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Article

Critical Levels of Copper, Zinc, and Manganese Toxicity in Soil and Tissues of Plants That Cohabit Vineyards in the Pampa Biome

by
Filipe Nunes de Oliveira
1,
Letícia Morsch
2,
Jean Michel Moura-Bueno
1,*,
Adriele Tassinari
1,
Edicarla Trentin
1,
Anderson César Ramos Marques
3,
Talita Andreolli
1,
Bianca Goularte Dias
1,
Luciane Almeri Tabaldi
3 and
Gustavo Brunetto
1
1
Soil Science Department, Federal University of Santa Maria (UFSM), Santa Maria 97105-900, RS, Brazil
2
Postgraduate Program in Agroecosystems, Center of Agricultural Science, Federal University of Santa Catarina UFSC, Florianópolis 88034-001, SC, Brazil
3
Biology Department, Federal University of Santa Maria (UFSM), Santa Maria 97105-900, RS, Brazil
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(7), 831; https://doi.org/10.3390/horticulturae11070831
Submission received: 22 May 2025 / Revised: 9 July 2025 / Accepted: 11 July 2025 / Published: 14 July 2025
(This article belongs to the Section Plant Nutrition)

Abstract

Old vineyards in production in the Pampa biome have high levels of metals, such as copper (Cu), zinc (Zn), and manganese (Mn). The high metal contents in the soil can damage the growth and development of the cover plant species that cohabit the vineyards. However, it is possible to define the critical toxicity level (CTL) of metals in soil and tissue in order to monitor and define possible strategies for reducing metal inputs and selecting more tolerant species. This study aimed to define the CTL of Cu, Zn, and Mn in the soil and plant tissue of plants present between the rows of vineyards with different cultivation histories in the Pampa biome in South America. For this purpose, soil and plant tissue samples were collected in a native field area (NF), without agricultural cultivation and in two vineyards, vineyard 1 (V1) and vineyard 2 (V2), both with a history of fungicide application. To define the CTL, the foliar concentrations and soil contents of Cu, Zn, and Mn were correlated with the dry mass production of the shoot. The CTLs for Cu, Zn, and Mn in the soil were set at 15, 3.0, and 35 mg kg−1, respectively. In the tissue, CTLs for Cu, Zn, and Mn were estimated at 75, 77, and 380 mg kg−1, respectively. The contents of Cu, Mn, and Zn in the soil of the vineyards are above the CTL. The concentrations of the metals in the tissue varied, with samples above the CTL for Cu and Zn in the vineyards. The values of Cu, Zn, and Mn in NF are below the CTL in soil and tissue. The high contents of Cu, Zn, and Mn in the soil and tissue limited the dry mass production of the plants between the rows of vineyards.

1. Introduction

The Pampa biome covers an area of more than 750,000 km2 in South America, extending across Brazil, Argentina, and Uruguay [1]. In Brazil, the Pampa makes up the so-called Campos Sulinos ecosystem, recognized as a biome in 2004, when the territory was no longer considered part of the Atlantic Forest biome [1]. Over the last few years, the native grassland areas of the Pampa biome historically used for raising beef cattle have been incorporated into a fruit-growing system, especially wine grapes [2], becoming one of the largest wine-growing regions in Brazil and South America [3]. Thus, several species originating from these native fields are kept between the rows of vineyards, helping to conserve the biome’s biodiversity. In addition, maintaining these species within vineyards performs important functions such as water and soil conservation, carbon (C) sequestration, and nutrient cycling [4,5]. Native species can also be used for the phytoremediation of elements, when in quantities considered toxic [6]. This favors the cultivation of vines and benefits the soil and the environment.
Excess elements in the soil can result from weathering, a process in which metals naturally present in the source material become available in the soil [7]. However, anthropogenic activities such as mining, industrial processes, the application of animal manure, mineral fertilizers, and especially fungicides can increase the levels of metals in soils [8]. Studies worldwide report that vineyard soils have high metal levels especially due to applications of fungicides containing copper (Cu), zinc (Zn), and manganese (Mn) in the formulation [2]. To date, no detailed survey of the history of contamination by metal has been carried out in the Pampa biome, or even in the study area. This may be because the Pampa biome region is a “new” region when compared to the main wine-growing regions of Brazil, or even due to the difficulty in standardizing applications, since the intensity of applications depends on climatic conditions, for example. However, in a study carried out by Poggere et al. [9] with a systematic search for data using previously published material, the authors presented Cu concentrations in vineyards via fungicides with values ranging from 0.5 kg ha−1 year−1 to 16 kg ha−1 year−1 (median of 2 kg ha−1 year−1).
Copper, Zn, and Mn are micronutrients and act in various roles in plants. Copper acts as a structural element in the regulation of proteins and participates in photosynthetic electron transport, mitochondrial respiration, responses to oxidative stress, cell wall metabolism, hormone signaling [10,11], and in the context of mineral metabolism, with impacts on the reduction in nutrients concentrations [12]. Zinc is required catalytically and structurally by many enzymes, as it acts in protein synthesis, carbohydrate metabolism and may also be required for chlorophyll biosynthesis [13,14]. Manganese is linked to functions in N metabolism and protein synthesis [15]; it helps against pathogens and hormonal signaling [16], as well as being included in various metabolic processes, as a cofactor for various enzymes that act in photosynthesis, respiration, and others [16,17,18]. Copper, Zn, and Mn can be absorbed and accumulated in the tissues when in high levels in the soil, causing negative morphological, anatomical, physiological, and biochemical responses which can impair plant development [16,19,20]. Excesses of Cu and Zn can impair the growth and development of the root system with consequent damage to the absorption of water and nutrients by plants [21,22]. In addition, excess Cu and Zn in the tissue causes oxidative stress due to the imbalance of antioxidant responses and increased production of reactive oxygen species (ROS) [23]. Excess Mn in the tissue can limit plant growth since the stress caused promotes the accumulation of ROS in plants, resulting in oxidative damage, chlorosis, and necrosis in leaves [24,25].
Given the phytotoxic effects that can be caused by the accumulation of Cu, Zn, and Mn in the soil and plant tissue, there is a tendency for the native plant community to degrade in vineyards in the Pampa biome [26,27]. Among the possible impacts is a decrease in vegetation cover and native species richness [28,29], as well as the favoring of some plant species that are better adapted to the high concentrations of these metals in the soil [30]. In addition, there is a tendency for exotic species, which may be more tolerant of excess metals, to become more invasive [31]. Thus, it is important to know the adaptability of the native flora of the Pampa biome in relation to the higher concentrations of Cu, Zn, and Mn in vineyards, in order to carry out appropriate management or interventions in these areas for the conservation of the biodiversity of these ecosystems, combined with the production of fruit trees.
For this to be possible, it is necessary to know reference values in soils and tissue that limit the development of these native plants. However, these values are not known for species in the Pampa biome. These values can be defined by determining the critical toxicity level (CTL) of these metals in soil and tissue in relation to dry matter production. The CTL of nutrients is fundamental information for the nutritional diagnosis of a crop [32]. The CTL values use univariate relation and relate nutrient levels (soil) and foliar concentrations (plant) to productivity, such as dry mass production. The CTL values can be obtained using regressions that describe the relation between the nutrient contents determined in soil and tissue samples and the yields recorded [33,34]. In view of the above, our hypothesis is that plants present between the rows of vineyards with more than 40 years of cultivation in the Pampa biome are above the estimated CTL for Cu, Zn, and Mn. This study aimed to define the CTL of Cu, Zn, and Mn in the soil and plant tissue of plants present between the rows of vineyards with different cultivation histories in the Pampa biome in South America.

2. Materials and Methods

2.1. Characterization of the Areas and Sampling of Soil and Tissue

This study was carried out in commercial vineyards (30°48′04.79″ S and 55°22′30.31″ W) located in the municipality of Santana do Livramento, state of Rio Grande do Sul (RS), Brazil, in the southern region of South America. The region’s climate is classified as subtropical, type Cfa [35], with no dry season and a hot summer. The average annual temperature is 17.8 °C, with January being the hottest month and June the coldest, with averages of 23.8 °C and 12.4 °C, respectively. The average annual rainfall is 1518.3 mm [36]. The relief is gentle to undulating [37] and the predominant soil in the region is classified as Typic Hapludalf [38].
Collections were carried out in three areas (Supplementary Table S1), one native field (NF) area without agricultural cultivation (used as a control) and two vineyards, vineyard 1 (V1) and vineyard 2 (V2), both with a history of fungicide application and high levels of metals such as Cu, Zn, and Mn in soil (Table S1). The quantities (grams per hectare) of the active ingredient (a.i.) of fungicides containing Cu, Zn, and Mn applied to vineyards per crop season are as follows: copper hydroxide [Cu(OH)2]—1725 g of a.i. per hectare, divided into 2 applications; Mancozeb [C4H6N2S4Mn and C4H6N2S4Zn]—7680 g of a.i. per hectare, divided into four applications. Vineyards V1 and V2 are equidistant, about 200 m from each other. Both vineyards are located at a distance of 500 m from the NF.
The V1 has had the same vines in production for 44 years and the soil has not been turned over since it was first planted. The V2 has been cultivated for 46 years, but after 29 years, the old vines were eradicated, the soil was turned over, and a new vineyard was planted in 2006. The cultivar used in V1 is ‘Sauvignon Blanc’, grafted onto the SO4 rootstock. In V2 is ‘Gewurztraminer’, grafted onto the SO4 rootstock. The grapevines are managed using an espalier system and the plants in vineyard rows are mowed at a height of 10 cm around five times a year.
Plant tissue from the plants (Axonopus compressus, Axonopus argentinos, Paspalum notatum, Paspalum plicatulum, and Vernonia nudiflora) present between the rows of the vineyards (V1 and V2) and in the NF was collected in the three areas, along with the soil, at two moments in 2022. The first was in summer and the second in winter, in January and July, respectively. In each area, NF, V1, and V2, four plots (repetitions) were delimited and randomly distributed in each area, with each plot in the vineyards consisting of five rows of crops. Three 60 by 60 cm frames (0.36 m2) were randomly placed in each plot to collect the shoot of the plants present.

2.2. Dry Mass and Tissue Concentrations of Cu, Zn, and Mn

The shoot biomass of the plants in each frame was collected to determine the dry mass and the concentrations of Cu, Zn, and Mn in the tissue. The samples were dried in a forced ventilation oven at 65 °C until they reached a constant weight. The dry mass was obtained using a precision scale. After drying, the tissue samples were ground in a Wiley mill, prepared, and subjected to the nitroperchloric acid digestion method [39]. The concentrations of Cu, Zn, and Mn in the extract were determined using an atomic absorption spectrophotometer (AAnalyst 200, Perkin-Elmer, Waltham, MA, USA).

2.3. Available Cu, Zn, and Mn in the Soil

Soil samples at NF, V1, and V2 areas were collected in a zigzag pattern with a cutting shovel. The soil samples were collected from the 0–20 cm layer, homogenized, and reserved (approximately 500 g). The collected soil was air-dried, homogenized, and passed through a sieve with a 2 mm mesh. The levels of available Cu, Zn, and Mn were extracted using Mehlich-1 [40]. The contents of Cu, Zn, and Mn in the extracts were determined using an atomic absorption spectrometer (AAnalyst 200, Perkin-Elmer, Waltham, MA, USA).

2.4. Statistical Analysis

To develop the models for estimating the CTL of Cu, Zn, and Mn in soil and plant tissue, dry mass production was converted into relative yield (%) for each area (NF, V1, and V2). The models were developed by means of a regression with a plateau (border line) [33,34] using Bayesian segmented quantile regression (BSQR) [41], to quantify the relation between the dependent variables (dry mass production), with the levels of Cu, Zn, and Mn in the soil and plant tissue. Bayesian analysis was used to adjust the parameters of the regression models [42] using Monte Carlo simulation with Markov chains (MCMCs) [43]. The simulation used the Gibbs sampling algorithm, with 20,000 random draws after a warm-up period of 10,000 interactions. The sampling stage was carried out according to the normal distribution, based on the a posteriori distribution of nutrient levels (concentrations and contents). The modeling was implemented using the ‘rjags’ package [44] in the R environment [45]. The critical levels were assumed to be the point at which the fitted line reaches the plateau, showing a reduction in yield as the levels of Cu, Zn, and Mn increases. Finally, a frequency density analysis was carried out, assuming a 90% confidence interval, to determine the highest nutrient occurrence density (CTL).

3. Results

The highest dry mass production of the shoot of the species was observed in the NF, followed by V2 (Table 1). The V1 showed the lowest shoot dry mass production of the species. The highest concentrations of Cu and Mn in the tissue were found in the plants in the V2 vineyard. The highest concentrations of Zn were found in the plants in the V1 vineyard. With regard to the levels of metals in the soil, the highest contents of Cu, Zn, and Mn were found in the V1 vineyard and the lowest in the NF (Table 1).
The proposed CTL of Cu in the soil was 15 mg kg−1 (Figure 1a). In the vineyards, V1 and V2, the Cu contents in the soil are mostly above the CTL. On the other hand, the Cu contents in the NF soil are below the CTL. The proposed CTL for Zn was 3 mg kg−1 (Figure 1b). The soil in V1 had the highest Zn values, followed by V2. Both values were higher than the CTL. The Zn content in the NF soil was lower than the CTL. The proposed CTL for Mn in the soil was 35 mg kg−1 (Figure 1c). The Mn content in the V1 soil and in parts of the V2 samples was higher than the Mn CTL. The Mn content in the NF soil was lower than the Mn CTL, which was also observed in part of the V2 soil samples (Figure 1c).
In relation to the CTL values in the tissue, the proposed CTL value for Cu in the tissue was 75 mg kg−1 (Figure 2a). The plants between the rows of the V1 and V2 vineyards predominantly had Cu concentrations lower than the CTL. However, both vineyards have plants with concentrations above the CTL for Cu. The NF plants showed lower concentrations than the estimated CTL for Cu. The proposed CTL for Zn in the tissue was set at 77 mg kg−1 (Figure 2b). The plants in V1 had the highest concentrations, with a predominance of plants with Zn values higher than the CTL. Plants in V2 had Zn concentrations higher than the CTL in the minority of sampling points. In the NF, the plants had lower Zn concentrations than the CTL, along with some plants between the rows in V2 (Figure 2b).
The proposed CTL of Mn in the tissue was 380 mg kg−1 (Figure 2c). In V1, the plants between the rows had lower Mn concentrations than the CTL, and in general had the lowest concentrations. In V2, plants at some sampling points had higher Mn concentrations than the CTL. The Mn concentrations in plants in the NF were lower than the CTL (Figure 2c).

4. Discussion

The lowest dry mass production was observed in soils with the highest contents of Cu, Zn, and Mn in the soil (V1), but not necessarily in the tissue (Table 1, Figure 1). This may be related to the different species that cohabit the evaluated areas. The soil Zn and Mn contents were higher than the proposed CTL value in vineyard V1 (Figure 1) and the concentrations of Cu and Mn in the shoot were higher than the proposed CTL value in V2 (Figure 2). This can possibly be attributed to the application of foliar fungicides in the vineyards over the years, which may be causing an increase in the levels of these metals in the soil of the Pampa biome and spatial variation of species that cohabit the vineyards [26]. Furthermore, fertilizer applications carried out can also increase metal levels in vineyard soils, especially the organic ones [8,46]. This can increase the availability and, consequently, the likelihood of absorption of Cu, Zn, and Mn by plants [47,48]. Another factor that may have contributed to the increase in soil metal content over the years is soil pH. There is a negative correlation between soil pH and metal bioavailability; as the pH of the soil solution decreases, metal bioavailability increases [49,50]. The study areas have an acidic pH (Table S1). This may have contributed to the increase in metal availability in the areas and, consequently, to an increase in their levels in the soil. Even the P presence in the soil (Table S1) may have reduced Cu bioaccumulation in the aboveground part of the biomass. This may have occurred because the P availability in the soil appears to insolubilize Cu and may also mitigate the negative effects of Cu toxicity [51]. In fact, in the areas evaluated, no evident symptoms of toxicity in the plant due to metals were observed, but rather concentrations that may be above the sufficiency range cited in regional technical recommendations.
The variability of species in each area and the intensity of applications carried out explain the differences in the concentrations of Cu, Zn, and Mn in tissue (Figure 2) and content of Cu, Zn, and Mn in soil (Figure 1), especially when above the proposed CTL values. Additionally, these results also help to explain the lower biomass production of the plants growing in the V1 and V2 vineyards compared to the NF (Table 1). Furthermore, our results show differences in the relation between Cu, Zn, and Mn levels in soil and tissue (Figure 1 and Figure 2). This can be attributed to the antagonistic effect between metals, where the excess of one metal can affect the absorption of another, decreasing or increasing the concentration of the other metal in the tissue [52]. This is especially because some of the families of metal transporters in plants can allow the entry of multiple metals showing a low specificity [53]. When there are several metals in high levels in the soil, there will be competition between them for the same absorption sites [54]. This competition affects the homeostasis of these metals in plant tissues, which, together with the chemical and genetic structure of each cover plant, contributes to the plant’s response behavior in relation to metal levels. This may be linked to metal transporters, which influence the allocation of these metals in the plant. For example, Cu tends to be more allocated in the roots or bound to the cell wall, Zn presents higher concentrations in the roots, while the highest concentrations of Mn are observed in the aerial part [55,56].
The literature shows several studies evaluating the impact of metals on plants that cohabit vineyards. In fact, dry mass production, as observed in our study, is one of the main variables affected, mainly due to the impairment of physiological, morphological, and biochemical processes occurring in plants subjected to environments with levels considered excessive for plant absorption. Among these studies, we observed that cover crop species respond differently to Cu concentrations [57]. However, lower plant biomass production, lower root growth, chlorosis, tanning, and necrosis are the common symptoms associated with Cu, when considered in excessive concentrations for plants caused by the increased generation of reactive oxygen species (ROS) and harmful interfaces at the cellular level [58]. Toselli et al. [59], evaluating grapevines grown in pots, reported that increased Cu in the soil reduces root growth, followed by reduced shoot growth, as well as promoting a reduction in the Zn and Mn concentrations in the roots. The lower root growth was confirmed by Morsch et al. [20] in an evaluation of different grapevine rootstocks in the presence of high Cu concentrations, which was caused by changes in morphological and anatomical aspects, such as root size, diameter, and color. Also, De Conti et al. [60], evaluating the responses of ryegrass (Lolium perenne L.) in vineyard areas under high levels of Cu in the soil, found that the physiological changes caused by the high Cu concentration in the plants also affected the concentration of amino acids in ryegrass roots. High Cu absorption causes changes in the nutritional composition, photosynthetic activity, growth, and plant biomass accumulation [61,62]. Silva et al. [26], when assessing the tolerance of the high Cu content of soil in native plants of the Pampa biome, reported that plants exposed to these high concentrations showed limited photosynthetic activity, root morphology, and nutritional status, both for macronutrients and micronutrients.
Zinc levels in the soil, when in excess for plants, can cause root tortuosity due to alterations in the cell division process, such as the disorganization of cell division and inhibition of cell elongation [63]. High Zn concentrations in the plant can interrupt the transport and distribution of auxin at the root tips, thus altering the morphology of the root system [64]. High Zn concentrations in plant tissue can affect the processes of membrane transporters and ion channels [65]. High concentrations of metals for plants absorption cause an increase in non-specific membrane permeability and may be responsible for causing nutritional imbalances in plants grown in soils with high levels of metals such as Zn [66]. The inhibition of dry mass production under Zn stress can be explained by the non-specific manifestation of changes in physico-biochemical characteristics that can cause direct effects, such as toxicity through accumulation in tissues and/or indirect effects, e.g., mineral limitation and water uptake [65].
Quantities considered excessive for the plants’ absorption capacity causes the impairment of various cell metabolism processes, causing the degradation of lipids, proteins, carbohydrates, and nucleic acids, which leads to cell death [67]. It can also cause chlorosis and necrosis, leaf wrinkling, or brown lesions, delaying plant growth [68]. In the tissue, Mn quantities considered excessive for the plants’ absorption capacity can affect the absorption, redistribution, and use of other elements such as phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), Sulphur (S), and boron (B), thus modifying the physiological and productive responses of plants [69]. The chloroplast is the main organelle affected by high Mn levels in the plant, due to the disruption of the structure of the thylakoids and the electron transport chain [15], caused by the formation of ROS, and consequently, oxidative stress, which is responsible for the degradation of various cellular structures [70]. In a study evaluating grapevine rootstocks grown in hydroponics under conditions of high Cu levels for plant uptake, Marastoni et al. [71] observed a reduction in the concentration of Zn and Mn in the root apoplast. A different behavior was observed in the root apoplast, with the Zn concentration increasing and Mn concentration decreasing. De Conti et al. [60] observed that soils contaminated with levels of 80 mg Cu kg−1 showed an increase in the concentration of Mn in leaf tissue, which could reach values close to critical levels of toxicity.
The BSQR models used to generate the CTL values are generated from several simulations based on the data set. It is observed that the CTL delimitation can be influenced by the sampling locations. However, it is noted that in the set, we have sample data from native areas, with very low values of Cu, Mn, and Zn, and that these data did not influence the CTL delimitation. This occurs because the CTL values are established by the model based on the relation between the concentration of Cu, Mn, and Zn in the soil or plant tissue and the production of dry mass in infinite combinations [41,44]. The BSQR models are robust for obtaining CTL values, as they show values from which there is a reduction in the production of dry mass of plants. However, it is worth mentioning that more accurate CTL values can be obtained with larger data sets, which is a demand for future research.
In this context, based on changes in dry mass production of native plants, CTL values in the soil and in native plants are indicators of soil contamination in vineyards in the Pampa biome and may even contribute to adjusting vineyard management. In addition, some native grasses of the Pampa biome (for example, P. plicatulum and P. notatum) have the potential to be used in the phytoremediation process [6,19,72], so knowledge of these values can help in the selection of species that are more tolerant to metals. In addition, the CTL values obtained in this study can be used to develop future projects to restore these areas by planting species native to the Pampa biome, benefiting not only winegrowers, but also the entire ecosystem and its functions.

5. Conclusions

The CTLs for Cu, Zn, and Mn in the soil were set at 15, 30, and 35 mg kg−1, respectively. In the tissue, CTLs for Cu, Zn, and Mn were estimated at 75, 77, and 380 mg kg−1, respectively.
The soils of vineyards with more than 40 years of cultivation in the Pampa biome evaluated in this study have Cu, Zn, and Mn values above the proposed CTL.
The concentrations of Cu and Zn in the tissue of the plants that live between the rows of vineyards are above the proposed CTL of these metals in the tissue, showing a reduction in dry mass production.
Finally, these CTL values of Cu, Mn, and Zn can be used to monitor the concentration of Cu, Mn, and Zn in vineyards, aiming to reduce the application of agricultural pesticides based on these elements. Also, these CTL values can be used to select tolerant native species with the aim of planning the restoration of ecosystems contaminated with these elements.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11070831/s1, Table S1. Characterization of the soils in the native field (NF), vineyard 1 (V1) and vineyard 2 (V2).

Author Contributions

Conceptualization, L.M., J.M.M.-B., E.T., and G.B.; methodology, F.N.d.O., L.M., A.T., E.T., A.C.R.M., T.A., and B.G.D.; formal analysis, F.N.d.O., L.M., J.M.M.-B., and A.T.; data curation, F.N.d.O., L.M., E.T., A.C.R.M., T.A., and B.G.D.; writing—original draft preparation, F.N.d.O., and L.M.; writing—review and editing, L.M., J.M.M.-B., A.T., L.A.T., and G.B.; supervision, project administration, and funding acquisition, G.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brazilian National Council for Scientific and Technological Development)—CNPq (process number 408318/2018; 302023/2019-4; 306146/2023-1), and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Foundation for Research Support of the State of Rio Grande do Sul)—FAPERGS (term of grant 17/2551-0000925-8).

Data Availability Statement

All the data used in this study are included in this article.

Acknowledgments

The authors are grateful to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Brazilian Federal Agency for Support and Evaluation of Graduate Education)—CAPES, Conselho Nacional de Desenvolvimento Científico e Tecnológico (Brazilian National Council for Scientific and Technological Development)—CNPq, and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Foundation for Research Support of the State of Rio Grande do Sul)—FAPERGS for the scholarships provided and the financial resources made available for this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Lanfranco, B.; Fernández, E.; Ferraro, B.; de Lima, J.M.S. Historical changes in the Pampas biome, land use, and climate change. In Handbook of Behavioral Economics and Climate Change; Edward Elgar Publishing: Cheltenham, UK, 2022; pp. 162–191. [Google Scholar] [CrossRef]
  2. Brunetto, G.; Melo, G.W.B.; Terzano, R.; Del Buono, D.; Astolfi, S.; Tomasi, N.; Cesco, S. Copper accumulation in vineyard soils: Rhizosphere processes and agronomic practices to limit its toxicity. Chemosphere 2016, 162, 293–307. [Google Scholar] [CrossRef] [PubMed]
  3. Gutiérrez-Gamboa, G.; Fourment, M. Research and innovations in latin american vitiviniculture: A review. Horticulturae 2025, 11, 506. [Google Scholar] [CrossRef]
  4. Vento, B.; Ginebra, M.; Vallebella, M.; Bonjour, L.; Ontivero, M.; Duplancic, A.; Mezzatesta, D.; Martinez-Carretero, E. Assessing the contribution of spontaneous vegetation to carbon storage and biodiversity in a vineyard of Argentina. Agroecol. Sustain. Food Syst. 2025, 49, 41–62. [Google Scholar] [CrossRef]
  5. Garavani, A.; Capri, C.; Del Zozzo, F.; Diti, I.; Poni, S.; Gatti, M. Relationship between intra-parcel variability and carbon allocation and sequestration in a mature Barbera (Vitis vinifera L.) vineyard ecosystem. Sci. Hortic. 2023, 309, 111617. [Google Scholar] [CrossRef]
  6. De Conti, L.; Marques, A.C.R.; Ceretta, C.A.; Tarouco, C.P.; Nicoloso, F.T.; Ferreira, P.A.A.; Brunetto, G. Tolerance and phytoremediation potential of grass species native to South American grasslands to copper-contaminated soils. Int. J. Phytoremediation 2021, 23, 726–735. [Google Scholar] [CrossRef] [PubMed]
  7. Angon, P.B.; Islam, M.S.; Das, A.; Anjum, N.; Poudel, A.; Suchi, S.A. Sources, effects and present perspectives of heavy metals contamination: Soil, plants and human food chain. Heliyon 2024, 10, e28357. [Google Scholar] [CrossRef]
  8. Silva, F.B.V.; Nascimento, C.W.A.; Araújo, P.R.M.; Silva, L.H.V.; Silva, R.F. Assessing heavy metal sources in sugarcane Brazilian soils: An approach using multivariate analysis. Environ. Monit. Assess. 2016, 188, 457. [Google Scholar] [CrossRef]
  9. Poggere, G.; Gasparin, A.; Barbosa, J.Z.; Melo, G.W.; Corrêa, R.S.; Motta, A.C.V. Soil contamination by copper: Sources, ecological risks, and mitigation strategies in Brazil. J. Trace Elem. Min. 2023, 4, 100059. [Google Scholar] [CrossRef]
  10. Marschner, H. Mineral Nutrition of Higher Plants, 2nd ed.; Academic Press: London, UK, 1995. [Google Scholar]
  11. Chen, G.; Li, J.; Han, H.; Du, R.; Wang, X. Physiological and molecular mechanisms of plant responses to copper stress. Int. J. Mol. Sci. 2022, 23, 12950. [Google Scholar] [CrossRef]
  12. Cruz, F.J.R.; da Cruz Ferreira, R.L.; Conceição, S.S.; Lima, E.U.; de Oliveira Neto, C.F.; Galvão, J.R.; Lopes, S.C.; Viegas, I.D.J.M. Copper toxicity in plants: Nutritional, physiological, and biochemical aspects. In Advances in Plant Defense Mechanisms; IntechOpen: Rijeka, Croatia, 2022. [Google Scholar] [CrossRef]
  13. Castillo-González, J.; Ojeda-Barrios, D.; Hernández-Rodríguez, A.; González-Franco, A.C.; Robles-Hernández, L.; López-Ochoa, G.R. Zinc metalloenzymes in plants. Interciencia 2018, 43, 242–248. [Google Scholar]
  14. Broadley, M.; Brown, P.; Cakmak, I.; Rengel, Z.; Zhao, F. Function of nutrients: Micronutrients. In Marschner’s Mineral Nutrition of Higher Plants, 3rd ed.; Academic Press: London, UK, 2012; pp. 191–248. [Google Scholar] [CrossRef]
  15. Chen, Z.; Sun, L.; Liu, P.; Liu, G.; Tian, J.; Liao, H. Malate synthesis and secretion mediated by a manganese-enhanced malate dehydrogenase confers superior manganese tolerance in Stylosanthes guianensis. Plant Physiol. 2014, 167, 176–188. [Google Scholar] [CrossRef]
  16. Alejandro, S.; Höller, S.; Meier, B.; Peiter, E. Manganese in plants: From acquisition to subcellular allocation. Front. Plant Sci. 2020, 11, 300. [Google Scholar] [CrossRef] [PubMed]
  17. Marschner, P. Marschner’s Mineral Nutrition of Higher Plants, 3rd ed.; Academic Press: New York, NY, USA, 2012. [Google Scholar]
  18. Schmidt, S.B.; Jensen, P.E.; Husted, S. Manganese deficiency in plants: The impact on photosystem II. Trends Plant Sci. 2016, 21, 622–632. [Google Scholar] [CrossRef] [PubMed]
  19. Schwalbert, R.; Milanesi, G.D.; Stefanello, L.; Moura-Bueno, J.M.; Drescher, G.L.; Marques, A.C.R.; Nicoloso, F.T. How do native grasses from South America handle zinc excess in the soil? A physiological approach. Environ. Exp. Bot. 2022, 195, 104779. [Google Scholar] [CrossRef]
  20. Morsch, L.; Somavilla, L.M.; Trentin, E.; Silva, K.R.; de Oliveira, J.M.S.; Brunetto, G.; Simão, D.G. Root system structure as a criterion for the selection of grapevine genotypes that are tolerant to excess copper and the ability of phosphorus to mitigate toxicity. Plant Physiol. Biochem. 2022, 171, 147–156. [Google Scholar] [CrossRef]
  21. Li, X.; Yang, Y.; Jia, L.; Chen, H.; Wei, X. Zinc-induced oxidative damage, antioxidant enzyme response and proline metabolism in roots and leaves of wheat plants. Ecotoxicol. Environ. Saf. 2013, 89, 150–157. [Google Scholar] [CrossRef]
  22. Somavilla, L.M.; Simão, D.G.; Hammerschmitt, R.K.; Tiecher, T.L.; Oliveira, J.M.S.; Mayer, N.A.; Pavanello, E.P.; Trentin, E.; Belles, S.W.; Bruneto, G. Structural changes in roots of peach rootstock cultivars grown in soil with high zinc content. Sci. Hortic. 2018, 237, 1–10. [Google Scholar] [CrossRef]
  23. Girotto, E.; Ceretta, C.A.; Rossato, L.V.; Farias, J.G.; Tiecher, T.L.; De Conti, L.; Nicoloso, F.T. Triggered antioxidant defense mechanism in maize grown in soil with accumulation of Cu and Zn due to intensive application of pig slurry. Ecotoxicol. Environ. Saf. 2013, 93, 145–155. [Google Scholar] [CrossRef]
  24. Skórka, M.; Sieprawska, A.; Telk, A. The implication of manganese surplus on plant cell homeostasis: A review. J. Plant Growth Regul. 2023, 42, 1327–1341. [Google Scholar] [CrossRef]
  25. Zhao, J.; Wang, W.; Zhou, H.; Wang, R.; Zhang, P.; Wang, H.; Xu, J. Manganese toxicity inhibited root growth by disrupting auxin biosynthesis and transport in Arabidopsis. Front. Plant Sci. 2017, 8, 272. [Google Scholar] [CrossRef]
  26. Silva, I.C.B.; Marques, A.C.R.; Quadros, F.F.; Sans, G.A.; Soares, V.M.; De Conti, L.; Brunetto, G. Spatial variation of herbaceous cover species community in Cu-contaminated vineyards in Pampa biome. Environ. Sci. Pollut. Res. Int. 2020, 27, 13348–13359. [Google Scholar] [CrossRef]
  27. Woch, M.W.; Kapusta, P.; Stefanowicz, A.M. Variation in dry grassland communities along a heavy metals gradient. Ecotoxicology 2016, 25, 80–90. [Google Scholar] [CrossRef]
  28. Vidic, T.; Jogan, N.; Drobne, D.; Vilhar, B. Natural revegetation in the vicinity of the former lead smelter in Žerjav, Slovenia. Environ. Sci. Technol. 2006, 40, 4119–4125. [Google Scholar] [CrossRef]
  29. Rola, K.; Osyczka, P.; Nobis, M.; Drozd, P. How do soil factors determine vegetation structure and species richness in post-smelting dumps? Ecol. Eng. 2015, 75, 332–342. [Google Scholar] [CrossRef]
  30. Wong, M. Ecological restoration of mine degraded soils, with emphasis on metal contaminated soils. Chemosphere 2003, 50, 775–780. [Google Scholar] [CrossRef]
  31. Dresseno, A.L.; Guido, A.; Balogianni, V.; Overbeck, G.E. Negative effects of an invasive grass, but not of native grasses, on plant species richness along a cover gradient. Austral Ecol. 2018, 43, 949–954. [Google Scholar] [CrossRef]
  32. Santos, A.P.; Matias, C.A.; Cantoni, F.; Miquelluti, D.J.; Campos, M.L. Critical limits for zinc to forage species. Rev. Ibero-Am. Ciênc. Ambient. 2021, 12, 97–107. [Google Scholar] [CrossRef]
  33. Webb, R.A. Use of the boundary line in the analysis of biological data. J. Hortic. Sci. 1972, 47, 309–319. [Google Scholar] [CrossRef]
  34. Makowski, D.; Doré, T.; Monod, H. A new method to analyze relationships between yield components with boundary lines. Agron. Sustain. Dev. 2007, 27, 119–128. [Google Scholar] [CrossRef]
  35. Alvares, C.A.; Stape, J.L.; Sentelhas, P.C.; Gonçalves, J.D.M.; Sparovek, G. Köppen’s climate classification map for Brazil. Meteorol. Z. 2013, 22, 711–728. [Google Scholar] [CrossRef]
  36. INMET—Instituto Nacional de Meteorologia. Climatological Normals. Available online: https://portal.inmet.gov.br/normais (accessed on 5 June 2023).
  37. Streck, E.V.; Kämpf, N.; Dalmolin, R.S.D.; Klamt, E.; Nascimento, P.C.; Schneider, P.; Giasson, E.; Pinto, L.F.S. Solos do Rio Grande do Sul, 3rd ed.; UFRGS: Porto Alegre, Brazil, 2018; 251p. (In Portuguese) [Google Scholar]
  38. USDA—Soil Survey Staff. Keys to Soil Taxonomy; United States Department of Agriculture Natural Resources Conservation Service: Washington, DC, USA, 2014.
  39. Embrapa—Empresa Brasileira de Pesquisa Agropecuária. Manual de Análises Químicas de Solos, Plantas e Fertilizantes, 2nd ed. rev. ampl.; Embrapa Informação Tecnológica: Brasília, Brazil, 2009; 627p. (In Portuguese) [Google Scholar]
  40. Tedesco, M.; Gianello, C.; Bissani, C. Análises de Solo, Plantas e Outros Materiais; UFRGS: Porto Alegre, Brazil, 1995; p. 174. (In Portuguese) [Google Scholar]
  41. Liang, Z.; Qian, S.S.; Wu, S.; Chen, H.; Liu, Y.; Yu, Y.; Yi, X. Using Bayesian change point model to enhance understanding of the shifting nutrients-phytoplankton relationship. Ecol. Modell. 2019, 393, 120–126. [Google Scholar] [CrossRef]
  42. Kruschke, J.K.; Liddell, T.M. Bayesian data analysis for newcomers. Psychon. Bull. Rev. 2018, 25, 155–177. [Google Scholar] [CrossRef] [PubMed]
  43. Gelman, A.; Hill, J. Data analysis using regression and multilevel models. In Data Analysis Using Regression and Multilevel/Hierarchical Models; Cambridge University Press: New York, NY, USA, 2007; p. 625. [Google Scholar]
  44. Plummer, M. rjags: Bayesian Graphical Models Using MCMC; R Package Version 3–13; R Foundation for Statistical Computing: Vienna, Austria, 2016; pp. 1–19. [Google Scholar]
  45. R Core Team. The R Project for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2022; Available online: https://www.r-project.org/ (accessed on 15 February 2025).
  46. Girotto, E.; Ceretta, C.A.; Rossato, L.V.; Farias, J.G.; Brunetto, G.; Miotto, A.; Nicoloso, F.T. Biochemical changes in black oat (Avena strigosa schreb) cultivated in vineyard soils contaminated with copper. Plant Physiol. Biochem. 2016, 103, 199–207. [Google Scholar] [CrossRef] [PubMed]
  47. Ferreira, G.W.; Lourenzi, C.R.; Comin, J.J.; Loss, A.; Girotto, E.; Ludwig, M.P.; Brunetto, G. Effect of organic and mineral fertilizers applications in pasture and no-tillage system on crop yield, fractions and contaminant potential of Cu and Zn. Soil Tillage Res. 2023, 225, 105523. [Google Scholar] [CrossRef]
  48. Brunetto, G.; Miotto, A.; Ceretta, C.A.; Schmitt, D.E.; Heinzen, J.; de Moraes, M.P.; Girotto, E. Mobility of copper and zinc fractions in fungicide-amended vineyard sandy soils. Arch. Agron. Soil Sci. 2013, 60, 609–624. [Google Scholar] [CrossRef]
  49. Wang, C.; Yang, Z.; Yuan, X.; Browne, P.; Chen, L.; Ji, J. The influences of soil properties on Cu and Zn availability in soil and their transfer to wheat (Triticum aestivum L.) in the Yangtze River delta region, China. Geoderma 2013, 193, 131–139. [Google Scholar] [CrossRef]
  50. Rashid, A.; Schutte, B.J.; Ulery, A.; Deyholos, M.K.; Sanogo, S.; Lehnhoff, E.A.; Beck, L. Heavy metal contamination in agricultural soil: Environmental pollutants affecting crop health. Agronomy 2023, 13, 1521. [Google Scholar] [CrossRef]
  51. Baldi, E.; Miotto, A.; Toselli, M.; Ceretta, C.A.; Brunetto, G. Increasing phosphorus concentration in soil as a possible strategy to overcome Cu excess toxicity symptoms. Acta Hortic. 2018, 1228, 421–426. [Google Scholar] [CrossRef]
  52. Zanin, L.; Tomasi, N.; Rizzardo, C.; Gottardi, S.; Terzano, R.; Alfeld, M.; Cesco, S. Iron allocation in leaves of Fe-deficient cucumber plants fed with natural Fe complexes. Physiol. Plant. 2015, 154, 82–94. [Google Scholar] [CrossRef]
  53. Grotz, N.; Guerinot, M.L. Molecular aspects of Cu, Fe and Zn homeostasis in plants. Biochim. Biophys. Acta 2006, 1763, 595–608. [Google Scholar] [CrossRef]
  54. Rai, S.; Singh, P.K.; Mankotia, S.; Swain, J.; Satbhai, S.B. Iron homeostasis in plants and its crosstalk with copper, zinc, and manganese. Plant Stress 2021, 1, 100008. [Google Scholar] [CrossRef]
  55. Page, V.; Feller, U. Heavy metals in crop plants: Transport and redistribution processes on the whole plant level. Agronomy 2015, 5, 447–463. [Google Scholar] [CrossRef]
  56. Chao, Z.F.; Chao, D.Y. Barriers and carriers for transition metal homeostasis in plants. Plant Commun. 2025, 6, 101235. [Google Scholar] [CrossRef] [PubMed]
  57. Eon, P.; Robert, T.; Goutouly, J.-P.; Aurelle, V.; Cornu, J.-Y. Cover crop response to increased concentrations of copper in vineyard soils: Implications for copper phytoextraction. Chemosphere 2023, 329, 138604. [Google Scholar] [CrossRef]
  58. Visconti, F.; López, R.; Olego, M.Á. The health of vineyard soils: Towards a sustainable viticulture. Horticulturae 2024, 10, 154. [Google Scholar] [CrossRef]
  59. Toselli, M.; Baldi, E.; Marcolini, G.; Malaguti, D.; Quartieri, M.; Sorrenti, G.; Marangoni, B. Response of potted grapevines to increasing soil copper concentration. Aust. J. Grape Wine Res. 2009, 15, 85–92. [Google Scholar] [CrossRef]
  60. De Conti, L.; Ceretta, C.A.; Melo, G.W.B.; Tiecher, T.L.; Silva, L.O.; Garlet, L.P.; Brunetto, G. Intercropping of young grapevines with native grasses for phytoremediation of Cu-contaminated soils. Chemosphere 2019, 216, 147–156. [Google Scholar] [CrossRef]
  61. Adrees, M.; Ali, S.; Rizwan, M.; Ibrahim, M.; Abbas, F.; Farid, M.; Bharwana, S.A. The effect of excess copper on growth and physiology of important food crops: A review. Environ. Sci. Pollut. Res. 2015, 22, 8148–8162. [Google Scholar] [CrossRef]
  62. Marques, D.M.; Veroneze Júnior, V.; Silva, A.B.; Mantovani, J.R.; Magalhães, P.C.; Souza, T.C. Copper toxicity on photosynthetic responses and root morphology of Hymenaea courbaril L. (Caesalpinioideae). Water Air Soil Pollut 2018, 229, 138. [Google Scholar] [CrossRef]
  63. Potters, G.; Pasternak, T.P.; Guisez, Y.; Palme, K.J.; Jansen, M.A. Stress-induced morphogenic responses: Growing out of trouble? Trends Plant Sci. 2007, 12, 98–105. [Google Scholar] [CrossRef]
  64. Zhang, P.; Sun, L.; Qin, J.; Wan, J.; Wang, R.; Li, S.; Xu, J. cGMP is involved in Zn tolerance through the modulation of auxin redistribution in root tips. Environ. Exp. Bot. 2018, 147, 22–30. [Google Scholar] [CrossRef]
  65. Kaur, H.; Garg, N. Zinc toxicity in plants: A review. Planta 2021, 253, 129. [Google Scholar] [CrossRef] [PubMed]
  66. Cambrollé, J.; Mancilla-Leytón, J.M.; Muñoz-Vallés, S.; Figueroa-Luque, E.; Luque, T.; Figueroa, M.E. Evaluation of zinc tolerance and accumulation potential of the coastal shrub Limoniastrum monopetalum (L.) Boiss. Environ. Exp. Bot. 2013, 85, 50–57. [Google Scholar] [CrossRef]
  67. Fernando, D.R.; Marshall, A.T.; Forster, P.I.; Hoebee, S.E.; Siegele, R. Multiple metal accumulation within a manganese-specific genus. Am. J. Bot. 2013, 100, 690–700. [Google Scholar] [CrossRef] [PubMed]
  68. Millaleo, R.; Reyes-Díaz, M.; Ivanov, A.G.; Mora, M.L.; Alberdi, M. Manganese as essential and toxic element for plants: Transport, accumulation and resistance mechanisms. J. Soil Sci. Plant Nutr. 2010, 10, 470–481. [Google Scholar] [CrossRef]
  69. Santos, E.F.; Santini, J.M.K.; Paixão, A.P.; Júnior, E.F.; Lavres, J.; Campos, M.; Dos Reis, A.R. Physiological highlights of manganese toxicity symptoms in soybean plants: Mn toxicity responses. Plant Physiol. Biochem. 2017, 113, 6–19. [Google Scholar] [CrossRef]
  70. Xue, S.; Zhu, F.; Wu, C.; Lei, J.; Hartley, W.; Pan, W. Effects of manganese on the microstructures of Chenopodium ambrosioides L., a manganese tolerant plant. Int. J. Phytoremediation 2016, 18, 710–719. [Google Scholar] [CrossRef]
  71. Marastoni, L.; Sandri, M.; Pii, Y.; Valentinuzzi, F.; Brunetto, G.; Cesco, S.; Mimmo, T. Synergism and antagonisms between nutrients induced by copper toxicity in grapevine rootstocks: Monocropping vs. intercropping. Chemosphere 2019, 214, 563–578. [Google Scholar] [CrossRef]
  72. Thiesen, L.A.; Brunetto, G.; Trentin, E.; Silva, A.A.K.; Tabaldi, L.A.; Schwalbert, R.; Nicoloso, F.T. Subcellular distribution and physiological responses of native and exotic grasses from the Pampa biome subjected to excess manganese. Chemosphere 2023, 310, 136801. [Google Scholar] [CrossRef]
Figure 1. Relation between the contents of Cu (a), Zn (b), and Mn (c) in the soil extracted by Mehlich-1 in the 0–20 cm layer and the dry mass production of the shoot of plants present in the inter-row of vineyard 1 (same grapevines in production since the first planting), vineyard 2 (soil revolved after the first planting of grapevines), and in the native field (without agricultural crops). The red dashed line represents the value of the critical toxicity level (CTL) of each of the metals in the soil determined by plateau linear regression at the 95th percentile BSQR (black dashed line).
Figure 1. Relation between the contents of Cu (a), Zn (b), and Mn (c) in the soil extracted by Mehlich-1 in the 0–20 cm layer and the dry mass production of the shoot of plants present in the inter-row of vineyard 1 (same grapevines in production since the first planting), vineyard 2 (soil revolved after the first planting of grapevines), and in the native field (without agricultural crops). The red dashed line represents the value of the critical toxicity level (CTL) of each of the metals in the soil determined by plateau linear regression at the 95th percentile BSQR (black dashed line).
Horticulturae 11 00831 g001
Figure 2. Relation between the concentrations of Cu (a), Zn (b), and Mn (c) and the dry mass production of the shoot of plants present in the inter-row of vineyard 1 (same grapevines in production since the first planting), vineyard 2 (soil revolved after the first planting of grapevines), and in the native field (without agricultural crops). The red dashed line represents the value of the critical toxicity level (CTL) of each of the metals in the soil determined by plateau linear regression at the 95th percentile BSQR (black dashed line).
Figure 2. Relation between the concentrations of Cu (a), Zn (b), and Mn (c) and the dry mass production of the shoot of plants present in the inter-row of vineyard 1 (same grapevines in production since the first planting), vineyard 2 (soil revolved after the first planting of grapevines), and in the native field (without agricultural crops). The red dashed line represents the value of the critical toxicity level (CTL) of each of the metals in the soil determined by plateau linear regression at the 95th percentile BSQR (black dashed line).
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Table 1. Dry mass production and Cu, Zn, and Mn levels in the soil and shoot of native plants present in the three areas evaluated, including the native field and vineyards 1 and 2.
Table 1. Dry mass production and Cu, Zn, and Mn levels in the soil and shoot of native plants present in the three areas evaluated, including the native field and vineyards 1 and 2.
Variable AnalyzedNative Field—NFVineyard 1—V1Vineyard 2—V2
Dry mass (g m−2)138.03 (±43.83)105.20 (±38.87)130.73 (±55.19)
Cu–shoot (mg kg−1)7.53 (±1.77)49.11 (±30.25)66.81 (±48.49)
Zn–shoot (mg kg−1)32.11 (±4.11)123.87 (±31.33)77.19 (±30.24)
Mn–shoot (mg kg−1)290.22 (±54.41)188.49 (±54.80)379.13 (±118.22)
Cu–soil (mg kg−1)0.44 (±0.10)23.06 (±4.45)18.62 (±4.15)
Zn–soil (mg kg−1)1.01 (±0.23)9.37 (±1.65)4.30 (±1.07)
Mn–soil (mg kg−1)23.15 (±4.88)55.33 (±13.17)29.31 (±9.48)
Values in brackets represent the standard deviation.
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de Oliveira, F.N.; Morsch, L.; Moura-Bueno, J.M.; Tassinari, A.; Trentin, E.; Marques, A.C.R.; Andreolli, T.; Dias, B.G.; Tabaldi, L.A.; Brunetto, G. Critical Levels of Copper, Zinc, and Manganese Toxicity in Soil and Tissues of Plants That Cohabit Vineyards in the Pampa Biome. Horticulturae 2025, 11, 831. https://doi.org/10.3390/horticulturae11070831

AMA Style

de Oliveira FN, Morsch L, Moura-Bueno JM, Tassinari A, Trentin E, Marques ACR, Andreolli T, Dias BG, Tabaldi LA, Brunetto G. Critical Levels of Copper, Zinc, and Manganese Toxicity in Soil and Tissues of Plants That Cohabit Vineyards in the Pampa Biome. Horticulturae. 2025; 11(7):831. https://doi.org/10.3390/horticulturae11070831

Chicago/Turabian Style

de Oliveira, Filipe Nunes, Letícia Morsch, Jean Michel Moura-Bueno, Adriele Tassinari, Edicarla Trentin, Anderson César Ramos Marques, Talita Andreolli, Bianca Goularte Dias, Luciane Almeri Tabaldi, and Gustavo Brunetto. 2025. "Critical Levels of Copper, Zinc, and Manganese Toxicity in Soil and Tissues of Plants That Cohabit Vineyards in the Pampa Biome" Horticulturae 11, no. 7: 831. https://doi.org/10.3390/horticulturae11070831

APA Style

de Oliveira, F. N., Morsch, L., Moura-Bueno, J. M., Tassinari, A., Trentin, E., Marques, A. C. R., Andreolli, T., Dias, B. G., Tabaldi, L. A., & Brunetto, G. (2025). Critical Levels of Copper, Zinc, and Manganese Toxicity in Soil and Tissues of Plants That Cohabit Vineyards in the Pampa Biome. Horticulturae, 11(7), 831. https://doi.org/10.3390/horticulturae11070831

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