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Article

Traceability and Heavy Metal Contamination in Agrosystems of Two Rice-Producing Areas of the Ecuadorian Coast

by
Jairo Jaime-Carvajal
1,*,
Jaime Naranjo-Morán
1,
Kevin Cedeño Vinces
1,
José Ballesteros
1,
Fernando Espinoza-Lozano
2,
Ivan Chóez-Guaranda
2 and
Simón Pérez-Martinez
3
1
Grupo de Investigación en Aplicaciones Biotecnológicas, GIAB, Universidad Politécnica Salesiana, UPS, Carrera de Biotecnología, Campus María Auxiliadora, Kilómetro 19.5 Vía a La Costa, Guayaquil 090901, Ecuador
2
Centro de Investigaciones Biotecnológicas del Ecuador, ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, Campus Gustavo Galindo, Kilómetro 30.5 Vía Perimetral, Guayaquil 090902, Ecuador
3
Facultad de Ciencias e Ingeniería, Universidad Estatal de Milagro (UNEMI), Milagro 091050, Ecuador
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(10), 2359; https://doi.org/10.3390/agronomy15102359 (registering DOI)
Submission received: 1 August 2025 / Revised: 26 August 2025 / Accepted: 3 September 2025 / Published: 9 October 2025
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
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Abstract

Rice (Oryza sativa) plays a fundamental role in the Ecuadorian diet. This study evaluated traceability and contamination by heavy metals in two rice-producing areas of Ecuador. Microwave-assisted digestion was used to process samples from rice agrosystems including irrigation water, soil, roots, stems, and leaves. Inductively coupled plasma optical emission spectroscopy (ICP-OES) was employed for elemental analysis. Arsenic (As), cadmium (Cd), lead (Pb), and chromium (Cr) were measured in samples collected in Daule and Ventanas. In soils, the concentrations of As (1.50–2.82 mg/kg) and Cd (1.22–1.45 mg/kg) exceeded the internationally recommended safety thresholds. In irrigation water, the content of As (0.85–1.12 mg/L), Pb (0.25–0.38 mg/L), and Cr (0.37–0.53 mg/L) surpass the international/national permissible limits. However, the limits established by Ecuadorian legislation indicate that As in soils did not exceed contamination thresholds. Additionally, the bioaccumulation of As and Pb in roots from Daule and Ventanas, respectively, was observed, along with the movement of Pb to aerial parts in Daule. Finally, preliminary As found in commercial rice grains suggest a potential health concern to the Ecuadorian population. These findings highlight the need for stricter heavy metal restrictions for rice agrosystems and effective agricultural pollution mitigation.

1. Introduction

Rice is a main crop and a fundamental component of the Ecuadorian food, particularly along the coastal provinces where climatic and soil conditions are ideal for cultivation. Ecuador ranks among the main rice producers in Latin America, with a production primarily centered in the provinces of Guayas and Los Ríos, which together account for over 93% of the national output [1,2]. These regions support both smallholder farmers and larger agro-industrial operations, contributing significantly to national food security and the rural economy. Traditional and semi-mechanized farming practices are commonly used, and irrigation systems play a crucial role in maintaining yields throughout the year [1]. However, challenges such as water quality, soil degradation, as well as potential contamination by agrochemicals have increased the bioavailability of heavy metals in agricultural systems worldwide [3]. Among these pollutants, phosphorus contamination of aquifers and cropland is particularly concerning, as it compromises food availability both regionally and globally. Studies have confirmed the presence of arsenic (As), cadmium (Cd), lead (Pb), and chromium (Cr) in groundwater, sediments, food, and human populations across at least 14 Latin American countries, emphasizing the need for continuous monitoring and assessment of these contaminants in the region [4,5].
In Ecuador, research in agricultural areas such as the Daule river basin in Guayas province an important rice-producing zone has documented heavy metals dispersion in irrigation water and soils, underscoring the urgency of evaluating their presence near rice processing facilities [6]. A previous study found that metal concentrations in soils including As, Pb, and Cd were below the permitted concentrations established by Ecuador and other countries. Nevertheless, a few samples have exhibited abnormally high levels of Cr along with copper (Cu), and nickel (Ni). Notably, Cd showed high bioavailability in the soil, while other elements such as As—when associated with labile, exchangeable, and soluble fractions—were found at concentrations that do not pose significant risks to crops [7]. These findings emphasize the importance of understanding metal speciation and distribution to assess potential threats to agricultural systems. In response, numerous studies have advanced analytical techniques to quantify As concentrations in water, soil, and rice samples aiming to better understand its mobility and potential risks [8,9,10]. A critical aspect of concern is the internal translocation of As from contaminated water to rice grains prior to consumption, as reported in regions like Córdoba, Colombia, where rice holds high nutritional and economic value [11,12,13,14]. Additionally, other investigations have revealed Cr contamination in rice fields in countries such as Bangladesh, India, Australia, Japan, Iran, and China [15].
The presence of heavy metals in rice-growing environments is especially problematic due to their environmental impacts such as contamination of water sources, soil degradation and reduced crop productivity which ultimately threaten food security. These metals can be absorbed by rice plants from contaminated irrigation water and soils, accumulate in edible grains, and enter to the human food chain, posing significant health risks [16]. As, a highly toxic metalloid, has been identified in both drinking and irrigation water in agricultural areas of Ecuador, raising concerns about chronic dietary exposure in populations that rely on rice as a staple food. In fact, a study conducted in Ecuador demonstrated that rice plays a more critical role in exposure than drinking water [17]. Likewise, Cr and its derivatives—commonly found in industrial compounds like chromic acid, chromates, and chromate molasses—are known for their high bioaccumulation potential and association with carcinogenicity and damage to the skin, eyes, and respiratory system [18]. Pb, which persists in the environment due to its historical use, also accumulates in plant tissues, with its organic forms being especially toxic due to their higher bioavailability and neurotoxic effects [19,20].
In response to these threats, international agencies such as the Codex Alimentarius have established maximum permissible levels for heavy metals in food products like rice: As (0.20 mg/kg), Cd (0.40 mg/kg) and Pb (0.20 mg/kg), while Cr (1.00 mg/kg) is regulated under guidelines from the National Institute for Occupational Safety and Health (NIOSH) [21]. However, data on As contamination in Ecuadorian rice remain limited, revealing a gap in knowledge that necessitates more comprehensive studies on the interaction of these metals with soil and environmental factors that influence their mobility and accumulation [22]. Therefore, the objective of this study was to determine the traceability and contamination levels of heavy metals in two rice-producing areas of Ecuador, to contribute further information about toxic contaminants in rice agrosystems given their implications for food security.

2. Materials and Methods

2.1. Sample Collection

Samples from rice agrosystems including irrigation water, soil, roots, stems, and leaves were collected from organic farming areas in Daule, Guayas province (2°01′28″ S, 80°02′43″ W), and Ventanas, Los Rios province (1°33′26″ S, 79°23′42″ W) as indicated in Figure 1. Soil: At each site, composite soil samples were collected within a one-hectare area by taking sub-samples from six points arranged in a zig-zag pattern at a depth of 20 cm. The sub-samples were thoroughly mixed to obtain a homogeneous composite sample weighing approximately 1 kg. Rice plants: Roots, stems, and leaves were collected from the corresponding points, with each sample composed of material from two individual plants at the flowering stage. Irrigation water: samples were collected directly from irrigation sources found on-site. Rice grains: commercial polished rice grains of different brands were obtained from local markets at two different locations in each province. In the Ecuadorian rice value chain, the milling and branding stages are vertically integrated. This means that the output of the mills operating in those regions processes rice grown in the surrounding local areas [23]. As required, samples were then placed in polypropylene bags (200 × 250 cm) as well as polypropylene bottles (1000 mL) and properly labeled for traceability prior to laboratory analysis. Afterward, solid samples were dried in a convection oven, ground using a mortar, and sieved through a 250 μm aperture mesh to obtain a homogeneous powder.

2.2. Microwave-Assisted Digestion

Sample preparation for elemental analysis was carried out by microwave-assisted digestion, following procedures described in the literature [24]. Solid samples (soil, root, stem, leaf, and grains) were digested as follows: 0.5 g of the sample was placed into digestion tubes and 10 mL of 65% nitric acid was added in an extractor hood. The tubes were properly closed, and the digestion process was carried out in the CEM MARS-6 microwave-assisted digestion equipment (CEM Corporation, Matthews, NC, USA). The digested samples were allowed to stand in the hood without a lid for 15 min. Subsequently, 10 mL of 2% nitric acid was added and filtered through metal-free filter paper. Finally, the samples were graduated to 50 mL in a volumetric flask with 2% nitric acid. Alternatively, water samples were processed according to U.S. EPA SW-846 method 3015A as follows: an aliquot of 100 mL was taken from the sample and 3 mL of 65% nitric acid was added. The acidified sample was evaporated to dryness using a hot plate in an extractor hood. Then, 5 mL of pure nitric acid was added and allowed to cool at room temperature. The treated sample was heated increasing the temperature until evaporation, thus completing total digestion. Then, 2 mL of pure nitric acid was added and heated until the residue was dissolved. Finally, the digested sample was washed with ultrapure water, filtered and graduated to 100 mL in a volumetric flask with distilled water.

2.3. Elemental Analysis by ICP-OES

Inductively coupled plasma optical emission spectroscopy (ICP-OES) is a validated technique for the detection and quantification of HMs in several type of samples. The analysis was conducted using a Thermo Scientific iCAP 7000 series ICP-OES instrument (Thermo Fisher Scientific Inc., Waltham, WA, USA). The ICP-OES method operates on the principle of utilizing argon gas to generate a radio frequency-coupled plasma. This high-temperature plasma (8000–10,000 K) converts the liquid sample into an aerosol, effectively atomizing and ionizing the sample. The resulting atomic spectra emitted by the sample are then measured by a light detector (monochromator), and the data is subsequently processed by a computer system [25].

2.4. Bioaccumulation and Translocation Factors

The bioaccumulation factor (BAF) indicates the ability of an organism to accumulate contaminants such as heavy metals from its surrounding environment. The BAF was calculated as the ratio of the concentration of heavy metals in the plant tissue (roots, stems and leaves) to their concentration in the soil or water. The translocation factor (TF) measures the ability of a plant to transfer absorbed elements from the roots to the aerial parts such as stems, leaves, or grains. A higher TF indicates greater mobility of the element within the plant. The TF was calculated as the ratio of concentration of heavy metals in the aerial parts (stems and leaves) to their concentration in the roots [26].

2.5. Statistical Analysis

Data analysis was performed in the statistical software Statgraphics Centurion 19 (Statgraphics Technologies, Inc., The Plains, VA, USA). All results were presented as mean ± standard deviation of six replicates. Differences in metal concentrations among samples from rice agrosystems were evaluated using two-way analysis of variance (ANOVA), followed by Tukey post hoc test with 5% of significance. For the two-way ANOVA, the assumptions tested included independence of observations, normality, homogeneity of variances, and additivity. The resulting data on heavy metal concentrations were then exported to MetaboAnalyst 6.0 for comprehensive multivariate statistical analysis. Data normalization was performed via cube root transformation and Pareto scaling. PLS-DA biplot was plotted with 95% confidence intervals applied to the first two components. Heatmap cluster analysis was generated using Pearson distance and average clustering method [27].

3. Results

3.1. Heavy Metals Detected in Rice Agrosystems

The concentration of heavy metals detected in different samples of rice agrosystems from two producing areas in Ecuador are presented in Table 1. As indicated, the spatial distribution of heavy metals followed consistent patterns across both study localities. As was predominantly accumulated in root tissues, with concentrations 1 to 3 times higher than those found in the soil. Overall, 63–68% of the total detected As was partitioned between the soil and root compartments. A similar below-ground distribution was observed for Cd and Cr, for which the soil and roots constituted the major reservoirs. These elements were either not detected or present in only minimal quantities in the irrigation water samples. In contrast, Pb was primarily distributed within the aerial plant structures. Between 72% and 79% of the total Pb was found across the stem and leaf compartments.
Despite these similar distribution trends, significant inter-locality differences were identified. The total content of all heavy metals in root tissues differed significantly between Daule and Ventanas. Furthermore, significant differences were observed for As concentrations in soil and for Cd concentrations in stems. No other samples showed statistically significant differences between the two sites. The overall burden of heavy metals across the entire agroecosystem, in descending order of total mass detected, was Cr (96.7 mg/kg) > As (18.4 mg/kg) > Pb (12.8 mg/kg) > Cd (4.8 mg/kg).

3.2. Multivariate Analysis of Heavy Metals Detected in Rice Agrosystems

Multivariate analysis was employed to visualize clustering patterns within the heavy metal content of different samples from the rice-producing areas. Figure 2. illustrates the biplot of the partial least squares-discriminant analysis (PLS-DA). The first two principal components explained 93.70% of data variability. The component 1 (50%) primarily distinguished samples with high As concentrations from those associated with elevated Cr and Cd levels. The component 2 (43.70%) further separated the samples with higher Cr and Cd concentrations from those with greater Pb accumulation. This separation indicated differential uptake and migration dynamics among heavy metals. Notably, soil samples from Daule and Ventanas were strongly associated with Cr and Cd, suggesting high metal concentrations in these matrices. Root samples, particularly from Daule, also were aligned with the direction of Cd, while leaf, stem, and water samples were clustered toward the direction of As, indicating movement of As into aerial parts of the plant. In contrast, Pb was positioned closer to stem and leaf samples, reflecting its moderate accumulation in above-ground parts. The clusters separation by producing area and sample matrix possibly demonstrates the influence of site-specific conditions and plant tissue on heavy metal distribution, highlighting differential dynamics of toxic elements in the rice agrosystems of Daule and Ventanas.
The heatmap cluster analysis shown in Figure 3. supported the separation explained by the PLS-DA biplot. Notably, Cr and Cd were predominant in soil samples from both locations, while As was predominant in water from Ventanas while Pb was predominant in leaves from Daule, suggesting significant mobility of Pb from the environment to the aerial parts of the plant. Root and soil samples tended to cluster closely, reflecting similar accumulation behaviors, while leaf and stem samples formed separate groups, likely due to varying degrees of metal mobility within the plant. The close clustering of water samples from Daule and Ventanas indicates comparable contamination profiles in irrigation sources. Overall, this analysis highlights the distinct accumulation and translocation patterns of toxic elements within the rice agrosystems of both producing areas.

3.3. Bioaccumulation and Translocation of Heavy Metals Detected in Rice Agrosystems

The bioaccumulation factors (BAF) and translocation factors (TF) of As, Cd, Pb, and Cr in rice plants collected from the two main producing areas in Ecuador are presented in Table 2. As previously indicated, the BAF values describe the efficiency of metal uptake from soil into different plant organs including roots, stems, and leaves, while the TF values indicate the extent of internal redistribution of metals from the roots to the aerial parts including stems, and leaves. This comparison allows us to evaluate both the capacity of rice plants to accumulate heavy metals from the soil and their potential to translocate them into edible plant tissues.

3.4. Heavy Metals Detected in Commercial Polished Rice Grains

The concentration of heavy metals detected in commercial polished rice grains from Daule and Ventanas are presented in Table 3. Although rice grain samples from the same plants were not included in the collection, commercial grain samples from the same locations were purchased and evaluated. The obtained data were analyzed in an exploratory manner and interpreted within that context due to the limited number of samples assessed [29]. In this sense, the results showed the presence of the assessed elements in both provinces.

4. Discussion

4.1. Trace Levels of Heavy Metals Detected in Rice Agrosystems

These results revealed significant differences in heavy metal content between samples of rice agrosystems from Daule and Ventanas (Table 1). Soil samples from Daule revealed the highest level of Cr, followed by those from Ventanas while roots showed significant accumulation of Cr, especially in Ventanas. Leaves and stems showed moderate transference, particularly in Ventanas, suggesting greater mobility of Cr compared to other metals. This could be attributed to localized contamination sources, including industrial operations such as mining or human related factors that impact the natural composition of the soils [7,30]. In fact, the high concentration of Cr in soil samples suggests possible historical contamination that has led to the accumulation of this metal in the agricultural ecosystem [31]. Regarding As, root samples from Daule showed the highest accumulation, being significantly superior to the other matrices. Root and soil samples from Ventanas showed comparable concentrations, whereas stem and leaves from two rice-producing areas indicated moderate metal mobilization, mainly in Ventanas. In both provinces, As showed increasing concentrations from water to soil to roots, followed by decreasing levels from stems to leaves. Similar patterns for the content of As from irrigation water (<5 μg/L) to soils (4.48 mg/kg) have been described for samples collected in Guayas province [6]. On the other hand, soil samples from Daule and Ventanas showed similar content of Cd, while root samples from both areas revealed noticeable accumulation, being slightly higher in Ventanas. The presence of Cd in stem samples was lower, denoting a limited redistribution of the element, while it was not detected in leaf samples. The Cd content of soil found in this study were higher than previous concentration of 0.26 mg/kg reported for samples collected in different location in the province of Guayas [32]. Regarding Pb, root samples from Ventanas presented the highest content, whereas the content of irrigation water were relatively low in both areas.
The results of irrigation water revealed a distinct contrast between Cd and Pb contamination. Cd was consistently below the limit of detection, suggesting its absence, or presence only in trace quantities that pose a minimal immediate risk via irrigation. Similar results have been reported in other studies conducted within the region, which also describe low background concentration (0.02 μg/L) [33]. Conversely, Pb occurred at elevated concentrations, exceeding by several orders of magnitude the 0.05 µg/L previously reported in the aforementioned study. This marked discrepancy points to potent and localized anthropogenic sources of Pb contamination in our study areas, such as industrial discharge, historical use of high-lead gasoline, or improper disposal of lead-based materials. The elevated Pb levels in water represent a direct and significant pathway for plant uptake and subsequent entry into the food chain. The results of soil samples indicate that As content in both rice-producing areas were within the range (5–10 mg/kg) considered typical for uncontaminated soil as described in other study [6]. Although As is detectable, the total As load is not particularly elevated. Notably, evidence from the same region highlights that the bioavailable fraction of As is generally minimal (~10% of total As) [6], suggesting a limited immediate phytoavailability despite its total presence. In contrast, Cd showed a more concerning profile. Our results exceeded the previously reported range (0.05–0.69 mg/kg) for these provinces [7,33]. More importantly, literature values indicate that the bioavailable fraction of Cd can be high, representing 24–61% of the total pool [7]. The combination of elevated Cd and its high potential bioavailability signify a considerable risk for plant uptake. For Pb, our measured concentrations were lower than the regional average of 13.52 mg/kg reported [33]. Conversely, Cr levels in our study were approximately half of those reported elsewhere (47–59 mg/kg) for the same rice-producing area [7]. Remarkably, the bioavailable fractions for both Cr and Pb are reported to be very low in these soils (~0.4% for Cr), significantly mitigating their potential mobility and toxicity despite their total concentrations.
Overall, the main pollution sources of heavy metals in the coastal provinces of Guayas and Los Rios are attributable to a combination of natural and anthropogenic sources. For instance, groundwater used for irrigation often contains naturally occurring As released from local geological formations, including mineral deposits and geothermal activity located in the Andean region of north-central Ecuador [34], which is further mobilized by the flooded conditions typical of rice paddies. Regarding anthropogenic input, in rice-producing countries including parts of Asia and South America, Cd and As contamination are particularly linked to phosphate fertilizer application and mining wastewater which contaminates paddy fields, while Pb and Cr are often tied to industrial effluents and tannery discharges [35,36,37]. Altogether, these are the sources of contamination that most contribute to elevated concentrations in soils and irrigation water.
It is important to highlight that our results were estimated as total As and total Cr since their assessment provides a foundational understanding of contamination levels. However, the speciation of these elements is critical to accurately evaluate their toxicity and bioavailability to rice plants. In the case of As, its toxicity is highly species dependent. Inorganic As (iAs) is the form of greatest concern for human health, with trivalent arsenic (As3+) being significantly more toxic than pentavalent arsenic (As5+) [38]. These inorganic forms have different mechanisms of toxicity. Arsenate disrupts phosphate metabolism, while arsenite binds thiol groups in proteins, impairing enzyme activity. Both pathways generate reactive oxygen species, causing oxidative stress [38]. Consequently, the measurement of iAs is considered the gold standard for health risk assessment [33]. In the context of rice, this focus remains particularly relevant. Although some iAs remains in inedible plant parts, its accumulation in the grain is the primary exposure route for humans. Our data indicating high As concentrations, along with significant root accumulation suggest a clear potential for grain contamination that warrants careful attention. Notably, the measurement of tAs remains valid as a robust screening tool. In fact, this is explicitly endorsed by the Codex Alimentarius, which stipulates that if the tAs concentration is at or below the maximum level established for iAs, the sample is deemed compliant, requiring no further speciation analysis [30]. Therefore, while tAs is a valuable initial indicator, future research should prioritize speciation analysis to precisely quantify iAs in grains, which is imperative for a robust and accurate human health risk assessment in the studied regions. On the other hand, the mobility and plant availability of Cr and Pb in paddy soils are strongly limited by their association with iron (Fe) oxyhydroxides. Specifically, these metals are often adsorbed onto the surfaces of crystalline Fe oxides. The prevailing mildly acidic to neutral pH and fluctuating redox conditions in Ecuadorian rice paddies promote the stability of these crystalline minerals [6]. Under these conditions, the adsorbed metallic fractions of total Cr and Pb become effectively non-bioavailable for rice plant uptake [7]. This is particularly relevant for Cr speciation since the stable form under these conditions is trivalent chromium (Cr3+), which has low solubility and mobility. In contrast, the highly toxic and mobile hexavalent chromium (Cr6+), is unstable in the reducing environments typical of flooded rice fields and is rapidly reduced to (Cr3+) or adsorbed. Therefore, while we report total Cr, the majority is likely in the immobile (Cr3+) form, sequestered by Fe oxides and thus posing a lower direct risk of plant translocation. Nevertheless, our reported total Cr values remain highly valuable for environmental assessment and regulatory purposes [39]. They provide crucial baseline data on the overall metal burden in the ecosystem, which is essential for monitoring pollution trends, assessing compliance with total concentration guidelines, and informing environmental management strategies.

4.2. Comparison of Heavy Metals Levels with Regulatory Standards

To contextualize the heavy metal concentrations within a regulatory framework, the results of irrigation water and soil samples were compared to the maximum permissible limits established by the Unified Text of the Secondary Legislation of the Ministry of Environment (TULSMA) [40,41] as well as the Food and Agriculture Organization and World Health Organization (FAO/WHO) [42,43,44] (Table 4). In this sense, differences in the permissible limits for heavy metals between Ecuadorian legislation (TULSMA) and international guidelines (FAO/WHO) primarily reflect variations in environmental conditions, methodological approaches, and regulatory priorities. For instance, the Ecuadorian legislation TULSMA defines soil quality criteria that reflect the geological background, agricultural practices, and exposure scenarios of the country, which may lead to more tolerant thresholds in areas with naturally high metal concentrations [41]. Moreover, permissible limits at the national level often consider feasibility of compliance and socio-economic implications, balancing the protection of human health with the practical realities of agricultural productivity and enforcement capacity [45]. In contrast, international guidelines such as the FAO/WHO are designed to protect consumers globally and adopt more conservative values based on average dietary intake, toxicological data, and cumulative exposure [44]. Consequently, discrepancies arise local standards may prioritize feasibility and adaptation to regional realities, while international frameworks emphasize harmonization of food safety. These differences are evident in Ecuador, where trace elements in soils sometimes exceed TULSMA limits, yet crop concentrations can also surpass the FAO/WHO maximum permissible levels, highlighting the tension between national adaptability and global health protection [30,46].
Given the above, the compliance of water and soil samples was reviewed separately. In irrigation water, As was the most significant contaminant, exceeding the stringent FAO/WHO limit (0.01 mg/L) in Daule (1.12 mg/L), and Ventanas (0.85 mg/L) showing an approximately 100-fold change in both provinces. When compared to the less strict national Ecuadorian limit (0.10 mg/L), As concentrations showed a 9.8-fold change on average considering both provinces. In addition, the measured levels of Pb (0.25–0.38 mg/L), and Cr (0.37–0.53 mg/L) were above the maximum permissible concentrations according to national and international guidelines. In soil, As (1.50–2.82 mg/kg) and Cd (1.22–1.45 mg/kg) levels were also above the international recommended thresholds, which are 1.00 mg/kg and 0.34 mg/kg, respectively. These elements showed fold-changes ranging from 1.5 to 4.2 above the FAO/WHO safety limits. In contrast, according to Ecuadorian legislation As was within the permitted levels (5.00 mg/kg), whereas Cd exceeded the established threshold (0.50 mg/kg). Altogether these elements showed a lower fold-change due to their higher permissible limits established in Ecuador. Furthermore, Cr (24.28–26.12 mg/kg) concentrations marginally exceeded the national regulatory thresholds in both localities, while Pb levels remained the permissible limits defined by both guidelines. As shown, the irrigation water samples presented a greater compliance issue, with average concentrations of As, Pb, and Cr exceeding the permissible limits and higher fold-changes, while the soil samples showed more localized exceedances including As, Cd, and Cr. These breaches confirmed that contaminated irrigation water represents a major pathway for heavy metal accumulation in crops. These contamination patterns have been shown in rice crops across Asia, Africa, and Latin America, causing soil contamination and phytotoxic effects, reducing plant growth and soil microbial activity [47]. Thus, implementing effective measures to reduce contamination and safeguard irrigation water quality is therefore essential for ensuring food safety and sustainable agricultural practices [48].

4.3. Bioaccumulation and Translocation of as and Pb from Soil to Rice Plants

The data presented in Table 2 revealed key insights into the bioaccumulation and translocation behavior of heavy metals (As, Cd, Pb, and Cr) in rice plants from the Daule and Ventanas. According to the thresholds, a bioaccumulation factor (BAF) greater than 1 indicates that the plant is accumulating metals efficiently from the soil, while a translocation factor (TF) above 1 suggests active movement of metals from roots to the aerial parts of the plant [26]. In both locations, As showed BAF values well above 1, especially in Daule (3.02), denoting a strong accumulation capacity in the root system. Meanwhile, Pb presented a moderate BAF value in Daule (1.50), and a higher value in Ventanas (2.42), indicating notable accumulation in both regions. In contrast, Cd and Cr consistently exhibited BAF values below 1 in both areas, suggesting a limited uptake from the soil and likely low mobility across the plant. Regarding translocation factors, the data suggest that Pb is the most mobile element within the plant. In particular, the TF values of the aerial parts from Daule exceeded the threshold of 1, indicating a high risk of Pb movement from roots to stems and leaves, and increasing the likelihood of accumulation in edible parts. On the other hand, As, Cd, and Cr showed TF values well below 1 in both areas, implying that these metals tend to remain confined within the roots with minimal redistribution. In general, bioaccumulation analysis showed that rice plants accumulate heavy metals, especially in its roots, whereas the translocation data suggest the presence of intrinsic physiological barriers in plants that restrict the movement of heavy metals from roots [49]. These results highlight As and Pb as metals of concern due to their efficient bioaccumulation and high translocation, especially in Daule, which may pose a greater threat to food safety.

4.4. Trace Levels of Heavy Metals Detected in Commercial Rice

According to Table 3, the levels of As, Cd and Pb were predominant in the commercial polished rice grains from Daule, while the levels of Cr were predominant in Ventanas. Similar values have been described for the content of Cd (0.02 mg/kg) and Pb (0.10 mg/kg) in rice grains from the province of Guayas with metal concentrations under maximum international permissible limits [32]. In contrast, the content of Cr was lower than the value of 0.5 mg/kg described for a pool of rice grains collected from different provinces of Ecuador including Guayas and Los Rios [7]. Additionally, the content of As in both areas was higher that the content reported for commercial rice samples from Guayas (0.17 mg/kg) and Los Rios (0.26 mg/kg) [22]. The occurrence of As could be attributed to the continuous application of phosphate fertilizers, which contribute not only As but also other heavy metals such as Cd, Cr, Hg, Ni, and Pb as these fertilizers are derived from phosphate rock naturally enriched with such inorganic elements [32,50]. These data provided implications into As distribution, highlighting the need to understand its relationship with soil and irrigation water in both provinces. According to the Codex Alimentarius and NIOSH, the average content of As (0.68–0.92 mg/kg) in commercial grains from both provinces exceeded the permissible levels of 0.20 mg/kg, whereas the average content of Cd (0.02 mg/kg), Pb (0.10–0.17 mg/kg) and Cr (0.08–0.27 mg/kg) were within the international established thresholds, which are 0.20 mg/kg, 0.40 mg/kg and 1.00 mg/kg, respectively [21]. In summary, these findings should be interpreted as preliminary insights rather than definitive conclusions. In summary, these findings should be interpreted as preliminary insights rather than definitive conclusions.
In general, the present study suggests potential environmental and health risks due to prolonged exposure and uptake of these heavy metals in rice agrosystems, underscoring the need for continuous monitoring, and mitigation strategies in these assessed rice-producing areas. In this context, it is important to highlight the concentration of all assessed heavy metals in root samples, as rice roots possess the ability to navigate and tolerate soil areas with elevated metal levels. This adaptive capacity is driven by a series of chemical signaling pathways, including the production of reactive oxygen species through specific oxidase enzymes and the modulation of plant hormones such as auxins, which together enable differential root growth in heterogeneous soil conditions [51]. Due to the systemic movement of heavy metals from soil to rice plants through the roots, posing health risks to consumers [52]. Accordingly, it is essential to review and establish maximum allowable limits for As and Cd in rice. For instance, in Thailand, heavy metal monitoring revealed levels below the threshold limit of 1.00 mg/kg across all rice varieties cultivated by farmers [53]. Given the potential health risks associated with the accumulation of these elements, their regulation is of critical importance [54].
For future research, it is important to consider the age of the plant and its developmental stages, since metal uptake can vary throughout its life cycle. Since protective proteins such as Oryza sativa Heavy Metal ATPase 3 (OsHMA3) can be evaluated, understanding their mechanisms of action may enable researchers to develop strategies for modifying this protein or engineering plants with enhanced capacity to sequester or remove heavy metals as Cd [55]. Also, spatiotemporal analysis can provide valuable insights for crop monitoring and risk assessment because the bioaccumulation and translocation of these elements varied depending on the metal and geographic the location [51]. Furthermore, it is imperative to determine the origin of these elements, whether from the soil or from organic or inorganic fertilizers [56]. This information is crucial for developing effective mitigation strategies to reduce heavy metal accumulation in rice crops. Finally, it is essential that local authorities prioritize food safety by implementing measures to ensure that crops intended for human consumption are free from contaminants that could pose risks to public health [57].

5. Conclusions

This study reveals significant heavy metal contamination patterns in rice agrosystems from Daule and Ventanas, with distinct spatial and elemental variations that pose varying degrees of environmental and food safety risks.
On the whole, Cr showed the highest soil concentrations in Daule (26.12 mg/kg), with significant root accumulation in Ventanas (21.30 mg/kg), suggesting localized industrial contamination sources and historical metal accumulation in agricultural ecosystems. As demonstrated a clear concentration gradient from water (0.85–1.12 mg/kg) to soil (1.50–2.82 mg/kg) to roots (3.30–4.53 mg/kg), with subsequent decreasing levels in stems (0.95–1.42 mg/kg) and leaves (0.67–1.28 mg/kg), indicating controlled mobility within the plant system despite detectable soil presence in both provinces. Cd presented the most concerning risk profile (1.22–1.45 mg/kg), with soil concentrations exceeding the national and international safety thresholds, denoting a significant degree of contamination, and creating significant plant uptake risks despite limited redistribution to aerial plant parts. In contrast, Pb levels in soil (1.20–1.23 mg/kg) as well irrigation water (0.25–0.38 mg/kg) remained within the tolerable levels established by the national and international guidelines.
As and Pb exhibited the highest degrees of bioaccumulation (BAF > 1) in plant roots of Daule and Ventanas, respectively, suggesting a strong affinity for uptake and retention in underground tissues. Only Pb revealed mobility (TF > 1) within the plant samples from Daule, indicating a potential for its transfer from roots to stems and leaves, and an elevated risk of accumulation in edible plant tissues. Furthermore, preliminary insights about the presence of As in commercial polished rice grains acquired in the same rice-producing areas were exposed.
These results provide additional data regarding previous studies conducted in these important rice fields and suggest that soil acts as a primary reservoir of heavy metals introduced through geological contamination or polluted irrigation water, which are subsequently absorbed by the roots of rice plants. Therefore, these findings underscore the need to establish stricter local limits for heavy metals in rice agrosystems and to develop targeted remediation strategies focusing on Cd management and continued monitoring of anthropogenic Pb sources in irrigation systems to ensure food safety in these important rice-producing regions.

Author Contributions

Conceptualization, J.J.-C. and J.B.; methodology, K.C.V.; software, J.J.-C., F.E.-L. and I.C.-G.; validation, J.J.-C., K.C.V., F.E.-L. and I.C.-G.; formal analysis, J.J.-C., K.C.V. and J.N.-M.; investigation, J.J.-C., J.N.-M., F.E.-L. and I.C.-G.; resources, J.J.-C., K.C.V. and J.N.-M.; data curation, J.J.-C., F.E.-L. and I.C.-G.; writing—original draft preparation, J.J.-C. and J.N.-M.; writing—review and editing, I.C.-G. and S.P.-M.; visualization, J.J.-C. and I.C.-G.; supervision, J.J.-C., K.C.V. and J.N.-M.; project administration, J.J.-C. and J.B.; funding acquisition, J.J.-C. and J.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was supported by the “Universidad Politécnica Salesiana-Ecuador, Sede Guayaquil”, under a project of the “Grupo de Investigación en Aplicaciones de Biotecnología (GIAB)” research group.

Data Availability Statement

All data have been placed in the manuscript.

Acknowledgments

The authors sincerely express their gratitude to the farmers from Daule and Ventanas for generously granting access to their rice plantations, with full consent for inclusion in this acknowledgement.

Conflicts of Interest

The authors have no competing interests to declare.

Abbreviations

The following abbreviations are used in this manuscript:
ANOVAAnalysis of variance
BAFBioaccumulation Factor
FAOFood and Agriculture Organization
ICP-OSInductively Coupled Plasma Optical Emission Spectroscopy
NIOSHNational Institute for Occupational Safety and Health
OsHMA3Oryza sativa Heavy Metal ATPase 3
PLSDAPartial Least Squares-Discriminant Analysis
TFTranslocation Factor
TULSMAUnified Text of the Secondary Legislation of the Ministry of Environment
WHOWorld Health Organization

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Agronomy 15 02359 g001
Figure 1. Map of the rice-producing study areas and the corresponding sample collection points. Red markers indicate the rice fields; black markers indicate the local markets where polished grain samples were purchased.
Figure 1. Map of the rice-producing study areas and the corresponding sample collection points. Red markers indicate the rice fields; black markers indicate the local markets where polished grain samples were purchased.
Agronomy 15 02359 g001
Agronomy 15 02359 g002
Figure 2. PLS-DA biplot derived from heavy metals content detected in samples of rice agrosystems including irrigation water, soil, root, stem, and leaf, from two main producing areas in Ecuador: Daule and Ventanas. The analysis was carried out with six independent replicates (n  =  6).
Figure 2. PLS-DA biplot derived from heavy metals content detected in samples of rice agrosystems including irrigation water, soil, root, stem, and leaf, from two main producing areas in Ecuador: Daule and Ventanas. The analysis was carried out with six independent replicates (n  =  6).
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Agronomy 15 02359 g003
Figure 3. Heatmap cluster analysis of heavy metals content detected in samples of rice agrosystems including irrigation water, soil, root, stem, and leaf, from two main producing areas in Ecuador: Daule and Ventanas. The correlations coefficients were estimated based on Pearson’s distance.
Figure 3. Heatmap cluster analysis of heavy metals content detected in samples of rice agrosystems including irrigation water, soil, root, stem, and leaf, from two main producing areas in Ecuador: Daule and Ventanas. The correlations coefficients were estimated based on Pearson’s distance.
Agronomy 15 02359 g003
Table 1. Heavy metals detected in samples of rice agrosystems from two main producing areas in Ecuador: Daule and Ventanas.
Table 1. Heavy metals detected in samples of rice agrosystems from two main producing areas in Ecuador: Daule and Ventanas.
OriginSampleAsCdPbCr
DauleWater1.12 ± 0.20 c
(0.80–1.30)		ND0.38 ± 0.09 e
(0.30–0.50)		0.53 ± 0.14 d
(0.40–0.70)
Soil1.50 ± 0.31 c
(1.10–2.00)		1.45 ± 0.23 a
(1.20–1.80)		1.23 ± 0.42 bcd
(0.80–1.80)		26.12 ± 3.81 a
(21.30–30.40)
Root4.53 ± 1.12 a
(2.20–5.60)		0.88 ± 0.31 c
(0.30–1.30)		1.03 ± 0.33 d
(0.50–1.50)		13.20 ± 4.35 c
(5.20–19.80)
Stem0.95 ± 0.49 c
(0.30–1.80)		ND1.33 ± 0.20 bcd
(1.10–1.70)		2.27 ± 0.80 d
(1.50–3.90)
Leaf0.67 ± 0.26 c
(0.30–1.00)		ND1.85 ± 0.23 b
(1.60–2.20)		3.17 ± 1.32 d
(1.90–5.10)
VentanasWater0.85 ± 0.08 c
(0.80–1.00)		ND0.25 ± 0.08 e
(0.20–0.40)		0.37 ± 0.14 d
(0.20–0.60)
Soil2.82 ± 0.87 b
(2.10–4.60)		1.22 ± 0.07 ab
(1.10–1.30)		1.20 ± 0.25 cd
(0.90–1.60)		24.28 ± 1.81 ab
(21.90–27.40)
Root3.30 ± 0.80 b
(2.20–4.40)		1.17 ± 0.07 b
(1.10–1.30)		2.90 ± 0.32 a
(2.40–3.40)		21.30 ± 0.97 b
(20.20–22.50)
Stem1.42 ± 0.40 c
(1.00–2.10)		0.05 ± 0.05 d
(ND–0.10)		0.87 ± 0.33 de
(0.70–1.60)		1.92 ± 0.79 d
(1.30–3.60)
Leaf1.28 ± 0.39 c
(0.80–1.70)		ND1.70 ± 0.47 bc
(0.80–2.20)		3.53 ± 1.28 d
(1.40–5.10)
Values are presented as mean (n = 6) ± standard deviation. Values of soil, root, stem, and leaf samples are expressed in mg/kg and are reported on a dry matter basis. Values of irrigation water samples are expressed in mg/L. Minimum and maximum values (min–max) are also provided for reference. The same letter indicates values that do not differ significantly between rice samples for each metal. ND = not detected.
Table 2. Bioaccumulation (BAF) and translocation factors (TF) of heavy metals in rice agrosystems from two main producing areas in Ecuador: Daule and Ventanas.
Table 2. Bioaccumulation (BAF) and translocation factors (TF) of heavy metals in rice agrosystems from two main producing areas in Ecuador: Daule and Ventanas.
OriginMetalBioaccumulation Factor (BAF)Translocation Factor (TF)
RootStemLeafPlantStemLeafAerial
Parts
DauleAs3.020.630.444.100.210.150.36
Cd0.610.000.000.610.000.000.00
Pb0.841.081.503.421.291.793.08
Cr0.510.090.120.710.170.240.41
VentanasAs1.170.500.462.130.430.390.82
Cd0.960.040.001.000.040.000.04
Pb2.420.721.424.560.300.590.89
Cr0.880.080.151.100.080.170.26
BAF > 1 indicates higher metals uptake by plants from the soil; BAF < 1 indicates lower uptake with more metals retained in soil. TF > 1 indicates higher transfer to aerial parts; TF < 1 indicates greater retention in the roots/soil [28].
Table 3. Content of heavy metals (mg/kg) in commercial polished rice samples obtained from local markets of Daule and Ventanas.
Table 3. Content of heavy metals (mg/kg) in commercial polished rice samples obtained from local markets of Daule and Ventanas.
OriginSampleAsCdPbCr
Daulerice
grains		0.92 ± 0.94
(ND–2.50)		0.02 ± 0.04
(ND–0.10)		0.17 ± 0.09
(ND–0.30)		0.08 ± 0.04
(ND–0.10)
Ventanasrice
grains		0.68 ± 1.04
(ND–2.70)		ND0.10 ± 0.08
(ND–0.20)		0.27 ± 0.29
(0.10–0.90)
Values are presented as mean (n = 6) ± standard deviation. Values are reported on a dry matter basis. Minimum and maximum values (Min–Max) are also provided for reference. ND = not detected.
Table 4. Permissible limits of heavy metals in water and agricultural soil.
Table 4. Permissible limits of heavy metals in water and agricultural soil.
Heavy MetalFAO/WHOTULSMA
Soil
(mg/kg)		Water
(mg/L)		Soil 1
(mg/kg)		Water 2
(mg/L)
As1.000.015.000.10
Cd0.340.030.500.01
Pb81.000.0520.000.05
Cr31.000.0525.000.10
TULSMA (Ecuadorian legislation); 1 TULSMA, Book VI, annexe 2; 2 TULSMA, Book VI, annexe 1.
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MDPI and ACS Style

Jaime-Carvajal, J.; Naranjo-Morán, J.; Vinces, K.C.; Ballesteros, J.; Espinoza-Lozano, F.; Chóez-Guaranda, I.; Pérez-Martinez, S. Traceability and Heavy Metal Contamination in Agrosystems of Two Rice-Producing Areas of the Ecuadorian Coast. Agronomy 2025, 15, 2359. https://doi.org/10.3390/agronomy15102359

AMA Style

Jaime-Carvajal J, Naranjo-Morán J, Vinces KC, Ballesteros J, Espinoza-Lozano F, Chóez-Guaranda I, Pérez-Martinez S. Traceability and Heavy Metal Contamination in Agrosystems of Two Rice-Producing Areas of the Ecuadorian Coast. Agronomy. 2025; 15(10):2359. https://doi.org/10.3390/agronomy15102359

Chicago/Turabian Style

Jaime-Carvajal, Jairo, Jaime Naranjo-Morán, Kevin Cedeño Vinces, José Ballesteros, Fernando Espinoza-Lozano, Ivan Chóez-Guaranda, and Simón Pérez-Martinez. 2025. "Traceability and Heavy Metal Contamination in Agrosystems of Two Rice-Producing Areas of the Ecuadorian Coast" Agronomy 15, no. 10: 2359. https://doi.org/10.3390/agronomy15102359

APA Style

Jaime-Carvajal, J., Naranjo-Morán, J., Vinces, K. C., Ballesteros, J., Espinoza-Lozano, F., Chóez-Guaranda, I., & Pérez-Martinez, S. (2025). Traceability and Heavy Metal Contamination in Agrosystems of Two Rice-Producing Areas of the Ecuadorian Coast. Agronomy, 15(10), 2359. https://doi.org/10.3390/agronomy15102359

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