Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=gags20 Archives of Agronomy and Soil Science ISSN: 0365-0340 (Print) 1476-3567 (Online) Journal homepage: https://www.tandfonline.com/loi/gags20 Differential response of soybean genotypes to two lime rates Adônis Moreira, Larissa Alexandra Cardoso Moraes, Isabelle Cristina Vilarino Lara & Thiago Assis Rodrigues Nogueira To cite this article: Adônis Moreira, Larissa Alexandra Cardoso Moraes, Isabelle Cristina Vilarino Lara & Thiago Assis Rodrigues Nogueira (2017) Differential response of soybean genotypes to two lime rates, Archives of Agronomy and Soil Science, 63:9, 1281-1291, DOI: 10.1080/03650340.2016.1274976 To link to this article: https://doi.org/10.1080/03650340.2016.1274976 Accepted author version posted online: 20 Dec 2016. Published online: 02 Jan 2017. Submit your article to this journal Article views: 58 View Crossmark data https://www.tandfonline.com/action/journalInformation?journalCode=gags20 https://www.tandfonline.com/loi/gags20 https://www.tandfonline.com/action/showCitFormats?doi=10.1080/03650340.2016.1274976 https://doi.org/10.1080/03650340.2016.1274976 https://www.tandfonline.com/action/authorSubmission?journalCode=gags20&show=instructions https://www.tandfonline.com/action/authorSubmission?journalCode=gags20&show=instructions http://crossmark.crossref.org/dialog/?doi=10.1080/03650340.2016.1274976&domain=pdf&date_stamp=2016-12-20 http://crossmark.crossref.org/dialog/?doi=10.1080/03650340.2016.1274976&domain=pdf&date_stamp=2016-12-20 Differential response of soybean genotypes to two lime rates Adônis Moreiraa, Larissa Alexandra Cardoso Moraesa, Isabelle Cristina Vilarino Laraa and Thiago Assis Rodrigues Nogueirab aDepartment of Soil Science and Mineral Plant Nutrition, National Soybean Research Center of EMBRAPA, Londrina, Brazil; bDepartment of Soils and Environmental Resources, São Paulo State University, Botucatu, Brazil ABSTRACT Soybean [Glycine max (L.) Merril] is the leading food crop worldwide, and selection of soybean genotypes for different levels of soil acidity may raise crop yield without the need to increase in planted area. An experi- ment in greenhouse conditions was conducted to determine the effects of two lime rates on soil chemical properties, grain yield (GY), yield components, nutritional status and physiological components of 15 soybean genotypes adapted to tropical and subtropical conditions. Genotypes BMX Apolo RR, BMX Potência RR, BRS 295RR, BRS 359RR, FPS Solar IPRO and TMG 716 IRR were the least responsive to soil acidity reduction, and BMX Turbo RR and BRS 360RR were the most responsive. Number of pods per pot, shoot dry weight yield, GY, photosynthesis, stomatal conductance, transpiration and chlorophyll increased signifi- cantly with increase in lime rate. Cultivar FPS Solar IPRO showed the highest foliar P, K, Ca and Mg concentrations in soybean, which was not observed in the grain, indicating the presence of genetic factors and the dilution effect on nutrient uptake. ARTICLE HISTORY Received 23 August 2016 Accepted 18 December 2016 KEYWORDS Glycine max; soil acidity; grain yield; physiological components; yield components Introduction Soybean is Brazil’s most important agricultural export product, with production of 95.6 million tons in the 2015/2016 season (CONAB 2016). This increase is mostly due to the high prices of the product in the international market, which resulted in expansion of cultivated areas, including sandy soils with lower fertility and degraded pastures, where soil acidity is a limiting factor in plant development because it restricts root growth and inhibits water and nutrient uptake (Fageria & Baligar 2008; Moreira & Fageria 2010). Soil acidity is one major factor limiting nutrient availability and uptake (Fageria & Baligar 2001). In Brazil, especially in the center region where agricultural expansion was more pronounced, soils are mostly of low fertility, with pH values lower than 4.5, high aluminum (Al3+) concentrations, high phosphorus (P) fixation capacity and potential acidity (H+ + Al3+) predominant in the cation exchange capacity (CEC) in soil solution (Fageria & Baligar 2008; Moreira et al. 2015a). Liming is the most widely used practice to neutralize acidity, increase nutrient availability, supply calcium (Ca2+) and/or magnesium (Mg2+), neutralize toxic Al3+, manganese (Mn2+) and hydrogen (H+), improve root environment and restore soil productive capacity (Kamprath 1984; Soratto & Crusciol 2008). The amount of lime to be used depends on the soil type (clay content), quality, cost of material, species and/or genotype (Moreira & Fageria 2010). Concomitantly, explora- tion of genetic yield potential of plants can also be used in plant breeding programs in order to CONTACT Adônis Moreira adonis.moreira@embrapa.br Department of Soil Science and Mineral Plant Nutrition, National Soybean Research Center of EMBRAPA, Londrina, Brazil ARCHIVES OF AGRONOMY AND SOIL SCIENCE, 2017 VOL. 63, NO. 9, 1281–1291 https://doi.org/10.1080/03650340.2016.1274976 © 2016 Informa UK Limited, trading as Taylor & Francis Group http://www.tandfonline.com http://crossmark.crossref.org/dialog/?doi=10.1080/03650340.2016.1274976&domain=pdf incorporate desirable traits in varieties susceptible to these limitations. In addition to ensure the appropriate management of chemical and biological soil properties, focus should be given to their recovery and conditioning of high-yielding cultivars under adverse conditions (Fageria & Morais 1987). The hypothesis of the present study was that genotypes respond differently to the lime rates. Its purpose was to assess the behavior of different soybean genotypes, recommended for tropical and subtropical conditions, subjected to two lime rates on grain yield (GY), soil chemical properties, nutritional status, yield components and physiological components of the plant. Material and methods Site and soil characteristics The experiment was conducted in greenhouse conditions at the Embrapa Soja, Londrina County, Paraná State, Brazil (23°11′39″LS and 51°10′40″LW) to evaluate the development of tropical and subtropical soybean genotypes submitted to different soil acidity rates. The soil used was Typic Quartzipsamment, with sandy texture (142 g kg−1 clay and 841 g kg−1 sand), collected from 0 to 20 cm depth in the Luis Eduardo Magalhães County, Bahia State, Brazil (20°45′04″LS and 51°40′42″LW), with the following soil chemical properties (EMBRAPA 1997) before treatments application: pH (H2O) = 3.9, organic matter (OM) = 9.3 g kg−1, P (Mehlich 1 extractant) = 1.0 mg kg−1, exchangeable potassium (K+) = 0.02 cmolc kg −1, exchangeable Ca2+ = 0.07 cmolc kg −1, exchangeable Mg2+ = 0.05 cmolc kg −1, exchangeable Al3+ (KCl 1.0 mol L−1 extractant) = 0.7 cmolc kg−1, potential acidity (H+ + Al3+) = 3.4 cmolc kg−1, sulfur (S– SO4 2−) = 5.8 mg kg−1, CEC (∑K+, Ca2+, Mg2+, H+ + Al3+) = 3.5 cmolc kg −1, effective CEC – CECE = (∑K+, Ca2+, Mg2+, Al3+) = 0.84 cmolc kg −1, base saturation – V [(∑K+, Ca2+, Mg2+/CEC) × 100] = 4.1%, available boron – B (hot water) = 0.13 mg kg−1, available copper – Cu (Mehlich 1) = 0.1 mg kg−1, available iron – Fe (Mehlich 1) = 59.0 mg kg−1, available manganese –Mn (Mehlich 1) = 0.3 mg kg−1 and available zinc – Zn (Mehlich 1) = 0.2 mg kg−1. Experimental design, fertilization and planting Completely randomized design in 15 × 2 factorial arrangement of treatments, with four replicates, was used. The treatments consisted of 15 genotypes (Table 1) and 2 liming rates with calcium oxide (CaO) 27.8%, magnesium oxide (MgO) 19.6% MgO and reactive power to completely neutralize (RPCN) 85.5%. The rates were calculated to raise soil base saturation to 40% and 70% – equivalent to 1.5 and 2.7 t ha−1, and defined as low and high lime rates application, according to the following formula: Table 1. Description of fifteen genotype used in the experiment. Genotype Characteristic Growing habit Maturation group Cycle BMX Apolo RR Transgenic Indeterminate 5.5 Super early BMX Força RR Transgenic Indeterminate 6.2 Early BMX Potência RR Transgenic Indeterminate 6.7 Semi-early BMX Turbo RR Transgenic Indeterminate 5.8 Super early BRS 294RR Transgenic Determinate 6.3 Early BRS 295RR Transgenic Indeterminate 6.5 Early BRS 359RR Transgenic Indeterminate 6.5 Early BRS 360RR Transgenic Indeterminate 6.5 Early NA 5909RR Transgenic Indeterminate 6.7 Semi-early NA 6262RR Transgenic Indeterminate 6.4 Early FTS Solar IPRO Transgenic Indeterminate 5.8 Super early TMG 1066RR Transgenic Determinate 6.6 Semi-early TMG 7161RR Transgenic Indeterminate 6.1 Early TMG 7262RR Transgenic Indeterminate 6.2 Early Vmax RR Transgenic Indeterminate 6.4 Early 1282 A. MOREIRA ET AL. LQ kg ha�1 � � ¼ V2 � V1ð Þ RPCN � CEC where LQ is amount of lime (kg ha−1), V2 (desired base saturation) is 40% (high acidity) or 70% (low acidity), V1 (base saturation found in soil) is 4.1%, RPCN is 85.5% and CEC is 3.5 cmolc kg −1. The experiment clay pots with 3.0 dm3 of soil passed through a 2.0-mm sieve were used. Except for N, which was supplied by inoculation of seeds with Bradyrhizobium elkanii + Bradyrhizobium japonicum, fertilizations with P, K, S, B, Co, Cu, Fe, Mn, molybdenum (Mo), nickel (Ni) and Zn were performed according to Moreira and Fageria (2010) adapted from Allen et al. (1976) for experi- ments conducted in greenhouse condition [150 mg kg−1 of P – monoammonium phosphate, 50 mg Ca kg−1 – calcium sulfate (CaSO4), 0.5 mg B kg−1 boric acid (H3BO3), 1.5 mg Cu kg−1 – copper sulfate (CuSO4∙7H2O), 0.1 mg Mo kg−1 – sodium molybdate (Na2Mo4∙2H2O), 2.5 mg Fe kg−1 – iron sulfate (FeSO4∙2H2O), 0.01 mg Co kg−1 – cobalt chloride (CoCl2), 0.01 mg Ni kg−1 – nickel sulfate (NiSO4∙6H2O), 5.0 mg Mn kg−1 – manganese sulfate (MnSO4∙3H2O), and 5.0 mg Zn kg−1 – zinc sulfate (ZnSO4∙7H2O)]. In V2 and V4 growth stages, top-dressing fertilizations were made twice with 50 mg K kg−1 (K2SO4), totaling 100 mg K kg−1 in the cycle. The pots were daily irrigated with deionized water to compensate for losses by evapotranspiration and maintain moisture content around 70% of total pore volume, using the method described by Cassel and Nielsen (1986). Ten seeds were sown, and after trimming, there were two plants per pot. Harvest and laboratory analysis At R2 reproductive stage (Fehr et al. 1971), in the morning, the following measurements were made from the third–fourth leaf pair from the apex: photosynthetic rate, A (μmol CO2 m−2 s−1), stomatal conductance, gs (mol H2O m−2 s−1), transpiration, Trmmol (mmol H2O m−2 s−1), internal carbon dioxide concentration, Ci (μmol CO2 mol−1) and intrinsic water use efficiency [IWUE] = A/ Trmmol (μmol CO2 m−2 s−1) was determined with a portable photosynthesis analyzer (LI-6400XT; LICOR®, Lincoln, NE). At this stage, Konica Minolta SPAD-502 Plus was used for the measurement of the SPAD units of these leaves. The SPAD data were converted into chlorophyll content (mg cm−2) using the equation ŷ = 16.033 + (7.5774 × SPAD) (Fritschi & Ray 2007). After the measurements, the same trifoliates were collected from the apex (diagnostic leaf) of each treatment and dried in forced circulation at 65 ± 2°C for determination of total N, P, K, Ca, Mg and S concentrations (Malavolta et al. 1997). Throughout the vegetative cycle, foliar senescent for the shoot dry weight yield (SDWY) was collected. After the physiological maturity stage (R8), GY, number of pods per pot (NPP), number of grain per pot (NGP) and number of pods were quantified. Again, the total N, P, K, Ca, Mg and S concentrations in grain were determined. After collection, soil sample of each pot was removed for determination of soil chemical properties (pH, OM, P, K+, Ca2+, Mg2+, H+ + Al3+, Al3+ and CEC), according to the methodologies described by EMBRAPA (1997). Relative yield (RY) of the genotypes was determined with the following equation: RY ð%Þ ¼ W W1 � 100 where W is GY in treatment V = 40% (high acidity) for each variety and W1 is GY in treatment V = 70% (low acidity) for each variety. Statistical analyses The results for soil chemical properties, yield and physiological components and nutritional status were subjected to normality tests (Hicks 1973), and subsequently to analysis of variance, F test and Scott–Knott test for multiple comparison of means (Scott & Knott 1974), at 5% of probability. ARCHIVES OF AGRONOMY AND SOIL SCIENCE 1283 Result and discussion Soil chemical properties Significant effect was reported for rates and genotypes and lack of interaction of these two factors on soil chemical properties after soybean harvest (Table 2). Regardless of the genotypes, increased lime rate provided a significant increase (23.2%) in pH values, while regarding the genotypes, BMX Apolo RR, NA 6262RR and TMG 7262RR caused the least statistically significant soil acidity (Table 2). Such results corroborate other studies (Castro & Crusciol 2013; Fageria et al. 2012; Moreira et al. 2014, 2015b), by demonstrating that lime in contact with soil moisture produces the following consequences: increased Ca2+ and Mg2+ levels, dissociation of (OH−) hydroxyl groups and reduc- tion of H+ ions in soil solution and consequent rise in pH value. Similarly to what was observed by Moreira et al. (2014) in soybean growing, increased lime rates generated a significant increase in exchangeable Ca2+ and Mg2+ and in CEC, as well as decrease in exchangeable Al3+, K+ and H+ + Al3+ of soil (Table 2). Regarding the genotypes, only the exchange- able Ca2+ and Mg2+ levels were significant, and Mg2+ showed genotype × lime rates interaction, indicating that the genotypes responded differently to the two lime rates (Table 2). The lowest nutrient concentrations in the soil were reported in genotypes BMX Potência RR (0.2 cmolc kg −1) in V = 40% and in genotype Vmax RR (0.4 cmolc kg−1) in V% = 70, while the highest rate was NA 6262RR (0.3 cmolc kg −1) and TMG 7161RR (0.7 cmolc kg −1). The referred increase in Ca2+ and Mg2+ soil concentrations was expected because the dolomite lime used has 27.8% of CaO and 19.6% of Mg in its composition. Moreira and Fageria (2010) and Castro and Crusciol (2013) reported a significant increase in the levels of these nutrients after lime application. Among the genotypes, Ca2+/K+ and Mg2+/K+ ratios increased from 1.4 to 3.2, and from 0.6 to 1.6, and Ca2+ and Mg2+ saturations in CEC from 14.9% to 25.3% and 6.8% to 8.0% with increased concentration of Ca2+ and Mg2+ in the soil, as a result of the higher lime rate used to raise base saturation from 40% to 70%. Fageria et al. (2013, 2014) and Moreira et al. (2015a) reported similar results regarding the increase of these variables after application of larger lime rates. Regardless of the rates and genotypes, Ca2+ and Mg2+ base saturations in the CEC were below 65–85% and 10– 20%, while K+ saturation in CEC was above 2–5% reported by Eckert (1987) as an adequate balance of these ions in soil CEC allowing the plants to express their potential yield. GY and yield components Genotypes and lime rates showed significant interaction for GY, NPP and SDWY, indicating that the genotypes responded differently to each lime rate used (Table 3). GY ranged from 10.9 g pot−1 (BRS 360RR) to 19.1 g pot−1 (BMX Potência RR), at lowest rate (V = 40%), with a mean value of 15.5 g pot−1. At higher lime rate (V = 70%), SY varied from 16.1 g pot−1 (BMX Força RR) to 22.9 g pot−1 (BMX Turbo RR), with a mean value of 20.3 g pot−1. In the mean of genotypes, increase in the lime rate applied resulted in an increase of 31.1% in GY. This was also observed for SDWY, which had a positive significant correlation with GY (ŷ = 10.482 + 0.171x, r = 0.51, p ≤ 0.05), and ranged from 23.2 g pot−1 (TMG 7161RR) to 48.4 g pot−1 (BRS 294RR) and 37.5 g pot−1 (NA 6262RR) to 62.1 g pot−1 (BMX Força RR) at low (V = 40%) and high (V = 70%) lime rates (Table 3). Moreira et al. (2015b) reported that soybean genotypes adapted to tropical and subtropical conditions showed different responses of growth for SDWY and GY, which has been stressed by RY, since genotype BRS 360RR was the most sensitive (58.7%) and NA 5909RR the least sensitive (88.8%) to soil acidity. Among the genotypes, the average RY value was 74.6% (Table 3). Corroborating Fageria et al. (2014), NPP showed a significant correlation with GY (ŷ = 5.163 + 2.610x, r = 0.52, p ≤ 0.05) and was also significantly increased with lime rate, which has not been reported for the mean NGP, regardless of the genotype and lime rate used (Table 3). Fageria et al. (2014) reported that decrease in soil acidity significantly increased NPP (Table 2), 1284 A. MOREIRA ET AL. Ta bl e 2. So il ch em ic al pr op er tie s af te r so yb ea n ha rv es t cu lti va te d w ith tw o lim e ra te s [lo w -b as e sa tu ra tio n of 40 % (1 .4 9 t ha − 1 of lim e) an d hi gh of 70 % (2 .7 3 t ha − 1 of lim e) ] ap pl ic at io n. a pH P K Ca M g Al H + + Al CE C (C aC l 2 ) (m g kg − 1 ) (c m ol c kg − 1 ) (c m ol c kg − 1 ) (c m ol c kg − 1 ) (c m ol c kg − 1 ) (c m ol c kg − 1 ) (c m ol c kg − 1 ) G en ot yp e Lo w H ig h Lo w H ig h Lo w H ig h Lo w H ig h Lo w H ig h Lo w H ig h Lo w H ig h Lo w H ig h BM X Ap ol o RR 4. 3a 5. 5a 40 .1 a 43 .7 a 0. 33 a 0. 33 a 0. 6a 0. 9a 0. 3a 0. 5a 0. 22 a 0. 00 a 2. 7a 2. 0a 3. 94 a 3. 92 a BM X Fo rç a RR 4. 3a 5. 3b 38 .1 a 32 .8 a 0. 47 a 0. 37 a 0. 6a 0. 9a 0. 3a 0. 4b 0. 18 a 0. 02 a 2. 5a 2. 1a 3. 83 a 3. 86 a BM X Po tê nc ia RR 4. 2a 5. 3b 40 .6 a 41 .6 a 0. 47 a 0. 30 a 0. 5b 1. 0a 0. 2b 0. 5b 0. 29 a 0. 01 a 2. 7a 1. 9a 3. 79 a 3. 69 a BM X Tu rb o RR 4. 3a 5. 5b 44 .4 a 36 .9 a 0. 47 a 0. 30 a 0. 6a 1. 0a 0. 3a 0. 6a 0. 22 a 0. 00 a 2. 5a 1. 9a 3. 86 a 3. 79 a BR S 29 4R R 4. 2a 5. 3b 39 .6 a 33 .0 a 0. 43 a 0. 37 a 0. 5b 1. 0a 0. 2b 0. 5b 0. 27 a 0. 03 a 2. 5a 2. 0a 3. 68 a 3. 88 a BR S 29 5R R 4. 4a 5. 1b 36 .6 a 33 .4 a 0. 33 a 0. 37 a 0. 6a 0. 8b 0. 3a 0. 4b 0. 17 a 0. 04 a 2. 5a 2. 4a 3. 65 a 3. 99 a BR S 35 9R R 4. 2a 5. 2b 46 .6 a 35 .6 a 0. 40 a 0. 40 a 0. 6a 1. 0a 0. 3a 0. 4b 0. 25 a 0. 03 a 2. 4a 2. 3a 3. 81 a 3. 93 a BR S 36 0R R 4. 3a 5. 3b 36 .7 a 43 .3 a 0. 37 a 0. 27 a 0. 6a 1. 1a 0. 2a 0. 4b 0. 21 a 0. 03 a 2. 5a 2. 2a 3. 70 a 3. 98 a N A 59 09 RR 4. 3a 5. 3b 43 .1 a 38 .4 a 0. 33 a 0. 23 a 0. 6a 1. 1a 0. 3a 0. 5b 0. 21 a 0. 03 a 2. 6a 2. 2a 3. 75 a 3. 98 a N A 62 62 RR 4. 4a 5. 6a 47 .0 a 44 .2 a 0. 40 a 0. 30 a 0. 6a 1. 1a 0. 3a 0. 7a 0. 15 a 0. 00 a 2. 3a 1. 8a 3. 68 a 3. 85 a FT S So la r IP RO 4. 2a 5. 3b 41 .0 a 36 .1 a 0. 37 a 0. 23 a 0. 5a 0. 9a 0. 3a 0. 5b 0. 24 a 0. 05 a 2. 7a 2. 2a 3. 88 a 3. 84 a TM G 10 66 RR 4. 2a 5. 3b 43 .4 a 36 .6 a 0. 53 a 0. 33 a 0. 5a 1. 0a 0. 2b 0. 5a 0. 29 a 0. 02 a 2. 7a 2. 1a 4. 03 a 4. 04 a TM G 71 61 RR 4. 4a 5. 4b 47 .3 a 49 .7 a 0. 52 a 0. 30 a 0. 6a 1. 1a 0. 3a 0. 7a 0. 17 a 0. 00 a 2. 5a 2. 1a 3. 97 a 4. 10 a TM G 72 62 RR 4. 4a 5. 5a 51 .5 a 41 .5 a 0. 48 a 0. 27 a 0. 6a 1. 1a 0. 3a 0. 6a 0. 17 a 0. 00 a 2. 5a 1. 9a 3. 94 a 3. 91 a V m ax RR 4. 2a 5. 1b 48 .8 a 41 .6 a 0. 43 a 0. 30 a 0. 5a 0. 9 0. 3a 0. 4b 0. 26 a 0. 05 a 2. 7a 2. 3a 3. 88 a 3. 92 a M ea n 4. 3B 5. 3A 43 .0 A 39 .2 A 0. 42 A 0. 31 B 0. 6B 1. 0A 0. 3B 0. 5A 0. 22 A 0. 02 B 2. 6A 2. 1B 3. 83 B 3. 91 A F te st G en ot yp e 2. 50 1* 0. 99 5N S 0. 69 9N S 2. 38 8* 5. 30 5* 1. 40 8N S 1. 70 2N S 1. 23 8N S Ra te s 22 3. 19 4* 0. 90 5N S 16 .7 22 * 60 1. 50 1* 35 4. 01 * 23 1. 12 5* 12 4. 54 1* 4. 61 0* G en ot yp e × ra te s 1. 35 1N S 0. 95 4N S 0. 55 2N S 1. 82 3N S 2. 77 1* 1. 37 6N S 1. 18 7N S 0. 75 2N S CV (% ) 3. 01 27 .9 8 28 .1 5 10 .3 3 16 .2 5 38 .2 6 8. 54 4. 91 *, N S S ig ni fi ca nt at th e 5% pr ob ab ili ty le ve la nd no t si gn ifi ca nt ,r es pe ct iv el y. a V al ue s fo llo w ed by si m ila r lo w er ca se le tt er s in th e sa m e co lu m n an d up pe rc as e le tt er in th e sa m e lin e w ith in th e sa m e va ria bl es ar e no t si gn ifi ca nt ly di ff er en t at p ≤ 0. 05 by Sc ot t– Kn ot t te st . Lo w -b as e sa tu ra tio n (V ) = 40 % .H ig h- ba se sa tu ra tio n (V ) = 70 % .C V: Co effi ci en t of va ria tio n. ARCHIVES OF AGRONOMY AND SOIL SCIENCE 1285 while NGP is more related to genetic characteristics of each genotype. Among the genotypes, the highest NPP level in the two lime rates (V = 40% and 70%) was observed in genotype BRS 295RR, and in the mean of genotypes, it was 47.6% higher for the higher lime applied (Table 3). Lime is an important source of Ca and Mg, improves root environment and biological N fixation (Moreira & Fageria 2010), which are directly related to GY. Leaf and grain nutrient concentration Leaf N, K, Ca, Mg and S concentrations were significantly influenced by increase in lime rates and genotype variety, with genotype × rates interaction observed for N and S concentrations and different responses only regarding P concentration (Table 4). Regardless of the treat- ments, leaf N, K and S concentrations were below 45.0–55.0 g N kg−1, 17.0–25.0 g K kg−1 and 2.0–2.5 g S kg−1, while leaf P, Ca and Mg concentrations were within the ranges of 2.6– 5.0 g P kg−1, 4.0–20.0 g Ca kg−1 and 3.0–10.0 g Mg kg−1 recommended as suitable for soybean crop (Malavolta et al. 1997; TPS 2013). Increase in lime rate increased leaf N, K, Mg, S, Mg and S concentrations by 39.2%, 10.2%, 35.5%, 27.2% and 19.7%, respectively, compared to the lower lime application. Fageria (2008) reported that in soils with higher acidity, the plants have visual symptoms of N deficiency, which was not observed in the present study. Among the genotypes, except for N and S, Intact RR2 technology (FPS Solar IPRO) soybean showed the highest leaf P, K, Ca and Mg concentrations compared to the genotypes with gene RR1 (Table 4). Regarding P, the lack of lime effect, this nutrient concentration on the leaves and increase in the soil exchangeable Ca2+ concentration was also reported by Key et al. (1962) and Moreira et al. (2015a). Increase in pH value from 3.9 to 4.3 and 3.9 to 5.3, respectively, with the low and high lime application (Table 2), was possibly not sufficient to change P Table 3. Grain yield (GY), number grain per pod (NGP), number of pods per pot (NPP), shoot dry weight yield (SDWY) and relative yield (RY) of 15 cultivars at 2 lime rates [low-base saturation of 40% (1.49 t ha−1 of lime) and high of 70% (2.73 t ha−1 of lime)] application.a Grain yield Grain per pod Number of pods SDWY (g pot−1) (n) (n) (g) RY Genotype Low High Low High Low High Low High (%) BMX Apolo RR 17.3a 20.2a 2a 2a 41b 43c 30.2c 40.2b 85.7 BMX Força RR 12.2b 16.1b 2a 2a 27c 53b 34.9b 62.1a 75.6 BMX Potência RR 19.1a 22.6a 2a 2a 51a 52b 42.8a 54.6b 84.8 BMX Turbo RR 13.4b 22.9a 2a 2a 30c 61b 28.7c 43.4c 58.8 BRS 294RR 14.7b 17.5b 2a 2a 61a 80a 48.4a 59.6a 84.0 BRS 295RR 13.3b 20.6a 2a 2a 59a 81a 36.7a 59.3a 64.5 BRS 359RR 17.1a 21.1a 2a 2a 49a 71a 41.1a 52.4b 81.1 BRS 360RR 10.9b 18.5b 2a 2a 36b 44c 38.5a 47.9b 58.7 NA 5909RR 18.2a 20.5a 2a 2a 50a 51b 38.8a 50.8b 88.8 NA 6262RR 14.5b 20.1a 2a 2a 39b 47c 30.2c 37.5c 72.1 FTS Solar IPRO 17.1a 19.8a 2a 2a 41b 72a 35.7b 48.4b 86.4 TMG 1066RR 18.0a 21.2a 2a 2a 44b 78a 45.1a 52.7b 85.1 TMG 7161RR 14.6b 21.2a 2a 2a 24c 55b 23.2c 38.4c 68.9 TMG 7262RR 15.7a 20.4a 2a 2a 35b 42c 34.8b 39.8c 76.8 Vmax RR 15.6a 21.0a 2a 2a 39b 78a 41.2a 55.8a 74.0 Mean 15.5B 20.3A 2A 2A 42B 52A 36.7B 49.5A 74.6 F test Genotype 4.799* 1.438NS 17.404* 14.279* Rates 127.646* 1.721NS 167.627* 185.125* Genotype × rates 2.696* 0.923NS 6.017* 2.456* CV (%) 11.29 9.49 14.11 10.39 *,NSSignificant at the 5% probability level and not significant, respectively. aValues followed by similar lowercase letters in the same column and uppercase letter in the same line within the same variables are not significantly different at p ≤ 0.05 by Scott–Knott test. Low-base saturation (V) = 40%. High-base saturation (V) = 70%. CV: Coefficient of variation. 1286 A. MOREIRA ET AL. uptake by the plants, and consequently, the leaf P concentration was not affected regardless of the genotypes. Potassium, Ca, Mg and S concentrations in soybean grain (SG) were significantly influenced by the genotypes, and K, Ca and S concentrations were influenced by lime rates, with genotypes × rates interaction reported only for Ca concentration (Table 5). Ca concentration in SG increased with the higher lime rate application (V = 70%) compared to the lower rate (V = 40%), and the opposite was observed for K and S. In turn, N, P andMg concentrations in the grainwere not affectedby the treatments. This result can be associated to nutrient mobility (Marschner 1995; Malavolta 2006) and to higher GY in response to increase in the lime rate applied (Table 5). Unlike the findings for leaf nutrients concentration, genotype variability was observed for each macronutrient concentration in soybean grain (Table 4). Regardless of the lime rate applied, macronutrient concentrations in soybean leaves across the genotypes were as follows N > K > P > Ca > Mg > S (Table 4), and in grain: N > K > P > Ca > S > Mg (Table 5). Higher N, P and K concentrations in soybean were also reported by Moreira et al. (2015b) in an experiment with the same type of soil and by Fageria et al. (2012) with common bean (Phaseolus vulgaris). Physiological components (A, gs, Ci, Trmmol and IWUE) Interaction genotypes × lime rates for photosynthesis rate (A), stomatal conductance (gs), respira- tory rate (Trmmol), IWUE, internal CO2 concentration (Ci) and chlorophyll content were not signifi- cant (Table 6) indicating that there was no differential response of genotypes to the different lime rates used. An independent significant response of genotypes and lime rate was observed for A, gs, Trmmol and chlorophyll content, while IWUE only differed among the genotypes and Ci did not respond significantly to the treatments (Table 6). Table 4. Macronutrients (N, P, K, Ca, Mg and S) concentration in leaves (3rd and 4th) of soybeans at R2 growth stage, depending on the two lime rates [low-base saturation of 40% (1.49 t ha−1 of lime) and high of 70% (2.73 t ha−1 of lime)] application.a N P K Ca Mg S (g kg−1) (g kg−1) (g kg−1) (g kg−1) (g kg−1) (g kg−1) Genotype Low High Low High Low High Low High Low High Low High BMX Apolo RR 18.9b 26.7a 4.8b 4.5b 13.3a 14.7a 6.4b 8.9b 3.5a 4.0b 1.3b 1.8a BMX Força RR 15.5b 22.8a 4.4b 5.7b 10.7b 11.8a 5.8b 8.2b 3.2a 3.8b 1.1b 1.2b BMX Potência RR 18.1b 29.2a 5.1a 4.6b 11.3b 15.0a 6.8a 5.6b 3.3a 4.3a 1.2b 1.3b BMX Turbo RR 24.2a 24.2a 5.8a 5.4a 13.9a 12.0a 6.9a 9.1b 3.4a 4.4a 2.3a 1.4b BRS 294RR 17.8b 21.6b 5.6a 4.8b 12.0b 14.2a 7.8a 8.9b 3.6a 4.3a 1.4b 1.4b BRS 295RR 15.5b 16.1b 5.8a 6.0a 14.9a 13.2a 5.4b 8.4b 3.2a 4.2a 1.2b 1.2b BRS 359RR 14.5b 24.2a 5.7a 4.9b 13.5a 12.9a 5.5b 7.5b 2.7a 3.7b 1.2b 1.3b BRS 360RR 15.0b 20.8b 4.1b 3.7b 12.3b 13.7a 5.8b 7.9b 2.3b 3.1c 1.1b 1.2b NA 5909RR 14.2b 23.7a 3.9b 4.1b 12.2b 12.4a 6.2b 7.5b 3.0b 3.7b 0.9b 1.3b NA 6262RR 14.6b 22.6a 5.3a 4.7b 12.2b 14.0a 5.8b 7.3b 2.9b 3.4c 1.2b 1.3b FTS Solar IPRO 17.2b 23.4a 5.9a 6.7a 14.7a 16.9a 8.0a 13.1a 3.8a 4.8a 1.2b 1.5a TMG 1066RR 18.2b 21.9b 4.3b 4.8b 11.5b 14.6a 5.5b 7.4b 2.8b 3.3c 1.1b 1.1b TMG 7161RR 14.3b 23.5a 4.8b 4.1b 13.9a 14.5a 4.6b 7.7b 2.8b 3.7b 1.2b 1.3b TMG 7262RR 21.6a 28.7a 4.6b 4.7b 10.7b 13.7a 5.4b 8.6b 3.1b 4.6a 1.1b 1.9a Vmax RR 15.5b 25.6a 4.4b 4.2b 12.3b 15.4a 5.8b 8.3b 2.9b 3.7b 1.2b 1.6a Mean 17.0B 23.7A 5.0A 4.9A 12.6B 13.9A 6.1B 8.3A 3.1B 3.9A 1.2B 1.4A F Test Genotype 2.296* 4.934* 3.768* 9.779* 11.263* 5.401* Rates 66.812* 1.382NS 11.347* 173.284* 169.537* 21.012* Genotype × rates 2.933* 0.625NS 1.646NS 1.923NS 1.271NS 5.284* CV (%) 17.58 16.89 13.45 11.71 8.63 15.34 *,NSSignificant at the 5% probability level and not significant, respectively. aValues followed by similar lowercase letters in the same column and uppercase letter in the same line within the same variables are not significantly different at p ≤ 0.05 by Scott–Knott test. Low-base saturation (V) = 40%. High-base saturation (V) = 70%. CV: Coefficient of variation. ARCHIVES OF AGRONOMY AND SOIL SCIENCE 1287 Photosynthesis rate varied from 6.93 μmol CO2 m−2 (TMG 7161RR) to 15.62 μmol CO2 m−2 (TMG 1066RR) at a lower lime rate (V = 40%) and 11.57 (BRS 295RR) to 21.15 μmol CO2 m−2 (TMG 7262RR) at a higher lime rate (V = 70%), with an average value of 12.92 μmol CO2 m −2 and general average increase of 35.5% of A when lime rate was increased. Regarding gs, Ci, Trmmol, IWUE and chlorophyll content, this range was 41.4, 1.3, 29.1, 4.9 and 17.3%, respectively (Table 6). For plants, the photosynthetic activity of leaves had increased significantly (ŷ = 11.366 + 0.502x, r = 0.51, p ≤ 0.05) with increase of lime application. According to Marschner (1995), Malavolta et al. (1997) and White and Broadley (2003), the use of a greater dolomite lime rate significantly increases the Ca and Mg concentration, nutrients that partici- pate directly or indirectly on photosynthetic activities, either in cell division and/or as enzyme activator via calmodulin protein, in the case of Ca, or as a constituent of chlorophyll molecule and ion uptake, in the case of Mg (Table 6). Roots functions can be altered by rhizosphere acidity. Production and translocation of such growth hormones as cytokinins possibly are affected by acidity (Tolley-Henry & Raper Junior 1986). Conclusion In Brazil, soybean culture is expanding in degraded pasture areas where soils have low clay content and high acidity. The selection of acid tolerant soybean genotypes is an effective strategy to yield costs reduce and yield increase. BMX Potencia RR had the greatest GY in soil with higher acidity. In this study, the genotypes showed different responses to the two lime rates. Increase in base saturation from 40 to 70% increased GY by 31.1%, raised pH, Ca2+, Mg2+ and soil CEC values and reduced K+, Al3+ and H+ + Al3+. In turn, yield and physiological components, NPP, shoot dry weight (SDW), photosynthesis (A), stomatal conductance (Ci), transpiration (Trmmol) and chlorophyll, increased significantly with the application of higher lime doses. Leaf macronutrient uptake was Table 5. Macronutrients (N, P, K, Ca, Mg and S) concentration in grain of soybeans, depending on the two lime rates [low-base saturation of 40% (1.49 t ha−1 of lime) and high of 70% (2.73 t ha−1 of lime)] application.a N P K Ca Mg S (g kg−1) (g kg−1) (g kg−1) (g kg−1) (g kg−1) (g kg−1) Genotype Low High Low High Low High Low High Low High Low High BMX Apolo RR 56.2a 55.1a 5.6a 5.7a 19.4a 18.5a 3.3a 4.5a 2.7a 2.9a 3.4a 3.3a BMX Força RR 54.1a 55.7a 6.2a 5.9a 19.9a 16.4b 3.3 3.0b 2.3b 2.3b 3.2a 2.4b BMX Potência RR 52.5a 53.9a 4.8a 5.5a 17.0b 17.2a 2.9b 3.1b 2.4b 2.4b 3.1a 2.3b BMX Turbo RR 53.0a 52.7a 5.9a 5.7a 19.2a 18.2a 2.6b 2.8b 2.3b 2.3b 3.3a 3.0a BRS 294RR 52.0a 55.8a 6.1a 5.5a 17.9b 16.6b 2.7b 3.4b 2.3b 2.2b 3.2a 2.2b BRS 295RR 52.5a 54.4a 6.6a 5.8a 18.8b 16.3b 3.7a 3.9a 2.3a 2.4b 2.8b 2.6b BRS 359RR 53.7a 56.9a 6.3a 6.4a 17.8b 17.7a 3.2a 2.7b 2.7a 2.6a 3.4a 2.8b BRS 360RR 51.1a 54.1a 6.4a 5.8a 18.3b 17.7a 3.7a 3.1b 2.7a 2.4b 3.2a 2.6b NA 5909RR 53.2a 53.0a 5.9a 5.8a 17.0b 15.7b 3.8a 4.1a 2.7a 2.7a 3.1a 2.8b NA 6262RR 51.8a 53.4a 5.9a 6.1a 19.0a 18.0a 3.5a 3.5a 2.6a 2.5b 2.9b 3.2a FTS Solar IPRO 49.9a 50.9a 6.5a 5.8a 19.4a 17.3a 3.3a 4.1a 2.6a 2.6a 3.3a 2.5b TMG 1066RR 48.5a 52.7a 5.3a 5.7a 18.0b 17.1a 2.7b 2.9b 2.4b 2.3b 3.0a 2.5b TMG 7161RR 48.8a 49.5a 6.9a 5.8a 20.5a 17.8a 3.4a 3.0b 2.8a 2.3b 3.4a 3.4a TMG 7262RR 51.1a 49.7a 5.4a 5.7a 18.6b 17.5a 2.8b 3.0b 2.5a 2.4b 3.4a 3.2a Vmax RR 54.6a 55.5a 5.8a 5.7a 17.8b 15.4b 3.5a 3.7a 2.7a 2.6a 3.1a 2.9b Mean 52.2A 53.6A 6.0A 5.8A 18.5A 17.2B 3.2B 3.4A 2.6A 2.5A 3.2A 2.8B F test Genotype 2.037NS 2.355NS 3.429* 5.805* 4.357* 2.154* Rates 3.518NS 2.536NS 35.140* 3.288* 2.263NS 20.229* Genotype × rates 0.371NS 1.244NS 1.342NS 1.871* 0.792NS 1.063NS CV (%) 6.46 9.15 6.06 12.55 7.46 1.361 *,NSSignificant at the 5% probability level and not significant, respectively. aValues followed by similar lowercase letters in the same column and uppercase letter in the same line within the same variables are not significantly different at p ≤ 0.05 by Scott Knott test. Low-base saturation (V) = 40%. High-base saturation (V) = 70%. CV: Coefficient of variation. 1288 A. MOREIRA ET AL. Ta bl e 6. Ph ys io lo gi ca lc om po ne nt s in so yb ea n w ith tw o lim e ra te s [lo w -b as e sa tu ra tio n of 40 % (1 .4 9 t ha − 1 of lim e) an d hi gh of 70 % (2 .7 3 t ha − 1 of lim e) ] ap pl ic at io n. a Li m e G en ot yp e A g s C i Tr m m ol IW U E Ch lo ro ph yl l (m g kg − 1 ) μ m ol CO 2 m − 2 m − 1 (m ol H 2O m − 2 s− 1 ) (μ m ol CO 2 m ol − 1 ) (m m ol H 2O m − 2 s− 1 ) (m m ol H 2O m − 2 s− 1 ) (m g m − 2 ) Lo w BM X Ap ol o RR 10 .8 1b 0. 25 b 28 4. 45 a 5. 72 b 2. 04 a 24 0. 13 a BM X Fo rç a RR 10 .4 9b 0. 27 b 29 1. 97 a 7. 14 b 1. 47 a 21 2. 76 b BM X Po tê nc ia RR 13 .4 5a 0. 29 b 27 8. 94 a 7. 25 b 1. 88 a 21 9. 93 b BM X Tu rb o RR 8. 47 b 0. 17 a 27 3. 02 a 5. 26 b 1. 62 a 20 1. 55 b BR S 29 4R R 12 .4 8a 0. 45 a 30 6. 57 a 9. 15 a 1. 38 a 20 6. 48 b BR S 29 5R R 11 .0 8b 0. 41 b 30 8. 47 a 8. 89 a 1. 37 a 20 6. 73 b BR S 35 9R R 9. 70 b 0. 22 a 28 7. 54 a 5. 79 b 1. 68 a 18 0. 08 b BR S 36 0R R 9. 93 b 0. 28 b 28 3. 76 a 7. 31 b 1. 46 a 19 5. 43 b N A 59 09 RR 8. 57 b 0. 23 a 29 9. 85 a 6. 19 b 1. 38 a 19 8. 46 b N A 62 62 RR 10 .0 0b 0. 23 a 26 2. 35 a 5. 50 b 2. 24 a 22 1. 13 b FT S So la r IP RO 10 .9 8b 0. 28 b 27 6. 53 a 6. 53 b 1. 71 a 21 3. 68 b TM G 10 66 RR 15 .6 2a 0. 34 b 27 2. 45 a 8. 55 a 1. 83 a 22 0. 62 b TM G 71 61 RR 6. 93 b 0. 26 b 26 9. 57 a 4. 78 b 1. 51 a 20 2. 18 b TM G 72 62 RR 14 .9 5a 0. 43 a 28 3. 30 a 9. 48 a 1. 58 a 24 8. 22 a V m ax RR 11 .1 6a 0. 32 b 29 6. 57 a 8. 84 a 1. 27 a 19 0. 50 b H ig h BM X Ap ol o RR 18 .3 5a 0. 77 a 29 2. 39 a 8. 09 b 2. 27 a 30 0. 88 a BM X Fo rç a RR 15 .5 8b 0. 58 b 29 7. 36 a 12 .0 4a 1. 29 a 24 3. 73 b BM X Po tê nc ia RR 16 .1 9b 0. 37 a 26 1. 95 a 7. 29 b 2. 41 a 28 7. 49 a BM X Tu rb o RR 13 .2 2b 0. 38 a 28 3. 01 a 7. 57 b 1. 74 a 23 7. 61 b BR S 29 4R R 12 .7 1b 0. 50 a 30 3. 77 a 11 .3 6a 1. 12 a 24 7. 96 b BR S 29 5R R 11 .5 7b 0. 34 a 29 7. 31 a 8. 77 b 1. 34 a 21 0. 84 b BR S 35 9R R 14 .2 6b 0. 39 a 28 3. 33 a 9. 89 b 1. 44 a 23 3. 13 b BR S 36 0R R 16 .0 1b 0. 38 a 27 3. 80 a 7. 40 b 2. 27 a 26 2. 87 a N A 59 09 RR 12 .9 2b 0. 42 a 29 7. 39 a 9. 89 b 1. 36 a 23 3. 82 b N A 62 62 RR 14 .1 5b 0. 38 a 28 6. 86 a 7. 89 b 1. 81 a 25 9. 71 a FT S So la r IP RO 12 .2 9b 0. 55 b 30 9. 47 a 11 .8 1a 1. 05 a 21 9. 93 b TM G 10 66 RR 15 .7 7b 0. 47 b 28 7. 66 a 8. 64 b 1. 83 a 22 3. 84 b TM G 71 61 RR 15 .1 9b 0. 40 a 28 7. 57 a 7. 89 b 1. 94 a 25 1. 18 b TM G 72 62 RR 21 .1 5a 0. 67 a 28 7. 57 a 9. 75 b 2. 18 a 27 3. 22 a V m ax RR 13 .6 6b 0. 41 b 28 0. 77 a 9. 14 b 1. 58 a 21 6. 58 b Lo w (V % = 40 ) 10 .9 7B 0. 29 B 28 5. 02 A 7. 09 B 1. 63 A 21 0. 52 B H ig h (V % = 70 ) 14 .8 7A 0. 41 A 28 8. 68 A 9. 16 A 1. 71 A 24 6. 85 A M ea n 12 .9 2 0. 35 28 6. 85 8. 13 1. 67 22 8. 69 F te st G en ot yp e 4. 43 5* 4. 28 3* 1. 58 5N S 2. 58 9* 3. 89 9* 4. 43 9* Ra te s 59 .8 77 * 21 .7 54 * 0. 73 5N S 25 .8 04 * 1. 04 7N S 56 .0 78 * G en ot yp e × ra te s 1. 77 4N S 0. 86 6N S 0. 79 8N S 1. 42 4N S 1. 74 9N S 1. 27 8N S CV (% ) 18 .4 7 26 .6 6 7. 06 23 .7 9 22 .6 6 10 .0 6 *S ig ni fi ca nt at 5% pr ob ab ili ty .N S N ot si gn ifi ca nt . a V al ue s fo llo w ed by si m ila r lo w er ca se le tt er s in th e sa m e co lu m n an d up pe rc as e le tt er in th e sa m e lin e w ith in th e sa m e va ria bl es ar e no t si gn ifi ca nt ly di ff er en t at p ≤ 0. 05 by Sc ot t– Kn ot t te st . Lo w -b as e sa tu ra tio n (V ) = 40 % .H ig h- ba se sa tu ra tio n (V ) = 70 % . CV : Co effi ci en t of va ria tio n; A: ph ot os yn th es is ra te ; g s : st om at al co nd uc ta nc e; C i : in te rc el lu la r CO 2 co nc en tr at io n; Tr m m ol : re sp ira to ry ra te ; IW U E: re la tiv e w at er us e effi ci en cy ; CV : co effi ci en t of va ria tio n. ARCHIVES OF AGRONOMY AND SOIL SCIENCE 1289 as follows: N > K > P > Ca > Mg > S, and in grain, it was N > K > P > Ca > S > Mg, with the highest levels of N, P, K and S reported in grain. Acknowledgments Authors would like to acknowledge Concita Campelo (CPAA) and Laboratory Santa Rita for laboratory analyses and the National Council for Scientific and Technological Development (CNPq) for the research productivity fellowship to the first author. Disclosure statement No potential conflict of interest was reported by the authors. Funding The project was funded by EMBRAPA(Empresa Brasileira de Pesquisa Agropecuária). References Allen SE, Terman GL, Clements LB. 1976. Greenhouse techniques for soil-plant fertilizer research. Muscle Shoals (AL): Tennessee Valley Authority. Cassel DK, Nielsen DR. 1986. Methods of soil analysis: physical and mineralogical methods. Madison (WI): America Society of Agronomy, Field capacity and available water capacity; p. 901–926. Castro GSA, Crusciol CAC. 2013. Effects of superficial liming and silicate application on soil fertility and crop yield under rotation. Geoderma. 195–196:234–242. CONAB (Companhia Nacional de Abastecimento). 2016. Acompanhamento da safra brasileira, 2015/2016 – Grãos. Brasília (Brazil): CONAB. Eckert DJ. 1987. Soil testing: sampling, correlation, calibration, and interpretation. Madison (WI): American Society of Agronomy, Soil test interpretations: Basic cation saturation ratios and sufficiency levels; p. 53–64. EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária). 1997. Manual for methods of soil analysis [Manual de Métodos de Análise de Solo]. Rio de Janeiro (Brazil): National Research Center for Soils. Fageria NK. 2008. Optimum soil acidity indices for dry bean production on an Oxisol in no-tillage system. Comm Soil Sci Plant Anal. 39:845–857. Fageria NK, Baligar VC. 2001. Improving nutrient use efficiency of annual crops in Brazilian acid soils for sustainable crop production. Comm Soil Sci Plant Anal. 32:1303–1319. Fageria NK, Baligar VC. 2008. Ameliorating soil acidity of tropical Oxisols by liming for sustainable crop production. Adv Agron. 99:345–399. Fageria NK, Morais OP. 1987. Evaluation of rice cultivars for utilization of calcium and magnesium in the Cerrado soil. Pesquisa Agropecuária Brasileira. 22:667–672. Fageria NK, Moreira A, Castro C, Moraes MF. 2013. Optimal acidity indices for soybean production in Brazilian Oxisols. Comm Soil Sci Plant Anal. 44:2941–2951. Fageria NK, Moreira A, Coelho AM. 2012. Nutrient uptake in dry bean genotypes. Comm Soil Sci Plant Anal. 43:2289– 2302. Fageria NK, Moreira A, Moraes LAC, Moraes MF. 2014. Influence of lime and gypsum on yield and yield components of soybean and changes in soil chemical properties. Comm Soil Sci Plant Anal. 45:271–283. Fehr WR, Caviness CE, Burmood DT, Pennington JS. 1971. Stage of development descriptions for soybeans, Glycine max (L.) Merrill1. Crop Sci. 11:929–931. Fritschi FB, Ray JD. 2007. Soybean leaf nitrogen, chlorophyll content, and chlorophyll a/b ratio. Photosynthetica. 45:92–98. Hicks CR. 1973. Fundamental concepts in the design of experiments. New York (EUA): Holt, Rinehart and Winston. Kamprath EJ. 1984. Soil acidity and liming. Madison (WI): American Society of Agronomy, Crop responses to lime on soils in the tropics; p. 349–368. Key JL, Kurtz LT, Tucker BB. 1962. Influence of ratio of exchangeable calcium-magnesium on yield and composition of soybeans and corn. Soil Sci. 93:265–270. Malavolta E. 2006. Manual of mineral nutrition of plants [Manual de Nutrição Mineral de Plantas]. Piracicaba (Brazil): Editora Ceres. 1290 A. MOREIRA ET AL. Malavolta E, Vitti GC, Oliveira SA. 1997. Evaluation of nutritional status of plants; principles and application [Avaliação do Estado Nutricional das Plantas; princípios e aplicações]. Piracicaba (Brazil): Associação Brasileira para Pesquisa da Potassa e do Fosfato. Marschner H. 1995. Mineral nutrition of higher plants. London (UK): Academic Press. Moreira A, Fageria NK. 2010. Liming influence on soil chemical properties, nutritional status and yield of alfalfa grown in acid soil. Revista Brasileira de Ciência do Solo. 34:1231–1239. Moreira A, Moraes LAC, Fageria NK. 2015b. Variability on yield, nutritional status, soil fertility, and potassium-use efficiency by soybean cultivar in acidic soil. Comm Soil Sci Plant Anal. 46:2490–2508. Moreira A, Sfredo GJ, Moraes LAC, Fageria NK. 2014. Agronomic efficiency of two lime and phosphate fertilizer sources in Brazilian Cerrado soils cultivated with soybean. Comm Soil Sci Plant Anal. 45:2319–2330. Moreira A, Sfredo GJ, Moraes LAC, Fageria NK. 2015a. Lime and cattle manure in soil fertility and soybean seed yield cultivated in tropical soil. Comm Soil Sci Plant Anal. 46:1157–1169. Scott AJ, Knott M. 1974. A cluster analysis method for grouping means in the analysis of variance. Biometrics. 30:507– 512. Soratto RP, Crusciol CAC. 2008. Chemical soil attributes as affected by lime and phosphogypsum surface application in a recently established no-tillage system. Revista Brasileira de Ciência do Solo. 32:675–688. Tolley-Henry L, Raper Junior CD. 1986. Utilization of aluminum as a nitrogen source. Plant Physiol. 82:54–60. TPS (Tecnologia de Produção de Soja). 2013. Technology of soybean yield in central region of Brazil. 2013 and 2014. Londrina (Brazil): Embrapa Soybean. White PJ, Broadley MR. 2003. Calcium in plants. Ann Botany. 92:487–511. ARCHIVES OF AGRONOMY AND SOIL SCIENCE 1291 Abstract Introduction Material and methods Site and soil characteristics Experimental design, fertilization and planting Harvest and laboratory analysis Statistical analyses Result and discussion Soil chemical properties GY and yield components Leaf and grain nutrient concentration Physiological components (A, gs, Ci, Trmmol and IWUE) Conclusion Acknowledgments Disclosure statement Funding References