Non-Target Site Resistance in Summer-Emerging Lolium rigidum and the Effect of Alternative Herbicides

Abstract

Herbicide resistance is an important weed management issue. Glyphosate is the most dominant herbicide, which controls a broad spectrum of weeds, including grasses such as Lolium rigidum. Lolium rigidum is a major weed of winter crops in Australia that is develo** glyphosate resistance in increasing numbers of populations and has been observed growing throughout summer in recent years. Three L. rigidum populations, one summer-emerging glyphosate-resistant (GR), one winter-emerging glyphosate-susceptible (GS), and one winter-emerging population with unknown resistance status (CC04), were analyzed for target-site resistance to glyphosate after confirming their resistance or susceptibility to glyphosate in a dose–response experiment. Population GR was obtained from plants that emerged in summer and contained plants that survived all rates of glyphosate applied (0 to 4560 g a.e. ha⁻¹). It was found to be 6.1 and 4.4 times more resistant than population GS across two experiments. Population CC04 was identified as susceptible. Plants from each population were analyzed for the presence of target-site mutations in the conserved region of the EPSPS gene; however, no mutations were identified that could cause resistance, suggesting non-target-site resistance in population GR. The effectiveness of alternative herbicides was also analyzed for each population. Paraquat was the most effective herbicide, with 0% survival across all populations. The ACCase-inhibiting herbicide clethodim was also highly effective (0 to 8% survival across populations). Other ACCase-inhibiting herbicides, propaquizafop, haloxyfop, and pinoxaden, were effective at controlling the two susceptible populations, CC04 and GS (0 to 36% and 0 to 20% survival, respectively), but were only moderately effective for controlling GR (28 to 51% survival). Paraquat and clethodim may be alternative options for controlling GR populations of L. rigidum and could be effective for use in management programs to slow the development of GR populations.

1. Introduction

Glyphosate is the most dominant herbicide for controlling weeds due to its non-selective mode of action allowing for high versatility in controlling a broad spectrum of weeds. It kills plants by inhibiting the enzyme 5-enolpyruvyl-shikimate-3-phosphate synthase (EPSPS), a key enzyme of the shikimate pathway [1]. The development of glyphosate-tolerant crops greatly increased the use of this herbicide; however, the increase in use has led to a rise in glyphosate-resistant (GR) weeds [2]. Glyphosate resistance has been detected in many different weed species but was first reported in L. rigidum [3,4], one of the major weed species of winter crops in Australia. Since the first reported incidence of glyphosate resistance in L. rigidum, resistance has been increasingly observed in more populations of this weed [5,6,7]. In addition, some populations of L. rigidum have evolved resistance to multiple herbicides, including diclofop, sulfometuron, and paraquat [8,9,10]. While L. rigidum is known as a winter annual species, recent reports of the weed’s occurrence during summer in the south-eastern region of Australia have shown that some populations of L. rigidum are capable of emerging outside their typical window [11]. This indicates that L. rigidum has the potential to cause greater economic loss to Australian agriculture through its effect on summer crops and raises concern around the potential for herbicide-resistant ryegrass to extend into summer.

The mechanisms by which weeds exhibit resistance to herbicides can be grouped into two main categories: target-site resistance (TSR) and non-target-site resistance (NTSR) [12]. TSR occurs when there is an alteration in the gene that encodes for the target protein of the herbicide, which can manifest as either a mutation in the gene leading to a change in the translated amino acid [7], or by affecting the copy number of the target gene [13]. NTSR covers a broader range of resistance mechanisms as it includes all mechanisms not related to the target-site, such as herbicide degradation [14], reduced leaf uptake [15], and reduced translocation [16] of the herbicide. NTSR has been reviewed more thoroughly by other authors [12,14,17]. Both TSR and NTSR have been observed in L. rigidum populations in Australia; however, as resistance status is specific to each population, it is important to expand resistance screening to include a larger pool of populations. This will help to increase the knowledge of L. rigidum resistance over more regions and will be helpful for identifying potential areas at risk of increasing herbicide resistance due to the exchange of resistant seeds between fields.

While non-herbicide control methods are used to help manage weeds, such as using cover crops [18], tillage [19], or harvest weed seed control [20], among others, herbicides are the main form of weed control. Therefore, with the increasing incidence of herbicide resistance, it is important to identify alternative herbicides that resistant populations are susceptible to. As cases of multiple herbicide-resistant populations have been observed, such as those mentioned above, GR populations of L. rigidum should be screened for resistance to other herbicides.

The aim of this study was to identify the resistance levels of L. rigidum populations which differed in seasonality, one summer GR, one winter GS, and one winter population of unknown glyphosate resistance, and to analyze the populations for the presence of target-site mutations in the conserved region of the EPSPS gene. Additionally, this study aimed to identify effective options for alternative herbicides of different modes of action.

2. Materials and Methods

2.1. Plant Material

Three L. rigidum populations were used in this study, consisting of one glyphosate-resistant (GR) population, one glyphosate-susceptible (GS) population, and one population of unknown glyphosate resistance status (CC04). Population GR was collected from Griffith, NSW, from plants that had emerged and grown throughout summer, while CC04 was collected from Croppa Creek, NSW, from plants that had emerged in autumn and grown during winter. Population GS is a common susceptible population of L. rigidum from Victoria. Populations GR and GS were grown together in the winter 2018 season at the Crop Research Unit of the University of Queensland’s Gatton campus to obtain sufficient seeds for all experiments. Seeds were stored in darkness at room temperature (~25 °C) until the initiation of experiments.

2.2. Glyphosate Dose–Response Experiment

A dose–response experiment was conducted in 12.5 cm diameter pots (14 cm height) in June 2019 (Experiment 1) and repeated in June 2020 (Experiment 2) at the Gatton campus of the University of Queensland (27.5392° S, 152.3355° E). Each pot contained five plants. At the four- to five-leaf stage, plants were sprayed with glyphosate at six different rates: 0 (control), 285, 570, 1140, 2280, and 4560 g a.e. ha⁻¹; with five replicates per treatment. Each treatment was applied via a research track sprayer (manufactured by Woodlands Road Engineering, Gatton, Australia) at a spray volume of 108 L/ha using Teejet XR flat fan (110015) nozzles at 2 kPa spray pressure (Teejet Spraying Systems Co., Wheaton, IL, USA). Plant survival was recorded 28 days after treatment (DAT) and plants that survived were dried in an oven at 70 °C for at least 72 h before dry weight data were taken.

2.3. EPSPS Sequencing

Leaves from five untreated plants of each population were obtained from seedlings for DNA extraction. DNA extraction was carried out via a modified version of the CTAB extraction method [21] using 100 mg of plant tissue. A NanoDrop (NanoDrop One, ThermoFisher, Waltham, MA, USA) was used to determine the nucleic acid concentration of each sample. PCR reactions were performed in a volume of 20 µL containing 30 ng template DNA, 4 µL 5x MyTaq reaction buffer (Bioline, Eveleigh, Australia), 0.3 µM of each primer AW1-Fwd (AACAGTGAGGAYGTYCACTACATGCT) and AW1-Rev (CGAACAGGAGGGCAMTCAGTGCCAAG) (Ngo et al. 2018), 0.2 µL MyTaq HS DNA polymerase (Bioline, Australia) and 13.6 µL water. PCR reactions were run in a T100 thermal cycler (Bio-Rad, Australia) with conditions including 3 min denaturing at 95 °C; 35 cycles of 30 s denaturation at 95 C, 30 s annealing at 57 °C, 45 s elongation at 72 °C, and a final extension for 7 min at 72 °C. PCR products were resolved in a 1.2% agarose gel, stained with GelRed (Biotium, Fremont, CA, USA), and visualized under UV light. PCR products were sequenced at the Australian Genome Research Facility, Brisbane, Australia, to obtain forward and reverse sequences.

2.4. Alternative Herbicide Response

A pot experiment was set up in June 2019 and repeated in June 2020 to analyze the effectiveness of alternative herbicides to glyphosate on the three populations of this study. Plants were grown in 12.5 cm diameter pots (14 cm height) with five replications of five plants per pot. Eight herbicides were sprayed on each population at recommended rates (

Table 1. Details of the alternative herbicides. All rates are field recommended rates for Lolium rigidum.

Active Constituents	Chemical Family	Mode of Action	Rate
Paraquat 360 g/L	Bipyridyls	Photosystem I inhibitor	600 g a.i. ha−1
Clethodim 240 g/L	Cyclohexanediones	Acetyl co-enzyme A carboxylase inhibitor	120 g a.i. ha−1 + 1% Supercharge
Propaquizafop 100 g/L	Aryloxyphenoxypropionates		30 g a.i. ha−1 + 0.5% Hasten
Haloxyfop 520 g/L			78 g a.i. ha−1 + 1% Hasten
Pinoxaden 100 g/L	Phenylpyrazoles		20 g a.i. ha−1 + 0.5% Adigor
Imazamox 33 g/L + Imazapyr 15 g/L	Imidazolinones	Acetolactate synthase inhibitor	25 + 11 g a.i. ha−1 + 1% Hasten
Pyroxsulam 150 g/kg + Halauxifen 50 g/kg	Triazolopyrimidines + Arylpicolinate	Acetolactate synthase inhibitor + disruptor of plant cell growth	15 + 5 g a.i. ha−1 + 0.25% BS1000
Glufosinate 200 g/L	Phosphinic acids	Glutamine synthetase inhibitor	750 g a.i. ha−1

Adigor^® contains 440 g L⁻¹ methyl esters of canola oil fatty acids; HASTEN™ contains 704 g L⁻¹ ethyl and methyl esters of vegetable oil with 196 g L⁻¹ nonionic surfactants; Supercharge^® is 471 g L⁻¹ paraffin oil; and BS1000 contains 1000 g L-1 alcohol alkoxylate.

) in addition to a control with no herbicide treatment. Herbicides were sprayed at the four to five-leaf stage using the same sprayer as the dose–response experiment. Plant survival was recorded at 28 DAT and plants that survived were dried in an oven at 70 °C for at least 72 h before dry weight data were taken.

2.5. Alternative Herbicide Dose–Response Experiment

A dose–response experiment was conducted in 12.5 cm diameter pots (14 cm height) in July 2019 (Experiment 1) and repeated in June 2021 (Experiment 2) at the Gatton campus of the University of Queensland (27.5392° S, 152.3355° E). Each pot contained five plants. Three treatments were set up for three different herbicides: propaquizafop, imazamox + imazapyr, and glufosinate. At the four to five-leaf stage, plants were sprayed with either propaquizafop (0, 7.5, 15, 30, 60, and 120 g a.i. ha⁻¹), imazamox + imazapyr (0, 6.1875, 12.375, 24.75, 49.5 and 99 g a.i. ha⁻¹), or glufosinate (0, 187.5, 375, 750, 1500, and 3000 g a.i. ha⁻¹), with five replicates application rate for each of the three herbicides. Each treatment was applied via a research track sprayer (manufactured by Woodlands Road Engineering, Gatton, Australia) at a spray volume of 108 L/ha using Teejet XR flat fan (110015) nozzles at 2 kPa spray pressure (Teejet Spraying Systems Co., Wheaton, IL). Plant survival was recorded 28 days after treatment (DAT) and plants that survived were dried in an oven at 70 °C for at least 72 h before dry weight data were taken.

2.6. Data Analysis

Each experimental run contained five replicates for each treatment. Paired t-tests were performed to determine differences between experiments using IBM SPSS Statistics ver. 27 (IBM Corp., 2020, Armonk, NY). As differences were observed between experimental runs for the glyphosate–dose response experiment and alternate herbicide experiment, data are presented separately for each run. A three-parameter logistic model was fitted to the survival and dry weight data for the dose–response experiment using the following equation:

$$y=\frac{a}{1+{\left(\frac{x}{x_0}\right)}^b}$$

(1)

where a is the maximum survival or dry weight, b is the slope, and x₀ is the herbicide dose required to reduce 50% of survival (LD₅₀) or dry weight (GR₅₀). To test the effect of herbicide and population on survival and dry weight in the alternate herbicide experiment, a two-way ANOVA was performed using the General Linear Model function in SPSS, with herbicide and population as the independent factors, and survival percent or dry weight as the dependent factors.

3. Results and Discussion

3.1. Glyphosate Dose–Response Experiment

A dose–response experiment was carried out to confirm that population GR was resistant to glyphosate and to determine the resistance status of CC04. Glyphosate was unable to completely control GR across all rates applied (Figure 1 and Figure 2), thus confirming its status as resistant. Both CC04 and GS showed similar responses to glyphosate and were completely controlled at rates higher than 570 g a.e. ha⁻¹ in experiment 2 (Figure 2), while there was low survival at rates of 1140 and 2280 g a.e. ha⁻¹ in experiment 1 (Figure 1).

A three-parameter log-logistic model was used to determine the LD₅₀ values for the three L. rigidum populations. The susceptible population GS displayed an LD₅₀ of 526 and 542 g a.e ha⁻¹ in Experiment 1 and 2, respectively (

Table 2. Glyphosate dose required to kill 50% of plants (LD₅₀) or cause a 50% reduction in growth (GR₅₀), and the level of resistance compared to the susceptible population (R/S).

Population	LD50		R/S		GR50		R/S
	2019	2020	2019	2020	2019	2020	2019	2020
	---g a.e. ha−1---				---g a.e. ha−1---
GS	526	542	-	-	506	288	-	-
CC04	324	542	0.6	1.0	406	276	0.8	1.0
GR	3185	2404	6.1	4.4	2265	2413	4.5	8.4

), which was similar to the population of unknown resistance status (CC04) which had LD₅₀ values 0.6 and 1 times that of GS for experiment 1 and 2, respectively. The average rate of survival for CC04 was the same as GS at each glyphosate dose in experiment 2. The LD₅₀ for these two populations was higher than is often seen for susceptible populations of L. rigidum [5,7,10,22], which could be due to environmental effects. Temperature is known to alter the effectiveness of glyphosate [23,24,25] and higher temperatures have previously been shown to increase the resistance level of L. rigidum [25]. However, temperature data for this experiment were not compared with data from studies showing lower LD₅₀ values, so the effect of data on resistance in this study cannot be confirmed. The low rate of survival of populations GS and CC04 at 1140 and 2280 g a.e. ha⁻¹, as well as the greater LD₅₀ in comparison to other susceptible populations of L. rigidum, may indicate that these populations are develo** resistance in some members of the population. However, as population CC04 was collected from the roadside it is unlikely to have been regularly sprayed with glyphosate, and as such would have no selection pressure to evolve glyphosate resistance.

Population GR was confirmed by the dose–response experiment to be resistant with 6.1 and 4.4 times greater LD₅₀ values than GS in Experiment 1 and 2, respectively (Table 2). GR also maintained 100% survival up to 570 g a.e. ha⁻¹ in experiment 1 and 84% survival at the same rate in Experiment 2. The LD₅₀ values of GR are higher than those seen in other studies for resistant L. rigidum [5,7], which may also indicate that there was an increased level of resistance for all populations due to environmental factors. However, Yu et al. [10] also showed a similar LD₅₀ in L. rigidum as seen for GR in Experiment 2, and Collavo and Sattin [22] have shown far greater levels of resistance in a L. rigidum population.

As with the LD₅₀ values, the two susceptible populations (CC04 and GS) had similar GR₅₀ values to one another for both experiments (Table 2). Glyphosate had less of a growth-reducing effect on both populations in Experiment 1 with GR₅₀ values of 406 and 506 g a.e. ha⁻¹ for population CC04 and GS, respectively, while GR₅₀ values in Experiment 2 were 276 and 288 g a.e. ha⁻¹, respectively. This indicates that while these two populations are not completely controlled at the standard glyphosate rate, any surviving populations will be stunted at rates of 285 g a.e. ha⁻¹ and above. The resistant population (GR) had the lowest growth reduction with a GR₅₀ of 2265 and 2413 g a.e. ha⁻¹ in experiment 1 and 2, respectively. As such, population GR was observed to be 4.5 and 8.4 times more resistant to glyphosate than GS in Experiment 1 and 2, respectively (Table 2). Overall, dry weight decreased with increasing glyphosate dose for all populations. In Experiment 2, no plants survived for populations CC04 and GS at rates of 1140, 2280, and 4560 g a.e. ha⁻¹, and as such, there was complete inhibition of new growth. In Experiment 1, however, there was still low survival at rates of 1140 and 2280 g a.e. ha⁻¹, which allowed new growth in some plants.

These results show that rates of glyphosate up to 4560 g a.e. ha⁻¹ are insufficient to control the summer population GR. As such, it suggests that alternative weed control options should be considered and demonstrates that GR-resistant L. rigidum could become an issue in summer crop** systems, such as cotton (Gossypium hirsutum L.). The results also show that a population initially thought to be susceptible can survive the application of the standard rate used in Australia.

3.2. EPSPS Sequencing

Mutations in the gene sequence of the target gene can cause TSR when the mutation changes the amino-acid sequence so that the enzyme’s function is not inhibited by the herbicide [26]. Target-site resistance to glyphosate occurs when there is a mutation in the sequence of the EPSPS gene [27]. Mutations have been found in multiple codons of the EPSPS gene in L. rigidum but are mostly found in the Pro-106 codon [5,7,10,28,29].

Sequence data for each population revealed no missense mutations in any of the populations. As such, no amino acid substitutions were observed in any population, suggesting that the resistance to glyphosate observed in population GR was likely due to NTSR mechanisms and further confirming the resistance status of populations CC04 and GS as susceptible to glyphosate. Silent mutations were observed in two codons for some of the plants analyzed (

Table 3. Aligned nucleotide sequences of the conserved region of EPSPS for populations of Lolium rigidum. Amino acids are numbered according to Baerson et al. (2002). ¹ Silent mutation, ² Missense mutation, ³ Y = T or C, ⁴ K = G or T, ⁵ W = A or T, ⁶ R = A or G, ⁷ S = G or C.

Amino Acid Number:	96	97	98	99	100	101	102	103	104	105	106	107	108
Amino acid:	Phe	Leu	Gly	Asn	Ala	Gly	Thr	Ala	Met	Arg	Pro	Leu	Thr
Sequence:	TTC	TTG	GGC	AAC	GCT	GGA	ACT	GCG	ATG	CGA	CCA	TTG	ACG
GS	TTC	TTG	GGC	AAC	GCT	GGA	ACT	GCR1,6	ATG	CGA	CCA	TTG	ACG
GR	TTC	TTG	GGS1,7	AAC	GCT	GGA	ACT	GCR1,6	ATG	CGA	CCA	TTG	ACG
CC04	TTC	TTG	GGS1,7	AAC	GCT	GGA	ACT	GCR1,6	ATG	CGA	CCA	TTG	ACG

), however, these mutations did not result in any amino acid substitutions and, therefore, are unlikely to confer any resistance. For populations GR and GS, the plants showed either GGC or GGG at codon 98, which both result in the amino acid glycine. For all populations, the plants showed either GCG or GCA at codon 103, which both result in the amino acid alanine. These results confirm the susceptibility to glyphosate observed in the dose–response experiment for populations CC04 and GS but do not identify the resistance mechanism that confers resistance in population GR. As such, further work is required to understand the mechanisms behind the resistance of GR to glyphosate.

Target-site resistance cannot be ruled out as a cause of resistance in this population as this type of resistance also includes changes to the gene copy number. An increase in the gene copy number of the EPSPS gene has been previously linked with glyphosate resistance due to the increased number of EPSPS enzymes synthesized [13,30]. It should also be noted that target-site mutations may be present in other plants of the population. Further testing of a larger batch of plants may identify target-site mutations.

Due to the lack of target-site mutations in the resistant population (GR), further experiments are required to determine whether NTSR mechanisms have caused the resistance. NTSR due to altered glyphosate translocation has been previously reported in L. rigidum [31]. However, NTSR can also be due to the degradation of the herbicide by detoxification [14,32]. The resistance observed in GR could also be due to a combination of these mechanisms or altogether new mechanisms that have yet to be identified.

3.3. Alternative Herbicide Response

Eight herbicides were tested on all three populations to determine the effectiveness of alternative herbicides to glyphosate (

Table 4. Seedling survival of three Lolium rigidum populations to different herbicide treatments in two experimental runs (2019 and 2020). Data are presented as the mean ± the standard error (SE) of the mean.

Treatment	Survival
	2019			2020
	CC04	GR	GS	CC04	GR	GS
	% ± SE
Control	100.0 ± 0.0	100.0 ± 0.0	100.0 ± 0.0	100.0 ± 0.0	100.0 ± 0.0	100.0 ± 0.0
Paraquat	0.0 ± 0.0	0.0 ± 0.0	0.0 ± 0.0	0.0 ± 0.0	0.0 ± 0.0	0.0 ± 0.0
Clethodim	4.2 ± 4.2	7.6 ± 3.5	0.0 ± 0.0	0.0 ± 0.0	4.0 ± 4.0	0.0 ± 0.0
Propaquizafop	0.0 ± 0.0	50.6 ± 8.3	0.0 ± 0.0	0.0 ± 0.0	44.0 ± 7.5	12.0 ± 12.0
Haloxyfop	0.0 ± 0.0	29.0 ± 9.7	2.4 ± 2.4	0.0 ± 0.0	28.0 ± 4.9	16.0 ± 4.0
Pinoxaden	35.7 ± 17.6	48.5 ± 5.2	20.2 ± 8.7	0.0 ± 0.0	48.0 ± 8.0	8.0 ± 4.9
Imazamox + Imazapyr	86.0 ± 8.0	27.0 ± 11.4	18.7 ± 8.0	44.0 ± 9.8	12.0 ± 8.0	0.0 ± 0.0
Pyroxsulam + Halauxifen	97.2 ± 2.8	85.4 ± 6.0	80.1 ± 7.5	68.0 ± 16.2	72.0 ± 10.2	68.0 ± 8.0
Glufosinate	78.7 ± 5.37	93.2 ± 3.1	76.1 ± 5.3	88.0 ± 4.9	90.0 ± 5.8	96.0 ± 4.0
LSD	53.3	42.2	45.7	54.5	44.1	53.0

and

Table 5. Dry weight of three Lolium rigidum populations after treatment with different herbicides in two experimental runs (2019 and 2020). Data are presented as the mean dry matter per plant ± the standard error (SE) of the mean. The data in parentheses represent the percentage of dry weight reduction compared to the control treatment.

Treatment	Dry matter per plant
	2019			2020
	CC04	GR	GS	CC04	GR	GS
	mg ± SE
Control	118.9 ± 15.3	94.9 ± 7.0	62.1 ± 1.0	428.2 ± 22.9	443.1 ± 25.2	463.4 ± 27.4
Paraquat	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)
Clethodim	2.3 ± 2.3 (98)	31.3 ± 15.2 (67)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	8.5 ± 8.5 (98)	0.0 ± 0.0 (100)
Propaquizafop	0.0 ± 0.0 (100)	84.2 ± 7.2 (11)	0.0 ± 0.0 (100)	0.0 ± 0.0 (100)	401.0 ± 88.0 (9)	91.6 ± 91.6 (80)
Haloxyfop	0.0 ± 0.0 (100)	85.8 ± 28.5 (10)	15.2 ± 15.2 (76)	0.0 ± 0.0 (100)	421.2 ± 99.0 (5)	294.5 ± 114.4 (36)
Pinoxaden	20.4 ± 10.1 (83)	60.8 ± 7.0 (36)	42.3 ± 15.9 (32)	0.0 ± 0.0 (100)	386.3 ± 96.8 (13)	27 ± 17.3 (94)
Imazamox + Imazapyr	38.8 ± 12.4 (67)	108.2 ± 25.6 (-14)	40.8 ± 14.1 (34)	80.9 ± 37.2 (81)	32.9 ± 26.8 (93)	0.0 ± 0.0 (100)
Pyroxsulam + Halauxifen	46.5 ± 2.5 (61)	49.2 ± 7.9 (48)	29.2 ± 2.4 (53)	288.4 ± 130.6 (33)	141.5 ± 36.2 (68)	179.1 ± 41.8 (61)
Glufosinate	29.4 ± 1.5 (75)	37.3 ± 6.2 (61)	54.4 ± 2.5 (12)	175.7 ± 46.0 (59)	161.9 ± 52.6 (63)	164.2 ± 37.0 (65)
LSD	30.0	52.1	36.5	235.1	260.6	241.4

). There was a significant interaction effect on both survival % and dry weight per plant between population and herbicide in both Experiment 1 (p ≤ 0.001) and Experiment 2 (p ≤ 0.001).

Paraquat was the most effective herbicide, controlling 100% of plants for all populations and in both experiments (Table 4). As such, there was no new dry matter production for any of these plants. Paraquat is a fast-acting non-selective herbicide that diverts electrons from Photosystem I and leads to a chain of reactions that ruptures cell membranes [33]. The complete control of all populations in this study suggests that this herbicide would be an effective substitute for glyphosate or could be used following glyphosate to kill any surviving weeds after the initial herbicide application. It could also be used in rotation with glyphosate. Paraquat resistance has previously been identified in L. rigidum [10,34]. Busi and Powles [35] also demonstrated the development of paraquat resistance when exposed to repeat selection under low doses of glyphosate. As such, there is the possibility for both the GR and GS L. rigidum populations to evolve paraquat resistance. While resistance to both glyphosate and paraquat is rare, it has been previously observed [10].

The enzyme acetyl co-enzyme A carboxylase (ACCase) is a critical component of the fatty acid biosynthesis pathway in plants [36]. In this study, the effectiveness of five ACCase-inhibiting herbicides was tested on the three L. rigidum populations (Table 4 and Table 5). Clethodim application controlled most plants across all three populations and over both experiments, with survival ranging from 0–8%. Corresponding to this was a large decline in dry weight per plant, ranging from 67–100% reductions in comparison to controls. Clethodim has been extensively used in Australia to control L. rigidum plants in dicotyledonous crops, which has led to many populations develo** resistance to clethodim [37]. As such, while this is an effective alternative to glyphosate, it should be used cautiously in populations without clethodim resistance to prevent further cases of resistance.

Population GR was the most resistant of the three populations to the ACCase-inhibiting herbicides propaquizafop, haloxyfop, and pinoxaden, ranging from 28–51% survival. Additionally, these three herbicides exhibited less of a growth-reducing effect on the surviving plants of GR than the other populations (5–36% reduction compared to control for GR, 83–100% for CC04, and 32–100% for GS). Therefore, while these herbicides can control some plants of the GR population, they may not be a good option for this population. Multiple herbicide resistance to both propaquizafop and haloxyfop, in addition to glyphosate and paraquat resistance, has occurred in a population of L. rigidum [10]. As such, the use of these herbicides may lead to increased resistance in this population. Pinoxaden was less effective in experiment 1 compared to Experiment 2 for populations CC04 and GS, with survival of 36 and 20% in Experiment 1 for CC04 and GS, respectively, compared with 0 and 8% in Experiment 2 for CC04 and GS, respectively. Propaquizafop and haloxyfop completely controlled CC04 in both experiments, while GS possessed some survival (0 to 16%).

While these herbicides may not be highly effective for controlling the GR population, they could be a good option to use in rotation with glyphosate to slow the development of herbicide resistance in susceptible populations. These ACCase-inhibiting herbicides are recommended for controlling grasses in broadleaf crops and, as such, they should only be used in fallow fields for cereal crops. Pinoxaden, on the other hand, has been observed to control grass weeds in wheat (Triticum aestivum L.) and barley (Hordeum vulgare) [38], although it may need to be supplied in a mixture with other modes of action herbicides [39].

Both GR and GS had low survival under the acetolactate synthase (ALS), inhibiting herbicide combination imazamox + imazapyr, while CC04 had the highest survival in both experiments. Imazamox + imazapyr had a larger growth-reducing effect in Experiment 2 than in Experiment 1, with 81–100% growth reductions compared to the control in Experiment 2, while CC04 and GS ranged from 34–67% reduction in Experiment 1 and GR produced 14% greater dry weight per plant compared to the control. This study showed a range of effectiveness for imazamox + imazapyr, indicating differences due to population and environment. Environmental differences between years, such as temperature and humidity, may have caused the difference in control between experiments; however, we did not measure these parameters. As such, while there is potential for this herbicide to control L. rigidum, it may be ineffective in some circumstances.

When sprayed with pyroxsulam + halauxifen, an ALS-inhibiting herbicide and a synthetic auxin herbicide, respectively, most plants survived for all populations across both experiments (Table 4). While survival ranged from 68–97% across populations, pyroxsulam + halauxifen had a moderate growth-reducing effect, where dry weight per plant was reduced by 33–68% (Table 5). The last herbicide tested, glufosinate, also showed a low ability to control each population across both experiments, with a survival rate ranging from 76–96%. Despite high survival rates, there was a moderate to large growth reduction for each population (ranging from 59–75%), except for GS in experiment 1 (12% reduction). Pyroxsulam + halauxifen and glufosinate were not effective alternatives to glyphosate for controlling these populations of L. rigidum, regardless of glyphosate resistance status. As some plants were killed and the surviving plants showed reductions in growth, these herbicides may reduce the number of seeds produced from infestations of L. rigidum but cannot be relied upon to control this weed.

3.4. Alternative Herbicide Dose–Response Experiment

Three herbicides were selected following the alternative herbicide response experiment to further elucidate their ability to control the three populations. Propaquizafop was selected due to its ability to control the two glyphosate-susceptible populations, CC04 and GS, but not GR. Imazamox + imazapyr was chosen due to its reduced control of the glyphosate-susceptible population CC04 compared with GR. Glufosinate was chosen due to its low efficacy to control any of the three populations. A dose–response experiment was carried out for these three herbicides to further identify their effectiveness for controlling glyphosate-susceptible and resistant L. rigidum.

Propaquizafop was effective in controlling most plants above 15 g a.i. ha⁻¹ for CC04 and GS, with only a few plants surviving at higher concentrations (Figure 3). However, some GR plants were able to survive at concentrations of up to 120 g a.i. ha⁻¹. Resistance to propaquizafop was previously observed by Yu et al. [10] in L. rigidum with higher rates of survival (>50%) at applications rates up to 200 g ha⁻¹. The low rate of survival in the GR population at 120 g a.i. ha⁻¹ may indicate that this population is also develo** resistance to Propaquizafop. Imazamox + Imazapyr controlled most plants of each population at concentrations above 24.75 g a.i. ha⁻¹ and completely controlled all populations at the highest concentration of 99 g a.i. ha⁻¹; however, a low rate of survival was observed at 49.5 g a.i. ha⁻¹ (Figure 4). While a low rate of plants did survive at these concentrations in Experiment 2, the biomass was reduced. This low rate of survival may be an indication of the populations develo** resistance. Broster et al. [40] identified populations of L. rigidum with resistance to imazamox + imazapyr, as well as several populations develo** resistance (survival rates between 10–19%) with plants sprayed with 48 g a.i. ha⁻¹. Glufosinate was only effective at rates of 1500 g a.i. ha⁻¹ and above in Experiment 1 but showed greater effectiveness on each population at lower concentrations in Experiment 2 (Figure 5). Population CC04 was completely controlled at rates of 1500 g a.i. ha⁻¹ and above. All populations had greater survival at lower application rates in experiment 1, which may be due to temperature differences at the time of each experiment (higher temperatures in experiment 1 due to delayed sowing). Glufosinate has shown varying effectiveness under different temperatures in Raphanus raphanistrum, although it was less effective under lower temperatures rather than higher temperatures [41]. The survival of some L. rigidum plants to 1500 g a.i. ha⁻¹ may indicate the presence of some glufosinate-resistant plants.

A three-parameter log-logistic model was used to determine the LD₅₀ values for CC04, GR, and GS. Populations CC04 and GS both had similar LD₅₀ values for the propaquizafop treatment, with values of 7.3 and 8.5 g a.i. ha⁻¹ for CC04 and 8.8 and 8.7 g a.i. ha⁻¹ for GS in Experiment 1 and 2, respectively (

Table 6. Propaquizafop dose required to kill 50% of plants (LD₅₀) or cause a 50% reduction in growth (GR₅₀).

Population	LD50		GR50
	2019	2021	2019	2021
	---g a.i. ha−1---		---g a.i. ha−1---
GS	8.8	8.7	10.4	53.9
CC04	7.3	8.5	7.6	8.9
GR	11.8	15.5	569.0	34.4

). For the imazamox + imazapyr treatment, population GS had the lowest LD₅₀ values of 9.7 and 10.2 g a.i. ha⁻¹, with LD₅₀ values for CC04 increasing to 13.9 and 13.9 g a.i. ha⁻¹ for Experiment 1 and 2, respectively (

Table 7. Imazamox + Imazapyr dose required to kill 50% of plants (LD₅₀) or cause a 50% reduction in growth (GR₅₀).

Population	LD50		GR50
	2019	2021	2019	2021
	---g a.i. ha−1---		---g a.i. ha−1---
GS	9.7	10.2	23.5	6.5
CC04	13.9	13.9	52.0	8.1
GR	21.4	11.3	15.2	6.5

). Glufosinate was less effective in the first experiment, where populations GS, CC04, and GR had LD₅₀ values of 1665, 901, and 1273 g a.i. ha⁻¹, respectively, compared with 439, 366, and 569 g a.i. ha⁻¹, respectively, in Experiment 2 (

Table 8. Glufosinate dose required to kill 50% of plants (LD₅₀) or cause a 50% reduction in growth (GR₅₀).

Population	LD50		GR50
	2019	2021	2019	2021
	---g a.i. ha−1---		---g a.i. ha−1---
GS	1665	439	324	425
CC04	901	366	686	610
GR	1273	569	460	600

).

In addition to survival %, dry weight measurements were also recorded (Figure 6, Figure 7 and Figure 8), and GR₅₀ values were calculated based on dry weight per plant (Table 6, Table 7 and Table 8). Population CC04 had the lowest GR₅₀ value when treated with propaquizafop, at 7.6 and 8.9 g a.i. ha⁻¹ for Experiment 1 and 2, respectively. GR₅₀ values varied across experiments for GS and GR populations treated with propaquizafop, with values of 10.4 and 53.9 g a.i. ha⁻¹ for GS in Experiments 1 and 2, respectively, and 596.0 and 34.4 g a.i. ha⁻¹ for GR in Experiments 1 and 2, respectively. The effect of herbicide on biomass reduction also differed between experiments for plants treated with imazamox + imazapyr. Population CC04 was less sensitive to Imazamox + Imazapyr than GS and GR, with GR₅₀ values of 52.0 and 8.1 g a.i. ha⁻¹ for Experiment 1 and 2, respectively. GS and GR each had the same GR₅₀ value of 6.5 g a.i. ha⁻¹ in Experiment 2, although GS had a higher GR₅₀ value of 23.5 g a.i. ha⁻¹ in Experiment 1 compared with 15.2 g a.i. ha⁻¹ for population GR. Population CC04 was also less sensitive to glufosinate, in terms of the effect on biomass, than populations GS and GR, with GR₅₀ values of 686 and 610 g a.i. ha⁻¹ for Experiment 1 and 2, respectively. GR₅₀ values were lowest for population GS, at 324 and 425 g a.i. ha⁻¹ for Experiment 1 and 2, respectively. GR₅₀ values for population GR ranged from 460 to 600 g a.i. ha⁻¹ across Experiment 1 and 2, respectively.

4. Conclusions

This study identified herbicide resistance in a summer population of L. rigidum without target-site mutations. Herbicide resistance conferred by NTSR is problematic, as the mechanism of resistance may confer resistance to multiple herbicides with different modes of action. As such, populations such as GR may require different methods for controlling glyphosate resistance than resistant populations possessing TSR. The testing of alternative herbicides to glyphosate revealed paraquat to be a highly effective alternative herbicide to glyphosate for all populations tested. ACCase-inhibiting herbicides were effective in controlling most plants of the susceptible populations CC04 and GS. These herbicides were only moderately effective for controlling the GR population, except for clethodim, which reduced survival to 4–8%. Therefore, paraquat and clethodim would be effective alternative herbicides for controlling these populations. Paraquat and clethodim could be implemented in L. rigidum management as methods to slow the development of glyphosate resistance, provided that there is no resistance to these herbicides. Dose–response experiments for propaquizafop, imazamox + imazapyr, and glufosinate did not find any resistant populations.