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Article

Competition of Palmer Amaranth and Corn Under Different Irrigation Regimes

by
Filiz Erbaş
1,*,
Safiye Pınar Tunalı
2,
Mehmet Nedim Doğan
1 and
Talih Gürbüz
3
1
Department of Plant Protection, Aydın Adnan Menderes University, 09070 Aydın, Türkiye
2
Department of Biosystems Engineering, Aydın Adnan Menderes University, 09070 Aydın, Türkiye
3
Department of Park and Garden Plants, Aydın Adnan Menderes University, 09070 Aydın, Türkiye
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(8), 1941; https://doi.org/10.3390/agronomy15081941
Submission received: 16 July 2025 / Revised: 8 August 2025 / Accepted: 11 August 2025 / Published: 12 August 2025
(This article belongs to the Section Weed Science and Weed Management)

Abstract

Water stress and weed competition emerge as pivotal stressors during the development of corn. This two-year study evaluated the effect of Amaranthus palmeri (AMAPA) on corn at varying densities (1, 2, and 4 plants per m−1) under two different irrigation (full and deficit) regimes. Water use efficiency and leaf water potential values were evaluated to determine the effects of different irrigation water amounts and AMAPA densities on corn water consumption. AMAPA height and fresh weight were also measured along with corn growth parameters. The results indicated that corn height, first ear height and number of rows in corn ear decreased by 14.5%, 22.1% and 9.47% on average with the effect of deficit irrigation compared to full irrigation. Under the pressure of four AMAPA plants, ear diameter, ear length, number of grains in a row of ears, ear weight and grain yield decreased by 10.7%, 22.4%, 26.3%, 43.0% and 43.1% on average compared to monoculture corn. Deficit irrigation increased water use efficiency values, while AMAPA density decreased these values. While this study demonstrated that a reduction in irrigation and an increase in AMAPA density exerted adverse effects on the growth parameters of corn, it was also observed that under deficit irrigation conditions, AMAPA did not demonstrate superiority over corn, which possesses a high degree of competitive power in comparison to other C3 summer crops.

1. Introduction

The Aegean region of Türkiye is distinguished by its high level of agricultural production, which is notable for its intensity and diversity. Corn, a significant agricultural product in the region, accounts for 24.5% of Türkiye’s total production [1]. However, a considerable portion of Türkiye’s territory is currently experiencing high water stress levels, which are categorized as high or extremely high [2]. This prompts further inquiry into the competitive dynamics among weeds and corn under conditions of water stress. Weed interference during the entire season can result in a yield reduction of over 40% for corn in this region [3]. Palmer amaranth (Amaranthus palmeri S. Wats. (Bayer Code = AMAPA)) is one of these weeds that causes significant agricultural yield losses in different global ecoregions [4]. It was documented in Türkiye in 2016 [5]. This species, characterized by its notably high invasive capacity in certain regions, has demonstrated a rapid and extensive dispersal pattern across Europe, Asia, Australia, and the western regions of North America [6]. AMAPA is among the most significant weed species in agricultural areas, particularly in the United States, and has been documented to cause severe damage to cotton, corn, and soybeans in the Southern US [7]. AMAPA has also demonstrated a notable capacity to develop resistance to various modes of action, such as EPSPS, ALS, PPO, VLCFA, PSII, HPPD, microtubule assembly, glutamine synthetase inhibitors, and auxin mimics (Group 4) [8], which has resulted in an increase in its competitive ability and invasion capacity. In Türkiye, it has been reported to exhibit resistance to EPSPS and ALS inhibitor herbicides, further complicating its management [9]
AMAPA is distinguished by its accelerated growth rate and its ability to accumulate substantial amounts of biomass [10], a trait that often confers a competitive advantage in relation to cultivated plants. In some studies, it was ascertained that when AMAPA was allowed to compete with crop plants, it caused significant yield losses [11,12]. As the density of AMAPA increased from 0.5 to 8 per meter in corn, the decrease in corn yield increased from 11% to 91%, and the water use efficiency of corn also decreased [13]. It has been determined that the presence of AMAPA in cotton results in a reduction in the relative water content of the soil up to 1 m depth. Notwithstanding the presence of ample water resources, AMAPA exhibited a significantly higher rate of water uptake compared to cotton, with values of 1.2 and 0.49 g H2O cm−2 d−1, respectively [14].
In the Aegean Region of Türkiye, the availability of irrigation water poses an important problem for summer crop cultivation during the hot and dry summer months [15]. The sporadic limitations on agricultural irrigation water during the summer months in our region have underscored the importance of conducting studies about weed–crop dynamics. Corn and AMAPA are both classified as C4 plant species [16], indicating their ability to efficiently utilize water resources. However, water stress and weed competition emerge as pivotal stressors during the development of corn [17]. Diaheliotropism, the adaptation exhibited by AMAPA, enables it to achieve optimal growth and hastens the completion of its life cycle prior to the advent of deleterious environmental conditions, including drought or elevated temperatures [18]. The present study was designed on the assumption that AMAPA would demonstrate superiority over corn, particularly in conditions of hydric stress. Therefore, we evaluated the effect of AMAPA on corn yield parameters at varying densities under two different irrigation regimes. The study is significant in terms of evaluating the potential effects of AMAPA on corn in the coming years under increasing drought stress.

2. Materials and Methods

2.1. The Data of the Experimental Area

Field studies were conducted at the Research and Application Farm of Aydın Adnan Menderes University’s Faculty of Agriculture (37°45′38″ N, 27°45′37″ E), spanning two corn growing seasons, from 2022 to 2024. The properties of the soil at a depth of 0–25 cm, which contains 48.2% sand, 34.3% silt, and 17.5% clay, are presented in Table 1.
The experimental area was fertilized with 15-15-15 NPK (Manufacturer: Gübretaş/Türkiye) at a rate of 500 kg ha−1 prior to planting.

2.2. The Design of the Study

The experimental design employed a split-plot configuration, which entailed the division of the primary irrigationtreatment plots (full and deficit irrigation) into five randomized subplots with four replications. The sub-plots consisted of plots where AMAPA was planted in conjunction with corn at 0, 1, 2, and 4 plants per meter, and plots where only AMAPA was planted one plant per m−1. In field trials, the Kurmez LF (Manufacturer: Rayal Tarım/Türkiye) variety of grain corn seeds was planted with an inter-row spacing of 70 cm and an intra-row spacing of 17 cm at a depth of 3 cm by using a drill. The AMAPA seeds were planted at a depth of 1 cm by drawing a line in the same row immediately after corn planting. The dimensions of each plot are precisely specified at 2.8 m width and 5 m length, amounting to a total surface area of 14 m2. The design is configured to accommodate four rows. Drip irrigation pipes were laid after planting.
Ten days after sowing AMAPA seeds, thinning was performed according to the AMAPA density as outlined in the experimental plan. During the experimental phase, the presence of weeds other than AMAPA was manually eradicated on a weekly basis. Evaluations for corn were conducted on 10 plants positioned in the central rows of each plot, a methodological strategy employed to circumvent edge effects. Given that the experiments were conducted in areas that were naturally uninfested, AMAPA plants were harvested to prevent them from producing seeds. Therefore, the competition lasted 76 days in the first year and 69 days in the second year. Their fresh weights were recorded after cutting above-ground parts, and the AMAPA fresh weight per plant was calculated in each plot.
Corn was harvested subsequent to height measurements. A comprehensive set of data was collected, encompassing various characteristics of corn plants, including plant height, initial ear height, ear diameter, ear length, the number of rows on the ear, the number of grains in each row, ear weight and grain yield.
The dates of the applications and measurements obtained during the experimental trials are presented in Table 2.
The data regarding mean air temperature and daily total precipitation, obtained during the course of the experiments, are displayed in Figure 1.

2.3. Irrigation Practices

The irrigation was carried out using the drip irrigation method; the irrigation water required for the plots was sourced from an underground water source (deep well) in the experimental area, pumped using a submersible pump. The irrigation water was supplied to the experimental plots through 63 mm outer diameter PE latch pipes. In addition, 16 mm outer diameter polyethylene (PE) laterals were used in each plot, with one lateral per row. As a result of the infiltration tests conducted in the experimental area, laterals with 25 cm intervals and inline drippers with a dripper flow rate of 2 L/h were used. Again, 16 mm diameter valves and meters were installed for each plot, and controlled irrigation was ensured. Irrigation was carried out using the Manna-Irrigation program. Using a sensorless, software-only approach, the program, which offers site-specific irrigation recommendations, uses high-resolution, frequently updated satellite data and hyper-local weather information [19].
Irrigation subjects in the study were formed from 2 different irrigation water levels, where 100% (full irrigation) and 50% (deficit irrigation) of the irrigation water amount determined by the Manna-Irrigation program were applied in the 7-day irrigation interval. The first irrigations were initiated when 50% of the total available water was consumed at the 90 cm effective plant root depth in both programs, and the amounts of irrigation water to be applied to other subjects were determined based on the 100% irrigation level. In the experiments, initial and post-harvest soil moisture levels were determined by the gravimetric method for each 30 cm layer at a depth of 90 cm.
The following soil water balance equation was used to calculate seasonal plant water consumption values [20]:
E T = I + R + C r + D p + R f S
where ET = seasonal crop water use (evapotranspiration) (mm); I = irrigation water amount (mm); R = effective rainfall amount (mm); Cr, capillary rise (mm); Dp = deep percolation (mm); Rf = surface runoff losses (mm) and ΔS = moisture changes in the soil profile (mm). The amount of water retained in the soil profile was calculated as the difference in moisture content between the beginning and end of the plant development period. Capillary rise, deep percolation, and surface runoff losses are assumed to be zero in DI method applications [21].
To compare different irrigation water amounts, water use efficiency values were used. Water use efficiency values, also expressed as the water utilization rate, were calculated with the help of the equations given below, which are expressed as the ratio of the efficiency values obtained for each irrigation subject to the seasonal plant water consumption and the applied irrigation water [22]. Accordingly,
W U E g = Y / E T
I W U E g = Y / I
where WUEg = grain yield water use efficiency (kg ha−1), IWUEg = grain yield irrigation water use efficiency (kg ha−1), Y = grain yield (kg ha−1), ET = seasonal crop water consumption (mm), and I = applied irrigation water (mm).
Leaf water potential (LWP) measurements were also made using a pressure chamber device in the experiment. The measurements were made in three repetitions, one day before and one day after irrigation, at noon when the sun’s rays hit the ground perpendicularly [23]. LWP is an effective measurement for determining water stress in plants and provides important insights into plant water relations and water management. LWP values are a reliable indicator that can show whether plants have sufficient water [24].

2.4. Statistical Analysis

A general linear model/univariate procedure was used to determine the effects of factors and Duncan’s multiple range test at p ≤ 0.05 was to separate means by using IBM SPSS Statistics 21 (IBM Corp., Armonk, NY, USA).
Firstly, repeats were treated as random factors and replicates (blocks), irrigation regimes and treatments (density of AMAPA) were considered as fixed factors for examining the effects different competitive environments under two different drip-irrigation regimes on AMAPA–corn growth and irrigation parameters. However, given the significance of the interaction effect of repeat in certain cases, statistical analyses were conducted separately for each year by splitting data for repeats. Syntax editors were used to calculate corrected error terms for irrigation regimes. The results of statistical analysis are given in the Supplementary Tables. The results obtained, contingent on the AMAPA density in each irrigation regime in each year, are displayed in the figures alongside the Duncan test (p < 0.05) results.

3. Results

The results of the statistical analysis evaluating the effects of different irrigation regimes and AMAPA density on the average height and average fresh weight of AMAPA in the first and second years of the experiment are given in Table S1. The findings indicated that the main effect of irrigation regimes on AMAPA height was statistically significant in both years, while AMAPA density did not influence the mean AMAPA height. In the initial year of the study, AMAPA height exhibited a 11.2% decrease in response to deficit irrigation in comparison to full irrigation. However, this rate increased to 24.5% in the subsequent year (Figure 2).
In contrast, the impact of AMAPA density on AMAPA fresh weight exhibited a significant effect in both years, while no discernible difference was observed in AMAPA fresh weight between the irrigation regimes (Table S1). As the AMAPA density increased from one to four, the mean fresh weight of the AMAPA decreased by 77.4–82.7% in the first year and by 68.3–75.3% in the second year, compared to AMAPA grown alone. The mean fresh weight of AMAPA under the pressure of corn changed but with intraspecific competition of AMAPA, the mean fresh weight did not change statistically as AMAPA density increased and remained the same among treatments (Figure 3).
The main effect of irrigation regimes was significant in terms of corn height and first ear height. However, the main effect of AMAPA density was statistically insignificant (Table S2). Under deficit irrigation, corn height decreased by 12.6% and 16.3%, respectively, compared to full irrigation in both years (Figure 4). During the same period, the decrease in the height of the first ear of corn was 21.4% and 22.7%, respectively (Figure 5).
In terms of corn ear diameter, only AMAPA density was found to be statistically different in the first year. It was also determined that irrigation regimes did not affect corn ear diameter in either year (Table S2). In the first year, competition conditions with only four AMAPA plants resulted in statistically different corn ear diameters when irrigation was deficit or full compared to when corn was grown alone. The presence of four AMAPA plants reduced ear diameter by 16.1% compared to corn grown alone under full irrigation conditions. The same AMAPA density reduced ear diameter by 9.1% under deficit irrigation conditions (Figure 6), although it did not display a statistically significant difference in the second year.
With regard to the length of the corn ear, the findings indicated that only the effects of AMAPA density during the first year, and AMAPA density and irrigation regime during the second year were found to be significant (Table S3). In the initial year, the ear length exhibited a decline of 25.5% in full irrigation and 30.1% in deficit irrigation when compared to monoculture corn with four AMAPA densities. In the second year, ear length exhibited a 16.5% decrease under deficit irrigation compared to full irrigation, reaching statistical significance. Furthermore, the ear length in monoculture corn under full irrigation conditions was 167.6 mm, while it was shortened to 138.3 mm under competition with four AMAPA plants. While a disproportionately greater decrease was observed in competition under deficit irrigation conditions in the second year, this was not statistically significant due to the high standard error (Figure 7).
The number of rows in corn ears exhibited statistically significant differences in terms of irrigation regimes only in the second year (Table S3), with an average decrease of 11.3% in deficit irrigation compared to full irrigation (Figure 8).
The data concerning the number of grains in a row of ears revealed that the effects of all factors, with the exception of the irrigation regime in the initial year, were found to be significant (Table S3). The presence of four AMAPA plants resulted in a 30.1% decrease in the number of grains in the corn row under full irrigation conditions and a 38.4% decrease under deficit irrigation conditions in the first year. In the second year, deficit irrigation caused a 17.6% decrease in the number of grains per row of corn ears compared to full irrigation, while AMAPA density did not provide a statistically significant decrease when evaluated according to irrigation regimes (Figure 9).
The findings revealed that the irrigation regimes did not generate a statistically significant variation in ear weight in both years (Table S4). Regarding AMAPA density, it was ascertained that AMAPA densities of 2 and 4 in the initial year led to a substantial reduction in ear weight compared to cultivated in monoculture under both irrigation regimes (Figure 10). While the main effect of AMAPA density was found to be significant in the second year (Table S4), no statistical difference was observed between the treatments when evaluated based on irrigation regimes (Figure 10). However, as AMAPA density increased, ear weight decreased in both irrigation regimes.
Regarding grain yield, the effect of solely AMAPA density demonstrated statistical significance in the initial year (Table S4). Grain yield exhibited a decline ranging from 31.3% to 56.6% in conjunction with an increase in AMAPA density under full irrigation conditions. A similar trend was observed, with a decrease ranging from 21.8% to 50.3% in response to the same density increase in deficit irrigation applications (Figure 11). In the second year, these differences were not found to be statistically significant.
Seasonal plant water consumption values obtained from the experiments are given in Table 3. In full irrigation, the results for both years were higher than those for deficit irrigation, as expected. The reason why the data obtained in 2022 are higher is due to the higher amount of rainfall.
The WUEg values obtained from the experiment are given in Figure 12. Upon examination of the figure, it is evident that the WUEg values obtained from deficit irrigation applications are higher than those from full irrigation applications in both years, as expected. Additionally, it was observed that the increase in the amount of AMAPA resulted in a decrease in the WUEg values. According to the statistical results, the effect of the amount of AMAPA becomes clearer. The highest water use efficiency is observed in plots with no AMAPA, and this value is also statistically significant (Table S5). The fact that there are four AMAPA plants in the plots shows that the AMAPA density in corn has a very significant effect on water use efficiency.
As a result of the study, the IWUEg values obtained from the plots are given in Figure 13. Upon examination of the figure, it is evident that the IWUEg values obtained from deficit irrigation applications are higher than those from full irrigation applications in both years, as is the case with the WUEg values. This shows that the plant’s utilization rate from limited water resources is higher. Additionally, it was observed that the increase in the amount of AMAPA resulted in a decrease in the IWUEg values. According to the statistically significant results, there were three different classes for both full and deficit irrigation applications in the first year of the experiment, based on the amount of AMAPA. In the second year of the experiment, it was observed that three classes were formed in the plots with deficit irrigation water application, and two classes were formed in the plots with full irrigation (Table S5). The presence of four AMAPA plants in the plots had a negative effect on irrigation water use efficiency, just as it did on water use efficiency. This means that AMAPA uses a significant portion of the given water. However, unlike other agronomic findings, when both WUEg and IWUEg values are taken into account, it is also concluded that corn is more successful in water uptake under competitive conditions against AMAPA in limited irrigation water applications.
The average LWP values, one of the parameters indicating plant water status [25], are given for corn in Figure 14 and Figure 15. When the pre- and post-irrigation LWP values with different irrigation water amounts and AMAPA densities are examined in general, it is seen that the pre-irrigation values are lower than the post-irrigation values in both years. As expected, the LWP values measured in subjects with limited irrigation in both years were lower than those in subjects with full irrigation. When the AMAPA rates are considered, the highest LWP values were obtained from the plots with only corn, both before and after irrigation measurements. This situation indicates that the amount of AMAPA makes it difficult for corn to absorb the available water in the soil.
When the LWPb values in Figure 14 were statistically examined, it was determined that two distinct groups formed among the full irrigation subjects in both years. In the first year of the experiment, the LWPb values in the plots planted only with corn were in a different statistical group from those with AMAPA. In the second year, plots planted with corn and four AMAPA plants were in a separate group from the other plots (Table S6).
When the LWPa values in Figure 15 are examined, it is observed that two statistically distinct classes emerged in both irrigation applications during the first year. However, when the LWPa values in the second year of the experiment are examined, it is observed that no statistical significance is found (Table S6).

4. Discussion

Türkiye, a nation situated within the arid and semi-arid regions, faces considerable vulnerability to agricultural drought [26]. Corn is one of many crops susceptible to the impacts of drought and water stress. The effect of water scarcity on vegetative and yield characteristics of corn was found to be significant and this was primarily attributed to the absence of irrigation during the critical stages of tasseling and cob formation [27]. The present study also demonstrated that, under constant weed pressure, deficit irrigation resulted in a reduction in various growth parameters of corn at some level. Irrigation regimes caused significant differences in corn, especially in terms of plant height and first ear height in both years. In the second year of the experiment, the main effect of irrigation was also observed to be significant in terms of ear length, number of rows in the ear, and number of grains in the row. The absence of this effect in the initial year is likely attributable to the delayed onset of rainfall.
In addition to water stress, competition from weeds has been demonstrated to be a key factor affecting corn growth and development. Amaranthus palmeri (AMAPA) is one of the most troublesome weeds worldwide in this regard [6]. Depending on emergence time and density, it can cause serious yield reductions in summer crops [4]. As indicated by earlier research, these reductions are about 60% when the AMAPA density is 4 m−1 and can reach 91% when the density 8 m−1 [11]. In our study, the yield loss at the 4 AMAPA density per 1 m corn row was determined to be averagely 43% under full and deficit irrigation conditions. As the AMAPA density increased, there was a decrease in other yield parameters in general. However, statistically significant differences began to occur with 4 AMAPA density in most cases. The most important parameter, grain yield, saw a statistically significant decrease due to AMAPA density, especially in the first year, ranging from 31.3 to 56.6% in full irrigation and 21.8–50.3% in deficit irrigation. Similar trend were observed in the second year but this decrease was not statistically important (p = 0.054).
Research conducted in this region has indicated that the optimal timing for the initiation of weed control measures in corn is between the 3- and 10-leaf stages, with the objective of maximizing yield [3]. However, for weeds such as AMAPA, which exhibit high levels of competitiveness and the capacity to thrive under conditions of drought stress, the initiation of the control period may need to occur earlier and be prolonged over a more extended duration.
In this study, WUEg and IWUEg values tended to decrease as the amount of water applied and the number of AMAPAs in the plot increased, as in some other water stress studies in corn [21,28,29]. Massinga et al.’s study demonstrated that grain yield and water use efficiency of corn were reduced by Palmer amaranth competition [13]. Studies have shown a direct relationship between the amount of water supplied to plants and leaf water potential (LWP). These studies indicate that leaf water potential values decrease as the amount of water supplied to plants decreases [24,30]. Furthermore, AMAPA’s water use in the soil, beyond the cultivated plant, also leads to a decrease in LWP values in cultivated plants.
The interaction effects of irrigation regimes and AMAPA density were not found to be significant for any growth parameter value obtained. This finding indicates that the changes observed in the parameters in both irrigation regimes and different AMAPA densities exhibited similar tendencies. However, it was observed that the effect of irrigation regimes on the parameters related to the vegetative parts of the plants and the effect of weed density on the parameters related to the generative parts of corn created statistical differences. Berger et al. [14] similarly reported that, despite the absence of change in cotton stomatal conductance (an indicator of water stress), yield loss due to Palmer amaranth was still observed. Therefore, they concluded that this was due to other factors, such as competition for light or response to neighboring plants during development.
This experiment demonstrated that these two plants, planted concurrently, were unable to form a canopy that would suppress each other’s growth. As a result, both plants maintained a short stature, a phenomenon attributed exclusively to the irrigation regime. Chalal et al. [16] demonstrated in their study that the height of AMAPA decreased by 30.33% and 50.56%, respectively, when exposed to 75% and 50% of the field capacity (FC) of water, in comparison to plants receiving 100% of the FC. Under identical conditions, the reduction in above-soil weight was determined to be 27.9% and 34.7%, respectively, under 75% and 50% FC. In this study, the impact of irrigation on AMAPA height was found to exceed its effect on AMAPA fresh weight. Furthermore, AMAPA fresh weight exhibited a greater sensitivity to intraspecific and interspecific competition. Smith and Burns’ research also examined the competition between Chenopodium album and corn in pots, demonstrating that reducing water levels had a more significant impact on weed height than intraspecific or interspecific competition [31].
In summary, while this study demonstrated that a reduction in irrigation and an increase in AMAPA density exerted adverse effects on the growth parameters of corn, it was also observed that under deficit irrigation conditions, AMAPA did not demonstrate superiority over corn. This phenomenon is hypothesized to result from the fact that corn is a C4 plant, which possesses a high degree of competitive power in comparison to other C3 summer crops. In the anticipated drought conditions of the coming years, weed control in corn may be feasible through the present management of AMAPA.
It has been reported that 280 g L−1 Dimethenamid-p + 250 g L−1 Terbuthylazine (BASF Corporation, NJ, USA), 312.5 g L−1 S-Metolachlor + 187.5 g L−1 Terbuthylazine (SYNGENTA Crop Protection Ag, Switzerland) and 225 g L−1 Isoxaflutole + 90 g L−1 Thiencarbazone-Methyl + 150 g L−1 Cyprosulfamide (BAYER Ag, Germany) have over 90% effectiveness against AMAPA in corn in the pre-emergence period, and 280 g L−1 Dimethenamid-p + 250 g L−1 Terbuthylazine (BASF Corporation, NJ, USA), 330 g L−1 Terbuthylazine + 70 g L−1 Mesotrione (SYNGENTA Crop Protection Ag, Switzerland), 326 g L−1 Terbuthylazine + 50 g L−1 Mesotrione (SYNGENTA Crop Protection Ag, Switzerland) in the post-emergence period [32]. However, a salient point that merits consideration is the development of AMAPA resistance to numerous herbicides [8]. Moreover, extant research has demonstrated that AMAPA plants whose parents were exposed to water stress exhibit demonstrated diminished sensitivity to certain herbicides [33]. This may result in the emergence of herbicide-resistant individuals in subsequent growing seasons of AMAPAs grown under water stress conditions. When mechanical control is applied, it is imperative to exercise caution during the extraction process to ensure the plant is removed from the soil surface with precision. It has also been determined that plants cut 3 cm or more above the soil surface regrow and produce seeds [34].

5. Conclusions

This study indicated that the effect of irrigation regimes on the vegetative parameters of corn, and the effect of AMAPA density on the generative parameters of corn created statistical differences in general. The implementation of deficit irrigation has been shown to enhance water use efficiency, while AMAPA density has been observed to exert a negative influence on this parameter, thereby demonstrating a decrease in water use efficiency values. However, under deficit irrigation conditions, AMAPA did not demonstrate superiority over corn, which possesses a high degree of competitive power in comparison to other C3 summer crops. The utilization of drought-tolerant corn varieties has the potential to enhance the competitiveness of the crop in the face of weed competition under conditions of low soil moisture. This adaptation can serve as a stress-buffering mechanism, mitigating the adverse effects of weed competition.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy15081941/s1: Table S1: Effects of irrigation regimes and AMAPA density on AMAPA height and fresh weight, Table S2: Effects of irrigation regimes and AMAPA density on corn height, first ear height and ear diameter, Table S3: Effects of irrigation regimes and AMAPA density on corn ear length, row number of ear and grain number of ear row, Table S4: Effects of irrigation regimes and AMAPA density on corn ear weight and grain yield, Table S5: Effects of irrigation regimes and AMAPA density on WUEg and IWUEg p values; Table S6: Effects of irrigation regimes and AMAPA density on LWPb and LWPa p values.

Author Contributions

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

Funding

This research was funded by the Aydin Adnan Menderes University Scientific Research Project Coordination Unit/Türkiye (No: ADU-ZRF-22009) and partly by The Scientific and Technological Research Council of Turkey (TUBITAK 119 O 525).

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

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

Abbreviations

The following abbreviations are used in this manuscript:
AMAPAAmaranthus palmeri
USUnited States
NPKNitrogen, phosphorus, and potassium
LWPLeaf water potential
EPSPS5-Enolpyruvylshikimate-3-phosphate synthase
ALSAcetolactate synthase
PPOProtoporphyrinogen oxidase
VLCFAVery-long-chain fatty acid
PSIIPhotosystem II
HPPD4-Hydroxyphenylpyruvate dioxygenase
IIrrigation water amount (mm)
REffective rainfall amount (mm)
ΔSMoisture changes in the soil profile (mm)
ETSeasonal crop water use (Evapotranspiration) (mm)

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Figure 1. Daily total precipitation and mean air temperature data collection during experiments.
Figure 1. Daily total precipitation and mean air temperature data collection during experiments.
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Figure 2. Effects of AMAPA density under different irrigation regimes on AMAPA height (cm). Vertical bars indicate standard errors.
Figure 2. Effects of AMAPA density under different irrigation regimes on AMAPA height (cm). Vertical bars indicate standard errors.
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Figure 3. Effects of AMAPA density under different irrigation regimes on AMAPA fresh weight (g). Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan test (p < 0.05) depending on AMAPA density.
Figure 3. Effects of AMAPA density under different irrigation regimes on AMAPA fresh weight (g). Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan test (p < 0.05) depending on AMAPA density.
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Figure 4. Effects of AMAPA density under different irrigation regimes on corn mean height (cm). Vertical bars indicate standard errors.
Figure 4. Effects of AMAPA density under different irrigation regimes on corn mean height (cm). Vertical bars indicate standard errors.
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Figure 5. Effects of AMAPA density under different irrigation regimes on corn first ear height (cm). Vertical bars indicate standard errors.
Figure 5. Effects of AMAPA density under different irrigation regimes on corn first ear height (cm). Vertical bars indicate standard errors.
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Figure 6. Effects of AMAPA density under different irrigation regimes on ear diameter (mm) of corn. Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 6. Effects of AMAPA density under different irrigation regimes on ear diameter (mm) of corn. Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 7. Effects of AMAPA density under different irrigation regimes on corn ear length (mm). Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 7. Effects of AMAPA density under different irrigation regimes on corn ear length (mm). Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 8. Effects of AMAPA density under different irrigation regimes on row number of corn ear. Vertical bars indicate standard errors.
Figure 8. Effects of AMAPA density under different irrigation regimes on row number of corn ear. Vertical bars indicate standard errors.
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Figure 9. Effects of AMAPA density under different irrigation regimes on corn grain number of ear row. Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 9. Effects of AMAPA density under different irrigation regimes on corn grain number of ear row. Vertical bars indicate standard errors. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 10. Effects of AMAPA density under different irrigation regimes on corn ear weight (g). Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 10. Effects of AMAPA density under different irrigation regimes on corn ear weight (g). Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 11. Effects of AMAPA density under different irrigation regimes on corn grain yield (g). Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 11. Effects of AMAPA density under different irrigation regimes on corn grain yield (g). Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 12. Effect of AMAPA density under different irrigation regimes on WUEg. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 12. Effect of AMAPA density under different irrigation regimes on WUEg. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 13. Effect of AMAPA density under different irrigation regimes on IWUEg. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 13. Effect of AMAPA density under different irrigation regimes on IWUEg. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 14. Effect of AMAPA density under different irrigation regimes on leaf water potential before irrigation. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 14. Effect of AMAPA density under different irrigation regimes on leaf water potential before irrigation. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Figure 15. Effect of AMAPA density under different irrigation regimes on leaf water potential after irrigation. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
Figure 15. Effect of AMAPA density under different irrigation regimes on leaf water potential after irrigation. Lower case letters indicate differences between treatments according to Duncan’s test (p < 0.05) depending on AMAPA density.
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Table 1. Soil properties of experimental area.
Table 1. Soil properties of experimental area.
pHSalt
(%)
Lime
(%)
Organic Carbon (%)Total
Nitrogen (%)
CEC *
(meq/100 g Soil)
8.390.0106.890.640.0811.78
* Cation exchange capacity.
Table 2. Dates of applications and measurements during experiments.
Table 2. Dates of applications and measurements during experiments.
First ExperimentSecond Experiment
Sowing corn and AMAPA seeds22 June 20227 June 2023
AMAPA height measurement24 August 202215 August 2023
AMAPA harvest6 September 202221 August 2023
Corn height measurement and harvest20 October 202212 September 2023
Table 3. Seasonal crop water consumption values of the study.
Table 3. Seasonal crop water consumption values of the study.
YearIrrigation ApplicationI (mm) 1R (mm) 2ΔS (mm) 3ET (mm) 4
2022Full irrigation420.0046.4041.92508.32
Deficit irrigation210.0046.4078.89335.29
2023Full irrigation353.4024.0017.49394.89
Deficit irrigation176.7024.0034.70235.40
1 Irrigation water amount, 2 effective rainfall amount, 3 moisture changes in the soil profile and 4 seasonal crop water use.
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MDPI and ACS Style

Erbaş, F.; Tunalı, S.P.; Doğan, M.N.; Gürbüz, T. Competition of Palmer Amaranth and Corn Under Different Irrigation Regimes. Agronomy 2025, 15, 1941. https://doi.org/10.3390/agronomy15081941

AMA Style

Erbaş F, Tunalı SP, Doğan MN, Gürbüz T. Competition of Palmer Amaranth and Corn Under Different Irrigation Regimes. Agronomy. 2025; 15(8):1941. https://doi.org/10.3390/agronomy15081941

Chicago/Turabian Style

Erbaş, Filiz, Safiye Pınar Tunalı, Mehmet Nedim Doğan, and Talih Gürbüz. 2025. "Competition of Palmer Amaranth and Corn Under Different Irrigation Regimes" Agronomy 15, no. 8: 1941. https://doi.org/10.3390/agronomy15081941

APA Style

Erbaş, F., Tunalı, S. P., Doğan, M. N., & Gürbüz, T. (2025). Competition of Palmer Amaranth and Corn Under Different Irrigation Regimes. Agronomy, 15(8), 1941. https://doi.org/10.3390/agronomy15081941

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