Iodine-Enriched Urea Enhances Maize Tolerance to Water Deficit via Modulation of Pigments and Sugars

Abstract

Water deficit (WD) impairs maize growth, but the application of beneficial elements such as iodine (I) has shown potential to mitigate WD. Nevertheless, strategies for incorporating I into the soil are still needed. In this context, the present study incorporated I into urea (I-enriched urea) at different I rates (0, 750, 1500, and 3000 g I hectare⁻¹) and evaluated its potential to alleviate WD in maize plants. For this purpose, maize plants were grown in Oxisol samples under simulated WD conditions and compared with plants grown without water limitation. Several parameters were evaluated during and after the stress period, including physiological parameters, pigment content, antioxidant activity, levels of compatible osmolytes, shoot dry matter, and shoot nitrogen (N) accumulation. Under WD conditions, the application of 1500 and 3000 g I hectare⁻¹ via I-enriched urea, compared with no I application, increased the leaf electron transport rate and relative water content (RWC) while reducing membrane damage. These responses were directly associated with increased chlorophyll a, b, and total contents, and with lower levels of catalase and phenolic compounds. This effect also resulted in reduced superoxide dismutase (SOD) levels after the stress period. Moreover, in the first evaluation of irrigated plants, I-enriched urea promoted greater N uptake, increasing N accumulation in the shoot. Thus, the use of I-enriched urea at I application rates of 1500 and 3000 g I hectare⁻¹ proved to be a promising strategy for mitigating WD. The results shown here have future implications that need validation under field conditions. Still, they suggest that I-enriched urea may be a viable agronomic approach to increase maize tolerance to WD and has high potential for integration into nutritional management strategies in environments subject to drought or irregular rainfall during maize growth.

1. Introduction

Maize is one of the world’s staple crops, with high yield potential due to its C₄ photosynthetic mechanism [1]. The global maize cultivation area is estimated at 197 million hectares [2]. Despite this yield potential, several biotic and abiotic factors can compromise maize production [3,4,5]. Maize’s high sensitivity to abiotic stresses is attributed to its low leaf plasticity and prolificacy, as well as its limited capacity for adequate compensation [6,7,8,9].

Among the abiotic factors that affect maize production, those related to water deficit (WD) have become increasingly frequent, primarily due to the impacts of global climate change [4,9,10]. During WD, plants alter their metabolism, often reducing stomatal opening, thereby limiting carbon dioxide (CO₂) uptake and carbon fixation in leaves. In addition, leaf tissue dehydrates [11,12]. However, plants can counteract these adverse effects by producing osmolytes, including nucleic acids, proteins, sugars, and amino acids, which help maintain cellular turgor [9,13,14,15].

One effect of WD and stomatal closure is that, when light energy is converted into chemical energy in the absence of sufficient CO₂ input into the leaf, excess energy that is not dissipated accumulates, promoting the formation of reactive oxygen species (ROS), which can subsequently lead to oxidative stress in chloroplasts, membrane lipids, and essential proteins [11,12]. However, to counteract ROS damage, plants can activate their antioxidant system, which includes enzymatic and non-enzymatic components, thereby promoting ROS detoxification [16,17,18,19,20]. Another mechanism that plants may develop under stress conditions is an increase in chlorophyll and pigment content in leaves to protect the photosynthetic reaction center [16,19].

Several strategies have been employed to improve plant resistance to WD, including the exogenous application of osmoprotectants, signaling molecules, and beneficial elements. These compounds can modulate plant metabolism, thereby enhancing stress tolerance [6,19,21,22,23]. Among these beneficial elements, iodine (I) has shown promising results, with recent studies demonstrating that its soil application increases crop tolerance to WD in coffee, soybean, and tomato [18,19,24]. Iodine can modulate plant metabolism in several ways, including increasing pigment levels (chlorophylls and carotenoids), stimulating antioxidant activity, and altering carbohydrate and other compatible osmolyte metabolism. These metabolic adjustments reduce ROS formation and, consequently, lipid peroxidation [18,19,21,25].

The beneficial effect of soil-applied I depends on the rate used; however, it is generally achieved at relatively low rates, around 3000 g I hectare⁻¹ [18,19]. Given the low application rate across a large area, practical implementation of this technology may pose challenges. Nonetheless, several studies have shown that beneficial elements can be applied in small amounts through fertilizers typically used at rates of kg hectare⁻¹, such as urea [26]. Recent studies have shown that low I rates can be incorporated into urea to reduce nitrogen (N) losses through volatilization [27]. This technology, in addition to improving N use efficiency, may also be a promising strategy for applying small amounts of I to the soil to mitigate WD.

In this context, we hypothesize that incorporating I into urea is a promising strategy to mitigate WD, with I exerting an I-rate-dependent effect that may modulate distinct metabolic pathways in the plant. The aims of this study were: (I) to evaluate whether incorporating I into urea is an effective strategy to mitigate WD; (II) to determine the appropriate I rate to incorporate into urea for WD mitigation; (III) to elucidate the physiological mechanisms involved in WD mitigation through iodine-enriched urea; and (IV) to assess the dual effect of I incorporation into urea on WD mitigation and on the improvement of N use efficiency from urea.

2. Results

In the results section, the evaluation of maize plants is divided into two phases: during the stress period and after the stress period, with one plant evaluated in each phase, resulting in separate analyses without comparison between the periods. This separation was made because the plants were at different phenological stages, and it would not be appropriate to compare them. This separation serves only to compare the effects of the treatments evaluated during and after maize stress. At each time point mentioned (during the stress period and after the stress period), the effect of plant irrigation (plants under WD versus irrigated plants) and the rates of iodine incorporated into the urea were compared, evaluating the interaction of these factors and comparing the treatments according to the absence or presence of this interaction. When there was interaction between the factors, the levels of one factor were compared across each level of the other factor.

It is important to clarify that the following explanation refers only to irrigated plants. These plants were not exposed to WD at any time during the experiment. Therefore, the expressions “during the stress period” and “after the stress period,” when used in reference to irrigated plants, do not imply that they experienced stress. Instead, these terms correspond to the same phenological stages established for the water-deficit treatment. For irrigated plants, these collection times represent only equivalent developmental stages and were adopted strictly as temporal reference points to standardize evaluations and facilitate interpretation of the results. This terminology does not imply that irrigated plants were submitted to stress, nor does it indicate a temporal comparison between phases for these plants.

2.1. Oxidative Damage, Membrane Damage, and Relative Water Content

For hydrogen peroxide (H₂O₂) content, there was an interaction between the factors studied (water conditions × I rates) during the stress period at the 5% significance level (p < 0.05). Figure 1A shows H₂O₂ content during the stress period in maize plants. Plants grown under WD during the stress period, regardless of the I rate used, showed no significant differences among treatments, with a mean H₂O₂ concentration of 0.70 mmol g⁻¹ FW. In irrigated plants during the stress period, 0 and 750 g I hectare⁻¹ resulted in the highest H₂O₂ content, with a mean of 0.83 mmol H₂O₂ g⁻¹ FW, which was 23.3% higher than at 1500 and 3000 g I hectare⁻¹ (Figure 1A). Also, during the stress period, comparing irrigated plants with those grown under WD at 0 g I hectare⁻¹ and 1500 g I hectare⁻¹, there were no differences in H₂O₂ content between these conditions, with values of 0.75 and 0.67 mmol H₂O₂ g⁻¹ FW, respectively. However, at 750 g I hectare⁻¹, the H₂O₂ content increased by 19.8% in the irrigated group compared with WD, and the opposite effect was observed at 3000 g I hectare⁻¹, where the H₂O₂ content increased by 13.7% under WD compared with irrigated plants (Figure 1A). For H₂O₂ content evaluated after the stress period, there was also an interaction between the factors studied (p < 0.05). Under irrigated conditions after the stress period, 0 g I hectare⁻¹ had the highest H₂O₂ content (0.90 mmol H₂O₂ g⁻¹ FW), with an increase of 80.8% compared with 750, 1500, and 3000 g I hectare⁻¹ (Figure 1B). Also, after the stress period, when plants were grown under WD, 3000 g I hectare⁻¹ had the highest H₂O₂ content (0.73 mmol H₂O₂ g⁻¹ FW), an increase of 18.9, 15.4, and 7.4% higher compared with 0, 750, and 1500 g I hectare⁻¹, respectively (Figure 1B).

Figure 1.

Effect of iodine (I) rate on hydrogen peroxide (H₂O₂) content, malondialdehyde (MDA) content, relative water content, and membrane damage during and after the stress period under different irrigation conditions. (A) Hydrogen peroxide content during the stress period—H₂O₂. (B) Hydrogen peroxide content after the stress period—H₂O₂. (C) Malondialdehyde content during the stress period—MDA. (D) Malondialdehyde content after the stress period—MDA. (E) Relative water content in leaf during the stress period. (F) Membrane damage during the stress period. Equal capital letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹) according to Duncan’s mean test (p > 0.05) within each irrigation condition. Equal lowercase letters indicate non-significant differences between irrigation conditions (irrigated plants and plants under water deficit) by F-test (p > 0.05) within each I rate. Error bars represent the treatment means and their respective standard errors (n = 4).

Malondialdehyde (MDA) content measured during the stress period revealed an interaction between the factors studied (p < 0.05). In plants under WD, 0 and 1500 g I hectare⁻¹ were statistically similar (15.56 nmol MDA g⁻¹ FW), 750 g I hectare⁻¹ had the lowest levels (10.71 nmol MDA g⁻¹ FW), and 3000 g I hectare⁻¹ was statistically similar to 0, 750, and 1500 g I hectare⁻¹ (Figure 1C). In irrigated plants, 0 g I hectare⁻¹ had the highest MDA value (15.23 nmol MDA g⁻¹ FW), with the mean 21.2% higher than at 750, 1500, and 3000 g I hectare⁻¹. Regarding I rates, irrigated plants and those under WD did not differ at 0 and 750 g I hectare⁻¹ during the stress period. At 1500 and 3000 g I hectare⁻¹, higher MDA values were observed under WD than under irrigated conditions, with increases of 55.9% and 47.1%, respectively (Figure 1C).

For MDA content measured after the stress period, an interaction between the studied factors was also observed (p < 0.05). In Figure 1D, MDA content after the stress period did not differ significantly among irrigated plants (mean of 15.48 nmol MDA g⁻¹ FW). Under WD after the stress period, 750, 1500, and 3000 g I hectare⁻¹ yielded similar results (mean of 19.23 nmol MDA g⁻¹ FW), with the mean at 70.9% of that at 0 g I hectare⁻¹. Plants grown under WD increased MDA content by 32.2% and 26.7% compared with irrigated plants at 1500 and 3000 g I hectare⁻¹, respectively (Figure 1D). However, at 0 g I hectare⁻¹, MDA content increased by 69.0% in irrigated plants compared with WD, whereas at 750 g I hectare⁻¹, there was no statistically significant difference between these conditions.

There was an interaction between the factors studied for relative water content (RWC) during the stress period (p < 0.05). In Figure 1E, RWC during the stress period is shown for irrigated plants and plants under WD. Under irrigated conditions, there was no statistically significant difference among I rates, with a mean of 99.0%. For plants grown under WD during the stress period, 0 g I hectare⁻¹ had the lowest RWC (82.5%), which was 10.9, 12.9, and 12.8% lower than at 750, 1500, and 3000 g I hectare⁻¹, respectively (Figure 1E). Regardless of the I rate, irrigated plants had higher RWC than plants grown under WD, with increases of 15.3, 8.1, 6.2, and 5.7% at 0, 750, 1500, and 3000 g I hectare⁻¹, respectively.

There was an interaction between the factors studied for membrane damage during the stress period (p < 0.05). The irrigated conditions showed no statistically significant difference in membrane damage, regardless of the I rate (mean 19.1%), during the stress period (Figure 1F). For plants grown under WD, 0, and 750 g I hectare⁻¹, the means were statistically similar at 39.5%, which was 46.9% higher than at 1500 and 3000 g I hectare⁻¹. Compared with WD, irrigated plants showed 46.8% and 50.3% increases in membrane damage at 0 and 750 g I hectare⁻¹, respectively (Figure 1F). At 1500 and 3000 g I hectare⁻¹, no statistical difference was observed between irrigation conditions evaluated during the stress period (Figure 1F).

2.2. FV:FM and ETR

In Figure 2A, the maximum quantum efficiency of PSII (Fv:Fm) during the stress period in plants under WD showed no statistically significant differences among I rates (p > 0.05). During the stress period, the electron transport rate (ETR) in plants under WD showed statistically significant differences between treatments (p < 0.05), with 3000 g I hectare⁻¹ being the highest, 29% higher than 0, 750, and 1500 g I hectare⁻¹ (Figure 2B).

Figure 2.

Effect of iodine (I) rate on physiological parameters under different irrigation conditions during and after the stress period. (A) Maximum quantum efficiency of PSII during the stress period (Fv:Fm); (B) electron transport rate during the stress period (ETR). Equal letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹) according to Duncan’s mean test (p > 0.05). Error bars represent the treatment means and their respective standard errors (n = 4).

2.3. Photosynthetic Pigments

For the chlorophyll a content evaluated during the stress period, there was an interaction between the factors studied (p < 0.05). As shown in Figure 3A, the chlorophyll a content during the stress period among irrigated treatments (0, 750, and 1500 g I hectare⁻¹) was statistically similar (mean of 1.50 mg g⁻¹ FW), with a mean 30.7% higher than at 3000 g I hectare⁻¹. For plants grown under WD, 750, 1500, and 3000 g I hectare⁻¹ yielded similar results, with a mean of 1.13 mg g⁻¹ FW, which was 31.9% higher than at 0 g I hectare⁻¹. During the stress period, at 0, 750, and 1500 g hectare⁻¹, a decrease of 44.7, 30.9, and 21.3% in chlorophyll a content was observed in WD-cultivated plants compared with irrigated plants. However, at 3000 g I hectare⁻¹, there were no statistical differences between WD and irrigated plants.

Figure 3.

Effect of iodine (I) rate on chlorophyll content under different irrigation conditions during and after the stress period. (A) Chlorophyll a during the stress period. (B) Chlorophyll a after the stress period. (C) Chlorophyll b during the stress period. (D) Chlorophyll b after the stress period. (E) Total chlorophyll during the stress period. (F) Total chlorophyll after the stress period. Equal capital letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹) according to Duncan’s mean test (p > 0.05) within each irrigation condition. Equal lowercase letters indicate non-significant differences between irrigation conditions (Irrigated plants and plants under water deficit) by F-test (p > 0.05) within each I rate. Error bars represent the treatment means and their respective standard errors (n = 4).

When chlorophyll a content was evaluated after the stress period, there was no interaction between the factors studied (p > 0.05), with only the irrigation condition effect being observed (p < 0.05). Chlorophyll a content after the stress period was not influenced by the I rates studied, regardless of whether the plants were irrigated or grown under WD, with mean values of 1.07 and 0.79 mg g⁻¹ FW for irrigated plants and those under WD, respectively (Figure 3B). Plants under WD compared with irrigated plants showed lower chlorophyll a content of 29.1, 30.2, 21.9, and 14.7%, respectively, at 0, 750, 1500, and 3000 g I hectare⁻¹ (Figure 3B).

For the chlorophyll b content evaluated during the stress period, there was an interaction between the factors studied (p < 0.05). As shown in Figure 3C, the chlorophyll b content during the stress period among irrigated treatments (0, 750, and 1500 g I hectare⁻¹) was statistically similar (mean of 1.55 mg g⁻¹ FW), with a mean 36.2% higher than at 3000 g I hectare⁻¹. For plants under WD, 750, 1500, and 3000 g I hectare⁻¹ yielded similar results, with a mean of 1.05 mg g⁻¹ FW, which was 56.0% higher than at 0 g I hectare⁻¹. In 0, 750, and 1500 g hectare⁻¹ during the stress period, a decrease of 66.5, 34.6, and 27.4% in chlorophyll b content was observed in plants cultivated under WD compared with irrigated plants. However, at 3000 g I hectare⁻¹, there were no statistical differences between WD and irrigated plants.

When chlorophyll b content was evaluated after the stress period, there was no interaction between the factors studied (p > 0.05), with isolated effects of the irrigation conditions (p < 0.05) and the I rates (p < 0.05). The chlorophyll b content after the stress period was increased by 3000 g I hectare⁻¹ compared with the other I rates, regardless of irrigation condition, yielding values of 1.08 and 0.83 mg g⁻¹ FW for irrigated and WD plants, respectively (Figure 3D). Also, after the stress period, regardless of the I rate applied, there was a reduction in chlorophyll b content in plants grown under WD compared with irrigated plants, with decreases of 30.0%, 33.6%, 28.7%, and 23.1% at 0, 750, 1500, and 3000 g I hectare⁻¹, respectively.

During the stress period, total chlorophyll content showed a significant interaction among the factors studied (p < 0.05). As shown in Figure 3E, the total chlorophyll content during the stress period among irrigated treatments (0, 750, and 1500 g I hectare⁻¹) was statistically similar (mean of 3.15 mg g⁻¹ FW), with a mean 33.8% higher than at 3000 g I hectare⁻¹. For plants under WD, 750, 1500, and 3000 g I hectare⁻¹ yielded similar results, with a mean of 2.16 mg g⁻¹ FW, which was 43.7% higher than at 0 g I hectare⁻¹. In 0, 750, and 1500 g hectare⁻¹ during the stress period, a decrease of 54.4, 33.8, and 24.6% in total chlorophyll content was observed in plants cultivated under WD compared with irrigated plants. However, at 3000 g I hectare⁻¹, there was no statistical difference between plants grown under WD and irrigated plants.

For total chlorophyll content measured after the stress period, there was no interaction between the factors studied (p > 0.05), with isolated effects of irrigation conditions (p < 0.05) and I rates (p < 0.05). Total chlorophyll content after the stress period increased by 3000 g I hectare⁻¹ compared with the other I rates, regardless of irrigation condition, resulting in increases of 29.1% and 14.9% for irrigated plants and plants grown under WD, respectively (Figure 3F). Also, after the stress period, regardless of the I rate, total chlorophyll content was lower in plants grown under WD than in irrigated plants, with decreases of 29.8%, 31.8%, 25.1%, and 15.5% at 0, 750, 1500, and 3000 g I hectare⁻¹, respectively.

2.4. Antioxidant System Activity

There was an interaction between the factors studied for superoxide dismutase (SOD) activity during the stress period (p < 0.05). In irrigated plants during the stress period, 1500 g I hectare⁻¹ had the highest SOD activity (47.97 U mg⁻¹ protein min⁻¹), with a mean of 50.28%, compared with 0, 750, and 3000 g I hectare⁻¹ (Figure 4A). In plants grown under WD, the I rates did not show statistical differences, with a mean SOD activity of 13.35 U mg⁻¹ protein min⁻¹. Irrigated plants showed increases in SOD activity of 46.5, 56.7, and 69.9% compared with plants grown under WD at 0, 750, and 1500 g I hectare⁻¹ (Figure 4A). Also, there was an interaction between the factors studied for SOD activity evaluated after the stress period (p < 0.05). In irrigated plants, after the stress period, 1500 g I hectare⁻¹ showed the highest SOD activity (U mg⁻¹ protein min⁻¹), which was 34% higher than 0, 750, and 3000 g I hectare⁻¹ (Figure 4B). Among plants grown under WD during the stress period, 0 g I hectare⁻¹ showed the highest SOD activity (U mg⁻¹ protein min⁻¹), which was 34% higher than 750, 1500, and 3000 g I hectare⁻¹ (Figure 4B). Irrigated plants showed 23% and 34% higher SOD activity than WD plants at 750 and 1500 g I hectare⁻¹, respectively, after the stress period. However, at 0 g I hectare⁻¹, plants under WD showed an increase in SOD activity of 23% compared with irrigated plants (Figure 4B).

Figure 4.

Effect of iodine (I) rate on the activities of oxidative enzymes during and after the stress period, under different irrigation conditions. (A) Superoxide dismutase activity during the stress period (SOD). (B) Superoxide dismutase activity after the stress period (SOD). (C) Catalase activity during the stress period (CAT). (D) Catalase activity after the stress period (CAT). Equal capital letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹), according to Duncan’s mean test (p > 0.05) within each irrigation condition. Equal lowercase letters indicate non-significant differences between irrigation conditions (irrigated plants and plants under water deficit) by F-test (p > 0.05) within each I rate. Error bars represent the treatment means and their respective standard errors (n = 4).

There was an interaction between the factors studied for catalase (CAT) activity, evaluated during the stress period (p < 0.05). In Figure 4C, the CAT activity during the stress period in maize plants was shown. Among the treatments under WD during the stress period, 0 and 3000 g I hectare⁻¹ were statistically similar (0.36 nmol H₂O₂ mg⁻¹ protein min⁻¹), with a mean of 71.04% compared with 750 and 1500 g I hectare⁻¹. In relation to irrigated plants during the stress period, 0 g I hectare⁻¹ showed the highest CAT activity, which was 69.8% higher than 750, 1500, and 3000 g I hectare⁻¹. Irrigated plants compared with plants under WD, regardless of the I rates applied, 0, 750, 1500, and 3000 g I hectare⁻¹, had lower CAT activity, a reduction of 63.4, 73.2, 65.8, and 85.5%, respectively, to 0, 750, 1500, and 3000 g I hectare⁻¹. Also, there was an interaction between the factors studied for CAT activity, evaluated after the stress period (p < 0.05). It was shown that the irrigated plants after the stress period exhibited the highest CAT activity (0.058 nmol H₂O₂ mg⁻¹ protein min⁻¹) at 0, 1500, and 3000 g I hectare⁻¹, which was 79.5% higher than at 750 g I hectare⁻¹ (Figure 4D). It was also observed that, at 3000 g I hectare⁻¹, plants cultivated under WD increased CAT activity by 31.5% compared with irrigated plants.

2.5. Compatible Osmolytes

There was no interaction between the factors studied on total phenolic compounds during the stress period (p > 0.05), with an effect observed only for the irrigation condition (p < 0.05). Regardless of irrigation conditions, there were no statistical differences in I rates for total phenolic compounds, with means of 0.11 and 0.14 mg g⁻¹ FW for irrigated plants and WD-treated plants during the stress period, respectively (Figure 5A). In relation to irrigation conditions during the stress period, plants under WD had higher total phenolic compound content than irrigated plants, with increases of 54.3%, 49.4%, 8.6%, and 9.6% at 0, 750, 1500, and 3000 g I hectare⁻¹, respectively.

Figure 5.

Effect of iodine (I) rate on compatible osmolytes during and after the stress period under different irrigation conditions. (A) Total phenolics during the stress period. (B) Total phenolics after the stress period. (C) Total soluble sugars (TSS) during the stress period. (D) Total soluble sugars (TSS) after the stress period. (E) Proline during the stress period. (F) Proline after the stress period. Equal capital letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹) according to Duncan’s mean test (p > 0.05) within each irrigation condition. Equal lowercase letters indicate non-significant differences between irrigation conditions (irrigated plants and plants under water deficit) by F-test (p > 0.05) within each I rate. Error bars represent the treatment means and their respective standard errors (n = 4).

Regarding total phenolic compounds measured after the stress period, there was a significant interaction between the factors studied (p < 0.05). For plants under WD evaluated after the stress period, I rates did not differ significantly in total phenolic compounds, with a mean of 0.11 mg g⁻¹ FW (Figure 5B). In irrigated plants evaluated after the stress period, 0 and 1500 g I hectare⁻¹ showed the highest total phenolic compound levels among I rates, with a mean of 0.12 mg g⁻¹ FW. An increase of 28.4% in total phenolic compounds was observed by plants grown under WD compared with irrigated plants evaluated after the stress period at 3000 g I hectare⁻¹ (0.11 mg g⁻¹ FW) (Figure 5B).

There was an interaction between the factors studied for total soluble sugars (TSS), evaluated during the stress period (p < 0.05). In irrigated plants evaluated during the stress period, 0 g I hectare⁻¹ had the highest TSS (121.067), which was 201.6, 103.2, and 49.7% higher than at 750, 1500, and 3000 g I hectare⁻¹, respectively (Figure 5C). In plants grown under WD evaluated during the stress period, 750 and 1500 g I hectare⁻¹ were statistically similar (115.22 mg g⁻¹ FW), increasing their content by 50.8% compared with 0 and 3000 g I hectare⁻¹ (Figure 5C). Evaluating plants during the stress period, increases of 200.7% and 84.2% were observed in WD-treated plants compared with irrigated plants at 750 and 1500 g I hectare⁻¹, respectively (Figure 5C). At 0 g I hectare⁻¹, evaluated during the stress period, plants grown under WD decreased the content of total soluble sugars by 36.5% compared with irrigated plants. Also, for TSS, there was an interaction between the factors studied, evaluated after the stress period (p < 0.05). After the stress period, the TSS was reduced at 750 and 1500 g I hectare⁻¹, regardless of the irrigation condition, compared with the treatment without I application (0 g I hectare⁻¹) (Figure 5D). Regarding the irrigation condition evaluated after the stress condition, 0, 750, and 1500 g I hectare⁻¹ did not show significant differences. However, at 3000 g I hectare⁻¹, irrigated plants showed higher levels (+55.6%) than under WD (Figure 5D).

There was no interaction between the factors studied for proline content during the stress period (p > 0.05), and only the irrigation condition tested had an effect (p < 0.05). Thus, no differences in proline content were observed among the tested I rates during the stress period (Figure 5E). An increase in proline content was observed in plants under WD compared with irrigated plants during the stress period, with increases of 32.8, 29.8, 19.0, and 13.3% for 0, 750, 1500, and 3000 g I hectare⁻¹, respectively (Figure 5E).

After the stress period, proline content showed a significant interaction among the factors studied (p < 0.05). Among plants under WD, treatments 1500 and 3000 g I hectare⁻¹ had the highest proline content (1.92 µmol proline g⁻¹ FW), exceeding that of the other treatments. In irrigated plants, 0 and 3000 g I hectare⁻¹ yielded the highest proline content (1.71 µmol proline g⁻¹ FW), compared with other I rates. Under WD, the rates of 0, 750, and 3000 g I hectare⁻¹ did not differ significantly (Figure 5F). However, at 1500 g I hectare⁻¹, proline content was 94.06% higher in plants under WD than in irrigated plants.

2.6. Biomass Production and Nitrogen Accumulation in the Shoot

There was no interaction between the factors studied for root dry matter (RDM) production during the stress period (p > 0.05), and only the isolated effect of I rates (p < 0.05) was observed. In Figure 6A, RDM was evaluated during the stress period. In irrigated plants, 0, 1500, and 3000 g I hectare⁻¹ showed higher values than 750 g I hectare⁻¹, with average increases of 39.1% and 63.4% compared to plants under WD and irrigated plants, respectively. For RDM evaluated after the stress period, there was no interaction between the factors studied (p > 0.05), nor was there an isolated effect of irrigation condition (p > 0.05) or I rates (p > 0.05) (Figure 6B).

Figure 6.

Effect of iodine (I) rate on dry matter production and nitrogen (N) accumulation under different irrigation conditions during and after the stress period. (A) Root dry matter during the stress period. (B) Root dry matter after the stress period. (C) Shoot dry matter during the stress period. (D) Shoot dry matter after the stress period. (E) N accumulation in the shoot during the stress period. (F) N accumulation in the shoot after the stress period. Equal capital letters indicate non-significant differences among I rates (0, 750, 1500, and 3000 g I hectare⁻¹) according to Duncan’s mean test (p > 0.05) within each irrigation condition. Equal lowercase letters indicate non-significant differences between irrigation conditions (irrigated plants and plants under water deficit) by F-test (p > 0.05) within each I rate. Error bars represent the treatment means and their respective standard errors (n = 4). NS: No significant difference.

There was an interaction between the factors studied for shoot dry matter (SDM) during the stress period (p < 0.05). During the stress period, SDM did not differ among I rates for plants grown under WD, with a mean of 2.27 g pot⁻¹ (Figure 6C). In irrigated plants evaluated during the stress period, the 3000 g I hectare⁻¹ treatment had the highest value, 46.0% higher than the 0, 750, and 1500 g I hectare⁻¹ treatments. There was no interaction between the factors studied in the SDM evaluated after the stress period (p > 0.05), with only an isolated effect of irrigation condition (p < 0.05). An increase in SDM was observed in irrigated plants compared to plants under WD, regardless of the I rate (Figure 6D).

There was an interaction between the factors studied for N accumulation in the shoot during the stress period (p < 0.05). There was no difference in N accumulation in the shoot for plants under WD during the stress period (Figure 6E). However, under irrigated conditions, N accumulation in the shoot increased with the highest I rate (3000 g I hectare⁻¹), resulting in a 58% increase compared with the other treatments (Figure 6E). For N accumulation in the shoot evaluated after the stress period, there was no interaction between the factors (p > 0.05), and only the irrigation condition showed an effect (p < 0.05). In the evaluation conducted after the stress period, only the irrigation condition influenced N accumulation, with irrigated plants accumulating more N than those under WD (Figure 6F).

2.7. Multivariate Analysis

Principal components 1 and 2 (PC1 + PC2) explained 54.1% of the variation in plants grown under WD during the stress period (Figure 7). For the plants cultivated under WD and evaluated during the stress period, a positive relationship was observed among the phenolic compounds, CAT activity, MDA content, H₂O₂, proline, and membrane damage (Figure 7). These variables were favored by the absence of I application. In contrast, these variables were negatively correlated with a set of variables that included RWC in plants, chlorophyll a, b, and total chlorophyll levels, TSS, and the Fv:Fm ratio. These latter variables were positively influenced by treatments involving different I rates. Total dry matter (RDM and TDM) and shoot N accumulation were positively correlated and were minimally affected by the other variables and the I rates studied.

Figure 7.

Principal component analysis of the effects of iodine (I) rates on plants under water deficit, evaluated during the stress period. Total soluble solids (TSS); malondialdehyde (MDA); hydrogen peroxide (H₂O₂); Relative water content (RWC); Total dry matter production (TDM); Root dry matter production (RDM); shoot dry matter production (SDM); nitrogen accumulation in the shoot (N in shoot); chlorophyll a (Chl a); chlorophyll b (Chl b); total chlorophyll (Chl T); photosynthetic quantum efficiency II (Fv:Fm); electron transport rate through PSII (ETR); catalase (CAT); superoxide dismutase (SOD); proline; total phenolic compounds (phenolics). Confidence ellipses are shower for each treatment, following the same color pattern as the applied I rate, as highlighted in the figure′s internal legend.

3. Discussion

Compared with unstressed plants, WD significantly stressed maize plants, resulting in increased H₂O₂ and lipid peroxidation (MDA) levels (Figure 1). When WD occurs, oxidative stress intensifies, leading to increased membrane damage and reduced RWC, thereby promoting a loss of cell growth and integrity [7,28,29]. This effect is directly related to the deleterious effects of WD, which include a marked reduction in photosynthetic pigments, thereby limiting the conversion of light energy into chemical energy through photosynthesis, and, consequently, limiting plant production [7,30,31]. In our study, the reduction of these pigments was directly associated with a decrease in SDM and in N accumulated in the maize shoot (Figure 6). However, the application of I incorporated into urea demonstrated potential to partially mitigate the effects of WD, increasing the RWC and photosynthetic efficiency due to changes in metabolism compared with no I application.

Although I is not considered a nutrient, several studies have shown its potential as a beneficial element, reducing damage caused by different types of stress, with effects dependent on the source, concentration used, and plant species [18,19,24,25,32,33]. Despite its potential, one difficulty encountered is finding an effective application method, as the low rates applied to the soil fail to produce a beneficial effect [19]. However, incorporating I into fertilizers such as urea has shown promise, as urea is applied in large amounts (kg ha⁻¹) to the soil, allowing I to promote changes in plant metabolism [27].

This beneficial effect of I, when incorporated into urea, was observed in our study, where the higher I rates (1500 and 3000 g I hectare⁻¹), particularly the higher rate, mitigated WD by reducing membrane damage and increasing RWC during the stress period (Figure 1). This beneficial effect involves several mechanisms, one of which is an increase in enzymatic antioxidant activity (SOD during a stress period), which enhances ROS detoxification, thereby reducing oxidative damage to membranes and photosynthetic pigments. SOD converts the highly toxic superoxide anion (2O^2•−) into H₂O₂, which is less reactive and can subsequently be converted into H₂O and O₂ by CAT activity [12,34]. Furthermore, our results show greater CAT activity at the highest I rate (3000 g I hectare⁻¹) and during the stress period (Figure 4C). This enzyme acts under higher concentrations of H₂O₂ (Figure 1A), an interesting fact, since under the same treatment, there is less damage to the membranes (Figure 1F), demonstrating a positive effect of I in protecting the plant against damage caused by WD. Studies have indicated a role for I applied in both iodate (IO³⁻) and iodide (I⁻) forms in increasing the levels of SOD and CAT in lettuce, tomato, and coffee plants, with these enzymes playing a fundamental role in combating ROS [18,19,21,25]. In soybean plants subjected to constant I application, I promoted antioxidant enzymatic activity, which may have consequently reduced oxidative stress in soybean leaves under suboptimal WD conditions [18].

Furthermore, I contributed to maintaining higher chlorophyll levels and photosynthetic efficiency, enabling the plant to continue capturing light energy efficiently. This indicates that it partially preserved photosynthetic pigments and maintained ETR, suggesting that its application protected the photosynthetic system against photo-oxidative damage. This effect of increasing chlorophyll levels through I application is commonly reported in other studies, showing a direct relationship between increased chlorophyll levels and greater plant resilience to different types of stress [19,27]. This effect is attributed to I’s potential to participate in photosynthesis as a component of chlorophyll and to promote the synthesis of carbohydrates and proteins [19,27].

Pigments, such as chlorophylls, are crucial for photosynthesis, as they capture light energy through the photosystems and convert it into chemical energy that the plant can use for growth [35,36,37]. This direct relationship between I application via soil with KIO₃, increased chlorophyll levels, and reduced WD was observed in coffee plants grown in pots, with the optimal application of 2.5 mg dm⁻³ KIO₃ (3000 g I hectare⁻¹). Rates above this were ineffective at mitigating WD [19].

Other mechanisms involved in mitigating WD by I incorporated into urea application include the accumulation of compatible osmolytes, such as TSS, during the stress period in plants subjected to stress, as well as proline content after the stress period. Proline, an amino acid, and TSS act as compatible osmolytes, and increasing their levels can help maintain cellular turgor and stabilize proteins and membranes [38,39]. This effect on cellular turgor is evident in the higher RWC values compared with stressed plants (Figure 1). Thus, I enhanced adaptive responses to WD, thereby promoting turgor preservation and stabilizing proteins and cell membranes. Our results show that, in addition to suppressing ROS, I at a rate of 1500 g hectare⁻¹ also increases TSS (Figure 5C), which may be directly related to biomass gains (Figure 6A,C). Carbohydrates, such as TSS, can provide structural elements and substrates [40], contribute to water loss, and act as osmotic and signaling agents [41,42]. Furthermore, the proline-increasing effect observed in our study due to the application of I has also been reported in tomato plants subjected to WD, where increasing the applied I rate promoted higher proline levels, which showed a direct relationship with greater resistance of the plants to WD [24].

Thus, the mechanisms by which I mitigates WD appear to involve a combination of antioxidant and osmotic effects, leading to activation of CAT and SOD and reducing the accumulation of H₂O₂ and superoxide radicals. At the same time, the increase in proline and TSS helps maintain osmotic homeostasis and cellular integrity, while also increasing RWC and photosynthetic efficiency and reducing biomass losses. Furthermore, the preservation of photosynthetic pigments (chlorophyll content) and electron transport, as assessed via MINIPAM analyses, indicates that I applied to maize maintains photosynthesis even under WD conditions, thereby reducing the negative impacts on biomass production and maize growth.

Our results suggest that I can be used as a tool to improve tolerance to WD, acting as a modulator of the balance between antioxidant defense and the maintenance of photosynthesis. In addition to these effects, and in relation to the N accumulated in the shoot, an interesting observation was made during the shaking carried out at 37 days in the cultivation situation without stress (Figure 6), where the incorporation of I into urea at the proportion of 3000 g I hectare⁻¹ allowed an increase in N accumulated by maize. This increase in N occurs because, when N is incorporated into urea, soil urease activity decreases. This enzyme promotes the conversion of urea into ammonia by oxidizing and deactivating the thiol groups (-SH) present in urease, thereby reducing urease activity and, consequently, N volatilization and increasing its absorption by maize [27,43]. This indicates that, in addition to acting as a possible mitigator of WD, under optimal water conditions, I also acts as a modulator of N nutrition.

Thus, based on the observed data, WD initially imposed a physiological limitation on maize plants, reducing leaf water content and cell turgor, leading to stomatal closure and restricting CO₂ assimilation. This primary limitation then unbalanced the relationship between light absorption and carbon fixation, favoring excess excitation energy in the photosynthetic apparatus and resulting in the overproduction of ROS. The observed accumulation of ROS (superoxide radicals and H₂O₂) promotes oxidative damage to membranes, photosynthetic pigments, and proteins, compromising photosynthetic efficiency, RWC, and biomass accumulation in maize. In this context, the addition of I to plants via N fertilizer at the optimal rates tested acted directly on this stress pathway by modulating the antioxidant and osmotic systems, thereby enhancing these systems, which favored the detoxification of ROS, limited ROS accumulation, preserved membrane integrity, maintained chlorophyll content and electron transport, and sustained cellular hydration under WD conditions.

Despite the beneficial effect of I, further studies should be conducted on the internal ionic status of I in leaves and how this state affects the plants’ resistance to WD. This limitation also arises from the difficulty of determining I in plants, since the determination of I involves an alkaline extraction followed by reading the extract using high-precision equipment such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and many of the methodologies found in the literature, when reproduced, show low efficiency in recovering I from standard materials with certified I values.

4. Materials and Methods

4.1. Experimental Conditions

The study was conducted in a greenhouse at the Department of Soil Science (DCS) of the Federal University of Lavras (UFLA) (21°13′33.2″ S, 44°58′43.3″ W). The greenhouse provided ample space, ventilation, and a water-supply system, facilitating proper plant management. During the experiment, the greenhouse temperature was maintained at 28 °C ± 2 °C during the day and 18 °C ± 2 °C at night. Two maize (Zea mays L.) plants were cultivated in pots containing 1 kg of Oxisol (Table 1), under normal water availability (close to the field capacity of the potting mix) until the 30th day after sowing (DAS). The soil used is classified as a Latossolo Vermelho-Amarelo distrófico [44], corresponding to Ferralsols [45] and Oxisols (<4 mm) in Soil Taxonomy [46]. Before the experiment, the soil was limed to increase Ca and Mg levels and correct soil acidity.

Table 1.

Chemical, physicochemical, and soil particle size distribution of the soil used.

Attributes	Values	Method
pH in water	4.5	pH at a ratio of 1:2.5 (w/v)
Soil organic matter (g kg−1)	24.9	Walkley-Black method
Clay (g kg−1)	670	Boyoucos method
Silt (g kg−1)	130	Boyoucos method
Sand (g kg−1)	200	Boyoucos method
Exchangeable calcium2+ (cmolc kg−1)	0.4	1 mol L−1 KCl solution-soil test
Exchangeable magnesium2+ (cmolc kg−1)	0.2	1 mol L−1 KCl solution-soil test
Available phosphorus (mg kg−1)	0.4	Mehlich−1soil test
Available potassium (mg kg−1)	24.8	Mehlich−1soil test
Available zinc (mg kg−1)	0.2	Mehlich−1soil test
Available iron (mg kg−1)	38.0	Mehlich−1soil test
Available manganese (mg kg−1)	3.4	Mehlich−1soil test
Available copper (mg kg−1)	1.2	Mehlich−1soil test
Available boron (mg kg−1)	0.01	Hot-water extraction method

1 The analyses were performed using methodologies already described and appropriate for the type of soil studied [47].

Initially, 10 maize seeds were sown, and after 7 days, thinning was performed, leaving only 2 plants per pot. At planting, the following nutrient amounts were provided [48]: 135, 300, 150, 40, 0.81, 1.33, 3.66, 0.15, 5.0, and 1.55 mg kg⁻¹, respectively for nitrogen (N), phosphorus (P), potassium (K), sulfur (S), boron (B), copper (Cu), manganese (Mn), molybdenum (Mo), zinc (Zn) and iron (Fe), using the following sources: NH₄H₂PO₄, K₂SO₄, H₃BO₃, CuSO₄.5H₂O, MnSO₄.7H₂O, Na₂MoO₄, ZnSO₄.7H₂O and FeCl₃.6H₂O (reagent-grade, Synth, Diadema, São Paulo, Brazil).

4.2. Experimental Design and Treatments

At 21 DAS, urea was applied along with the treatments studied for I incorporation into urea. A dose of 150 mg kg⁻¹ of N was provided using urea (CH₄N₂O) (reagent-grade, Synth, Diadema, São Paulo, Brazil). The incorporation of I into urea was performed according to previously published protocols. In summary, the synthesis of I-enriched urea involved mixing urea with triethanolamine and I, using potassium iodate (KIO₃), along with an organic dye to confirm proper incorporation and homogenization of I into urea [27]. Different I rates (0, 750, 1500, and 3000 g I hectare⁻¹) were studied. The iodine rates used were similar to those reported in previously published articles, with rates up to 3000 g I hectare⁻¹. The authors observed that rates of 1500–3000 g I hectare⁻¹ were effective in mitigating water stress in coffee plants [19]. Based on the tested rates, one group of plants was subjected to WD, and the others were not, thus forming the second factor to be studied. Hence, the experiment was conducted in a 4 × 2 factorial design (Table 2), with 4 repetitions per treatment, totaling 32 experimental units.

Table 2.

Description of treatments used in the experiment.

Treatments	Iodine Rate (g hectare−1)	Condition
T1	0	Water deficit
T2	750	Water deficit
T3	1500	Water deficit
T4	3000	Water deficit
T5	0	Irrigated plants
T6	750	Irrigated plants
T7	1500	Irrigated plants
T8	3000	Irrigated plants

To establish field capacity, the soil water retention curve was determined. For this purpose, saturated undisturbed samples were placed under the following matric potentials: −2, −4, and −6 kPa using the Buchner funnel and −10, −33, −100, and −1500 kPa using the Richards’ Chamber [49] until drainage from each sample stopped. After the last potential, the samples were dried in a laboratory oven at 105 °C until constant weight. The samples were weighed, and their moisture readings were used to fit the water retention curve using the van Genuchten model (1980) with the Mualem restriction (m = 1 − 1/n) [50] in the R software [51].

Field capacity (FC) was determined as the moisture at −6 kPa, a value suggested for heavily weathered Oxisols, and stress was induced by maintaining plants at −1500 kPa, considered the permanent wilting point. To establish the WD treatment, regular irrigation was suspended for a group of plants on the 30th DAG until the plants entered a condition of water deficiency (7 days), which was monitored by tracking physiological parameters and weighing the pots until they approached the initial soil weight. On the final day of stress, metabolic, nutritional, and growth analyses were performed on one plant in the pot. Shortly after, the remaining plant was rehydrated and cultivated until the vegetative cycle closed. The plants were grown for 45 days in total. The retention curve data, along with the gravimetric moisture values at field capacity and near permanent wilting point, are presented in Figure 8.

Figure 8.

Gravimetric water content (g g⁻¹) (θ) in function of the matric potentials.

4.3. MINI-PAM Analysis and Biochemical Analysis

Biochemical analyses were performed on fresh mass during the stress period (for all 8 treatments) and at the end of cultivation. On the last day of the stress, fluorescence measurements were taken on fully expanded leaves using the saturation pulse method with a Portable Photosynthesis System, Mini-Pam. From the fluorescence data, the maximum quantum efficiency of Photosystem II and the apparent ETR were calculated. Following this analysis, leaves were collected. Half of the leaf blade was used to determine the RWC and membrane damage [52], and the other half was immediately placed in liquid N and stored at −80 °C. Then, one plant was removed to determine its dry mass and shoot N content. Three days after rehydration, a second leaf from the remaining maize plant was collected for biochemical analysis and stored at −80 °C. At the end of cultivation, the remaining plant was harvested to determine shoot dry mass and N content. Subsequently, the frozen samples were individually ground to a powder in liquid N and stored at −80 °C for further analyses.

Relative water content was determined in the leaf blade collected and described earlier. Ten leaf discs were collected and immediately weighed on an analytical balance to determine the fresh weight of this part of the leaf blade. The leaf discs were then placed in plastic cups with 30 mL of distilled water for saturation and kept for 24 h. After this period, excess water was removed with filter paper, and the discs were weighed again to determine the turgid weight. Following this procedure, the samples were dried in an oven at 65 °C until constant weight to determine dry matter [53].

4.4. Chlorophyll Content, Osmoprotectants, H₂O₂, and MDA

Initially, ethanol extraction was performed by adding 0.05 g of fresh and frozen tissue to microtubes. Each microtube received 350 µL of 100% ethanol and was then placed in a water bath at 70–75 °C for 20 min. The microtubes were then placed on ice to stop the reaction. After this period, the samples were centrifuged at 14,000× g and 4 °C for 5 min. The supernatant was collected, and two additional sequential extractions were performed with 80% ethanol and 50% ethanol, respectively, following the same procedure. All collected supernatants (ethanolic extract) were stored at −20 °C for future determinations [54].

Twenty-five (25) µL of the ethanolic extract was placed in microplates and mixed with 145 µL of 100% ethanol. Absorbance was measured at 663 nm, 647 nm, and 450 nm for chlorophyll a, chlorophyll b, and carotenoids, respectively. Based on the absorbance values and the fresh weight (FW) of the leaf tissues used in the extraction, the contents of chlorophyll a, chlorophyll b, and carotenoids were calculated [55].

Malondialdehyde content was measured as a marker of lipid peroxidation. For this measurement, 250 µL of the ethanolic extract and 250 µL of a solution containing 20% trichloroacetic acid and 0.5% thiobarbituric acid were added to microtubes. The microtubes were then placed in a water bath at 95 °C for 30 min. Afterward, the samples were cooled on ice and centrifuged at 3000× g for 10 min at 4 °C. Subsequently, 150 µL of the samples were pipetted in duplicate into a microplate, and absorbance was measured at 532 nm and 600 nm. MDA content was calculated from these absorbance readings [56]. In the ethanolic extract, hydrogen peroxide (H₂O₂) content was determined by reaction with potassium iodide and measurement of absorbance at 390 nm [57].

Total soluble sugars in the ethanolic extract were determined by the anthrone method [58]. For this, 10 µL of the ethanolic extract was added to a microtube along with 320 µL of distilled water and 670 µL of anthrone solution. The microtubes were placed in a water bath at 100 °C for 3 min. After cooling, duplicate absorbance readings at 620 nm were recorded.

Proline determination was also performed using the ninhydrin method. For this, 50 µL of the ethanolic extract was mixed with 100 µL of the reaction mixture (1% ninhydrin in 60% acetic acid and 20% ethanol). The samples were then incubated in a water bath at 95 °C for 20 min. After cooling, the samples were centrifuged for 1 min at 2500× g, and absorbance was measured at 520 nm. Total phenolic compounds were determined by the Folin–Ciocalteu method [59].

Protein extraction was performed from the pellet formed after ethanol extraction and removal of the supernatant. For this extraction, 350 µL of 100% ethanol was added to the microtube containing the pellet. The samples were centrifuged at 14,000× g and 4 °C for 10 min; the supernatant was then discarded. The samples were centrifuged again for 5 min to remove any residual alcohol. After that, 400 µL of 0.1 mmol L⁻¹ NaOH solution was added to the pellet, and the samples were incubated in a water bath at 75–80 °C for 60 min. After cooling, protein quantification was performed using the Bradford method [60].

4.5. Antioxidant Activity

Extraction of enzymes from the antioxidant system (SOD and CAT) involved macerating 0.20 g of fresh mass in liquid N, then adding 1.5 mL of a buffered solution (0.1 mol L⁻¹ potassium phosphate, pH 7.8; 0.1 mol L⁻¹ ethylenediaminetetraacetic acid, pH 7.0; 0.5 mol L⁻¹ dithiothreitol; 0.1 mol L⁻¹ phenylmethylsulfonyl fluoride; 1 mmol L⁻¹ ascorbic acid; and 22 mg of PVPP). The supernatant was collected after centrifugation at 13,000× g for 10 min at 4 °C [61]. The supernatant was then analyzed in a microplate spectrophotometer (Epoch, BioTek, Winooski, VT, USA) using the recommended methods for SOD and CAT [62,63].

4.6. Biomass Production and Nitrogen Accumulation

After collecting the physiological data described above at the first sampling and at the end of the experiment, plants from each experimental unit were harvested, separated into shoot and root, and dried at 60 °C (until a constant weight was reached) to determine SDM and RDM. Total dry matter was calculated as the sum of SDM and RDM. This variable was used only in the multivariate analysis. From the collected shoot tissue (SDM), a representative sample was taken to determine N concentration by digesting the sample with sulfuric acid, then distilling and titrating the digest [64]. Nitrogen accumulation in the shoot (mg N pot⁻¹) was calculated by multiplying SDM (g of dry matter pot⁻¹) by the corresponding N concentration in the shoot tissue (mg N g⁻¹ dry matter).

4.7. Statistical Analysis

All statistical analyses were performed in R 4.5.0 [51] using the packages stats, plotrix, agricolae, factoextra, and FactoMineR [51,65,66,67,68]. Treatments were compared using Duncan’s test (p < 0.05), considering the interaction between the studied factors, after meeting the basic assumptions of analysis of variance (normality, homoscedasticity, additivity, and independence of residuals) and achieving significance in the F-test (p < 0.05). To evaluate relationships among variables in a multidimensional manner for stressed plants during the stress phase, a PCA was performed, highlighting which variables were favored by the treatments studied.

5. Conclusions

The incorporation of I into urea at a rate of 3000 g I hectare⁻¹ proved to be an effective strategy for increasing N use efficiency in maize in the short term and potentially mitigating the adverse effects of WD in maize plants by integrating different aspects of plant metabolism, including the enzymatic and non-enzymatic antioxidant systems, osmotic control, and photosynthetic adjustment. It was shown that I promoted increased cellular integrity in plants subjected to WD, thereby favoring the accumulation of osmolytes, such as proline and total soluble sugars, which help maintain cell turgor. Furthermore, I application increased chlorophyll levels during WD, which, together with the previously mentioned mechanism, improved maize photosynthetic performance, directly impacting iodine’s potential for WD mitigation. Thus, our results, as well as those of several others, indicate that iodine acts as a beneficial element that modulates antioxidant and osmotic metabolism under WD and simultaneously optimizes nitrogen nutrition under favorable growth conditions.

Author Contributions

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

Data Availability Statement

The data supporting this study’s findings are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the study’s design; the collection, analysis, or interpretation of data; manuscript writing; or the decision to publish the results.

Funding Statement

This research was funded by the Coordination for the Improvement of Higher Education Personnel (CAPES) (Grant Code-001); the National Council for Scientific and Technological Development (CNPq), via grant number #153474/2024-6; and the National Institute of Science and Technology (INCT) on Soil and Food Security, CNPq grant #406577/2022-6.