pup1. Four promising ICF3 plants (BP-10-1, BP-10-3, BP-10-5 and BP-10-15 with Xa21, Xa38 and Pup1) along with parents and checks were screened both in low P plot (2O5 ha-1 ) as well as in normal plot (>25 kg P2O5 ha-1) during dry and wet seasons 2018. Based on the field evaluation, four promising intercrossed lines were identified with better root architecture in terms of root length and root volume. In addition, less % reduction in grain yield (39.10%) under P starvation and less susceptibility indices values (

The brown planthopper (Nilaparvatalugens (Stal) is a major insect pest that is primarily present in Asia causing a significant impact on rice crop. Seventy-three rice genotypes were evaluated for molecular diversity based on known BPH resistance loci. A total number of 108 alleles were detected by 39 polymorphic markers with an average of 2.37 alleles per locus. The allele frequency which is useful in estimating the frequency of alleles, ranged from 0.054 to 0.9726, while the expected heterozygosity varied between 0.054 (RM494) and 0.688 (RM231) with an average of 0.431.The Polymorphic Information Content (PIC) values provided an estimation of the marker’s discriminating power by ranged from 0.066 (RM496) to 0.621 (RM231) suggesting moderate level of polymorphism for the selected BPH specific SSR markers among the germplasm lines. Accounting the major allele frequency, heterozygosity and PIC content, the marker RM231 associated with QBph3.1 and regarded as the most informative one along with RM19291, RM335, RM469, RM518, RM8213, RM228, RH078 and RM589 for dissecting the molecular diversity of germplasm lines with respect to BPH resistance. Based on the marker data, the genotypes were classified into seven clusters that distinguished the lines clustering as resistant and susceptible separately. The information about the genetic diversity of these lines will be extremely useful for proper selection of parents related to BPH reaction, especially for gene mapping and for marker assisted selection. Key wordsRice, Brown planthopper resistance, Molecular diversity, Microsatellite markers

Thirty-one accessions ofOryza glaberrimawere evaluated to study the genetic variability, correlation, path, principal component analysis (PCA) andD2analysis. Box plots depicted high estimates of variability for days to 50% flowering and grain yield per plant inKharif2016, plant height, productive tillers, panicle length and 1000 seed weight inKharif2017. Correlation studies revealed days to 50% flowering, plant height, panicle length, number of productive tillers, spikelets per panicle having a high direct positive association with grain yield, while path analysis identified the number of productive tillers having the maximum direct positive effect on grain yield. Days to 50% floweringviaspikelets per panicle, productive tillers and plant heightviaspikelets per panicle exhibited high positive indirect effects on grain yield per plant. PCA showed that a cumulative variance of 54.752% from yield per plant, days to 50% flowering, spikelets per panicle and panicle length, contributing almost all the variation of traits whileD2analysis identified days to 50% flowering and grain yield per plant contributing maximum to the genetic diversity. Therefore, selection of accessions with more number of productive tillers and early maturity would be most suitable for yield improvement programme. The study has revealed the utility of African rice germplasm and its potential to utilize in the genetic improvement ofindica rice varieties.

Background: Identification of suitable factors that influence significantly to the response is crucial for the traits based breeding program to make a better decision about improvement in productivity. Multiple linear regression (MLR) is the benchmark method commonly using to identify suitable factors for crop improvement. It doesn’t work always due to stringent assumption (Multicollinearity, Linearity) behind the MLR model. Here we tried to develop an efficient model for the selection of major traits that contribute to seed yield in soybean by comparing different models.Methods: Field experiment was conducted using 98 soybean core population through augmented design.18 morphometric traits obtain from soybean core population were considered under the study as regressors.Multiple linear regression (MLR), Principle component Regression (PCR), Regression tree and Random Forest models were compared to select traits based on prediction accuracy.Result: All the models identified the number of pods per plant (NPP) has the most influencing variable to the soybean yield. However random forest has a much higher prediction power (RMSE=4.59, MAPE=0.18) compared to other models under study. The results of random forest revealed that the number of pods per plant, number of branches per plant and other associated characters like plant height at harvest as highly influencing traits for seed yield in soybean.Finally, tried to identify genotypesthat possess superiority about most influencing morphological characters on seed yield using cluster analysis.

Genetic improvement of rice for grain micronutrients, viz., iron (Fe) and zinc (Zn) content is one of the important breeding objectives, in addition to yield improvement under the irrigated and aerobic ecosystems. In view of developing genetic resources for aerobic conditions, line (L) × tester (T) analysis was conducted with four restorers, four CMS lines and 16 hybrids. Both hybrids and parental lines were evaluated in irrigated and aerobic field conditions for grain yield, grain Fe and Zn content. General Combining Ability (GCA) effects of parents and Specific Combining Ability (SCA) effects of hybrids were observed to be contrasting for the micronutrient content in both the growing environments. The grain Fe and Zn content for parental lines were negatively correlated with grain yield in both the contrasting growing conditions. However, hybrids exhibited positive correlation for grain Fe and Zn with grain yield under limited water conditions. The magnitude of SCA mean squares was much higher than GCA mean squares implying preponderance of dominance gene action and also role of complementary non-allelic gene(s) interaction of parents and suitability of hybrids to the aerobic system. The testers HHZ12-SAL8-Y1-SAL1 (T1) and HHZ17-Y16-Y3-Y2 (T2) were identified as good combiners for grain Zn content under irrigated and aerobic conditions respectively.

With an objective of mapping novel low soil P (Phosphorus) tolerance loci in the non-Pup1 type donor rice line, Wazuhophek, we screened a recombinant inbred line (RIL) mapping population consisting of 330 lines derived from the cross Wazuhophek x Improved Samba Mahsuri (which is highly sensitive to low soil P) in a plot with low soil P for tolerance associated traits. Molecular mapping with SSR markers revealed a total of 16 QTLs (seven major and nine minor QTLs), which are associated with low soil P tolerance related traits. Interestingly, a QTL hotspot, harbouring 10 out of 16 QTLs were identified on the short arm of chromosome 8 (flanked by the makers RM22554 and RM80005). Five major QTLs explaining phenotypic variance to an extent of 15.28%, 17.25%, 21.84%, 20.23%, and 18.50%, associated with the traits, plant height, shoot length, the number of productive tillers, panicle length and yield, respectively, were located in the hotspot. Two major QTLs located on chromosome 1, associated with the traits, total biomass and root to shoot ratio, explaining 15.44% and 15.44% phenotypic variance, respectively were also identified. Complex epistatic interactions were observed among the traits, grain yield per plant, days to 50% flowering, dry shoot weight, and P content of the seed. In-silico analysis of genomic regions flanking the major QTLs revealed the presence of key putative candidate genes, possibly associated with tolerance.

This study was conducted to characterize new plant type (NPT) traits among 650 genetically diverse rice genotypes of tropical japonica and indica and to establish an initial core set for NPT traits. Analysis of variance revealed highly significant differences among the genotypes for all the traits assessed except flag length and width and leaf angles. Dendrogram categorized the genotypes into five distinct duration groups. Genotypes viz., Pumphamah, IRGC5097, IRGC37015, IRGC43741, IRGC50448, IRGC53089, IRGC39111, IRGC18021, Haorei Machang, IRGC44069, IRGC8269, Thangmoi, IRGC33130 and IRGC29772 were identified as possessing strong culm. Long panicles with a length of more than 35 cm were found in IRGC8269, IRGC9147, IRGC14694, IRGC19642, IRGC27435, IRGC39111, IRGC31051, IRGC26011and IRGC25892. Ideal leaf angle of NPT genotypes of 5°, 10° and 20° of flag leaf, 1st and 2nd leaves was not found in any genotype but with a combination of 5°, 10° and 10° was observed in IRGC63102 and IRGC66644. NPT flag leaf length and width of 50 and 2 cm, respectively, was seen in ‘Kemenya Kepeu’ and ‘IRGC29772’. High grain number of more than 350 was observed in IRGC53089, IRGC31063 and Azhoghi. A total of 72 genotypes were found with a combination of one or more ideal plant type traits of which, hierarchical cluster analysis based on genetic distances selected 32 as NPT core set. This core set will serve as an ideal genetic resource for breeding programs aimed at NPT development.

Soybean is a leading oilseed crop in India, which contains about 40% of protein and 20% of oil. Core collection will accelerate the management and utilization of soybean genetic resources in breeding programmes. In the present study, eight agromorphological traits of 3443 soybean germplasm were analysed for the development of core collection using the principal component score (PCS) strategy and the power core method. The PCS strategy yielded core collection (CC1) of 576 accessions, which accounted for 16.72% of the entire collection (EC). The analysis based on the power core programme resulted in CC2 of 402 accessions, which accounted for 11.67% of the EC. Statistical analysis showed similar trends for the mean and range estimated in both core collections and EC. In addition, the variance, standard deviation and coefficient of variance were in general higher in core collections than in the EC. The correlations observed in the EC in general were preserved in core collections. A total of 311 and 137 unique accessions were found in CC1 and CC2 in addition to 265 accessions that were found to be common in both core collections. These 265 common accessions were the most diverse core sets, which accounted for 7.64% of the EC. We proposed to constitute an integrated core collection (ICC) by integrating both common and unique accessions. The ICC comprised 713 accessions, which accounted for about 20.62% of the EC. Statistical analysis indicated that the ICC captured maximum variation than CC1 and CC2. Therefore, the ICC can be extensively evaluated for a large number of economically important traits for the identification of desirable genotypes and for the development of mini core collection in soybean.

A set of 90 Indian soybean landraces were analysed for polymorphism at 43 SSRs and five allele specific markers of four major genes involved in regulating flowering and photoperiod response. A total of 42 polymorphic SSRs had amplified 126 alleles which served as raw data for estimation of genetic relationship and population structure among 90 accessions. Rare alleles of four and three SSRs were detected in accessions IC18768 and IC15089, respectively. Gene diversity in the population ranges from 0.065 to 0.717 with a mean value of 0.411. The polymorphism information content of 42 SSRs varied from 0.063 to 0.668. Hierarchical clustering based on neighbour-joining method identified three major clusters among 90 soybean accessions. Model based population structure analysis divided the 90 soybean accessions into four populations (K = 4). Mean value of Fst for different populations ranged between 0.4143 and 0.7239. Genotyping of 90 accessions with allele specific markers had identified accession IC15089 as triple recessive mutant of flowering genes E1, E2 and photoperiod sensitivity gene E3. The triple mutant IC15089 (e1, e3, e3) had been characterized phenotypically and identified as early maturing (88 days) and photoperiod insensitive genotype under extended photoperiod. The present study characterized genetic relationship among 90 Indian soybean landraces and had identified a few diverse and unique genotypes for utilization in soybean breeding programmes targeting development of short duration and photoperiod insensitive varieties through marker assisted selection. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12298-018-0615-3) contains supplementary material, which is available to authorized users.

Oryza latifolia Desv is an aquatic plant belonging to the Officinalis complex of Oryza. It is an allotetraploid species contains a CCDD genome with 2n = 48 chromosomes. It grows widely in aquatic ecosystems of Latin American region. Oryza latifolia is closely related to two other allotetraploid species of the Officinalis complex, namely O. alta and O. grandiglumis. Morphologically and cytologically, these three species resemble each other with few distinct features. However, genomic studies have demonstrated clear distinctions among these three species of the Officinalis complex. Multiple sequence-based phylogenetic studies have revealed that the CD genome of O. latifolia might have originated from a single hybridization event between C genome species (O. officinalis or O. rhizomatis) as maternal parent and an E genome species (O. australiansis) as paternal parent during evolution. O.latifolia possesses important genes/QTLs for yield-enhancing traits, biotic, and biotic stress. Through interspecific hybridization and embryo rescue, synthetic amphidiploids of O. sativa and O. latifolia are successfully developed. Several QTLs for plant height, primary branches per panicles, grains per panicle, biomass, and lodging resistance have been identified from O. latifolia. Monosomic alien addition lines derived from O. latifolia were developed for introgression of beneficial QTLs. Brown planthopper resistance gene Bph12 was identified and introgressed from O. latifolia. Therefore, O. latifolia is an important genetic resource for genetic improvement of domesticated cultivars.

Oryza alta Swallen is an allotetraploid perennial wild rice belonging to the Officinalis complex and contains a CCDD genome with 2n = 48 chromosomes. It is closely related to other two species of the Officinalis complex, namely O. latifolia and O. grandiglumis. It is widely distributed in South American regions and grows along the river basins, canals in open and sunny areas. The total genome size of O. alta is estimated to be 1008 Mbp. Genome sequence analysis reveals that duplicated contigs in the genome are due to orthologous genes, while gene loss and gene rearrangement could be due to polyploidization. The phylogenetic analysis of mitochondrial and chloroplast using SSR markers has revealed that CC genome (O. eichengeri) could be the maternal parent. O. alta has a higher biomass and resistance to several insects and diseases. Hence, it could serve as important genetic resources for improvement of domesticated rice cultivars.

The damage caused to stored seed by bruchids (Callosobruchus maculatus) is considered to be a major production constraint in rice bean (Vigna umbellata). Breeding for genetically determined resistance is the most environmentally benign and cost-effective means to mitigate the losses to bruchid infestation. Here, a screen of rice bean germplasm identified two sources of resistance, and determined the genetic basis of the resistance using a quantitative trait locus (QTL) mapping approach. The two resistant accessions (LRB238 and JP100304) were each crossed to a common susceptible cultivar (LRB26) to generate F2 mapping populations, one of which (LRB238 × LRB26) was genotyped with a range of Vigna sp. microsatellite assays and by sequence related amplified polymorphism (SRAP) fingerprinting. The resulting linkage map comprised ten linkage groups and covered a genetic distance of 872.1 cM with a mean inter-marker distance of 32.05 cM. The subsequent QTL analysis detected the presence of 11 QTL, distributed over all ten linkage groups, most of which were associated with the % damage caused to the seed. Two major QTL, Cmpd1.5 (flanked by the SRAP markers E2M9-270 and E12M7-311) and Cmpd1.6 (flanked by the SRAP marker E7M10-141 and the microsatellite locus CEDG259) mapped within 11.9 cM and 13.0 cM of the flanking markers, respectively, accounted for, 67.3 and 77.4 % of the variance respectively, for % damaged seeds. A bulked segregation analysis carried out in the JP100304 × LRB26 population revealed that the resistance donor harboured some resistance factors not represented in LRB238.

The bread wheat line WR95 showed seedling resistance to several Indian stem rust (Puccinia graminis Pers. f. sp. tritici) isolates. Genetic analysis of stem rust resistance in WR95 was undertaken in populations derived from crosses NI5439/WR95 and Agra Local/WR95. The F1, F2, and F3 generations derived from the cross NI5439/WR95 were tested against stem rust isolate 40A and genetic analysis showed a recessive gene for resistance. The results were confirmed in another F2 population derived from the cross Agra Local/WR95. Interestingly, genetic analysis in F2 population from the later cross i.e. Agra Local/WR95 identified a dominant gene against isolates 11 and 11A. The recessive gene against isolate 40A was mapped to the long arm of 5D chromosome. WR95 showed resistance to virulent isolates of Sr30 which is also located on 5DL chromosome. The dominant gene in WR95 that conferred the resistance to isolate 11 and 11A was mapped towards telomeric region of the long arm of 2B chromosome. The long arm of chromosome 2B also carries stem rust resistance genes Sr9, Sr16 and Sr28. WR95 showed resistance to virulent isolates to Sr9b (11, 11A, 21A-2 and 40A), Sr9e (15-1 and 40A) and Sr28 (11, 11A, 15-1, 21A-2 and 40A). The map position of dominant gene identified in WR95 is different from Sr9 and Sr28 while Sr16 is towards telomeric region and not mapped so far. Therefore, the dominant gene in WR95 may be either Sr16 or a new gene.

The subjective method of eye testing (Myopia/Hyperopia) involves the communication between the optometrist and the Patient. Communication about the vision/clarity of an eye chart, which the Patient experiences, to the Optometrist and the communication which the Optometrist does to Patient would decide the final prescription. Though the Optometrist is expert in communication, if the Patient gives incorrect responses, it leads to inaccurate prescription. To overcome the above problem, the idea is to develop a novel eye testing method called “Patient Subjective Eye Testing (PSET)”, in which a Myopia/Hyperopia Patient interacts with a software application installed on a tablet. A standard eye chart is projected on to a screen. A similar eye chart is also displayed on the tablet. Now the Patient blurs the eye chart that is displayed on the tablet device by applying power in the units of 0.0625 diopters until he/she experiences no difference in the blurness of the optotypes in the projected chart and the displayed chart. The power is recorded and written in to prescription. For the realization of the above method, a Gaussian spatial filter is designed, which blurs the optotypes of the displayed eye chart similar to the blurness experienced in human eye. To design the filter, the amount of Gaussian blur per unit refraction error in human eye is determined by designing a human eye model using ZEMAX tool. For every unit of 0.0625 diopters ( in the range -2 diopters to +2 diopters) change in refraction power of the eye the amount of deviation in Gaussian energy distribution, on the retina, is determined. With these deviation values Gaussian masks are generated which are used by Gaussian filter to blur the eye chart images that are displayed on a tablet device.

Molecular characterization and genetic diversity among 82 soybean accessions was carried out by using 44 simple sequence repeat (SSR) markers. Of the 44 SSR markers used, 40 markers were found polymorphic among 82 soybean accessions. These 40 polymorphic markers produced a total of 119 alleles, of which five were unique alleles and four alleles were rare. The allele number for each SSR locus varied between two to four with an average of 2.97 alleles per marker. Polymorphic information content values of SSRs ranged from 0.101 to 0.742 with an average of 0.477. Jaccard's similarity coefficient was employed to study the molecular diversity of 82 soybean accessions. The pairwise genetic similarity among 82 soybean accessions varied from 0.28 to 0.90. The dendrogram constructed based on genetic similarities among 82 soybean accessions identified three major clusters. The majority of genotypes including four improved cultivars were grouped in a single subcluster IIIa of cluster III, indicating high genetic resemblance among soybean germplasm collection in India.

Efficiency and applicability of a new method of hybridization called ‘pollination without emasculation’ was evaluated in a set of crosses involving Glycine max and Glycine soja genotypes. The genotypes were crossed in various combinations to develop MAGIC (multiparent advanced generation intercross) and NAM (nested association mapping) population as well as to widen the genetic base of soybean through wide hybridization. Success of hybridization ranged from 33% to 77% during kharif season. Number of false crossed seeds as measured through hybridity testing was negligible (0–15%). Rate of crossing success was more during kharif than rabi (17.33%) season. The PWE appeared to be highly efficient and applicable equally to intra-specific and inter-specific crosses in soybean.

Eighty-six soybean varieties differing for various morphological characters were characterized for DUS traits during the kharif seasons from 2007 to 2010 to protect these varieties under Protection of Plant Varieties and Farmers Rights Act (PPV&FRA) 2001. Results of their PCA revealed that days to 50% flowering, plant height and nodes per plant traits accounted for the most variability. The cluster analysis grouped 86 varieties in to 13 groups. The present study proposes sets of hybridization between the high and low mean yield clusters to achieve yield gain in soybean.

An investigation was undertaken to elucidate information on the effects of water stress on yield and yield attributes of soybean { Glycine max (L.) Merrill} at pod development stage. The soybean accessions viz., JS92-22-A, IC18596, IC9311, IC216380, IC110399JS (SH) 99-02, IC16040, IC16040 and VLS53 showed better performance for morphological traits under water stress condition. Among the morphological traits studied, days to maturity showed the maximum reduction (94%) followed by harvest index (69%) and seed yield per plant (55%), while plant height was recorded the lowest reduction of 16% at pod development stage under water stress condition. The genotype VLS53 showed the highest drought tolerance index for seed yield.

Leaf rust of wheat, caused by Puccinia triticina Eriks. is the most regularly occurring rust disease that can cause severe yield losses. Due to relatively lower economic value of durum wheat compared to the common wheat, genetic analysis of leaf rust resistance in durum wheat has been carried out only to a limited extent. Durum wheat genotype Trinakria showed high level and broad spectrum seedling resistance to 18 Indian leaf rust pathotypes. Genetic analysis at seedling stage in F2 and BC1 populations using leaf rust pathotype 77-5 showed a single dominant gene for resistance. The leaf rust resistance gene was mapped to the short arm of 5B chromosome and Xgwm234 was the closest marker at a distance of 6.3cM. The leaf rust resistance gene present in Trinakria is tentatively named as LrTrk. In durum wheat very few Lr genes have been documented, and hence Trinakria could be a promising source of leaf rust resistance for wheat breeders. The Xgwm234 marker linked to leaf rust resistance can be used for transfer of leaf rust resistance from Trinakria to other wheat cultivars through marker assisted selection.

A study was undertaken to assess the response of rice genotypes grown under alkaline soil condition using various multivariate analytical tools. ANOVA and MANOVA revealed significant differences among 33 genotypes for different traits. Principal component analysis (PCA) grouped the traits into three components, which jointly explained 67% of the total variation. Largest variation was explained by total biomass, spikelet per panicle and grain yield per panicle. When different alkalinity groups were compared in pairwise fashion using SIMPER analysis, it was found that there is no common trait to differentiate between the groups. Considering all traits together, Vikas and KMR 3 were identified as the most suitable genotypes which can be utilized as donors for tolerance to alkalinity.