Composition and correlation between major seed constituents in selected lentil (Lens culinaris. Medik) genotypes

2011 ◽  
Vol 91 (5) ◽  
pp. 825-835 ◽  
Author(s):  
Mohammad Tahir ◽  
Nienke Lindeboom ◽  
Monica Båga ◽  
Albert Vandenberg ◽  
Ravindra Chibbar

Tahir, M., Lindeboom, N., Båga, M., Vandenberg, A. and Chibbar, R. N. 2011. Composition and correlation between major seed constituents in selected lentil ( Lens culinaris Medik.) genotypes. Can. J. Plant Sci. 91: 825–835. Development of lentil cultivars with increased seed amylose, protein and reduced concentration of anti-nutritional constituents are desired from the perspectives of lentil utilization and human health. In selected lentil genotypes, we studied seed weight, seed coat weight and color, seed composition and the association between major quality traits. Significant (P ≤ 0.05) variation existed for all traits except seed coat weight. The starch and protein concentrations ranged from 39.4 to 45.3 g and from 23.8 to 29.3 g 100 g−1 flour DM whereas the amylose concentration ranged from 29.8 to 34.0 g 100 g−1 starch. Glucose, sucrose and raffinose family oligosaccharides (RFO) concentrations of lentil genotypes ranged from 0.04 to 0.08 g, from 0.7 to 2.4 g, and from 4.6 to 6.6 mmoles 100 g−1 flour DM, respectively. Raffinose, stachyose and verbascose concentrations varied from 1.6 to 2.4 g, from 1.7 to 2.9 g, and from 1.2 to 1.9 g 100 g−1 flour DM, respectively. A significant (P ≤ 0.05) positive correlation existed between 1000-seed weight and starch, 1000-seed weight and RFO and sucrose concentration. Similarly, a significant (P ≤ 0 .05) negative correlation was found between starch and protein concentration, 1000-seed weight and protein concentration, and 1000-seed weight and amylose concentration. The lack of a significant correlation between RFO and other quality traits indicates that selection for low RFO concentration may not affect other important quality traits in lentil seeds.

2004 ◽  
Vol 55 (11) ◽  
pp. 1189 ◽  
Author(s):  
M. Mera ◽  
R. Jerez ◽  
H. Miranda ◽  
J. L. Rouanet

Abstract. The relatively high seed coat proportion of the narrow-leafed lupin reduces its economic value. This character has been shown to be affected by seed weight, and this limits the use of seed coat proportion as a selection criterion. We examined the variation for seed coat specific weight, a potential alternative selection criterion, and tested its relationship with seed coat proportion and seed weight. Seeds were sampled from mainstem pods of 14 winter-sown genotypes of Lupinus angustifolius L. grown at 4 southern Chile sites over 2 years. Seed coat specific weight had an overall mean of 30.1 mg/cm2. Highly significant genotypic effects were found (range 28.9–32.1 mg/cm2). The ranges for sites and years were 29.1–31.1 and 28.9–31.2 mg/cm2, respectively. Genotypes interacted significantly with years, but not with sites. Broad-sense heritability was 0.59, a value that predicts a good response to selection for this character. Seed coat specific weight was weakly correlated (rph = 0.11*) with seed coat proportion, and was not associated with mean seed weight. Seed coat proportion was negatively correlated with mean seed weight (rph = –0.75***) and had high broad-sense heritability (0.95). The correlation between seed coat specific weight and a theoretical seed coat thickness, calculated under the assumptions of equal mass density of seed coat, cotyledons, and embryo, and a spherical-shaped seed, was r = 0.14*. Phenotypic and genotypic correlations between seed coat specific weight and number of seeds per pod were 0.41 and 0.84, respectively. Our results indicate that selection for low seed coat proportion will lead to larger seeded genotypes, but will not reduce seed coat specific weight. Selection for low seed coat proportion after crosses would presumably be effective in reducing seedcoat specific weight if all segregating materials were uniformly large seeded, but that scenario is unrealistic. The evidence presented here suggests that selection for low seed coat specific weight (or measures correlated with it) in segregating populations will be necessary in order to increase the proportion of higher value kernels in seeds and to improve the economic yield of lupins.


1986 ◽  
Vol 66 (2) ◽  
pp. 241-246 ◽  
Author(s):  
R. VAILLANCOURT ◽  
A. E. SLINKARD ◽  
R. D. REICHERT

In lentil (Lens culinaris Medik.) condensed tannins are responsible for seed coat darkening during storage and the associated reduction in crop quality. The vanillin-HCl method was used to measure tannin concentration. Tannins were present only in the seed coat. Tannin concentration in the seed coat of 87 lines from the USDA World Lentil Collection ranged from 35 to 93 g kg−1 and averaged 63.3 g kg−1. The zero-tannin trait of PI 345635 lentil was controlled by a single recessive gene (tan tan) that had pleiotropic effects on plant pigmentation and seed coat thickness. Heritability of tannin concentration among lines containing tannin was 66.4 ± 4.4%, based on the components of variance method. Selection for lower or higher tannin concentration in lentil should be effective.Key words: Lentil, tannin, tannin genetics, proanthocyanidin, Lens culinaris


2014 ◽  
Vol 50 (No. 2) ◽  
pp. 130-134 ◽  
Author(s):  
G. Suvorova

Cultivated lentil L. culinaris was crossed to the wild species L. tomentosus ILWL90 and ILWL120. An ovule rescue technique was used to overcome interspecific incompatibility. Out of 296 hybrid ovules being planted in vitro 27 explants began to grow and three hybrids were recovered. A hybrid between L. culinaris and L. tomentosus accession ILWL90 was obtained by means of ovule recovery only. F<sub>1</sub> plant and next generations of the hybrid were either sterile or partly fertile. Hybridization with L. tomentosus accession ILWL120 was achieved by ovule culture as well as in a usual way i.e. without ovule culture. Seed progenies of these hybrids were fertile in both cases. Breeding lines recombinant in flower, seed coat and cotyledon coloring were developed as a result of multiple regular selection for highly productive plants in F<sub>2</sub>&ndash;F<sub>7</sub> (L. culinaris &times; L. tomentosus ILWL120).


2002 ◽  
Vol 80 (10) ◽  
pp. 2566 ◽  
Author(s):  
J. Estany ◽  
D. Villalba ◽  
M. Tor ◽  
D. Cubiló ◽  
J. L. Noguera

2021 ◽  
Vol 2 ◽  
Author(s):  
Rajender Kumar Sharma

Abstract Seeds of Abrus precatorius L. (Fabaceae) were used as weight measure by Indigenous people. Where, the seeds were referred as Ratti; a traditional Indian unit of mass measurement. Seed weight fluctuates depending upon age, moisture, storage-period/conditions. Therefore, use of seeds as a weighing unit become dubious and need to be validated. For this purpose, seeds of A. precatorious were subjected to different moisture conditions and periodically monitored. Surprisingly, there was no change in seed weight was observed, indicating the impermeability of seed coat. The later was confirmed by scarification of seed coat which resulted in 53% increase in seed weight against 0% in control. Further, presence of a potent toxin (abrin) in the seed coat protects it from pests and microbes, and contributes to the maintenance of impermeability for longer period of time. The data validates the use of A. precatorious seeds as a weighing unit (ratti) by the indigenous people and discussed.


2007 ◽  
Vol 64 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Harry X. Wu ◽  
Mike B. Powell ◽  
Junli L. Yang ◽  
Milo Ivković ◽  
Tony A. McRae

2019 ◽  
Author(s):  
Keith Halcro ◽  
Kaitlin McNabb ◽  
Ashley Lockinger ◽  
Didier Socquet-Juglard ◽  
Kirstin E Bett ◽  
...  

AbstractBackgroundSeed analysis is currently a bottleneck in phenotypic analysis of seeds. Measurements are slow and imprecise with potential for bias to be introduced when gathered manually. New acquisition tools were requested to improve phenotyping efficacy with an emphasis on obtaining colour information.ResultsA portable imaging system (BELT) supported by image acquisition and analysis software (phenoSEED) was created for small-seed optical analysis. Lentil (Lens culinaris L.) phenotyping was used as the primary test case. Seeds were loaded into the system and all seeds in a sample were automatically and individually imaged to acquire top and side views as they passed through an imaging chamber. A Python analysis script applied a colour calibration and extracted quantifiable traits of seed colour, size and shape. Extraction of lentil seed coat patterning was implemented to further describe the seed coat. The use of this device was forecasted to eliminate operator biases, increase the rate of acquisition of traits, and capture qualitative information about traits that have been historically analyzed by eye.ConclusionsIncreased precision and higher rates of data acquisition compared to traditional techniques will help breeders to develop more productive cultivars. The system presented is available as an open-source project for academic and non-commercial use.


Author(s):  
Enrique Wulff

The purpose of this chapter is to follow the evolution of what has occurred over time in the ontologies published in response to the COVID-19 pandemic. Correctness and completeness of ontologies on the schema and instance level are important quality criteria in their selection for an application. To help both the librarians and the users, there is a need of a framework for the comparison of different semantic data sources in the COVID-19 pandemic. Meanwhile, online services and/or applications based on ontologies or SKOS-based COVID-19 thesauri are still rare. As an emerging technology in libraries, an all-integrating ontology for coronavirus disease knowledge and data refers to the continuing development of an existing technology. In spite of using ontologies in the Semantic Web, meanings of concepts and relationships are still largely unrealized in terms of obtaining accurate and timely information about COVID-19. But the nature of causal relationships on this disease is made accessible through ontologies as the material in which its main concepts are supported.


2020 ◽  
Vol 13 (10) ◽  
pp. 2704-2722 ◽  
Author(s):  
Jean Beaulieu ◽  
Simon Nadeau ◽  
Chen Ding ◽  
Jose M. Celedon ◽  
Aïda Azaiez ◽  
...  

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