Genotype environment interaction analysis for fruit yield in okra (Abelmoschus esculentus L.) under alkaline environments

Twenty four Okra genotypes were evaluated for marketable fruit yield and its related traits for genotype environment interaction during 2015-16 and 2016-17. The genotypes were exposed to alkaline environment with a pH range of 8.0±0.2, 8.5±0.2, 9.0±0.2 and 9.5±0.2. A significant level of deviation in expression of different traits was observed in all the genotypes with increasing pH. Based on Additive Main Effects and Multiplicative Interaction (AMMI), Genotype and Genotype Environment Interaction (GGE) biplot, Wrick’s ecovalence (Wi2 ), AMMI Stability Value (ASV) and Yield Stability Index (YSi) stable genotypes with high fruit yield were identified over the eight environments. The combined AMMI analysis of variance indicated that genotype main effect, environment and genotype-by-environment interaction effects showed variation of 19.83%, 63.07% and 17.10%, respectively for fruit yield. On the basis of different stability measures, VRO-112, VRO-110, Kashi Kranti, VROB178, AE-70 and VRO-108 were differentiated as high yielding and stable genotypes over the tested environments. This study will be helpful for selecting alkali tolerant okra parents for further breeding programme and recommending the suitable genotypes for alkalinity prone area

Inheritance of photo-sensitivity in pigeonpea

Pigeonpea [Cajanus cajan (L.) Millsp.] is a short-day legume species and the late maturing genotypes are more photosensitive than early types. To generate information about the inheritance of photo-sensitivity, this study was conducted under natural and artificially extended (16 h) photo-periods using F1, F2 and BC1F1 generations. Under natural photo-period, F1 hybrids showed partial dominance of earliness; while in F2 , a normal distribution that was skewed towards earliness was observed. In contrast under extended photo-period, the spread of F2 data was wide with discontinuities recorded at day 70, 82 and 103. Chisquare tests, when applied to F2 and BC1F1 data, suggested that three dominant genes (PS3 , PS2 and PS1 ) controlled the expression of photo-sensitivity. These genes were found operating in a hierarchical order with PS2 and PS1 genes failing to express in the presence of PS3 gene. Similarly in the absence of PS3 gene, PS2 expressed but it masked the expression of PS1 . Further, PS1 gene expressed only when both PS3 and PS2 were in recessive homozygous state. Hence, the proposed genetic model for photosensitivity in pigeonpea is PS3 > PS2 > PS1 and photoinsensitive genotype being a triple recessive (ps3ps3ps2 ps2ps1ps1 ). .

R-AMMI-LM: Linear-fit Robust-AMMI model to analyze genotype-by environment interactions

Outliers are a common phenomenon when genotypes are evaluated over locations and years under field conditions and such outliers makes studying genotype-environment Interactions difficult. Robust-AMMI models which use a combination of robust fit and robust SVD approaches, denoted as ‘R-AMMI-RLM’ have been proposed to study GEI in presence of such outliers. Instead of ‘R-AMMI-RLM’ we propose a model which uses a combination of linear fit and robust SVD to study GEI in presence of outliers and we denote this model as ‘R-AMMI-LM’. Here we prove that ‘RAMMI-LM’ was superior over ‘R-AMMI-RLM’ as it recorded very low residual sum of squares and low RMSE values. Thus proposed, ‘R-AMMI-LM’ model could explain the GEI more precisely even in presence of outliers.

Identification of pigeonpea genotypes with wider adaptability to rainfed environments through AMMI and GGE biplot analyses

Pigeonpea [Cajanus cajan (L.) Millspaugh] is an important pulse crop grown under Indian rainfed agriculture. Twenty eight pigeonpea genotypes were tested for stability and adaptability across ten rainfed locations in the States of Telangana and Karnataka, India using AMMI (additive main effects and multiplicative interaction) model and GGE (genotype and genotype by environment) biplot method. The grain yields were significantly affected by environment (56.8%) followed by genotype × environment interaction (27.6%) and genotype (18.6%) variances. Two mega environments were identified with several winning genotypes viz., ICPH 2740 (G15), TS 3R (G10), PRG 176 (G8) and ICPL 96058 (G22). E2 (Gulbarga, Karnataka), E3 (Bidar, Karnataka) and E6 (Vikarabad, Telangana) were the most discriminating environments. Genotypes, ICPH 2740, PRG 176 and TS 3R were the best cultivars in all the environments whereas PRG 158 (G9), ICPL 87119 (G12), ICPL 20098 (G19) and ICPL 96058 (G22) were suitable across a wide range of environments. Genotypes, ICPH 2740 and PRG 176 can be recommended on a large scale to the farmers with small holdings to enhance pigeonpea productivity and improve the food security

New hyper-variable SSRs for diversity analysis in mango (Mangifera indica L.)

Whole genome sequence in mango offers unprecedented opportunities for genomics assisted crop improvement via enabling access to genome-wide genetic markers. In the present study, simple sequence repeats (SSRs) were predicted from genome sequence of mango. Based on the SSR length (? 50 bp), highly-variable mango SSRs (MSSRs) were sorted. A sub-set of 129 MSSRs was validated on a set of 24 diverse mango genotypes yielding marker validation and polymorphism of 88.96 and 85.27 per cent, respectively. One hundred and ten polymorphic markers were identified for the present set of mango genotypes. Polymorphic information content (PIC) ranged from 0.10 to 0.78 and the highest value was observed with MSSR133. The mean PIC value was 0.40 but 33 MSSR markers showed PIC values ? 0.5, suggesting that these markers can efficiently measure genetic diversity and serve for mapping of quantitative trait loci (QTLs) in mango. MSSRs data was further used for diversity analysis of mango genotypes belonging to different agro-ecological conditions including chance seedlings, landraces, exotic and indigenous germplasm and hybrids. Cluster analysis using UPGMA of 24 mango genotypes revealed that these MSSRs were informative in diversity analysis and distinguished mango genotypes based on their origin, parentage and embryo types. A novel set of 110 hyper-variable SSR markers have been added to the mango repository depicting usefulness in discriminating closely related mango germplasm and their use in mango improvement programme.

Resolvable mating-environmental designs for partial triallel cross experiments

Triallel crosses can be readily exploited as breeding tool for developing commercial hybrids with traits of genetical and commercial importance by acquiring information on specific combining ability effects along with general combining ability effects if the experimentation size is reduced to an economical extent. In this paper, methods of constructing designs involving partial triallel crosses in smaller blocks using different types of lattice designs have been introduced. The designs have low degree of fractionation, which suggests their utility when there is a resource crunch. Canonical efficiency factor of these designs relative to an orthogonal design with same number of lines, assuming constant error variance for both situations, is high indicating that adoption of these designs for the trials could bring about improvement as the recommendations from the experiment will be associated with a high precision.

Identification of potential donor for pro-vitamin A using functional markers in maize (Zea mays L)

Vitamin A deficiency (VAD) is a global health problem. Maize naturally accumulates carotenoids including ?-carotene, a major source of vitamin A. Thirty-seven Indian maize genotypes were screened for total carotenoids and ?carotene content. A positive significant association of kernel colour was observed with total carotenoid but not for ?-carotene. The level of ?-carotene among the selected 37 genotypes was low (0.14 to 4.63µg/g) as compared to total carotenoids (15.94 to 66.46 µg/g) thus necessitates the introduction and deployment of lines with high ?carotene. Hence, 54 inbred lines developed under the HarvestPlus programme were screened with functional markers of lcyE and crtRB1 genes of the carotenoid biosynthetic pathway. Three genotypes (HP704-13, HP704- 22, and HP704-23) amplified most of the favorable alleles for both these genes. However, due to long Anthesis Silking Interval (ASI) and poor adaptation HP704-13 and HP704-23 could not be maintained. Under normal storage condition genotype, HP704-22 recorded 7.32 µg/g of ?-carotene which can be used as a donor for provitamin-A or to diversify the Indian germplasm.

Characterizing the diversity of grain phytic acid content in Indian rice landraces by multivariate genetic analyses

Phytic acid (PA) acts as chelator of cationic mineral elements iron (Fe) and zinc (Zn) and obstructs their absorption in the human gut. We have evaluated a set of 162 traditional rice landraces for phytic acid phosphorus (PA-P), inorganic phosphorus (Pi) and total phosphorus (TP). Wide variability was observed for PA-P, Pi and TP ranging from 1.12 to 3 mg/g, 0.004 to 0.16 mg/g and 1.17 to 3.04 mg/g respectively. The mineral micronutrients, Fe and Zn were not in correlation with PA-P, Pi and TP implicating the possibility of their independent improvement while PAP showed a significant positive correlation with TP and significant negative correlation with Pi. Principal component analysis (PCA) identified two principal components PC1 and PC2, explaining 50.6 % and 32.1 % of the total variation, respectively. Cluster analysis grouped the accessions into four clusters. The study has also led to the identification of promising donors such as P1490 and Gowri with low PA content to be utilized in rice biofortification programmes.

Principal component analysis of JNPT lines of rice for the important traits responsible for yield and quality

In present study, 67 JNPT (Jawahar New Plant Type) lines were evaluated for 28 morphological and quality traits planted in RCBD with three replications. Principal Component Analysis (PCA) revealed that out of 28, only eight PCs exhibited more than 1.0 eigen value and showed about 81.84% total variability. For selecting the high yielding genotypes in rice, the characters viz., spikelet density, spikelet fertility, number of tillers plant–1and panicle weight plant–1 may be considered. On the basis of high PC score ten most prominent lines namely JNPT-1059-9, JNPT-1059- 10, JNPT1062-1, JNPT-1062-2, JNPT-1064-9, JNPT-1065-1, JNPT-1065-2, JNPT1065-3, JNPT-1066-52 and JNPT-1068- 65 were identified for yield and quality traits.

Selection of elite parents and crosses for seed yield and its components using combining ability analysis over the three environments in safflower (Carthamus tinctorious L.)

Thirty crosses developed through line × tester mating design were evaluated along with parents in three environments to estimate gca and sca effects of parents and crosses, respectively for yield and its contributing traits. Based on consistent performance over three environments in safflower (Carthamus tinctorious L.) genotypes, BHIMA, GMU 3876, GMU 3863, GMU 7351, GMU 2757, AKS 08R and AKS CMS 2B were found to be good general combiners for yield and most of yield contributing characters. Hybrids, AKS CMS 2A x BHIMA, AKS CMS 2A x GMU 3876 and AKS CMS 2A x GMU 3863 having high sca effects were found promising for seed yield per plant and other traits over the three environments. The results indicated that these parents could be exploited in hybridization programmes for genetic improvement of individual traits. However, the promising hybrids having high sca effects may be used for heterosis breeding after multi-locations testing.