Crop Water Use Efficiency Research Articles

Growth and Yield Response of Pea (Pisum sativum L.) Crop to Classical and Regulated Deficit Irrigation along with Nitrogen Fertilization under Drip Irrigation

Background: The conventional methods of applying water and nutrient results lot of wastage and negatively affect the soil, environment and crop response of pea. Methods: The experiments were conducted at Lovely Professional University, Punjab during two years. The five drip irrigated treatments having full irrigation, classical deficit irrigation and regulated deficit irrigation in combination same level of nitrogen fetigation @90% recommended dose of nitrogen (RDN) were taken in 4 replications. One control plot (having flood irrigation with soil application of nitrogen @100% RDN through broadcasting) was taken for comparison. Result: Plant growth, yield contributing parameters, pod yield and water use efficiency (WUE) were significantly affected by drip irrigation in combination with 90% RDN through fetigation over conventional method of irrigation and fertilizer application. Among all the drip irrigated treatments, the increment in crop yield, WUE and irrigation water saving varied from 27.6 to 65.7%, 63.6 to 99.7% and 26.1 to 44.6%, respectively over control plot. In case of same nitrogen fertigation level, the yield and water use efficiency of drip irrigated pea crop can be improved by adoption of moderate water deficit level (which is 15% less than full IWR) under regulated deficit irrigation approach over full irrigation approach. The findings of the work can be utilized by farm managers for irrigation planning and nitrogen management for pea crop and by policy makers to conserve available fresh water resources in water scares regions.

Effect of Dry Land Technologies on Water Use and Yield of Millet Crops

Preserving soil moisture is an important means to maintain the necessary water for agricultural production and also to minimize the irrigation needs of the crops. This is especially important in areas where rainwater for irrigation is scarce or decreasing due to climate change or other causes. A field trial was conducted with the Ragi crop to study the increase in infiltration rate and moisture content under subsoil and to estimate the yield and water use efficiency of the millet crop at Agricultural Engineering College & Research Institute, Kumulur. A non-replicated trial with the treatments of deep tillage with a chisel plow, coir pith application in subsoil, random tie ridging, broad bed, and furrows, straw mulching, and vetiver bunding was conducted. The average raise of moisture content, higher range (8%) was observed in the treatment of coir pith application (T2), and followed by 6% raise in deep tillage, random tied ridging broad bed furrows and straw mulching. The maximum infiltration was found to be in deep tillage (4.7 cm/hr), followed by straw mulching in the range of 4.5 cm/hr. The higher yield 1121 kg/ha and WUE 5.20 kg/ha mm was obtained in treatment T2 (coir pith application) followed by treatment T3 (random tied ridging) as 1067 kg/ha & WUE of 4.95 kg/ha mm

The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX): A Science-Based Path for Sustainable Water Management and Climate Resilience

Abstract Water scarcity threatens agriculture in California. During the last two decades, historically severe droughts have led to severe water shortages. Under projected changes in climate, droughts of greater severity and duration will exacerbate this situation. California produces 80% of the world’s almonds, which require consistent water supplies for irrigation. Almonds are the most commonly grown crop in California, covering nearly 1.4 million acres over about 8,000 farms. In response to these challenges, almond growers are considering a myriad of management strategies to save water and mitigate climate change. The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX) aims to identify water and orchard management opportunities to maximize water use efficiency and carbon sequestration in almonds and other woody perennial tree crops. The project combines satellite, uncrewed aerial vehicles, and proximal sensing technologies to retrieve key variables used to model surface fluxes and biophysical properties. We aim to advance our understanding of water management and cultural practices on water–carbon relationships in tree-perennial agroecosystems. Through new methods, such as evapotranspiration-based irrigation scheduling, even a modest 10% decrease in almond orchard irrigation across the state equates to about a third of the water in Lake Oroville, California’s second-largest reservoir, at average levels. From a carbon perspective, almond orchards could sequester 8% of the state’s current greenhouse gas emissions by transitioning toward climate-smart practices. As such, the almond industry is uniquely positioned to curb water use and contribute to climate change mitigation while maintaining economic viability of almond production. An overview of initial results related to evapotranspiration observational and modeling uncertainty and carbon sequestration potential are presented in this article.

Determinants of the accuracy of using carbon isotopes in estimating water use efficiency of selected cereal and legume crops: A global perspective

AbstractField assessments of crop water use efficiency (WUE) are resource‐consuming since they require simultaneous assessment of the total amount of water assimilated by crops for biomass and/or grain production. Alternative methods exist, such as estimating the carbon isotopic ratio (13C/12C) of the crop's leaf, aboveground biomass, or grain samples. There is limited information on the determinants of the accuracy of carbon isotopes in estimating water use efficiency between crop types and environments. Therefore, this study aimed to evaluate the extent to which the estimation of the 13C/12C ratio in crop parts constitutes an accurate proxy of WUE, globally. Data on observed WUE (WUEobs) were collated involving 518 experiments conducted worldwide on major cereals and legumes and compared with WUE estimates (WUEest) from carbon isotopes. The mean WUEobs among all experiments was 3.4 g L−1 and the mean absolute error (MAE) was 0.5 g L−1 or 14.7% of WUEobs, corresponding to accurate predictions at p < 0.05. However, the percentage mean absolute error of observed water use efficiency (%MAE) estimated from grains was 3.6 ± 11.5%, which was lower than the %MAE from aboveground biomass collected at harvest (3 ± 22.8%). In addition, the %MAE increased from 1.1 ± 5.1% for soybean, 1.6 ± 7.2% for maize, 1.2 ± 8.6% for rice, 1.8 ± 12.1% for groundnut, 2.1 ± 14.3% for cowpea, 2.3 ± 16.2% for bush bean, 1.8 ± 19.9% for wheat, 2.2 ± 21.4% for barley to 6.3 ± 39.3% for oat, with only the latter corresponding to significant errors. WUEest were, in all cases, unbiased but slightly overestimated from 0.8% (maize) to 15.4% (oat). The accuracy in estimating WUE significantly decreased with the increase in soil clay content, with sand, showing a positive correlation of 0.3 with %MAE, but negatively correlated with the silt content (r = −0.4). Furthermore, a multivariate analysis pointed out a tendency for prediction errors and bias to increase with the decrease in WUEobs and air temperature. Using carbon isotopes for estimating crop WUE thus appeared reliable for all crops and world environments, provided grain samples are considered. The technique tended to perform better under high WUE conditions, such as those generally found in maize and soybean cropping systems. The identified factors that affect the accuracy of using carbon isotopes in measuring WUE provide valuable insights for water resource management and sustainable crop production. These findings contribute to the ongoing discourse on water conservation strategies in agriculture, offering a basis for decision‐making in crop improvement programs. Implementing the recommended practices from this study can potentially improve yield gains and promote resilient and sustainable agricultural systems in the changing environmental circumstances. Further research should investigate the mechanisms that cause low accuracy of the isotopic technique using aboveground biomass and under arid and cool environments.

Multiple taxa inoculants of arbuscular mycorrhizal fungi enhanced colonization frequency, biomass production, and water use efficiency of cassava (Manihot esculenta).

Increasing water use efficiency (WUE) in crops is critical to maintaining agricultural production under climate change-exacerbated drought. One of these approaches may consist of leveraging on the beneficial interactions between crops and arbuscular mycorrhizal fungi (AMF). In this study, we investigated how inoculation with AMF from three different taxa (Claroideoglomus etunicatum (T1), Gigaspora margarita (T2), and Rhizophagus irregularis (T3)) and their combination (T123) and a non-inoculated "control" treatment in a greenhouse could achieve increased biomass production and water use efficiency in cassava under three levels of water availability (100% PC, 60%-moderate stress, and 30%-severe stress). Whereas T1 and T2 resulted in a lower growth rate for the plants than the control, T123 enhanced cassava height and the number of petioles and leaves. T123 and T3 increased the total plant dry biomass in comparison with uninoculated plants by 30% and 26%, respectively. The T123 and plants inoculated with T3 significantly increased cassava above-ground biomass by 19% as compared to T1 (8.68 ± 2.44g) and T2 (8.68 ± 2.44g) inoculated plants. T123 resulted in higher WUE, which was validated by the leaf carbon (δ13C) isotopic signature, significantly outperforming cassava with T1 and T2, yet there was no difference between the control and T3. Overall, this study demonstrated that the use of multiple AMF from different taxa can increase cassava growth and WUE under greenhouse conditions.

The impact of compost and expanded perlite on soil physical properties and water productivity under different irrigation practices

Finding an appropriate field management strategy for improving crop and water production becomes an imperious necessity because of the irrigation water deficiency in most of the agricultural fields in Iraq. Studying the response of soil properties to the applied soil amendments represents one of the critical parameters in agricultural field management for improving crop production and water use efficiency of Iraqi strategic crops. The effect of soil amendments (compost = 7.5 t/ha and perlite/0.1% Polyvinyl alcohol = 0.25 t/ha) on the water use efficiency and crop production under three levels of water depletion (30, 50, and 70%) of the available soil water was examined for wheat and barley crops. The study was applied under the sprinkler irrigation system. The experimental design was RCBD within 6 treatments and 3 replications for each wheat and barley. The results show that the soil amendments of expanded perlite and compost exhibit an improvement in the soil properties of soil bulk density and soil water content. Soil amendments, especially, the expanded perlite improved the crop yield and water use efficiency under all irrigation levels. The effect of expanded perlite shows the maximum effect on barley production under the 50% irrigation level with 3500 kg/ha. The irrigation level of 70% could be a worth-able management strategy if it is associated with the soil amendments of compost and expanded perlite. As a result, the effectiveness of expanded perlite increased with the increase in the drought of Iraqi soil.

Response of Three Barley Cultivars Hordeum vulgare L. to Water Stress Under Field Conditions

A field experiment was conducted in one of the agricultural fields located in the center of Hilla/Babylon, within latitude 32°31’ north and longitude 44°21’ east. During the season 2021-2022 in a soil with a loam silty texture. The aim of the study is to know the effect of water stress on the yield of green feed and grain and its components and the water use efficiency of the barley crop. A split-plot design with RCBD arrangement was used with three replicates. The irrigation treatments that include the comparison treatment (50% depletion of the available water) were occupied and three water depletion treatments (40, 60, 80%) of the amount of water for the control treatment, the main plot, while the cultivars occupied subplot No significant differences appeared between the control treatment and the irrigation treatment, 80% of the control treatment in the yield of green feed and grains, and thus it was possible to save water by 20% without a significant decrease from the control treatment. The irrigation treatments 80 and 60% showed higher efficiency in using water for grain production than the control treatment. The cultivars showed significant differences in yield, as Bohouth 244 gave the highest yield of feed and grain, and it did not differ significantly from cultivar IPA 99. Also, Bohouth 244 showed the best water use efficiency to produce a larger amount of grain, and it did not differ significantly from IPA 99.

Farmland Carbon and Water Exchange and Its Response to Environmental Factors in Arid Northwest China

Carbon neutrality is an important target in China’s efforts to combat the climate crisis. The implementation of carbon neutrality requires high crop yields in farmland ecosystems of arid regions. However, the responses of farmland ecosystems to environmental changes and their effects on the conversion and intensity of carbon sources/sinks within farmlands in arid regions remain unclear, which limits carbon sequestration. In this study, we used a set of eddy covariance systems to observe carbon and water fluxes in cotton and spring maize, two typical crops in arid regions of Northern Xinjiang in China. The carbon and water exchange and water use efficiency (WUE) of cotton and spring maize were evaluated over the entire growth cycle with respect to changes in the environment. Our results show that the carbon sequestration capacity of farmland ecosystems in arid regions is undeniable and is strongly influenced by the growth and development of plants. Spring maize, as a representative of C4 plants, exhibited a 58.4% higher carbon sequestration efficiency than cotton, a C3 plant, and they both reached their carbon sequestration efficiency peak in July. Throughout the growth period, temperature, net surface radiation, and saturated vapor pressure differences (VPD) significantly affected the carbon sequestration capacity and WUE of both crops. Optimal temperatures can maximize the carbon sequestration efficiency of cotton and spring maize; for cotton, they are 20–25 °C, and for spring maize, they are 22–27 °C, respectively. In addition, it is recommended that spring maize be harvested at the end of July when it meets the harvesting standards for silage feed and achieves the maximum carbon sequestration. Afterward, winter crops should be planted to maximize the yield and improve the carbon sequestration capacity of farmlands.

Using Soil Water Status Sensors to Optimize Water and Nutrient Use in Melon under Semi-Arid Conditions

Nowadays, agriculture must satisfy the growing demand for food, and increasing its sustainability, from an environmental, economic, and social point of view, is the only way to achieve this. The objective of this study was to increase the water and nutrient use efficiency of a melon crop during two consecutive seasons under commercial conditions, growing under semi-arid area. For this purpose, two treatments were studied: (i) a farmer treatment (FRM), fertigated at ~100% of crop evapotranspiration (ETc) during the whole growing season; and (ii) a precision irrigation treatment (PI), irrigated by adjusting, between flowering and ripening, the weekly farmer irrigation to minimize the leaching below the root system. The threshold for allowable soil water depletion in the active root uptake zone was set at 20–30%. The cumulative water savings in each year relative to the FRM treatment ranged between 30 and 27% for 2020 and 2021, respectively. Yield was not negatively affected, with no differences in fruit load (fruit per m) or fruit weight (kg) between irrigation treatments, although higher yields were obtained in the second year due to seasonal changes. The crop water status indicators evaluated (stem water potential, net photosynthesis, and stomatal conductance) were not affected by the irrigation treatments. Water and nitrogen productivity, on average, increased by 45.5 and 54.4% during the experimental period, respectively; the average PI ascorbic acid content increased by 33.4%.

Sustainable management of water, nitrogen and biochar resources for soybean growth considering economic, environmental and resource use efficiency aspects: An integrated modeling approach

Intensive soybean production requires that water and fertilizer are collaboratively managed in an accurate and efficient manner, while biochar application offers a sustainable approach for protecting land, alleviating water scarcity, and increasing crop yield. The purpose of this study was to carry out a multifactor coupling orthogonal experiment of irrigation, nitrogen and biochar in the soybean growing season in 2021 and 2022 via plot treatment, linking the effect of irrigation and nitrogen on soybean yield with the carbon sequestration and emission reduction properties of biochar. A dynamic regulation model with multi-dimensional objective synergy for soybean yield, water footprint (WF), carbon footprint (CFP), water use efficiency (WUE) and partial productivity of nitrogen fertilizer (PFPN) based on the comprehensive regulation framework of experimental-simulation-optimization was constructed. This model was used to explore the optimal irrigation, nitrogen and biochar application patterns and their synergistic effects on yield and environmental benefits. The results showed that soybean yield and PFPN were affected by irrigation, nitrogen application affected WF and WUE, and biochar application affected CFP. Irrigation significantly affected the soil water content and consequently the WF while enhancing the crop yield and PFPN. Compared to the I1 treatment, the I0 treatment reduced water consumption, and the addition of nitrogen (N0 and N1) contributed to higher crop yields and WUE. The addition of biochar significantly increased crop yield, WUE and PFPN while mitigating the impact of nitrogen fertilizer application on greenhouse gas emissions. Based on the three-factor interaction, the yield, WF, CFP, WUE, and PFPN in 2022 increased by 3.03%, 3.51%, 2.17%, 1.59%, and 7.61%, respectively, compared to those in 2021. In addition, combined with water and nitrogen application, biochar application reduced CFP while increasing soybean yield, WUE and PFPN. A multiobjective optimization model demonstrated that when the amounts of irrigation, nitrogen, and biochar in 2021 and 2022 were 178.4 mm, 104.6 kg/hm2, and 8650.8 kg/hm2 and 153.7 mm, 93.7 kg/hm2, and 8063.4 kg/hm2, respectively, the synthetic degrees of yield, WF, CFP, WUE, and PFPN reached 0.866 and 0.872, respectively. The coordinated regulation of irrigation, nitrogen, and biochar reached a high-quality coordinated level that was 14.39% and 7.13% higher in 2021 and 2022 than the best I0N0B1 treatment, respectively. In this study, a combination of experiment-simulation-optimization is used to propose optimal irrigation, nitrogen and biochar regulation methods that synergize soybean yield, resource use efficiency and environmental benefits, which are of theoretical value for promoting green and efficient soybean production in black soil areas.

Using a crop water stress index to determine water use efficiency in a raspberry crop in the Mediterranean Central Chile

AbstractWater availability is projected to decrease in Mediterranean Central Chile, necessitating sustainable production strategies based on improved irrigation management. This study focuses on estimating water use efficiency (WUE) in raspberry crops at two validation sites using remote sensing and soil irrigation data. By employing the crop water stress index (CWSI), we demonstrate the potential of this tool in enhancing irrigation management and establishing sustainable production practices. The results demonstrate the successful estimation of actual evapotranspiration (ETa) using the Operational Simplified Surface Energy Balance (SSEBop) model (coefficient of determination [R2] = 0.92; root mean square error [RMSE] = 0.97 mm day−1), while the CWSI indicated high stress levels after 5 days of irrigation. Moreover, validation at two sites reveals significant differences in applied irrigation, with sites A and B receiving 17,097 and 3760 m3 ha−1, respectively, while the average water demand is close to 5300 m3 ha−1. These variations result in discrepancies in WUE, with values of 0.79 and 3.64 kg m−3. By integrating remote sensing indices and soil data, this study proposes that maintaining an 85% ETa rate during noncritical periods can enhance WUE. This work demonstrates the potential use of a water stress index to monitor crops in the Chilean central zone for efficient water resource use under future scarcity scenarios.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

Biostimulant Application Alleviates the Negative Effects of Deficit Irrigation and Improves Growth Performance, Essential Oil Yield and Water-Use Efficiency of Mint Crop

The scarcity of water is limiting crop production and is one of the most important stressors that severely affects crop yield, and it may also decrease the quality of the final products. Most of the medicinal and aromatic plants are considered resilient to water stress and constitute a sustainable choice for crop production in arid and semiarid conditions. In the present study, we examined the effect of scheduled deficit irrigation (e.g., I1: 40% of field capacity); I2: 70% of field capacity; and I3: 100% of field capacity) combined with biostimulant application (four different products that consisted of nitrogenous compounds and carboxylic acids (M1); nitrogenous compounds and seaweed extracts (M2); humic and fulvic acids and seaweed extracts (M3); and CaO, SiO2, calcium mobilization and translocation factor and microminerals (M4)) on crop performance and essential oil production of mint plants (Mentha arvensis L.). Our aim was to define an irrigation regime that increases water-use efficiency and the biostimulant products that alleviate water stress effects. Our results indicate that moderate deficit irrigation (I2 treatment) and biostimulants that contained seaweed extracts and nitrogenous compounds and humic and fulvic acids (M2 and M3 treatments, respectively) significantly improved yield parameters in terms of fresh and dry herb yield and essential oil production. Moreover, the same biostimulant treatments significantly increased water-use efficiency of mint crops based on the various yield parameters tested in this study. In conclusion, our results indicate that selection of proper biostimulatory products may allow to apply deficit irrigation regimes in mint cultivation without compromising the crop performance in terms of both biomass production and essential oil yield. Therefore, the combination of these agronomic tools could facilitate water saving strategies in arid and semiarid regions and contribute to the sustainable management of water resources.

Role of Bacterial Inoculant and Organic Matter in Improving some Soil Physical Properties and Water use Efficiency of Maize under Drought Conditions in Iraq

Field experiment was carried out at the Agricultural Research Directorate Research Station, Ministry of Science and Technology in Autumn 2018 to study the role of liquid bacterial inoculant and addition of organic matter in improving physical properties, water consumption and water use efficiency of the maize crop (Zea mays L.) under drought conditions prevailing in Iraq. Bacterial inoculated was added with two levels with, without adding, adding organic fertilizer at three levels (0, 1.5 and 3%) of the soil weight. Irrigation was scheduled when depleting (50, 60 and 70%) of the available water. Water consumption were 584, 437 and 317 mm under (50, 60 and 70%) of available water depletion respectively. The addition of bacterial inoculant and 3% organic matter was significantly superior to treatments at 50 and 60% of available water depletion. Saturated hydraulic conductivity and soil aggregate stability under these two treatments were 1.81 and 1.75 cm h−1 and 0.530 and 0.524% respectively. The grain yield was 12.321 and 12.162 t ha−1 under the above-mentioned treatments respectively. The highest rate of water use efficiency was 2.98 kg m−3 under 60 % moisture depletion, with bacterial inoculant and under addition of organic matter at the level of 3%.

Agricultural Cultivation Structure in Arid Areas Based on Water–Carbon Nexus—Taking the Middle Reaches of the Heihe River as an Example

China faces challenges of food security and sustainable agricultural production. However, current studies rarely address the spatial distribution patterns of water consumption and carbon emissions. We studied the irrigation water use efficiency and carbon emission differences of crops in arid areas and their spatial distribution using wheat and maize, two major food crops in the middle reaches of the Heihe River, as examples. Furthermore, we have optimized low-carbon cropping of crops under the multiple objectives of water conservation and economic development. The results show that: (1) The carbon emissions per unit of water consumption for maize are 0.03 × 10−6 t mm−1 and 0.49 × 10−6 t mm−1 for wheat. Irrigation water consumption per unit yield is 515.6 mm t−1 for maize and 426.7 mm t−1 for wheat. (2) The spatial distribution patterns of irrigation water consumption were opposites for maize and wheat. The former has lower irrigation water consumption in the planting area upstream of the Heihe River and higher in the lower reaches. In contrast, the pattern of wheat irrigation is the opposite. (3) After optimizing the cropping mix for both crops, the area planted with wheat should be reduced to 59% of the current size, while maize should be expanded to 104%. The results of the research hold immense importance in guiding the future grain crop planting patterns for water-saving agriculture and low-carbon agriculture development in arid zones worldwide, aligning with the United Nations’ Sustainable Development Goals.

Modelling Crop Evapotranspiration and Water Use Efficiency of Maize Using Artificial Neural Network and Linear Regression Models in Biochar and Inorganic Fertilizer-Amended Soil under Varying Water Applications

The deficit irrigation strategy is a well-known approach to optimize crop water use through the estimation of crop water use efficiency (CWUE). However, studies that comprehensively reported the prediction of crop evapotranspiration (ETc) and CWUE under deficit irrigation for improved water resources planning are scarce. The objective of the study is to predict seasonal ETc and CWUE of maize using multiple linear regression (MLR) and artificial neural network (ANN) models under two scenarios, i.e., (1) when only climatic parameters are considered and (2) when combining crop parameter(s) with climatic data in amended soil. Three consecutive field experimentations were carried out with biochar applied at rates of 0, 3, 6, 10 and 20 t/ha, while inorganic fertilizer was applied at rates of 0 and 300 Kg/ha, under three water regimes: 100% Full Irrigation Treatment (FIT), 80% and 60% FIT. Seasonal ETc was determined using the soil water balance method, while growth data were monitored weekly. The CWUE under each treatment was also estimated and modelled. The MLR and ANN models were developed, and their evaluations showed that the ANN model was satisfactory for the predictions of both ETc and CWUE under all soil water conditions and scenarios. However, the MLR model without crop data was poor in predicting CWUE under extreme soil water conditions (60% FIT). The coefficient of determination (R2) increased from 0.03 to 0.67, while root mean-square error (RMSE) decreased from 4.07 to 1.98 mm after the inclusion of crop data. The model evaluation suggests that using a simple model such as MLR, crop water productivity could be accurately predicted under different soil and water management conditions.

Multiobjective optimization of regional irrigation and nitrogen schedules by using the CERES-Maize model with crop parameters determined from the remotely sensed leaf area index

Using crop models to develop reasonable irrigation and nitrogen schedules (INSs) is critical for achieving high yields and maximizing water use efficiency (WUE) and nitrogen use efficiency. However, the INSs developed based on crop parameters determined through field experiments have low robustness at the regional scale. Remote sensing data indicate the growth conditions of regional crops, and representative regional crop parameters can be determined using remote sensing data. The objective of the present study was to develop a regional INS by adopting a crop model with crop parameters calibrated using the remotely sensed leaf area index (LAI). First, the crop parameters of a field-scale crop model were calibrated on the basis of field-scale trial data for four summer maize growing seasons. Sensitive crop parameters at the regional scale were then identified using an assimilation algorithm based on the remotely sensed LAI. The rationality of using the remotely sensed LAI for determining regional crop parameters was demonstrated by simulating regional maize growth. Finally, a regional-scale crop model was developed and coupled with a multiobjective genetic algorithm to optimize the regional INS for different typical-rainfall years. The results indicated that the regional-scale crop model was more accurate than was the field-scale crop model in simulating the regional LAI, plant height, soil water content, and yield and the corresponding RMSE decreased by 0.50 m2/m2, 0.15 m, 0.02 cm3/cm3, 344.11 kg/ha. Compared with the INSs currently used by farmers, the optimized INS was associated with a marginally higher irrigation quantity (average increase of 2.66%) but a significantly lower nitrogen application rate (average decrease of 31.6%). The crop yield, WUE, and partial factor productivity for nitrogen were 6.35–12.51%, 2.64–10.41%, and 61.8–66.2% higher, respectively, in different typical-rainfall years when using the optimized INS than when using an unoptimized INS. The results of this study indicate that a regional INS established on the basis of regional crop model parameters estimated using remote sensing data can aid irrigation and nitrogen application scheduling.

Energy Balance Assessment in Agricultural Systems; An Approach to Diversification

The energy in agricultural systems is two-fold: transformation and utilization. The assessment and proper use of energy in agricultural systems is important to achieve economic benefits and overall sustainability. Therefore, this study was conducted to evaluate the energy balance of crop and livestock production, net energy ratio (NER), and water use efficiency (WUE) of crops of a selected farm in Sri Lanka using the life cycle assessment (LCA) approach. In order to assess the diversification, 18 crops and 5 livestock types were used. The data were obtained from farm records, personal contacts, and previously published literature. Accordingly, the energy balance in crop production and livestock production was −316.87 GJ ha−1 Year−1 and 758.73 GJ Year−1, respectively. The energy related WUE of crop production was 31.35 MJ m−3. The total energy balance of the farm was 736.2 GJ Year−1. The results show a negative energy balance in crop production indicating an efficient production system, while a comparatively higher energy loss was shown from the livestock sector. The procedure followed in this study can be used to assess the energy balance of diversified agricultural systems, which is important for agricultural sustainability. This can be further developed to assess the carbon footprint in agricultural systems.

Enhancement growth, water use efficiency and economic benefit for maize by drip irrigation in Northwest China

The application of drip irrigation has been paid more and more attention, but there was lack of systematic comparative analysis between drip irrigation and conventional border irrigation method for maize, currently. A 7-year field study from 2015 to 2021 evaluated the effects of drip irrigation (DI, 540 mm) or conventional border irrigation method (BI, 720 mm) on maize growth, water use efficiency (WUE) as well as profitability. The results showed the plant height, leaf area index, yield, WUE and economic benefit of maize with DI had significantly higher than BI. The dry matter translocation, the dry matter transfer efficiency and contribution of dry matter translocation to grain with DI showed significant increase of 27.44%, 13.97% and 7.85% compared to BI, respectively. In comparison to conventional border irrigation, the yield of drip irrigation increased by 14.39%, as well as WUE and irrigation water use efficiency (IWUE) increased by 53.77% and 57.89%. The net return and economic benefit of drip irrigation was 1998.87 and 756.58 USD$ hm−1 higher than that of BI. Drip irrigation increased net return and benefit/cost ratio by 60.90% and 22.88% compared with BI. These results demonstrate that the drip irrigation can effectively improve the growth, yield, WUE and economic benefit of maize in northwest China. Therefore, drip irrigation can be used for maize cultivation to increase crop yield and WUE in northwest China, which has cut down on irrigation water about 180 mm.

Field, plant, to leaf: A meta-analysis on crop water use efficiency response to potassium fertilization

Applying potassium (K) fertilizer to fields is considered to be an important agricultural production practice to improve crop water use efficiency (WUE). However, the magnitude of crop WUE response to K fertilization has only been reported for individual regions, crops and scales due to lack of extensive and complete global datasets. Here we quantified the responses of crop WUE to K fertilization at the three scales of field-population (WUEfield), whole-plant (WUEplant) and single-leaf (WUEleaf) through synthesizing 797 paired observations from 81 field-based studies worldwide. Meta-analysis results showed that K fertilization increased WUEfield, WUEplant and WUEleaf of crops by 19.0%, 12.0% and 29.9%, respectively, with the key factors influencing this being crop type, mean annual precipitation and soil pH, respectively. It should be noted that the magnitude of WUEfield, WUEplant and WUEleaf response to K fertilization was significantly positively correlated with mean annual precipitation, while significantly negatively correlated with soil pH, which implying that K fertilization is an effective way to improve crop WUE in the region with humid climate or acidic soil. Furthermore, the conclusive findings of this meta-analysis showed that the relative importance of environmental factors in the magnitude of the WUEfield, WUEplant and WUEleaf response to K fertilization was 49.8%, 68.8% and 82.0%, respectively, which indicated that climatic characteristics and soil properties were drivers of crop WUE response to K fertilization rather than management practices. Overall, our meta-analysis provides new insight into the crop WUE response to K fertilization from field, plant, to leaf was driven by environmental factors and highlights the great potential of improved field K fertilization strategies in developing sustainable agriculture under the condition of climate change.