Weed management is a significant challenge that must be addressed both globally and in Australia, where traditional methods of control have become limited. The avoidance of mechanical practices has resulted in reduced erosion but has also led to an increased reliance on chemicals and a subsequent increase in rates of herbicide resistance. To address this challenge, alternative forms of weed management, such as electric weed control (electro-weeding), need to be considered. Electric weed control functions by transferring electrical current through the target plant following electrode contact, causing the plant’s cells to burst and either killing the plant or suppressing its growth. However, a multitude of variables, such as electrical power and speed of application, weed morphology, and site-specific environmental conditions, can impact the use of electric weed control and its efficacy. While electric weed control holds promise, and despite its recent global popularity with numerous companies producing machinery, the applicability, efficacy, and risks of using electric weed control internationally and in Australia have yet to be thoroughly analyzed. Given the existing knowledge gaps, this review provides a comprehensive overview of the theory and recent advances in electric weed control. Additionally, the review discusses the potential for resistance development and safety risks associated with electric weed control and presents an overview of modern machines and their application in various settings. It also highlights the need for further research to determine the applicability and efficacy of implementing this new weed control method before widespread adoption and integration into pest management strategies.

This review summarizes what is currently known about herbicide resistance in Bromus spp. worldwide. Additional information on the biology and genetics of Bromus spp. is provided to further the understanding of resistance evolution and dispersal of the different species. Cases of herbicide resistance have been confirmed in Bromus catharticus Vahl., Bromus commutatus Schrad. (syn.: Bromus racemosus L.), Bromus diandrus Roth, Bromus japonicus Thunb. (syn.: Bromus arvensis L.), Bromus madritensis L., Bromus rigidus Roth (syn.: Bromus diandrus Roth ssp. diandrus), Bromus rubens L., Bromus secalinus L., Bromus sterilis L., and Bromus tectorum L. in 11 countries. Bromus spp. populations have evolved cross- and multiple resistance to six herbicide sites of action: acetyl-coenzyme A carboxylase, acetolactate synthase, photosystem II, very-long-chain fatty-acid, 5-enolpyruvylshikimate-3-phosphate synthase, and 4-hydroxyphenylpyruvate dioxygenase inhibitors. Resistance mechanisms varied from target-site to non–target site or a combination of both. Bromus spp. are generally highly self-pollinated, but outcrossing can occur at low levels in some species. Bromus spp. have different ploidy levels, ranging from diploid (2n = 2x = 14) to duodecaploid (2n = 12x = 84). Herbicide resistance in Bromus spp. is a global issue, and the spread of herbicide-resistance alleles primarily occurs via seed-mediated gene flow. However, the transfer of herbicide-resistance alleles via pollen-mediated gene flow is possible.

Mitotic-inhibiting herbicides, like prodiamine and dithiopyr, are used to control annual bluegrass (Poa annua L.) preemergence in managed turfgrass; however, resistance to mitotic-inhibiting herbicides has evolved due to repeated applications of herbicide from a single mechanism of action. Three suspected resistant populations (R1, R2, and R3) were collected in Alabama and Florida and screened for resistance to prodiamine. Part of the α-tubulin gene was sequenced for known target-site mutations. Target-site mutations were reported in all three R populations, with each containing an amino acid substitution at position 239 from threonine to isoleucine (Thr-239-Ile). Previous research has indicated that the Thr-239-Ile mutation confers resistance to dinitroaniline herbicides in other species. Dose–response screens using prodiamine and dithiopyr were conducted and I50 values were calculated for R1, R2, and R3 using regression models based on seedling emergence. For prodiamine, I50 values for R1, R2, and R3 were 35.3, 502.7, and 91.5 g ai ha−1, respectively, resulting in 2.9-, 41.9-, and 7.6-fold resistance, respectively, when compared with a susceptible (S) population. For dithiopyr, I50 values for R1, R2, and R3 were 154.0, 114.2, and 190.1 g ai ha−1, respectively, resulting in 3.6-, 2.7-, and 4.5-fold resistance, respectively, when compared with an S population. When comparing I90 values with the highest labeled use rates, R2 had a 2.9-fold level of resistance to prodiamine, and R1, R2, and R3 had a 2.4-, 2.0-, and 3.2-fold levels of resistance to dithiopyr, respectively. This is the first report of a variable response in P. annua to prodiamine despite each R population possessing the same mutation.

Site-specific weed management (on the scale of a few meters or less) has the potential to greatly reduce pesticide use and its associated environmental and economic costs. A prerequisite for site-specific weed management is the availability of accurate maps of the weed population that can be generated quickly and cheaply. Improvements and cost reductions in unmanned aerial vehicles (UAVs) and camera technology mean these tools are now readily available for agricultural use. We used UAVs to collect aerial images captured in both RGB and multispectral formats of 12 cereal fields (wheat [Triticum aestivum L.] and barley [Hordeum vulgare L.]) across eastern England. These data were used to train machine learning models to generate prediction maps of locations of black-grass (Alopecurus myosuroides Huds.), a prolific weed in UK cereal fields. We tested machine learning and data set resampling methods to obtain the most accurate system for predicting the presence and absence of weeds in new out-of-sample fields. The accuracy of the system in predicting the absence of A. myosuroides is 69% and its presence above 5 g in weight with 77% accuracy in new out-of-sample fields. This system generates prediction maps that can be used by either agricultural machinery or autonomous robotic platforms for precision weed management. Improvements to the accuracy can be made by increasing the number of fields and samples in the data set and the length of time over which data are collected to gather data across the entire growing season.

Purple nutsedge (Cyperus rotundus L.) is a globally distributed noxious weed that poses a significant challenge for control due to its fast and efficient propagation through the tuber, which is the primary reproductive organ. Gibberellic acid (GA3) has proven to be crucial for tuberization in tuberous plants. Therefore, understanding the relationship between GA3 and tuber development and propagation of C. rotundus will provide valuable information for controlling this weed. This study shows that the GA3 content decreases with tuber development, which corresponds to lower expression of bioactive GA3 synthesis genes (CrGA20ox, two CrGA3ox genes) and two upregulated GA3 catabolism genes (CrGA2ox genes), indicating that GA3 is involved in tuber development. Simultaneously, the expression of two CrDELLA genes and CrGID1 declines with tuber growth and decreased GA3, and yeast two-hybrid assays confirm that the GA3 signaling is DELLA-dependent. Furthermore, exogenous application of GA3 markedly reduces the number and the width of tubers and represses the growth of the tuber chain, further confirming the negative impact that GA3 has on tuber development and propagation. Taken together, these results demonstrate that GA3 is involved in tuber development and regulated by the DELLA-dependent pathway in C. rotundus and plays a negative role in tuber development and propagation.

African mustard (Brassica tournefortii Gouan), turnipweed [Rapistrum rugosum (L.) All.], and African turnipweed (Sisymbrium thellungii O.E. Schulz) are common broadleaf weeds in chickpea (Cicer arietinum L.) crops, particularly under dryland region conditions in eastern Australia. Information on crop yield losses and the seed production potential for these weeds in chickpea are limited. Field studies were conducted in the winter seasons of 2020 and 2021 in eastern Australia with different densities of the three weeds (B. tournefortii, R. rugosum, and S. thellungii) in chickpea. Based on the sigmoidal model, chickpea yield was reduced by 50% at 11 plants m−2 of B. tournefortii. Based on hyperbolic models, a 50% yield reduction of chickpea occurred at 5 and 25 plants m−2 of R. rugosum and S. thellungii, respectively. Based on the linear model, B. tournefortii, R. rugosum, and S. thellungii produced a maximum of 448,000, 206,700, and 869,400, seeds m−2, respectively. At chickpea harvest, the low seed retention (<55%) of B. tournefortii and S. thellungii suggests limited opportunities for harvest weed seed control, and the seed rain of these weeds may enrich the weed seedbank in the soil. At crop harvest, the seed retention of R. rugosum was found to be greater than 90%, suggesting that it is a suitable candidate for harvest weed seed control. This study demonstrated that R. rugosum could cause a greater reduction in chickpea yield compared with B. tournefortii and S. thellungii. Furthermore, restricting seed rain of B. tournefortii and S. thellungii by not allowing the plants to produce seeds is recommended to reduce their weed seedbanks in the soil. The information generated from this study could aid in strengthening integrated weed management in chickpea.

The extent to which weed species vary in their ability to acquire and use different forms of nitrogen (N) (inorganic and organic) has not been investigated but could have important implications for weed survival and weed–crop competition in agroecosystems. We conducted a controlled environment experiment using stable isotopes to determine the uptake and partitioning of organic and inorganic N (amino acids, ammonium, and nitrate) by seven common weed and non-weed species. All species took up inorganic and organic N, including as intact amino acids. Concentrations of 15N derived from both ammonium and amino acids in shoot tissues were higher in large crabgrass [Digitaria sanguinalis (L.) Scop.] and barnyardgrass [Echinochloa crus-galli (L.) P. Beauv] than in common lambsquarters (Chenopodium album L.), redroot pigweed (Amaranthus retroflexus L.), and sorghum-sudangrass [Sorghum bicolor (L.) Moench × Sorghum bicolor (L.) ssp. drummondii (Nees ex Steud.) de Wet & Harlan]. In contrast, the concentration of 15N derived from nitrate was higher in wild mustard (Sinapis arvensis L.) shoots than in wild oat (Avena fatua L.) shoots. Root concentration of 15N derived from ammonium was lower in sorghum-sudangrass compared with other species, except for A. retroflexus and A. fatua, while root concentration of 15N derived from nitrate was lower in A. retroflexus compared with other species, except for C. album and S. arvensis. Discriminant analysis classified species based on their uptake and partitioning of all three labeled N forms. These results suggest that common agricultural weeds can access and use organic N and differentially take up inorganic N forms. Additional research is needed to determine whether species-specific differences in organic and inorganic N uptake influence the intensity of competition for soil N.

No-till planting organic soybean [Glycine max (L.) Merr.] into roller-crimped cereal rye (Secale cereale L.) can have several advantages over traditional tillage-based organic production. However, suboptimal cereal rye growth in fields with large populations of weeds may result in reduced weed suppression, weed–crop competition, and soybean yield loss. Ecological weed management theory suggests that integrating multiple management practices that may be weakly effective on their own can collectively provide high levels of weed suppression. In 2021 and 2022, a field experiment was conducted in central New York to evaluate the performance of three weed management tactics implemented alone and in combination in organic no-till soybean planted into both cereal rye mulch and no mulch: (1) increasing crop seeding rate, (2) interrow mowing, and (3) weed electrocution. A nontreated control treatment that did not receive any weed management and a weed-free control treatment were also included. Cereal rye was absent from two of the five fields where the experiment was repeated; however, the presence of cereal rye did not differentially affect results, and thus data were pooled across fields. All treatments that included interrow mowing reduced weed biomass by at least 60% and increased soybean yield by 14% compared with the nontreated control. The use of a high seeding rate or weed electrocution, alone or in combination, did not improve weed suppression or soybean yield relative to the nontreated control. Soybean yield across all treatments was at least 22% lower than in the weed-free control plot. Future research should explore the effects of the tactics tested on weed population and community dynamics over an extended period. Indirect effects from interrow mowing and weed electrocution should also be studied, such as the potential for improved harvestability, decreased weed seed production and viability, and the impacts on soil organisms and agroecosystem biodiversity.

Preemergence herbicides associated with cereal rye (Secale cereale L.) cover crop (hereafter “cereal rye”) can be an effective waterhemp [Amaranthus tuberculatus (Moq.) Sauer.] and Palmer amaranth (Amaranthus palmeri S. Watson) management strategy in soybean [Glycine max (L.) Merr.] production. Delaying cereal rye termination until soybean planting (planting green) optimizes biomass production and weed suppression but might further impact the fate of preemergence herbicides. Limited research is available on the fate of preemergence herbicides applied over living cereal rye in the planting green system. Field experiments were conducted in Illinois, Kansas, Pennsylvania, and Wisconsin to evaluate the fate of flumioxazin and pyroxasulfone and Amaranthus spp. residual control under different cover crop management practices in soybean in 2021 and 2022 (8 site-years). A flumioxazin + pyroxasulfone herbicide premix was applied preemergence at soybean planting under no-till without cereal rye, cereal rye early terminated before soybean planting, and cereal rye terminated at soybean planting. Flumioxazin and pyroxasulfone concentrations in the soil were quantified at 0, 7, and 21 d after treatment (DAT), and Amaranthus spp. density was determined at postemergence herbicide application. The presence of cereal rye biomass intercepted flumioxazin and pyroxasulfone at preemergence application and reduced concentration in the soil when compared with no-till, mainly at 0 DAT. Main differences in herbicide concentration were observed between no-till and cereal rye treatments rather than cereal rye termination times. Despite reducing herbicide concentration in the soil, the presence of the cereal rye biomass did not affect early-season residual Amaranthus spp. control. The adoption of effective preemergence herbicides associated with a properly managed cereal rye cover crop is an effective option for integrated Amaranthus spp. management programs in soybean production systems.

The herbicide 2,4-D is commonly used for sucker control in hazelnut (Corylus avellana L.). However, the use of 2,4-D for sucker control has been implicated in delaying natural abscission in hazelnut. Hazelnuts naturally abscise and are collected from the orchard floor. Delays in abscission may reduce nut quality due to the onset of the rainy season, increasing mold and mud in the nuts. The effect of basal-directed applications of 2,4-D on hazelnut abscission, yield, and quality was assessed. In the first study, four basal-directed applications of 2,4-D (1.06 kg ae ha−1) did not affect hazelnut abscission, yield, or quality compared with glufosinate (1.1 kg ai ha−1) or manual pruning. In a second 3-yr study, a single yearly simulated drift of 2,4-D to the tree canopy at 0.06 and 0.6 mg L−1 increased the growing degree-day requirement from 50 to 141 to reach 50% hazelnut abscission, compared with the nontreated control. This is the equivalent of 5 to 15 calendar days. No effect was observed in the third year of the study when the simulated drift was not performed. No differences in abscission were observed with basal-directed applications of 2,4-D at rates up to 4.4 kg ha−1 when applied four times each season during all 3 yr of the study. Simulated drift reduced hazelnut yield by up to 37% and reduced the percentage of marketable nuts during 1 yr of the study. No effect on average kernel weight was observed. However, 2,4-D drift did delay hazelnut abscission, highlighting the importance of drift control measures.