Experimental study to understand the effects of deficit irrigation in maize

Water has become an increasingly scarce resource because of the combined effects of climate change, population increase, and rising living standards putting an enormous strain on once plentiful natural resources (Shemer et al. 2023). Around 40% of people on Earth are expected to reside in river basins in extreme water stress by 2050 (AbuEltayef et al. 2023). Anthropogenic influences and climate change have led to declined water quality and quantity, affecting 2.3 billion, people living in water-scarce areas, of which 733 million are from three continents: Asia, Africa, and Latin America – as the world's population keeps growing (Hasan et al. 2023).

The UN Water (2021) has identified the agricultural sector as a significant user of water resources, using 70% of the freshwater drawn globally to irrigate just 25% of all cropland. The availability of water for agricultural production is also on a decline due to population growth and higher industrial water demand (Shemer et al. 2023). Eventually, the unscientific management of agricultural water would make the scarcity of water resources even worse (Yang et al. 2022). Global and local water and food security are facing a huge challenge due to the heavy reliance of food production on unsustainable irrigation (Rosa 2022). Crop production faces challenges due to water scarcity in many tropical sub-humid and hot semi-arid climates. Improving irrigation efficiency is essential for reducing water use in farming while preserving optimal crop yields (Levidow et al. 2014). Being the cheapest method for irrigation, the majority of irrigated land worldwide goes with surface irrigation with high deep percolation losses (Nikolaou et al. 2020). Developments in irrigation must, however, keep up with the growing global population. But with irrigated lands lost to salinization, competition for scarce supplies of high-quality irrigation water intensifying, and development expenses growing, the expansion won't be as simple as it once was (Oster & Wichelns 2003). So it is important to increase agricultural water productivity (the yield per unit of water consumed). We must study and rely on global initiatives to bring down the amount of water used in agriculture, such as mulching, saturated soil culture, rainwater collection, drip irrigation, micro irrigation, alternate wetting and drying, and groundwater replenishment (Hasan et al. 2023).

Water-efficient production of crops can be achieved with the promising and eco-friendly technique of alternate wetting and drying irrigation (AWD) (Ishfaq et al. 2020). Another technique is drip irrigation which can lower the amount of water used in agriculture and increase water productivity by delivering water directly to plant roots. This technique also maximizes yields, enhances water efficiency, and guarantees food security, by reducing runoff and percolation losses. But with obstacles like exorbitant prices and inconsistent performance due to pollution clogging prevent its common use (Greenland et al. 2018). Deficit irrigation (DI) is another efficient method, and it was first explored in the 1970s for improved productivity and to conserve water by reducing irrigation throughout the growth season (Yu et al. 2020). DI can be explained as an irrigation management method that results in crop transpiration that is less than the maximum unstressed value due to the application of insufficient water (Fereres & Villalobos 2016). Crop varieties with drought resistance are well suited for DI (Kirda 2002). For many horticultural crops, regulated irrigation has helped improve not only water productivity but also farmers' net income (Fereres et al. 2003). The optimal amount of soil moisture required for the most favourable growing conditions depends on various factors including weather conditions, soil dryness, soil hydraulic conductivity, plant growth stages, solar radiations, etc. Water stress might force plants to passively adapt to less water provided, but deficits controlled by targeted irrigation treatments can be used as an effective tool to improve crop quality and water use efficiency. However, with saline conditions, deficient irrigation is risky and may lead to increased soil salinity due to reduced leaching (Du et al. 2015). Several studies have reported that the temperature rise and elevated levels of carbon dioxide with this changing climate have a direct impact on crops by increasing the accumulation of biomass in C3 crops and decreasing the demand for water in C3 and C4 crops (Lawlor & Mitchell 1991; Challinor et al. 2009; Srivastava et al. 2021).

Usually, the amount of water retained by the plant is set by a balance between the root water uptake and transpiration through the leaves. During heavy rains or over-irrigation, water logging for a longer duration could cause damage to the root by rotting. If the availability of water is limited (under-watering) and the moisture content is below a specified limit called permanent wilting point (PWP), then the root water uptake stops and the plant will wilt (Roose & Fowler 2004). The crop water use process has two main steps: one is the evaporative loss from soil and transpiration from crops, often referred to as evapotranspiration (ET), and the other includes all losses that happen due to the redistribution of water in the soil. If irrigation is applied below ET, the crop starts using water from the soil reservoir to compensate for the deficit. Then two situations may arise. In the first case, if sufficient water is available in the soil and groundwater does not limit evaporation, consumptive use (ET) will not be affected even by reducing the amount of irrigation water. However, if soil water is insufficient to meet crop demand, growth and ET are reduced, and insufficient irrigation causes ET to decrease below its maximum potential (Fereres et al. 2003; Fereres & Soriano 2007). Therefore, determining the soil moisture to be maintained during different stages of crop period, climate, and soil is critical for economic and productive agriculture planning.

Soil water content is measured through volumetric moisture content (VMC) and soil matric potential (SMP). VMC represents the ratio of water volume to the unit volume of soil. SMP, also known as soil tension or soil suction, indicates the forces binding water molecules to solid particles and each other in soil pores, restricting the water movement through the soil matrix. Plants have to exert a force greater than the matric potential to extract water from the soil, and this force increases as the soil becomes drier when water is held more strongly to the soil (Datta et al. 2017).

The relation between the two parameters, VMC and SMP is non-linear, and the majority of VMC changes occur within SMP values of 0–300 kPa. Beyond 300 kPa, the soil becomes excessively dry for the roots of many plants, and the VMC changes per unit change in SMP are significantly smaller. This relationship can be plotted as a characteristic curve known as the soil water retention curve (Datta et al. 2017).

Water stress affects the plant growth and alters root/shoot ratio, resulting in a notable reduction in leaf enlargement when leaf water potential (LWP) falls below −2 bars, coming to a complete halt at LWP levels of −7 to −9 bars. Water stress also causes the closure of stomata, which reduces water loss and CO² exchange, thereby decreasing the level of photosynthesis. Generally, stomata are not very sensitive to changes in LWP, until a critical threshold value is reached. Even though the threshold value is not reached, the yield could be reduced by a variety of other physiological and morphological factors of the plant.

Soil water thresholds serve as specific limits that indicate water availability for plants, influencing the timing and quantity of irrigation needed for crops. Saturation is the threshold at which all pores or empty spaces between solid soil particles are filled with water. VMC at saturation varies from 30% in sandy soils to 60% in clayey soil. The SMP at saturation is less dependent on soil texture, allowing plants to readily extract water from the soil with minimal energy. Field capacity (FC) is the upper limit at which water in larger pores has been drained away by the force of gravity. FC is considered the upper threshold for irrigation management, as irrigation beyond FC is unfavorable, leading to additional water percolating to deeper layers inaccessible to roots. A typical value of SMP at FC varies from 10 kPa (−1.019 m) to 33 kPa (−3.365 m). PWP is the threshold where it becomes impossible for plants to absorb water rapidly enough to meet their water demand. At this stage the soil holds water so strongly that transpiration and other vital processes come to a halt, resulting in a reduction in crop growth and yield. PWP values depend on weather, crop, and soil type, ranging from 7% in sandy soils to 24% in clay soils. The SMP at this threshold ranges from 500 (−50.985 m) to 3,000 kPa (−305.91 m). The value of 1,500 kPa (−152.955 m) is usually considered the average SMP at PWP for most agricultural soils (Datta et al. 2017).

Real-time soil moisture measurements in the field can be obtained using various devices, including portable surface sensors, profiling tubes with or without access tubes, buried sensors, and near-real-time data derived from processed satellite data (PSD) or land surface model data (LSMD) containing soil moisture information (Evans et al. 2021).

Soil moisture deficit (SMD) represents the amount of water, expressed as the depth of water, needed to bring the soil moisture to FC. DI techniques, applied in both larger agricultural operations and smaller research projects, rely on SMD data specific to a particular crop and cultivation scenario. Recently researchers have focused more on providing actionable irrigation advisories to farmers based on this data (Evans et al. 2021).

DI pilot studies have demonstrated the effectiveness of utilizing crop water stress guidance for making informed irrigation decisions. One notable study took place on a mixed-crop farm in Bologna, Italy, during 2014–2015. High spatial resolution SMD data were derived from in situ sensors, including the cosmic ray neutron sensor (CRNS), which measures neutrons originating from cosmic rays from neutron count rates dependent on soil moisture values. The data are compared with ET estimates based on the Penman–Monteith equation and direct Eddy covariance evaporation measurements. The study calculates soil moisture at the majority of the root mass area (0–50 cm) using a weighted average from the sensors. The findings revealed that ET estimates, including crop factors, were significantly overestimated. Additionally, it was confirmed that employing new techniques to determine soil and crop water requirements could save at least 40% of water (Evans et al. 2021).

The study by Evans et al. (2021) highlighted the effectiveness of SMD for crop water stress assessment. SMD requires knowledge of soil hydrological properties, while crop water stress assessment necessitates understanding typical water requirements for various crop types during different growth stages and seasons, including wilting points and waterlogging stages. In instances where high spatial resolution soil moisture information is not readily available or there is no in situ monitoring, satellite data can be specially processed for smaller spatial extents (Evans et al. 2021). The integration of this data and predictions can assist farmers and large-scale cultivators in optimizing irrigation, reducing water resource exploitation and energy consumption, and maximizing crop productivity. This, in turn, can lead to more profitable investments in agriculture as a whole.

Crops such as cotton, maize, wheat, sunflower, sugar beet and potato can be cultivated using DI either during the full growing season or at a certain growth stage (Kirda 2002). Igbadun et al. (2008) investigated the effect of some selected irrigation schedules on the yield of irrigated maize in southwestern Tanzania and found that maximum irrigation water efficiency was achieved with DI during the vegetative growth stage. Camporese et al. (2021) conducted field experiments with uncontrolled and controlled irrigated corn fields in Veneto (Northeastern Italy) and compared the water budget terms of numerical models. It was found that any excess irrigation water applied to the uncontrolled irrigation site didn't positively impact ET. Jiao et al. (2024) studied the effects of regulated irrigation at various growth stages on maize yield and crop water productivity in a four-year field experiment conducted with spring maize under membrane drip irrigation from 2016 to 2019 in an arid region of northwest China and observed that moderate water stress maximizes crop water productivity and ensures a healthy crop growth cycle. Zhang et al. (2019) did a three-year-long study to assess the outcomes of DI on maize (Zea mays L.) in the late growth and maturity stage. The results showed that an irrigation deficit in the maturity stage is more harmful than a deficit in the late growth stage by limiting kernel development.

The response of crops on yield to water stress needs to be studied before practising DI on a large scale. From the field experimental studies, a curve can be drawn between the relative yield reduction and the relative ET reduction; and the slope of this curve known as the crop yield response factor gives an idea about the tolerance of the crop to water stress and corresponding change in yield (Garg & Dadhich 2014).

DI practices differ from traditional irrigation practices as the manager/farmer needs to have knowledge about the level of transpiration deficit that can be applied without leading to significant yield reduction (Kirda 2002). As crops vary in their growth and yield in response to water deficit, experimental studies are required to understand the effect of the magnitude of water deficit on crop growth and yield, which helps in scheduling available limited water supply over growing periods of the crop (Doorenbos & Kassam 1979).

A large amount of irrigation is utilized for maize, a globally cultivated and highly consumed cereal crop used for both feed and fuel. Consequently, we chose to study maize because inadequate or excessive irrigation can reduce its production (Liu et al. 2022).

In view of the work by Liu et al. (2022), the optimization of the DI water without any yield reduction becomes very much relevant. The present study is an attempt to optimize the DI, which will not compromise maize yield. Towards this, a series of controlled experiments are conducted to monitor the crop yield and biomass under different DI scenarios. Details of the methodology are described in the subsequent section along with the further processing of the data. The main objective of the study is to evaluate the effect of different DI methods on crops and to validate the yield response of maize under DI with the FAO guidelines.

In the comparative study, a test environment encompassing a land area of 10 m × 20 m (200 sq. m) with a general loamy sand soil composition is selected at the Indian Institute of Technology Roorkee, India. The central coordinates are approximately 29° 51′ 44.48″ N latitude and 77° 54′ 1.76″ E longitude. Three sets of experiments are conducted on soils at three random locations to assess various quantitative and qualitative soil characteristics, including bulk density, particle density, texture, saturated hydraulic conductivity, and other soil properties. Experiments using a pressure plate apparatus are conducted to get the soil water retention parameters. Saturated hydraulic conductivity is obtained from the constant head experiments using Guelph type Permeameter, particle density of the soil is obtained from the pycnometer experiment and a mechanical sieve and hydrometer are used for getting the soil texture and particle size distribution. Soil moisture levels are gauged daily (average of 3 readings) with a Profile probe (PR2/6) at 10, 20, 30, 40, 60 and 100 cm depths, while the leaf area index (LAI) is determined weekly using an AccuPAR Ceptometer. Additionally, root depth is assessed weekly by uprooting the plant and measuring it with a ruler. The weather data – including temperature, relative humidity, wind speed, precipitation, and sunshine duration – from the National Institute of Hydrology (NIH) Roorkee's weather station (situated less than 1 km from the research site), for the study period is collected.

The designated plot is divided into seven separate plots, and maize (VBL-55 Hybrid) is planted in February 2021. The study plots' dimensions and the targeted moisture content are outlined in Table 1. In plots 1 and 2, the target moisture is considered to be a little higher than the FC to incorporate other miscellaneous loss in moisture, so that the achieved moisture content will be close to FC. This controlled setup aims to facilitate a detailed analysis of the soil and crop interactions, allowing for the monitoring of moisture requirements throughout the maize crop's entire life cycle.

In this study, manure and pesticides are applied uniformly and at appropriate intervals based on site requirements. For nutrient supplementation, 0.5 kg of urea and 1 kg of di ammonium phosphate are used, and CANETOX-10CG is applied for pest control.

Each land plot is meticulously maintained, with different targeted moisture levels achieved through timely re-watering when the measured moisture drops below the assigned minimum level. Whenever the average soil moisture in the root zone goes below the targeted soil moisture, irrigation requirements for the specific plot are supplied to bring back the soil moisture to the FC. Flood irrigation supplied through a pipe is used for irrigation. The discharge through the irrigation supply pipe is measured prior to the supply on each irrigation day and the flow is regulated by altering the water supply timing for each plot.

The growth and yield of maize (VBL-55 Hybrid) are closely observed and recorded, along with soil moisture levels at various depths in the seven plots throughout the crop period, from February 2021 to June 2021. This comprehensive approach aims to monitor the impact of soil moisture variations on plant development and productivity, taking into account the influence of weather conditions and the applied agricultural inputs.

The study operates under several key assumptions to simplify and streamline the research process:

• 1. Temperature and sunlight: Zenith Angle, Solar Exposure, and Thermal Radiation are assumed to be uniform for all plots.

• 2. Precipitation and wind: The extent of rainfall, fog, and wind speed is generalized for the entire area based on local weather data.

• 3. Relative humidity: Dry Bulb Temperature (DBT), Wet Bulb Temperature (WBT), Wind speed, and Direction are considered uniform across the study area.

• 4. Soil characteristics: Physical and chemical properties such as soil manure, pH, salinity, electrical conductivity, soil type, grain size, porosity, texture, and water retention are assumed to be uniform and homogeneous.

• 5. Soil subsurface and surrounding layers: Subsurface and surrounding layers up to 3 feet in depth are assumed to be homogeneous and uniformly absorbing, with ideal water retention trends.

• 6. Crop/Seed (VBL55 hybrid maize seed) characteristics: Seed quality, variety, mutations, and other growth defects are regarded as uniform and minimum.

• 7. Insect/pest and rodent infestation: Infestation levels are assumed to be minimal across all areas, and the pesticide CANETOX-10CG is used to control infestation levels on a timely basis.

• 8. Hysteresis in soil water retention: This study does not consider hysteresis on the soil water retention curve during wetting and drying events.

• 9. Water losses: Miscellaneous soil moisture losses due to wind and other thermal changes are assumed to be uniform for all plots.

These assumptions help to simplify the study for a more focused analysis of the specific factors under investigation by acknowledging certain generalizations and limitations in the research scope.

The months during which the crop exhibits ideal growth in terms of leaf area, root growth, and yield, considering both soil and weather conditions, are also identified. The tracking and implementation of the optimal moisture content level for ideal yield during the crop period are crucial components of the study. This involves maintaining targeted moisture levels through strategic watering intervals, ensuring that the soil conditions are conducive to the different stages of the crop period. Integrating data on soil moisture, weather conditions, and crop growth enables the identification of patterns and correlations, providing insights into the relationship between these factors. Ultimately, the study offers comprehensive findings and recommendations for irrigation practices, aiming to enhance crop yield and profitable agricultural productivity.

Maximum root depth RD is observed in plot 1, followed by plot 2 and plot 6; the biomass weight is observed to be maximum in plot 2, followed by plot 1 and plot 6 and the highest crop productivity is observed from plot 2. Plot 1 and plot 6 gave almost similar yields of 1.9 kg/sq. m after the highest yield of 2.59 kg from plot 2. Almost similar yield could be achieved because of the compensated root water uptake from the root zone, to manage the plant water requirement.

The achieved moisture content in the majority of the plots was observed to be lower than the targeted moisture content by 2–3% on average and the plot targeted for the lowest moisture content showed only a 1% difference in the achieved moisture content (Table 2).

It is observed that the general trend of actual ET is similar to the trend of rate of depletion in soil moisture in all the plots. The actual ET is observed to be the highest during the development and maturation stage in all plots when compared to the initial and end stages of the crop period.

The DI methodology applied in the study proves the effectiveness of irrigation management in plot maintained at a moisture level of 13%, producing a maximum yield of 2.59 kg/m², maximum LAI of 3.09, and 7.16 kg/m² biomass among all the seven plots under study.

The average moisture level over a depth of 0–30 cm in the other plots (in the order of 7, 4, 5, 6, 1) displayed a positively proportional increase in the root depth with reference to the increase in moisture content in the soil. The average moisture level for a depth of 0–30 cm in the other plots (in the order of 7, 4, 5, 6, 1) displayed a positively proportional increase in the yield and biomass with reference to the rise in moisture content in the soil. Average soil moisture is observed to be the highest at the initial stage, gradually decreasing and steeply depleting when the crop undergoes water stresses due to the starting of crop development, leaf area increases gradually initially and increases sharply during the maturation stage, confirming low water uptake during the sowing season, high water demand during the development stage and maturation stage.

The variation of moisture depletion at different depths indicates a non-linear root water uptake pattern. The root depth turns maximum to absorb more water from the deeper layers to compensate for the rapid increase in water demand at the start of leaf enlargement and stabilizes at a stage when the required supply is adequately taken in the development stage.

The yield response factor obtained from the water deficit experimental study is 1.41 and is found close to the FAO reported value of 1.25. This indicates that the tolerance of maize grown in Indian conditions under DI is showing similar sensitivity on yield to the water stress as reported from different water DI experiments at the flowering stage, reported in Smith & Steduto (2012).

Hence, for sustainable yield production, an average moisture content of 13% in the root zone could be recommended as the optimum moisture content to be maintained on the field for water-effective agricultural practices for maize in similar soil and climate zone areas. In this study, different plots were separated by field bunds only which is a limitation of the study, partitions with impermeable materials can be used below ground in between the plots for more precise moisture monitoring. Similar experimental studies on different crops under different seasons can also be conducted to understand their sensitivity of yield to water stress and to identify the minimum moisture condition to be maintained during DI. Numerical modelling can be done to understand the soil moisture pattern at different depths and to estimate the root water uptake during the crop period.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.