Fitness costs on herbicide-resistant Digitaria insularis (L.) Fedde germination

Custo adaptativo na germinação de Digitaria insularis (L.) Fedde resistentes a herbicidas

Abstract

Digitaria insularis poses a significant challenge in weed control due to its perennial habit, dense clumping growth, and the widespread presence of herbicide-resistant biotypes. Our research investigates whether single or multiple herbicide resistance biotypes of D. insularis experience fitness costs, specifically affecting their germination. To determine the resistance factor, a dose-response curve was employed using glyphosate and haloxyfop-P-methyl herbicides separately in a completely randomized design (CRD) with four replicates per dose (nine doses total). Shoot dry mass was measured at 100 days after herbicide application (DAA), with control assessments performed at 14, 28, and 42 DAA. Subsequently, a separate CRD experiment examined the germination rate as a function of temperature and photoperiod for each biotype. This factorial scheme tested six temperatures across three biotypes (susceptible and two resistant types) under three light exposure periods (0, 8, and 12 hours). Germination percentage and the germination speed index (GSI) were calculated for 14 days, with counts of healthy seedlings recorded daily. Statistical analysis confirmed the resistance/susceptibility of the biotypes based on the dose-response curve. For the susceptible and simple resistance biotypes, the most favorable temperatures for germination were 20, 30 and 40 °C, at which the highest germination percentages and a higher germination speed index were observed. On the other hand, for the biotype with multiple resistance, the temperatures of 25, 30 and 35 °C were more favorable, promoting superior results in both parameters studied.

Keywords:  glyphosate; haloxyfop-P-methyl; sourgrass; resistance

Resumo

A Digitaria insularis é uma espécie de difícil controle devido a perenização, intensa formação de touceiras e ampla presença de biótipos resistentes a herbicidas. Objetiva-se testar a hipótese que os biótipos de D. insularis com resistência simples ou múltipla aos herbicidas possuem custos adaptativos que influenciam em sua germinação. Para se determinar o fator de resistência, foi realizado uma curva de dose resposta, aplicando isoladamente os herbicidas glyphosate e haloxyfop-P-methyl. O delineamento experimental utilizado foi inteiramente casualizado (DIC), constituído das 9 doses de cada herbicida para cada um dos biótipos, com quatro repetições. As avaliações de controle foram realizadas aos 14, 28 e 42 DAA e massa seca de parte aérea aos 100 DAA. O segundo estudo foi realizado em DIC, para mensurar a taxa de germinação em função da temperatura e fotoperíodo para cada período de luminosidade (0, 8 e 12 horas). Conduzido em câmaras de germinação, em esquema fatorial 6x3, com 6 diferentes temperaturas e 3 biótipos, respectivamente. As avaliações ocorreram até 14 DAA, onde foram realizadas as contagens das plântulas sadias. Calculou-se a porcentagem de germinação e o índice de velocidade de germinação IVG. Os resultados foram submetidos à análise estatística e através da curva de dose resposta foi confirmada a resistência e/ou suscetibilidade dos biótipos. Para os biótipos suscetíveis e com resistência simples, as temperaturas mais favoráveis para a germinação foram 20, 30 e 40 °C, nas quais se observaram as maiores porcentagens de germinação e um índice de velocidade de germinação mais elevado. Em contrapartida, para o biótipo com resistência múltipla, as temperaturas de 25, 30 e 35 °C foram mais favoráveis, promovendo resultados superiores em ambos os parâmetros estudados.

Palavras-chave:  glyphosate; haloxyfop-P-methyl; capim-amargoso; resistência

1. Introduction

Weeds are any plant species growing in an undesired location, competing for resources and interfering with crops of interest, thus affecting their productivity and/or product quality (Oliveira et al., 2018). The greater the similarity between crop species and weeds, the more intense the competition for resources, and the more challenging the control becomes (Barbosa et al., 2019; Radosevich et al., 1997). Moreover, weeds exhibit greater genetic variability, ensuring better adaptation to the environment compared to cultivated species (Pitelli, 1985).

Digitaria insularis, known as sourgrass, is a plant capable of year-round growth and is one of the main weeds in both annual and perennial crops (López-Ovejero et al., 2017). This behavior is accentuated by the perennialization process that the plant undergoes after establishment, allowing for flowering and effective seed dispersal, thereby increasing the complexity in infestation control (Gemelli et al., 2013). In addition to its year-round adaptability, D. insularis seeds demonstrate germination capability across a broad range of temperatures and light intensities, with temperature variations between 20 and 35 °C (Mendonça et al., 2014). It is worth noting that the seeds are considered photoblastic neutral, indicating that they can germinate in both the presence and absence of light (Klein and Felippe, 1991).

There are few active ingredients registered for D. insularis control in Brazil in post-emergence of soybeans. Only two of the mechanisms of action can effectively control this species, including 5-enolpyruvylshikimate-3-phosphate synthase (EPSP) inhibitors and acetyl-CoA carboxylase (ACCase), which are often used in combination (Gemelli et al., 2013).

Glyphosate (EPSP inhibitor) is the primary herbicide used for weeding management (Lucio et al., 2019). Its frequent use increases the selection of tolerant species or herbicide-resistant biotypes. In Brazil, 13 species have been reported to have resistant biotypes to this herbicide (Heap, 2023). Glyphosate resistance mechanisms in D. insularis include slower absorption, faster glyphosate metabolism, and significantly lower herbicide translocation in resistant plants compared to susceptible ones, even with 3-4 leaves (Carvalho et al., 2011).

An option for controlling glyphosate-resistant grasses is ACCase inhibitor herbicides (quizalofop-p-tefuryl, haloxyfop-P-methyl, sethoxydim, and clethodim), recommended for use in post-emergence grasses (Correia et al., 2020). They act on advanced plant development stages, presenting the characteristic symptom of meristematic zone necrosis (Takano et al., 2020).

In theory, in some cases, herbicide resistance may have a fitness cost, which means that, in the absence of selective pressure exerted by herbicides, resistant plants bear an energy cost associated with the presence of genes responsible for this trait (Mariani et al., 2016). The strong interest in fitness costs associated with herbicide resistance arises from the potential for these costs to reduce the occurrence of resistant weed genotypes in populations once herbicide selective pressure is eliminated, providing valuable insights for managing these resistant plants (Vila-Aiub et al., 2011).

In this context, this work was developed in order to investigate the hypothesis that D. insularis biotypes displaying single resistance to glyphosate or multiple resistance to glyphosate and haloxyfop-P-methyl exhibit fitness costs affecting their germination.

2. Materials and Methods

2.1. Confirmation of resistance - calculation of resistance factor (RF)

An experiment was carried out at the Corteva Agriscience™ experimental station in Mogi-Mirim-SP (22°27’05.23”S, 47°04’14.35” W) in the 2021/2022 crop season. Seeds of Digitaria insularis were collected from three locations: the first from the Ponta Grossa-PR region (25º13'50”S, 50°06’31”W), which was presumed to be susceptible to glyphosate and haloxyfop-P-methyl herbicides. These seeds were acclimatized conditions and reproduced for four generations in Mogi-Mirim-SP for use in the study. The second location was Mogi-Mirim (22°27’00.10”S, 47°04’39.20” W), presumed to be resistant to glyphosate, and the third was Mogi-Mirim (22°26’43.34”S, 47°03’55.20” W), presumed to be resistant to both glyphosate and haloxyfop-P-methyl. According to Gonçalves Netto et al. (2021), D. insularis plants in Brazil are genetically similar, originating from a common parent, making it possible to compare plants from diverse sources in the study.

Each collected biotype was sown to test the resistance factor, where each experimental unit consisted of pots with a volumetric capacity of 700 mL, filled with a mixture of soil classified as Dystroferric Red Latosol (Embrapa, 2013), with sandy-clay texture. The experiment adopted a completely randomized design (CRD) with four replicates for each treatment. Nine doses of each herbicide (glyphosate and haloxyfop-P-methyl) were tested, along with an absolute untreated control for each of the three biotypes. A dose-response curve was used as recommended by Christoffoleti (2002).

Herbicide doses were expressed as multiples of the recommended dose (D) of haloxyfop-P-methyl (62.1 g ai ha^-1, Verdict Max™) and glyphosate (720 g ai ha^-1, Roundup Original™). Then, treatments were defined as follows: 16D, 8D, 4D, 2D, 1D, 1/2D, 1/4D, 1/8D, and 1/16D. For haloxyfop-P-methyl, this resulted in doses of 3.88, 7.76, 15.53, 31.05, 62.10, 124.20, 248.40, 496.8, 993.60 g ai ha^-1, and when necessary, mineral oil (Joint Oil™) was added at 0,5% v v^-1. For glyphosate, doses were 45.0, 90.0, 180.0, 3600, 720.0, 1440.0, 2880.0, 5760.0, 11520.0 g ai ha^-1. Both treatments included an untreated control.

Applications were made when D. insularis plants reached the two-tiller stage, corresponding to BBCH 22 as described by Hess et al. (1997). An automatic CO₂-pressurized track sprayer system was used, maintaining a constant pressure of 40 PSI and employing XR110015EVS spray nozzles, resulting in an application volume of 100 L ha^-1. The application was performed under conditions of 22 °C and 68% relative humidity.

Control assessments were based on the following scale, with 0% representing complete absence of control and 100% representing absolute control, according to the method proposed by SBCPD (1995), at 14, 28, and 42 days after application (DAA). In addition to visual control assessments, shoot dry mass (SDM) was measured at 100 DAA. This involved cutting plants at ground level and then drying the plant material in an oven at 60 °C ± 5 °C for 72 hours before weighing.

Statistical analysis involved applying the F-test for analysis of variance, and when the treatment means were significant, they were subjected to regression analysis. After analyzing the first dose-response curve, the experiment was repeated using seeds from this study (F2), following the same method, thereby adhering to HRAC rules for resistance confirmation in a biotype (HRAC, 2023).

Resistance level or resistance factor (RF) was calculated based on the means of the control for D. insularis biotypes. RF (F = R/S) is the value expressing the number of times the dose required to provide 50% control (C₅₀ or DL₅₀) of the resistant population is greater than the dose that controls 50% of the susceptible population. Resistance is confirmed when the RF of the resistant biotype is greater than 1.0 (Hall et al., 1998; Takano et al., 2016, 2017; Markus et al., 2021).

Dose-response curve data were fitted to a non-linear logistic regression model. The control variable was fitted using the model proposed by Streibig (1988) (Equation 1):

$y=\frac{a}{\left[1+{\left(\frac{x}{b}\right)}^c\right]}$ (1)

where: y = control rate, x = herbicide dose, and a, b, and c = curve parameters, of which a is the difference between maximum and minimum points of the curve, b is the dose promoting 50% of the variable response, and c is the curve slope.

For the dry mass variable, the model proposed by Seefeldt et al. (1995) was used (Equation 2):

$y=a+\frac{b}{\left[1+{\left(\frac{x}{c}\right)}^d\right]}$ (2)

where: y = residual percentage of dry mass, x = herbicide dose, and a, b, c, and d = curve parameters, of which a is the lower limit of the curve, b is the difference between maximum and minimum points of the curve, c is the dose promoting 50% of the variable response, and d is the curve slope.

2.2. Fitness cost of resistant biotypes - germination under different temperatures and photoperiod conditions

Germination rates of the biotypes mentioned in the preceding experiment were assessed concerning temperature and photoperiod. The seeds used in this experiment were obtained from the second generation of the dose-response curve experiment. This experiment was carried out under controlled conditions within the Seed Analysis Laboratory at the Federal University of Grande Dourados (UFGD) Farm School in Dourados-MS, during the 2022/2023 growing season.

The experiment was conducted in germination chambers (BOD) using a completely randomized design (CRD), with four replicates for each treatment. A 6 × 3 factorial scheme was adopted, where the first factor corresponds to the temperatures (15, 20, 25, 30, 35, and 40 °C) and the second factor to the biotypes (susceptible, single-resistant, and multiple-resistant). The experiments were carried out separately for three photoperiod simulations: 0, 8, and 12 hours.

Experimental units consisted of transparent acrylic Gerbox™ boxes (11.0 × 11.0 × 3.0 cm). Each box was sown with 50 D. insularis seeds, which were previously disinfected using a sodium hypochlorite solution (40% commercial solution and 5% active ingredient) for two minutes (adapted from Orzari et al., 2013). The seeds were laid on two Germitest™ paper sheets as substrate (10.5 × 10.5 cm), which were previously moistened with distilled water at a ratio of 2.5 times the dry paperweight. These paper sheets were daily moistened. For treatments without light, planting was done under green light, using Gerbox™ boxes covered with foil to prevent light interference during germination (Gillard et al., 2022).

Evaluations were performed daily until seedling germination stabilized, which occurred 14 days after planting (DAP). Germination was considered to have occurred when healthy seedlings with primary root protrusion and/or developed embryos were observed. Germination rate (G%) was determined following seed analysis rules (Brasil, 2009), and germination speed index (GSI) followed the formula by Maguire (1962), as follows (Equation 3):

$$GSI=\frac{N1}{D1}+\frac{N2}{D2}+\dots .+\frac{Nn}{Dn}$$ (3)

where: GSI = germination speed index, N = number of seedlings counted on the day of counting, and D = number of days after sowing when counting was done.

Data on G% and GSI were subjected to analysis of variance (ANOVA) using the F-test. When differences were significant, treatment means were compared using the Scott-Knott test at a 5% probability level (p ≤ 0.05).

3. Results

3.1. Resistance confirmation and resistance factor calculation

Through analysis of variance, dose-response curve data were subjected to a control factor (%) and found to be significant. Non-linear regression models proposed by Streibig (1988) were used, in which the parameters “a”, “b”, and “c” generated the dose-response curve (Table 1).

Table 1
Estimated parameters “a”, “b” and “c” of the dose-response curve and coefficient of determination (R²), adjusted for percentage control of D. insularis biotypes, when glyphosate and haloxyfop-P-methyl were applied, at 42 DAA.

Glyphosate	a	b	c	R2
D. insularis susceptible	102.65	586.63	-2.29	0.9963
D. insularis single resistance	106.02	2851.60	-2.88	0.9951
D. insularis multiple resistance	104.84	3086.06	-3.54	0.9963
Haloxyfop	a	b	c	R2
D. insularis susceptible	100.00	4.19	-34.48	>0.9999
D. insularis single resistance	100.00	4.14	-33.83	>0.9999
D. insularis multiple resistance	101.78	373.85	-4.09	0.9999

• “a” is the difference between the maximum and minimum points of the curve, “b” is the dose that provides a 50% response of the variable, and “c” is the slope of the curve.

The data obtained from the dose-response curve analysis for shoot dry matter reduction (%) underwent a variance analysis, revealing statistical significance. Non-linear regression models proposed by Seefeldt et al. (1995) were employed, where the parameters “a,” “b,” “c,” and “d” generated the dose-response curve (Table 2).

Table 2
Estimation of the parameters “a”, “b”, “c” and “d” of the dose-response curve and the coefficient of determination (R²), adjusted for the reduction in the dry matter of the aerial part (%) of the biotypes of D. insularis, when glyphosate and haloxyfop-P-methyl were applied, at 42 DAA.

Glyphosate	a	b	c	d	R2
D. insularis susceptible	-1.62	102.18	408.65	-2.78	0.9994
D. insularis single resistance	26.02	75.90	1307.43	-1.88	0.9445
D. insularis multiple resistance	9.54	93.59	3366.17	-4.76	0.9812
Haloxyfop	a	b	c	d	R2
D. insularis susceptible	-4.19	104.19	4.10	-33.53	>0.9999
D. insularis single resistance	25.48	74.51	-3.98	-31.48	>0.9999
D. insularis multiple resistance	-0.41	102.23	330.87	-3.50	0.9997

• “a” is the lower limit of the curve, “b” is the difference between the maximum and minimum points of the curve, “c” is the dose that provides a 50% response of the variable, and “d” is the slope of the curve.

Considering the parameters used to calculate the glyphosate doses required to control (%) susceptible, single-resistant, and multiple-resistant D. insularis biotypes, dose-response curves were generated 42 days after application (DAA) (Figure 1A). Besides the control parameter, another curve was generated for shoot dry matter reduction (Figure 1B). The non-linear regression analysis underscores the resistance of the two biotypes in comparison to the susceptible biotype. Susceptible biotype exhibits control or reduction in dry matter mass at lower doses compared to the resistant biotypes (both single and multiple resistance).

Figure 1
Curve of dose-response to glyphosate for control (%) (A) and shoot dry matter reduction (%) (B) of the 3 biotypes of Digitaria insularis studied at 42 DAA.

The DL₅₀ values of glyphosate were 586.63, 2851.6, and 3086.06 g ai ha^-1 for the susceptible, single-resistant, and multiple-resistant biotypes, respectively. Therefore, the resistance factors (RF) of the control parameter were 4.86 and 5.26 for the single and multiple glyphosate-resistant biotypes, respectively, which are above 1, thus confirming their resistance.

Regarding SDM reduction, glyphosate dose required to reduce weed growth by 50% (GR₅₀) reached values of 408.65, 1307.43, and 3366.17 for the susceptible, single-resistant, and multiple-resistant biotypes, respectively. The RF values were 3.20 and 8.24 for the single and multiple glyphosate-resistant biotypes, respectively.

Based on the parameters derived from the haloxyfop-P-methyl doses required to achieve control (%) (Figure 2A) and dry matter reduction (Figure 2B) in D. insularis susceptible, single-resistant, and multiple-resistant biotypes, dose-response curves were generated at 42 DAA. These curves, analyzed through non-linear regression, prominently demonstrate the resistance of the multiple-resistant biotype in comparison to the susceptible biotype.

Figure 2
Curve of dose-response to haloxyfop-P-methyl para control (%) (A) and shoot dry matter reduction (%) (B) of the 3 biotypes of Digitaria insularis studied at 42 DAA.

Regarding control (%), RF values for the single and multiple haloxyfop resistant biotypes were 0.98 and 89.22, respectively, confirming the resistance of the latter. This also confirms the susceptibility of the former, which is only resistant to glyphosate.

Regarding SDM reduction, the GR₅₀ values were 4.10, -3.98, and 330.87 for the susceptible, single-resistant, and multiple-resistant biotypes, respectively. Therefore, RF values were -0.97 and 80.7 for the single and multiple glyphosate-resistant biotypes, respectively.

3.2. Fitness cost of resistant biotypes regarding germination under different temperatures and photoperiod conditions

A significant interaction was observed between biotypes and temperatures across the three photoperiods, which were analyzed as independent experiments, for both germination percentage and germination speed index (GVI) (Tables 3 and 4).

Table 3
Germination rate (G%) for susceptible, single-resistant, and multiple-resistant biotypes at temperatures of 15, 20, 25, 30, 35, and 40 °C with zero, eight and twelve hours of photoperiod.

Temperature	0 hours of photoperiod
	Susceptible				Single R				Multiple R
15 °C	13.00		bC		35.50		bB		82.00	aA
20 °C	89.50		aA		94.00		aA		68.00	cB
25 °C	3.50		cC		11.50		cB		88.00	aA
30 °C	93.50		aA		96.00		aA		78.00	bB
35 °C	9.00		bC		16.50		cB		85.00	aA
40 °C	88.50		aA		93.50		aA		76.50	bB
F	A=349.79*; B=239.37**; AxB=133.77**
CV(%)	7.91
Temperatura		8 hours of photoperiod
		Susceptible				Single R			Multiple R
15 °C		75.50		bB		89.00		aA	95.00	aA
20 °C		94.50		aA		93.00		aA	92.50	aA
25 °C		61.00		cB		84.00		aA	91.50	aA
30 °C		95.00		aA		94.00		aA	92.50	aA
35 °C		70.00		bB		75.00		bB	83.00	aA
40 °C		87.50		aA		91.50		aA	92.50	aA
F		A=12.97**; B=13.26**; AxB=3.48**
CV(%)		8.4
Temperatura		12 hours of photoperiod
		Susceptible				Single R			Multiple R
15 °C		66.00		bB		69.00		bB	89.00	aA
20 °C		92.50		aA		81.00		bB	72.50	bB
25 °C		67.00		bB		76.50		bB	86.50	aA
30 °C		91.50		aA		90.50		aA	78.50	bB
35 °C		62.50		bC		73.00		bB	85.50	aA
40 °C		91.00		aA		91.00		aA	66.50	bB
F		A=6.32**; B=0.39ns; AxB=11.29**
CV (%)		9.06

• Factor A: Biotypes; Factor B: Temperatures; CV: Coefficient of Variation;
• ^**
  significant at 1%, and NS not significant at the 5% probability level according to the F-test. Means followed by the same lowercase letters in the column and uppercase letters in the row do not differ from each other according to the Scott-Knott test at a 5% significance level.

Table 4
Germination speed index (GSI) for susceptible, single-resistant, and multiple-resistant biotypes at temperatures of 15, 20, 25, 30, 35, and 40 °C with twelve hours of photoperiod.

Temperature	0 hours of photoperiod
	Susceptible		Single R		Multiple R
15 °C	2.81	dA	0.63	dA	1.41	eA
20 °C	16.91	cA	4.16	dB	5.39	eB
25 °C	69.72	bB	96.24	bA	87.71	cA
30 °C	91.89	aB	118.60	aA	112.53	bA
35 °C	98.21	aB	124.05	aA	123.86	aA
40 °C	67.03	bB	77.46	cA	77.89	dA
F	A=25.70**; B=694.66**; AxB=8.16**
CV (%)	9.84
Temperature	8 hours of photoperiod
	Susceptible		Single R		Multiple R
15 °C	29.52	cA	22.53	dA	32.60	dA
20 °C	42.90	bA	48.77	cA	42.16	dA
25 °C	86.08	aA	94.18	bA	77.94	cA
30 °C	87.16	aA	100.16	bA	91.50	bA
35 °C	93.56	aB	114.21	aA	105.77	aA
40 °C	85.42	aB	111.27	aA	117.83	aA
F	A=10.15**; B=170.10**; AxB=3.87**
CV (%)	11.24
Temperature	12 hours of photoperiod
	Susceptible		Single R		Multiple R
15 °C	15.93	dA	13.39	dA	12.44	eA
20 °C	35.93	cA	34.65	cA	31.14	dA
25 °C	72.86	aA	80.53	bA	85.87	bA
30 °C	76.12	aB	97.35	aA	97.28	aA
35 °C	64.75	bB	97.78	aA	101.38	aA
40 °C	80.08	aA	81.64	bA	71.96	cA
F	A=12.38**; B=207.27**; AxB=6.14**
CV (%)	12.03

• Factor A: Biotypes; Factor B: Temperatures; CV: Coefficient of Variation;
• ^**
  significant at 1%, and NS not significant at the 5% probability level according to the F-test. Means followed by the same lowercase letters in the column and uppercase letters in the row do not differ from each other according to the Scott-Knott test at a 5% significance level.

Regarding germination percentage, in the absence of light (0 hours of photoperiod), temperatures of 20, 30, and 40 °C resulted in the highest germination rates at 14 DAP across all biotypes studied. At 30 °C, germination was significantly higher in the susceptible biotype (93.50%) and the biotype with single resistance (96.00%) compared to the biotype with multiple resistance (78.00%). Conversely, temperatures of 15 and 25 °C led to lower germination percentages in all biotypes, underscoring the adverse impact of temperatures outside the ideal range of 20 to 40 °C on germination in this species (Table 3).

Under an 8-hour photoperiod, the highest germination percentages were observed at temperatures between 20 and 30 °C for both the susceptible biotype and the biotype with single resistance, whereas the biotype with multiple resistance maintained high germination across a broader range of 15 to 40 °C. At 15 °C, all biotypes exhibited the lowest germination rates (61.00% to 75.50%), suggesting that lower temperatures are less favorable for germination. However, when comparing biotypes at 15 °C, the biotype with multiple resistance had significantly higher germination (95.00%) than the susceptible and single resistance biotypes (75.50% and 89.00%, respectively) (Table 3).

With a 12-hour photoperiod, greater variation was observed among the biotypes. For the susceptible and multiple resistance biotypes, temperatures of 25, 30, and 35 °C yielded the highest germination rates, while for the single resistance biotype, higher germination rates were observed at 20, 25, 30, 35, and 40 °C at 14 DAP. The lowest germination rates were recorded at 15 and 40 °C for all biotypes, with the multiple resistance biotype achieving higher germination at 15 °C (89.00%) compared to the susceptible and single resistance biotypes (66.00% and 69.00%, respectively) (Table 3).

For the germination speed index (GVI), under no light conditions, temperatures of 30 and 35 °C in the single and multiple resistance biotypes exhibited significant differences, standing out as superior compared to other conditions (Table 4).

Under the 8-hour photoperiod, the single and multiple resistance biotypes recorded the highest GVI values within the 25 to 40 °C range, with the multiple resistance biotype showing the highest GVI at 40 °C (117.83), followed by the single resistance biotype (111.27) (Table 4).

In the 12-hour photoperiod, the lowest GVI values for all biotypes were observed at temperatures of 15 and 20 °C. Once again, temperatures of 25, 30, 35, and 40 °C produced the highest GVI values. For the susceptible biotype, the highest GVI was observed at 25, 30, and 40 °C, whereas the single and multiple resistance biotypes showed superior performance at 30 and 35 °C (Table 4).

4. Discussion

Our findings are consistent with those of Carvalho et al. (2011), who observed comparable results for the resistance factor (RF) of D. insularis biotypes to glyphosate in São Paulo, where the plants were cultivated in pots with 2 to 3 tillers, and RF values ranged from 3.5 to 5.6. Similarly, Melo et al. (2015) carried out a study in São Paulo and Minas Gerais States, confirming resistance in the Minas biotype with an RF of 4.01. Furthermore, Adegas et al. (2010) also confirmed glyphosate resistance in D. insularis biotypes from Paraná State, resulting in an RF of 6.46. These data collectively highlight the rapid selection of resistance in this weed species due to the extensive use of glyphosate herbicide and the swift seed dispersal of this species.

Carvalho et al. (2011) obtained equivalent results for SDM reduction, with RF values between 2.3 and 3.9, confirming the resistance of the biotypes in question. Adegas et al. (2010) tested alternatives to glyphosate and found 100% control of D. insularis biotypes at a dose of 48 ai ha^-1 of haloxyfop-P-methyl, consistent with our results for the single and susceptible biotypes.

Takano et al. (2020) obtained related results in D. insularis populations, with an RF of 61.3 for the control (%) parameter. Compared to the proportion in Brazil, there has been a drastic decrease in reports of resistance biotypes to haloxyfop compared to glyphosate. This is attributed to the reduced use of graminicides for weed management, and when used as a tool, it is generally associated with other modes of action and applied sequentially, either with contact herbicides or other graminicides from different chemical groups (Cassol et al., 2019).

The low germination observed can be attributed to the prolonged exposure of seeds to constant temperatures and the absence of light, suppressing enzymatic processes related to germination. These lower rates are in line with the observations made by Pyon et al. (1977).

Germination responses to temperature and light differ among species but also within species across their latitudinal and altitudinal ranges. In response to environmental factors, seed dormancy and germination characteristics may vary within one species (Klupczyńska and Pawłowski, 2021). Along with moisture and oxygen, these factors determine the predominance of certain species in different geographical contexts. For instance, the preference of Cyperus esculentus for colder regions in the United States, in contrast to the intolerance of Cyperus rotundus to low temperatures, as observed by Singh and Singh (2009) and Travlos et al. (2020).

At the field level, germination can be influenced by the presence and amount of straw on the soil surface. This occurs because straw regulates thermal conditions, resulting in less temperature fluctuations. Moreover, high straw quantities on the soil surface prevent light penetration, thereby hindering the germination of some species that respond to temperature variation or are photoblastic (Wang et al., 2023). Despite D. insularis being a neutral photoblastic plant, Mendonça et al. (2014) demonstrated that under higher luminosity, its germination rates and GSI are increased. Similarly, Petter et al. (2015) studied D. insularis germination under the mulch of different cover crops and noted significant differences in weed germination control.

Regarding the multiple resistance biotype, the highest germination rates occur in the temperature range between 25 and 40 °C, highlighting its greater temperature sensitivity compared to the other biotypes. Mondo et al. (2010) observed comparable results when evaluating the effects of light and temperature on four species of the genus Digitaria.

Mendonça et al. (2014) performed germination studies on different D. insularis populations. These authors demonstrated that temperatures of 25 and 35 °C were more favorable for germination of all studied populations compared to temperatures of 15 and 40 °C. These findings corroborate our results, in which temperatures between 25 and 35 °C achieved the highest germination percentages overall, across photoperiods of 0, 8, and 12 hours.

5. Conclusion

For seed germination, light did not prove to be a limiting factor, while temperature played a determining role, resulting in variations in the germination rates of the D. insularis biotypes studied.

For the susceptible and simple resistance biotypes, the most favorable temperatures for germination were 20, 30 and 40 °C, at which the highest germination percentages and a higher germination speed index were observed. On the other hand, for the biotype with multiple resistance, the temperatures of 25, 30 and 35 °C were more favorable, promoting superior results in both parameters studied.

References

• ADEGAS, F.S., GAZZIERO, D.L.P., VOLL, E. and OSIPE, R. 2010. Diagnóstico da existência de Digitaria insularis resistente ao herbicida glyphosate no sul do Brasil. In: Anais do XXVII Congresso Brasileiro da Ciência das Plantas Daninhas, 2010, Ribeirão Preto, SP. Londrina: SBCPD, pp. 761-765.
• BARBOSA, E.M., BONILLA, O.H., DE LUCENA, E.M.P. and DE ANDRADE, L.M., 2019. Estrutura de um fragmento de Caatinga infestado por Cryptostegia madagascariensis Bojer ex Decne. Revista Brasileira de Geografia Física, vol. 12, no. 5, pp. 1952-1966. http://doi.org/10.26848/rbgf.v12.5.p1952-1966
  » http://doi.org/10.26848/rbgf.v12.5.p1952-1966
• BRASIL. Ministério da Agricultura, Pecuária e Abastecimento. Secretaria de Defesa Agropecuária, 2009. Regras para análise de sementes. Brasília: Mapa/ACS, 399 p.
• CARVALHO, L.B., CRUZ-HIPOLITO, H., GONZÁLEZ-TORRALVA, F., DA COSTA AGUIAR ALVES, P.L., CHRISTOFFOLETI, P.J. and PRADO, R., 2011. Detection of sourgrass (Digitaria insularis) Biotypes resistant to glyphosate in Brazil. Weed Science, vol. 59, no. 2, pp. 171-176. http://doi.org/10.1614/WS-D-10-00113.1
  » http://doi.org/10.1614/WS-D-10-00113.1
• CASSOL, M., MATTIUZZI, M.D., ALBRECHT, A.J.P., ALBRECHT, L.P., BACCIN, L.C. and SOUZA, C.N.Z., 2019. Efficiency of isolated and associated herbicides to control glyphosate-resistant sourgrass. Planta Daninha, vol. 37, e019190671. http://doi.org/10.1590/s0100-83582019370100060
  » http://doi.org/10.1590/s0100-83582019370100060
• CHRISTOFFOLETI, P.J., 2002. Curvas de dose-resposta de biótipos resistente e suscetível de Bidens pilosa L. aos herbicidas inibidores da ALS. Scientia Agrícola, vol. 59, no. 3, pp. 513-519. http://doi.org/10.1590/S0103-90162002000300016
  » http://doi.org/10.1590/S0103-90162002000300016
• CORREIA, N.M., RAMPAZZO, P.E., ARAÚJO, L.D.S. and ROSSI, C.V.S., 2020. Sensitivity of Digitaria insularis to herbicides in agricultural areas, in the Brazilian Cerrado biome. Pesquisa Agropecuária Brasileira, vol. 55, e01570. http://doi.org/10.1590/s1678-3921.pab2020.v55.01570
  » http://doi.org/10.1590/s1678-3921.pab2020.v55.01570
• EMPRESA BRASILEIRA DE PESQUISA AGROPECUÁRIA – EMBRAPA. Centro Nacional de Pesquisa Agropecuária de Solos, 2013. Sistema brasileiro de classificação de solos. Brasília: Embrapa Solos, 198 p.
• GEMELLI, A., OLIVEIRA JUNIOR, R.S., CONSTANTIN, J., BRAZ, G.B.P., JUMES, T.M.C., GHENO, E.A. and FRANCHINI, L.H.M., 2013. Estratégias para o controle de capim-amargoso (Digitaria insularis) resistente ao glyphosate na cultura milho safrinha. Revista Brasileira de Herbicidas, vol. 12, no. 2, pp. 162-170. http://doi.org/10.7824/rbh.v12i2.201
  » http://doi.org/10.7824/rbh.v12i2.201
• GILLARD, M.B., CASTILLO, J.M., MESGARAN, M.B., FUTRELL, C.J. and GREWELL, B.J., 2022. Germination niche breadth of invasive Iris pseudacorus (L.) suggests continued recruitment from seeds with global warming. American Journal of Botany, vol. 109, no. 7, pp. 1108-1119. http://doi.org/10.1002/ajb2.16026 PMid:35716120.
  » http://doi.org/10.1002/ajb2.16026
• GONÇALVES NETTO, A., CORDEIRO, E.M., NICOLAI, M., DE CARVALHO, S.J., OVEJERO, R.F.L., BRUNHARO, C.A., ZUCCHI, M.I. and CHRISTOFFOLETI, P.J., 2021. Population genomics of Digitaria insularis from soybean areas in Brazil. Pest Management Science, vol. 77, no. 12, pp. 5375-5381. http://doi.org/10.1002/ps.6577 PMid:34302709.
  » http://doi.org/10.1002/ps.6577
• HALL, L.M., STROMME, K.M. and HORSMAN, G.P., 1998. Resistance to acetolactate synthase inhibitors and quinclorac in a biotype of false clover (Gallium spurium). Weed Science, vol. 46, no. 4, pp. 390-396. http://doi.org/10.1017/S0043174500090780
  » http://doi.org/10.1017/S0043174500090780
• HEAP, I.M., 2023 [viewed 16 March 2023]. International survey of herbicide resistant weeds [online]. Available from: www.weedscience.org/Homa.espx
  » www.weedscience.org/Homa.espx
• HESS, M., BARRALIS, G., BLEIHOLDER, H., BUHR, L., EGGERS, T.H., HACK, H. and STAUSS, R., 1997. Use of the extended BBCH scale-general for the descriptions of the growth stages of mono, and dicotyledonous weed species. Weed Research, vol. 37, no. 6, pp. 433-441. http://doi.org/10.1046/j.1365-3180.1997.d01-70.x
  » http://doi.org/10.1046/j.1365-3180.1997.d01-70.x
• HERBICIDE RESISTANCE ACTION COMMITTEE – HRAC, 2023 [viewed 16 March 2023]. HRAC confirming resistance [online]. Available from: https://hracglobal.com/herbicide-resistance/confirming-resistance
  » https://hracglobal.com/herbicide-resistance/confirming-resistance
• KLEIN, A. and FELIPPE, M., 1991. Efeito da luz na germinação de sementes de ervas invasoras. Pesquisa Agropecuária Brasileira, vol. 26, no. 7, pp. 955-966.
• KLUPCZYŃSKA, E.A. and PAWŁOWSKI, T.A., 2021. Regulation of seed dormancy and germination mechanisms in a changing environment. International Journal of Molecular Sciences, vol. 22, no. 3, pp. 1357. http://doi.org/10.3390/ijms22031357 PMid:33572974.
  » http://doi.org/10.3390/ijms22031357
• LÓPEZ-OVEJERO, R.F., TAKANO, H.K., NICOLAI, M., FERREIRA, A., MELO, M.S., CAVENAGHI, A.L., CHRISTOFFOLETI, P.J. and OLIVEIRA JÚNIOR, R.S., 2017. Frequency and dispersal of glyphosate-resistant sourgrass (Digitaria insularis) populations across Brazilian agricultural production areas. Weed Science, vol. 65, no. 2, pp. 285-294. http://doi.org/10.1017/wsc.2016.31
  » http://doi.org/10.1017/wsc.2016.31
• LUCIO, F.R., KALSING, A., ADEGAS, F.S., ROSSI, C.V.S., CORREIA, N.M., GAZZIERO, D.L.P. and DA SILVA, A.F., 2019. Dispersal and frequency of glyphosate-resistant and glyphosate-tolerant weeds in soybean-producing edaphoclimatic microregions in Brazil. Weed Technology, vol. 33, no. 1, pp. 217-231. http://doi.org/10.1017/wet.2018.97
  » http://doi.org/10.1017/wet.2018.97
• MAGUIRE, J.D., 1962. Speed of germination aid in selection and evaluation for seedling emergence and vigor. Crop Science, vol. 2, no. 2, pp. 176-177. http://doi.org/10.2135/cropsci1962.0011183X000200020033x
  » http://doi.org/10.2135/cropsci1962.0011183X000200020033x
• MARIANI, F., VARGAS, L., AGOSTINETTO, D., NOHATTO, M.A., LANGARO, A.C. and DUARTE, T.V., 2016. Valor adaptativo e habilidade competitiva de azevém resistente e suscetível ao iodosulfuron em competição com o trigo. Pesquisa Agropecuária Brasileira, vol. 51, no. 6, pp. 710-719. http://doi.org/10.1590/S0100-204X2016000600002
  » http://doi.org/10.1590/S0100-204X2016000600002
• MARKUS, C., BARROSO, A.A.M., DALAZEN, G., RONCATTO, E. and MEROTTO JÚNIOR, A., 2021. Resistência de plantas daninhas aos herbicidas. In: A.A.M. BARROSO and A.T. MURATA, eds. Matologia: estudos sobre plantas daninha Jaboticabal: Fábrica da Palavra, 547 p.
• MELO, M.S.C., SILVA, D.C.P., ROSA, L.E., NICOLAI, M. and CHRISTOFFOLETI, P.J., 2015. Herança genética da resistência de capim-amargoso ao glyphosate. Revista Brasileira de Herbicidas, vol. 14, no. 4, pp. 296-305. http://doi.org/10.7824/rbh.v14i4.443
  » http://doi.org/10.7824/rbh.v14i4.443
• MENDONÇA, G.S., MARTINS, C.C., MARTINS, D. and COSTA, N.V., 2014. Ecophysiology of seed germination in Digitaria insularis ((L.) Fedde). Revista Ciência Agronômica, vol. 45, no. 4, pp. 823-832. http://doi.org/10.1590/S1806-66902014000400021
  » http://doi.org/10.1590/S1806-66902014000400021
• MONDO, V.H.V., CARVALHO, S.J.P.D., DIAS, A.C.R. and MARCOS FILHO, J., 2010. Efeitos da luz e temperatura na germinação de sementes de quatro espécies de plantas daninhas do gênero Digitaria. Revista Brasileira de Sementes, vol. 32, no. 1, pp. 131-137. http://doi.org/10.1590/S0101-31222010000100015
  » http://doi.org/10.1590/S0101-31222010000100015
• OLIVEIRA, E.F.D., SANTOS, P.R.R.D. and SANTOS, G.R.D., 2018. Seeds of weeds as an alternative host of phytopathogens. Arquivos do Instituto Biológico, vol. 85, no. 0, pp. 1-7. http://doi.org/10.1590/1808-1657000972017
  » http://doi.org/10.1590/1808-1657000972017
• ORZARI, I., MONQUERO, P.A., REIS, F.C., SABBAG, R.S. and HIRATA, A.C.S., 2013. Germinação de espécies da família Convolvulaceae sob diferentes condições de luz, temperatura e profundidade de semeadura. Planta Daninha, vol. 31, no. 1, pp. 53-61. http://doi.org/10.1590/S0100-83582013000100006
  » http://doi.org/10.1590/S0100-83582013000100006
• PETTER, F.A., SULZBACHER, A.M., SILVA, A.F., FIORINI, I.V.A., MORAIS, L.A. and PACHECO, L.P., 2015. Use of cover crops as a tool in the management strategy of sourgrass. Revista Brasileira de Herbicidas, vol. 14, no. 2, pp. 200-209. http://doi.org/10.7824/rbh.v14i3.432
  » http://doi.org/10.7824/rbh.v14i3.432
• PITELLI, R.A., 1985. Interferência de plantas daninhas em culturas agrícolas. Informe Agropecuário, vol. 11, pp. 16-27.
• PYON, J.Y., WHITNEY, A.S. and NISHIMOTO, R.K., 1977. Biology of sourgrass and its competition with buffelgrass and guineagrass. Weed Science, vol. 25, no. 2, pp. 171-174. http://doi.org/10.1017/S0043174500033191
  » http://doi.org/10.1017/S0043174500033191
• RADOSEVICH, S., HOLT, J. and GHERSA, C. 1997. Weed ecology: implications for vegetation management. 2nd ed. New York: Wiley, 589 p.
• SOCIEDADE BRASILEIRA DA CIÊNCIA DAS PLANTAS DANINHAS – SBCPD, 1995. Procedimentos para instalação, avaliação e análise de experimentos com herbicidas Londrina: SBCPD, 42 p.
• SEEFELDT, S.S., JENSEN, S.E. and FUERST, E.P., 1995. Log-logistic analysis of herbicide dose-response relationship. Weed Technology, vol. 9, no. 2, pp. 218-227. http://doi.org/10.1017/S0890037X00023253
  » http://doi.org/10.1017/S0890037X00023253
• SINGH, S. and SINGH, M., 2009. Effect of temperature, light and pH on germination of twelve weed species. Indian Journal of Weed Science, vol. 41, pp. 113-126.
• STREIBIG, J.C., 1988. Herbicide bioassay. Weed Research, vol. 28, no. 6, pp. 479-484. http://doi.org/10.1111/j.1365-3180.1988.tb00831.x
  » http://doi.org/10.1111/j.1365-3180.1988.tb00831.x
• TAKANO, H.K., OLIVEIRA JUNIOR, R.S., CONSTANTIN, J., BRAZ, G.B.P. and GHENO, E.A., 2017. Goosegrass resistant to glyphosate in Brazil. Planta Daninha, vol. 35, e017163071. http://doi.org/10.1590/s0100-83582017350100013
  » http://doi.org/10.1590/s0100-83582017350100013
• TAKANO, H.K., MELO, M.S.C., OVEJERO, R.F.L., WESTRA, P.H., GAINES, T.A. and DAYAN, F.E., 2020. Trp2027Cys mutation evolves in Digitaria insularis with cross-resistance to ACCase inhibitors. Pesticide Biochemistry and Physiology, vol. 164, pp. 1-6. http://doi.org/10.1016/j.pestbp.2019.12.011 PMid:32284114.
  » http://doi.org/10.1016/j.pestbp.2019.12.011
• TAKANO, H.K., OLIVEIRA JUNIOR, R.S.D., CONSTANTIN, J., BRAZ, G.B.P., FRANCHINI, L.H.M. and BURGOS, N.R., 2016. Resistência múltipla a atrazina e imazethapyr em picão-preto (Bidens pilosa). Ciência e Agrotecnologia, vol. 40, no. 5, pp. 547-554. http://doi.org/10.1590/1413-70542016405022316
  » http://doi.org/10.1590/1413-70542016405022316
• TRAVLOS, I., GAZOULIS, I., KANATAS, P., TSEKOURA, A., ZANNOPOULOS, S. and PAPASTYLIANOU, P., 2020. Key factors affecting weed seeds’ germination, weed emergence, and their possible role for the efficacy of false seedbed technique as weed management practice. Frontiers in Agronomy, vol. 2, pp. 1. http://doi.org/10.3389/fagro.2020.00001
  » http://doi.org/10.3389/fagro.2020.00001
• VILA-AIUB, M.M., NEVE, P. and ROUX, F., 2011. A unified approach to the estimation and interpretation of resistance costs in plants. Heredity, vol. 107, no. 5, pp. 386-394. http://doi.org/10.1038/hdy.2011.29 PMid:21540885.
  » http://doi.org/10.1038/hdy.2011.29
• WANG, W., WANG, W., WANG, P., WANG, X., WANG, L., WANG, C., ZHANG, C. and HUO, Z., 2023. Impact of straw return on soil temperature and water during the freeze-thaw period. Agricultural Water Management, vol. 282, pp. 108292. http://doi.org/10.1016/j.agwat.2023.108292
  » http://doi.org/10.1016/j.agwat.2023.108292

Publication Dates

• Publication in this collection
  11 Nov 2024
• Date of issue
  2024

History

• Received
  22 Jan 2024
• Accepted
  08 Sept 2024