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Selection at ultra-low density identifies plants escaping virus infection and leads towards high-performing lentil (Lens culinaris L.) varieties

Published online by Cambridge University Press:  18 July 2013

A. KARGIOTIDOU ,
E. CHATZIVASSILIOU ,
C. TZANTARMAS ,
E. SINAPIDOU ,
A. PAPAGEORGIOU ,
G. N. SKARACIS  and
I. S. TOKATLIDIS
A. KARGIOTIDOU
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
E. CHATZIVASSILIOU
Affiliation:
Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
C. TZANTARMAS
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
E. SINAPIDOU
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
A. PAPAGEORGIOU
Affiliation:
Department of Forestry and Management of the Environment and Natural Resources, Democritus University of Thrace, 68200 Orestiada, Greece
G. N. SKARACIS
Affiliation:
Department of Crop Science, Agricultural University of Athens, 11855 Athens, Greece
I. S. TOKATLIDIS*
Affiliation:
Department of Agricultural Development, Democritus University of Thrace, 68200 Orestiada, Greece
*
*To whom all correspondence should be addressed. Email: [email protected]; [email protected]
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Summary

Cultivated lentil (Lens culinaris L.) landraces offer a challenge to exploiting their genetic variability and deriving new pure-line varieties. For insect-transmitted viruses, low densities favour increased virus spread. The objective of the present work was to evaluate a selection procedure applied within a landrace under ultra-low plant density and low-input conditions toward the isolation of high-performing genotypes that escape virus infection. Field trials were conducted through four growing seasons (2006–2011) in the Democritus University of Thrace research farm in Orestiada, Greece. Selection of individual plants for high grain yield was applied for three generations, while virus presence was tested by enzyme-linked immunosorbent assay in the seeds used or the plants selected in each selection cycle. Early high plant-to-plant phenotypic variability, reflected by high coefficient of variation (CV) values, was partly attributed to virus infection. However, sister lines were consistently higher yielding and of lower CV than the mother population (MP). Second generation lines yielded up to 136 and 23% more than the source landrace at the ultra-low density and dense stand, respectively. Pea seed-borne mosaic virus was detected in the seeds of the MP, whereas bean yellow mosaic virus and bean leafroll virus were mainly involved in the subsequent selection rounds. In general, the highest-yielding plants were free of the viruses detected during experimentation. It was concluded that selection at ultra-low density of the highest-yielding plants from the sister lines with the lowest CV constitute an effective way to improve the health status of the seeds produced and result in high yielding and potentially virus-tolerant pure-line varieties.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 152 , Issue 5 , October 2014 , pp. 749 - 758
Copyright
Copyright © Cambridge University Press 2013 

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References

Andrews, M. & McKenzie, B. A. (2007). Adaptation and ecology. In Lentil: An Ancient Crop for Modern Times (Eds Yadav, S. S., McNeil, D. L. & Stevenson, P. C.), pp. 23–32. The Netherlands: Springer.CrossRefGoogle Scholar
Batzios, D. P. & Roupakias, D. G. (1997). Honey: a microcomputer program for plant selection and analyses of the honeycomb designs. Crop Science 37, 744–747.Google Scholar
Clark, M. F. & Adams, A. N. (1977). Characteristics of the microplate method of enzyme-linked immunosorbent assay for the detection of plant viruses. Journal of General Virology 34, 475–483.CrossRefGoogle ScholarPubMed
Coutts, B. A., Prince, R. T. & Jones, R. A. C. (2008). Further studies on Pea seed-borne mosaic virus in cool-season crop legumes: responses to infection and seed quality defects. Australian Journal of Agricultural Research 59, 1130–1145.CrossRefGoogle Scholar
Coutts, B. A., Prince, R. T. & Jones, R. A. C. (2009). Quantifying effects of seed-borne inoculum on virus spread, yield losses, and seed infection in the pea seed-borne mosaic virus-field pea pathosystem. Phytopathology 99, 1156–1167.Google Scholar
Erskine, W., Muehlbauer, F. J., Sarker, A. & Sharma, B. (2009). Introduction. In The Lentil: Botany, Production and Uses (Eds Erskine, W., Muehlbauer, F. J., Sarker, A. & Sharma, B.), pp. 1–3. Wallingford, Oxfordshire, UK: CAB International.CrossRefGoogle Scholar
Fasoula, D. A. (2012). Nonstop selection for high and stable crop yield by two prognostic equations to reduce yield losses. Agriculture 2, 211–227.Google Scholar
Fasoula, V. A. & Boerma, H. R. (2007). Intra-cultivar variation for seed weight and other agronomic traits within three elite soybean cultivars. Crop Science 47, 367–373.CrossRefGoogle Scholar
Fasoula, V. A. & Tokatlidis, I. S. (2012). Development of crop cultivars by honeycomb breeding. A review. Agronomy for Sustainable Development 32, 161–180.CrossRefGoogle Scholar
Fasoulas, A. C. (1993). Principles of Crop Breeding. Thessaloniki, Greece: A.C. Fasoulas.Google Scholar
Fasoulas, A. C. & Fasoula, V. A. (1995). Honeycomb selection designs. Plant Breeding Reviews 13, 87–139.Google Scholar
Hampton, R. O., Kraft, J. M. & Muehlbauer, F. J. (1993). Minimizing the threat of seedborne pathogens in crop germ plasm: elimination of pea seedborne mosaic virus from the USDA-ARS germ plasm collection of Pisum sativum. Plant Disease 77, 220–224.Google Scholar
Hansen, J. & Renfrew, J. M. (1978). Palaeolithic–Neolithic seed remains at Franchthi Cave, Greece. Nature 271, 349–352.Google Scholar
Jones, R. A. C. (2004). Using epidemiological information to develop effective integrated virus disease management strategies. Virus Research 100, 5–30.Google Scholar
Kotzamanidis, S. T., Lithourgidis, A. S. & Roupakias, D. G. (2009). Plant density effect on the individual plant to plant yield variability expressed as coefficient of variation in barley. Spanish Journal of Agricultural Research 7, 607–610.CrossRefGoogle Scholar
Kumari, S. G., Larsen, R., Makkouk, K. M. & Bashir, M. (2009). Virus diseases and their control. In The Lentil: Botany, Production and Uses (Eds Erskine, W., Muehlbauer, F. J., Sarker, A. & Sharma, B.), pp. 306–325. Wallingford, Oxfordshire, UK: CAB International.Google Scholar
Mabrouk, O. & Mansour, A. N. (1998). Effect of pea seed borne mosaic and broad bean stain viruses on lentil growth and yield in Jordan. Scientia Horticulturae 73, 175–178.Google Scholar
Makkouk, K. M. & Kumari, S. G. (2009). Epidemiology and integrated management of persistently transmitted aphid-borne viruses of legume and cereal crops in West Asia and North Africa. Virus Research 141, 209–218.Google Scholar
McKirdy, S. J., Jones, R. A. C., Latham, L. J. & Coutts, B. A. (2000). Bean yellow mosaic potyvirus infection of alternative annual pasture, forage, and cool season crop legumes: susceptibility, sensitivity, and seed transmission. Australian Journal of Agricultural Research 51, 325–346.Google Scholar
Papadopoulos, I. I. & Tokatlidis, I. S. (2011). A novel statistic estimated in the absence of competition to foresee genotype performance at the farming conditions parallels the agronomic concept of stability. Australian Journal of Crop Science 5, 822–830.Google Scholar
Sarker, A. & Erskine, W. (2006). Recent progress in the ancient lentil. Journal of Agricultural Science, Cambridge 144, 19–29.Google Scholar
Sarker, A., Singh, M., Rajaram, S. & Erskine, W. (2010). Adaptation of small-seeded red lentil (Lens culinaris Medik. subsp. culinaris) to diverse environments. Crop Science 50, 1250–1259.Google Scholar
Tambal, H. A. A., Erskine, W., Baalbaki, R. & Zaiter, H. (2000). Relationship of flower and pod numbers per inflorescence with seed yield in lentil. Experimental Agriculture 36, 369–378.CrossRefGoogle Scholar
Tokatlidis, I. S., Xynias, I. N., Tsialtas, J. T. & Papadopoulos, I. I. (2006). Single-plant selection at ultra-low density to improve stability of a bread wheat cultivar. Crop Science 46, 90–97.Google Scholar
Tokatlidis, I. S., Tsikrikoni, C., Tsialtas, J. T., Lithourgidis, A. S. & Bebeli, P. J. (2008). Variability within cotton cultivars for yield, fibre quality and physiological traits. Journal of Agricultural Science Cambridge 146, 483–490.Google Scholar
Tokatlidis, I. S., Papadopoulos, I. I., Baxevanos, D. & Koutika, O. (2010). Genotype × environment effects on single-plant selection at low density for yield and stability in climbing dry bean populations. Crop Science 50, 775–783.Google Scholar
Tokatlidis, I. S., Has, V., Melidis, V., Has, I., Mylonas, I., Evgenidis, G., Copandean, A., Ninou, E. & Fasoula, V. A. (2011). Maize hybrids less dependent on high plant densities improve resource use efficiency in rainfed and irrigated conditions. Field Crops Research 120, 345–351.CrossRefGoogle Scholar
Vlachostergios, N. D., Lithourgidis, A. S. & Roupakias, D. G. (2011). Effectiveness of single-plant selection at low density under organic environment: A field study with lentil. Crop Science 51, 41–51.CrossRefGoogle Scholar
Wang, D. & Maule, A. J. (1994). A model for seed transmission of a plant virus: genetic and structural analyses of pea embryo invasion by Pea seed-borne mosaic virus. Plant Cell 6, 777–787.Google Scholar