Investigation and Analysis of the Residual Status and Distribution of Long-Lasting-Effect Herbicides in Field Soil: A Case Study of Henan Province, a Major Agricultural Producing Area in China

Abstract

The results demonstrated that among the total 365 investigated samples, the proportion of samples detecting three target herbicides simultaneously, two herbicides, one herbicide, and none were 0.3%, 6.4%, 65.2%, and 23.2%, respectively. For samples with only one detected herbicide, the detection rates in Jiyuan, Luohe, Puyang, Luoyang, Xuchang, and Hebi were relatively high (ranging from 44% to 100%), whereas those in Sanmenxia, Nanyang, Xinxiang, and Kaifeng were relatively low (ranging from 6% to 20%). Regarding individual herbicides, the detection rates of mesosulfuron-methyl, quinclorac, halosulfuron-methyl, diflufenican, imazethapyr, pyroxasulfone, imazapic, fomesafen, and atrazine were 1.2%, 3.8%, 5.5%, 6.1%, 8.7%, 8.7%, 10.4%, 11.0%, and 33.9%, respectively. Based on these findings, the current reliance on long-acting effect herbicides for weed management in China’s agricultural management practices was systematically analyzed. Within the framework of agricultural sustainability, it is proposed that there is an urgent need to promote the concept of scientific herbicide use among farmers and that pesticide scientists must recognize the extreme importance of continuous innovation and the development of alternative herbicides with new mechanisms of action as a long-term strategic goal.

1. Introduction

Pesticides are the result of agricultural development and the crystallization of scientific and technological progress, playing an invaluable role in ensuring a sufficient supply of agricultural products (such as grains, vegetables, and fruits) for human consumption. They have become an indispensable tool of production in modern agricultural production practices. In recent decades, global agricultural production has undergone a significant restructuring from extensive traditional farming to technology-driven intensive agriculture, resulting in substantial transformations in the structure of the global pesticide industry. This industrial evolution has been driven by escalating demands for productivity optimization alongside mounting pressures for resource-efficient cultivation practices.

According to the statistical analysis conducted by S & P Global Commodity Insights Crop Science team (www.spglobal.com), the global sales of the crop pesticide market in 2022 reached USD 78.715 billion. Notably, herbicides accounted for a significant portion with a market share of USD 37.150 billion, which was nearly equivalent to the combined market shares of insecticides (USD 19.655 billion) and fungicides (USD 19.646 billion). This represents approximately 47.20% of the total agrochemical market share, indicating a steady growth trajectory expected for herbicides in the forthcoming years. According to Molan Digital Intelligence Research Center’s report (https://caifuhao.eastmoney.com/), China’s herbicides market size has achieved almost 30% of the global herbicides market size in 2023.

Undoubtedly, herbicides play an indispensable role in controlling weeds, reducing labor, and expanding agriculture in current agricultural production. However, concerns have been raised among experts in crop science, food safety, and environmental ecology, as well as the public, due to the extensive and frequent use of herbicides, particularly ones with long-lasting effects. These concerns arise from issues such as the development of weed resistance, the presence of pesticide residues in agricultural products, and contamination of ecological environments. According to the literature [1], only approximately 5% of sprayed herbicide quantities effectively reached target weeds to ensure optimal weed control efficacy. Meanwhile, around 95% of the herbicide enters soil, water, or air and interacts with non-target organisms, thus posing threats to farmland quality, crop health, agricultural product quality, and environmental safety.

The nine herbicides investigated in this study, including atrazine, imazethapyr, imazapic, mesosulfuron-methyl, halosulfuron-methyl, fomesafen, diflufenican, quinclorac, and pyroxasulfone, exhibited prolonged residual periods in field soil. The basic information regarding these herbicides is presented in

Table 1. The basic information of nine representative long-lasting-effect herbicides.

Chemicals	Chemical Category	Research & Development	Target Sites	Application
Atrazine	Triazine	Ciba-Geigy, 1958	PSII a	Corn, sorghum, millet, nursery, and non-cultivated land
Imazethapyr	Imidazolinone	ACC, 1983	ALS b	Corn
Imazapic	Imidazolinone	ACC, 1983	ALS	Sugarcane and peanut
Mesosulfuron-methyl	Sulfonylurea	Bayer, 2002	ALS	Wheat
Halosulfuron-methyl	Sulfonylurea	Nissan Chemical & Monsanto, 1987	ALS	Wheat, corn, rice, sugarcane, and sorghum
Fomesafen	Diphenyl ether	ICI, 1979	PPO c	Soybean, peanut, and non-cultivated land
Diflufenican	pyridyl aniline	Rhone-Poulenc, 1982	PDS d	Wheat, rice, and garlic
Quinclorac	Quinoline acid	BASF, 1985	PSII	Rapeseed, rice, and sorghum
Pyroxasulfone	Isoxazole	Kumiai Chemical, 2002	VLCFA e	Wheat, soybean, and corn

Note: ^a Photosystem II; ^b Acetolactate synthase; ^c Protoporphyrinogen oxidase; ^d Phytoene desaturase; ^e very-long-chain fatty acid synthesis.

. While their long-lasting effect in weed control was highly desirable in agricultural practices, the visible phytotoxicity resulting from soil residue remains a significant concern [2,3,4,5,6,7,8,9]. Furthermore, they were also suspected to exert substantial adverse effects on soil microorganisms [6,10,11,12,13,14,15,16,17,18], contributing to the inevitable contamination of agricultural products by pesticide residue. The presence of these chemical residues in field soil has garnered significant attention and necessitates comprehensive analysis methods and performance indicators. A summary of the currently reported residue analysis methods and their corresponding performance parameters can be found in

Table 2. Typical residue analysis methods of nine herbicides in soil in the literature.

Analytes	Techniques	Sample Treatment	Detection Performance		Reference
			Linear Range	LOQ i
Atrazine	GC-NPD	SLE a	0.01~20 mg/L	0.02 mg/kg	[19]
	GC-MS/MS	SLE	5–100 mg/L	0.2 μg/kg	[20]
	LC-MS/MS	QuEChERS b	0.01–1 mg/L	<7.1 μg/kg	[21]
Imazethapyr	LC-UVD	UAE c	0.1–20 mg/L	0.51 mg/kg	[22]
	GC-NPD	SLE	2–10 mg/L	5 µg/kg	[23]
	GC-MS	MAE d	1–50 μg/L	1 μg/L	[24]
Imazapic	LC-SPD	MSPE e	1–50 mg/L	0.5 mg/kg	[25]
	LC-MS/MS	UAE	0.25–5 μg/L	0.1 μg/kg	[26]
	LC-MS/MS	QuEChERS	0.2–20 μg/L	5.0 μg/kg	[27]
Mesosulfuron-methyl	LC-UVD	UAE	0.008–5 mg/L	0.008 mg/kg	[28]
	LC-UVD	SLE	0.01–5 mg/L	0.004 mg/kg	[29]
Halosulfuron-methyl	LC-MS	QuEChERS	0.001–1 mg/L	0.005 mg/kg	[30]
	LC-PAD	SLE	0.05–2 mg/L	0.05 mg/kg	[31]
	LC-DAD	SLE	0.01–5 mg/l	0.02 mg/kg	[32]
Fomesafen	HPLC-DAD	SLE-LTP f	25–270 μg/kg	22.1 μg/kg	[33]
	LC-MS/MS	QuEChERS	0.1–500 μg/L	0.15 μg/kg	[34]
	Bioassay	not required	0.3–1.5 mg/L	0.1 mg/kg	[35]
	sensor	UAE	5–500 μmol/L	5 μmol/L	[36]
	ELISA	SLE	1.92–779.8 μg/L	0.00192 mg/kg	[37]
Diflufenican	GC-MS	LEP-TLC	-	4 μg/kg	[38]
	LC-MS/MS	QuEChERS	0.01–5 μg/L	0.1 ng/kg	[39]
Quinclorac	LC-UV	DSPE-DLLME g	10–300 μg/L	5 μg/kg	[40]
	LC-PDA	LE-SPE h	0.05–20 mg/L	0.05 mg/kg	[41]
Pyroxasulfone	Bioassay	not required	0.05–2 mg/kg	-	[42]
	GC/MS	SLE	-	5 μg/kg	[43]

Note: ^a Solid liquid extraction; ^b Quick, Easy, Cheap, Effective, Rugged, and Safe; ^c ultrasound assisted extraction; ^d microwave assisted extraction; ^e matrix solid phase extraction; ^f low-temperature partitioning; ^g dispersive liquid–liquid microextraction; ^h solid phase extraction; ⁱ limit of quantitation.

. However, to the best of our knowledge, no existing simultaneous determination method is available for assessing the aforementioned herbicide residues in field soil.

Henan Province is strategically located in the heartland of the Central Plains of China. The distinctive climatic conditions conducive to agricultural production have bestowed upon Henan Province its renowned title as the “Granary of the Central Plains”. As a prominent grain-producing region in China, Henan Province consistently maintains an annual wheat sowing area of approximately 5.6 million hectares, yielding around 35 million tons per year. The corn planting area remains consistently above 3.8 million hectares, resulting in an annual output of about 28 million tons. The rice planting area exhibits stable figures at 600,000 hectares annually and yields around 20 million tons each year. Soybean cultivation encompasses an average planting area of about 300,000 hectares annually, with an approximate yearly output of 4 million tons. In terms of both planting area and production volume, peanut cultivation in Henan Province holds the top position nationwide, with an annual planting area of approximately 1.3 million hectares and a total production volume reaching around 6 million tons (https://data.stats.gov.cn/). Furthermore, Henan Province plays a pivotal role as a prominent vegetable-producing region within China. In the Henan Province of China, the information regarding crop fields where the nine representative long-lasting-effect herbicides investigated by this research institute were applied is provided in Table S1 of the supporting information.

The nine representative long-lasting-effect herbicides mentioned above are widely used in the management of farmland weeds in Henan Province, China. This study aims to provide insight into the residual status and distribution characteristics of these herbicides in farmland soil in Henan Province by using a multi-residue analysis method specifically developed for them. Furthermore, it is essential to propose effective strategies to mitigate the potential adverse effects of these herbicides on the sustainable development of agriculture. Simultaneously, these results should establish a fundamental theoretical foundation for the implementation of pollution control measures targeting herbicide-induced contamination in farmlands.

2. Materials and Methods

2.1. Chemicals and Materials

Analytical standards of imazethapyr (purity, 99.9%), imazapic (purity, 98.0%), mesosulfuron-methyl (purity, 98.3%), atrazine (purity, 99.0%), quinclorac (purity, 98.1%), halosulfuron-methyl (purity, 99.8%), pyroxasulfone (purity, 99.7%), and fomesafen (purity, 98.9%) were purchased from Alta Scientific Co., Ltd. (Tianjin, China); the analytical standard of diflufenican (purity, 99.9%) was obtained from Dr. Ehrenstorfer GmbH (Augsburg, Germany). Formic acid, sodium chloride, and anhydrous magnesium sulfate (analytical grade) were supplied from Sinopharm Chemical Reagent Co., Ltd. (Beijing, China). HPLC-grade acetonitrile was purchased from Mreda Medical Technologies Inc. (Beijing, China). The sorbents of primary secondary amine (PSA, 40–60 μm) and octadecylsilane (C₁₈, 50 μm particle size, 60 Å pore size) were supplied by Bonna-Agela Technologies Inc. (Tianjin, China). Ultrapure water was prepared using a Millipore-Q water purification system (Millipore Corporation, MA, USA).

2.2. Chromatography Analysis Conditions

The analytes were separated and analyzed using the Waters Acquity UPLC system (Waters Corporation, MA, USA), which consisted of a binary pump, vacuum degasser, and temperature controller for the column; vial autosampler; and eλ-PDA. For this purpose, a Cosmocore PBr column (2.1 × 150 mm, 2.6 μm) (Nacalai Tesque Inc. Kyoto, Japan) was utilized with the column oven temperature maintained at 35 °C. Instrument control, data acquisition, and processing were performed utilizing Waters Empower-3 LC software. The mobile phase comprised a acetonitrile (A)-10% volume fraction of acetonitrile in 0.1% formic acid aqueous solution (B).

The multi-channel detection capability of the PDA was fully utilized based on the ultraviolet absorption spectral characteristics of target analytes. Different detection wavelengths were configured for UPLC-PDA to screen residues of nine herbicides in soil samples from diverse regions.

2.3. Preparation of Analytic Sample

The instructions for preparation are as follows: Take 10 ± 0.1 g of homogenized and sieved soil sample in a 50 mL polypropylene centrifuge tube, and add 10 mL of deionized water along with 10 mL of sample extraction solution (containing 0.1% acetic acid in acetonitrile) and 2 g of sodium chloride. Vortex the mixture for three minutes, followed by ultrasonic extraction maintained at a temperature of 40 °C for five minutes; subsequently, centrifuge it at a speed of 4500 rpm for five minutes. Transfer the resulting supernatant extract (1.0 mL) into a pre-loaded materials-containing centrifuge tube (2 mL) consisting of anhydrous magnesium sulfate (100 mg), PSA (25 mg), and C₁₈ (25 mg). Vortex the mixture again for one minute before subjecting it to another round of centrifugation at 12,000 rpm for five minutes. Finally, filter the supernatant through a syringe filter with the pore size set at 0.22 μm into an appropriate clean vial suitable for chromatographic analysis.

2.4. Analysis of Field Soil Samples

A total of 365 soil samples were systematically collected from 120 counties across 18 provincial-level cities (shown in Figure S1 in Supplementary Materials) in Henan Province, and standardized sampling was conducted using the grid sampling design with the BeiDou navigation and positioning system (BDNPS) between May and October 2023. The sampled areas encompassed a diverse range of crops, including wheat, corn, soybeans, peanuts, garlic, vegetables, orchards, and nursery plots.

Upon arrival at the laboratory, farmland soil samples collected from various locations were meticulously removed of gravel and plant remains. Subsequently, these samples underwent sieving through a 2 mm sieve size before being divided into sub-samples weighing approximately 200 g each. The refined soil samples were then transferred into polyethylene self-sealing bags, appropriately labeled, and stored at −20 ± 1 °C for freezing preservation. During the analysis process, the analytical samples were prepared following the sample preparation procedure outlined in Section 2.3, followed by analyzing the residue levels of nine herbicides in soil samples using the chromatographic conditions described in Section 2.2.

The chromatographic analysis results of 9 herbicides in the investigated soil samples were processed by Waters Empower-3 LC software to obtain the residue detection data. Then, the residue detection data of the target analytes in the samples from different regions were analyzed by Microsoft Excel 2003 software and plotted as intuitive distribution pattern column charts.

3. Results

3.1. Optimized Chromatographic Conditions

A mobile phase flow rate of 0.3 mL/min was employed, and a gradient elution procedure was utilized as follows: initially, the system contained 15% B for 4.5 min; subsequently, the concentration of B increased to 40% within 6.0 min; further elevation to 60% B occurred over a period of 10.0 min; achieving a final concentration of 95% B and maintaining it for 3.0 min before returning to the initial conditions (15% B).

Based on a comprehensive analysis of standard chromatograms and ultraviolet spectra (210 nm to 400 nm) of nine herbicides, considering both detection sensitivity and interference from the soil sample matrix, different detection wavelengths were selected using UPLC-PDA for quantitative analysis of residual levels of these nine herbicides in soil samples collected from diverse regions. Specifically, the ultraviolet detection wavelength was set at 220 nm for quinclorac, atrazine, and pyroxasulfone; 235 nm for mesosulfuron-methyl; 254 nm for imazethapyr and imazapic; and 290 nm for fomesafen and diflufenican. The standard chromatograms of the nine target analytes under the optimized chromatographic conditions are shown in Figure 1. Details regarding the optimization process for wavelength detection can be found in Supplementary Materials (Figure S2).

3.2. Method Validation

According to the method validation guideline (CAC/GL 90-2017, http://down.foodmate.net/standard/sort/11/51256.html, 22 February 2025), the optimized method was evaluated for linearity, spiked fortified recoveries, relative standard deviations (RSDs), and sensitivity.

3.2.1. Linearity

The linearity was assessed by determining the correlation coefficient (R²) of determination for the seven-point calibration curves, which were obtained by diluting mixed standard solutions of nine target herbicides with acetonitrile extract from blank soil samples. The concentrations of the mixed matrix standard solvents ranged from 0.01 mg/L to 10.0 mg/L for soil, including concentrations of 0.01 mg/L, 0.05 mg/L, 0.1 mg/L, 0.5 mg/L, 1 mg/L, 5 mg/L, and 10.0 mg/L. Linear regression analysis was performed to establish quantitative calibration equations between the mass concentration of these analytes and their corresponding chromatographic response values. The obtained linear responses and the quantitative calibration equations were presented in Supplementary Materials (Figure S3), demonstrating favorable linearity for all nine target herbicides within the tested range of mass concentrations under optimized chromatographic conditions. Results revealed a linear detection range from 0.05 mg/L to 10 mg/L for mesosulfuron-methyl, while the remaining eight herbicides exhibited a detection range of 0.01 mg/L to 10 mg/L.

3.2.2. Accuracy, Precision, and Sensitivity

To evaluate the accuracy and precision of the methodology, recovery tests were performed on campus soil samples that had been confirmed to be free of the target analytes at three different levels (0.1 mg/kg, 0.5 mg/kg, and 1 mg/kg). The results obtained from these tests were used to determine both the recoveries and RSDs between detection values of three parallel treatments at each spiked level. Additionally, the LOQ for the analysis method was determined by calculating the detection sensitivities based on test results from nine herbicides spiked at a mass concentration of 0.1 mg/kg in blank soil samples with a signal-to-noise ratio (S/N) of 10:1.

The recoveries of all nine analytes ranged from 76% to 100%, with corresponding RSDs all being less than 7%, as observed in the results presented in

Table 3. The recoveries (%) and RSD (%) of nine herbicides at different spiked levels in soil.

Chemicals	0.1 mg/g				0.5 mg/g				1 mg/g				LOQ (mg/kg)
	Ⅰ	Ⅱ	Ⅲ	RSD	Ⅰ	Ⅱ	Ⅲ	RSD	Ⅰ	Ⅱ	Ⅲ	RSD
Atrazine	86.8	84.6	80.8	3.0	85.8	91.9	86.2	3.4	98.9	86.9	95.6	6.2	0.017
Imazethapyr	96.9	92.3	96.3	2.5	93.2	80.9	92.3	6.9	84.0	88.7	78.1	5.3	0.016
Imazapic	80.7	83.3	78.4	2.5	96.7	95.7	86.4	5.7	79.2	83.1	84.8	2.9	0.016
Mesosulfuron-methyl	86.2	82.1	85.9	2.3	82.4	90.5	82.3	4.7	99.9	95.7	96.3	6.2	0.017
Halosulfuron-methyl	83.6	91.8	83.9	4.7	92.8	86.0	90.4	3.4	83.0	86.4	84.1	1.7	0.026
Fomesafen	85.7	82.9	78.4	2.8	84.6	81.2	80.5	2.2	83.1	80.8	87.4	3.4	0.031
Diflufenican	89.5	85.3	93.9	4.3	93.3	86.0	84.4	3.1	83.5	87.4	82.2	2.7	0.026
Quinclorac	86.9	82.5	76.3	5.3	78.3	87.9	86.7	5.2	79.1	84.9	82.3	2.9	0.016
Pyroxasulfone	86.4	77.4	80.3	4.6	82.8	84.5	84.9	1.1	84.8	78.0	86.7	4.2	0.031

. The calculated LOQs for imazapic, imazethapyr, and quinclorac in soil were determined to be at a level of accuracy up to or equaling that which is required by an LOQ (0.016 mg/kg), while those for halosulfuron-methyl and diflufenican were established slightly higher at a level still within LOQs (0.026 mg/kg). Both atrazine and mesosulfuron-methyl exhibited LOQ values also within acceptable standards (0.017 mg/kg), whereas pyroxasulfone and fomesafen demonstrated LOQs of 0.031 mg/kg each. These findings underscore the precision, sensitivity, and robustness of the employed analytical sample preparation method.

3.3. Residual Detection Results of Nine Herbicides in Field Soil

To ensure the credibility of the detection results for the nine herbicides investigated in the collected soil samples, it is necessary to employ a grid sampling design to determine the sampling locations while minimizing the inclusion of industrial areas, towns, villages, ponds, and breeding farms. A total of 365 field soil samples were collected from various vegetable fields (including cabbage, cowpea, carrot, chili pepper, pumpkin, scallion, garlic, and potato), resulting in 28 samples. Furthermore, wheat fields contributed 63 samples; corn fields contributed 150; peanut fields contributed 64; soybean fields contributed 35; rice and sesame fields each provided 7 samples; and tea gardens accounted for 3 samples. The remaining soil samples (totaling 15) were obtained from cotton fields as well as those associated with sweet potato cultivation, along with orchards and nurseries.

The distribution pattern and detection ratios of herbicides across different regions are visually depicted in Figure 2. From an alternative perspective, out of the total 365 soil samples collected from agricultural fields using the grid sampling design, only a mere 0.3% exhibited simultaneous detection of three target herbicides out of the nine herbicides under investigation. Meanwhile, the detection ratio for two herbicides was found to be 6.4%, and it was observed that one herbicide alone had a detection ratio of 65.2%.

The non-detection ratio for any herbicide accounted for 23.2%. In terms of detecting a specific herbicide, relatively high detection ratios were observed in Jiyuan (100%), Luohe (86%), Puyang (58%), Luoyang (50%), and Xuchang (50%) regions. However, it should be noted that Jiyuan is located in a major industrial area with limited agricultural land, comprising only 32,000 hectares of cultivated land. Therefore, the representativeness of the two samples considered from Jiyuan may be compromised. On the contrary, Sanmenxia, Nanyang, and Xinxiang regions all demonstrate detection frequencies below 20%. Furthermore, for the entire Henan province situation depicted in Figure 3, individual herbicides’ detection ratios were as follows: mesosulfuron-methyl was detected at 0.8%, quinclorac at 4.4%, halosulfuron-methyl at 4.7%, diflufenican at 5.8%, imazethapyr at 8.5%, pyroxasulfone at 10.7%, imazapic at 9.9%, fomesafen at 10.7%, and atrazine at 32.1%.

It is noteworthy that none of the twenty-eight soil samples collected from vegetable fields showed detectable residues of the target herbicides. This observed outcome could be due to either the detection results being below the limit of detection or no application of herbicides for weed management during vegetable cultivation.

4. Discussion

The objective of investigating soil herbicide contamination is to quantify the level of herbicide pollution in agricultural soils and analyze their spatial distribution. During this process, it is crucial to carefully allocate sampling points for accurate and scientifically valid survey results. The uncertainty arising from the sampling location contributes approximately 50% to the overall uncertainty in estimating pollutant content [44]. However, by effectively designing a sampling scheme based on both historical background regarding pesticide application and the geographical environment specific to the survey area [45,46], we can significantly improve accuracy during investigations of soil pollution. In this study, a grid sampling method based on the BDNPS was employed to investigate the provincial-scale geographical distribution of residues from nine typical long-lasting-effect herbicides in soil samples collected from Henan Province, which is a prominent agricultural region in China. The successful analytical method developed for these herbicides in soil samples was leveraged.

Considering both a large sample size (a total of 365 samples) and a wide distribution range for soil sampling sites (covering an area of 167,000 square kilometers), as well as an extended duration for sampling (lasting for six months), it becomes evident that despite classifying these nine target herbicides under investigation as pesticides with long-lasting residual properties, there is potential for detected residues to originate from either recent crop applications or remnants in previous crop fields. Furthermore, herbicide application timings often vary among different regions even when considering current crops. Therefore, discussing absolute residue values regarding these investigated herbicides lacks significance within this scope; instead, all results exceeding LOQ were included in our analysis process.

Based on the comprehensive survey results, it is evident that weed management practices in diverse crop fields across China’s primarily agricultural regions predominantly rely on conventional herbicides like atrazine, imazethapyr, imazapic, fomesafen, quinclorac, and mesosulfuron-methyl. However, in recent years, there has been a gradual adoption of newly developed advanced herbicides such as pyroxasulfone, halosulfuron-methyl, and diflufenican. This phenomenon can be attributed to the entrenched practice of herbicide usage in local areas and the provision of high-quality professional training aimed at enhancing knowledge related to plant protection during China’s intensive agricultural development process.

In the survey results, several phenomena were also observed. For instance, samples from multiple sampling points revealed residues of herbicides unsuitable for this season’s crop fields. These residues could be attributed to the remnants left by previous crops or even traced back to earlier years’ applications of herbicides in the fields. This occurrence is undoubtedly linked to the long-lasting-effect nature of the investigated herbicides but is further facilitated by their long-term, continuous, and high-dose application. The survey results also reveal a noteworthy situation: the relatively simple cropping system (primarily consisting of wheat–corn and wheat–soybean/peanut rotation) in Henan Province of China predominantly relies on traditional herbicide varieties, which may serve as the fundamental reason behind the rapid development of weed resistance in various regions of Henan Province in recent years.

Due to the influence of multiple factors, the deeply entrenched cultivation system has exhibited remarkable resistance to change. Therefore, there is an urgent need to enhance farmers’ selection and application techniques for herbicides, including rational blending, timely replacement, and strict adherence to label instructions. Additionally, it is crucial for pesticide scientists to continuously innovate and develop alternative herbicide varieties with novel mechanisms as a long-term objective.

Meanwhile, in order to align with the sustainable development goals of modern agriculture, it is imperative to give due attention to the survey results and systematic analysis presented in this article as a significant source of inspiration for weed management in other regions.

Although the investigation results obtained in this study are relatively comprehensive, the influence of key soil enzyme activities that are closely associated with assessing the soil pollution status has not yet been addressed. Additionally, even without considering climatic factors, differences exist in the degradation patterns of pesticides in soils with varying textures. It appears inappropriate to evaluate the residual risks of these herbicides solely based on the findings of this investigation as a uniform benchmark. Moreover, there remains a significant gap in long-term dynamic monitoring data regarding the residues of related herbicides in farmland soil. All these aspects require further attention and improvement in subsequent studies.