Irrigated Corn Research Articles

Long-Term Effects of Nitrogen and Tillage on Yields and Nitrogen Use Efficiency in Irrigated Corn

By tonnage, corn (Zea mays L.) is the #1 crop produced globally, and recent research has suggested that no-till (NT) systems can lead to reduced yields of this important crop. Additionally, there is a lack of long-term data about the effects of tillage and N management on cropping systems. Corn is the most nitrogen (N)-fertilized crop in the USA, and N losses to the environment contribute to significant impacts on air and water quality. We conducted long-term studies on conventional tillage (CT) and conservation tillage systems, such as strip tillage (ST) and NT, under different N rates. We found that immediately after conversion to NT, yields from NT were significantly lower than yields from CT (p < 0.1), but after five years of NT, the NT yields were 1.5% higher than the CT yields (p < 0.1). Initially, the NT yields were lower than the ST (p < 0.01), but after seven years of NT, the NT yields were comparable to ST grain yields. Although the total aboveground N uptake with NT immediately after conversion to NT was lower than with CT and ST, these differences were not significant in the long run. The nitrogen use efficiency (NUE) with NT increased over time. The present work highlights the importance of long-term research for determining the cumulative impacts of best management practices such as NT. We found that NT becomes a more viable practice after five or seven years of implementation, demonstrating the high importance of long-term research.

Long‐term tillage and residue removal effects on soil carbon, nitrogen, and grain yield in irrigated corn

AbstractCorn (Zea mays L.) stover demand as a forage or for an emerging bioeconomy has increased the importance of determining the long‐term effects of stover removal on grain yield and soil properties. Study objectives were to evaluate grain yield, soil organic carbon (SOC), and total soil N (0–150 cm) in a 20‐year, irrigated, continuous corn study, located in eastern Nebraska, under conventional tillage (CT) and no‐till (NT) with variable corn stover removal rates (none, medium, and high). After 20 years, grain yield was up to 6.0% greater under NT with stover removal compared with NT and no stover removal, while yield was similar for CT in all stover removal treatments. Grain yield was similar between NT with stover removal and CT in all stover removal treatments. High stover removal rates resulted in greater SOC loss at the surface soil layers (0–15 cm and 0–30 cm) after 20 years compared with no or medium stover removal. Corn stover retention under NT resulted in the same cumulative SOC stock loss as CT or stover removal. All management practices resulted in cumulative (0–120 cm) SOC stock loss (8% decrease) that occurred in the last 10 years of the study. Total soil nitrogen stocks were maintained or increased after 20 years at the surface soil layers (0–15 cm and 0–30 cm) and were similar between NT and CT. In an irrigated continuous corn system, neither NT nor stover retention was able to maintain cumulative SOC stocks over time.

Contrasting corn acreage trends in the Midwest and Southeast: The role of yield, climate, economics, and irrigation

The US corn area footprint has changed significantly since the 20th century, declining in the southeastern states while exhibiting an increase or stable variations in the Midwest. As harvested acreage directly impacts the total corn production, understanding the influencing factors is crucial. This study assesses the role of potential drivers on the contrasting trajectories of harvested corn acreage between midwestern and southeastern US. Profit-acreage analysis reveals that antecedent profits/losses have a statistically significant influence on corn acreage changes, with southeastern US, which experienced more loss-making years, also experiencing more frequent reductions in corn acreage. The high number of loss-making years in the Southeast is primarily attributed to the region's low corn yield, influenced by climate and other agro-environmental factors. Using a panel regression model, we find that the loss-making years in the Southeast could have reduced to fewer than 26 out of the considered 45 years, or almost similar to the average in the Midwest, by just increasing the irrigated corn area to 50 %, a realistic irrigated corn area fraction already achieved in several Georgia counties. This underscores the potential for early policy interventions like irrigation facilitation to sustain and expand cropped acreage. However, we also find that this would only be economically feasible with incentives for both the installation and sustained operation of irrigation infrastructure.

Irrigated corn yield and soil phosphorus response to long‐term phosphorus fertilization

AbstractLong‐term experiments can help to understand soil phosphorus (P) dynamics and improve nutrient management strategies. This research evaluated long‐term (2002–2021) soil P dynamics and yield response to a range of P fertilizer rates in a continuous high‐yielding irrigated corn (Zea mays L.) experiment with low initial soil phosphorus test (SPT, 10.5 mg kg−1). The experiment was established near Clay Center, NE, and five P rates (0, 10, 20, 39, and 59 kg P ha−1) were evaluated. Soil samples at 20‐cm depth were collected in eight cropping seasons. Yield response to P fertilizer increased after 20 years from 0.64 to 2.79 Mg ha−1. The application of 39 kg P ha−1 year−1 increased soil Bray‐1 P to 19.5 mg kg−1, outyielded all other P treatments, and resulted in a positive relative P balance. Over 20 years, 0 kg P ha−1 year−1 decreased Bray‐1 P from 10.5 to 5.5 mg kg−1. Annual P rates of 0, 10, and 20 kg P ha−1 produced a negative relative P balance and SPT below the critical soil test value (CSTV). The CSTV was 22.2 mg kg−1 for a continuous irrigated corn cropping system. A 53% increase in the P fertilizer rate (from 39 to 59 kg P ha−1 year−1) produced a threefold increment in the soil test P build‐up rate. High‐yielding irrigated continuous corn production systems (>14 Mg ha−1) are required to apply at least 39 kg P ha−1 year−1 to maintain SPT and a positive relative P balance over years.

Explorando la eficiencia técnica de la producción agrícola en tres regiones de México

This work assesses the technical efficiency (TE) in agricultural production under irrigation of corn, alfalfa, sorghum, and plantain; the analysis is conducted for three hydrological subregions of Mexico: Río San Juan (north), Valley of Mexico (center) and Valle Bajo de Grijalva (South). The measurement was carried out by agricultural cycle (spring-summer, autumn-winter and perennial), and by land size. We use stochastic frontier analysis to corroborate whether the farmer's skills favor efficiency, with a production function that relates irrigated land as a basic element, and a set of explanatory socioeconomic variables. Despite limitations in the data, the results contribute to the knowledge of TE in Mexican agriculture. Indirectly, the contribution of irrigation is recognized, so identifying their economic relevance could help define strategies to improve agricultural production and support water management in agriculture.

Groundwater quality vs. groundwater quantity. Combining information on irrigator concerns with past water use and cropping behavior.

The effectiveness of groundwater in fulfilling crop water deficits depends on its quality and quantity. This paper examines the relationship between irrigators’ stated concerns over groundwater quality and groundwater quantity and their past water use and cropping decisions. Information on irrigator concerns over groundwater quality and quantity is obtained from 626 survey responses of agricultural producers in the Kansas portion of the High Plains Aquifer. We combine 20 years of field-level water use and cropping data with each of the 626 survey responses. We find that irrigators indicating elevated concern over either groundwater quality or groundwater quantity correlates with less total water use, fewer total irrigated acres, and fewer acres of irrigated corn. Additionally, concerns over groundwater quantity generally correlate with a greater reduction in water use along multiple water use margins compared to equal concerns over groundwater quality.

Estimating Agricultural Irrigation Water Usage in Delaware, USA

Irrigation is an important agricultural management practice and the second largest consumer of freshwater resources in Delaware. As more farmland is converted to irrigated agriculture, it is crucial that water resource managers be able to determine reasonable estimates of irrigation water usage in order to protect the resource. This study used a soil water balance approach to simulate irrigation for corn and soybeans in Delaware (USA). The simulations were divided into four scenarios to determine which irrigation management method best represents agricultural irrigation water usage in Delaware. Two scenarios utilized an evapotranspiration-based (ET-based) approach using meteorological data from the Delaware Environmental Observing System (DEOS) with a soil water availability threshold to determine when and how much to irrigate. A second set of scenarios used a calendar-based approach and a rain gauge trigger to simulate irrigation. Analyses were performed to examine the seasonal and spatial variability of irrigation in Delaware and to compare simulated irrigation data to reported water use data provided by the Delaware Department of Natural Resources and Environmental Control’s Water Allocation Permit program. Seasonal irrigation varied due to environmental as well as irrigation decision making factors. Spatially, irrigation varied primarily as a result of the soil water holding properties. The ET-based scenario with a fixed amount of irrigation had the best agreement with the reported irrigated water use data. This study demonstrated the utility of high-resolution, environmental data with a soil water balance approach to improve estimates of irrigated water usage at the state and regional scale.

Vadose zone flushing of fertilizer tracked by isotopes of water and nitrate

AbstractA substantial fraction of nitrogen (N) fertilizer applied in agricultural systems is not incorporated into crops and moves below the rooting zone as nitrate (NO3−). Understanding mechanisms for soil N retention below the rooting zone and leaching to groundwater is essential for our ability to track the fate of added N. We used dual stable isotopes of nitrate (δ15N–NO3− and δ18O–NO3−) and water (δ18O–H2O and δ2H–H2O) to understand the mechanisms driving nitrate leaching at three depths (0.8, 1.5, and 3.0 m) of an irrigated corn field sampled every 2 weeks from 2016 to 2020 in the southern Willamette Valley, Oregon, USA. Distinct periods of high nitrate concentrations with lower δ15N–NO3− values indicated that a portion of that nitrate was from recent fertilizer applications. We used a mixing model to quantify nitrate fluxes associated with recently added fertilizer N versus older, legacy soil N during these “fertilizer signal periods.” Nitrate leached below 3.0 m in these periods made up a larger proportion of the total N leached at that depth (∼52%) versus the two shallower depths (∼13%–16%), indicating preferential movement of recently applied fertilizer N through the deep soil into groundwater. Further, N associated with recent fertilizer additions leached more easily when compared to remobilized legacy N. A high volume of fall and winter precipitation may push residual fertilizer N to depth, potentially posing a larger threat to groundwater than legacy N. Optimizing fertilizer N additions could minimize fertilizer losses and reduce nitrate leaching to groundwater.

Corn Irrigation with Reduced Well Capacity

Corn Irrigation with Reduced Well Capacity

Integrating machine learning and empirical evapotranspiration modeling with DSSAT: Implications for agricultural water management

The availability of accurate reference evapotranspiration (ETo) data is crucial for developing decision support systems for optimal water resource management. This study aimed to evaluate the accuracy of three empirical models (Hargreaves-Samani (HS), Priestly-Taylor (PT), and Turc (TU)) and three machine learning models (Multiple linear regression (LR), Random Forest (RF), and Artificial Neural Network (NN)) in estimating daily ETo compared to the Penman-Monteith FAO-56 (PM) model. Long-term data from 42 weather stations in Florida were used. Moreover, the effect of ETo model selection on sweet corn irrigation water use was investigated by integrating simulated ETo data from empirical and ML models using the Decision Support System for Agrotechnology Transfer (DSSAT) model at two locations (Citra and Homestead) in Florida. Furthermore, a linear bias correction calibration technique was employed to improve the performance of empirical models. Results were consistent in that the NN and RF models outperformed the empirical models. The empirical models tended to underestimate and overestimate small and high daily ETo values, respectively, with the HS model exhibiting the least accuracy. However, calibrated PT and TU models performed comparably to the ML models. Results also revealed that using an inappropriate ETo model could lead to over-irrigation by up to 54 mm during a single crop season. Overall, ML models have proven reliable alternatives to the PM model, especially in regions with access to long-term data due to their site-independent performance. In areas without long-term data for ML model training and testing, calibrating empirical models is viable, but site-specific calibration is needed. It is important to highlight that distinct plant species exhibit varying transpiration characteristics and, consequently, have different water requirements. These differences play a pivotal role in shaping the overall impact of ETo models on crop water use.

Field evaluation and numerical simulation of water and nitrate transport in subsurface drip irrigation of corn using HYDRUS-2D

Field evaluation and numerical simulation of water and nitrate transport in subsurface drip irrigation of corn using HYDRUS-2D

Determination of effective irrigation intervals in the center pivot sprinkler system for maize (Zea mays L.) varieties

The increasing importance of the corn plant in animal nutrition as silage and grain feed has led to expand of corn cultivation in large areas. One of the best ways to meet the demand for irrigation of corn in large areas in Iraq is to establish a center pivot sprinkler system. This experimental study was carried out to determine the effective irrigation intervals in the center pivot sprinkler system in the cultivation of some corn varieties registered in Iraq in Kirkuk Governorate / Iraq in 2021. Another aim of this study is to identify the variety or varieties that have higher yields under different irrigation interval conditions. Another aim of this study was to determine the variety or varieties with higher yield under different irrigation interval conditions. The experiment was conducted in a randomized block design with three replications. Five registered maize varieties (AlFajer, AlMaha, AlSafa, Buhooth-106 and Sara) were used as experiment materials and three irrigation intervals (2, 4 and 6 day periods) were applied using the pivot sprinkler method. According to the result of this experiment, Buhooth-106 variety had the highest yield (7.23 kg ha⁻ˡ). Although the 6-day irrigation interval resulted in the lowest grain yield for all varieties, the difference in terms of corn grain yield between 4-day and 2-day irrigation interval was not found significant, statistically. In conclusion, the 4-day irrigation interval application using the center pivot irrigation system and Buhooth-106 variety can be recommended growing corn in conditions of Kirkuk Governorate of Iraq.

REMOTE SENSING AND GEOSTATISTICS APPLIED TO NDVI, KC AND PRODUCTIVE PARAMETERS IN IRRIGATED CORN CROP

Remote sensing (SR) has contributed to digital agriculture, associated with the use of geostatistical techniques that allow data acquisition, analysis and decision making. In view of this, the objective of this work was to evaluate the spatial variability of soil physical attributes, NDVI and second crop corn productivity in the territory of Santa Helena de Goiás, and to estimate values of crop coefficient (KC) through the NDVI, and to evaluate the spatiality. Soil samples were collected in a georeferenced way using a regular grid. The images were from the Sentinel 2A satellite. The Normalized Difference Vegetation Index (NDVI) was calculated, the Kc values of the crop were estimated, using two methodologies Toureiro et al., (2017) and Kamble et al. (2013), and later the values were extracted through a regular GRID, with which the geostatistical analyzes and correlations with productivity were submitted. The NDVI showed an increase up to 69 days after planting, in addition to proving the spatial variability and spatial dependence. With the geostatistics it was possible to generate a map of the spatial distribution of productivity. The NDVI allowed to obtain the Kc corresponding to the different phases of cultivation, sensitive to the methodologies used. The Kc obtained presents a high response and potential to the management of irrigated corn..

Life cycle greenhouse gas emissions for irrigated corn production in the U.S. great plains

Agricultural management practices improve crop yields to satisfy food demand of the growing population. However, these activities can have negative consequences, including the release of greenhouse gas (GHG) emissions that contribute to global climate change. To mitigate this global environmental problem, the management practices that contribute the most to system GHG emissions should be identified and targeted to mitigate emissions. Accordingly, we estimated the cradle-to-product GHG emissions of irrigated corn production under various farmer-selected scenarios at an experimental testing field in the semi-arid U.S. Great Plains. We applied a carbon footprint approach to quantify life cycle GHG emissions associated with pre-field (e.g., energy production, fertilizer production) and in-field (e.g., groundwater pumping, fertilizer application) activities within fourteen scenarios in the 2020 Oklahoma Testing Ag Performance Solutions (TAPS) sprinkler corn competition. We determined that 63% of the total GHG emission from corn production was associated with in-field activities and that agricultural soil emissions were the overall driving factor. Soil biochemical processes within agricultural soils were expected to contribute an average of 89 ± 18 g CO2-eq kg−1 corn of the total 271 ± 46 g CO2-eq kg−1 corn estimated from these systems. On-site natural gas combustion for agricultural groundwater pumping, pre-field fertilizer production, and pre-field energy production for groundwater pumping were the next most influential parameters on total GHG emissions. Diesel fuel, seed, and herbicide production had insignificant contributions to total GHG emissions from corn production. The model was most sensitive to the modeled GHG emissions from agricultural soil, which had significant uncertainty in the emission factor. Therefore, future efforts should target field measurements to better predict the contribution of direct soil emissions to total GHG emissions, particularly under different managements. In addition, identifying the optimal application rate of irrigation water and fertilizer will help to decrease GHG emissions from groundwater irrigated crops.

Perspective of the Development of Irrigated Agriculture in the Garabakh and East Zangezur Economic Regions

In the presented article, along with natural conditions, geological, geomorphological structure, climate, soil and vegetation cover, the issues of systematic use of land in agricultural development in compliance with irrigation standards are considered. The irrigated lands of Aghdam, Zangilan, Jabrayil, Fizuli, Terter, Kalbajar, Gubadli, Lachin and Shusha Districts, suitable for use under various agricultural crops, were taken as the object of study. It is planned to develop and use norms and regimes for irrigation of perennial grasses, winter cereals, grain and silage corn, vineyards and orchards, vegetables, tobacco in accordance with the soil and climatic conditions of the region and provide farms for use.

Technological proposal for a greater irrigated corn (Zea mays L.) pro-duction

O Objective: To validate the experimental results of corn (Zea mays L.) production under irrigation during the 2019-2022 autumn-winter cycles. Design/Methodology/Approach: Six validation plots were established, three in the Cuxtepeques irrigation district and three in irrigation systems in Chiapas, Mexico. Results: Corn grain production is 64% higher with the INIFAP technology than the traditional methods; however, the average yield obtained in the validation phase (11.5 t ha-1) was lower than the yield of the experimental phase (15.9 t ha-1). Study Limitations/Implications: None. Findings/Conclusions: Production requires machinery for sowing and precision fertilization, efficient irrigation infrastructure, access to credit, and permanent technical assistance to achieve yields similar to those obtained in the experiment.

Long-term numerical modeling of nitrate leaching into groundwater under surface drip irrigation of corn.

Proper management of fertigation is necessary to deal with the harmful impacts of fertilizers. This research aimed to investigate the nitrate leaching rate into groundwater in different fertigation management under the climate change impact in drip irrigation of corn. For this purpose, HYDRUS-2D was calibrated by performing field experiments. Plant water requirement and rainfall were projected until 2050 using LARS-WG6 under the RCP85 scenario. Then, nitrate leaching up to groundwater at the depth of 5m was simulated in the growing season of corn and the like until 2050 in three fertigation scenarios, including S1 (three regional fertigation splits with irrigation efficiency of 85%), S2 (weekly fertigation with irrigation efficiency of 85%), and S3 (optimum fertigation with irrigation efficiency of 100%). Finally, the annual nitrate leaching rate to groundwater and leached amount were compared in the studied scenarios. The results demonstrated that nitrate penetrated to the depth of 117 and 105cm at the end of the first year in S1 and S2 scenarios, respectively. In these scenarios, nitrate will reach groundwater in 2031, but nitrate concentrations will not be the same. In the S3 scenario, the nitrate will reach a depth of 180cm by 2050. Total leached nitrate to groundwater up to 2050 will be 1740, 1200, and zero kg/ha in S1, S2, and S3 scenarios, respectively. Based on the approach of this study, the vulnerability of groundwater to nitrate contamination in different agricultural areas can be evaluated, and appropriate strategies with minimum environmental impacts of fertilizer abuse can be selected accordingly.

Evaluating the Use of Intelligent Irrigation Systems Based on the IoT in Grain Corn Irrigation

This study was conducted to evaluate the management of smart irrigation in grain maize production (KSC 715 cultivar) at the Seed and Plant Improvement Institute (SPII) located in Karaj, Iran, in the year 2020. Irrigation was performed based on 40% moisture discharge farm capacity and was compared with irrigation based on long-term meteorological statistics that have become common in the field (drip irrigation system, type strip, and determining the irrigation time based on the apparent reaction of the plant). The experimental results showed that under the conditions of smart irrigation management, sensitive phenological stages of the plant occur earlier, and the field is ready to be harvested approximately one month earlier; moreover, 35% of irrigation water consumption can be saved. Water consumption decreased from 8839.5 to 5675.67 m3/ha; in addition, grain yield and water productivity decreased. Although the moisture stress applied in the intelligent irrigation system completed the plant phenology period faster and due to earlier harvest, irrigation water consumption was decreased by 35%, water productivity was reduced. Finally, it seems that by adjusting the drought stress application time in more tolerant stages of maize growth in future studies and experiments, it will be possible to decrease irrigation water consumption while increasing the physical productivity of water.

Effect of heat stress during anthesis on the Summer Maize grain formation: Using integrated modelling and multi-criteria GIS-based method

Dealing with high temperatures during the anthesis stage is an important factor that can affect summer maize. Here, the possibility of heat stress injury (HSI) in the summer maize-grown fields of Golestan province was investigated. A multi-criteria weighted overlay procedure was used to determine the suitability of arable land for maize cultivation. Using the CERES-Maize model and long-term meteorological data, the map of the days with Tmax > 35 °C from three days before to seven days after anthesis was provided. The results showed that the irrigated corn fields in the study area have suitable degrees for corn cultivation and different conditions in the field of HSI experience around pollination. Although most of the fields were located in highly suitable areas, probable HSI (as described by PDT35) affected the final suitability. Also, more reliable sowing dates were introduced. The results revealed that on 18th of June, maize could be sown at all suitable areas except in some arable lands of Kalaleh where the PDT35 was more than 40%. The results showed that HSI should also be considered around the pollination stage to obtain reliable results from land suitability.

Measured and simulated effects of residue removal and amelioration practices in no-till irrigated corn (Zea mays L.)

Reducing nitrous oxide (N2O) emissions to the atmosphere is expected to provide substantial climate mitigation benefits. Herein, we measured soil N2O emission and crop yield responses in a nine-year, no-till continuous corn system under contrasting management practices including irrigation (full; deficit), corn stover retention (100 % retention; maximum mechanical removal), and cover crop use (winter cereal rye, Secale cereale L.; no cover crop). Field-measured data were used to construct a structural equation model (SEMobs) to explore the causal effects of management on soil N2O emissions. We also used the Root Zone Water Quality Model 2 (RZWQM2) to simulate management effects on soil N2O emission. Structural equation modeling was used for the field-measured data (SEMobs) and the RZWQM2 simulated data (SEMsim) to quantify management relationships with soil and determine whether relationships observed in field data were captured by RZWQM2 simulations. Our experimental field results showed that stover removal decreased annual N2O emissions compared to stover retention, only for deficit irrigated soil (2.83 ± 1.31 vs. 4.49 ± 3.65 kg N ha−1 y−1) and that deficit irrigation decreased annual N2O emissions compared to full irrigation, only for soil with cover crops (3.31 ± 3.19 vs. 4.11 ± 3.80 kg N ha−1 y−1). The SEMobs and SEMsim results showed similar direction and magnitude of relationships between daily soil N2O emissions and various management and environmental drivers. Our study improved the mechanistic understanding for the effects of agricultural management on soil N2O emissions and can help reduce N2O emissions from agricultural systems.