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Relevant bibliographies by topics / Weeds

Academic literature on the topic 'Weeds'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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Journal articles on the topic "Weeds"

1

James, T. K., A. Rahman, and J. Mellsop. "Weed competition in maize crop under different timings for postemergence weed control." New Zealand Plant Protection 53 (August 1, 2000): 269–72. http://dx.doi.org/10.30843/nzpp.2000.53.3706.

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The effect of early weed competition was determined for a maize (Zea mays) crop grown in Waikato Maize was established in three different environments viz weedy (no herbicide) grass weeds (preemergence atrazine) and broadleaf weeds (preemergence metolachlor) Surviving weeds were controlled with postemergence nicosulfuron (60 g/ha) after different periods of competition and the plots kept weed free for the remainder of the trial Weeds left completely uncontrolled for 4 weeks after emergence significantly reduced crop yields When a preemergence herbicide was used surviving weeds began to reduce maize yields after about 6 weeks with grasses having greater effect than broadleaf weeds The actual period before the weeds started affecting crop growth and yield appeared to be related to the time taken by the weeds to achieve complete ground cover

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Place, G. T., S. C. Reberg-Horton, D. L. Jordan, T. G. Isleib, and G. G. Wilkerson. "Influence of Virginia Market Type Genotype on Peanut Response to Weed Interference." Peanut Science 39, no. 1 (January 1, 2012): 22–29. http://dx.doi.org/10.3146/ps10-12.1.

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Abstract Differences in the ability of cultivars to compete with weeds are not well-defined for peanut. Research was conducted in 2007 and 2008 to compare the growth and competitiveness of the virginia market type cultivars NC 10C, NC-V 11, NC 12C, Phillips, VA 98R, and breeding lines N99027L, N01013T, and N02020J under weedy and weed-free conditions. Weed-free peanut was established by applying preemergence and postemergence herbicides throughout the growing season supplemented by weekly hand removal of weeds. Clethodim was applied to weedy peanut to eliminate annual grass interference but not interference from broadleaf weeds and sedges. Weed-free peanut biomass, weedy peanut biomass, and weed biomass were not affected by genotype 10 weeks after peanut emergence. Although substantial yield loss was noted in presence of weeds, the percent yield loss did not vary by genotype when comparing weedy and weed-free yield. These data suggest that cultivar selection within virginia market type peanut will have limited utility in a comprehensive weed management strategy.

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Takim, F. "Weed competition in maize (Zea mays L.) as a function of the timing of hand-hoeing weed control in the southern Guinea savanna zone of Nigeria." Acta Agronomica Hungarica 60, no. 3 (September 1, 2012): 257–64. http://dx.doi.org/10.1556/aagr.60.2012.3.8.

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Field studies were conducted in 2010 and 2011 at the Teaching and Research Farm of the University of Ilorin, Nigeria (9°29′ N, 4°35′ E) to evaluate the effect of early weed competition on the growth and yield of maize. The experiment was designed as a randomized complete block (RCBD) with a split-plot arrangement and three replications. The main plots consisted of three weed control treatments included weedy (no herbicide), grass weeds (pre-emergence atrazine) and broadleaf weeds (pre-emergence metolachlor), while the sub-plots consisted of six durations of weed infestation (3, 4, 5, 6, 7 and 8 weeks after emergence). The pre-emergence herbicides had a greater effect on weed density and weed dry weight. Weed seedling emergence and weed dry weight increased significantly with an increase in the duration of weed interference. The grasses and broadleaf weeds had a similar influence on the growth and grain yield of maize. Three to five weeks of weed interference gave similar grain yields, which were significantly higher than those obtained in plots that had 6-8 weeks of weed interference. These results suggest that the maize crop must be kept free of weeds for 6-8 weeks after the application of pre-emergence herbicide to minimize weed-crop competition and harvest a good grain yield.

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Njoroge, J. M. "Weeds and Weed Control in Coffee." Experimental Agriculture 30, no. 4 (October 1994): 421–29. http://dx.doi.org/10.1017/s0014479700024662.

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SUMMARYThe effects of weeds on coffee productivity and the methods used for their control are discussed. The more common weeds are listed, together with the control methods that can be used at various phases of coffee production.Malezas y control de las mismas en el café

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Hamada, Azhari Abdelazim. "Weeds and Weed Management in Sudan." Journal of Weed Science and Technology 45, no. 2 (2000): 131–36. http://dx.doi.org/10.3719/weed.45.131.

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Mubeen, Khuram, Muhammad Shehzad, Naeem Sarwar, Haseeb ur Rehman, Tauqeer Ahmad Yasir, Allah Wasaya, Matlob Ahmad, et al. "The impact of horse purslane (Trianthema portulacastrum L.) infestation on soybean [Glycine max (L.) Merrill] productivity in northern irrigated plains of Pakistan." PLOS ONE 16, no. 9 (September 20, 2021): e0257083. http://dx.doi.org/10.1371/journal.pone.0257083.

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Horse purslane (Trianthema portulacstrum L.) is an important weed of soybean crop capable of causing significant yield reduction. Therefore, this study assessed the impact of horse purslane and other weeds’ infestation on the productivity of soybean. Ten treatments, i.e., weed-free throughout the growing season, horse purslane-free till 20, 40 and 60 days after emergence (DAE), all weeds-free till 20, 40 and 60 DAE, weedy-check (excluding horse purslane), weedy-check (horse purslane alone) and weedy-check (all weeds) were included in the study. Data relating to density and dry weight of recorded weed species, and yield and related traits of soybean were recorded. Overall, infestation percentage of horse purslane was 33.10 and 51%, whereas dry weight was 12 and 44 g m-2 during 1st and 2nd year, respectively. The highest dry weight of all weed species was recorded at 45 DAE in weedy-check all weeds treatment during both years. The lowest relative density and frequency of horse purslane were recorded in the treatment where it was controlled until 20 DAE during 2018 at 30 DAE, whereas the same treatment recoded the lowest density of horse purslane at 45 DAE during 2019. The relative frequency of horse purslane was non-significant for weedy-check horse purslane and weedy-check all weeds treatments during 2018, whereas former treatment had higher relative frequency of horse purslane in weedy-check all weeds than the later during 2019. Yield and related traits significantly differed among different treatments used in the study. The treatment all weeds controlled until 40 DAE recorded higher number of pods per plant, 1000-seed weight and seed yield during both years. The yield reduction in weedy-check treatments was; weedy-check all weeds > weedy-check all weeds except horse purslane > weedy-check horse purslane only. It is concluded that horse purslane was not the sole weed interfering soybean fields and weed flora consisted of false amaranth [Digera muricata (L.) Mart.] and purple nut sedge (Cyperus rotundus L.). Hence, if the soybean fields in northern irrigated plains of Pakistan are infested with horse purslane or heavily infested with horse purslane or other weeds, these should be controlled in initial 40 DAE to improve soybean productivity.

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A.Y, Mamudu,, and Adeyemi, M. "CRITICAL PERIOD OF WEED INTERFERENCE ON SOYBEAN (GLYCINE MAX (L) MERRILL)." Reviews In Food and Agriculture 3, no. 2 (January 6, 2022): 76–79. http://dx.doi.org/10.26480/rfna.02.2022.76.79.

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Weeds are one of the important factors affecting agriculture production, weeds and inadequate weed control and management pose a detrimental factor affecting crop production. The experiment was conducted at the Teaching and Research Farm of Federal University Technology, Minna, Nigeria, to determine the effectiveness of different weeding regime and critical period of weed interference in the growth and yield of soyabean. The treatments were laid out in a Randomized Complete Block Design (RCBD) and replicated three times. There are ten treatments consisting of weed infested and weed-free as follows T1= soybean + weeding for 2 weeks, T2= soybean + weeding for 4 weeks, T3= soybean + weeding for 6 weeks, T4= soybean + weeding for 8 weeks, T5= soybean + weedy for 2 weeks, T6= soybean + weedy for 4 weeks ,T7= soybean + weedy for 6 weeks, T8= soybean + weedy for 8 weeks, T9= soybean + weed-free plot till end and T10= soybean + no weeding till end. Data were collected on weed cover score, weed dry weight, plant height, pod weight and grain yield. The Data were subjected to analysis of variance using SAS, software version 9, 2002. The results showed that soyabean with weed-free plot for 4, 6 8 and weed-free throughout significantly P<0.05 suppressed weed and increases yield by 70 % compared to other treatments The use of early maturing variety of soybean in addition to weed-free plot throughout the growth stage and weed-free for 8 weeks could be recommended in controlling weed interference in soybean for better soybean growth and yield.

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Jursík, M., J. Holec, J. Soukup, and V. Venclová. "Competitive relationships between sugar beet and weeds in dependence on time of weed control." Plant, Soil and Environment 54, No. 3 (March 19, 2008): 108–16. http://dx.doi.org/10.17221/2687-pse.

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Small plot trials were carried out in years 2001–2003 with sugar beet. In the treatment without weed control, dry weight of sugar beet top and LAI of sugar beet were very low (approx. 50 g/m<sup>2</sup> and 0.5 m<sup>2</sup>/m<sup>2</sup>, respectively). Yield loss of sugar beet was 80–93%. Dominant weeds were <I>Chenopodium album, Fumaria officinalis</I> and <I>Galium aparine</I>. In the treatments where weeds were removed (by hand) until 4 leaf stage of sugar beet, dry weight of sugar beet top and LAI of sugar beet at first increased normally, but were markedly decreased from the half of the vegetation period. Yield loss of sugar beet was 54–28%. Dominant weed in this treatment was <I>Amaranthus retroflexus</I>. The development of sugar beet top dry weight and LAI of sugar beet was practically identical in the treatments where weeds were removed until 8–10 leaf stage of the crop and in those where weeds were removed during the whole vegetation period (500–900 g/m<sup>2</sup>, or 4–7 m<sup>2</sup>/m<sup>2</sup>, respectively). No yield loss of sugar beet was recorded. Dry weight of weeds did not exceed 30 g/m<sup>2</sup> and LAI 0.1 m<sup>2</sup>/m<sup>2</sup>. <I>A. retroflexus</I> and <I>Mercurialis annua</I> were the most frequent weeds in this treatment.

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Moyo, C., K. C. Harrington, P. D. Kemp, and J. P. J. Eerens. "Herbicide deposition on weeds from weed wipers." New Zealand Plant Protection 61 (August 1, 2008): 395. http://dx.doi.org/10.30843/nzpp.2008.61.6873.

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Weed wipers available in New Zealand vary in their mechanisms for delivering herbicide The objective of this experiment was to measure clopyralid output from three weed wipers using a standardised methodology The herbicide output for the Eliminator Rotowiper and Weedswiper was investigated at different speeds of application The herbicide was applied to artificial weeds covered in plastic sleeves folded at the base to collect drips while the three wipers were driven over the artificial weeds The sleeves were then removed and washed with water The resultant solution was then analysed for clopyralid using a spectrophotometer and a predetermined calibration equation The experiment showed there was no relationship between the speed at which wipers were pulled and their herbicide output The Eliminator and Rotowiper had on average twice the output of the Weedswiper although their output was more variable than that of the Weedswiper Because of the variability in output in some wipers the concentration rates to be used in each wiper need to be high enough to compensate for occasional low quantities being wiped on weeds

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Tei, F., P. Montemurro, D. T. Baumann, A. Dobrzanski, R. Giovinazzo, Y. Kleifeld, F. Rocha, et al. "WEEDS AND WEED MANAGEMENT IN PROCESSING TOMATO." Acta Horticulturae, no. 613 (September 2003): 111–21. http://dx.doi.org/10.17660/actahortic.2003.613.13.

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Dissertations / Theses on the topic "Weeds"

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Tracey, Sara A. "In the Weeds." University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1195243379.

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Howatt, Stephen M. (Stephen Michael). "Control of hexazinone tolerant weeds in lowbush blueberries." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61161.

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Field experiments were conducted from 1989 to 1991 to evaluate several sulfonylurea herbicides, glyphosate and clopyralid for the control of bunchberry and other hexazinone tolerant weeds in lowbush blueberry. Broadcast applications of chlorosulfuron, metsulfuron and glyphosate reduced bunchberry densities at all application dates, though crop damage and subsequent yield reductions were unacceptable. Glyphosate was very effective in controlling a large number of plant species when applied as a spot spray treatment. Tribenuron and DPX R9674 were effective in suppressing bunchberry stem densities at all application dates, without major adverse effects on blueberry, and also controlled a large number of hexazinone tolerant weeds when applied as a spot spray treatment. Clopyralid, at rates as low as 100 g a.i. ha$ sp{-1}$, was very effective as a broadcast treatment for the control of tufted vetch, although problems with crop tolerance and yield reductions were evident in some instances. Clopyralid did not control a large number of hexazinone tolerant species when applied as a spot spray treatment.

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Minkey, David Mark. "Weed seed predation by ants in the crop growing areas of Western Australia /." Connect to this title, 2006. http://theses.library.uwa.edu.au/adt-WU2007.0089.

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McGinley, Susan. "Fighting Weeds in Lemon Orchards: Weed-Sensing Sprayer Could be the Key." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2002. http://hdl.handle.net/10150/622246.

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Mühleisen, Martin Bernd. "Chemical weed control : options in fibre flax." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0031/MQ64411.pdf.

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Sciegienka, Joanna Katarzyna. "Vegetative reproduction and the integrated management of Canada thistle." Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/sciegienka/SciegienkaJ0509.pdf.

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Canada thistle (Cirsium arvense (L.) Scop.) is an aggressive, introduced creeping perennial weed that flourishes in a wide variety of environments. Its deep, creeping root system and colony forming tendencies make it one of the most difficult weeds to control. A strategy that incorporates a better understanding of the biology of Canada thistle into the development of an integrated management plan that includes herbicides and biological control could help reduce the dispersal and impact of this species. The objectives of this work were to: 1) determine how Canada thistle emergence and growth are affected by changes in root size, biomass, burial depth, and soil moisture and 2) compare single and joint impacts of herbicides and biological control agents on Canada thistle growth. Objective 1 was carried out in a greenhouse and in field conditions. To monitor Canada thistle emergence and growth responses, a completely randomized factorial design was used in the greenhouse, and a randomized complete block design was used in the field. Models were developed to predict emergence and growth patterns based on available water, burial depth, and various root metrics. For the exception of available water, the same predictors were used in field conditions to predict Canada thistle emergence and growth. The variables that were manipulated were able to significantly predict the responses measured, and we concluded that available water, root burial depth, and root weight, length, diameter, and volume are indicators of emergence likelihood, emergence time, shoot and root growth, and shoot number. Objective 2 was carried out in greenhouses and field settings. Three herbicides were evaluated with and without insects to determine reduction in Canada thistle root and shoot biomass in the greenhouse. One herbicide was also used at a low rate and evaluated singly and in combination with a stem-boring weevil (Hadroplontus litura (F.)) and a pathogen (Pseudomonas syringae pv. tagetis) to determine effect on Canada thistle response in the greenhouse and field. We failed to reject our null hypothesis of additivity between control agents, and concluded that integrating individual control methods yields greater Canada thistle control than any singular method.

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Goudy, Heather Jayne. "Evaluation of site-specific weed management and implications for spatial biology of weeds." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0022/MQ51068.pdf.

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Shirzadifar, Alimohammad. "Identification of Weed Species and Glyphosate-Resistant Weeds Using High Resolution UAS Images." Diss., North Dakota State University, 2018. https://hdl.handle.net/10365/29304.

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Adoption of a Site-Specific Weed Management System (SSWMS) can contribute to sustainable agriculture. Weed mapping is a crucial step in SSWMS, leads to saving herbicides and protecting environment by preventing repeated chemical applications. In this study, the feasibility of visible and near infrared spectroscopy to classify three problematic weed species and to identify glyphosate-resistant weeds was evaluated. The canopy temperature was also employed to identify the glyphosate-resistant weeds. Furthermore, the ability of UAS imagery to develop accurate weed map in early growing season was evaluated. A greenhouse experiment was conducted to classify waterhemp (Amaranthus rudis), kochia (Kochia scoparia), and lambsquartes (Chenopodium album) based on spectral signature. The Soft Independent Modeling of Class Analogy (SIMCA) method on NIR (920-2500 nm) and Vis/NIR (400-2500 nm) regions classified three different weed species with accuracy greater than 90 %. The discrimination power of different wavelengths indicated that 640, 676, and 730 nm from red and red-edge region, and 1078, 1435, 1490, and 1615 nm from the NIR region was the best wavelengths for weed species discrimination. While, wave 460, 490, 520 and 670 nm from Vis range, and 760, 790 nm from NIR region were the significant discriminative features for identifying glyphosate-resistant weeds. Random Forest was able to detect glyphosate-resistant weeds based on spectral weed indices with more than 95% accuracy. Analysis of thermal images indicated that the canopy temperature of glyphosate-resistant weeds was less than susceptible ones early after herbicide application. The test set validation results showed the support vector machine method could classify resistant weed species with accuracy greater than 95 %. Based on the stepwise method the best times for discrimination of kochia, and waterhemp resistant were 46 and 95 hours after glyphosate application, respectively. In addition, a field study was proposed on soybean field to identify weed species and glyphosate-resistant weeds using multispectral and thermal imagery. Results revealed that the object-based supervised classification method could classify weed species with greater than 90% accuracy in early growing season. Furthermore, the glyphosate-resistant kochia, waterhemp and ragweed were identified based on canopy temperature with 88%, 93% and 92% accuracy, respectively.

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Zwickle, Sarah Lynn. "Weeds and Organic Weed Management: Investigating Farmer Decisions with a Mental Models Approach." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1316453516.

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McCloskey, William B., Paul B. Baker, and Will Sherman. "Survey of Cotton Weeds and Weed Control Practice in Arizona Upland Cotton Fields." College of Agriculture, University of Arizona (Tucson, AZ), 1998. http://hdl.handle.net/10150/210369.

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The distribution of weed species and the herbicides and cultural practices used to control weeds in Arizona cotton fields were surveyed in 1995 and 1996. The most common weeds were purple nutsedge, bermudagrass, annual morningglory, Palmer amarnath, Wright groundcherry, common purselane, yellow nutsedge and Johnsongrass. The average statewide cost for hand weeding in 1995 was reported as $27.87 per acre in addition to other weed control costs. Statewide, most growers used preemergence herbicides before or at planting and used pre- and post-emergence herbicides later in the season. Most of these applications were broadcast applications suggesting that many of the postemergence herbicide applications were layby applications. Preemergence herbicides (usually applied preplant incorporated) such as Treflan, Prowl, and Prometryn were more commonly used than postemergence herbicides. Statewide, few growers banded preemergence herbicides or used electro- hydraulic quick-hitch guidance systems and in-row weeding tools with their cultivators.

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Books on the topic "Weeds"

1

Manuel, Juliana S. Weeds. Manila: Pundasyon sa Pagpapaunlad ng Kaalaman sa Pagtuturo ng Agham, Ink. by Island Pub. House, Inc., 1997.

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Roger, Phillips. Weeds. London: Elm Tree, 1986.

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Martin, Alexander C. Weeds. New York: St. Martin's Press, 1987.

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Jean, Zallinger, ed. Weeds. New York: Golden Press, 1987.

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Leopold, Muenscher Walter Conrad. Weeds. Ithaca, N.Y: Comstock Pub. Associates, 1987.

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Fletcher, James. Weeds. [Ottawa?]: Dept. of Agriculture, 1993.

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Roger, Phillips. Weeds. London: Elm Tree Books, 1986.

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Goetze, Norman R. Controlling weeds in home lawns. Corvallis, Or: Extension Service, Oregon State University, 1989.

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Controlling weeds. Emmaus, Pa: Rodale Press, 1995.

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Rogers, Garry. Desert Weeds. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45854-6.

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Book chapters on the topic "Weeds"

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Schweizer, E. E., and M. J. May. "Weeds and weed control." In The Sugar Beet Crop, 485–519. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-009-0373-9_12.

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Peters, Elroy J., and R. A. Peters. "Weeds and Weed Control." In Agronomy Monographs, 555–73. Madison, WI, USA: American Society of Agronomy, 2015. http://dx.doi.org/10.2134/agronmonogr15.c25.

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Peters, Elroy J., and Dean L. Linscott. "Weeds and Weed Control." In Agronomy Monographs, 705–35. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2015. http://dx.doi.org/10.2134/agronmonogr29.c23.

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Bakker, H. "Weeds." In Sugar Cane Cultivation and Management, 239–45. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4725-9_16.

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Nechet, Kátia de Lima, Marcelo Diniz Vitorino, Bruno Sérgio Vieira, and Bernardo de Almeida Halfeld-Vieira. "Weeds." In Natural Enemies of Insect Pests in Neotropical Agroecosystems, 437–49. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24733-1_35.

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Aly, Radi, and Neeraj Kumar Dubey. "Weed Management for Parasitic Weeds." In Recent Advances in Weed Management, 315–45. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1019-9_14.

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Gerhards, Roland. "Spatial and Temporal Dynamics of Weed Weeds Epidemiology Weeds Distribution Populations." In Precision Crop Protection - the Challenge and Use of Heterogeneity, 17–25. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9277-9_2.

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Rogers, Garry. "Controlling Weeds." In Desert Weeds, 11–18. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-45854-6_3.

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Sidorkewicj, S., M. R. Sabbatini, O. A. Fernández, and J. H. Irigoyen. "Aquatic Weeds." In Weed Biology and Management, 115–35. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-94-017-0552-3_5.

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Vurro, Maurizio, Alejandro Pérez-de-Luque, and Hanan Eizenberg. "Parasitic Weeds." In Weed Research, 313–53. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119380702.ch11.

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Conference papers on the topic "Weeds"

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Hudson, Kevin, and Bradford Simonsen. "Weeds." In SIGGRAPH '18: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209800.3232906.

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Darbyshire, Madeleine, Adrian Salazar-Gomez, Callum Lennox, Junfeng Gao, Elizabeth Sklar, and Simon Parsons. "Localising Weeds Using a Prototype Weed Sprayer." In UKRAS22 Conference "Robotics for Unconstrained Environments". EPSRC UK-RAS Network, 2022. http://dx.doi.org/10.31256/ua7pr2w.

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Mowla, Md Najmul, and Mustafa Gok. "Weeds Detection Networks." In 2021 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, 2021. http://dx.doi.org/10.1109/asyu52992.2021.9599046.

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Owen, Micheal D. K. "Update 2005 on Herbicide Resistant Weeds and Weed Population Shifts." In Proceedings of the 16th Annual Integrated Crop Management Conference. Iowa State University, Digital Press, 2005. http://dx.doi.org/10.31274/icm-180809-810.

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Owen, Micheal D. K. "Weeds 2011: What is new, herbicide-resistant weeds and management tactics." In Proceedings of the 21st Annual Integrated Crop Management Conference. Iowa State University, Digital Press, 2010. http://dx.doi.org/10.31274/icm-180809-43.

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Marković, Dušan, Uroš Pešović, Dalibor Tomić, and Vladeta Stevović. "CROP WEEDS DETECTION USING NEURAL NETWORK MODELS." In 1st International Symposium on Biotechnology. University of Kragujevac, Faculty of Agronomy, 2023. http://dx.doi.org/10.46793/sbt28.093m.

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Weeds are one of the most important factors affecting agricultural production. Environmental pollution caused by the application of herbicides over the entire agricultural land surface is becoming more and more obvious. Accurately distinguishing crops from weeds by machines and achieving precise treatment of only weed species is one possibility to reduce the use of herbicides. However, precise treatment depends on the precise identification and location of weeds and cultivated plants. The aim of the work was to describe and point out the importance of deep learning models for the detection and classification of weeds, in order to enhance their application in real conditions.

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Wilson, R. G. "Influence of preplant nitrogen fertilizer on sugarbeet, weeds and postemergence weed control." In 33rd Biennial Meeting of American Society of Sugarbeet Technologist. ASSBT, 2005. http://dx.doi.org/10.5274/assbt.2005.25.

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Hartzler, Bob, and Meaghan Anderson. "Cover crops, weeds and herbicides." In Proceedings of the 24th Annual Integrated Crop Management Conference. Iowa State University, Digital Press, 2014. http://dx.doi.org/10.31274/icm-180809-150.

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Hartyányi, Gábor, and Laszlo Czuni. "Recognition of Weeds in Cornfields." In 18th Conference on Computer Science and Intelligence Systems. IEEE, 2023. http://dx.doi.org/10.15439/2023f2610.

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Zhenchenko, K. G., E. N. Turin, A. A. Gongalo, V. Yu Ivanov, N. V. Karaeva, and V. V. Reent. "Weed infestation in the crop rotations depending on the cultivation technology in the Crimea." In CURRENT STATE, PROBLEMS AND PROSPECTS OF THE DEVELOPMENT OF AGRARIAN SCIENCE. Federal State Budget Scientific Institution “Research Institute of Agriculture of Crimea”, 2020. http://dx.doi.org/10.33952/2542-0720-2020-5-9-10-20.

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The stationary experiment on the comparative study of the direct sowing and traditional cultivation technology was laid in 2015–2016 at the trial field of the FSBSI “Research Institute of Agriculture of Crimea”. Two five-course crop rotations were taken as a base; all fields were included in the crop rotation. During the years of research, we observed mixed weed infestation. No matter what cultivation technology was applied, actual weed flora at the fields with winter crops was represented by overwintering and winter weeds; at the fields with spring crops – annual spring weeds. There were no rootstock grasses and rhizomatous perennial weeds or there were few of them at all fields in the experimental crop rotations both by traditional cultivation technology and direct sowing. Timely and high-quality weed control put the direct sowing on equal footing with the traditional one. It is advisable to change herbicides, their doses, as well as use tank mixes, after moving to a direct sowing system.

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Reports on the topic "Weeds"

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Hartzler, Robert G., Douglas D. Buhler, Lowell Sandell, Bernard J. Havlovic, and Carroll Olsen. Emergence Characteristics of Several Annual Weeds. Ames: Iowa State University, Digital Repository, 2001. http://dx.doi.org/10.31274/farmprogressreports-180814-1035.

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Hartzler, Robert G., Douglas D. Buhler, and Lowell Sandell. Emergence Characteristics of Several Annual Weeds. Ames: Iowa State University, Digital Repository, 2001. http://dx.doi.org/10.31274/farmprogressreports-180814-527.

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Hartzler, Robert G., Douglas D. Buhler, Lowell Sandell, and Kevin Van Dee. Emergence Characteristics of Several Annual Weeds. Ames: Iowa State University, Digital Repository, 2001. http://dx.doi.org/10.31274/farmprogressreports-180814-92.

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Hansen, Benjamin, Keaton Miller, and Caroline Weber. Getting into the Weeds of Tax Invariance. Cambridge, MA: National Bureau of Economic Research, July 2017. http://dx.doi.org/10.3386/w23632.

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Roos, R. C., and M. B. Malady. Guidelines for management of noxious weeds at Hanford. Office of Scientific and Technical Information (OSTI), October 1995. http://dx.doi.org/10.2172/410328.

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Kool, Janne, Eva de Jonge, Ard Nieuwenhuizen, and Hendrik Braam. Green on Green weed detection : Finding weeds in a soybean crop in Brazilian fields with the Rometron WEED-IT sensor : intermediary report. Wageningen: Wageningen Plant Research, 2023. http://dx.doi.org/10.18174/649472.

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Lenssen, Andrew W., Terry L. Basol, Joel L. DeJong, John D. Holmes, Mark A. Licht, Zachary A. Koopman, Micah B. Smidt, and Joshua L. Sievers. Influence of Land Rolling on Soybean Production and Associated Weeds. Ames: Iowa State University, Digital Repository, 2013. http://dx.doi.org/10.31274/farmprogressreports-180814-953.

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Miles, Gaines E., Yael Edan, F. Tom Turpin, Avshalom Grinstein, Thomas N. Jordan, Amots Hetzroni, Stephen C. Weller, Marvin M. Schreiber, and Okan K. Ersoy. Expert Sensor for Site Specification Application of Agricultural Chemicals. United States Department of Agriculture, August 1995. http://dx.doi.org/10.32747/1995.7570567.bard.

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In this work multispectral reflectance images are used in conjunction with a neural network classifier for the purpose of detecting and classifying weeds under real field conditions. Multispectral reflectance images which contained different combinations of weeds and crops were taken under actual field conditions. This multispectral reflectance information was used to develop algorithms that could segment the plants from the background as well as classify them into weeds or crops. In order to segment the plants from the background the multispectrial reflectance of plants and background were studied and a relationship was derived. It was found that using a ratio of two wavelenght reflectance images (750nm and 670nm) it was possible to segment the plants from the background. Once ths was accomplished it was then possible to classify the segmented images into weed or crop by use of the neural network. The neural network developed for this work is a modification of the standard learning vector quantization algorithm. This neural network was modified by replacing the time-varying adaptation gain with a constant adaptation gain and a binary reinforcement function. This improved accuracy and training time as well as introducing several new properties such as hill climbing and momentum addition. The network was trained and tested with different wavelength combinations in order to find the best results. Finally, the results of the classifier were evaluated using a pixel based method and a block based method. In the pixel based method every single pixel is evaluated to test whether it was classified correctly or not and the best weed classification results were 81% and its associated crop classification accuracy is 57%. In the block based classification method, the image was divided into blocks and each block was evaluated to determine whether they contained weeds or not. Different block sizes and thesholds were tested. The best results for this method were 97% for a block size of 8 inches and a pixel threshold of 60. A simulation model was developed to 1) quantify the effectiveness of a site-specific sprayer, 2) evaluate influence of diffeent design parameters on efficiency of the site-specific sprayer. In each iteration of this model, infected areas (weed patches) in the field were randomly generated and the amount of required herbicides for spraying these areas were calculated. The effectiveness of the sprayer was estimated for different stain sizes, nozzle types (conic and flat), nozzle sizes and stain detection levels of the identification system. Simulation results indicated that the flat nozzle is much more effective as compared to the conic nozzle and its relative efficiency is greater for small nozzle sizes. By using a site-specific sprayer, the average ratio between the spraying areas and the stain areas is about 1.1 to 1.8 which can save up to 92% of herbicides, especially when the proportion of the stain areas is small.

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Sutherland, Steve. Fuels planning: science synthesis and integration; environmental consequences fact sheet 07: fire and weeds. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2004. http://dx.doi.org/10.2737/rmrs-rn-23-v7.

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Aly, Radi, and John I. Yoder. Development of resistant crop plants to parasitic weeds based on trans-specific gene silencing. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598146.bard.

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Broomrapes (Orobanche/Phelipanchespp.) are holo parasitic plants that subsist on the roots of a variety of agricultural crops and cause severe losses to the yield quality and quantity. Effective methods for controlling parasitic weeds are scarce, with only a few known cases of genetic resistance. In the current study, we proposed an improved strategy for the control of parasitic weeds based on trans-specific gene-silencing of three parasite genes at once. We used two strategies to express dsRNA containing selected sequences of three Phelipancheaegyptiacagenes PaACS, PaM6PR and PaPrx1 (pma): transient expression using Tobacco rattle virus (TRV:pma) as a virus-induced gene-silencing (VIGS) vector and stable expression in transgenic tomato Solanumlycopersicum(Mill.) plants harboring a hairpin construct (pBINPLUS35:pma). siRNA-mediated transgene-silencing (20–24 nt) was detected in the host plants. Our results demonstrate that the quantities of PaACSand PaM6PR transcripts from P. aegyptiacatubercles grown on transgenic tomato or on Tobacco rattle virus-infected Nicotianabenthamianaplants were significantly reduced. However, only partial reductions in the quantity of PaPrx1 transcripts were observed in the parasite tubercles grown on tomato and on N. benthamianaplants. Concomitant with the suppression of the target genes, there were significant decreases in the number and weight of the parasite tubercles that grew on the host plants, in both the transient and the stable experimental systems. The results of the work carried out using both strategies point to the movement of mobile exogenous siRNA from the host to the parasite, leading to the impaired expression of essential parasite target genes. In light of the importance of parasitic weeds to world agriculture and the difficulty of obtaining resistance by conventional methods, we assume that genetic resistance based on the silencing of key metabolic genes in the parasite is now feasible. BARD Report - Project4622 Page 2 of 60

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