Implications of selection in common bean lines in contrasting environments concerning nitrogen levels

Implicações da seleção no feijoeiro efetuada em ambientes contrastantes em níveis de nitrogênio

ARTICLE

Implications of selection in common bean lines in contrasting environments concerning nitrogen levels

Implicações da seleção no feijoeiro efetuada em ambientes contrastantes em níveis de nitrogênio

Isabela Volpi FurtiniI, ^*; Magno Antonio Patto Ramalho^II; Ângela de Fátima Barbosa Abreu^III

^IEmbrapa Arroz e Feijão, Rodovia MT 222, km 2, 5, CP343, 78.550-970, Sinop, MT, Brazil

^IIUniversidade Federal de Lavras (UFLA), Departamento de Biologia, Setor de Genética e Melhoramento de Plantas, CP 3037, 37.200-000, Lavras, MG, Brazil

^IIIEmbrapa Arroz e Feijão, Current address UFLA

ABSTRACT

Grain productivities of 100 bean lines were evaluated in the presence and absence of nitrogen fertilizer in order to identify those with high nitrogen use efficiency (NUE) and to determine the correlated response observed in a stressed environment following selection in a non-stressed environment. The genetic and phenotypic characteristics of the lines, as wellas the response index to applied nitrogen, were determined. The average grain productivities at both locations were 39.5% higher in the presence of nitrogen fertilizer, with 8.3 kg of grain being produced per kg of nitrogen applied. NUE varied greatly between lines. Lines BP-16, CVII-85-11, BP-24, Ouro Negro and MA-IV-15-203 were the most efficient and responsive. The results showed that it is possible to select bean lines in stressed and non-stressed environments. It was inferred that common bean lines for environments with low nitrogenav ailability should preferably be selected under nitrogen stress.

Key words: Phaseolus vulgaris L., nitrogen use efficiency, correlated response, selection gain

RESUMO

A produtividade de grãos de 100 linhagens de feijoeiro foi avaliadana presença e ausência de fertilizante nitrogenado visando identificar aquelascom maior eficiência no uso de nitrogênio (EUN) e estimar a respostacorrelacionada em ambientes sob baixa disponibilidade de nitrogênio, pelaseleção efetuada sem o estresse do nutriente. Estimaram-se os índices deresposta à aplicação de nitrogênio e os parâmetros genéticos e fenotípicos. Namédia dos locais, a produtividade de grãos obtida com N foi 39, 5% acima daobtida sem N, correspondendo a 8, 3 kg de grãos por kg de N aplicado. A EUNvariou entre as linhagens. As linhagens BP-16, CVII-85-11, BP-24, Ouro Negro eMA-IV-15-203 foram as mais eficientes e responsivas. É possível obter sucessocom a seleção em ambientes com e sem estresse de nitrogênio, contudo a seleçãode linhagens para ambientes sob baixa disponibilidade de nitrogênio deve serrealizada preferencialmente nesta condição.

Palavras-chave: Phaseolus vulgaris L., eficiência na utilização de nitrogênio, resposta correlacionada, ganho com a seleção

INTRODUCTION

A range of different types of cropping systemsare available for the cultivation of the common bean (Phaseolus vulgaris L.). Although many small farmers do not apply modern technologies in cropproduction, a number of large rural businesses make use of novel irrigationmethods, advanced agricultural techniques and modern implements.

Although P. vulgaris is a member of thefamily Leguminosae (Fabaceae), the quantities of nitrogen fixed is insufficientfor the daily requirements of the plant (Cassini and Franco 2006, Brito et al.2011). Thus, nitrogen supplementation to common bean cultures is essential inachieving increased yield. However, while many farmers employ fertilizers incrop production, others choose to cultivate their crops in the absence of suchsupplements. Considering that fertilizers represent a significant proportion ofproduction costs (Skalsky et al. 2008), that the continuous use of N can causeenvironmental impacts (Hirel et al. 2007) and since farmers plant similarcultivars regardless of the cropping system used, it is important to developbean lines that offer high nitrogen use efficiency.

The nitrogen use efficiency (NUE) of a crop maybe determined on the basis of either the grain yield produced per unit ofnitrogen supplied, or the grain yield produced under conditions of low nitrogenavailability (Lopes and Guilherme 2000, Hirel et al. 2007). Generally speaking, most breeding programs evaluate cultivars or progenies in the presence ofnitrogen fertilizer since, under such conditions, productivity is high and thecontrol of environmental variabilities is more efficient. Moreover, because theassessment of genotypic differences between cultivars and progenies is morestraightforward, it is considered that heritability estimates can be determinedmore accurately (Ceccarelli et al. 1998, Emede and Alika 2012). However, thereare contradictory reports concerning the efficiency of direct and indirect selectionof cultivars and progenies. For example, some results obtained demonstratedthat the selection under favourable conditions did not reveal gains expressedunder unfavourable conditions (Banziger et al. 1997, Brancourt-Hulmel et al.2005, Mandal et al. 2010, Weber et al. 2012). In contrast, some reports(Gallais et al. 2008, Anbessa et al. 2010) have shown that such indirectselection can be more efficient than direct selection. Atlin and Frey (1989), on the other hand, report that direct and indirect selection are equallyefficient since there was a high genetic correlation between oat linescultivated under low and high nitrogen availability, and the responses in bothenvironments were similar. The use of alternate direct and indirect selectionprocedures has been proposed by some researchers (Van Ginkel et al. 2001).

According to Falconer and Mackay (1996), indirect selection is advantageous when the square root of the heritabilityvalue (h_x) obtained under non-stressed conditions is largerthan that obtained under stressed conditions (h_y), or whenthe genetic correlation between the two conditions (r_xy) isstrong (h_y < r_xyh_x).

The most studies on nitrogen use efficiency(NUE) was performed with grasses, especially with crops of corn (Banziger etal. 1997, Presterl et al. 2003, Emede and Alika 2012, Weber et al. 2012) andwheat (Le Gouis et al. 2000, Brancourt-Hulmel et al. 2005). As the vastmajority of common bean breeding programs in Brazil evaluates the progenyand/or lines in the presence of N, it is important to check whether theselection made under favorable conditions to culture, is also effective forstress conditions. Since information relating to these aspects of the cultureof bean is limited, the objective of the present study was to identify beanlines presenting high NUE and to determine the correlated response of grainproductivity observed in a stressed environment following selection in anon-stressed environment.

MATERIAL AND METHODS

The experiments were conducted in Lavras (lat21º 14' S, long 44º 59' W and alt 919 m asl), on a Dystroferric Red Oxisol andin Ijaci (lat 21º 10' S, long 44º 55' W and alt 805 m asl), on a Red-YellowUltisol, both in the State of Minas Gerais, Brazil. The chemicalcharacteristics of the soils at these two locations are presented in Table 1.

A total of 100 bean lines derived from thegermplasm bank of the Universidade Federal de Lavras (UFLA) were evaluated.Most of these lines were of the carioca type and some were commercial cultivarsoriginating from breeding programmes conducted at UFLA over the last 30 years.Each bean line was submitted to two separate, but adjacent, experiments. In thefirst experiment no nitrogen fertilizer was applied, whilst in the secondexperiment 100 kg ha^-1 of nitrogen [(NH₄)₂SO₄]was applied (1/3 before sowing, 1/3 20 days after sowing and 1/3 27 days aftersowing). In both experiments, 80 kg ha^-1 of phosphorus (P₂O₅) and potassium (K₂O) were applied to the soil before sowing.

A 10 x 10 triple lattice design was employed.The plots consisted of two lines (2 m each) spaced at 50 cm from each other andseeds were sown at a density of 15 seeds/m. The grain yields (kg ha^-1)of the bean lines were determined for each nitrogen level and location, and theresults were subjected to individual and combined analysis of varianceinvolving the two N levels per location as well as all levels and locations, according to the model:

y_ljtu = µ + p_l + n_t + a_u + q _{j (tu)}+ (pn) _lt + (pa) _lu + (na) _tu + (pna) _ltu + e_ljtu

in which y_ljtu isthe observation relating to line l, repetition j, nitrogen level t, location u ; µ is the average value; p_l isthe effect of line l (l = 1, 2, 3, ..., 100); n_t is the effect of nitrogen level t (t = 1, 2); a_u is the effect of location u (u = 1, 2); q _{j (tu)}is the effect of repetition j, nitrogen level t, location u ;(pn) _lt is the effect of the interaction between beanlines x nitrogen level; (pa) _lu is the effect ofthe interaction between bean lines x locations; (na) _tu is the effect of the interaction between nitrogen levels x locations; (pna) _ltu is the effect of the interaction between bean lines x nitrogen levels x locations; and e_ljtu is the experimental error e_ljtu N (0, σ²).

Nitrogen level (presence or absence), locationand the average value were considered as fixed effects, whilst the others wereconsidered to be random effects. The genetic and phenotypic parameters wereestimated from the expected mean square values according to the literature(Falconer and Mackay 1996, Bernardo 2002). The errors associated with theexpected gains from selection by the expression proposed by Bridges et al.(1991) were also calculated.

The response index to applied nitrogen (α)was calculated from average grain yield values (kg.ha^-1) using theequation (Thung 1990):

α_i = (N_li – N _{2 i})/ Q

in which α_i is the response index of line i ; N_li is the averagegrain yield of line i in the presence of nitrogen fertilizer; N _{2 i}is the average grain yield of line i in the absence of nitrogenfertilizer; and Q is the amount of nitrogen applied (100 kg ha^-1).

RESULTS AND DISCUSSION

In experiments testing fertilizer levels it isadvisable to use borders surrounding the plots. However, when 100 bean linesare evaluated, the plots would be large, and it would hardly be possible toevaluate homogeneous areas, particularly in terms of organic matter content.For this reason, two contiguous experiments were performed without borderssurrounding the plots. With this strategy it was expected that the twoexperiments close to each other would differ predominantly due to the Napplication levels. The strategy was apparently appropriate, since theexperimental precision was good, when considering the experiments separately.

The differences between the N levels weresignificant (P <0.01). In the mean of the two locations, the experimentswith N fertilization produced 39% more than where no N was applied, ie, therewas a mean grain yield increase of 826 kg ha^-1, which corresponds to8.3 kg grain per kg N applied (Table 2). Nitrogen is the most required nutrientby most crops, including common bean. For this reason, N response to nitrogenin common bean can frequently be observed (Furtini et al. 2006, Binotti et al.2007). In a total of 80 field experiments with common bean, the response to Napplication was positive in 64% of the trials (Vieira 2006). However, acomparison of the response between experiments is difficult because it dependson a number of factors, related to the environment as well as the genotype.

The interaction locations x N levels was alsosignificant (P<0.01). The response to N application was most significant inIjaci, where grain yield increased by 11.1 kg grain per kg N (Table 2). Theconditions of soil fertility at the experimental locations, although close toeach other, were somewhat different (Table 1). It was therefore not surprising, that the response of the lines differed between locations.

For thiskind of experiments the existence of genetic variability in the lines for thetrait is essential. The differences between lines were significant in allexperiments (P<0.01). The lines tested had been bred in the last 30 years inthe UFLA improvement program as well as in other breeding programs in Brazil.Differences in yield, as in fact observed, had therefore been expected.

The genetic variability between lines was alsoshown by the estimates of genetic variance (σ²_G) inthe lines (Table 3). In all environments (locations and N levels), σ²_Gdiffered from zero (P <0.05).

The variability between lines can also beconfirmed by the estimates of heritability (h²). In all experiments, the lower limit of the confidence interval (CI) of the h² estimateswas positive. It was also inferred that the h² estimates weresimilar under most conditions (Table 3).

It was often reported that h²estimates are lower in stressed environments due to the lower accuracy undersuch experimental conditions (Banziger et al. 1997, Ceccarelli et al. 1998, Brancourt-Humel et al. 2005, Emede and Alika 2012). However, it was observedthat the h² estimates were similar in conditions with and without Nstress (Table 2). Similar results were reported by Presterl et al. (2003). Itcan therefore be inferred, in principle, that the conditions for success withselection do not depend on the presence or absence of stress.

Estimates of the expected gains with selection(GS) were established for 10% of the best lines, at each N level. It appearsthat the estimates of GS were significant (Table 4), both with or without Napplication. It follows therefore that the success can be high, regardless ofwhether selection is performed with or without N stress.

It is questionable whether indirect selectionunder high N would result in gains for performance under low N. The correlated response to indirect selection only exceeds direct trait selection, if thesquare root of h², under N-stress conditions (h_y) islower than the product of genetic correlation of line performance in bothconditions by the square root of heritability (h_x) between lines inthe presence of N (r_xyh_x) (Falconer and Mackay 1996). Inthis study, the h_y estimates always exceeded the product r_xyh_x.Under this condition, the estimates of correlated response by the selection inthe presence of N and the response to environmental stress were all lower thanin direct selection (Table 3). These results are similar to those reported byBanziger et al. (1997), Brancourt-Hulmel et al. (2005), Mandal et al. (2010)and Weber et al. (2012). These authors observed that if the goal is theselection of cultivars for N-poor environments, the selection must be performedunder N stress to maximize the gain with selection.

The estimates of genetic correlation of lineperformance in environments with or without N application (r_G) wereintermediate at both locations (Table 4). The estimates of correlated response(RC_y/x) by selection in the environment with N application wasrelatively high (Table 3). The relationship between RC_y/x and the gain with direct selection in thestressed environment (GS_y) showed that the highest and lowestestimates of the gain with indirect selection accounted for 62% and 46% of thegain with direct selection, respectively.

Although the correlated response to indirectselection was lower than to direct selection, it was significant (Table 4).Some lines that performed well in stressed as well as unstressed environmentscould therefore be identified. Based on estimates of the response index to Napplication associated with line yields in the nitrogen-stressed environment, the lines were grouped into four categories, according to Blair (1993), namely:

Inefficient and non-responsive (INR): linesthat produced less than the overall mean of the N- stressed experiments and hada α below the overall mean of the indexes; Inefficient andresponsive (IR): lines that produced less than the overall mean of the N-stressed experiments, but α exceeded the overall mean of theindexes; Efficient and non-responsive (ENR): lines that produced more than theoverall mean of the N- stressed experiments and had a α below theindex mean; Efficient and responsive (ER): lines that produced more than theoverall mean of N-stressed experiments and had a α above thegeneral index mean.

The lines were distributed in 29% INR, 23% IR, 21% ENR and 27% ER (Figure 1). The mean grain yield of the lines PF2-53 andP5-9, classified as INR, was low and did not respond to N fertilization. Thelines CVII-45-5, P1-103 and RC-II-2-19 however, classified as IR, responded toN application, but had low mean grain yields. The lines BP-16, CVII-85-11, BP-24, Ouro Negro, and MA-IV-15-203 performed best in the category ER. Theperformance of the lines Pérola, CVIII-6, CVII-215-10 and MA-I-2.5 was alsointeresting, since they produced high grain yields in the environment under Nstress, although they responded poorly to N fertilization (Figure 1).

The performance of Ouro Negro and MA-I-2.5, inresponse to N, has been described elsewhere (Furtini et al. 2006). Firstly, itcan be inferred that these lines make better use of available soil N than theothers. Possibly these lines also have greater efficiency in biologicalnitrogen fixation with native soil strains, since the seeds were notinoculated. For the line Ouro Negro line this last aspect has already beenreported in the literature (Franco 1995).

ACKNOWLEDGEMENTS

The authors thank the Conselho Nacional deDesenvolvimento Científico e Tecnológico (CNPq) for a scholarship granted andFAPEMIG for funding the research project.

Received 23 August 2013

Accepted 08 May 2014

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Publication Dates

• Publication in this collection
  25 Nov 2014
• Date of issue
  Oct 2014

History

• Received
  23 Aug 2013
• Accepted
  08 May 2014