Recent technologies for glyphosate removal from aqueous environment: A critical review.

The growing demand for food has led to an increase in the use of herbicides and pesticides over the years. One of the most widely used herbicides is glyphosate (GLY). It has been used extensively since 1974 for weed control and is currently classified by the World Health Organization (WHO) as a Group 2A substance, probably carcinogenic to humans. The industry and academia have some disagreements regarding GLY toxicity in humans and its effects on the environment. Even though this herbicide is not mentioned in the WHO water guidelines, some countries have decided to set maximum acceptable concentrations in tap water, while others have decided to ban its use in crop production completely. Researchers around the world have employed different technologies to remove or degrade GLY, mostly at the laboratory scale. Water treatment plants combine different technologies to remove it alongside other water pollutants, in some cases achieving acceptable removal efficiencies. Certainly, there are many challenges in upscaling purification technologies due to the costs and lack of factual information about their adverse effects. This review presents different technologies that have been used to remove GLY from water since 2012 to date, its detection and removal methods, challenges, and future perspectives.

Optimizing herbicide selection for pre-emergence control of itchgrass and cypressvine morningglory in sugarcane.

The aim of this study was to assess the efficacy of herbicides in association to control Rottboellia exaltata and Ipomoea quamoclit during pre-emergence while also to evaluate the potential impact on the sugarcane. The experimental design employed a randomized block with seven treatments and four replications. The treatments were: 1 - no herbicide application; 2 - indaziflam + sulfentrazone; 3 - indaziflam + diclosulam; 4 - indaziflam + tebuthiuron; 5 - flumioxazin + diclosulam, 6 - flumioxazin + pyroxasulfone and 7 - clomazone + sulfentrazone. The evaluated parameters were: percentage of weeds control, green coverage percentage (Canopeo® system), weed biomass (g m-2), itchgrass height, and sugarcane tiller. Several herbicide associations have been proven effective alternatives for managing itchgrass and cypressvine morningglory. The most successful treatments for itchgrass control were indaziflam + tebuthiuron (100%) and indaziflam + diclosulam (97%), whereas for cypressvine morningglory, the betters were indaziflam + sulfentrazone (97%), indaziflam + diclosulam (98%), indaziflam + tebuthiuron (97%), flumioxazin + diclosulam (94%), and clomazone + sulfentrazone (96%). All treatments reduced the weed biomass, with indaziflam + tebuthiuron being the safest option for protecting sugarcane.

Application of Moringa leaves as soil amendment to tiger-nut for suppressing weeds in the Nigerian Savanna.

BACKGROUND: The allelopathic effect of Moringa (Moringa oleifera Lam.) leaves applied as organic manure in tiger nut (Cyperus esculentus L.) production on associated weeds was investigated in the guinea savanna of South West Nigeria, during the 2014 (September - November) and 2015 (June - August) wet seasons. METHODS: Five Moringa leaves rates (0, 2.5, 5.0, 7.5 and 10 t/ha) and three tuber sizes (0.28 g, 0.49 g and 0.88 g dry weight) were laid out in the main plot and sub-plot, respectively in a split-plot arrangement fitted into randomized complete block design and replicated three times. RESULTS: Parameters measured, which include, weed cover score (WCS), weed density (WD) and weed dry matter production (WDMP) were significantly (p<0.05) influenced in both years by Moringa leaf. In 2015, WCS, WD and WDMP significantly (p<0.05) reduced by 25-73%, 35-78% and 26-70% on Moringa leaves-treated plots respectively. There were significant (p<0.05) interactions between quantity of Moringa leaves incorporated and tuber size. The bigger the tuber and the higher the quantity of Moringa leaves incorporated the lower the WCS, WD and WDMP. CONCLUSIONS: Consequently, application of 10 t.ha- 1 Moringa leaves and planting of large or medium-sized tubers were recommended for optimum weed suppression in tiger nut production in South West Nigeria.

Rational design of Striga hermonthica-specific seed germination inhibitors.

The obligate hemiparasitic weed Striga hermonthica grows on cereal roots and presents a severe threat to global food security by causing enormous yield losses, particularly in sub-Saharan Africa. The rapidly increasing Striga seed bank in infested soils provides a major obstacle in controlling this weed. Striga seeds require host-derived strigolactones (SLs) for germination, and corresponding antagonists could be used as germination inhibitors. Recently, we demonstrated that the common detergent Triton X-100 is a specific inhibitor of Striga seed germination by binding noncovalently to its receptor, S. hermonthica HYPO-SENSITIVE TO LIGHT 7 (ShHTL7), without blocking the rice (Oryza sativa) SL receptor DWARF14 (OsD14). Moreover, triazole ureas, the potent covalently binding antagonists of rice SL perception with much higher activity toward OsD14, showed inhibition of Striga but were less specific. Considering that Triton X-100 is not suitable for field application and by combining structural elements of Triton and triazole urea, we developed two hybrid compounds, KK023-N1 and KK023-N2, as potential Striga-specific germination inhibitors. Both compounds blocked the hydrolysis activity of ShHTL7 but did not affect that of OsD14. Binding of KK023-N1 diminished ShHTL7 interaction with S. hermonthica MORE AXILLARY BRANCHING 2, a major component in SL signal transduction, and increased ShHTL7 thermal specificity. Docking studies indicate that KK023-N1 binding is not covalent but is caused by hydrophobic interactions. Finally, in vitro and greenhouse tests revealed specific inhibition of Striga seed germination, which led to a 38% reduction in Striga infestation in pot experiments. These findings reveal that KK023-N1 is a potential candidate for combating Striga and a promising basis for rational design and development of further Striga-specific herbicides.

Bacterial secondary metabolites: possible mechanism for weed suppression in wheat.

Chemical weed control is an effective method, but has proved hazardous for humans, environment, and soil biodiversity. Use of allelopathic bacteria may be more efficient and sustainable weed control measure. The bacterial inoculants have never been studied in context of their interaction with weed root exudates and precursor-dependent production of the natural phytotoxins (cyanide, cytolytic enzymes and auxin) by these strains to understand their weed suppression and wheat growth promotion abilities. Therefore, root exudates of Avena fatua, Phalaris minor, Rumex dentatus, and wheat were quantified and their role in microbial root colonization and secondary metabolite production, i.e., cyanide, cytolytic enzymes, phenolics, and elevated auxin concentration, was studied. The results depicted l-tryptophan and glycine as major contributors of elevated cyanide and elevated levels in weed rhizosphere by the studied Pseudomonas strains, through their higher root colonization ability in weeds as compared with wheat. Furthermore, the higher root colonization also enhanced p-coumaric acid (photosynthesis inhibitor by impairing cytochrome c oxidase activity in plants) and cytolytic enzyme (root cell wall degradation) concentration in weed rhizosphere. In conclusion, the differential root colonization of wheat and weeds by these strains is responsible for enhancing weed suppression (enhancing phytotoxic effect) and wheat growth promotion (lowering phytotoxic effect).

Hyperspectral Analysis for Discriminating Herbicide Site of Action: A Novel Approach for Accelerating Herbicide Research.

In agricultural weed management, herbicides are indispensable, yet innovation in their modes of action (MOA)-the general mechanisms affecting plant processes-has slowed. A finer classification within MOA is the site of action (SOA), the specific biochemical pathway in plants targeted by herbicides. The primary objectives of this study were to evaluate the efficacy of hyperspectral imaging in the early detection of herbicide stress and to assess its potential in accelerating the herbicide development process by identifying unique herbicide sites of action (SOA). Employing a novel SOA classification method, eight herbicides with unique SOAs were examined via an automated, high-throughput imaging system equipped with a conveyor-based plant transportation at Purdue University. This is one of the earliest trials to test hyperspectral imaging on a large number of herbicides, and the study aimed to explore the earliest herbicide stress detection/classification date and accelerate the speed of herbicide development. The final models, trained on a dataset with nine treatments with 320 samples in two rounds, achieved an overall accuracy of 81.5% 1 day after treatment. With the high-precision models and rapid screening of numerous compounds in only 7 days, the study results suggest that hyperspectral technology combined with machine learning can contribute to the discovery of new herbicide MOA and help address the challenges associated with herbicide resistance. Although no public research to date has used hyperspectral technology to classify herbicide SOA, the successful evaluation of herbicide damage to crops provides hope to accelerate the progress of herbicide development.

Weed Detection Using Deep Learning: A Systematic Literature Review.

Weeds are one of the most harmful agricultural pests that have a significant impact on crops. Weeds are responsible for higher production costs due to crop waste and have a significant impact on the global agricultural economy. The importance of this problem has promoted the research community in exploring the use of technology to support farmers in the early detection of weeds. Artificial intelligence (AI) driven image analysis for weed detection and, in particular, machine learning (ML) and deep learning (DL) using images from crop fields have been widely used in the literature for detecting various types of weeds that grow alongside crops. In this paper, we present a systematic literature review (SLR) on current state-of-the-art DL techniques for weed detection. Our SLR identified a rapid growth in research related to weed detection using DL since 2015 and filtered 52 application papers and 8 survey papers for further analysis. The pooled results from these papers yielded 34 unique weed types detection, 16 image processing techniques, and 11 DL algorithms with 19 different variants of CNNs. Moreover, we include a literature survey on popular vanilla ML techniques (e.g., SVM, random forest) that have been widely used prior to the dominance of DL. Our study presents a detailed thematic analysis of ML/DL algorithms used for detecting the weed/crop and provides a unique contribution to the analysis and assessment of the performance of these ML/DL techniques. Our study also details the use of crops associated with weeds, such as sugar beet, which was one of the most commonly used crops in most papers for detecting various types of weeds. It also discusses the modality where RGB was most frequently used. Crop images were frequently captured using robots, drones, and cell phones. It also discusses algorithm accuracy, such as how SVM outperformed all machine learning algorithms in many cases, with the highest accuracy of 99 percent, and how CNN with its variants also performed well with the highest accuracy of 99 percent, with only VGGNet providing the lowest accuracy of 84 percent. Finally, the study will serve as a starting point for researchers who wish to undertake further research in this area.

Current progress in Striga management.

The Striga, particularly S. he rmonthica, problem has become a major threat to food security, exacerbating hunger and poverty in many African countries. A number of Striga control strategies have been proposed and tested during the past decade, however, further research efforts are still needed to provide sustainable and effective solutions to the Striga problem. In this paper, we provide an update on the recent progress and the approaches used in Striga management, and highlight emerging opportunities for developing new technologies to control this enigmatic parasite.

Modeling the evolution of herbicide resistance in weed species with a complex life cycle.

A growing number of weed species have evolved resistance to herbicides in recent years, which causes an immense financial burden to farmers. An increasingly popular method of weed control is the adoption of crops that are resistant to specific herbicides, which allows farmers to apply the herbicide during the growing season without harming the crop. If such crops are planted in the presence of closely related weed species, it is possible that resistance genes could transfer from the crop species to feral populations of the wild species via gene flow and become stably introgressed under ongoing selective pressure by the herbicide. We use a density-dependent matrix model to evaluate the effect of planting such crops on the evolution of herbicide resistance under a range of management scenarios. Our model expands on previous simulation studies by considering weed species with a more complex life cycle (perennial, rhizomatous weed species), studying the effect of environmental variation in herbicide effectiveness, and evaluating the role of common simplifying genetic assumptions on resistance evolution. Our model predictions are qualitatively similar to previous modeling studies using species with a simpler life cycle, which is, crop rotation in combination with rotation of herbicide site of action effectively controls weed populations and slows the evolution of herbicide resistance. We find that ignoring the effect of environmental variation can lead to an over- or under-prediction of the speed of resistance evolution. The effect of environmental variation in herbicide effectiveness depends on the resistance allele frequency in the weed population at the beginning of the simulation. Finally, we find that degree of dominance and ploidy level have a much larger effect on the predicted speed of resistance evolution compared to the rate of gene flow.

Weed Classification from Natural Corn Field-Multi-Plant Images Based on Shallow and Deep Learning.

Crop and weed discrimination in natural field environments is still challenging for implementing automatic agricultural practices, such as weed control. Some weed control methods have been proposed. However, these methods are still restricted as they are implemented under controlled conditions. The development of a sound weed control system begins by recognizing the crop and the different weed plants presented in the field. In this work, a classification approach of Zea mays L. (Crop), narrow-leaf weeds (NLW), and broadleaf weeds (BLW) from multi-plant images are presented. Moreover, a large image dataset was generated. Images were captured in natural field conditions, in different locations, and growing stages of the plants. The extraction of regions of interest (ROI) is carried out employing connected component analysis (CCA), whereas the classification of ROIs is based on Convolutional Neural Networks (CNN) and compared with a shallow learning approach. To measure the classification performance of both methods, accuracy, precision, recall, and F1-score metrics were used. The best alternative for the weed classification task at early stages of growth and in natural corn field environments was the CNN-based approach, as indicated by the 97% accuracy value obtained.

Transformer-Based Weed Segmentation for Grass Management.

Weed control is among the most challenging issues for crop cultivation and turf grass management. In addition to hosting various insects and plant pathogens, weeds compete with crop for nutrients, water and sunlight. This results in problems such as the loss of crop yield, the contamination of food crops and disruption in the field aesthetics and practicality. Therefore, effective and efficient weed detection and mapping methods are indispensable. Deep learning (DL) techniques for the rapid recognition and localization of objects from images or videos have shown promising results in various areas of interest, including the agricultural sector. Attention-based Transformer models are a promising alternative to traditional constitutional neural networks (CNNs) and offer state-of-the-art results for multiple tasks in the natural language processing (NLP) domain. To this end, we exploited these models to address the aforementioned weed detection problem with potential applications in automated robots. Our weed dataset comprised of 1006 images for 10 weed classes, which allowed us to develop deep learning-based semantic segmentation models for the localization of these weed classes. The dataset was further augmented to cater for the need of a large sample set of the Transformer models. A study was conducted to evaluate the results of three types of Transformer architectures, which included Swin Transformer, SegFormer and Segmenter, on the dataset, with SegFormer achieving final Mean Accuracy (mAcc) and Mean Intersection of Union (mIoU) of 75.18% and 65.74%, while also being the least computationally expensive, with just 3.7 M parameters.

Molecular basis of strigolactone perception in root-parasitic plants: aiming to control its germination with strigolactone agonists/antagonists.

The genus Striga, also called "witchweed", is a member of the family Orobanchaceae, which is a major family of root-parasitic plants. Striga can lead to the formation of seed stocks in the soil and to explosive expansion with enormous seed production and stability once the crops they parasitize are cultivated. Understanding the molecular mechanism underlying the communication between Striga and their host plants through natural seed germination stimulants, "strigolactones (SLs)", is required to develop the technology for Striga control. This review outlines recent findings on the SL perception mechanism, which have been accumulated in Striga hermonthica by the similarity of the protein components that regulate SL signaling in nonparasitic model plants, including Arabidopsis and rice. HTL/KAI2 homologs were identified as SL receptors in the process of Striga seed germination. Recently, this molecular basis has further promoted the development of various types of SL agonists/antagonists as seed germination stimulants or inhibitors. Such chemical compounds are also useful to elucidate the dynamic behavior of SL receptors and the regulation of SL signaling.

Selective fertilization with phosphite allows unhindered growth of cotton plants expressing the ptxD gene while suppressing weeds.

Weeds, which have been the bane of agriculture since the beginning of civilization, are managed manually, mechanically, and, more recently, by chemicals. However, chemical control options are rapidly shrinking due to the recent rise in the number of herbicide-resistant weeds in crop fields, with few alternatives on the horizon. Therefore, there is an urgent need for alternative weed suppression systems to sustain crop productivity while reducing our dependence on herbicides and tillage. Such a development will also allay some of the negative perceptions associated with the use of herbicide-resistance genes and heavy dependence on herbicides. Transgenic plants expressing the bacterial phosphite dehydrogenase (ptxD) gene gain an ability to convert phosphite (Phi) into orthophosphate [Pi, the metabolizable form of phosphorus (P)]. Such plants allow for a selective fertilization scheme, based on Phi as the sole source of P for the crop, while offering an effective alternative for suppressing weed growth. Here, we show that, when P is supplied in the form of Phi, ptxD-expressing cotton (Gossypium hirsutum L.) plants outcompete, in both artificial substrates and natural soils from agricultural fields, three different monocot and dicot weed species intentionally introduced in the experiments, as well as weeds naturally present in the tested soils. Importantly, the ptxD/Phi system proved highly efficacious in inhibiting the growth of glyphosate-resistant Palmer amaranth. With over 250 weed species resistant to currently available herbicides, ptxD-transgenic plants fertilized with Phi could provide an effective alternative to suppressing the growth of these weeds while providing adequate nutrition to the crop.

Bioactive Diterpenes from the Brazilian Native Plant (Moquiniastrum pulchrum) and Their Application in Weed Control.

Even today, weeds continue to be a considerable problem for agriculture. The application of synthetic herbicides produces serious environmental consequences, and crops suffer loss of their activity due to the appearance of new resistant weed biotypes. Our aim is to develop new effective natural herbicides that improve the problem of resistance and do not harm the environment. This work is focused on a bioassay-guided isolation and the characterization of natural products present in Moquiniastrum pulchrum leaves with phytotoxic activity and its preliminary application in weeds. Moquiniastrum pulchrum was selected for two reasons: it is an abundant species in the Cerrado region (the second most important ecosystem in Brazil, after the Amazon)-the explanation behind its being a dominant species is a major focus of interest-and it has traditional employment in folk medicine. Six major compounds were isolated in this plant: one flavone and five diterpenes, two of which are described for the first time in the literature. Four of the six compounds exhibited phytotoxic activity in the bioassays performed. The results confirmed the phytotoxic potential of this plant, which had not been investigated until now.

Strigolactones, from Plants to Human Health: Achievements and Challenges.

Strigolactones (SLs) are a class of sesquiterpenoid plant hormones that play a role in the response of plants to various biotic and abiotic stresses. When released into the rhizosphere, they are perceived by both beneficial symbiotic mycorrhizal fungi and parasitic plants. Due to their multiple roles, SLs are potentially interesting agricultural targets. Indeed, the use of SLs as agrochemicals can favor sustainable agriculture via multiple mechanisms, including shaping root architecture, promoting ideal branching, stimulating nutrient assimilation, controlling parasitic weeds, mitigating drought and enhancing mycorrhization. Moreover, over the last few years, a number of studies have shed light onto the effects exerted by SLs on human cells and on their possible applications in medicine. For example, SLs have been demonstrated to play a key role in the control of pathways related to apoptosis and inflammation. The elucidation of the molecular mechanisms behind their action has inspired further investigations into their effects on human cells and their possible uses as anti-cancer and antimicrobial agents.

Effects of mixtures of allelopathic plant water extracts and a herbicide on weed suppression.

The present study investigated integrated effects of two allelopathic plant water extracts (WE) (Ambrosia artemisiifolia [AMBEL] and Xanthium strumarium [XANST]) and a herbicide (mesotrione) on morphological (height and fresh weight of plants) and physiological (pigments content) parameters of Abutilon theophrasti and Chenopodium album. Also, the study aimed to identify the main components of AMBEL and XANST WE and to evaluate their potential allelopathic effects. Of the 18 investigated compounds, 13 were detected in both tested WE, and p-coumaric acid was the leading component in AMBEL, while quinic acid was the predominant component of XANST. The WE of both weed species and their mixtures with the herbicide exhibited more powerful allelopathic effects on fresh weight and content of pigments than on the height of A. theophrasti and C. album. The results showed that all measured parameters of both weeds were inhibited in treatments with mesotrione and its mix with AMBEL and XANST WE. The data revealed a highly significant difference in effects (P < 0.05) between control weeds and those treated with AMBEL WE and mesotrione, where the inhibition of fresh weight was over 90%, while the inhibition of pigments content exceeded 80%, and plant height was inhibited by over 70%.

Phytochemical Study of Safflower Roots (Carthamus tinctorius) on the Induction of Parasitic Plant Germination and Weed Control.

Weeds have been a major threat in agriculture for several generations as they lead to decreases in productivity and cause significant economic losses. Parasitic plants are a specific type of weed causing losses in crops of great relevance. A new strategy has emerged in the fight against parasitic plants, which is called 'suicidal germination' or the 'honey-pot strategy'. Regarding the problem of weed control from an ecological point of view, it is interesting to investigate new natural compounds with allelopathic activity with the aim of developing new natural herbicides that can inhibit the growth of weeds without damaging the environment. Safflower crops have been affected by parasitic plants and weeds and, as a consequence, the secondary metabolites exuded by safflower roots have been studied. The sesquiterpene lactone dehydrocostuslactone was isolated and characterised, and the structurally related costunolide was identified by UHPLC-MS/MS in safflower root exudates. These sesquiterpene lactones have been shown to stimulate germination of Phelipanche ramosa and Orobanche cumana seeds. In addition, these compounds were phytotoxic on three important weeds in agriculture, namely Lolium perenne, Lolium rigidum and Echinochloa crus-galli. The exudation of the strigolactones solanacol and fabacyl acetate have also been confirmed by UHPLC-MS/MS. The study reported here contributes to our knowledge of the ecological role played by some secondary metabolites. Moreover, this knowledge could help identify new models for the development of future agrochemicals based on natural products.

Preliminary screening of rhizobacteria for biocontrol of little seed canary grass (Phalaris minor Retz.) and wild oat (Avena fatua L.) in wheat.

Conventional weed control methods often have environmental impact. The present study was conducted to screen selected accessions of Pseudomonas for both potential biocontrol of Phalaris minor and Avena fatua and potential concurrent growth promotion of wheat. The four Pseudomonas strains (B11, T19, T24, and T75) were found positive for cyanide production, siderophore production, phosphorus solubilization, oxidase activity, catalase activity, and ACC deaminase activity in vitro. These strains were phytotoxic, causing up to 73.3% mortality in the lettuce seedling bioassay. Consortia of compatible Pseudomonas strains increased A. fatua and P. minor seedling mortality up to 50.0% and 56.7%, respectively, and reduced root length up to 73.8% and 53.9%, respectively, as compared with the uninoculated control. Consortia of compatible Pseudomonas strains increased wheat shoot length, root length, fresh biomass, dry biomass, and leaf greenness up to 41.6%, 100%, 79.9%, 81.5%, and 21.1%, respectively, over the uninoculated control. Four of the 11 Pseudomonas consortia tested expressed good weed suppression and wheat growth promotion capacity and deserve further experimentation. The findings from this study may lead to the formulation of bioherbicides that will improve human and environmental health.

Sorption and desorption of pendimethalin alone and mixed with adjuvant in soil and sugarcane straw.

Sugarcane straw may work as a physical barrier for pre-emergent herbicides and interact with their molecules, increasing sorption process. Adjuvants may change herbicides dynamics in the environment and improve their efficiency for weed control. The objective of this work was to evaluate sorption and desorption of pendimethalin alone and in mixture with adjuvant in soil and sugarcane straw. Sorption experiments were performed using pendimethalin alone and in mixture with vegetable oil with herbicide solution concentrations ranging between 2.5 and 40 µg mL-1 for both conditions. Sorption distribution coefficient (Kd) for soil was 18.48 mL g-1 using pendimethalin alone. Kd value was not determined when pendimethalin was in mixture with adjuvant due to the complete retention of the herbicide in the soil regardless of the initial aqueous phase concentration. Sugarcane straw sorption experiment had Kd values corresponding to 355.52 and 27.24 mL g-1 for pendimethalin alone and in mixture with adjuvant, respectively, indicating the addition of vegetable oil may significantly decrease pendimethalin retention in the straw and could improve weed control. Besides all desorption coefficients were higher than the respective sorption coefficients, which means that the sorption process may be considered irreversible.

Endophytic fungal extracts: evaluation as photosynthesis and weed growth inhibitors.

A central pillar of modern weed control is the discovery of new herbicides which are nontoxic to humans and the environment and which have low application dosage. The natural products found in plants and microorganisms are well suited in this context because they are generally nontoxic and have a wide variety of biological activities. In this work, Diaporthe phaseolorum (Dp), Penicillium simplicissimum (Ps) and Trichoderma spirale (Ts) (methanolic extracts) were evaluated as photosynthesis and plant growth inhibitors in Senna occidentalis and Ipomoea grandifolia. The most significant results were observed for Ts and Dp in S. occidentalis and I. grandifolia, respectively. Ts reduced PI(abs), ET0/CS0, PHI(E0) and PSI0 parameters by 64, 28, 40 and 38%, respectively, indicating a reduction on electron transport efficiency. Additionally, Ts decreased shoot length by 9%, affecting the plant growth. Dp reduced PI(abs), ET0/CS0 and PHI(E0) parameters by 50, 20, 26 and 22%, respectively, revealing the inhibition competency on PSII acceptor site. Furthermore, Dp decreased by 50% the shoot length on germination assay. Thus, the phytotoxic behaviors based on endophytic fungal extracts may serve as a valuable tool in the further development of a bioherbicide since natural products represent an interesting alternative to replace commercial herbicides.