Abstract
The objective of this work was to evaluate the grain yield potential of modern soybean (Glycine max) cultivars subjected to high- and low-input management levels on different sowing dates, in the southwestern region of the state of Paraná, Brazil. The experiment was carried out in the 2017/2018 and 2018/2019 crop seasons in the municipality of Itapejara D’Oeste. Five soybean cultivars (BMX Zeus IPRO, BMX Ativa RR, BMX Lança IPRO, NS 5445 IPRO, and NA 5909 RG) were evaluated in four environments formed by the combination of input management levels (high and low) and sowing dates (first and second). The experimental design was a randomized complete block with three replicates. The evaluated traits were: grain yield potential (kg ha-1), in the R5 phenological stage; and grain yield (kg ha-1) and its components, in the R8 stage. Cultivar, sowing date, and input management are determinant for maximizing grain yield potential. In the first sowing date, in October, the BMX Zeus IPRO cultivar shows a better response to the high level management, with a higher yield potential in the R5 stage (19,682 kg ha-1) and a higher grain yield (8,248 kg ha-1), whereas NA 5909 RG shows the best results with the low input management.
Index terms:
Glycine max
; grain yield; high performance management
Resumo
O objetivo deste trabalho foi avaliar o potencial de rendimento de grãos de cultivares de soja (Glycine max) modernas submetidas a níveis alto e baixo de manejo de insumos, em diferentes datas de semeadura, na região Sudoeste do Paraná, Brasil. O experimento foi realizado nas safras de 2017/2018 e 2018/2019, no município de Itapejara D’Oeste. Cinco cultivares de soja (BMX Zeus IPRO, BMX Ativa RR, BMX Lança IPRO, NS 5445 IPRO e NA 5909 RG) foram avaliadas em quatro ambientes formados pela combinação de nível de manejo de insumos (alto e baixo) e datas de semeadura (primeira e segunda). O delineamento experimental foi de blocos ao acaso, com três repetições. As características avaliadas foram: potencial de rendimento de grãos (kg ha-1), no estádio fenológico R5; e rendimento de grãos (kg ha-1) e seus componentes, no estádio R8. A cultivar, a época de semeadura e o manejo dos insumos são determinantes para a maximização do potencial produtivo dos grãos. Na primeira data de semeadura, em outubro, a cultivar BMX Zeus IPRO apresenta melhor resposta ao manejo de alto nível, com maior potencial produtivo no estádio R5 (19.682 kg ha-1) e maior produtividade de grãos (8.248 kg ha-1), enquanto NA 5909 RG apresenta os melhores resultados com baixo manejo de insumos.
Termos para indexação:
Glycine max
; rendimento de grãos; manejo de alto desempenho
Introduction
The growing international demand for commodities intensified during the Covid-19 pandemic, with price levels reaching new record highs (Borgards et al., 2021BORGARDS, O.; CZUDAJ, R.L.; VAN HOANG, T.H. Price overreactions in the commodity futures market: an intraday analysis of the Covid-19 pandemic impact. Resources Policy, v.71, art.101966, 2021. DOI: https://doi.org/10.1016/j.resourpol.2020.101966.
https://doi.org/10.1016/j.resourpol.2020...
). The Food and Agricultural Organization (FAO, 2017FAO. Food and Agriculture Organization of the United Nations. The future of food and agriculture: trends and challenges. Rome, 2017. 163 p .) forecasts that there will be an increase of 2.3 billion people in the global population by 2050 and, consequently, an increase of 34% in the demand for food, which requires expanding considerably the agricultural area, as well as increasing yield per area.
Among the most important crops for world agribusiness, soybean [Glycine max (L.) Merrill] is considered an excellent protein – the main one in animal feed – and oil source (Anderson et al., 2019ANDERSON, E.J.; ALI, M.L.; BEAVIS, W.D.; CHEN, P.; CLEMENTE, T.E.; DIERS, B.W.; GRAEF, G.L.; GRASSINI, P.; HYTEN, D.L.; MCHALE, L.K.; NELSON, R.L.; PARROTT, W.A.; PATIL, G.B.; STUPAR, R.M.; TILMON, K.J. Soybean [Glycine max (L.) Merr.] breeding: history, improvement, production and future opportunities. In: AL-KHAYRI, J.M.; JAIN, S.M.; JONHSON, D.V. (Ed.). Advances in plant breeding strategies: legumes. Cham: Springer, 2019. v.7, p.431-516. DOI: https://doi.org/10.1007/978-3-030-23400-3_12.
https://doi.org/10.1007/978-3-030-23400-...
). Currently, Brazil is the world’s leading soybean producer and exporter, followed by the United States and Argentina (USDA, 2022USDA. United States Department of Agriculture. World Agricultural Production. Washington, 2022. 39p. (USDA. Circular Series WA P 2-22).).
Worldwide, the average soybean grain yield per year is 2,880 kg ha-1, with the highest average yield per country obtained in the United States (3,350 kg ha-1), followed by Brazil (3,320 kg ha-1) (USDA, 2022USDA. United States Department of Agriculture. World Agricultural Production. Washington, 2022. 39p. (USDA. Circular Series WA P 2-22).). Despite this high average, soybean still has a high yield potential that is yet to be explored. In competitive audits, the Brazilian yield record was 8,945 kg ha-1, whereas the world record was 12,792 kg ha-1 in the United States (Iglesias, 2019IGLESIAS, R. Produtor americano bate recorde de produtividade de soja com 213,2 sc/ha. 2019. Available at: <https://www.grupocultivar.com.br/noticias/produtor-americano-bate-recorde-deprodutividade-de-soja-com-213-2-sc-ha>. Accessed on: June 19 2021.
https://www.grupocultivar.com.br/noticia...
; Cesb, 2020CESB. Comitê Estratégico Soja Brasil. 2020. Available at: <http://www.cesbrasil.org.br/>. Acessed on: July 20 2020.
http://www.cesbrasil.org.br/...
).
The expression of yield potential depends on the production environment, which must have an adequate nutrient availability, structured soil, high organic matter content, and water storage capacity (Mbuthia et al., 2015MBUTHIA, L.W.; ACOSTA-MARTÍNEZ, V.; DEBRUYN, J.; SCHAEFFER, S.; TYLER, D.; ODOI, E.; MPHESHEA, M.; WALKER, F.; EASH, N. Long term tillage, cover crop, and fertilization effects on microbial community structure, activity: implications for soil quality. Soil Biology and Biochemistry, v.89, p.24-34, 2015. DOI: https://doi.org/10.1016/j.soilbio.2015.06.016.
https://doi.org/10.1016/j.soilbio.2015.0...
; Calonego et al., 2017CALONEGO, J.C.; RAPHAEL, J.P.A.; RIGON, J.P.G.; OLIVEIRA NETO, L. de; ROSOLEM, C.A. Soil compaction management and soybean yields with cover crops under no-till and occasional chiseling. European Journal of Agronomy, v.85, p.31-37, 2017. DOI: https://doi.org/10.1016/j.eja.2017.02.001.
https://doi.org/10.1016/j.eja.2017.02.00...
). In addition to the production environment, other important factors are the choice of adapted and responsive cultivars (Felici et al., 2019FELICI, P.H.N.; HAMAWAKI, O.T.; NOGUEIRA, A.P.O.; JORGE, G.L.; HAMAWAKI, R.L.; HAMAWAKI, C.D.L. Adaptability and stability of conventional early maturity soybeans in 15 different environments in Brazil. Genetics and Molecular Research, v.18 , gmr18169, 2019. DOI: https://doi.org/10.4238/gmr18169.
https://doi.org/10.4238/gmr18169...
), the right sowing date (Rattalino Edreira et al., 2017RATTALINO EDREIRA, J.I.; MOURTZINIS, S.; CONLEY, S.P.; ROTH, A.C.; CIAMPITTI, I.A.; LICHT, M.A.; KANDEL, H.; KYVERYGA, P.M.; LINDSEY, L.E.; MUELLER, D.S.; NAEVE, S.L.; NAFZIGER, E.; SPECHT, J.E.; STANLEY, J.; STATON, M.J.; GRASSINI, P. Assessing causes of yield gaps in agricultural areas with diversity in climate and soils. Agricultural and Forest Meteorology, v.247, p.170-180, 2017. DOI: https://doi.org/10.1016/j.agrformet.2017.07.010.
https://doi.org/10.1016/j.agrformet.2017...
; Nóia Júnior & Sentelhas, 2020NÓIA JÚNIOR, R. de S.; SENTELHAS, P.C. Yield gap of the double-crop system of main-season soybean with off-season maize in Brazil. Crop & Pasture Science, v.71, p.445-458, 2020. DOI: https://doi.org/10.1071/CP19372.
https://doi.org/10.1071/CP19372...
), available nutrients (Fontana et al., 2021FONTANA, M.B.; NOVELLI, L.E.; STERREN, M.A.; UHRICH, W.G.; BENINTENDE, S.M.; BARBAGELATA, P.A. Long-term fertilizer application and cover crops improve soil quality and soybean yield in the Northeastern Pampas region of Argentina. Geoderma, v.385, art.114902, 2021. DOI: https://doi.org/10.1016/j.geoderma.2020.114902.
https://doi.org/10.1016/j.geoderma.2020....
), and pest management (Bandara et al., 2020BANDARA, A.Y.; WEERASOORIYA, D.K.; BRADLEY, C.A.; ALLEN, T.W.; ESKER, P.D. Dissecting the economic impact of soybean diseases in the United States over two decades. PLoS ONE, v.15, e0231141, 2020. DOI: https://doi.org/10.1371/journal.pone.0231141.
https://doi.org/10.1371/journal.pone.023...
; Roth et al., 2020ROTH, M.G.; WEBSTER, R.W.; MUELLER, D.S.; CHILVERS, M.I.; FASKE, T.R.; MATHEW, F.M.; BRADLEY, C.A.; DAMICONE, J.P.; KABBAGE, M.; SMITH, D.L. Integrated management of important soybean pathogens of the United States in changing climate. Journal of Integrated Pest Management, v.11, p.1-28, 2020. DOI: https://doi.org/10.1093/jipm/pmaa013.
https://doi.org/10.1093/jipm/pmaa013...
).
According to the cultivar protection law of April 25, 1997 (Brasil, 1997BRASIL. Lei nº 9.456, de 25 de abril de 1997. Institui a Lei de Proteção de Cultivares e dá outras providências. 1997. Available at: <http://www.planalto.gov.br/ccivil_03/leis/l9456.htm>. Accessed on: Jun. 19 2021.
http://www.planalto.gov.br/ccivil_03/lei...
), a large number of cultivars with a high productive potential were released in Brazil. Therefore, it is necessary to evaluate the grain yield potential of these recent cultivars, in order to define management strategies and investment levels that would result in economic profitability.
The objective of this work was to evaluate the grain yield potential of modern soybean cultivars subjected to high- and low-input management levels on different sowing dates, in the southwestern region of the state of Paraná, Brazil.
Materials and Methods
Field trials were conducted in the 2017/2018 and 2018/2019 crop seasons, on two sowing dates, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil (25º97'S, 52º82'W, at an average altitude of 632 m). The average daily temperature during the soybean crop cycle was 22.5°C, and the accumulated precipitation was 1,154.6 and 1,196.4 mm for each crop season (Figure 1). The soil of the region is classified as a Latossolo Vermelho distrófico, according to the to the Brazilian soil classification system (Santos et al., 2018SANTOS, H.G. dos; JACOMINE, P.K.T.; ANJOS, L.H.C. dos; OLIVEIRA, V.Á. de; LUMBRERAS, J.F.; COELHO, M.R.; ALMEIDA, J.A. de; ARAÚJO FILHO, J.C. de; OLIVEIRA, J.B. de; CUNHA, T.J.F. Sistema brasileiro de classificação de solos. 5. ed. rev. e ampl. Brasilia: Embrapa, 2018. 356p.), corresponding to a Hapludox. The physicochemical soil analysis showed: 4.9 pH (CaCl2), 28.05 g dm-3 organic matter (wet combustion), 7.21 mg dm-3 P ( Mehlich-1) , 0.08 cmolc dm-3 K, cation exchange capacity of 11 cmolc dm-3, base saturation of 63.92%, 550 g kg-1 clay, 260 g kg-1 silt, and 190 g kg-1 sand. The experimental area has been cultivated under a no-tillage system for over 20 years.
Meteorological data for daily average temperature, daily precipitation, and solar radiation in the 2017/2018 and 2018/2019 soybean (Glycine max) crop seasons, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil. Source: Simepar (2022)SIMEPAR. Sistema de Tecnologia e Monitoramento Ambiental do Paraná. Available at: <http://www.simepar.br/prognozweb/simepar/dados_estacoes/25264916>. Accessed on: June 27 2022.
http://www.simepar.br/prognozweb/simepar... , Code ANA: 2652042.
Five soybean cultivars (BMX Zeus IPRO registered as 55I57RSF IPRO, BMX Ativa RR, BMX Lança IPRO registered as 58I60RSF IPRO, NS 5445 IPRO, and NA 5909 RG) were evaluated in four different environments (E1 to E4), formed by combinations of the first or second sowing date with high or low input management. The environments were: E1, high input and first sowing date on October 10; E2, low input and first sowing date on October 10; E3, high input and second sowing date on November 10; and E4, low input and second sowing date on November 10. The experimental design was a randomized complete block with three replicates. Each plot consisted of four lines of soybean (5.0 m long and spaced at 0.45 m), and planting density was adjusted according to the recommendations for each cultivar.
In the high input management treatment, millet [Pennisetum americanum (L.) Leeke] was cultivated in the experimental area before the soybean crop during summer, and black oat (Avena strigosa Schreb.) was planted immediately after in winter. Soybean was seeded manually, and a drip irrigation system was used for each line, spaced at 0.2 m. Ten tensiometers were installed at specific points to monitor soil water potential, aiming to keep soil moisture close to field capacity. All crops were cultivated using a mineral fertilizer to facilitate high yields. Base fertilization consisted of 350 kg ha-1 mineral fertilizer, containing 7.0% nitrogen, 36% phosphorus oxide, 10% potassium oxide, 1.2% calcium, 7.0% sulfur, 0.08% boron, 0.08% copper, 0.16% manganese, and 0.16% zinc. In addition, a topdressing fertilization with 250 kg ha-1 KCl was applied in the V4 phenological stage. In the low input treatment, the area was kept fallow in autumn, followed by the cultivation of black oat without fertilization, as usually practiced in the region. Soybean was also seeded manually, but no irrigation system was used. Base fertilization consisted of 350 kg ha-1 mineral fertilizer, containing 2.0% N, 20% P2O5, and 20% K2O. The agricultural production inputs that were used in the high- and low-input management levels are described in Table 1.
Description of high- and low-input level managements for five soybean (Glycine max) cultivars – BMX Zeus IPRO, BMX Ativa RR, BMX Lança IPRO, NS 5445 IPRO, and NA 5909 RG – evaluated during the 2017/2018 and 2018/2019 crop seasons in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil.
Grain yield potential (kg ha-1) was estimated according to methodology adapted from Maehler et al. (2003)MAEHLER, A.R.; PIRES, J.L.F.; COSTA, J.A.; FERREIRA, F.G. Potencial de rendimento da soja durante a ontogenia em razão da irrigação e arranjo de plantas. Pesquisa Agropecuária Brasileira, v.38, p.225-231, 2003. DOI: https://doi.org/10.1590/S0100-204X2003000200009.
https://doi.org/10.1590/S0100-204X200300...
and Rambo et al. (2004)RAMBO, L.; COSTA, J.A.; PIRES, J.L.F.; PARCIANELLO, G.; FERREIRA, F.G. Estimativa do potencial de rendimento por estrato do dossel da soja, em diferentes arranjos de plantas. Ciência Rural, v.34, p.33-40, 2004. DOI: https://doi.org/10.1590/S0103-84782004000100006.
https://doi.org/10.1590/S0103-8478200400...
. In each plot, five plants were identified and the number of reproductive structures in the R5 stage was counted (Fehr & Caviness, 1977FEHR, W.R.; CAVINESS, C.E. Stages of soybean development. Ames: Iowa State University, 1977. 11p. (Special report, 80).). At the R8 maturity stage, these plants were harvested and evaluated for number of grains per pod (NGP) and weight of a thousand grains (TGW, g). From the obtained data, grain yield potential (YP) was estimated using the following equation: YP = (NER × NGP × TGW × NP / 1000), where NER is the number of reproductive structures (flowers and pods) quantified at R5, NGP is the average number of grains per pod measured at R8, TGW is the weight of a thousand grains quantified at R8, and NP is the final stand of plants per hectare.
To determine grain yield (kg ha-1), the two central lines of each plot were harvested manually. After the plants were threshed, grain weight was converted to kg ha-1 and expressed at a moisture content of 13%. The TGW was obtained by multiplying the weight of eight replicates of 100 seeds per plot by a factor of ten (Brasil, 2009BRASIL. Secretaria de Defesa Agropecuária. Regras para análise de sementes. Brasília: Mapa/ACS, 2009.). The following measurements were taken for the five plants identified in each plot: plant height (cm); and number of pods per plant (NPP), calculated by multiplying the NGP by NPP.
Data were subjected to the analysis of homogeneity of variance and normality of residuals using the Bartlett and Lilliefors tests, respectively. A joint analysis of variance was performed in a factorial arrangement, taking into account environment × cultivar factors in each crop season. Tukey’s test was used to verify if the means differed significantly at 5% probability. Statistical analyses were carried out using the ExpDes. pt package (Ferreira al., 2018FERREIRA, E.B.; CAVALCANTI, P.P.; NOGUEIRA, D.A. Package ‘ExpDes.pt’. version 1.2.0. 2018.) in the R software (R Development Core Team, 2019R DEVELOPMENT CORE TEAM. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2019.).
Results and Discussion
The analysis of variance showed a significant cultivar × environment interaction for yield potential and plant height in the 2017/2018 crop season, as well as for grain yield, TGW, and plant height in 2018/2019 (Table 2). However, in both crop seasons, all evaluated traits were significantly affected by cultivar and environment. Furthermore, in 2017/2018, E1 resulted in the highest grain yield, with an average of 7,141 kg ha-1, whereas, in 2018/2019, E1, E2, and E3 showed grain yields higher than the average (Table 3).
Summary of the analysis of variance for agronomic traits of five soybean (Glycine max) cultivars grown under different environments (combination of first or second sowing dates and high or low input levels) during the 2017/2018 and 2018/2019 crop seasons, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil.
Grain yield potential and grain yield of five soybean (Glycine max) cultivars evaluated in four environments in the 2017/2018 and 2018/2019 crop seasons, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil(1).
Yield potential did not differ significantly between environments for cultivars BMX Ativa RR and BMX Lança IPRO in the 2017/2018 crop season (Table 3).
In both crop seasons, however, a lower mean yield potential was observed in the second sowing date, i.e., in E3 and E4, both with a mean of 7,087 kg ha-1, compared with the first sowing date, that is, with E1 and E2, with means of 15,471 and 14,524 kg ha-1, respectively. Sowing date is an important factor for the success of a crop due to the differences in water relations, as well as in temperature, photoperiod, and solar radiation availability (Zanon et al., 2015ZANON, A.J.; WINCK, J.E.M.; STRECK, N.A.; ROCHA, T.S.M. da; CERA, J.C.; RICHTER, G.L.; LAGO, I.; SANTOS, P.M. dos; MACIEL, L. da R.; GUEDES, J.V.C.; MARCHESAN, E. Desenvolvimento de cultivares de soja em função do grupo de maturação e tipo de crescimento em terras altas e terras baixas. Bragantia, v.74, p.400-411, 2015. DOI: https://doi.org/10.1590/1678-4499.0043.
https://doi.org/10.1590/1678-4499.0043...
; Nóia Júnior & Sentelhas, 2020NÓIA JÚNIOR, R. de S.; SENTELHAS, P.C. Yield gap of the double-crop system of main-season soybean with off-season maize in Brazil. Crop & Pasture Science, v.71, p.445-458, 2020. DOI: https://doi.org/10.1071/CP19372.
https://doi.org/10.1071/CP19372...
). In the western region of the state of Santa Catarina, Brazil, Meotti et al. (2012)MEOTTI, G.V.; BENIN, G.; SILVA, R.R.; BECHE, E.; MUNARO, L.B. Épocas de semeadura e desempenho agronômico de cultivares de soja. Pesquisa Agropecuária Brasileira, v.47, p.14-21, 2012. DOI: https://doi.org/10.1590/S0100-204X2012000100003.
https://doi.org/10.1590/S0100-204X201200...
also observed that later sowing dates negatively affected the performance of adaptive characters and the grain yield of the evaluated cultivars. Therefore, sowing at an ideal time can be an effective way to reach a grain yield near the maximum yield potential of soybean.
Cultivar BMX Zeus IPRO showed a higher yield potential in E1 in the first crop season and a high mean grain yield in the same environment in 2017/2018 and 2018/2019 (Table 3), with an increase of 9.5%, on average, in grain yield in the high input management. Cultivar BMX Ativa RR showed a similar average grain yield and yield potential in both crop seasons. The NA 5909 RG cultivar showed good performance as to yield potential in E2 in the 2017/2018 and 2018/2019 crop seasons. Moreover, among the studied cultivars, there was an increase in the conversion rate of yield potential to grain yield of ~62 and ~72% in each crop season. Therefore, when yield potential and grain yield are related, the mean conversion rate is 47% in both crop seasons.
The highest yield potential was obtained with the high-level input management in E1 (Table 3). Grain yield increased in 9.5% from the low (E2 and E4) to the high (E1 and E3) input management, which showed a mean grain yield of 5,567 and 6,096 kg ha-1, respectively. However, the response of the crops to the different technological levels of management depends on the growing region. Orlowski et al. (2016)ORLOWSKI, J.M.; HAVERKAMP, B.J.; LAURENZ, R.G.; MAR BURGER, D.A.; WILSON, E.W.; CASTEEL, S.N.; CONLEY, S.P.; NAEVE, S.L.; NAFZIGER, E.D.; ROOZEBOOM, K.L.; ROSS, W.J.; THELEN, K.D.; LEE, C.D. High-input management systems effect on soybean seed yield, yield components, and economic break-even probabilities. Crop Science, v.56, p.1988-2004, 2016. DOI: https://doi.org/10.2135/cropsci2015.10.0620.
https://doi.org/10.2135/cropsci2015.10.0...
, for example, when using high input management, observed that, from the Southern to the Northern region of the United States, there was an increase of 12% in yield.
In the 2017/2018 crop season, plant height was higher in the first sowing date (E1 and E2) for all cultivars (Table 4). This could be explained by the fact that the second sowing date (E3 and E4) occurred when days were shorter, a period when photoperiodsensitive soybean cultivars show reduced height, early flowering, and reduced yield (Han et al., 2006HAN, T.; WU, C.; TONG, Z.; MENTREDDY, R.S.; TAN, K.; GAI, J. Postflowering photoperiod regulates vegetative growth and reproductive development of soybean. Environmental and Experimental Botany, v.55, p.120-129, 2006. DOI: 10.1016/j.envexpbot.2004.10.006.
https://doi.org/10.1016/j.envexpbot.2004...
). In this crop season, the highest plant heights were obtained for: cultivar NA 5909 RG in E1 and E4; cultivars NA 5909 RG, NS5445 IPRO, and BMX Lança IPRO in E2; and cultivars NA 5909 RG and BMX Lança IPRO in E3. In the 2018/2019 crop season, plant height was higher in E1 and E3, both with a high input management, compared with E2, with a low input management.
Plant height and weight of a thousand grains (TGW) of five soybean (Glycine max) cultivars evaluated in four environments in the 2017/2018 and 2018/2019 crop seasons, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil(1).
In the 2017/2018 crop season, a greater TGW was observed for cultivars NS 5445 IPRO and BMX Zeus IPRO (Table 5). In 2018/2019, the values obtained were greater for cultivar BMX Zeus IPRO in E1 and E3 (Table 4) and lower for NA 5909 RG in E1 and E3 (high input) and for BMX Lança IPRO in E2 and E4 (low input). According to Orlowski et al. (2016)ORLOWSKI, J.M.; HAVERKAMP, B.J.; LAURENZ, R.G.; MAR BURGER, D.A.; WILSON, E.W.; CASTEEL, S.N.; CONLEY, S.P.; NAEVE, S.L.; NAFZIGER, E.D.; ROOZEBOOM, K.L.; ROSS, W.J.; THELEN, K.D.; LEE, C.D. High-input management systems effect on soybean seed yield, yield components, and economic break-even probabilities. Crop Science, v.56, p.1988-2004, 2016. DOI: https://doi.org/10.2135/cropsci2015.10.0620.
https://doi.org/10.2135/cropsci2015.10.0...
, high input management usually promotes the greatest TGW, as observed in the present study.
Mean number of pods per plant (NPP) and weight of a thousand grains (TGW) of five soybean (Glycine max) cultivars evaluated in four environments in the 2017/2018 and 2018/2019 crop seasons, in the municipality of Itapejara D’Oeste, in the state of Paraná, Brazil.
Cultivar NA 5909 RG had the highest NPP, followed by BMX Lança IPRO, in the 2017/2018 crop season (Table 5). However, the NA 5909 RG and BMX Lança IPRO cultivars showed the highest NPP, followed by BMX Zeus IPRO, in 2018/2019. Regarding environments, E1 and E2 (first sowing date) showed higher NPP in both crop seasons. These results agree with those of Zanon et al. (2015)ZANON, A.J.; WINCK, J.E.M.; STRECK, N.A.; ROCHA, T.S.M. da; CERA, J.C.; RICHTER, G.L.; LAGO, I.; SANTOS, P.M. dos; MACIEL, L. da R.; GUEDES, J.V.C.; MARCHESAN, E. Desenvolvimento de cultivares de soja em função do grupo de maturação e tipo de crescimento em terras altas e terras baixas. Bragantia, v.74, p.400-411, 2015. DOI: https://doi.org/10.1590/1678-4499.0043.
https://doi.org/10.1590/1678-4499.0043...
, who found more pods in plants planted at an earlier sowing date, which is considered better for soybean development due to photoperiod and temperature effects.
The results obtained in the present study and in the literature (Orlowski et al., 2016ORLOWSKI, J.M.; HAVERKAMP, B.J.; LAURENZ, R.G.; MAR BURGER, D.A.; WILSON, E.W.; CASTEEL, S.N.; CONLEY, S.P.; NAEVE, S.L.; NAFZIGER, E.D.; ROOZEBOOM, K.L.; ROSS, W.J.; THELEN, K.D.; LEE, C.D. High-input management systems effect on soybean seed yield, yield components, and economic break-even probabilities. Crop Science, v.56, p.1988-2004, 2016. DOI: https://doi.org/10.2135/cropsci2015.10.0620.
https://doi.org/10.2135/cropsci2015.10.0...
; Santos et al., 2021SANTOS, T.G.; BATTISTI, R.; CASAROLI, D.; ALVES JR, J.; EVANGELISTA, A.W.P. Assessment of agricultural efficiency and yield gap for soybean in the Brazilian Central Cerrado biome. Bragantia, v.80, e1821, 2021. DOI: https://doi.org/10.1590/1678-4499.20200352.
https://doi.org/10.1590/1678-4499.202003...
) are indicative that high-input crop management – with an increased application of fertilizers and chemicals – has positive effects on grain yield; however, it may compromise economic sustainability, which was not assessed here. In this context, high input systems must be implemented in stages, starting by improving soil physicochemical characteristics and analyzing annually if it is necessary to invest in specific applications (Quinn & Steinke, 2019QUINN, D.; STEINKE, K. Soft red and white winter wheat response to inputintensive management. Agronomy Journal, v. 111 , p.428-439, 2019. DOI: https://doi.org/10.2134/agronj2018.06.0368.
https://doi.org/10.2134/agronj2018.06.03...
). Greer et al. (2020)GREER, K.; MARTINS, C.; WHITE, M.; PITTELKOW, C.M. Assessment of high-input soybean management in the US Midwest: balancing crop production with environmental performance. Agriculture, Ecosystems & Environment, v.292, art.106811, 2020. DOI: https://doi.org/10.1016/j.agee.2019.106811.
https://doi.org/10.1016/j.agee.2019.1068...
evaluated the impact of input level on sustainability and economy during three years in the United States and found that, in two seasons, the high input level showed results superior to those of the low- and standard-input managements. In their economic analysis, the authors observed a greater return when associating the high input level with high commodity prices. Therefore, before using a high input management, environmental and economic sustainability should be considered.
In the present study, the expression of maximum potential yield depended on the interaction between genetic, environmental, and crop management factors. A high input environment maximizes grain yield and increases the conversion rate of potential yield to grain yield. Therefore, choosing an adequate sowing date and prioritizing the period of greatest radiation and temperature are important for obtaining a better result. To reduce losses in soybean potential yield, in future studies, there is also a need to improve management factors such as plant architecture, soil fertility, seed quality, plant standard, disease control, and insect resistance, among others.
Conclusions
Cultivar, sowing date, and input management are determinant for maximizing soybean (Glycine max) grain yield potential.
In the first sowing date, in October, cultivar BMX Zeus IPRO shows the best response, as well as a greater yield potential and grain yield in the high input management, whereas NA 5909 RG presents the best performance in the low input management.
Acknowledgments
To Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), for financial support (Finance Code 001).
References
- ANDERSON, E.J.; ALI, M.L.; BEAVIS, W.D.; CHEN, P.; CLEMENTE, T.E.; DIERS, B.W.; GRAEF, G.L.; GRASSINI, P.; HYTEN, D.L.; MCHALE, L.K.; NELSON, R.L.; PARROTT, W.A.; PATIL, G.B.; STUPAR, R.M.; TILMON, K.J. Soybean [Glycine max (L.) Merr.] breeding: history, improvement, production and future opportunities. In: AL-KHAYRI, J.M.; JAIN, S.M.; JONHSON, D.V. (Ed.). Advances in plant breeding strategies: legumes. Cham: Springer, 2019. v.7, p.431-516. DOI: https://doi.org/10.1007/978-3-030-23400-3_12
» https://doi.org/10.1007/978-3-030-23400-3_12 - BANDARA, A.Y.; WEERASOORIYA, D.K.; BRADLEY, C.A.; ALLEN, T.W.; ESKER, P.D. Dissecting the economic impact of soybean diseases in the United States over two decades. PLoS ONE, v.15, e0231141, 2020. DOI: https://doi.org/10.1371/journal.pone.0231141
» https://doi.org/10.1371/journal.pone.0231141 - BORGARDS, O.; CZUDAJ, R.L.; VAN HOANG, T.H. Price overreactions in the commodity futures market: an intraday analysis of the Covid-19 pandemic impact. Resources Policy, v.71, art.101966, 2021. DOI: https://doi.org/10.1016/j.resourpol.2020.101966
» https://doi.org/10.1016/j.resourpol.2020.101966 - BRASIL. Lei nº 9.456, de 25 de abril de 1997 Institui a Lei de Proteção de Cultivares e dá outras providências. 1997. Available at: <http://www.planalto.gov.br/ccivil_03/leis/l9456.htm>. Accessed on: Jun. 19 2021.
» http://www.planalto.gov.br/ccivil_03/leis/l9456.htm - BRASIL. Secretaria de Defesa Agropecuária. Regras para análise de sementes Brasília: Mapa/ACS, 2009.
- CALONEGO, J.C.; RAPHAEL, J.P.A.; RIGON, J.P.G.; OLIVEIRA NETO, L. de; ROSOLEM, C.A. Soil compaction management and soybean yields with cover crops under no-till and occasional chiseling. European Journal of Agronomy, v.85, p.31-37, 2017. DOI: https://doi.org/10.1016/j.eja.2017.02.001
» https://doi.org/10.1016/j.eja.2017.02.001 - CESB. Comitê Estratégico Soja Brasil 2020. Available at: <http://www.cesbrasil.org.br/>. Acessed on: July 20 2020.
» http://www.cesbrasil.org.br/ - FAO. Food and Agriculture Organization of the United Nations. The future of food and agriculture: trends and challenges. Rome, 2017. 163 p .
- FEHR, W.R.; CAVINESS, C.E. Stages of soybean development Ames: Iowa State University, 1977. 11p. (Special report, 80).
- FELICI, P.H.N.; HAMAWAKI, O.T.; NOGUEIRA, A.P.O.; JORGE, G.L.; HAMAWAKI, R.L.; HAMAWAKI, C.D.L. Adaptability and stability of conventional early maturity soybeans in 15 different environments in Brazil. Genetics and Molecular Research, v.18 , gmr18169, 2019. DOI: https://doi.org/10.4238/gmr18169
» https://doi.org/10.4238/gmr18169 - FERREIRA, E.B.; CAVALCANTI, P.P.; NOGUEIRA, D.A. Package ‘ExpDes.pt’ version 1.2.0. 2018.
- FONTANA, M.B.; NOVELLI, L.E.; STERREN, M.A.; UHRICH, W.G.; BENINTENDE, S.M.; BARBAGELATA, P.A. Long-term fertilizer application and cover crops improve soil quality and soybean yield in the Northeastern Pampas region of Argentina. Geoderma, v.385, art.114902, 2021. DOI: https://doi.org/10.1016/j.geoderma.2020.114902
» https://doi.org/10.1016/j.geoderma.2020.114902 - GREER, K.; MARTINS, C.; WHITE, M.; PITTELKOW, C.M. Assessment of high-input soybean management in the US Midwest: balancing crop production with environmental performance. Agriculture, Ecosystems & Environment, v.292, art.106811, 2020. DOI: https://doi.org/10.1016/j.agee.2019.106811
» https://doi.org/10.1016/j.agee.2019.106811 - HAN, T.; WU, C.; TONG, Z.; MENTREDDY, R.S.; TAN, K.; GAI, J. Postflowering photoperiod regulates vegetative growth and reproductive development of soybean. Environmental and Experimental Botany, v.55, p.120-129, 2006. DOI: 10.1016/j.envexpbot.2004.10.006.
» https://doi.org/10.1016/j.envexpbot.2004.10.006 - IGLESIAS, R. Produtor americano bate recorde de produtividade de soja com 213,2 sc/ha 2019. Available at: <https://www.grupocultivar.com.br/noticias/produtor-americano-bate-recorde-deprodutividade-de-soja-com-213-2-sc-ha>. Accessed on: June 19 2021.
» https://www.grupocultivar.com.br/noticias/produtor-americano-bate-recorde-deprodutividade-de-soja-com-213-2-sc-ha - MAEHLER, A.R.; PIRES, J.L.F.; COSTA, J.A.; FERREIRA, F.G. Potencial de rendimento da soja durante a ontogenia em razão da irrigação e arranjo de plantas. Pesquisa Agropecuária Brasileira, v.38, p.225-231, 2003. DOI: https://doi.org/10.1590/S0100-204X2003000200009
» https://doi.org/10.1590/S0100-204X2003000200009 - MBUTHIA, L.W.; ACOSTA-MARTÍNEZ, V.; DEBRUYN, J.; SCHAEFFER, S.; TYLER, D.; ODOI, E.; MPHESHEA, M.; WALKER, F.; EASH, N. Long term tillage, cover crop, and fertilization effects on microbial community structure, activity: implications for soil quality. Soil Biology and Biochemistry, v.89, p.24-34, 2015. DOI: https://doi.org/10.1016/j.soilbio.2015.06.016
» https://doi.org/10.1016/j.soilbio.2015.06.016 - MEOTTI, G.V.; BENIN, G.; SILVA, R.R.; BECHE, E.; MUNARO, L.B. Épocas de semeadura e desempenho agronômico de cultivares de soja. Pesquisa Agropecuária Brasileira, v.47, p.14-21, 2012. DOI: https://doi.org/10.1590/S0100-204X2012000100003
» https://doi.org/10.1590/S0100-204X2012000100003 - NÓIA JÚNIOR, R. de S.; SENTELHAS, P.C. Yield gap of the double-crop system of main-season soybean with off-season maize in Brazil. Crop & Pasture Science, v.71, p.445-458, 2020. DOI: https://doi.org/10.1071/CP19372
» https://doi.org/10.1071/CP19372 - ORLOWSKI, J.M.; HAVERKAMP, B.J.; LAURENZ, R.G.; MAR BURGER, D.A.; WILSON, E.W.; CASTEEL, S.N.; CONLEY, S.P.; NAEVE, S.L.; NAFZIGER, E.D.; ROOZEBOOM, K.L.; ROSS, W.J.; THELEN, K.D.; LEE, C.D. High-input management systems effect on soybean seed yield, yield components, and economic break-even probabilities. Crop Science, v.56, p.1988-2004, 2016. DOI: https://doi.org/10.2135/cropsci2015.10.0620
» https://doi.org/10.2135/cropsci2015.10.0620 - QUINN, D.; STEINKE, K. Soft red and white winter wheat response to inputintensive management. Agronomy Journal, v. 111 , p.428-439, 2019. DOI: https://doi.org/10.2134/agronj2018.06.0368
» https://doi.org/10.2134/agronj2018.06.0368 - R DEVELOPMENT CORE TEAM. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, 2019.
- RAMBO, L.; COSTA, J.A.; PIRES, J.L.F.; PARCIANELLO, G.; FERREIRA, F.G. Estimativa do potencial de rendimento por estrato do dossel da soja, em diferentes arranjos de plantas. Ciência Rural, v.34, p.33-40, 2004. DOI: https://doi.org/10.1590/S0103-84782004000100006
» https://doi.org/10.1590/S0103-84782004000100006 - RATTALINO EDREIRA, J.I.; MOURTZINIS, S.; CONLEY, S.P.; ROTH, A.C.; CIAMPITTI, I.A.; LICHT, M.A.; KANDEL, H.; KYVERYGA, P.M.; LINDSEY, L.E.; MUELLER, D.S.; NAEVE, S.L.; NAFZIGER, E.; SPECHT, J.E.; STANLEY, J.; STATON, M.J.; GRASSINI, P. Assessing causes of yield gaps in agricultural areas with diversity in climate and soils. Agricultural and Forest Meteorology, v.247, p.170-180, 2017. DOI: https://doi.org/10.1016/j.agrformet.2017.07.010
» https://doi.org/10.1016/j.agrformet.2017.07.010 - ROTH, M.G.; WEBSTER, R.W.; MUELLER, D.S.; CHILVERS, M.I.; FASKE, T.R.; MATHEW, F.M.; BRADLEY, C.A.; DAMICONE, J.P.; KABBAGE, M.; SMITH, D.L. Integrated management of important soybean pathogens of the United States in changing climate. Journal of Integrated Pest Management, v.11, p.1-28, 2020. DOI: https://doi.org/10.1093/jipm/pmaa013
» https://doi.org/10.1093/jipm/pmaa013 - SANTOS, H.G. dos; JACOMINE, P.K.T.; ANJOS, L.H.C. dos; OLIVEIRA, V.Á. de; LUMBRERAS, J.F.; COELHO, M.R.; ALMEIDA, J.A. de; ARAÚJO FILHO, J.C. de; OLIVEIRA, J.B. de; CUNHA, T.J.F. Sistema brasileiro de classificação de solos 5. ed. rev. e ampl. Brasilia: Embrapa, 2018. 356p.
- SANTOS, T.G.; BATTISTI, R.; CASAROLI, D.; ALVES JR, J.; EVANGELISTA, A.W.P. Assessment of agricultural efficiency and yield gap for soybean in the Brazilian Central Cerrado biome. Bragantia, v.80, e1821, 2021. DOI: https://doi.org/10.1590/1678-4499.20200352
» https://doi.org/10.1590/1678-4499.20200352 - SIMEPAR. Sistema de Tecnologia e Monitoramento Ambiental do Paraná Available at: <http://www.simepar.br/prognozweb/simepar/dados_estacoes/25264916>. Accessed on: June 27 2022.
» http://www.simepar.br/prognozweb/simepar/dados_estacoes/25264916 - USDA. United States Department of Agriculture. World Agricultural Production Washington, 2022. 39p. (USDA. Circular Series WA P 2-22).
- ZANON, A.J.; WINCK, J.E.M.; STRECK, N.A.; ROCHA, T.S.M. da; CERA, J.C.; RICHTER, G.L.; LAGO, I.; SANTOS, P.M. dos; MACIEL, L. da R.; GUEDES, J.V.C.; MARCHESAN, E. Desenvolvimento de cultivares de soja em função do grupo de maturação e tipo de crescimento em terras altas e terras baixas. Bragantia, v.74, p.400-411, 2015. DOI: https://doi.org/10.1590/1678-4499.0043
» https://doi.org/10.1590/1678-4499.0043
Publication Dates
-
Publication in this collection
22 Aug 2022 -
Date of issue
2022
History
-
Received
31 Jan 2021 -
Accepted
05 Apr 2022