Multiple Resistance to PS II-Inhibiting and ALS-Inhibiting Herbicides in Common Lambsquarters (Chenopodium album L.) from China

Abstract

Chenopodium album is a troublesome weed in soybean fields in China. Many C. album populations have evolved resistance to herbicides and pose a growing challenge to weed management. This study characterizes the molecular and physiological resistance mechanisms in C. album populations against ALS- and PSII-inhibiting herbicides, focusing on thifensulfuron-methyl and bentazone. Dose-response assays confirmed significant resistance in two populations (R1 and R2), with resistance index values of 5.28 and 6.51 for thifensulfuron-methyl, and 4.83 and 5.10 for bentazone. Herbicide target gene amplification and sequence analysis showed an Ala-122-Thr substitution in the ALS but no psbA mutation in R1, while no ALS or psbA mutation was identified in R2. ALS enzyme assays further supported the resistance in R1. Cross-resistance tests indicated that R1 and R2 populations exhibited low-level resistance to oxyfluorfen and acifluorfen, but no detectable resistance to cloransulam-methyl, flumetsulam, or fomesafen. These findings highlight the need for integrated weed management strategies, including herbicide diversification and metabolic resistance monitoring, to mitigate the further evolution of resistance.

1. Introduction

Acetolactate synthase (ALS) is a crucial enzyme responsible for the biosynthesis of branched-chain amino acids, including valine, leucine, and isoleucine [1]. This enzyme is the target of five major classes of commercially used herbicides: sulfonylureas (SUs), imidazolinones (IMIs), triazolopyrimidines (TPs), pyrimidinyl thiobenzoates (PTBs), and sulfonyl-aminocarbonyl-triazolinones (SCTs) [2,3,4,5,6]. The widespread adoption of ALS-inhibiting herbicides is attributed to their high efficacy, broad-spectrum weed control, and relatively low toxicity to non-target organisms [7]. However, the repeated and intensive use of these herbicides has led to the rapid evolution of herbicide resistance in weed populations. To date, resistance to ALS-inhibiting herbicides has been confirmed in 273 weed species, including 156 dicotyledonous and 117 monocotyledonous species [8].

With the rise of ALS-inhibitor resistance, many agricultural systems have shifted towards using photosystem II (PSII)-inhibiting herbicides as alternative chemical control measures. These herbicides disrupt the photosynthetic electron transport chain, effectively managing herbicide-resistant weeds. However, resistance to PSII-inhibiting herbicides has also emerged due to selective herbicide pressure.

One of the primary mechanisms underlying resistance to ALS- and PSII-inhibiting herbicides is target-site resistance (TSR), which results from specific mutations in herbicide target genes. Resistance to ALS inhibitors is commonly associated with mutations in amino acid residues at key positions such as Ala-122, Pro-197, Ala-205, Phe-206, Asp-376, Arg-377, Trp-574, Ser-653, and Gly-654, which alter herbicide binding and efficacy [8]. The Pro-197 mutation, in particular, has been widely linked to resistance against sulfonylureas and triazolopyrimidines, whereas mutations at Asp-376 and Trp-574 confer resistance across all five classes of ALS inhibitors [9,10,11]. Similarly, resistance to PSII inhibitors has been associated with mutations in the psbA gene, which encodes the D1 protein in the photosystem II complex. Specific amino acid changes, including those at Leu218, Val219, Ala251, Phe255, Ser264, Asn266, and Phe274, have been shown to reduce herbicide binding and effectiveness [12,13].

Common lambsquarters (Chenopodium album L.), an annual broadleaf weed, is one of the most problematic weed species globally. It has a high reproductive capacity, with a single plant capable of producing over 70,000 seeds [14]. In northern China, this weed is a major concern in soybean fields, where it competes with crops for essential resources, significantly reducing yield and quality [15,16]. Previous studies have reported that its density in spring soybean fields can reach up to 2.4 plants per square meter [17]. Traditionally, ALS-inhibiting herbicides have been widely used to control C. album, but continuous application has led to the development of resistance in multiple regions, including Canada, Finland, the United States, and China [8].

In recent years, frequent herbicide applications in northern Chinese soybean fields have driven the evolution of resistance to multiple herbicides in C. album populations. The present study aims to (1) determine the resistance levels of two suspected resistant C. album populations to thifensulfuron-methyl and bentazone, and (2) investigate the molecular and physiological resistance mechanisms in these populations.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

To investigate herbicide resistance in Chenopodium album, seed samples were collected in 2019 from different locations in Heilongjiang Province, China. A susceptible (S) population was obtained from a field with no history of herbicide use (N 48°39′, E 126°17′). Two suspected resistant populations, R1 (N 49°19′, E 125°31′) and R2 (N 49°14′, E 125°53′), were collected from fields with over ten years of continuous application of ALS-inhibiting (thifensulfuron-methyl) and PSII-inhibiting (bentazone) herbicides. To enhance germination, seeds were soaked in a 200 mg·L⁻¹ gibberellin (GA₃) solution for 12 h before sowing. Twenty seeds were sown in each plastic pot (9 cm diameter) filled with sterilized soil. Seedlings were cultivated in a controlled greenhouse environment with day/night temperatures of 30 ± 3 °C (14 h light) and 25 ± 3 °C (10 h dark), with sufficient water and nutrients to ensure healthy growth. When seedlings reached the three- to four-leaf stage, they were thinned to six uniform plants per pot, ensuring morphological consistency across replicates. This growth stage was selected for herbicide application because it represents an early, actively growing period in the plant’s development, which enhances the accuracy and reproducibility of herbicide resistance assessments due to increased sensitivity to treatment.

2.2. Whole-Plant Dose–Response Experiment

Herbicide resistance was assessed through dose–response assays using a laboratory sprayer (3WP-2000, Nanjing Agricultural Mechanization Research Institute, Nanjing, China) equipped with a flat-fan nozzle delivering 450 L·ha⁻¹. Treatments were applied when plants reached the three- to four-leaf stage. Herbicide rates were selected based on preliminary experiments to ensure accurate characterization of dose–response curves and precise calculation of GR₅₀ values for both susceptible and resistant populations. Bentazone (BASF Plant Protection Co., Ltd., Jiangsu, China) was applied at 0, 22.5, 45, 90, 180, 360, and 720 g a.i.·ha⁻¹ for the susceptible (S) population, and at 0, 90, 180, 360, 720, 1440, and 2880 g a.i.·ha⁻¹ for the resistant (R1 and R2) populations. Thifensulfuron-methyl (Jiangsu Ruidong Pesticide Co., Ltd., Jiangsu, China) was applied at 0, 2.81, 5.63, 11.25, 22.5, 45, and 90 g a.i.·ha⁻¹ for the S population, and at 0, 11.25, 22.5, 45, 90, 180, and 360 g a.i.·ha⁻¹ for the R1 and R2 populations. The higher dose ranges for the resistant populations were based on prior findings indicating strong resistance.

The experiment followed a completely randomized design with three biological replicates (pots) per herbicide dose. Each treatment was repeated in two independent experimental runs to ensure reproducibility. Visual injury ratings and aboveground biomass were assessed 21 days after treatment, allowing sufficient time for herbicide effects to manifest and enabling differentiation between transient damage and actual survival or regrowth in resistant individuals.

2.3. PsbA and ALS Gene Sequence Analysis

To identify potential genetic mutations associated with resistance, fresh leaf samples were collected from 10 untreated plants per population (S, R1, and R2) following the dose–response experiment. Genomic DNA extraction was performed using a commercial DNA extraction kit (Tiangen Biochemical, Beijing, China). Polymerase chain reaction (PCR) amplifications targeting psbA and ALS genes were carried out using previously reported primer sets (

Table 1. Summary of primers used in this study.

Primers	Sequence (5′-3′)	Amplicon	Tm (°C)	Purpose of
		Length (bp)		Primers
psbA-680F	TTTCCGTCTGGGTATGCGTC	680	58.1	Amplify the psbA
psbA-680R	AGATGGAGCTTCGATAGCGG
psbA-182F	AACCGGAGCCGAATATGCAA	182	56.3	qRT–PCR analysis of psbA gene
psbA-182R	GTGGTTATACAACGGTGGTCCT
β-actin F	TCCATAATGAAGTGTGATGT	129	57.5	qRT–PCR analysis of β-actin gene
β-actin R	GGACCTGACTCGTCATACTC
ALS-853F	TTTGCCCCTGATGAACCC	853	58.1	Amplify the ALS
ALS-853R	ACAAAAAAGAGCCAACGAG
ALS-798F	AGCAGATTGTGAGGTTGATGAG	798	57.2
ALS-798R	TAACAAAAAAGAGCCAACGAG
ALS-179F	GATAACCAGCACTGAAAACC	179	55.7	qRT–PCR analysis of ALS gene
ALS-179R	ATTGGAAGATCAATCGACC
β-tub F	CGTAAGCTTGCTGTGAATCTCATC	133	56.4	qRT–PCR analysis of β-tub gene
β-tub R	CTGCTCGTCAACTTCCTTTGTG

). Each 20 μL PCR reaction contained 2 μL of 200 ng DNA, 10 μL 1× Taq MasterMix, 7 μL ddH₂O, and 0.5 μL of 10 μM forward and reverse primers. The amplification conditions were as follows: 3 min at 94 °C, 35 cycles of 10 s at 94 °C, 10 s at 58 °C, and 1 min at 72 °C, with a final extension of 5 min at 72 °C. The PCR products were analyzed via agarose gel electrophoresis and sequenced using Biomed Biotech (Beijing, China). The resulting sequences were aligned and compared with reference sequences using SnapGene 6.0.2 to identify target-site mutations associated with herbicide resistance.

2.4. PsbA and ALS Expression Analysis

To quantify the expression levels of the ALS and psbA genes, plants from the S, R1, and R2 populations were treated with thifensulfuron-methyl and bentazone at the three- to four-leaf stage. Leaf tissues were harvested at 0 and 24 h post-treatment. Total RNA was extracted using the RNAprep Pure Plant Kit (TianGen Biotechnology, Beijing, China), and RNA integrity was verified by 1% agarose gel electrophoresis. RNA concentrations were measured with a NanoDrop spectrophotometer (Thermo Scientific, Waltham, MA, USA), and first-strand cDNA was synthesized using the Reverse Transcription System (TransGen Biotech, Beijing, China). Quantitative real-time PCR (qRT-PCR) was performed using an ABI 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA) on 96-well plates. Each 20 μL reaction contained 10 μL of 2× TransStart^® Top Green qPCR SuperMix (TransGen Biotech), 0.4 μL each of forward and reverse primers, 1 μL of cDNA template, and 7.8 μL of RNase-free ddH₂O. The qRT-PCR cycling program consisted of an initial denaturation at 95 °C for 2 min, followed by 45 cycles of 95 °C for 10 s, 60 °C for 15 s, and 72 °C for 20 s. Melting curve analysis was conducted at the end of amplification to verify primer specificity.

Gene expression levels were normalized to the reference genes β-tub(psbA) and β-actin(ALS), and relative expression was calculated using the comparative Ct method (2^−ΔΔCt), according to Livak and Schmittgen [18]. The ΔCt value was determined by subtracting the Ct of the internal control gene from that of the target gene. Each sample was analyzed with three biological replicates. The student’s t-test (p < 0.05) was used to determine statistically significant differences in gene expression between the resistant and susceptible populations using SPSS software (v 15.0).

2.5. In Vitro ALS Enzyme Activity Assays

To further assess ALS resistance, in vitro enzyme activity assays were performed. Fresh leaves (4 g) from untreated plants (S, R1, R2) were flash-frozen in liquid nitrogen and stored at −80 °C. ALS enzyme extraction followed the protocol described by Yu et al. [19]. The enzyme activity was tested under different thifensulfuron-methyl concentrations, set at 0, 0.00005, 0.0005, 0.005, 0.05, 0.5, 5, 50, and 500 mM for the S population, and 0, 0.00005, 0.0005, 0.005, 0.05, 0.5, 5, 50, 500, 5000, and 50,000 mM for R1 and R2 populations. Each assay was conducted twice with independent enzyme extractions for reproducibility.

2.6. Cross- and Multiple-Resistance Patterns of Specific Populations to Other Herbicides

To assess the extent of cross- and multiple-resistance, the S, R1, and R2 populations were screened against a range of ALS- and PPO-inhibiting herbicides commonly used in soybean fields, as listed in

Table 2. Information on herbicides used in multiple-resistance experiments.

Target	Herbicide a	Rate Applied (g a.i. ha−1)
ALS	Cloransulam-methyl [Methyl 2-chloro-5-ethoxycarbonyl-6-methoxyanthranilate 85% WP]	25.2  50.4
	Flumetsulam [N-(2,6-difluorophenyl)-5-methyl-[1,2,4]triazolo[1,5-a]pyrimidine-2-sulfonamide 80% WP]	48.0  96.0
PPO	Acifluorfen [5-[2-chloro-4-(trifluoromethyl)phenoxy]-2-nitrobenzoic acid 25% SL]	384.0  774.0
	Fomesafen [5-[2-chloro-4-(trifluoromethyl)phenoxy]-N-(methylsulfonyl)-2-nitrobenzamide 25% SL]	450.0  900.0
	Oxyfluorfen [2-chloro-1-(3-ethoxy-4-nitrophenoxy)-4-(trifluoromethyl)benzene 240 g/L EC]	900.0  1800.0

^a WP, wettable powder; SL, soluble liquid; EC, emulsifiable concentrate. Values in bold represent the recommended dosages for field application.

. Plants were treated with varying herbicide doses, and untreated controls (water-only) were included to normalize biomass data. Aboveground biomass was recorded 21 days after treatment (DAT) to evaluate herbicide efficacy. Cross- and multiple-resistance assays were conducted using separate groups of untreated seedlings, grown under the same conditions and at the same developmental stage as those used in the dose–response experiments. These plants were treated independently—without prior exposure to bentazone or thifensulfuron-methyl—with other ALS and PPO inhibitors listed in Table 2. Each treatment was performed with three biological replicates, and all experiments were repeated twice to ensure reproducibility.

2.7. Data Analysis

Dose–response and enzyme activity data were analyzed using SigmaPlot v15.0 (SigmaPlot Software, Chicago, IL, USA). The log-logistic model was applied to calculate the herbicide dose required to reduce plant biomass by 50% (GR₅₀) and the ALS-inhibitor concentration needed to inhibit 50% of enzyme activity (IC₅₀):

$$y=C+{\displaystyle \frac{(D-C)}{1+{\left(\frac{x}{{GR}_{50}}\right)}^b}}$$

In this model, C signifies the minimum response limit, D represents the maximum response limit, b denotes the slope of the curve, and GR₅₀ corresponds to either GR₅₀ or IC₅₀ values. The GR₅₀ values were subsequently used to calculate the resistance index (RI), which indicates the resistance levels of the R1 and R2 populations relative to the susceptible control. In this study, resistance levels were categorized as high (RI ≥ 10), moderate (5 ≤ RI < 10), or low (2 ≤ RI < 5), based on the calculated RI values.

During the manuscript preparation, the authors used ChatGPT-4 (OpenAI, San Francisco, CA, USA) to assist with improving the clarity and fluency of some English expressions. All content was subsequently reviewed and verified by the authors to ensure scientific accuracy and integrity.

3. Results

3.1. Whole-Plant Dose–Response Assays

Whole-plant dose–response assays revealed that both R1 and R2 populations exhibited clear resistance to thifensulfuron-methyl. At the recommended field rate of 22.5 g a.i.·ha⁻¹, all plants in the susceptible (S) population died, while 77.8% of R1 and 83.3% of R2 plants survived and resumed growth 21 days after treatment, as determined by visual assessment relative to untreated controls. The GR₅₀ values for R1 and R2 were 58.95 and 72.59 g a.i.·ha⁻¹, respectively, in contrast to 11.15 g a.i.·ha⁻¹ for the S population. Accordingly, the resistance indices (RIs) were calculated to be 5.28 for R1 and 6.51 for R2, indicating moderate resistance (

Table 3. The rates of thifensulfuron-methyl and bentazone causing a 50% reduction in plant growth for the S, R1, and R2 populations.

Population	Thifensulfuron-Methyl
	GR50 a (g a.i. ha −1)	RI b	Mix	Max	Hillslope	R2	Adjust R2
S	11.15 ± 1.61	-	19.4922	99.4435	−1.3612	0.99	0.99
R1	58.95 ± 10.55	5.28	2.0991	92.2802	−1.1605	0.99	0.99
R2	72.59 ± 13.34	6.51	1.3732	90.4761	−1.1666	0.99	0.99
	Bentazone
S	41.92 ± 5.33	-	11.8279	97.6648	−1.177	0.99	0.99
R1	202.68 ± 25.03	4.83	17.2614	89.1525	−1.3197	0.99	0.99
R2	213.65 ± 33.38	5.1	10.1247	99.6071	−1.2267	0.99	0.99

^a GR₅₀: herbicide concentration that caused a 50% reduction in plant growth. ^b RI (resistance index) = GR₅₀ of resistant population/GR₅₀ of susceptible population.

; Figure 1).

Similarly, following bentazone treatment, all populations exhibited herbicide injury symptoms, including leaf chlorosis and necrosis; however, R1 and R2 plants demonstrated strong regrowth capacity. The GR₅₀ values for R1 and R2 were 202.68 and 213.65 g a.i.·ha⁻¹, with corresponding RIs of 4.83 and 5.10, also indicating moderate resistance to bentazone (Table 3; Figure 1).

3.2. PsbA and ALS Gene Sequencing Analysis

Post PCR amplification, an 1879 base pair segment of the ALS gene, which includes all nine recognized codon mutations, was successfully amplified and sequenced. Within the ALS gene sequences of the R1 populations, one different amino acid substitution was identified. Specifically, in the R1 population, sequence alignment of the ALS gene revealed a substitution of alanine with threonine at the 122nd amino acid position (Ala122Thr), observed in 10 clones (Figure 2). In the case of the R2 population, no mutations were detected. Additionally, an interesting observation was noted in the R1 population: the chromatograms at the Ala122 position for all tested individuals exhibited double peaks, aligning with the findings of previous research studies.

The psbA genes in the S, R1, and R2 populations were successfully amplified. Sequence analysis using BLASTN confirmed that all populations carried identical psbA sequences. No known or novel mutations were detected in the psbA gene across the tested populations.

3.3. PsbA and ALS Gene Expression Quantification by qRT–PCR

According to Figure 3, quantitative PCR (qPCR) analysis of genomic DNA (gDNA) revealed no significant differences in the relative copy number of the ALS and psbA genes between the S, R1, and R2 biotypes. This finding indicates that gene amplification is not responsible for the increased tolerance to thifensulfuron-methyl observed in the R1 and R2 biotypes, and there is likely no copy number variation in the S biotype. Additionally, ALS or psbA gene expression analysis showed no significant differences between treated and untreated plants within each biotype. The expression levels of the ALS and psbA genes in the R1 and R2 biotypes were comparable to those in the S biotype. These results suggest that overexpression of the ALS or psbA genes is unlikely to contribute to the higher resistance to thifensulfuron-methyl in the R1 and R2 biotypes.

3.4. Effects of Thifensulfuron-Methyl on Vitro ALS Enzyme Activity

The results of in vitro ALS enzyme activity assays were used to calculate the I₅₀ values and assess the resistance levels of the R1 and R2 populations. When the thifensulfuron-methyl concentration exceeded 500 mM, the S, R1, and R2 populations exhibited differential ALS activity responses. The enzyme activity assays revealed that the R1 and R2 populations were 4.64-fold and 1.15-fold resistant to thifensulfuron-methyl, respectively (Figure 4).

3.5. Cross- and Multiple-Resistance Patterns of C. album to Other Herbicides

This study evaluated the resistance levels of C. album populations to several commonly used ALS- and PPO-inhibiting herbicides in soybean fields (

Table 4. GR₅₀ values and resistance levels of S, R1, and R2 C. album populations to different herbicides.

Herbicide	Populations	GR50 (g a.i. ha−1)	RIs
Cloransulam-methyl	R1	27.82	1.47
	R2	21.92	1.16
	S	18.95	-
Flumetsulam	R1	21.54	1.30
	R2	18.24	1.11
	S	16.57	-
Acifluorfen	R1	674.12	2.44
	R2	604.90	2.19
	S	276.21	-
Fomesafen	R1	557.19	1.54
	R2	498.37	1.38
	S	362.11	-
Oxyfluorfen	R1	373.44	4.74
	R2	315.38	4.01
	S	78.82	-

). The results indicated that both R1 and R2 populations showed no resistance to cloransulam-methyl, flumetsulam, and fomesafen, while exhibiting low-level resistance to oxyfluorfen and acifluorfen. In contrast, the S population was highly sensitive to herbicides tested, with fresh weight inhibition rates exceeding 80%, confirming their effectiveness. Moreover, both R1 and R2 populations exhibited multiple resistance to ALS- and PPO-inhibiting herbicides. These findings highlight the need for diverse and integrated weed management strategies to prevent the further development of herbicide resistance.

4. Discussion

The resistance of C. album to ALS- and PSII-inhibiting herbicides is an increasing global concern, complicating weed management strategies [20]. Our study identified the Ala-122-Thr mutation in the ALS gene of the R1 population, a well-documented target-site resistance (TSR) mechanism previously observed in other weed species such as Amaranthus retroflexus and Kochia scoparia, frequently conferring cross-resistance to sulfonylurea herbicides [8,21]. Interestingly, the R2 population exhibited ALS inhibitor resistance without ALS target-site gene mutations, strongly suggesting a non-target-site resistance (NTSR) mechanism involving enhanced herbicide metabolism. Such metabolism-based ALS resistance mechanisms have been noted in other weed populations, including an Amaranthus palmeri population from Kansas, where resistance could be reduced by the cytochrome P450 inhibitor treatment.

The absence of psbA target-site gene mutations in both resistant populations (R1 and R2) further supports the existence of NTSR mechanisms driving bentazone resistance, likely involving cytochrome P450 monooxygenases and glutathione S-transferases (GSTs). This aligns with findings from other species, where metabolic resistance was reversed through cytochrome P450 inhibition. Additional pathways involving ATP-binding cassette (ABC) transporters and GST-based conjugation have also been documented in weeds such as Alopecurus myosuroides and A. palmeri, underscoring the complexity of NTSR mechanisms [22,23]. Similar metabolic resistance observed in C. album populations in Canada and Europe highlights the growing concern about NTSR as a robust mechanism capable of enabling weeds to resist multiple herbicides over time [24,25,26].

The coexistence of TSR and NTSR within a single population, such as the Ala-122-Thr ALS mutation observed in R1 alongside NTSR, demonstrates the adaptive flexibility of weed populations under continuous herbicide pressure [27]. This phenomenon, where multiple resistance mechanisms accumulate in weed populations, significantly complicates resistance management. Previous studies have reported similar layered resistance strategies in weeds like A. retroflexus, indicating an increasing trend of combined TSR and metabolic resistance mechanisms globally [27]. To further elucidate metabolism-based resistance mechanisms in C. album, advanced metabolic profiling, gene expression analyses, and enzyme activity assays will be essential. Specifically, identifying the enzymes involved in herbicide detoxification through metabolomics and transcriptomics could substantially enhance understanding. Long-term field studies monitoring the evolutionary trajectory of resistant alleles will also inform proactive management strategies [28,29].

The cross- and multiple-resistance patterns observed in C. album (populations R1 and R2) highlight the complexity and herbicide-specific nature of evolving resistance mechanisms. Both populations remained susceptible to chlorimuron-ethyl (an ALS-inhibitor) yet exhibited clear resistance to acifluorfen (a PPO inhibitor), suggesting distinct resistance mechanisms that are herbicide-specific. In R1, the Ala-122-Thr ALS mutation conferred resistance specifically to thifensulfuron-methyl but not chlorimuron-ethyl, reflecting differential herbicide-target binding influenced by individual mutations. The observed resistance to acifluorfen despite no known PPO gene mutations further indicates metabolic NTSR mechanisms.

The rise in PSII inhibitor resistance, particularly to bentazone, continues to compromise the effectiveness of post-emergent herbicides, complicating soybean weed control globally [24,30]. Effective integrated weed management (IWM) strategies are essential, including the use of pre-emergent herbicides, crop rotations, cover cropping, and diversified herbicide applications to delay resistance development [30,31,32]. Future research must focus on identifying the biochemical pathways and specific genes underpinning metabolic resistance, such as P450 enzymes or GST isoforms, as well as understanding the ecological dynamics and fitness costs associated with resistance. Enhanced resistance monitoring employing molecular diagnostics and metabolomic profiling is critical for proactive management, given the increasing global spread of herbicide-resistant C. album populations [33,34,35].

5. Conclusions

In conclusion, this study demonstrates the presence of both target-site and non-target-site resistance mechanisms in C. album populations from northern China. The R1 population exhibited a known ALS Ala-122-Thr mutation, while the R2 population showed evidence of metabolic resistance without any target-site mutations. Both populations showed cross- and multiple-resistance patterns to other ALS- and PPO-inhibiting herbicides. These findings underscore the importance of resistance monitoring and highlight the urgent need to implement integrated weed management strategies to mitigate further herbicide resistance evolution.