Prerpints.org logo
Preprint
Brief Report

Efficacy of S-Metolachlor + Glyphosate for Weed Control in Different Levels of Eucalyptus Straw

Altmetrics

Downloads

123

Views

79

Comments

0

A peer-reviewed article of this preprint also exists.

Submitted:

17 July 2023

Posted:

18 July 2023

You are already at the latest version

Alerts
Abstract
The Eucalyptus genus is the most planted forest crop in the world, with Brazil being one of the countries with the greatest productive potential. However, the occurrence of weeds can cause losses in productivity. Chemical control is widely used, but the efficiency of herbicides depends on factors such as the presence of straw in the soil and the occurrence of rainfall. Due to the scarcity of results regarding the interaction between herbicide, straw, and water depth in the forest sector, the objective of this study is to evaluate the efficiency of S-metolachlor + glyphosate in the control of grasses in different densities of eucalyptus straw and with simulated rain after the application of the product. The experiment was conducted in DBC, factorial 3×3×2, with four replications. The first factor represented 0, 50 and 100% of the commercial dose of S-metolachlor + glyphosate, the second 0, 5, and 10 ton ha-2 of straw, and the third 25 and 50mm of water depth applied in soil with a mix of grasses previously sowed. The rainfall simulation was performed 24 hours after herbicide application on each straw volume. The fresh mass of the aerial part of the grasses was collected 43 days after sowing and dried in an oven to determine the dry mass. Visual analyzes of the percentage of control were performed with scales ranging from 0 to 100, where 0 represents no control and 100 efficient control. The fresh and dry mass and the grasses' dry mass/water ratio decreased with increasing herbicide dosage and straw density. The dosage of 2.12 + 1.59 kg i.a. ha-1 of S-metolachlor + glyphosate resulted in greater control of grasses, and the treatments without straw and with the application of the herbicide had the highest percentages of control. Applying different water depths (25 mm or 50 mm) did not influence the control. Despite the control of grasses, the efficiency of the herbicide mixture was affected by the presence of vegetation cover.
Keywords: 
Subject: Environmental and Earth Sciences  -   Environmental Science

1. Introduction

The genus Eucalyptus, originating in Australia and belonging to the Myrtaceae family, stands out as the most planted forest crop in the world [1,2]. Brazil has the greatest eucalyptus production potential, with increasing productivity, reaching 38.9 m³/ha/year and 7.53 million hectares planted [3]. However, biotic disturbances threaten eucalyptus cultivation [4]. Physiological disturbances such as pests, diseases, and weeds can cause losses, negatively impacting productivity [5]
Grasses such as Digitaria insularis, Digitaria horizontalis, Panicum maximum, Brachiaria decumbens and Brachiaria brizantha were identified by the Ministry of Agriculture, Livestock, and Supply as priority pests in eucalyptus cultivation [6]. These species have a high ability to absorb and use nutrients [7], leading to nutritional imbalance, especially in the initial development of Eucalyptus [8]. Thus, weed control is essential for crop growth and yield [9].
Chemical control is widely used in eucalyptus cultivation [10], and about 207 products are registered in Brazil [11]. The glyphosate herbicide is used in agricultural and forestry crops, the increase in the use of this product was due to the adoption of the technology of genetically modified organisms tolerant to the herbicide [12]. The main glyphosate-tolerant crops are food crops or used in the production of biofuels, but transgenic eucalyptus has already been developed and released for planting in Brazil [13,14].
The constant use of glyphosate caused an increase in the number of resistant weed biotypes, requiring control alternatives [15]. Thus, the number of herbicides applied in pre-emergence and mixtures of products with different mechanisms of action increased [16]. In addition, the recent release of herbicide-tolerant eucalyptus may cause changes in chemical weed management in forest stands.
The most used herbicides include flumioxazin, glyphosate, indaziflam, isoxaflutole, oxyfluorfen, saflufenacil, and S-metolachlor [17,18,19,20]. S-metolachlor is a herbicide derived from chloroacetamide applied pre-emergence or incorporated pre-planting [21]. The product originated from a mixture of S-metolachlor and glyphosate. It has systemic action and, as it contains S-metolachlor in its formulation, has residual action on the germination and emergence of weeds [11].
Herbicides applied pre-emergence promote early weed control and help manage resistant biotypes [22,23,24]. However, the efficiency of these molecules depends on their bioavailability in the solution, the physicochemical characteristics of the soil, the method of preparing the area, and climatic factors during and after application [25,26,27,28,29].
Straw can be found in forested areas, where crop residues remain covering the soil, affecting the effectiveness of herbicides applied in subsequent cycles [17]. This is because herbicides, mainly pre-emergent, have to cross this barrier and reach the soil to control the seed bank [30,31]. However, straw also reduces exposure to light, photosynthesis, and, consequently, the emergence of weeds [32,33]; in addition to benefiting the soil with moisture, nutrients and an environment conducive to the microbiota [34].
The occurrence of rain is essential for the herbicide to pass through the straw and reach the soil solution [35], but in dry conditions, there is retention and adsorption of these products to the straw, which reduces weed control [36,37]. Thus, the efficiency of pre-emergent herbicides applied under straw depends on the product's characteristics, the nature and amount of straw in the soil, and rainfall [17]. Studying the interaction between these three factors is essential, especially in the forest sector, where these studies are little explored. This work aimed to evaluate the efficiency of the herbicide S-metolachlor + glyphosate (Sequence®) in the control of grasses in different densities of eucalyptus straw and with simulated rainfall after application of the product.

2. Material and Methods

2.1. Location and Soil

The experiment was carried out at the JK Campus of the Federal University of the Vales of Jequitinhonha and Mucuri, in Diamantina, Minas Gerais, Brazil, between November and December 2022, in a climate-controlled greenhouse with a minimum temperature of 15.3°C, a maximum of 43°C. 6ºC, and average 26.8ºC.
The soil was collected in Curvelo, Minas Gerais, Brazil (Table 1), sieved through a 4mm mesh, and fertilized as recommended for pastures in Minas Gerais, Brazil [38].

2.2. Experimental Design

The experiment was designed in randomized blocks, in a 3×3×2 factorial, with four replications. Where the first factor represented the doses of the herbicide S-metolachlor + glyphosate (Sequence ®), equivalent to 0, 50, and 100% of the recommended commercial dose for eucalyptus (0; 1.06 + 0.79 and 2.12 + 1 .59 kg ai ha-1); the second factor the straw density (0; 5 and 10 ton ha-2), and the third the applied water depth (25 and 50mm).

2.3. Conducting the Experiment

The grass mix is composed of Digitaria insularis, Urochloa brizantha cv. marandu, U. brizantha cv. piatã, and U. decumbens, in equal proportions, were sown in trays with an individual capacity of 10L and an area of 0.28 m2, containing sieved and fertilized soil. Grasses were chosen based on their occurrence in forest plantations and competition with eucalyptus plants. The eucalyptus straw was collected, weighed, and distributed in trays according to the pre-established treatments (0 and 10 ton ha-2).
About 24 hours after sowing the grasses and adding the straw, the herbicide S-metolachlor + glyphosate (Sequence ®) was applied to the experimental units, according to the defined doses and with the aid of the electric backpack sprayer Yamaho FT5®, the capacity of 5L.
The rainfall simulation was carried out 24 hours after herbicide application, using the sprinklers coupled in the greenhouse, with an intensity of 0.3mm min-1. The blades applied corresponded to 25 and 50mm, varying according to the treatments. Irrigation was performed daily, maintaining the humidity between 60 and 70% of field capacity.

2.4. Evaluated Parameters

The aerial part of the grasses was collected 43 days after the sowing of the grasses (DAS) and weighed on a precision scale to establish the fresh mass. Subsequently, they were packed in paper bags, taken to an oven with forced air circulation at 60ºC until constant mass, and weighed to determine the dry mass.
Visual assessments of the percentage of control were performed at 43 DAS, with scales ranging from 0 to 100, where 0 represents no control and 100 efficient control.

2.5. Statistical Analysis

Analysis of variance (ANOVA) was performed using the F test, and when significant, the means were compared using the Tukey test at 95% probability with the statistical program R® version 4.1.1. Response surface graphs were generated using SigmaPlot® software version 12.0.

3. Results and Discussions

The fresh and dry mass of the grasses, in the treatments without the application of S-metolachlor + glyphosate and under the effect of the dose of 1.06 + 0.79 kg i.a. ha-1, were lower in the density of 10 ton ha-2 of eucalyptus straw (Table 2). The lower dry and fresh mass of grasses under the effect of higher straw density, with none or 50% of the recommended herbicide dose, is due to the control performed by this soil cover [39]. Grasses need an optimal temperature for germination between 25-35ºC [40,41,42]; however, the presence of a greater volume of straw can reduce the average daily temperature of the soil [43], which, together with less exposure to light and restrictions on the emergence of the epicotyl, results in a decrease in germination and, consequently, in the fresh and dry mass [44].
In general, grasses' fresh and dry mass decreased with increasing herbicide dosage (Table 2). The lowest fresh and dry mass of grasses submitted to the herbicide S-metolachlor + glyphosate occurred because S-metolachlor targets the condensing enzyme 3-ketoacyl-CoA synthase, which stops cell multiplication and division, inhibiting growth and causing embryonic mortality [45,46]. In grasses, the product acts on the epicotyl, which generates reductions in the aerial part and biomass accumulation [34]. The grasses' dry mass/water ratio was also reduced with increasing doses of S-metolachlor + glyphosate (Table 2). Grasses subjected to a higher dose of S-metolachlor + glyphosate produced less biomass using the same amount of water, which suggests that water use efficiency decreased as a function of the amount of herbicide applied [47,48].
The greatest control occurred at the dosage of 2.12 + 1.59 kg, i.a. ha-1 of S-metolachlor + glyphosate. Treatments without straw and with herbicide application, regardless of the water level applied, obtained the highest control percentages (Figure 1). The highest percentage of control in the treatments without the presence of straw occurred because there was less herbicide adsorption. Even though it is partially adsorbed, commercial doses allow good availability of herbicides in the soil solution [49]. Herbicide adsorption is influenced by the product's and straw's physicochemical characteristics [50]. Soil cover from forest species generally has a higher presence of lignin and cellulose, which causes greater adsorption [49]. Despite glyphosate having low adsorption in straw [50,51], S-metolachlor has a solubility in water of 530 mg L-1 and a standardized sorption coefficient for organic carbon (Koc) of 200 L kg-1 [52,53], which results in high adsorption of this compound in organic materials [34,50]. In general, the herbicide straw interaction controlled the grasses. However, the greater efficiency in the isolated use of S-metolachlor + glyphosate suggests that the presence of vegetation cover may have an antagonistic effect on the product.
There was no significant difference in the percentage of grass control depending on the rainfall simulation (25 or 50 mm) (Figure 2). The water level applied after S-metolachlor + glyphosate did not influence the control of grasses because about 20 to 50mm of precipitation is needed for pre-emergent herbicides to cross the residues present in agricultural and forestry areas and reach the soil [17,54,55]. Harvest residues can retain, degrade and intercept herbicides [17]. Therefore, the occurrence and volume of rain after application can influence the efficiency of chemical control [56]; mainly causing the molecule to reach the soil and not remain in the straw, where microbial degradation may occur [57]. In this case, 25 and 50mm precipitations facilitated the herbicide molecule to cross the straw and reach the soil, controlling the grasses.

4. Conclusions

The eucalyptus straw at a density of 10 ton ha-2 exerted control of approximately 40% without applying the herbicide and reduced the fresh and dry mass of the grasses.
The greatest control was observed without straw and at a dose equivalent to 100% of the commercial dose of S-metolachlor + glyphosate. This suggests that, in treatments with straw, the herbicide was partially adsorbed by the vegetation cover.
Grass control was not influenced by the rainfall simulation (25 and 50mm) performed after herbicide application.

Author Contributions

Conceptualization, Tayna Sousa Duque. and Fernanda Santos Oliveira; Methodology, Tayna Sousa Duque and José Barbosa dos Santos; Software, Fernanda Santos Oliveira and Iasmim Marcella Souza; Validation, Bruno Caio Chaves Fernandes, Luma Loureiro da Silva Rodrigues and Daniel Valadão Silva; Formal Analysis, Tayna Sousa Duque and Fernanda Santos Oliveira; Investigation, X.X.; Resources, Iasim Marcella Souza and Bruno Caio Chaves Fernandes; Writing – Original Draft Preparation, Tayna Sousa Duque and Fernanda Santos Oliveira; Writing – Review & Editing, José Barbosa dos Santos and Daniel Valadão Silva; Supervision, José Barbosa dos Santos and Daniel Valadão Silva.

Acknowledgments

To the “Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)”, “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Código Financeiro 001”, “Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)” and to Programa MAI DAI CNPq Syngenta UFVJM.

References

  1. Flores, T. B.; Alvares, C. A.; Souza, V. C.; Stape, J. L. Eucalyptus no Brasil: zoneamento climático e guia para identificação, Piracicaba: IPEF, 2016; pp. 447.
  2. Teixeira, C. M. Redução do volume de irrigação de plantio de eucalipto para ganhos operacionais, sociais e ambientais, 2023.
  3. Indústria Brasileira De Árvores (IBÁ). Relatório Anual 2022. São Paulo: IBÁ, 2022. URL https://www.iba.org/datafiles/publsicacoes/relatorios/relatorio-anual iba2022compactado.pdf. (Accessed on May 24, 2023).
  4. Indústria Brasileira De Árvores (IBÁ). Relatório Anual 2017. São Paulo: IBÁ, 2017.
  5. Wilcken, C. F. As pragas exóticas que estão chegando. Revista Opiniões, 2017, 46(14), 2627. URL https://florestal.revistaopinioes.com.br/revista/detalhes/9-pragas-exoticas-que-estao-chegando/. (Accessed on May 24, 2023).
  6. Brasil. Instrução normativa Nº 112 de 15 de Outubro de 2018. Diário Oficial da União (1): 42018. 2018. URL https://www.jusbrasil.com.br/diarios/212979560/dou-secao-1-15-10-2018-pg-4 (Accessed on May 24, 2023).
  7. Adams, P. R.; Beadle, C. L.; Mendham, N. J.; Smethurst, P. J. The impact of time and duration of grass control on the growth of a young Eucalyptus globulus Labill. plantation. New Forests, 2003, 26, 147-165. [CrossRef]
  8. Maciel, J. C.; Duque, T. S.; Ferreira, E. A.; Zanuncio, J. C.; Plata-Rueda, A.; Silva, V. P.; Dos Santos, J. B. Growth, Nutrient Accumulation, and Nutritional Efficiency of a Clonal Eucalyptus Hybrid in Competition with Grasses. Forests, 2022, 13, 1157. [CrossRef]
  9. Junior, W. R. C.; da Costa, Y. K. S.; Carbonari, C. A.; Duke, S. O.; Alves, P. L. D. C. A.; De Carvalho, L. B. Growth, morphological, metabolic and photosynthetic responses of clones of eucalyptus to glyphosate. Forest ecology and management, 2020, 470, 118218. [CrossRef]
  10. De Carvalho, L. B.; Duke, S. O.; Alves, P. D. C. Physiological responses of Eucalyptus urograndis to glyphosate are dependent on the genotype. Scientia Forestalis, 2018, 118, 177-187. [CrossRef]
  11. Agrofit, Ministério da agricultura pecuária e desenvolvimento. URL. http://agrofit.agricultura.gov.br/agrofit_cons/principal_agrofit_cons. (Accessed on May 18, 2023).
  12. Milesi, M.M., Lorenz, V., Durando, M., Rossetti, M.F., Varayoud, J. Glyphosate herbicide: reproductive outcomes and multigenerational effects. Frontiers in Endocrinology, 12, 2021. [CrossRef]
  13. Gianessi, L.P. The increasing importance of herbicides in worldwide crop production. Pest management science 69(10): 1099–1105, 2013. [CrossRef]
  14. CTNBio, 2021. Comissão Técnica Nacional De Biossegurança: Parecer Técnico Nº 1638/2021/SEI-CTNBio. URL http://ctnbio.mctic.gov.br/documents/566529/2292301/Parecer+T%C3%A9cnico+7788-2021/eff8fe21-1a5d-49dd-9268-394d99f4f0df?version=1.0. (Accessed on July 13, 2023).
  15. Bain, C., Selfa, T., Dandachi, T., Velardi, S. ‘Superweeds’ or ‘survivors’? Framing the problem of glyphosate resistant weeds and genetically engineered crops. Journal of Rural Studies, 51(1), 211–221, 2017. [CrossRef]
  16. Ribeiro, V.H., Oliveira, M.C., Smith, D.H., Santos, J.B., Werle, R. Evaluating efficacy of preemergence soybean herbicides using field treated soil in greenhouse bioassays. Weed Technology, 35(5), 830–837, 2021. [CrossRef]
  17. Carbonari, C. A.; Gomes, G. L. G. C.; Krenchinski, F. H.; Simões, P. S.; Batista de Castro, E.; Velini, E. D. Dynamics and efficacy of sulfentrazone, flumioxazin, and isoxaflutole herbicides applied on eucalyptus harvest residues. New Forests, 2020, 51, 723-737. [CrossRef]
  18. Da Costa, A. C. P. R.; da Costa, N. V.; Pereira, M. R. R.; Martins, D. Simulated drift effect of glyphosate in different parts of Eucalyptus grandis plants. Semina: Ciências Agrárias (Londrina), 2012, 33, 1663-1672. [CrossRef]
  19. Sebastian, D. J.; Fleming, M. B.; Patterson, E. L.; Sebastian, J. R.; Nissen, S. J. Indaziflam: a new cellulose-biosynthesis-inhibiting herbicide provides long-term control of invasive winter annual grasses. Pest management science, 2017, 73, 2149-2162. [CrossRef]
  20. Minogue, P. J.; Osiecka, A. Selective herbicides for cultivation of Eucalyptus urograndis clones. International Journal of Forestry Research, 2015, 1-12. [CrossRef]
  21. Yang, L.; Ivantsova, E.; Souders II, C. L.; Martyniuk, C. J. The agrochemical S-metolachlor disrupts molecular mediators and morphology of the swim bladder: Implications for locomotor activity in zebrafish (Danio rerio). Ecotoxicology and Environmental Safety, 2021, 208, 111641. [CrossRef]
  22. Zhao, N.; Zuo, L.; Li, W.; Guo, W.; Liu, W.; Wang, J. Greenhouse and field evaluation of isoxaflutole for weed control in maize in China. Scientific Reports, 2017, 7, 1-9. https://www.nature.com/articles/s41598-017-12696-7.
  23. Susha, V. S.; Das, T. K.; Nath, C. P.; Pandey, R.; Paul, S.; Ghosh, S. Impacts of tillage and herbicide mixture on weed interference, agronomic productivity and profitability of a maize–Wheat system in the North-western Indo-Gangetic Plains. Field Crops Research, 2018, 219, 180-191. [CrossRef]
  24. Knezevic, S. Z.; Pavlovic, P.; Osipitan, O. A.; Barnes, E. R.; Beiermann, C.; Oliveira, M. C.; Jhala, A. Critical time for weed removal in glyphosate-resistant soybean as influenced by preemergence herbicides. Weed Technology, 2019, 33, 393-399. [CrossRef]
  25. Vinther, F. P.; Brinch, U. C.; Elsgaard, L.; Fredslund, L.; Iversen, B. V.; Torp, S.; Jacobsen, C. S. Field-scale variation in microbial activity and soil properties in relation to mineralization and sorption of pesticides in a sandy soil. Journal of environmental quality, 2008, 37, 1710-1718. [CrossRef]
  26. Fast, B. J.; Ferrell, J. A.; MacDonald, G. E.; Krutz, L. J.; Kline, W. N. Picloram and aminopyralid sorption to soil and clay minerals. Weed science, 2010, 58, 484-489. [CrossRef]
  27. Rigi, M. R.; Farahbakhsh, M.; Rezaei, K. Adsorption and desorption behavior of herbicide metribuzin in different soils of Iran. Journal of Agricultural Science and Technology, 2015, 17, 777-787. http://dorl.net/dor/20.1001.1.16807073.2015.17.3.16.1.
  28. Schneider, J. G.; Haguewood, J. B.; Song, E.; Pan, X.; Rutledge, J. M.; Monke, B. J.; Xiong, X. Indaziflam effect on bermudagrass (Cynodon dactylon L. Pers.) shoot growth and root initiation as influenced by soil texture and organic matter. Crop Science, 2015, 55, 429-436. [CrossRef]
  29. Mendes, K. F.; Ionoue, M. H.; Tornisielo, V. L. Herbicidas no ambiente: Comportamento e destino. Editora UFV, 2022.
  30. Monquero, P. A.; Amaral, L. R.; Binha, D. P.; Silva, P. V.; Silva, A. C.; Martins, F. R. A. Mapas de infestação de plantas daninhas em diferentes sistemas de colheita da cana-de-açúcar. Planta Daninha, 2005, 26, 47-55. [CrossRef]
  31. Osipitan, O. A.; Dille, J. A.; Assefa, Y.; Radicetti, E.; Ayeni, A.; Knezevic, S. Z. Impact of cover crop management on level of weed suppression: a meta-analysis. Crop Science, 2019, 59, 833-842. [CrossRef]
  32. Da Silva Neto, H. F.; de Pauli, F. A.; Júnior, L. C. T.; Marques, M. O. Quantificação da palhada de cana-de-açúcar e potencial controle de plantas daninhas, 2019. [CrossRef]
  33. Pitelli, R. A.; Durigan, J. C.; Rossello, R. D. Ecologia das plantas daninhas no sistema de plantio direto. In: Siembra directa en el cono sur. Montevideo: PROCISUR, 2001, 203-210.
  34. Correia, N. M.; Gomes, L. P.; Perussi, F. J. Control of Brachiaria decumbens and Panicum maximum by S-metolachlor as influenced by the occurrence of rain and amount of sugarcane straw on the soil. Acta Scientiarum. Agronomy, 2012, 34, 379-387. [CrossRef]
  35. Maciel, C. D. G.; Velini, E. D. Simulação do caminhamento da água da chuva e herbicidas em palhadas utilizadas em sistemas de plantio direto. Planta daninha, 2005, 23, 471-481. [CrossRef]
  36. Da Silva, P. V.; Tronquini, S. M.; Barbosa, G. C.; de Carvalho Dias, R.; Veiga, J. P. S.; Inácio, E. M. Eficácia do herbicida flumioxazin no controle de Euphorbia heterophylla, na aplicação sobre diferentes tipos de palha e simulações de chuva: Controle de Euphorbia heterophylla com flumioxazin. Revista de Ciências Agrárias, 2020, 43, 324-332. [CrossRef]
  37. Clark, S. L.; da Silva, P. V.; Dayan, F. E.; Nissen, S. J.; Sebastian, D. J. The influence of winter annual grass litter on herbicide availability. Weed Science, 2019, 67, 702-709. [CrossRef]
  38. Barros, N. F.; Novais, R. F. Eucalipto. In: Recomendação para o uso de corretivos e fertilizantes em Minas Gerais: 5º Aproximação. Ribeiro, A.C.; Guimaraes, P.T.G.; Alvarez, V.H. Minas Gerais, Viçosa, MG, 1999, pp. 303–305.
  39. Bhullar, M. S.; Kaur, S.; Kaur, T.; Jhala, A. J. Integrated weed management in potato using straw mulch and atrazine. HortTechnology, 2015, 25, 335-339. [CrossRef]
  40. Cabrera, D.; Sobrero, M. T.; Pece, M.; Chaila, S. Effect of environmental factors on the germination of Megathyrsus maximus: an invasive weed in sugarcane in Argentina. Planta Daninha, 2020, 38. [CrossRef]
  41. Ustarroz, D.; Kruk, B. C.; Satorre, E. H.; Ghersa, C. M. Dormancy, germination and emergence of Urochloa panicoides regulated by temperature. Weed Research, 2016, 56, 59-68. [CrossRef]
  42. Nakao, E. A.; Cardoso, V. J. M. Priming and temperature limits for germination of dispersal units of Urochloa brizantha (Stapf) Webster cv. basilisk. Brazilian Journal of Biology, 2015, 75, 234-241. [CrossRef]
  43. Teasdale, J. R.; Mohler, C. L. Light transmittance, soil temperature, and soil moisture under residue of hairy vetch and rye. Agronomy Journal, 1993, 85, 673-680. [CrossRef]
  44. Nichols, V.; Verhulst, N.; Cox, R.; Govaerts, B. Weed dynamics and conservation agriculture principles: A review. Field Crops Research, 2015, 183, 56-68. O'Connell, P. J.; Harms, C. T.; Allen, J. R. Metolachlor, S-metolachlor and their role within sustainable weed-management. Crop protection, 1998, 17, 207-212.
  45. Kouame, K. B. J.; Bertucci, M. B.; Savin, M. C.; Bararpour, T.; Steckel, L. E.; Butts, T. R.; Roma-Burgos, N. Resistance of Palmer amaranth (Amaranthus palmeri) to S-metolachlor in the midsouthern United States. Weed Science, 2022, 70, 380-389. [CrossRef]
  46. Marchi, G.; Marchi, E. C. S.; Guimarães, T. G. Herbicidas: mecanismos de ação e uso. 2008.
  47. Negrisoli, R. M.; Negrisoli, M. M.; Cesco, V. J.; Bianchi, L.; Gomes, D. M.; Carbonari, C. A.; Velini, E. D. Glyphosate effect on Merremia aegyptia water transpiration and water use efficiency. Crop Protection, 2023, 169, 106237. [CrossRef]
  48. Singh, M.; Kukal, M. S.; Irmak, S.; Jhala, A. J. Water use characteristics of weeds: a global review, best practices, and future directions. Frontiers in Plant Science, 2022, 12, 794090. [CrossRef]
  49. Saha, D.; Marble, S. C.; Pearson, B.; Pérez, H.; MacDonald, G.; Odero, D. C. Short-term preemergence herbicide adsorption by mulch materials and impacts on weed control. HortTechnology, 2019, 29, 889-897. [CrossRef]
  50. Aslam, S.; Garnier, P.; Rumpel, C.; Parent, S. E.; Benoit, P. Adsorption and desorption behavior of selected pesticides as influenced by decomposition of maize mulch. Chemosphere, 2013, 91, 1447-1455. [CrossRef]
  51. Nunes, A. L.; Vidal, R. A. Persistência do herbicida S-metolachlor associado ao glyphosate ou paraquat em plantio direto. Planta Daninha, 2008, 26, 385-393. [CrossRef]
  52. Westra, E. P. Adsorption, leaching, and dissipation of pyroxasulfone and two chloroacetamide herbicides. Doctoral dissertation, Colorado State University, 2012.
  53. Westra, E. P.; Shaner, D. L.; Barbarick, K. A.; Khosla, R. Evaluation of sorption coefficients for pyroxasulfone, S-metolachlor, and dimethenamid-p. Air, Soil and Water Research, 2015, 8, ASWR-S19682. [CrossRef]
  54. Rossi, C. V. S.; Velini, E. D.; Luchini, L. C.; Negrisoli, E.; Correa, M. R.; Pivetta, J. P.; Silva, F. M. L. Dinâmica do herbicida metribuzin aplicado sobre palha de cana-de-açúcar (Saccarum officinarum). Planta daninha, 2013, 31, 223-230. [CrossRef]
  55. Carbonari, C. A.; Gomes, G. L.; Trindade, M. L.; Silva, J. R.; Velini, E. D. Dynamics of sulfentrazone applied to sugarcane crop residues. Weed Science, 2016, 64, 201-206. [CrossRef]
  56. Watts, D. W.; Hall, J. K. Tillage and application effects on herbicide leaching and runoff. Soil and Tillage Research, 1996, 39, 241-257. [CrossRef]
  57. Martinez, C. O.; Silva, C. M.; Fay, E. F.; Abakerli, R. B.; Maia, A. H.; Durrant, L. R. Microbial degradation of sulfentrazone in a Brazilian rhodic hapludox soil. Brazilian Journal of Microbiology, 2010, 41, 209-217. [CrossRef]
Preprints 79709 g001
Figure 1. Grasses at 43 days after sowing under 0, 5, and 10 ton ha-2 of eucalyptus straw, application of 0, 50, and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®) and water depth of 25 and 50 mm.
Figure 1. Grasses at 43 days after sowing under 0, 5, and 10 ton ha-2 of eucalyptus straw, application of 0, 50, and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®) and water depth of 25 and 50 mm.
Preprints 79709 g001
Preprints 79709 g002
Figure 2. Surface response of the percentage of grass control at 43 days after sowing, under 0, 5, and 10 ton ha-2 of eucalyptus straw, application of 0, 50, and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®) and water depth of 25 (A) and 50 mm (B).
Figure 2. Surface response of the percentage of grass control at 43 days after sowing, under 0, 5, and 10 ton ha-2 of eucalyptus straw, application of 0, 50, and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®) and water depth of 25 (A) and 50 mm (B).
Preprints 79709 g002
Table 1. Physical-chemical characteristics of the soil samples used in the experiment.
Table 1. Physical-chemical characteristics of the soil samples used in the experiment.
pH
(H20) 		P K Ca Mg Al H+Al SB (t) T V m MO
dag kg-1
mg dm-3 ----------------cmolc dm-3------------------ ---%---
5,5 2,3 88 1,24 0,44 0,1 2,97 1,91 2,01 4,88 39,1 5,0 1,9
P-rem Zn Fe Mn Cu B Sand % 6
mg L-1 -----------mg dm-3----------- Clay 69
20,1 2,0 37,8 148, 0,8 0,1 Silt 25
Source: Viçosa Soil Analysis Laboratory, LTDA. pH in water, KCl and CaCl Ratio 1:2.5; P - K - Fe – Zn - Mn – Cu - Mehlich extractor 1; Ca - Mg - Al - Extractor: KCl - 1 mol/L; H + Al - Calcium Acetate Extractor 0.5 mol/L - pH 7.0; S - Extractor - Monocalcium phosphate in acetic acid; SB = Sum of Exchangeable Bases; CEC (t) - Effective Cation Exchange Capacity; CEC (T) - Cation Exchange Capacity at pH 7.0; V = Base Saturation Index; m = Aluminum Saturation Index; Mat. Org. (MO) = C.Org x 1.724 - Walkley-Black; P-rem = Remaining Phosphorus.
Table 2. Fresh mass (g), dry mass (g), and fresh mass/dry mass ratio (g) of grasses at 43 days after sowing under 0, 5, and 10ton ha-2 of eucalyptus straw and application of 0.50 and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®).
Table 2. Fresh mass (g), dry mass (g), and fresh mass/dry mass ratio (g) of grasses at 43 days after sowing under 0, 5, and 10ton ha-2 of eucalyptus straw and application of 0.50 and 100% (0; 1.06 + 0.79 and 2.12 + 1.59 kg i.a. ha-1) of the commercial dose of S-metolachlor + glyphosate (Sequence®).
Variable Straw (ton ha-2) S-metolachlor + glyphosate (kg i.a. ha-¹) CV%
0 1,06 + 0,79 2,12 + 1,59
Fresh mass (g) 0 155,31 Aa 54,79 Ab 12,34 NSc 21,1
5 127,33 Aa 44,08 Ab 12,92 NSc
10 82,71 Ba 27,13 Bb 21,63 NSc
Dry mass
(g) 		0 43,10 Aa 8,92 Ab 1,32 Cc 26,1
5 32,86 Ba 7,82 Ab 1,73 ABc
10 19,15 Ca 3,90 Bb 2,92 Ab
Dry mass/water ratio 0 0,397 Aa 0,216 NSb 0,105 NSc 20,3
5 0,348 ABa 0,217 NSb 0,156 NSc
10 0,299 Ba 0,175 NSb 0,150 NSb
NS: not significant by F-test at 95% probability. Means followed by the same letter, case in the column and lowercase in the row, do not differ by the Tukey test at 95% probability. CV: Coefficient of variation (%).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

facebook logotwitter logolinkedin logo
MDPI Initiatives
Important Links
Subscribe

Disclaimer

Terms of Use

Privacy Policy

© 2024 MDPI (Basel, Switzerland) unless otherwise stated