Background: The genotype × environment interaction greatly influences the success of breeding and in multi-location trials complicates the identification of superior genotypes for a single location, due to magnitude of genotype by location interaction are often greater than genotype by year interaction. This necessitates genotype evaluation in multi environments trials in the advanced stages of selection. Methods: Nine elite pigeonpea genotypes of mid-early duration were evaluated in six diverse locations in randomized complete block design with three replications during kharif, 2019 to ascertain the stable genotypes, environments discrimination and genotype by environment crossovers using AMMI and GGE biplot stability models. Result: The results in the present investigation revealed that first two principal components explained 73.4% of variation interaction, while, 80.50% in GGE biplot. Both the models identified WRGE-126 (G6) as stable performer with high yield (1733 kg ha-1) and among the locations Tandur (E1) measured as the ideal environment. Whereas, the environments, Adilabad (E3) and Warangal (E4) were observed representative with better discriminating ability.
Background: Pigeon pea is considered an excellent and affordable source of plant-based protein, essential amino and fatty acids, fibers, minerals and vitamins with consistent source of income and employment to small and marginal farmers and thus holds premier position in the world agriculture. Shifts in rainfall patterns and seasons due to climatic change require the development of varieties with stable and high yield over a wide range of environmental conditions became major objective of crop improvement. Methods: The present study was carried out to ascertain the stable genotypes, environments discrimination and genotype by environment crossovers using different stable models by conducting Multi-location pigeon pea trial in five environments during Kharif, 2018 in Randomized Complete Block Design. Stability analysis for grain yield was performed by deploying the AMMI (Additive Main Effects and Multiplicative Interaction) model and GGE (Genotype and Genotype by Environment) biplot method. The pigeon pea genotype WRG-330 was found superior among all the genotypes over checks over locations, while, WRG-327 exhibited almost minimum interaction with the environments convincing the reliability of the performance. The test environments at Adilabad and Tandur were observed representative with better discriminating ability. Conclusion: It is concluded that there is no large difference between the AMMI and GGE biplot analyses in evaluation of experimental pigeon pea genotypes in different locations and both methods revealed similar results convincing that both methods can be used equally.
Lemon (Citrus lemon (L.) Burm. f.) is an important fruit crop cultivated worldwide, and is grown practically in every state in India (3). During a survey conducted in 2013, a few small trees in a lemon orchard near Mysore city (Karnataka) (12°19.629′ N, 76°31.892′ E) were found affected by dieback disease. Approximately 10 to 20% of trees were affected as young shoots and branches showed progressive death from the apical region downward. Different samples were collected and diagnosed via morphological methods. The fungus was consistently isolated from the infected branches when they were surface sanitized with 1.5% NaOCl and plated on potato dextrose agar (PDA). Plates were incubated at 26 ± 2°C for 7 days at 12/12 h alternating light and dark period. Fungal colonies were whitish with pale brown stripes having an uneven margin and pycnidia were fully embedded in the culture plate. No sexual state was observed. Pycnidia were globose, dark, 158 to 320 μm in diameter, and scattered throughout the mycelial growth. Both alpha and beta conidia were present within pycnidia. Alpha conidia were single celled (5.3 to 8.7 × 2.28 to 3.96 μm) (n = 50), bigittulate, hyaline, with one end blunt and other truncated. Beta conidia (24.8 to 29.49 × 0.9 to 1.4 μm) (n = 50) were single celled, filiform, with one end rounded and the other acute and curved. Based on the morphological and cultural features, the fungal pathogen was identified as Phomopsis citri H.S. Fawc. Pathogenicity test was conducted on nine healthy 2-year-old lemon plants via foliar application of a conidial suspension (3 × 106); plants were covered with polythene bags for 6 days and maintained in the greenhouse. Sterile distilled water inoculated plants (in triplicate) served as controls and were symptomless. Development of dieback symptoms was observed after 25 days post inoculation and the fungal pathogen was re-isolated from the inoculated lemon trees. The internal transcribed spacer region (ITS) of the isolated fungal genomic DNA was amplified using universal-primer pair ITS1/ITS4 and sequenced to confirm the species-level diagnosis (4). The sequence data of the 558-bp amplicon was deposited in GenBank (Accession No. KJ477016.1) and nBLAST search showed 99% homology with Diaporthe citri (teleomorph) strain 199.39 (KC343051.1). P. citri is known for its association with melanose disease of citrus in India, the United States, and abroad. P. citri also causes stem end rot of citrus, which leads to yield loss and reduction in fruit quality (1,2). Dieback disease is of serious concern for lemon growers as it affects the overall productivity level of the tree. To the best of our knowledge, this is the first report of P. citri causing dieback of lemon in India. References: (1) I. H. Fischer et al. Sci. Agric. (Piracicaba). 66:210, 2009. (2) S. N. Mondal et al. Plant Dis. 91:387, 2007. (3) S. P. Raychaudhuri. Proc. Int. Soc. Citriculture 1:461, 1981. (4) T. J. White et al. Page 315 in: PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, CA, 1990.
An experiment was carried-out with forty-eight hybrids of pigeonpea and two checks for nine characters at Agricultural Research Station, Tandur (Professor Jayashankar Telangana State Agricultural University). Analysis of variance revealed significant differences among the hybrids for all the nine characters studied. The results of genetic parameters revealed that, high genotypic (GCV) and phenotypic coefficients of variations (PCV) were observed for seed yield and number of pods per plant. Six characters viz., number of branches per plant, number of pods per plant, number of seeds per pod, pod length, test weight and seed yield exhibited high heritability estimates coupled with high genetic advance as per cent of mean which suggested that these traits were amenable for further improvement following simple selection methods. Character association revealed significant positive association of seed yield with plant height,number of branches per plant, number of pods per plant, number of seeds per pod and pod length. Based on divergence studies, the hybrids were grouped into nine clusters in Tocher’s method, cluster II (14 hybrids) was the largest followed by cluster I (13), cluster VI (9), cluster IV (6), cluster IX (4) and the remaining clusters were solitary (III, V, VII and VIII). Out of the nine characters studied, seed yield, days to 50% flowering, test weight and plant height contributed 85.62 per cent of the total divergence and these traits were found to be important factors for genetic differentiation in the hybrids. The overall results of the study revealed that, hybrids under cluster IV and VIII and cluster VII and VIII had maximum and minimum inter cluster distances respectively and possessing high genetic diversity for the characters viz. plant height, number of branches per plant, number of seeds per pod and yield.
The present investigation entitled “Assessment of morphometric diversity for yield and yield attributing traits in rice (Oryza sativa L.) for tolerance to heat stress” was carried out with objective of assessing genetic divergence in 200 germplasm of rice for eleven characters at ICRISAT, Patencheru, Hyderabad. The genotypes were grouped into fifteen clusters in Tocher’s method, cluster analysis and principal component analysis, out of the 11 characters studied, number of grains per panicle, plant height, pollen viability and spikelet fertility contributed 96.73 per cent of the total divergence and these traits were found to be important potent factors for genetic differentiation in genotypes. Principal component analysis identified five principal components, which contributed for 78.66 percent % of cumulative variance. The overall results of the study revealed that crossing using the genotypes under cluster V and XI and cluster XI and XIII could be exploited by hybridization programme to yield good recombinants because they had maximum inter cluster distance and possessing high genetic diversity for the characters viz. panicle length, number of grains per panicle and single plant yield. The genotypes of cluster I, II, IV, VI, VII, VIII, XI, XII and XIII showed high spikelet fertility percentage. Hence the genotypes of these clusters can be used in breeding programmes for development of heat tolerant varieties. Euclidean2 method indicated that genotypes of cluster III and IX exhibited high spikelet fertility percentage which can be utilized in development of heat tolerant cultivars. The results of principal component analysis revealed that genotypes of cluster I, cluster IV, cluster V, cluster VIII, cluster IX, cluster XI, cluster XII and cluster XV exhibited highest spikelet fertility percentage. Hence, the genotypes of the clusters can be used in breeding programmes for the development of heat tolerant varieties.
The yield stability of promisingpigeon pea genotypes across six locations was assessed using additive main effects and multiplicative interaction and Genotype plus genotype and environment interaction biplot models. The combined analysis of variance indicated that yield was significantly affected by genotypes, environments and genotype and environment interaction. The first two interaction principal componentsfrom the AMMI analysis accounted for 68.48% and from GGE accounted for 64.4% of variation due to GxE interaction. Both AMMI and GGE biplots identified G3 and G4 as most stable andG4 with the highest yield across six locations. The “What-won-where” biplot revealed that six environments fell into four sectors i.e.,E1and E2fell into one mega environment (ME 1), E3and E6another (ME 2), E4in one mega environment (ME 3) andE5 into another (ME 4). Environments E5and E1were most representative while E1could be regarded as least representative environment. Bangladesh J. Bot. 51(2): 371-380, 2022 (June)
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