Plants have numerous strategies for phytoremediation depending upon the characteristic of pollutants. Plant growth promoting rhizobacteria (PGPR) are essential to the process of phytoremediation and play a key part in it. The mechanism of PGPR for phytoremediation is mediated by two methods; under the direct method there is phytohormone production, nitrogen fixation, nutrient mineral solubilization, and siderophore production while the indirect method includes quorum quenching, antibiosis, production of lytic enzyme, biofilm formation, and hydrogen cyanide production. Due to their economic and environmental viability, most researchers have recently concentrated on the potential of weed plants for phytoremediation. Although weed plants are considered unwanted and noxious, they have a high growth rate and adaptability which opens a high scope for its role in phytoremediation of contaminated site. The interaction of plant with rhizobacteria starts from root exudates containing various organic acids and peptides which act as nutrients essential for colonization and siderophore production by the rhizospheric bacteria. The rhizobacteria, while colonizing, tend to promote plant growth and health either directly by providing phytohormones and minerals or indirectly by suppressing growth of possible phytopathogens. Recently, several weed plants have been reported for phytoextraction of heavy metals (Ni, Pb, Zn, Hg, Cd, Cu, As, Fe, and Cr) contaminants from various agro-based industries. These potential native weed plants have high prospect of eco-restoration of polluted site with complex organo-metallic waste for sustainable development.

Together with rice, weeds strive for nutrients and space in farmland, resulting in reduced rice yield and quality. Planting herbicide-resistant rice varieties is one of the effective ways to control weeds. In recent years, a series of breakthroughs have been made to generate herbicide-resistant germplasm, especially the emergence of biotechnological tools such as gene editing, which provides an inherent advantage for the knock-out or knock-in of the desired genes. In order to develop herbicide-resistant rice germplasm resources, gene manipulation has been conducted to enhance the herbicide tolerance of rice varieties through the utilization of techniques such as physical and chemical mutagenesis, as well as genome editing. Based on the current research and persisting problems in rice paddy fields, research on the generation of herbicide-resistant rice still needs to explore genetic mechanisms, stacking multiple resistant genes in a single genotype, and transgene-free genome editing using the CRISPR system. Current rapidly developing gene editing technologies can be used to mutate herbicide target genes, enabling targeted genes to maintain their biological functions, and reducing the binding ability of target gene encoded proteins to corresponding herbicides, ultimately resulting in herbicide-resistant crops. In this review article, we have summarized the utilization of conventional and modern approaches to develop herbicide-resistant cultivars in rice as an effective strategy for weed control in paddy fields, and discussed the technology and research directions for creating herbicide-resistant rice in the future.

Agricultural weeds frequently hybridize with each other or with related crop species. Some hybrid weeds exhibit heterosis (hybrid vigor), which may be stabilized through mechanisms like genome duplication or vegetative reproduction. Even when heterosis is not stabilized, hybridization events diversify weed gene pools and often enable adaptive introgression. Consequently, hybridization may promote weed evolution and exacerbate weed-crop competition. However, hybridization does not always increase weediness. Even when viable and fertile, hybrid weeds sometimes prove unsuccessful in crop fields. This review provides an overview of weed hybridization and its management implications. We describe intrinsic and extrinsic factors that influence hybrid fitness in agroecosystems. We also survey the rapidly growing literature on crop-weed hybridization and the link between hybridization and invasiveness. These topics are increasingly relevant in this era of genetic tools for crop improvement, intensive and simplified cropping systems, and globalized trade. The review concludes with suggested research priorities, including hybridization in the context of climate change, plant-insect interactions, and redesigned weed management programs. From a weed management perspective, hybridization is one of many reasons that researchers and land managers must diversify their weed control toolkits.

The phytotoxicity of herbicides on crops is a major dilemma in agricultural production. Fortunately, the emergence of herbicide safeners is an excellent solution to this challenge, selectively enhancing the performance of herbicides in controlling weeds while reducing the phytotoxicity to crops. But owing to their potential toxicity, only a tiny proportion of safeners are commercially available. Natural products as safeners have been extensively explored, which are generally safe to mammals and cause little pollution to the environment. They are typically endogenous signal molecules or phytohormones, which are generally difficult to extract and synthesize, and exhibit relatively lower activity than commercial products. Therefore, it is necessary to adopt rational design approaches to modify the structure of natural safeners. This paper reviews the application, safener effects, structural characteristics, and modifications of natural safeners and provides insights on the discovery of natural products as potential safeners in the future.

Invasive plants are known for their impacts to ecosystems and societies, but their potential cultural use tend to be unexplored. One important mechanism of plant invasion is the use of \"allelochemicals\" or \"novel weapons\": chemical defenses which are new to their invaded habitats and that confer them competitive advantages. However, these chemicals are precisely what confers them ethnobotanical and medicinal properties. We reviewed the literature assessing the biogeography of the cultural uses of the model invasive plant yellow-starthistle (Centaurea solstitialis L.; Asteraceae), and assessed the extent to which the introduction of a weed native to Eurasia into several non-native world regions was paralleled by the spread of cultural uses from its native range. We found that the species was rich in pharmaceutically active compounds and that the species had been traditionally used for medicinal purposes, as raw material, and as food. However, ethnobotanical uses were reported almost exclusively in its native range, with no uses described for the non-native range, apart from honey production in California, Argentina, and Australia. Our study exemplifies how, when plant introductions are not paralleled synchronously by significant human migrations, cultural adoption can be extremely slow, even within the native range of the species. Invasive species can provide real-time insights into the cultural processes by which humans learn to use plants. This case study highlights how biological invasions and cultural expansions can be subjected to different constraints.

Climate change is a concern worldwide that could trigger many changes with severe consequences. Since human demography is steadily increasing, agriculture has to be constantly investigated to aim at improving its efficiency. Weeds play a key role in this task, especially in the recent past and at present, when new introductions have been favoured by a rise in tourism and international trade. To obtain knowledge relating weeds and their behaviour to climate change, species distribution models (SDMs) have also increased recently. In this work, we have reviewed some articles published since 2017 on modelled weeds, aiming to give a response to, among other things, the species most studied, the scale and location of the studies, the algorithms used and validation parameters, global change scenarios, types of variables, and the sources from which the data were collected. Fifty-nine articles were selected to be reviewed, with maximum entropy (MaxEnt) and area under the curve (AUC) being the most popular software and validation processes. Environmental and topographic variables were considered above pedological and anthropogenic ones. Europe was the continent and China, the USA, and India the countries most studied. In this review, it was found that the number of published articles between developed and developing countries is unbalanced and comes out in favour of the former. The current knowledge on this topic can be considered to be good not enough, especially in developing countries with high population densities. The more knowledge we can obtain, the better our understanding is of how to deal with this issue, which is a worldwide preoccupation.

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.

Invasive plant species (IPS) are often considered weeds that cause high yield losses in crops, negatively affect the environment, and disrupt certain ecosystem services. The negative impact of IPS on biodiversity is increasing and disturbing native vegetation. The management of plant invasions can be divided in two phases (before and after invasion). Prior to introduction it is crucial to develop the knowledge base (biology, ecology, distribution, impact, management) on IPS, prevention measures and risk assessment. After introduction if eradication fails, the monitoring and the integrated management of IPS are imperative to prevent the naturalization and further dispersal. This review uses two major invasive weed species (Amaranthus palmeri S. Wats. and Solanum elaeagnifolium Cav.) as case studies to propose a framework for early detection, rapid herbicide resistance screening, and integrated management. The holistic framework that is presented exploits recent: (i) novel detection tools, (ii) rapid tests and assays for herbicide resistance, and (iii) biology, ecology, distribution traits, and management tools for the IPS. Farmers, advisors, researchers, and policymakers need briefing on IPS growth dynamics, adaptability rates, and response to conventional and novel treatments to prevent new invasions, eradicate isolated stands, and mitigate the impact of invasive weed species in the long term. © 2022 Society of Chemical Industry.

Detoxification plays an important role in herbicide action. Herbicide safeners selectively protect crops from herbicide injury without reducing the herbicidal efficiency against the target weeds. With the large-scale use of herbicides, herbicide safeners have been widely used in sorghum, wheat, rice, corn, and other crops. In recent years, an increasing number of unexpected new herbicide safeners have been designed. The varieties, structural characteristics, uses, and synthetic routes of commercial herbicide safeners are reviewed in this paper. The design ideas and structural characteristics of novel herbicide safeners are summarized, which provide a basis for the design of bioactive molecules as new herbicide safeners in the future.

The genus Lolium comprises many species, of which L. perenne ssp. multiflorum, L. perenne ssp. perenne, and L. rigidum are of worldwide agricultural importance as both pasture crops and as weeds. These three species are inter-fertile, obligate out-crossers with a self-incompatible reproduction system. This combination contributes to high genetic diversity that supplies new variants during expansion to new natural areas and agricultural environments. Human dispersal, de-domestication and crop-weed hybridization events between Lolium spp., or with others such as Festuca spp., are likely associated with their distinct weediness abilities. Furthermore, new introductions followed by introgression may hasten adaptation to new environments. Most Lolium-related weed science studies have focused on adaptation leading to herbicide resistance, but other forms of adaptation may also occur. In this review, we explore how the wide genetic variation among Lolium species and hybridization with other species may contribute to range expansion, and adaptation to both new agricultural practices and future predicted climate change scenarios. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.