HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Horneburg, B. Articles by Becker, H. C. Search for Related Content PubMed Articles by Horneburg, B. Articles by Becker, H. C. Agricola Articles by Horneburg, B. Articles by Becker, H. C. Related Collections Germplasm Enhancement Plant and Environment Interactions Plant Genetic Resources

Crop Adaptation in On-Farm Management by Natural and Conscious Selection: A Case Study with Lentil

Dep. of Crop Sciences, Univ. of Göttingen, Von-Siebold-Str. 8, 37075 Göttingen, Germany

^* Corresponding author (bhorneb{at}gwdg.de).

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
On-farm management of landraces or older cultivars of crop plants is often recommended to combine conservation and use of genetic resources, but experimental studies on on-farm management are hard to find, particularly in industrialized countries. To investigate whether on-farm management results in regional adaptation and enhances crop biodiversity, an experiment with lentils (Lens culinaris Medik.) was designed. Lentil production has almost ceased to exist in central Europe, but lentils may still be found in gene banks and have remained a popular food. Three landraces were evaluated on three farms in Germany; at each farm, three populations evolved, based on three selection methods: (i) natural selection, (ii) visual mass selection, and (iii) selection for yield of single plant progenies. These selection methods were applied for two to four years. The nine populations developed for each landrace (three methods x three locations) were grown in a comparative trial on two of the farms. In most cases, populations selected at a specific location were at this location superior in yield to populations selected at other locations, indicating that on-farm management can result in site-specific adaptation. Significant changes in morphological and phenological traits occurred. For one landrace, natural selection increased seed weight. The response to different selection methods largely depended on landrace and selection site, and no method was generally superior. In conclusion, on-farm management is a useful approach to maintain, use, and develop plant genetic resources. Natural selection as the most cost-efficient method is recommended.

	ACKNOWLEDGMENTS

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication March 26, 2007.

Crop Adaptation in On-Farm Management by Natural and Conscious Selection: A Case Study with Lentil

Dep. of Crop Sciences, Univ. of Göttingen, Von-Siebold-Str. 8, 37075 Göttingen, Germany

^* Corresponding author (bhorneb{at}gwdg.de).

On-farm management of landraces or older cultivars of crop plants is often recommended to combine conservation and use of genetic resources, but experimental studies on on-farm management are hard to find, particularly in industrialized countries. To investigate whether on-farm management results in regional adaptation and enhances crop biodiversity, an experiment with lentils (Lens culinaris Medik.) was designed. Lentil production has almost ceased to exist in central Europe, but lentils may still be found in gene banks and have remained a popular food. Three landraces were evaluated on three farms in Germany; at each farm, three populations evolved, based on three selection methods: (i) natural selection, (ii) visual mass selection, and (iii) selection for yield of single plant progenies. These selection methods were applied for two to four years. The nine populations developed for each landrace (three methods x three locations) were grown in a comparative trial on two of the farms. In most cases, populations selected at a specific location were at this location superior in yield to populations selected at other locations, indicating that on-farm management can result in site-specific adaptation. Significant changes in morphological and phenological traits occurred. For one landrace, natural selection increased seed weight. The response to different selection methods largely depended on landrace and selection site, and no method was generally superior. In conclusion, on-farm management is a useful approach to maintain, use, and develop plant genetic resources. Natural selection as the most cost-efficient method is recommended.

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
SINCE THE EMERGENCE OF scientific breeding techniques at the beginning of the twentieth century, most of the landraces and many botanical taxa used in agriculture and horticulture have disappeared from fields and gardens. Seeds became a commodity, one of the means of production, and were no longer an integral part of a farm or a geographical region. In the words of Bennett (1970), "Genetic resources stand now in the greatest danger of irretrievable extinction." Frankel (1970) described the eminent danger of genetic erosion on a global scale. The storage of genetic resources in collections ex situ is generally restricted in scale and scope, and the effective population size sets further limitations to the integrity of samples. Thus, only a fraction of the total diversity originally found in the fields can be conserved for future generations (Frankel 1970). In fact, studies have shown that the loss rates of material stored in a gene bank can be similar to erosion rates on farms (Hammer and Laghetti, 2005). Examples for the erosion of genetic diversity during conservation ex situ have been demonstrated by Parzies et al. (2000) and van Hintum et al. (2007). In their search for a better way to preserve genetic diversity, many practical farmers, gardeners, and researchers have proposed practical methods that will allow crop conservation, adaptation, and improvement within practical agriculture and horticulture (Bretting and Duvick, 1997; BUKO Agro Coordination, 1998; Brush, 2000; Hammer, 2003a,b). In agriculture there is an increased need for close contact between consumers and producers, transparent production lines, high-quality food, heritage varieties, and crops and products related to local culture and history. Farms and gardens have the potential to play an important role as centers of crop development that could answer this need. Legislation in many countries remains one of the major obstacles to increased on-farm biodiversity. Landraces frequently do not (and should not) meet the required standards of distinctness, uniformity, and stability (UPOV, 2003) for registration and sale.

In ex situ conservation, population changes are undesirable. In farms and gardens, however, specific adaptation to the local pedoclimatic conditions and the needs of producers and consumers often is considered desirable. The "exploitation of genotype x environment interactions" (Simmonds, 1991) is a potential advantage of on-farm management and an alternative approach to breeding for general adaptation in breeding stations. To our knowledge, no experiments investigating specific adaptation by natural and conscious selection on-farm have been published. We designed this experiment to supply needed information. Three gene bank accessions of lentils (Lens culinaris Medik.) were grown on three farms in Germany that were chosen to represent a variety of pedoclimatic conditions. One of the farms was in an area where lentils had traditionally been grown. The selection methods applied were chosen due to their applicability in on-farm management. Natural selection, mass selection, and progeny selection were performed at all three locations. The subsequent comparison of all modes of selection (three methods x three locations) was performed at two of these locations. Additionally, calibration for the largest seeds was done at one location. Independent selection at three locations allowed us to investigate the effect of the selection method and of the location. Site-specific adaptation would be revealed by the superior relative performance of populations at the location of their selection. For the present experiment, a self-pollinating species (Horneburg, 2006) was used to test the adaptive properties at prevailing autogamy.

Lentils are an important staple food source on a global scale in semiarid areas, particularly in Asia (Muehlbauer et al. 1995). Production increased from 855,000 t in 1961 to 4,172,000 t in 2005 according to the FAO (2007). In Europe lentils are among the three most important leguminous food crops, following peas (Pisum sativum L.) and Phaseolus beans, despite decreasing production. Until the beginning of the twentieth century, lentils were widely grown in central Europe, mainly as a protein source in subsistence agriculture. They have almost vanished from cropping systems since the middle of the last century, but traditional cultivars survived in ex situ collections. Lentil breeding in central Europe came to an end about 1950, but lentils have remained a popular food (Horneburg, 2003b). Thus, lentils are a good example for a neglected but still well-known crop. On-farm management could answer the demand for adapted cultivars and regional lentil production in central Europe.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
The three populations used were chosen from a group of 20 accessions of central European origin. We obtained them from the gene bank of the Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany, which had maintained them for periods ranging from 38 to 47 years and during 8 to 17 cycles of regeneration (Horneburg, 2003a). Passport data did not allow us to differentiate between landraces or cultivars, and so we use both terms. Observations in 1998 of five single plant progenies of each accession showed phenotypic variation. Pisarecka Perla, LENS 122, has large beige seeds (average seed weight 58 mg) and large white flowers. Gestreifte Linse (striped lentil), LENS 103, has seeds of medium size (37 mg), green color mottled dark, and small white flowers. Schwarze Linse (black lentil), LENS 106, is small (24 mg) and black seeded, with small blue flowers.

In 1996 a sample of 30 to 40 seeds was sown in Göttingen, Germany, for seed multiplication (Fig. 1 ). Growing of the cultivars at Reinshof and in Schönhagen in central Germany and another location in the north of the country began in 1997. Plots were sown with 100 seeds in 1997 and 400 seeds in 1998, and only natural selection occurred. Since 1999 Tangsehl has been the northern German location. The three sites used for our lentil selection studies each represent a unique pedoclimatic condition (Table 1 ). Schönhagen, where lentils had been grown traditionally until 1958, has poor, shallow, and stony calcareous clay soils. Reinshof is characterized by some of the most fertile loess soils in the area. Tangsehl, on the other hand, has slightly acid and sandy soils.

View larger version (27K): [in this window] [in a new window]   Figure 1. Outline of four selection methods applied on three farms and three cultivars of lentil, 1996 to 2001, to monitor population changes

• Natural selection (four cycles of selection): 300 seeds were sown at 100 seeds m^–2 and harvested as bulk.
  
• Positive mass selection (two cycles): Out of 1500 plants (66 plants/m^–2), 100 plants were selected visually during the harvest by the first author according to apparent yield, health, and lodging resistance. One-half of the seeds was bulked and used for a second cycle of selection.
  
• Progeny testing (one cycle): 50 seeds each of 100 individual plants of the selection described for positive mass selection were sown in 2000, and the 20 top-yielding progenies were selected.
  

Performance of the crops was evaluated using the following procedure. An area measuring 1 m² in the center of each plot was used to count emergence and the number of plants at harvest. The percentage of abnormally discolored (yellow or brown) area per plot was measured to describe the effect of pests and diseases. Seed and straw yield in grams per plot were determined by threshing the air-dried plants with Pelz K35 (Wachtberg-Villip, Germany) or plot combine Hege 125 (Waldenburg, Germany), respectively. The beginning of flowering was scored as follows: 0 = no open flowers, 1 = up to 1%, 2 = <10%, 3 = 10 to 50%, 4 = >50%. The scoring for Pisarecka Perla occurred on June 15 at Reinshof and June 16 for Tangsehl; scoring for Gestreifte Linse occurred on June 22 at both Reinshof and Tangsehl; and scoring for Schwarze Linse occurred on June 17 at Reinshof and June 18 for Tangsehl on June 18. Analysis of variance was performed with PLABSTAT Version 2n (Utz, 1997). The following model was used: x_ijklm = µ + c_i + l_j + r_kl + cl_ij + e_a + p_l +s_m + lp_jl + cp_il + ls_jm + cs_im + ps_lm + cls_ijm + cps_ilm + lps_jlm + clp_ijl + clps_ijlm + e_b, where x_ijklm is the performance of a single plot, µ is the general mean, c_i is the effect of cultivar i (main plot), l_j is the effect of location j, r_kl is the effect of replicate k within location l, p_l is the effect of the selection site l (provenance), s_m is the effect of the selection method m, cl_ij, lp_jl, cp_il, ls_jm, cs_im, ps_lm, cls_ijm, cps_ilm, lps_jlm, clp_ijl, and clps_ijlm are the respective interactions, e_a is the error of the main plots, and e_b is the error of the subplots. All effects except the replicate were considered as fixed. Multiple comparisons of means were made with the Tukey test at p = 0.05.

	RESULTS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
The effect of the three selection methods applied at Reinshof, Schönhagen, and Tangsehl was investigated by a comparison of all modes of selection (three methods x three locations) at Reinshof and Schönhagen in 2001. We use the term provenance for the origin of seeds, that is, the location of selection.

The mean seed yield over all cultivars and modes of selection was only slightly greater at Reinshof than at Tangsehl (Table 2 ). Straw yield was significantly larger at Reinshof, and thus the harvest index was significantly increased at Tangsehl (data not shown). Generally, provenances yielded higher values at the location where they had been selected, the one exception being straw yield at Tangsehl. At Reinshof the seed yield of provenance Reinshof was greater than provenance Schönhagen. Selection at Schönhagen resulted in the highest seed weight, and selection at Tangsehl resulted in the lowest seed weight. Flowering of the provenance Schönhagen began earlier than provenance Tangsehl, followed by provenance Reinshof.

View this table: [in this window] [in a new window]   Table 7. Beginning of flowering of nine modes of selection (three methods x three provenances) of three lentil cultivars at Reinshof and Tangsehl, 2001. Mean of provenances in italics.

	DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

Generally, selection will reduce genetic diversity. On the other hand "the loss of genetic diversity in individual locations may be substantial, but the gain among populations in diverse locations may in fact cause an overall increase" (Jana and Khangura 1986) and sustain and develop adapted diversity for future generations.

Specific Adaptation and the Influence of the Locations
To our knowledge, no research has been done to support the hypothesis that on-farm management results in a specific adaptation to the selection site. Experiments that focused on the development of composite crosses of barley (Hordeum vulgare L. em. Alef.) (Jana and Khangura, 1986) and wheat (Triticum aestivum L.) (Goldringer et al., 1998) demonstrated the influence of location and management practices on population dynamics. Based on his experiences with barley, Suneson (1956) strongly suggested the use of long-term natural selection as an "evolutionary plant breeding method." Specific adaptation could not be tracked in these approaches because the comparison of provenances was done at only one location.

Specific adaptation would manifest itself in greater yield and/or improved yield stability at the location of selection accompanied by favorable phenological and morphological changes. Thus, experimental evidence indicated a specific adaptation in seed yield. As expected, differences in seed yield were larger than in straw yield because progenies were selected for seed yield and mass selection was done for vigorous plants with many pods. Comparative trials for more than one growing season would give clearer results and allow the investigation of yield stability.

Lentil selection on three farms led to site-specific changes in some of the traits tested. Flowering time varied significantly for the three provenances of Pisarecka Perla and Gestreifte Linse. Seed size and seed yield of Pisarecka Perla also varied significantly by provenance. It is no easy task, however, to relate changes in population structure to mechanisms of specific adaptation. In both Schönhagen and Tangsehl, the growing season is in some years terminated by drought, while the water capacity at Reinshof is excellent. Drought has possibly been a selective force favoring earlier flowering at Schönhagen and later flowering at Reinshof. The fertile soil at Reinshof led to an increase in straw biomass (Table 2), which led to an increased danger of lodging combined with stands too dense to dry off quickly after precipitation. Additionally, the Pisarecka Perla plants that had large seeds also had larger leaflets (Horneburg, 2003a) that increased lodging and dampness. Selection for smaller seeds at Reinshof could be a result of better water supply. Very dry or wet periods would probably lead to more differentiation between locations. In other experiments, geographical location and management practices such as irrigation, nitrogen fertilizer, and herbicides have been shown to exert a strong influence on selective processes (Jana and Khangura, 1986; Goldringer et al., 1998; Tin et al., 2001). The observed changes included agronomic traits (seed size, number of seeds per ear), plant morphology (plant height, length of awns), and phenology (heading date, days to maturity). Physiological changes (protein composition, resistance against powdery mildew) were reported by David et al. (1997) and Paillard et al. (2000a,b).

In contrast to older literature reviewed by Horneburg (2003b), we found that lentil production seems to be feasible on marginal soils outside the traditional central European production areas that are characterized by poor calcareous soils. The yield level on a sandy soil at Tangsehl was only slightly reduced compared with that at Reinshof.

Methods of Selection
As we began to design our experiment, we expected it to produce an increasing efficiency of selection in the following order: progeny selection > mass selection > natural selection. Selection started with one common seed source for all methods, but the number of cycles of selection varied. Natural selection was applied for four annual cycles, mass selection for two annual cycles and progeny selection for one biannual cycle. Populations deriving from natural selection were finally based on 300 individuals, mass selection was based on 100 individuals, and progeny selection was based on only 20 grandparental plants. The results did not confirm our expectations, however. All methods of selection affected population structure in agronomic, morphological, and phenological traits. In fact, even natural selection led to major population changes. We found, with one exception, no particular trend to the results of each of the three selection methods. That one exception was Pisarecka Perla, in which natural selection increased seed weight at all three locations.

According to Goldringer et al. (1998), eight years of natural selection increased seed weight in four populations deriving from a composite cross of wheat. That finding was somewhat surprising and suggests an adaptive value of larger seeds or closely linked traits. It might be expected that small-seeded plants—which produce a larger number of offspring at any given yield level—would be favored by natural selection. On the other hand, selection might favor larger seedlings deriving from larger seeds. The work of Jana and Khangura (1986) showed that a significant decrease in seed weight evolved from F₅ to F₁₉ in two out of four populations deriving from a composite cross of barley, while the remaining two populations remained stable. A number of studies have demonstrated that natural selection can be an efficient breeding technique. Both Jana and Khangura (1986) and Suneson (1956) reported yield gains during 11 to 29 generations. In the latter case, about 15 generations sufficed to reach the yield level of a standard cultivar.

According to conversations with farmers and gardeners, mass selection is used in many cases of on-farm management. It is frequently applied for many consecutive years and can lead to improved cultivars. Two cycles of selection in the present experiment resulted in significant changes in all three cultivars, but the resulting populations were not generally superior to natural selection in yield. Both Boyce et al. (1947) and Briggs and Shebeski (1970) indicated that visual selection was an efficient way to improve populations. They are in disagreement with Shebeski (1967) and Hanson et al. (1979), who demonstrated the opposite. The choices made by the individual breeder can have a significant impact on the results and, thus, the efficiency of the work (Briggs and Shebeski, 1970; Salmon and Larter, 1978). To avoid these unwanted influences, the first author alone made all of the selections. The question of how many cycles of mass selection are optimal for the adaptation of an inbreeding crop remains open; two cycles do not seem to be sufficient.

Progeny selection was based on visual selection of individual plants in the first year. The highest-yielding progenies were chosen at the end of the second year. Although the first cycle of mass selection and the first step of progeny selection were based on the same plants, the second year of selection led to significantly different results in one of the cultivars: in most of the provenances of Pisarecka Perla, straw yield, seed weight, and/or the beginning of flowering were affected. Progeny selection produced larger seeds than mass selection. The seed size is not accessible in visual selection, but empty pods are discernible for the experienced eye. Generally, visual selection has been observed to be less reliable for yield than for traits like height, seed weight, and days to maturity (Briggs et al., 1978).

Calibration for the smallest and the largest seeds had a significant effect on yield and other traits. That effect can be the result of (i) the selection of genotypes according to heritable seed size and (ii) the selection for seed size due to the environmental conditions during seed formation and maturation. Genetic variation in Pisarecka Perla for seed size, yield, and the beginning of flowering was shown by Horneburg (2003a). A positive correlation between seed size and earlier flowering and a negative correlation between seed size and yield were observed. Thus, significant changes in seed weight and flowering time in the present experiment were probably mainly caused by the selection of genotypes. Kaufmann and Mc Fadden (1963), Austenson and Walton (1970), Thomas et al. (1978), and Dornbusch et al. (1992) gave evidence that increased seed size can have a positive influence on seedling performance and later development. In our experiment, this influence was of minor importance as the calibration for larger seeds did not increase the seed yield.

It has been shown that on-farm management can lead to evolutionary changes in many traits. However, to choose one selection method or a combination of methods for an on-farm management project is not easy. The amount of labor and specialized knowledge needed will play an important role in the decision. Natural selection can be highly efficient; its great advantage is its simplicity. Calibration, too, is simple and can be done during the cleaning of the harvest. Mass selection needs a deeper knowledge of the crop. During the busy harvest period, time is needed to observe and select individual plants. Progeny selection is highly labor intensive and cannot be done without (technical) means to deal with small seed lots. This method allows deep insights into the population structure. Intensive selection for traits like seed weight, flowering time, or days to maturity can be done successfully. On the other hand, progeny selection can create bottlenecks in population size. Thus, without a profound knowledge of the cultivar that is to be improved, interesting genotypes are easily lost.

The Cultivars' Response to Selection
We used gene bank samples of old cultivars and landraces for the present study, although the response to selection is expected to be stronger in segregating populations, such as composite crosses, than in landraces. We had two reasons for our decision. The first is that it is difficult to obtain segregating populations for on-farm management. To start on-farm management, seed lots from colleagues, gene banks, and (older) commercial cultivars are frequently used. Second, segregating populations would be of limited use to a farmer. In lentil, as in many other crops, consumers prefer a uniform seed quality. Thus, the experimental design corresponded to the conditions in practical on-farm and in-garden management.

All three cultivars were most probably influenced by drift during the first two years of the project because only 30 to 100 seeds per location and cultivar were sown. During the experiment, population changes were much stronger in Pisarecka Perla than in the other cultivars. Pisarecka Perla showed far more within-cultivar variability in 2000 than Schwarze or Gestreifte Linse (Horneburg, 2003a). High variability in Pisarecka Perla was most probably a combined effect of two aspects. First were bottlenecks in the number of individuals in the cultivars' histories (Horneburg, 2003a). During the time they were in gene bank storage, the Schwarze Linse population was reduced to a minimum of 11 seeds and Pisarecka Perla and Gestreifte Linse to <10 g of seeds apiece. The low number of individuals may have caused a reduction of variation in the case of Schwarze and Gestreifte Linse. In Pisarecka Perla, however, different morphotypes remained. Second was an outcrossing rate of up to 5.1% for Pisarecka Perla compared with 2.3% for Schwarze Linse and 1.1% for Gestreifte Linse (Horneburg, 2006).

One of the difficult tasks in on-farm management is finding the most suitable population to start with if evolutionary development is the aim. Despite preliminary tests, we chose two cultivars with restricted evolutionary potential for the experiment. In research and practical on-farm management, it is highly advisable to work with more than one cultivar.

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
On-farm management led to changes in population structure within a few years of selection. Changes were discernible in agronomic, morphological, and phenological traits. On-farm management did benefit from specific adaptation to the local conditions. Differences between natural selection, mass selection, and progeny selection were ambiguous. Natural selection can increase seed weight in some cases. Because natural selection is generally the easiest method to use, we recommend it. Longer studies are needed, however, to pinpoint scope and mechanisms of specific adaptation and the influence of the selection methods and locations. The response to selection depends on the population structure of a cultivar reflecting its history. Bottlenecks in populations during the maintenance in gene banks or on-farm management can drastically reduce adaptive properties and should be avoided.

On-farm management can help reintroduce lentils to central European agriculture. Lentil production is possible in diverse conditions, including nontraditional areas.

We thank our colleagues on farms for a number of years of both pleasant and efficient cooperation. We are indebted to the German Federal Ministry of Consumer Protection, Food and Agriculture for funding the project "Enhanced Species Diversity in Agriculture by Means of Lentil Production and On-Farm Management." Thanks also to Dreschflegel e.V.

All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.

Received for publication March 26, 2007.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 

• Austenson, H., and P.D. Walton. 1970. Relationships between initial seed weight and mature plant characters in spring wheat. Can. J. Plant Sci. 50:457–469.
• Bennett, E. 1970. Adaptation in wild and cultivated plant populations. p. 115–129. In O.H. Frankel and E. Bennett (ed.) Genetic resources in plants: Their exploration and conservation. IBP Handbook 11. Blackwell Scientific Press, Oxford, UK.
• Boyce, S.W., I.G.I. Copp, and O.H. Frankel. 1947. The effectiveness of selection for yield in wheat. Heredity 1:223–233.[Web of Science]
• Bretting, P.K., and D.N. Duvick. 1997: Dynamic conservation of plant genetic resources. Adv. Agron. 61:2–53.
• Briggs, K.G., and L.H. Shebeski. 1970. Visual selection for yielding ability of F₃ lines in a hard red spring wheat breeding program. Crop Sci. 10:400–402.[Abstract/Free Full Text]
• Briggs, K.G., D.G. Faris, and H.A. Kelker. 1978. Effectiveness of selection for plant characters of barley in simulated segregating rows. Euphytica 27:157–166.[CrossRef][Web of Science]
• Brush, S.B. (ed.). 2000. Genes in the field: On farm conservation of crop diversity. Int. Plant Genet. Res. Inst., Rome, Italy; Int. Dev. Res. Centre, Ottawa, Canada; Lewis Publishers, Boca Raton, FL.
• BUKO Agro Coordination (ed.). 1998. In Safe Hands—Communities Safeguard Biodiversity for Food Security: Proc. of the Int. NGO Conf. on the Occasion of IV. FAO/ITC, Leipzig, Germany. 14–16 June 1996. Forum Umwelt & Entwicklung, Bonn, Germany.
• David, J.L., M. Zivy, M.L. Cardin, and P. Brabant. 1997. Protein evolution in dynamically managed populations of wheat: Adaptive responses to macro-environmental conditions. Theor. Appl. Genet. 95:932–941.[CrossRef][Web of Science]
• Dornbusch, Ch., A. Schauder, H.-P. Piorr, and U. Köpke. 1992. Seed growing in organic agriculture: Improved criteria of seed quality of winter wheat. p. 19–24. In U. Köpke and D.G. Schulz (ed.) Proc. of the 9th Int. Scientific Conf. of IFOAM, Sao Paulo, Brazil. 16–21 Nov. 1992. Int. Federation of Organic Agriculture Movement, Tholey-Theley, Germany.
• FAO. 2007. FAOSTAT. Available at http://faostat.fao.org/site/567/DesktopDefault.aspx?PageID=567 (verified 14 Nov. 2007). FAO, Rome.
• Frankel, O.H. 1970. Genetic conservation in perspective. p. 469–489. In O.H. Frankel and E. Bennett (ed.) Genetic resources in plants: Their exploration and conservation. IBP Handbook 11. Blackwell Scientific Press, Oxford, England.
• Goldringer, I., S. Paillard, J. Enjalbert, J.L. David, and P. Brabant. 1998. Divergent evolution of wheat populations conducted under recurrent selection and dynamic management. Agronomie 18:413–425.[CrossRef][Web of Science]
• Hammer, K. 2003a. A paradigm shift in the discipline of plant genetic resources. Genet. Resour. Crop Evol. 50:3–10.[CrossRef]
• Hammer, K. 2003b. Resolving the challenge posed by agrobiodiversity and plant genetic resources: An attempt. Journal of Agriculture and Rural Development in the Tropics and Subtropics, Beiheft 76. Kassel Univ. Press, Kassel, Germany.
• Hammer, K., and G. Laghetti. 2005. Genetic erosion: Examples from Italy. Genet. Resour. Crop Evol. 52:629–634.[CrossRef]
• Hanson, P.R., G. Jenkins, and B. Westcott. 1979. Early generation selection in a cross of spring barley. Z. Pflanzenzuecht. 83:64–80.
• van Hintum, Th.J.L., C.C.M. van de Wiel, D.L. Visser, R. van Treuren, and B. Vosman. 2007. The distribution of genetic diversity in a Brassica oleracea gene bank collection related to the effects on diversity of regeneration, as measured with AFLPs. Theor. Appl. Genet. 114:777–786.[CrossRef][Web of Science][Medline]
• Horneburg, B. 2003a. Standortspezifische Sortenentwicklung: Eine Studie mit Landsorten der Linse. Schriften zu Genetischen Ressourcen Vol. 21. Informationszentrum Biologische Vielfalt, Bonn, Germany.
• Horneburg, B. 2003b. Frischer Wind für eine alte Kulturpflanze! Linsen im ökologischen Anbau, ihre Geschichte und Verwendung. Dreschflegel e.V. and Institute for Agronomy and Plant Breeding, Univ. of Göttingen, Germany.
• Horneburg, B. 2006. Outcrossing in lentil (Lens culinaris Medik.) depends on cultivar, location, and year, and varies within cultivars. Plant Breed. 125:638–640.[CrossRef]
• Jana, S., and B.S. Khangura. 1986. Conservation of diversity in bulk populations of barley (Hordeum vulgare L.). Euphytica 35:761–776.[CrossRef][Web of Science]
• Kaufmann, M.L., and A.D. Mc Fadden. 1963. The influence of seed size on results of barley yield trials. Can. J. Plant Sci. 43:51–58.
• Muehlbauer, F.J., W.J. Kaiser, S.L. Clement, and R.J. Summerfield. 1995. Production and breeding of lentil. Adv. Agron. 54:283–332.
• Paillard, S., I. Goldringer, J. Enjalbert, M. Trottet, J. David, C. de Vallavieille-Pope, and P. Brabant. 2000a. Evolution of resistance against powdery mildew in winter wheat populations conducted under dynamic management: I. Is specific seedling resistance selected? Theor. Appl. Genet. 101:449–456.[CrossRef][Web of Science]
• Paillard, S., I. Goldringer, J. Enjalbert, M. Trottet, J. David, C. de Vallavieille-Pope, and P. Brabant. 2000b. Evolution of resistance against powdery mildew in winter wheat populations conducted under dynamic management: II. Adult plant resistance. Theor. Appl. Genet. 101:457–462.[CrossRef][Web of Science]
• Parzies, H.K., W. Spoor, and R.A. Ennos. 2000. Genetic diversity of barley landrace accessions (Hordeum vulgare ssp. vulgare) conserved for different length of time in ex situ gene banks. Heredity 84:476–486.[CrossRef][Web of Science][Medline]
• Salmon, D.F., and E.N. Larter. 1978. Visual selection as a method for improving yields of triticale. Crop Sci. 18:427–430.[Abstract/Free Full Text]
• Shebeski, L.H. 1967. Wheat and breeding. p. 249–272. In K.F. Neilsen (ed.) Pro. Can. Centennial Wheat Symp. Modern Press, Saskatoon, Saskatchewan, Canada.
• Simmonds, N.W. 1991. Selection for local adaptation in a plant breeding programme. Theor. Appl. Genet. 82:363–367.[CrossRef][Web of Science]
• Suneson, C.A. 1956. An evolutionary plant breeding method. Agron. J. 48:188–191.[Abstract/Free Full Text]
• Thomas, T.H., D. Gray, and N.L. Biddington. 1978. The influence of the position of the seed on the mother plant on seed and seedling performance. Symposium on seed problems in horticulture. Acta Hortic. 83:57–66.
• Tin, H.Q., T. Berg, and Å. Bjørnstad. 2001. Diversity and adaptation in rice varieties under static (ex situ) and dynamic (in situ) management. Euphytica 122:491–502.[CrossRef][Web of Science]
• UPOV. 2003. International Convention for the Protection of New Varieties of Plants of December 2, 1961, as revised at Geneva on November 10, 1972, on October 23, 1978, and on March 19, 1991. International Union for the Protection of New Varieties of Plants, Geneva, Switzerland.
• Utz, H.F. 1997. Plabstat: Ein Computerprogramm zur statistischen Analyse von pflanzenzüchterischen Experimenten, Version 2N. Institut für Pflanzenzüchtung und Populationsgenetik, Univ. Hohenheim, Stuttgart, Germany.

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Horneburg, B. Articles by Becker, H. C. Search for Related Content PubMed Articles by Horneburg, B. Articles by Becker, H. C. Agricola Articles by Horneburg, B. Articles by Becker, H. C. Related Collections Germplasm Enhancement Plant and Environment Interactions Plant Genetic Resources