Abstract The rapid adoption of spray drones in agriculture has outpaced the scientific research needed to support their effective and safe use. While current research on spray drones has examined parameters like flight speed, flight height, application rate, and droplet sizes, the combined effects of spray width and droplet size settings remain unstudied, especially for spot spray applications. This study employed a three by three randomized complete block design to evaluate deposition and drift responses using a DJI Agras T40 drone. Water-sensitive cards were sprayed with water in a single pass under three spray width settings (3.0, 4.6, and 6.1 m) and three droplet size settings (220, 280, and 340 µm). Wider spray widths (4.6 and 6.1 m) and larger droplet size settings (340 µm) significantly increased application volume observed on water-sensitive cards, reflecting higher flow rates and lesser susceptibility of droplets to downwash effects. Increased flow rates reduce centrifugal nozzle spin, which resulted in significantly larger average droplet diameters at the 6.1-m setting. Effective swath width (ESW) measurements varied by method. The bilateral method produced the widest ESWs, whereas the 50% deposition and ESW30 methods produced ESWs at or below intended spray widths. Despite uniform droplet distribution (diameter variation coefficient <20%), substantial drift occurred, extending up to eight times the intended spray width. Overall, our data suggests that increasing spray width settings to 4.6 m and 6.1 m and droplet size settings to 340 μm improved deposition and reduced drift due to greater droplet sizes; however, programmed settings did not consistently reflect field outcomes. This shows the need to (1) account for high drift potential in prescription mapping, (2) conduct field calibrations to optimize ESW selection and overlap, and (3) modify flight plans and spray formulations to better align programmed and actual spray performance.
Abstract Resurgence of weedy rice ( Oryza spp.) poses a growing threat to California rice production due to its high genetic diversity, seed dormancy, seedbank persistence, and lack of registered herbicides for in-season control. Cultural methods like fall tillage and winter flooding may offer control. Therefore, outdoor experiments were conducted in Colusa County, CA, from 2019 to 2021 to evaluate the effects of winter flooding (no flood vs. 10-cm flood), burial depth (2-cm shallow vs. 6-cm deep), and duration (30, 60, 90 d) on seed mortality and dormancy of four weedy rice biotypes (B1, B2, B3, and B5) in comparison with a commercial rice cultivar (‘M-206’). Flooding had no significant main effect in 2019 but increased overall mortality in 2020 to 2021 (24% no flood vs. 32% flood). Shallow burial (41%) produced greater mortality than deep burial (28%) in 2019; this pattern reversed in 2020 to 2021 (deep 30%, shallow 26%). Burial duration increased mortality from 19% (30 d) to 46% (90 d) in 2019 and from 13% to 44% in 2020 to 2021. Flooding increased M-206 (38% to 62%) and B2 (25% to 34%) mortality in 2020 to 2021, reduced B1 mortality (13% to 7%, indicating anaerobic protection), and reversed direction for B3 and B5 between year strata. Under no-flood conditions, B1 (65%) and B5 (82% in 2019) mortality peaked at 90 d under shallow burial; flooding suppressed this depth effect. Year effects were substantial, with 2019 producing consistently higher mortality coinciding with subzero minimum air temperatures (−0.5 to −2.8 C) within the first three burial days and above-average precipitation. Flooding-induced secondary dormancy was restricted to B1 (deep burial) in 2019; in 2020 to 2021, M-206, B1, B2, and B3 showed the same response, but B5 did not. These biotype-specific responses confirm that winter management strategies must be tailored to weed population composition.
Abstract Common lambsquarters ( Chenopodium album L.) is one of the most troublesome weeds in Atlantic Canadian potato ( Solanum tuberosum L.) production systems. A high proportion of C. album in this region has been identified as resistant to commonly used herbicides and has become increasingly difficult to control with existing management practices. Atlantic potato producers have adopted cover crops into their rotations for soil conservation and nutrient cycling benefits, as well as suppression of crop pests, including weeds. Four cover crops and termination methods were evaluated for their ability to suppress C. album populations in a potato rotation at Harrington, PE, and Fredericton, NB, from 2018 to 2020. Brown mustard [ Brassica juncea (L.) Czern.], buckwheat ( Fagopyrum esculentum Moench), timothy ( Phleum pratense L.), and a mixture of hairy vetch ( Vicia villosa Roth), annual ryegrass [ Lolium perenne L. ssp. multiflorum (Lam.) Husnot], and crimson clover ( Trifolium incarnatum L.), were spring sowed and terminated by mowing, roller-crimping, disking, or glyphosate in fall. Effects of cover crops and termination methods were consistently greater at Fredericton than at Harrington and were attributed to lower initial C. album seedbank density. Buckwheat and brown mustard cover crops established rapidly and reduced C. album densities in the subsequent potato crop by greater than 46%. Termination via disking and glyphosate improved marketable yields, yet the soil incorporation through disking buckwheat maximized the weed suppressive effects and reduced the germinable fraction of the C. album seedbank by 64% when compared with glyphosate. Our results highlight the importance of the starting seedbank density on the success of weed management tactics, where higher initial weed seedbank density can hinder the success of cover crop establishment in potato rotations. Further, these results verify the importance of proper cover crop selection for managing the seedbank in potato rotations and reduce the impact of herbicide-resistant weeds on production systems.
Abstract Barnyardgrass [ Echinochloa crus-galli (L.) P. Beauv.] is one of the most problematic weeds in Kerala rice ( Oryza sativa L.) ecosystems because of its morphological similarity to rice and its potential to cause substantial yield losses. This study evaluated integrated cultural weed management strategies by examining the effects of seed burial depth, flooding depth, and rice straw mulch on weed emergence and seedling vigor. Surface-sown seeds recorded the highest emergence, whereas burial at 1 cm reduced emergence by 84%, with negligible emergence (<1%) at burial depths of 6 to 8 cm. Flooding significantly suppressed weed establishment, with a water depth of 5 cm reducing emergence by 75% and seedling biomass by 83%, while depths of ≥6 cm completely inhibited emergence. Rice straw mulch also effectively reduced weed emergence by 50% or more at application rates of 6,000 to 8,000 kg ha −1 and completely prevented emergence at 10,000 kg ha⁻ 1 . Correlation analysis revealed significant negative relationships between seed burial depth, flooding depth, mulch rate, and weed emergence and seedling vigor. Regression analysis showed significant negative linear relationships between seedling biomass and both seed burial depth and mulch rate, and between seedling length and these factors, whereas the response to flooding depth was best described by a significant quadratic model. Integrating deep tillage or the stale seedbed technique with appropriate water management in wet direct-seeded rice or rice straw mulching (6,000 to 10,000 kg ha⁻ 1 ) in aerobic and rainfed upland rice, can suppress E. crus-galli emergence and growth by 80% to 100%, providing a sustainable alternative to herbicide-based weed management.
Abstract In the wild blueberry ( Vaccinium angustifolium Aiton) system, perennial weeds are a significant challenge. Weeds compete for resources and have a patchy, heterogeneous distribution, often growing among the rhizome of the crop. Producers broadcast spray herbicides to control weeds, but currently seek to lower costs, reduce environmental impact, and mitigate herbicide resistance. Site-specific weed management (SSWM) using weed maps offers a targeted solution, but its adoption is limited by the lack of software compatible with commercial spray equipment and by technological constraints, such as weed patch size thresholds. The objective of this work is to suggest new weed-mapping workflows for ground and drone spraying in wild blueberry fields using RGB drone imagery processed in drone-compatible GIS software: PIX4Dfields. Drone aerial imagery from two commercial wild blueberry fields in Maine was captured in May 2025. To create maps for ground spot spraying, PIX4Dfield’s machine learning-driven “Magic Tool” and five vegetation Index Tool workflows were assessed. For drone zone spraying, maps created with minimum weed patch sizes of 9.3 m 2 and 405 m 2 were evaluated. All maps were validated using image-based and ground-based accuracy assessments. The “Magic Tool” workflow proved most effective for ground spray maps, achieving ≤98% (image-based) and ≤86% (ground-based) overall accuracy. Among the vegetation indices, the Triangular Greenness Index performed best (≤93% and ≤85% image-based and ground-based accuracies, respectively) at a 20% to 25% pixel exclusion level. For drone zone spraying, the 9.3-m 2 minimum weed patch size yielded higher accuracy than the 405-m 2 size, although performance was site dependent. Classification accuracy decreased at sites with greater weed species diversity, more uniform weed distribution, and when evaluated against more reliable ground-based reference data. Nevertheless, the resulting maps identified weed coverage ranges of 39% to 52% and 58% to 61% across the two fields, giving growers a practical tool to reduce inputs and implement SSWM.
