Introduction
Soybean
(Glycine max [L.] Merrill) was introduced in Brazil in the late 19th
century, especially in the late 1940s. Soybeans are of great importance, not
only in Brazil, but also in the worldwide agricultural production system. In
Brazil, it occupies a prominent position and is the most important culture in
grain production and export. Soybean is considered one of the main sources of
vegetable oils and proteins for human and animal food. It is a vital product in
the Brazilian economy, especially for the supply of oil for domestic
consumption, animal feed as the main protein source, and biofuel production
(Sediyama et al. 2009; Freitas and Mendonça 2016). In this context, research
on this activity aims to increase profitability. Therefore, the use of
transgenic cultivars and herbicides to control weeds is worth mentioning.
The herbicide glufosinate is classified as
non-selective; it inhibits the activity of the glutamine synthetase (GS)
enzyme. The GS enzyme detoxifies ammonia and produces amino acid glutamine from
ammonia and glutamate (Barnett et al. 2012). Glufosinate comes from the
natural toxin (phosphinothricin) of the fungi Streptomyces viridochromogenes
and S. hygroscopicus (Dayan and Duke 2014; ISAAA 2021).
After the application of glufosinate, susceptible
plants display glutamine deficiency, intoxication due to the accumulation of
ammonia and glyoxylate, disruption of the chloroplast structure, concomitant
with a reduction in electron flow and inhibition of photosynthesis (Dayan et
al. 2015; Carbonari et al. 2016). Thus, glufosinate interferes with
chlorophyll content and the assimilation of nitrogen by plants.
The pat gene comes from S. viridochromogenes,
when transcribed in the plant, produces the phosphinothricin acetyltransferase
(PAT) enzyme, which has the capacity to metabolize glufosinate into
N-acetyl-L-glufosinate (NAG). This compound is non-toxic to plants and does not
inhibit GS enzymes (Herouet et al. 2005; Tan et al. 2006). This
gene is present in transgenic events at soybean, maize and cotton, conferring
tolerance to glufosinate. Transgenic Liberty Link® (LL) soybean,
A2704‒12 and A5547‒127 events, are tolerant to glufosinate due to
the insertion of this gene (ISAAA 2021; Albrecht et al. 2021).
In other crops tolerant to glufosinate with either the
pat or bar genes, as in the case of maize and cotton, the
application of this herbicide can lead to the appearance of visual injuries,
reduced electron transport flow and ammonia accumulation, among other factors (Carbonari
et al. 2016; Silva et al. 2016; Krenchinski et al. 2018a).
In soybean, the application of glufosinate at 450 g active ingredient (ai) ha-1
did not cause a reduction in chlorophyll, biomass accumulation, nodule mass, or
yield (Reddy et al. 2011). Kaur et al. (2014) reported injury to
soybean of up to 10% for glufosinate application (594 g ai ha-1), in
different mixtures with other herbicides.
The insertion of the pat gene allows
applications of glufosinate on LL soybean at rates up to three times higher
than that recommended for use in the field (CTNB 2010). The maximum recommended
rate in the package insert for glufosinate application in LL soybean is 700 g
ai ha-1 (Rodrigues and Almeida 2018). However, even with the
tolerance of LL soybean to glufosinate, there is little literature on amounts
that can cause harmful effects.
High rates of glufosinate can be applied to the field
by farmers. However, studies on the effects of high rates of glufosinate are
scarce, on development, chlorophyll, biomass accumulation, and biological
nitrogen fixation in soybeans. It is believed that high rates of glufosinate
may affect these aspects of soybean. Thus, this study aimed to evaluate the
development, chlorophyll, biomass accumulation, and nodule development of
glufosinate-tolerant soybean cultivars (with the pat gene) after
application of the herbicide glufosinate.
Materials and Methods
Experimental setup
The
experiment was conducted in a greenhouse in Palotina, state of Paraná (PR),
Brazil (24°17’45.1″ S, 50°50’35.4″ W). The temperature was
maintained at an average of 25°C ± 2, with an irrigation of 5 mm day-1
and an average photoperiod of 12 h, from March to May 2017. The test was
conducted in 5-liter pots containing soil collected at a depth of 0–20 cm. The
soil was classified as clayey (clay: 63.75%; sand: 17.5%; silt: 18.75%), had a
pH (CaCl2): 5.3 and CEC: 17.74 cmol.dm-3.
Experimental design
A
completely randomized design (CRD) was used in a 2 × 7 factorial arrangement (cultivars
× rates), with four repetitions. The two soybean cultivars used were: LL0291
and LL0767 (non-commercial lines - event A5547‒127) and seven rates (0, 250, 500, 750, 1,000, 1,250
and 1,500 g ai ha-1) of glufosinate (Liberty®, Bayer
S.A.). Five soybean seeds were sown per pot, and at 7 days after emergence, the
pots were thinned to two plants per unit.
Herbicide was applied at the V4 stage (4 nodes on the main
stem with fully developed leaves beginning with the unifoliolate nodes) of
soybean plants using a CO2
pressurized backpack sprayer at a constant pressure of 2 bars. The flow rate
was 0.65 L min-1, in a bar containing six fan nozzles (XR 110
02, Teejet), at a speed of 1 m s-1, with a 50 cm wide application
range per nozzle, providing a spray volume of 150 L ha-1. The
application was carried out at a temperature of 25.2°C and relative humidity of
80.3%.
Data collection
The chlorophyll
index and crop injury to soybean plants were measured 4, 7, 14, 21, 28 and 35
days after application (DAA). The chlorophyll index was evaluated in the
central leaflet of the third fully expanded trifoliate leaf of the two plants
in each pot, considering the count from top to bottom. Chlorophyll indices were
measured using an electronic chlorophyll meter (ClorofiLOG - CFL1030, Falker Automação Agrícola Ltd.) as reported (Júnior et al. 2012).
Visual crop injury scores were attributed to soybean plants after the
application of glufosinate. These
assessments were carried out through visual analysis at each experimental unit
considering significantly visible symptoms at soybean plants, according to
their development. Scores from 0 to 100% were assigned, where 0 represented the
absence of symptoms and 100% the death of the plant (Velini et al.
1995). The glufosinate rate 0 g ai ha-1 (without herbicide effect) was used as a
reference for evaluations, always with a score of 0, for injuries to soybean
plants.
Plant height was measured with the aid of a measuring
tape and the plants were measured from the last fully expanded trifoliate leaf
to the ground surface. These analyses were performed 0, 4, 7, 14, 21, 28, 35
and 42 DAA.
At the end of the experiment (42 DAA), the shoots and
roots of the plants were collected to study the fresh and dry matter of the
root and shoot. After cutting the plant material from the shoot, the soil with
the roots was removed from each pot, carefully with the aid of running water and
sieves. In addition to these evaluations, nodules of nitrogen-fixing bacteria
present in the roots were collected, counted, weighed, and then dried. The
shoots and roots of the plants were stored in paper bags and dried in forced
air circulation (60°C to constant weight). Then, each part of the plant was
weighed on a precision scale (0.0001 g), and the weight values were expressed
in percentage relative to the values of rate 0 (control).
Statistical analysis
After checking the assumptions, no data transformation
it was required. The data were subjected to analysis of variance (ANOVA) (P ≤
0.05). For the factor glufosinate
rates, the data were subjected to regression analysis (P ≤ 0.05). For the factor soybean cultivars,
the data were compared using the F-test (P ≤ 0.05). All necessary breakdowns have been made (Pimentel-Gomes and
Garcia 2002). For ANOVA, the Sisvar 5.6 software was used (Ferreira 2011). For
regression analysis, the SigmaPlot 13 software was used.
In the model selection at regression analysis, the
following fit quality parameters were adopted: significant regression,
regression deviations or lack of adjustment, significant t-test for all
regression coefficients, residue analysis without trend, low coefficient of
variation, high R, and biological explanation. To create the Figs, the
Microsoft 365 Excel software was used.
Results
There
was no significant effect (P > 0.05)
on the chlorophyll indices of either factor. For crop injury, no significant
effect was observed for cultivar (P > 0.05) at 4, 7, 14, 21, 28 and 35 DAA; for all crop injury
assessments the variation in rates had a significant effect (P ≤ 0.05). For height, there was no
significant effect (P > 0.05)
on cultivar at 7 and 14 DAA, while in the other assessments effect was significant
(P ≤ 0.05). For height,
a significant effect (P ≤ 0.05)
was observed only at 7 and 14 DAA. For the assessments related to the nodules,
no significant effect was detected (P > 0.05) for either factor. For dry and fresh shoot matter, a
significant effect (P ≤ 0.05)
was found for both factors. For root weight, no significant effect (P >
0.05) was observed for the factor
cultivar only in the case of dry matter (Table 1).
An increasing linear fit of the rates of glufosinate
it was adjusted for crop injury, with values of up to 26.25% for the highest
rate. With increasing rates, an increase in symptoms was observed. Among the
cultivars, differences were found only at 14 DAA, with a higher percentage in
cultivar LL0291 for the application of 500 g ai ha-1 (Fig. 1).
For height, it was observed that cultivar LL0291 was
inferior to cultivar LL0767, with a difference on the day of application as
well as at 4, 21, 28, 35 and 42 DAA. This can be explained by the specific
differences of each cultivar; from the beginning of the assessments, it was
observed that cultivar LL0291 had shorter heights than cultivar LL0767 (Fig.
2). The two cultivars have an indeterminate cycle, that is, with no exact
growth parameters. At 7 and 14 DAA, an effect of rate of application was observed
on height for cultivar LL0291 - a reduction in height was observed with
increasing rates, with linear fit (Fig. 3).
For fresh shoot matter, a polynomial fit of
glufosinate rates it was adjusted, with cultivar LL0767 being superior at a
rate of 1,000 g ai ha-1, similar to that observed for shoot dry
matter. For fresh root matter, a decreasing linear fit was possible with
increasing rates for cultivar LL0291. A polynomial fit was possible for the
cultivar LL0767. Comparison between cultivars showed that LL0767 was superior
to LL0291 at rates of 750 and 1,250 g ai ha-1. For root dry matter,
no differences were detected between cultivars, with a decreasing linear fit
with increasing rates of glufosinate (Fig. 4). In this sense, it is emphasized
that the maximum recommended rate of glufosinate for post-application in LL
soybean plants is 700 g ai ha-1, on the package insert (Rodrigues
and Almeida 2018).
Discussion
The scores for crop injury assessments gradually
decreased, showing a good recovery capacity for both cultivars. The insertion
of the pat gene confers a great tolerance to glufosinate (Silva et al.
2017; Krenchinski et al. 2018b; Albrecht et al. 2020), which was
also observed in this study. This gene encodes the PAT enzyme, which detoxifies
glufosinate in NAG in transgenic plants. The NAG compound does not inhibit the
GS enzyme, which explains the tolerance of plants, with the pat gene, to
glufosinate (Müllner et
al. 1993). Carbonari et al. (2016) compared two cotton cultivars
containing the pat gene (FM 975WS and IMACD 6001LL) and observed that
cultivar FM 975WS had much lower levels of the pat gene, which means
that the rates supported by this cultivar were lower than those supported by
cultivar IMACD 6001LL.
In another study, in LL soybean, injury of 15% was
observed for the glufosinate (740 g ai ha-1) applied at the V2
stage, with sequential application at V6 (593 g ai ha-1) (Aulakh and
Jhala 2015). Albrecht et al. (2020) observed that application of
glufosinate (at 2,800 g ai ha-1), which was up to four times the
maximum recommended, caused crop injury (up to 38.5%) in soybean plants, but
soybean yield remained unaffected. Other studies have not observed significant
injury in LL soybean plants (Johnson et al. 2014; Chahal and Jhala 2015;
Schultz et al. 2015) or have observed injury (up to 13%) mainly in
mixtures with other herbicides, but always without a reduction in yield
(Striegel et al. 2020). Thus, glufosinate had no effect on the crop
yield. The deleterious effects, in some aspects, are generally observed at
rates above the recommended value. Similar to that observed in the present
study, in which the application of glufosinate was selective up to the maximum
recommended rate, with deleterious effects at higher rates.
Nitrogen assimilation is one of the most important
functions of the cell, and GS is an important enzyme in the assimilation of
ammonia. GS is inhibited by the action of glufosinate, with a rapid
accumulation of ammonia, which is related to the destruction of chloroplasts,
reduced levels of photosynthesis, and decreased production of amino acids
(Brunharo et al. 2014). In a study that compared the effect of rates of
glufosinate in soybeans with and without pat genes, it was observed that
ammonia accumulation increased with increasing rate, with greater accumulation
in soybeans without the pat gene (Albrecht et al. 2020). However,
other study reported that ammonia accumulation in plant tissues due to the
inhibition of glutamine synthetase is not enough to cause injury to plant tissues.
However, inhibition of glutamine synthetase rapidly increases the levels of
reactive oxygen species that are extremely phytotoxic and cause loss of
membrane integrity due to lipid peroxidation (Takano et al. 2019).
Table 1: Significance results of the
analysis of variance (by F-test), for all variables analyzed
|
|
Chlorophyll index (Falker index) |
||||||||||||
|
|
|
4 DAA |
7DAA |
14 DAA |
21 DAA |
28 DAA |
35 DAA |
|
|||||
|
F cultivar (c) |
|
ns |
ns |
ns |
ns |
ns |
ns |
|
|||||
|
F rate (r) |
|
ns |
ns |
ns |
ns |
ns |
ns |
|
|||||
|
F c x r |
|
ns |
ns |
ns |
ns |
ns |
ns |
|
|||||
|
Mean |
|
25.6 |
19.6 |
24.5 |
28.3 |
28.9 |
35.0 |
|
|||||
|
|
Injury (%) |
||||||||||||
|
|
|
4 DAA |
7 DAA |
14 DAA |
21 DAA |
28 DAA |
35 DAA |
|
|||||
|
F cultivar (c) |
|
ns |
ns |
* |
ns |
ns |
ns |
|
|||||
|
F rate (r) |
|
* |
* |
* |
* |
* |
* |
|
|||||
|
F c x r |
|
ns |
ns |
ns |
ns |
ns |
ns |
|
|||||
|
Mean |
|
8.2 |
12.8 |
10.4 |
6.4 |
3.1 |
2.4 |
|
|||||
|
|
Plant Height (cm) |
||||||||||||
|
|
0DAA |
4 DAA |
7 DAA |
14 DAA |
21 DAA |
28 DAA |
35 DAA |
42 DAA |
|||||
|
F cultivar (c) |
* |
* |
ns |
ns |
* |
* |
* |
* |
|||||
|
F rate (r) |
ns |
ns |
* |
* |
ns |
ns |
ns |
ns |
|||||
|
F c x r |
ns |
ns |
ns |
ns |
ns |
ns |
ns |
ns |
|||||
|
|
FN |
DN |
NN |
SF |
SD |
RF |
RD |
||||||
|
F cultivar (c) |
ns |
ns |
ns |
* |
* |
* |
ns |
||||||
|
F rate (r) |
ns |
ns |
ns |
* |
* |
* |
* |
||||||
|
F c x r |
ns |
ns |
ns |
ns |
ns |
ns |
ns |
||||||
|
Mean |
3.1 |
2.1 |
124.6 |
97.1 |
100.2 |
73.3 |
66.8 |
||||||
DAA: days after application;
FN: fresh nodules mass (g); DN: dry nodules mass (g); NN: number of nodules;
SF: shoot fresh mass (%); SD: shoot dry mass (%); RF: root fresh mass (%); RD:
root dry mass (%)
*Significant (P ≤
0.05), means differ each other by
F-test. ns: Non-significant (P > 0.05), means do not differ each other by F-test
%20217-223_files/image002.png)
Fig. 1: Increasing linear fit for injury soybean
cultivars with the pat gene (LL0767 and LL0291), at 4, 7, 14, 21, 28 and 35
days after application of glufosinate rates. Palotina, PR, Brazil, 2017
At 14 DAA,
means followed by the same letter, when comparing cultivars, do not differ by
the F-test (P ≤ 0.05).
At other dates, for cultivars, means do not differ each other by
F-test (P > 0.05)
Regarding the development of
soybean plants, regarding nodules, no effect due to glufosinate rates was
observed. Few studies have evaluated the development of soybean nodules under
the application of glufosinate. With respect to the mass of the shoots and
roots, reductions were observed, especially at high rates. This is similar to
observations by Garcia et al. (2020), who analyzed the quality of seeds
produced from soybeans with the pat gene, in which the application of
glufosinate (500 g ai ha-1) at the V6 soybean stage reduced the
shoot mass of the seedlings.
%20217-223_files/image004.png)
Fig. 2: Height of soybean plants (cm) with the pat gene
(LL0767 and LL0291) under rates of glufosinate at 0,
4, 28, 35 and 42 days after application (DAA). Palotina,
PR, Brazil, 2017
Means followed by the same letter, when comparing
cultivars, on each evaluation date, do not differ by the F-test (P ≥
0.05)
%20217-223_files/image006.png)
Fig. 3: Height of soybean plants (cm) with the pat
gene (LL0767 and LL0291), under glufosinate rates at
7 and 14 days after application (DAA), with decreasing linear fit at
LL0291 cultivar. Palotina, PR, Brazil, 2017
For cultivars, means do not differ each other by F-test (P > 0.05)
%20217-223_files/image008.png)
Fig. 4: Mass (%) of
soybean cultivars with the pat gene (LL0767 and LL0291) under glufosinate rates. Palotina, PR,
Brazil, 2017
Polynomial fit at shoot
fresh mass, shoot dry mass, and root fresh mass (LL0767)
Decreasing linear fit at
root fresh mass (LL0291) and root dry mas
For cultivars, at root dry mass, means do not differ with each other by
F-test (P > 0.05), at other
variables, means
followed by the same letter, do not differ by the F-test (P ≤ 0.05)
In the present study, the chlorophyll indices of LL
soybeans were not affected by the application of glufosinate. Similarly, Kita et
al. (2009) found no reduction in the chlorophyll index (SPAD index) for the
application of glufosinate in soybean. Information on chlorophyll indices in LL
soybeans is scarce. In other genetically modified crops that are tolerant to
glufosinate (such as maize with the pat gene), no reductions in
chlorophyll indices have been reported for glufosinate application (Krenchinski et al. 2018a).
For chlorophyll content,
Reddy et al. (2011) did not find a reduction in LL soybean upon
glufosinate application (450 + 450 g ai ha-1) post-emergence (V3-V4
+ V7-V8). In the same study, the authors observed a crop injury of 3%, with no
reduction in soybean yield. This is one of the few studies reporting the
effects of glufosinate in commercial soybean cultivars (with the pat
gene). This highlights the importance of the results observed in this study,
indicating the selectivity of the herbicide for soybean LL, especially
considering that in the coming years, Enlist™ E3 soybean (with the pat gene)
may be commercially available, and this technology also has a tolerance to
glufosinate.
Conclusion
Glufosinate rates above 1,250 g ai ha-1 may
interfere with development (especially biomass accumulation), of soybean with
the pat gene. The maximum recommended rate of 700 g ai ha-1
was safe for soybean plants with the pat gene. Recovery capacity was
observed in both, showing high selectivity in glufosinate for soybean genotypes
with the pat gene. Soybean with the pat gene is an alternative
for farmers in the alternation of technologies and consequently, the rotation
of mechanisms of action of herbicides.
Acknowledgments
Thanks to the Supra Pesquisa team from the Federal University of
Paraná, for operational support in the implementation of activities.
Author Contributions
TTM, LPA, AJPA and CAC conceived and designed the
study. TTM, FHK, VGCP and FGW collected study data. TTM and AFMS analyzed the
data and wrote the original version of the manuscript. All authors critically revised
the manuscript for important intellectual contents and approved the final
version.
Conflict of Interest
The authors declare that they have no conflict of
interest.
Data Availability
The data
will be made available on acceptable requests to the corresponding author.
Ethics
Approval
Not applicable.
References
Albrecht
LP, AJP Albrecht, AFM Silva, AAM Barroso (2021). Manejo
de organismos geneticamente modificados tolerantes a herbicidas. In:
Matologia: Estudos Sobre Plantas Daninhas, pp:506‒547. Barroso AAM, T Murata
(Eds). Fábrica da Palavra, Jaboticabal, SP, Brazil
Albrecht
AJP, IPF Brito, LP Albrecht, AFM Silva, AKA Matos, CA Carbonari, ED Velini (2020).
Metabolic changes, agronomic performance, and quality of seeds in soybean with
the pat gene after application of glufosinate. Weed Sci 68:594‒604
Aulakh JS, AJ Jhala (2015). Comparison of
glufosinate-based herbicide programs for broad-spectrum weed control in
glufosinate-resistant soybean. Weed Technol 29:419‒430
Barnett KA, TC
Mueller, LE Steckel (2012). Glyphosate-resistant giant ragweed (Ambrosia
trifida) control in WideStrike® flex cotton. Weed
Technol 26:611‒616
Brunharo CACG, PJ Christoffoleti, M Nicolai (2014). Aspectos do
mecanismo de ação do amônio glufosinato: Culturas resistentes e resistência de
plantas daninhas. Rev Bras Herb 13:163‒177
Carbonari
CA, DO Latorre, GL Gomes, ED Velini, DK Owens, Z Pan, FE Dayan (2016). Resistance to
glufosinate is proportional to phosphinothricin acetyltransferase expression
and activity in LibertyLink® and WideStrike® cotton. Planta 243:925‒933
Chahal
PS, AJ Jhala (2015). Herbicide programs for control
of glyphosate-resistant volunteer corn in glufosinate-resistant soybean. Weed
Technol 29:431‒443
CTNB - Comissão Técnica Nacional de Biossegurança () (2010). Technical
Report n 2273.2010, CTNBio, Brasília, DF, Brazil
Dayan
FE, SO Duke (2014). Natural compounds as next-generation herbicides. Plant Physiol 166:1090‒1105
Dayan FE, DK Owens, N
Corniani, FML Silva, SB Watson, JL Howell, DL Shaner (2015). Biochemical
markers and enzyme assays for herbicide mode of action and resistance studies. Weed Sci 63:23‒63
Ferreira
DF (2011). Sisvar: A computer statistical analysis system. Cienc Agrotecnol 35:1039‒1042
Freitas RE, MAA Mendonça (2016). Expansão agrícola no Brasil e a
participação da soja: 20 anos. Rev Econ Sociol Rur 54:497‒516
Garcia JR, AAM Vargas, LT Perboni, EA Souza, D Tessaro, FR Lucio, D
Agostinetto (2020). Physiological attributes of Enlist E3™ soybean seed submitted to
herbicides application. Plant Danin 38;
Article e020220418
Herouet C, DJ
Esdaile, BA Mallyon, E DeBruyne, A Schulz, T Currier, K Hendrickx, RJ van der
Klis, D Rouan (2005). Safety evaluation of the phosphinothricin
acetyltransferase proteins encoded by the pat and bar sequences
that confer tolerance to glufosinate-ammonium herbicide in transgenic plants. Regul
Toxicol Pharmacol 41:134‒149
ISAAA - International Service
for the Acquisition of Agri-biotech Applications (2021). GM Crop Events approved
in Brazil. Available at: http://www.isaaa.org/gmapprovaldatabase/ (Accessed: 17
Jan 2021)
Johnson DB, JK
Norsworthy, RC Scott (2014). Herbicide programs for controlling
glyphosate-resistant johnsongrass (Sorghum halepense) in
glufosinate-resistant soybean. Weed Technol 28:10‒18
Júnior E, ROP
Rossiello, RVMM Silva, RC Ribeiro, MJF Morenz (2012). A new chlorophyll meter
to estimate chlorophyll contents in leaves of Tifton 85 bermudagrass. Cienc
Rur 42:2242‒2245
Kaur S, LD Sandell,
JL Lindquist, AJ Jhala (2014). Glyphosate-resistant giant ragweed (Ambrosia
trifida) control in glufosinate-resistant soybean. Weed Technol
28:569‒577
Kita Y, MS Hanafy, M
Deguchi, H Hasegawa, T Terakawa, K Kitamura, M Ishimoto (2009). Generation and
characterization of herbicide-resistant soybean plants expressing novel
phosphinothricin N-acetyltransferase genes. Breed Sci 59:245‒251
Krenchinski FH, AJP Albrecht,
VJS Cesco, DM Rodrigues, VGC Pereira, LP Albrecht, CA Carbonari, RV Filho
(2018a). Post-emergent applications of isolated and combined herbicides on corn
culture with cp4-epsps and pat genes. Crop Prot 106:156‒162
Krenchinski FH, CA
Carbonari, VJS Cesco, AJP Albrecht, MCL Arcuri, IG Maia, ED Velini (2018b).
Glufosinate resistance level is proportional to phosphinothricin
acetyltransferase gene expression in glufosinate-resistant maize. J Agric
Food Chem 66:12641‒12650
Müllner
H, P Eckes, G Donn (1993). Engineering crop resistance to the naturally
occurring glutamine synthetase inhibitor phosphinothricin. In: Pest Control
with Enhanced Environmental Safety (ACS Symposium Series 524), pp:38‒47. Duke SO, JJ Menn, JR Plimmer JR (Eds). American Chemical Society,
Washington, DC, USA
Pimentel-Gomes F, CH Garcia (2002). Estatística Aplicada a Experimentos
Agronômicos e Florestais: Exposição Com Exemplos e Orientações Para uso de Aplicativos.
Fealq, Piracicaba, SP, Brazil
Reddy KN, RM Zablotowicz, N Bellaloui, W Ding
(2011). Glufosinate effects on nitrogen nutrition,
growth, yield, and seed composition in glufosinate-resistant and
glufosinate-sensitive soybean. Intl
J Agron 2011; Article 109280
Rodrigues BN, FS Almeida (2018). Guia de herbicidas, 7th
edn, pp:137–142. Londrina, PR, Brazil
Sediyama T, RC Teixeira, HB Barros (2009). Tecnologias de Produção e
usos da Soja. Mecenas, Londrina,
PR, Brazil
Silva AFM, AJP
Albrecht, BF Giovanelli, GA Ghirardello, VW Damião,
LP Albrecht, RV Filho (2017). Seletividade de herbicidas isolados
e em associações para milho RR2/LL®. Rev Bras Herb 16:60‒66
Silva
IPF, CA Carbonari, ED Velini, JFS Junior, L Tropaldi L, GLGC Gomes (2016). Absorption
velocity of glufosinate and its effects on weeds and cotton. Agrociencia
50:239‒249
Schultz JL, DB Myers,
KW Bradley (2015). Influence of soybean seeding rate, row spacing, and
herbicide programs on the control of resistant waterhemp in
glufosinate-resistant soybean. Weed Technol 29:169‒176
Striegel A, KM
Eskridge, NC Lawrence, SZ Knezevic, GR Kruger, CA Proctor, AJ Jhala (2020).
Economics of herbicide programs for weed control in conventional, glufosinate,
and dicamba/glyphosate‐resistant soybean across Nebraska. Agron J 112:5158‒5179
Takano HK, R Beffa, C Preston, P Westra, FE Dayan (2019). Reactive
oxygen species trigger the fast action of glufosinate. Planta 249:1837‒1849
Tan S, R Evans, B Singh (2006).
Herbicidal inhibitors of amino acid biosynthesis and herbicide-tolerant crops. Amino
Acids 30:195‒204
Velini ED, R Osipe, DLP Gazziero
(1995). Procedimentos Para Instalação, Avaliação e Análise de Experimentos Com
Herbicidas. SBCPD, Londrina, PR, Brazil