10 research outputs found

    Species diversity of genus Capsicum using agromorphological descriptors and simple sequence repeat markers

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    Sustainability of crops in most demand depends upon their genetic diversity. Capsicum, commonly called chilli, is one such crop with its fruits extensively used as vegetable across the world. Knowledge on various traits is important for genetic improvement of such species. Here, we assessed the genetic diversity among 10 genotypes of six Capsicum species, namely Capsicum annuum, C. chinense, C. chacoense, C. frutescens, C. tovarii and C. galapagoense. C. annuum MS-12 is a genetic male sterile line. We used morphological descriptors and simple-sequence repeat (SSR) molecular markers for this study. Out of 60 SSR screened, 22 markers (36.66%) showed polymorphism. Alleles number per locus varied from 3 to 7. Average PIC value for 22 polymorphic markers was 0.69, and ranged from 0.54 for the primer Hpms 1-139 to 0.85 for the primer CAMS-072. Ten genotypes of Capsicum species were grouped into three major clusters such that genotypes in a single cluster had less dissimilarity matrix values among themselves than which belongs to other clusters. Range of fruit weight and pericarp thickness varied from 0.1 g (‘PAU-621’) to 2.3 g (‘MS-12’), and from 0.29 mm (‘PAU-621’) to1.09 mm (‘MS- 12’), respectively. These two genotypes can be used in hybridization or in recombinant breeding program for obtaining higher heterotic effects/ heterosis or for transgressive segregants in chilli pepper

    Species diversity of genus Capsicum using agromorphological descriptors and simple sequence repeat markers

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    906-915Sustainability of crops in most demand depends upon their genetic diversity. Capsicum, commonly called chilli, is one such crop with its fruits extensively used as vegetable across the world. Knowledge on various traits is important for genetic improvement of such species. Here, we assessed the genetic diversity among 10 genotypes of six Capsicum species, namely Capsicum annuum, C. chinense, C. chacoense, C. frutescens, C. tovarii and C. galapagoense. C. annuum MS-12 is a genetic male sterile line. We used morphological descriptors and simple-sequence repeat (SSR) molecular markers for this study. Out of 60 SSR screened, 22 markers (36.66%) showed polymorphism. Alleles number per locus varied from 3 to 7. Average PIC value for 22 polymorphic markers was 0.69, and ranged from 0.54 for the primer Hpms 1-139 to 0.85 for the primer CAMS-072. Ten genotypes of Capsicum species were grouped into three major clusters such that genotypes in a single cluster had less dissimilarity matrix values among themselves than which belongs to other clusters. Range of fruit weight and pericarp thickness varied from 0.1 g (‘PAU-621’) to 2.3 g (‘MS-12’), and from 0.29 mm (‘PAU-621’) to1.09 mm (‘MS12’), respectively. These two genotypes can be used in hybridization or in recombinant breeding program for obtaining higher heterotic effects/ heterosis or for transgressive segregants in chilli pepper

    RAIL: Road Recognition from Aerial Images Using Inductive Learning

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    Roads, together with buildings, are one of the major man-made surface features of interest in remote sensing imagery. Most knowledge-based road recognition systems use a priori heuristic rules to enable recognition. These rules place explicit constraints on road properties and scene content. However, in remote sensing imagery, scene content varies, with roads taking on a wide variety of geometrical, radiometric, topological and contextual properties. The limitation of using a priori rules is that the systems are restricted to the kind of imagery for which these explicit constraints are valid. These systems typically fail on imagery outside of these conditions. In this paper, we propose an adaptive and trainable road recognition system. This system is able to perform semiautomatic extraction of roads from aerial imagery, using inductive learning techniques from the field of Machine Learning within Artificial Intelligence. The system is called RAIL, for Road Recognition from Aerial Image..

    Phenotypic and genotypic characterization of tomato genotypes for resistance to root-knot nematode, Meloidogyne incognita

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    Root-knot nematode is a major constraint to tomato cultivation in open and protected structures. Resistance sources need to be continuously identified for combating pathogens affecting the yield. In the present studies, forty-seven genotypes of tomato were evaluated phenotypically along with their genotypic characterization. On the basis of their phenotypic reaction, the genotypes were grouped into four categories viz.: resistant, moderately resistant, susceptible and highly susceptible. Of these genotypes, only five were found to be resistant while forty-two were rated from moderately resistant to highly susceptible. Multiplication of Meloidogyne incognita was greatly reduced (Rf < 1) in resistant genotypes as compared to susceptible genotypes. Root galling index was also very low in resistant genotypes. Using molecular markers, the presence of the Mi-1.2 resistance gene was also confirmed in five resistant genotypes (L-0272, NR-14, L-097, L-0275 and PNR-7). These resistant sources could become a source of germplasm in breeding programs for the development of resistant cultivars.Le nĂ©matode Ă  galles est une contrainte majeure Ă  la culture de la tomate dans des structures ouvertes et protĂ©gĂ©es. Les sources de rĂ©sistance doivent ĂȘtre identifiĂ©es en permanence pour lutter contre les agents pathogĂšnes affectant le rendement. Jusqu’à prĂ©sent, quarante-sept gĂ©notypes de tomate ont Ă©tĂ© Ă©valuĂ©s phĂ©notypiquement, de mĂȘme que leur caractĂ©risation gĂ©notypique. Selon leur rĂ©action phĂ©notypique, les gĂ©notypes ont Ă©tĂ© regroupĂ©s en quatre catĂ©gories : rĂ©sistant, modĂ©rĂ©ment rĂ©sistant, sensible et trĂšs sensible. Parmi ces gĂ©notypes, seuls cinq se sont rĂ©vĂ©lĂ©s rĂ©sistants tandis que quarante-deux ont Ă©tĂ© classĂ©s de modĂ©rĂ©ment rĂ©sistants Ă  trĂšs sensibles. La multiplication de Meloidogyne incognita Ă©tait fortement rĂ©duite (Rf < 1) dans les gĂ©notypes rĂ©sistants par rapport aux gĂ©notypes sensibles. L'indice de galles racinaires Ă©tait Ă©galement trĂšs faible dans les gĂ©notypes rĂ©sistants. À l'aide de marqueurs molĂ©culaires, la prĂ©sence du gĂšne de rĂ©sistance Mi-1.2 a Ă©galement Ă©tĂ© confirmĂ©e dans cinq gĂ©notypes rĂ©sistants (L-0272, NR-14, L-097, L-0275 et PNR-7). Ces sources rĂ©sistantes pourraient devenir une source de matĂ©riel gĂ©nĂ©tique dans les programmes de sĂ©lection pour le dĂ©velop-pement de cultivars rĂ©sistants

    Study of gelatin-agar intermolecular aggregates in the supernatant of its coacervate

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    Intermolecular interaction leading to formation of aggregates between gelatin, a polyampholyte, and agar, a polysaccharide was studied in the supernatant of the complex coacervate formed by these biopolymers. Electrophoresis, laser light scattering and viscometry data were used to determine the interaction and the physical structure of these intermolecular soluble complexes by modeling these to be prolate ellipsoids of revolution (rod-like structures with well defined axial ratio and Perrin's factor). Solution ionic strength was found to reduce the axial ratio of these complexes implying the presence of screened polarization-induced electrostatic interaction between the two biopolymers. (c) 2007 Elsevier B.V. All rights reserved

    Intermolecular complexation and phase separation in aqueous solutions of oppositely charged biopolymers

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    Turbidity measurements performed at 450 nm were used to follow the process of complex formation, and phase separation in gelatin-agar aqueous solutions. Acid (Type-A) and alkali (Type-B) processed gelatin (polyampholyte) and agar (anionic polyelectrolyte) solutions, both having concentration of 0.1% (w/v) were mixed in various proportions, and the mixture was titrated (with 0.01 M HCl or NaOH) to initiate associative complexation that led to coacervation. The titration profiles clearly established observable transitions in terms of the solution pH corresponding to the first occurrence of turbidity (pH(c), formation of soluble complexes), and a point of turbidity maximum (pH(phi), formation of insoluble complexes). Decreasing the pH beyond pH, drove the system towards precipitation. The values of pH(c) and pH(phi) characterized the initiation of the formation of intermolecular charge neutralized soluble aggregates, and the subsequent formation of microscopic coacervate droplets. These aggregates were characterized by dynamic light scattering. It was found that Type-A and -B gelatin samples formed soluble intermolecular complexes (and coacervates) with agar molecules through electrostatic and patch-binding interactions, respectively. (C) 2007 Elsevier B.V. All rights reserved
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