Improve Crop Water Use Research Articles

Prediction of reference crop evapotranspiration based on improved convolutional neural network (CNN) and long short-term memory network (LSTM) models in Northeast China

The accurate prediction of reference crop evapotranspiration (ET0) is essential to better manage crop irrigation water consumption and improve crop water use efficiency. To effectively improve the accuracy of ET0 simulated by machine learning models, five meteorological stations in Hailaer, Harbin, Hohhot, Changchun, and Dalian were taken as representative stations, daily and monthly ET0 data from 1952 to 2020 were used, and empirical mode decomposition (EMD) and wavelet threshold denoising (WD) were considered. The convolutional neural network (CNN) and long short-term memory network (LSTM) models were improved, and two new hybrid neural network models (EMD–WD–CNN and EMD–WD–LSTM) were constructed. Using the ET0 calculated using the FAO-56 Penman–Monteith (P–M) formula as the standard value, the applicability of the improved machine learning model was evaluated. Results showed the following: i) the daily ET0-PM minimum values of five stations were close to 0, the average values were not significantly increased, and the maximum values significantly fluctuated (the fluctuations in Hailaer and Hohhot showed an upward trend, and the fluctuations in Harbin, Changchun, and Dalian showed a downward trend). The annual average monthly ET0-PM varied seasonally, with the peak in June in the Hailaer station and May in all other stations (the peak in Hohhot was the largest, and the peak in Dalian was the smallest). ii) The daily and monthly ET0 values predicted by the proposed EMD–WD–CNN and EMD–WD–LSTM models were highly consistent with the calculated results of the P–M model, showing high accuracy on the daily and monthly ET0 of the simulated five stations (daily: mean absolute error (MAE), 0.30–0.41 mm/day; root mean square error (RMSE), 0.46–0.60 mm/day; R2, 0.86–0.95; monthly: MAE, 5.66–13.71 mm/month; RMSE, 8.97–18.04 mm/month; R2, 0.91–0.95). iii) The EMD–WD–CNN model was suitable for daily scale ET0 simulation and prediction in Northeast China and monthly scale in Harbin, Changchun, and Hohhot. The EMD–WD–LSTM model was suitable for monthly ET0 simulation and prediction in Hailaer and Dalian in Northeast China. The mixed models of EMD–WD–CNN and EMD–WD–CNN can effectively improve the prediction accuracy of ET0 and can provide a new method for agricultural development and irrigation regulation in Northeast China.

SLPA-Net: A Real-Time Recognition Network for Intelligent Stomata Localization and Phenotypic Analysis.

Plant stomatal phenotype traits play an important role in improving crop water use efficiency, stress resistance and yield. However, at present, the acquisition of phenotype traits mainly relies on manual measurement, which is time-consuming and laborious. In order to obtain high-throughput stomatal phenotype traits, we proposed a real-time recognition network SLPA-Net for stomata localization and phenotypic analysis. After locating and identifying stomatal density data, ellipse fitting is used to automatically obtain phenotype data such as apertures. Aiming at the problems of small stomata and high similarity to background, we introduced ECANet to improve the accuracy of stoma and aperture location. In order to effectively alleviate the unbalance problem in bounding box regression, we replaced the Loss function with a more effective Focal EIoU Loss. The experimental results show that SLPA-Net has excellent performance in the migration generalization and robustness of stomata and apertures detection and identification, as well as the correlation between stomata phenotype data obtained and artificial data.

Improving vineyard irrigation efficiency with soil water sensors

Improving vineyard irrigation efficiency with soil water sensors Using soil water sensors to automatically schedule irrigation in winegrape vineyards offers the potential for growers to enhance water use productivity under warmer climate conditions. The use of electrical soil water sensors for improving crop water use efficiency is an emerging trend in agricultural regions of the world where irrigation is vital for sustainable food production. This advancement uses solar powered electronic capacitance probes to activate irrigation in real time for maintaining a desired level of soil water content needed by a particular crop.

Improving field-scale crop actual evapotranspiration monitoring with Sentinel-3, Sentinel-2, and Landsat data fusion

One of the primary applications of satellite Land Surface Temperature (LST) observations lies in their utilization for modeling of actual evapotranspiration (ET) in agricultural crops, with the primary goals of monitoring and enhancing irrigation practices and improving crop water use productivity, as stipulated by Sustainable Development Goal (SDG) indicator 6.4.1. Evapotranspiration is a complex and dynamic process, both temporally and spatially, necessitating LST observations with high spatio-temporal resolution. Presently, none of the existing spaceborne thermal sensors can provide quasi-daily field-scale LST observations, prompting the development of methods for data fusion (thermal sharpening) of observations from various shortwave and thermal sensors to meet this spatio-temporal requirement. Previous research has demonstrated the effectiveness of combining shortwave-multispectral Sentinel-2 observations with thermal-infrared Sentinel-3 observations to derive daily, field-scale LST and ET estimates. However, these studies also highlighted limitations in capturing the distinct thermal contrast between cooler LST in irrigated agricultural areas and the hotter, adjacent dry regions. In this study, we aim to address this limitation by incorporating information on thermal spatial variability observed by Landsat satellites into the data fusion process, without being constrained by infrequent or cloudy Landsat thermal observations and while retaining the longwave radiance emission captured by the Sentinel-3 thermal sensor at its native resolution. Two approaches are evaluated, both individually and as a complementary combination, and validated against in situ LST measurements. The best performing approach, which leads to reduction in root mean square error of up to 1.5 K when compared to previous research, is subsequently used to estimate parcel-level actual evapotranspiration. The ET modeling process has also undergone various improvements regarding the gap-filling of input and output data, input datasets and code implementation. The resulting ET is validated using lysimeters and eddy covariance towers in Spain, Lebanon, Tunisia, and Senegal resulting in minimal overall bias (systematic underestimation of less than 0.07 mm/day) and a low root mean square error (down to 0.84 mm/day) when using fully global input datasets. The enhanced LST sharpening methodology is sensor agnostic and should remain relevant for the upcoming thermal missions while the accuracy of the modeled ET fluxes is encouraging for further utilization of observations from Sentinel satellites, and other Copernicus data, for monitoring SDG indicator 6.4.1.

Deficit irrigation combined with nitrogen application in the early growth stage of sugar beet increases the production capacity of canopy and avoids yield loss.

Properly reduced irrigation combined with nitrogen (N) application can be used to improve crop water use efficiency (WUE) in arid regions, but its effect on sugar beet is unknown at present. A two-year field experiment was conducted to evaluate the effects of N application (N0, 0; N1, 150; N2, 225 kg N ha-1 ) on the canopy production capacity (CPC), yield and WUE of sugar beet under normal irrigation (W1, 70% of field capacity (FC)) and deficit irrigation (DI) (W2, 50% FC) in the early growth stage (EGS). The results showed that the W2 treatment reduced the CPC by reducing gas exchange, leaf area index (LAI) and chlorophyll content (SPAD value) of sugar beet leaves compared to the W1 treatment. However, DI combined with N application increased these parameters. Specifically, N application increased the net photosynthetic rate by 40.7% by increased gas exchange, SPAD and LAI compared to the N0 treatment. In addition, N application increased WUE by 12.5% by increasing thickness of upper surface, stomatal aperture and cross-sectional area of petiole. This ultimately led to a significant increase in taproot yield (TY; 19.7%) and sugar yield (SY; 57.6%). Although the TY of the N2 treatment was higher than that of the N1 treatment, the SY and WUE did not increase significantly and the harvest index decreased significantly by 9.3%. DI combined with 150 kg N ha-1 in the EGS of sugar beet increases the WUE in arid areas while avoiding yield loss by improving the CPC. © 2023 Society of Chemical Industry.

Data-Driven Modelling of Soil Moisture Dynamics for Smart Irrigation Scheduling

In the face of increasing water scarcity and uncertainties of climate change, improving crop water use efficiency and productivity, while minimizing negative environmental impacts, is becoming crucial to meet the surging global food demand. Smart irrigation has a potential of improving water use efficiency in precision agriculture especially when efficient irrigation control strategies are adopted. Conventionally, irrigation systems rely on heuristic methods to schedule irrigation which either leads to over-irrigation or under-irrigation. This influences the crop physiological characteristics as well as the water use efficiency. To tackle this menace, model-based irrigation management has been overemphasized. A closed-loop irrigation control strategy relies on a mathematical model of the system for irrigation scheduling decisions. In this study, a data-driven approach was used to learn soil moisture dynamics from a drip irrigated tomato in an open field agricultural system. A total number of 9674 data samples were collected using an ATMOS41 weather station, TERROS 12 soil moisture sensor and a YFS-201 flow sensor for crop evapotranspiration and precipitation, soil moisture and irrigation volumes respectively. Data driven modelling was then performed using the system identification toolbox in a MATLAB environment. The model formulation was a multi-input single-output (MISO) system with reference evapotranspiration, irrigation and rainfall as inputs and soil moisture as the output. Different model structures including transfer functions, state space models, polynomial models and ARX models were evaluated. Model performance was evaluated using the mean square error (MSE), final prediction error (FPE) and estimated fit of the model approaches. Simulation results indicate that the soil moisture dynamics model provides a satisfactory approximation of the process dynamics with a state space model giving an estimated fit of 97.04 %, MSE and FPE of 1.74×10−7 and 1.75×10−7 respectively. This model will be used to design a model predictive controller for smart irrigation scheduling in open field environmental conditions.

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.

Effect of biochar addition and reduced irrigation regimes on growth, physiology and water use efficiency of cotton plants under salt stress

To alleviate the salinity and drought stresses faced in agricultural production, and to improve crop water use efficiency (WUE) in drought-prone regions, novel management strategies are needed. The combination of biochar amendment and reduced irrigation regimes could mitigate the negative effects of salinity and drought stresses and improve WUE of cotton plants. A split-root pot trial was performed in order to investigate the effects of two biochar amendments [wheat straw pellets biochar (WSP) and soft wood pellets biochar (SWP)] combined with three irrigation schemes [full irrigation (FI), deficit irrigation (DI), and partial root-zone drying irrigation (PRD)] on the growth, physiology and WUE of cotton plants under two salinity levels [0 mM NaCl (S0) and 200 mM NaCl (S1)]. The results showed that salt stress depressed plant growth and physiology, and reduced seed cotton yield and lint yield by 19.33–47.22% and 40.43–58.81%, respectively. However, the biochar amendment alleviated salt stress and increased plant dry biomass allocation ratio by 3.85%–12.54%, 5.07%–14.39% and 9.78%–46.62% in boll, seed cotton and lint cotton under S1, respectively, and also increased lint ginning out turn (GOT), harvest index (HI), WUE at plant and yield level (WUEp and WUEy) by 0.21%–28.69%, 5.07%–14.39%, −0.30%–15.71% and 5.83%–32.44%, respectively. Moreover, WSP was superior to SWP in terms of improving plant growth and yield. PRD showed better growth and physiological effects than DI, especially WUEp and WUEy were 6.88%–13.73% and 9.16%–22.78% greater under PRD than under DI. The combined application of biochar and PRD counteracted the decrease in WUE caused by biochar application alone under S0. Collectively, WSP combined with PRD could be a promising strategy in sustainable cotton production under drought and salinity stress.

Determination of energy partition of a cucumber grown Venlo-type greenhouse in southeast China

Accurate determination of energy partition inside greenhouses is a key procedure in optimizing efficient water management. In this study, micro-meteorological data and energy fluxes of cucumber were measured during four planting seasons (2018–2021) in a Venlo-type greenhouse to analyze the energy manifestation in different growing stages. The results showed that the latent heat flux (λET) was the primary component of net radiation (Rn), accounting for 61.2–72.6 % of Rn during the whole growing seasons, followed by sensible heat flux (H, 19.8–24.3 % of Rn) and soil heat flux (G, 7.6–14.8 % of Rn). The λET increased while both H and G decreased as the crop grew. Especially, H was larger than λET at midday in the initial growing stage. Energy partition was intensely affected by the leaf area index (LAI). The λET/Rn increased linearly with the increase in LAI, while the H/Rn decreased linearly and G/Rn decreased exponentially until LAI reached 4 m2 m−2. Canopy conductance (Gc), Priestley-Taylor coefficient (α), and the decoupling coefficient (Ω) were calculated to evaluate the controlling factors over cucumber λET. The high values of the α (= 1.15 ± 0.05) and the Ω (= 0.65 ± 0.05) indicated that the cucumber λET was principally constrained by Rn. The Gc was calculated by inverting Penman-Monteith (PM) equation using aerodynamic conductance (Ga) values obtained by the heat transfer coefficient (hs) method based on accurate convection regimes. The Gc varied from 1.42 to 17.98 mm s−1 and high Gc values corresponded to high λET. The λET was estimated by the Ω model with the mean root mean square error (RMSE) and mean absolute error (MAE) equaled 32.65 and 25.73 W m−2, while the determination coefficient (R2) was 0.94. The H was reproduced by the Bulk Transfer (BT) model to validate Ga with the RMSE and MAE equaled 32.57 and 24.95 W m−2, the R2 was 0.86. The results also indicated that the simplified energy balance (EB) method was an optional approach to analyzing energy partition in greenhouses. Consequently, more energy could be saved by avoiding the excessive application of water and thus improving crop water use efficiency in greenhouses.

How to put plant root uptake into a soil water flow model: A documentation with complete computer code.

The need for improved crop water use efficiency calls for flexible modelingplatforms to implement new ideas in plant root uptake and its regulation mechanisms. Thispaper documents the details of modifying a soil infiltration and redistribution model to include(a) dynamic root growth, (b) non-uniform root distribution and water uptake, (c) the effect ofwater stress on plant water uptake, and (d) soil evaporation. The paper also demonstratesstrategies of using the modified model to simulate soil water dynamics and plant transpirationconsidering different sensitivity of plants to soil dryness and different mechanisms of rootwater uptake. In particular, the flexibility of simulating various degrees of compensateduptake (whereby plants tend to maintain potential transpiration under mild water stress)is emphasized. The paper also describes how to estimate unknown root distributionand rooting depth parameters by the use of a simulation-based searching method. Thefull documentation of the computer code will allow further applications and new development.

Stable Soil Moisture Improves the Water Use Efficiency of Maize by Alleviating Short-Term Soil Water Stress.

Weaker temporal variation of soil moisture can improve crop water use efficiency (WUE), but its physiological mechanism was still unclear. To explore the mechanism, an organized experiment was conducted in Beijing from June to September. From the jointing stage to maturity stage of maize, stable soil moisture (SSM) and fluctuating soil moisture (FSM) were established with Pressure Potential Difference-Crop Initiate Drawing Water (PCI) and manual irrigation (MI), respectively, to explore the physiological mechanism of SSM to improve maize WUE. Among them, PCI treatments were set with 3 pressure differences of -5, -10, and -15 kPa, and MI treatment was watering every 3 days with the irrigation amount of 9.3 mm. The results showed that (1) after water treatment, the average soil water content of PCI-5 kPa, PCI-10 kPa, PCI-15 kPa, and MI treatments were 53% field capacity (FC), 47, 38, and 78% FC, respectively. It was SSM with weak temporal variation under PCI treatments, and FSM with medium temporal variation under MI treatment. (2) PCI treatments reduced the content of proline, malondialdehyde, and abscisic acid in each organ of maize. (3) Compared with FSM 78% FC, the maize root activity at the filling stage of 53% FC SSM and 47% FC SSM increased significantly by 57.1 and 28.6%, respectively, and the carbon isotope discrimination value (Δ13C) in bracts of the two treatments increased by 18.3 and 10.4%, respectively. (4) There was a very significant positive correlation between WUE based on biomass (WUEb) and Δ13C in bracts. In conclusion, a large temporal variation of soil moisture was an important factor that caused water stress in maize. Under SSM treatments, the accumulation of abscisic acid, proline, and malondialdehyde was synergistically reduced. SSM improved the WUE of maize by alleviating short-term soil water stress caused by the fluctuation of soil moisture.

Physiological and genetic control of transpiration efficiency in African rice, Oryza glaberrima Steud.

Improving crop water use efficiency, the amount of carbon assimilated as biomass per unit of water used by a plant, is of major importance as water for agriculture becomes scarcer. In rice, the genetic bases of transpiration efficiency, the derivation of water use efficiency at the whole-plant scale, and its putative component trait transpiration restriction under high evaporative demand remain unknown. These traits were measured in 2019 in a panel of 147 African rice (Oryza glaberrima) genotypes known to be potential sources of tolerance genes to biotic and abiotic stresses. Our results reveal that higher transpiration efficiency is associated with transpiration restriction in African rice. Detailed measurements in a subset of highly contrasted genotypes in terms of biomass accumulation and transpiration confirmed these associations and suggested that root to shoot ratio played an important role in transpiration restriction. Genome wide association studies identified marker-trait associations for transpiration response to evaporative demand, transpiration efficiency, and its residuals, with links to genes involved in water transport and cell wall patterning. Our data suggest that root-shoot partitioning is an important component of transpiration restriction that has a positive effect on transpiration efficiency in African rice. Both traits are heritable and define targets for breeding rice with improved water use strategies.

Benefits and Limitations to Plastic Mulching and Nitrogen Fertilization on Grain Yield and Sulfur Nutrition: Multi-Site Field Trials in the Semiarid Area of China.

Plastic mulching (PM) is widely used to improve crop water use efficiency and grain yield, but few studies have reported the effects of PM on cereal crop quality, especially sulfur (S) nutrition of wheat, which has significant effects on grain protein content, dough rheology, baking quality and human health. To fill this knowledge gap, we conducted a multi-site field experiment on the Loess Plateau from 2014 to 2016 to study the effects of PM combined with nitrogen (N) fertilizer on grain yield, shoot S accumulation, and grain S concentration of winter wheat in dryland. Compared with no mulching (NM), PM increased grain yield by 13.7% but decreased grain S concentration, S requirement for 1,000 kg–1 grain, soil available S concentration, and post-anthesis S uptake by 9.0, 9.7, 24.4, and 51.8%, respectively. Plastic mulching significantly increased shoot S accumulation at anthesis by 19.2%, but there was no significant difference at maturity. Additionally, grain S concentration and S requirement had a linear-plateau relationship with N fertilization amount, reaching maximum values at 110 and 127 kg N ha–1 under PM, 37.5 and 27.0% higher than those under NM. Furthermore, shoot S accumulation and N application rates well-fitted the linear-plateau model at anthesis and maturity. At maturity, straw, grain, and shoots accumulated the most S at threshold N rates of 120, 85 and 110 kg N ha–1, respectively. Crucially, stem + leaf S concentration at anthesis had a significant linear relationship with grain S concentration under PM; a 1 g kg–1 increase in stem leaf concentration corresponded with a 0.24 g kg–1 increase in grain S concentration. This study’s findings suggest that combining soil S supplementation with optimal N fertilizer under PM in northwest China and other regions with similar cropping systems increases grain S concentration and improves nutritional and processing qualities.

Estimating fractional vegetation cover of maize under water stress from UAV multispectral imagery using machine learning algorithms

Crop water stress is an inevitable and increasing challenge for agriculture. To improve crop water use efficiency, management of water stress and accurate estimation of crop traits were required. Among crop traits used to detect crop growth status and predict yield, fractional vegetation cover (FVC) is of great significance. We conducted studies in a maize field located in Inner Mongolia, China with different irrigation levels during 2018 and 2019 growing seasons. UAV RGB imagery was captured to investigate the effect of image sensors on thresholds obtained by the fixed-threshold method (proposed in our recent study), and to provide reference FVC (FVCUAV_R) for FVC models based on UAV multispectral imagery. Five vegetation indices (VIs), calculated from UAV multispectral imagery, and three regression algorithms (RF: random forest, ANN: artificial neural network, and MLR: multivariate linear regression) were used to build the FVC model suitable for different growing seasons, growth stages, and crop water stress. The results showed that there was a change in thresholds obtained using the fixed-threshold method based on different image sensors, but this change did not make a big difference on the accuracy of FVCUAV_R, with the R2 difference of 0.01 and the RMSE difference of 0.01. As for the three FVC regression models, RF model was the most suitable model when these models established in 2018 were used to estimate maize FVC in 2019 for different growth stages and water stress. The low estimation accuracy for high FVC levels was the reason why MLR model could not be used in the other maize growing season. This study provides a low cost and easy way to estimate maize FVC and its inter-field variability under various water status in different maize growing seasons or growth stages.

Partitioning evapotranspiration by measuring soil water evaporation with heat-pulse sensors and plant transpiration with sap flow gauges

Understanding the contributions of soil water evaporation (E) and crop transpiration (T) to evapotranspiration (ET) is essential for irrigation management and improving crop water use efficiency. Current methods for partitioning ET are subject to uncertainties, due in part to the scale differences in determining E, T, and ET. In this study, ET of a lysimeter planted with maize (Zea mays L.) was partitioned into E and T using sensors that had compatible measurement scales: E was measured with heat pulse sensors (following the sensible heat balance (SHB) and modified sensible heat balance (MSHB) approaches), and T was measured with sap flow gauges (following the heat-balance sap-flow (HBSF) method). The accuracy of the measurements was evaluated by comparing the sum of E and T values (E + T) to weighing lysimeter ET data. During the study period, E, T, and ET had average values of 0.9, 4.0, and 4.8 mm d−1, respectively, and the fractions of E and T were 19% and 81% of E + T, respectively. In general, the E + T values agreed well with the lysimeter ET data, but slight overestimations and underestimations were observed at relatively small and relatively large ET rates, respectively. By combining the SHB and MSHB approaches and the HBSF method, it is possible to partition ET into E and T with satisfactory accuracy.

Irrigation Management in Potato (Solanum tuberosum L.) Production: A Review

Limited water resources coupled with the increase of the human population calls for more efficient use of water in irrigated agriculture. Potato (Solanum tuberosum L.) is one of the most widely grown crops worldwide and is very sensitive to water stress due to its shallow rooting system. With the dilemma of potato sensitivity to drought and limited available water resources restricting crop production, researchers and crop growers have been investigating different approaches for optimizing potato yield and improving crop water use efficiency under different irrigation methods. While potato response to water is affected by other management practices such as fertilizer management, the present review is focused on the potato response to water under different environments and different irrigation methods and the impact on potato quality and potato diseases. Variable results obtained from research studies indicate the non-transferability of the results from one location to another as potato cultivars are not the same and potato breeders are still making effort to develop new high-yielding varieties to increase crop production and or develop new varieties for a specific trait to satisfy consumers exigence. This review is a valuable source of information for potato growers and scientists as it is not only focused on the impact of irrigation regimes on potato yield and water productivity as most reviews on water management, but it also presents the impact of irrigation regime on diseases in potatoes, tuber specific gravity, metabolite content of the tubers and the quality of the processed potato products.

Effect of natural factors and management practices on agricultural water use efficiency under drought: A meta-analysis of global drylands

Agriculture’s need to feed the growing population is challenged by the decline in available water resources especially in the context of global climate change. Improving crop water use efficiency (WUE) will help to safeguard the environmental sustainability of food production in dryland areas. However, the impact of drought on crop WUE varies—a comprehensive and quantitative understanding of relevant factors is needed to support evidence-based management decisions. Here, we used a meta-analysis of global drylands (81 studies with 836 paired observations) to evaluate the response of various crop WUEs to drought based on various natural and human induced factors. Our results showed that responses of crop types’ WUE varied under drought intensity, which probably a reference for crop selection in drylands. Cotton could be one of crop selection reference in hyper-arid or arid regions, and legume is not recommended for drylands without irrigation. Cereal crop are suitable for growing in semi-arid or dry sub-humid areas. Moreover, soil improvement and fertilizer management are the effective methods to alleviate drought stress, in addition to irrigation. Soil with medium-texture, 1.3–1.4 g cm−3 bulk density and 15–20 g kg−1 organic matter is beneficial for improving WUE under drought. Fertilizer should be carefully considered and not exceed 200 kg ha−1 for wheat in drylands. Water deficit can improve crop WUE, but should not exceed 40% of the full irrigation amount. Field management practices, such as mulching and weed control, can help alleviate drought by regulating WUE to some extent. This study evaluated the responses of various crop WUEs to drought and highlighted the factors contributing to and/or decreasing crop WUE from natural factor and management practices, which provides a basis for agricultural drought mitigation strategies under future climate change in dryland areas.

How Moderate Water Stress Can Affect Water Use Efficiency Indices in Potato

Since water is increasingly becoming an expensive and limited resource, it is necessary to improve crop water use efficiency (WUE) to save water while maintaining high yields. The objective of this research was to evaluate the effects of moderate water stress compared to well-watered conditions (supplying 50 or 100% of the maximum evapotranspiration (ETm)) on dry aboveground biomass yield (AB-Y), dry whole biomass yield (WB), tuber yield, irrigation WUE, and WUE at early harvest (E-TY, E-IWUE, E-YWUE), and at final harvest (F-TY, F-IWUE, F-YWUE), on WUE for dry aboveground biomass (AB-WUE) and for dry whole biomass (WB-WUE), on sink/source ratio and dry matter content of tubers in two potato cultivars—Sieglinde and Spunta, in two planting dates (early and late). Moderate water stress, compared to well-watered conditions, resulted in a small decrease in E-TY (−14%) and F-TY (−11%), but a high increase in E-IWUE (+69%) and F-IWUE (+78%), making savings in irrigation water of roughly 380 or 600 m3 per crop cycle in relation to early or final harvest. Moderate water stress improved in Sieglinde IWUE, YWUE, and WB-WUE at final harvest, whereas Spunta appeared more appropriate for early harvest. In the late planting date, the crop used water better compared to the early planting, resulting in a greater increase in IWUE (+77 vs. +66%) and an, albeit, slight increase in the WUE. It would, therefore, be convenient to apply the moderate water stress in the late planting, saving a further 100 m3 of irrigation water. The highest yield, IWUE, and YWUE were reached when moderate water stress was applied in both planting dates on cv. Spunta for early harvest and on cv. Sieglinde for final harvest. It was possible to increase WUE indices and save water, not only by water management, but also by choosing opportune planting dates and cultivars.

Effect of using pruning waste as an organic mulching on a drip-irrigated vineyard evapotranspiration under a semi-arid climate

ABSTRACT In a drip-irrigated vineyard soil evaporation (E) can reach up to 30-40% of the seasonal grapevine crop evapotranspiration (ETc). Vineyard soil management can be used as a technique to reduce soil E for improving crop water use efficiency. The aim of this experiment was to analyze the effect of using pruning waste as an organic mulching on vineyard ETc. During three experimental seasons, several cycles of grapevines water use determinations were conducted using a large weighing lysimeter located in Albacete (southeast Spain) under drip irrigation. Measurements were carried out under different soil management practices: i) keeping the bare soil within the lysimeter during the first 2-3 days (bare soil), ii) covering the lysimeter soil surface with pruning waste as an organic mulching (about 5 cm thick) for the next 2-3 days (organic mulch), and iii) covering the lysimeter with a waterproof canvas (plastic mulch), similar in colour to the soil, for the last 2-3 days of each measurement cycle. In 2017, the measurements period was initiated when midday stem water potential (Ψstem) values reached -1.3 MPa, in order to study the effect of the different soil management on grapevine ETc when vines in the lysimeter were suffering from severe water stress. During the 3-year study, plant determinations (i.e., canopy cover and the phenological stage) showed that vines were at the same stage of development during each period of measurements. Under equal evaporative demand and fractional canopy cover, results showed a reduction in the vineyard ETc between 16-18% with the organic mulching, and up to 24-30% with the plastic mulching. Even though plastic mulches significantly reduced water evaporation from soil surface, this reduction could have resulted in an increase in crop transpiration (T). However, results in this experiment show that both organic and inorganic mulching did not increase vine T compared to no mulching conditions, based on vine T values estimated during the three experimental periods of 2015. Therefore, using pruning waste as an organic mulch could be an environmental friendly alternative to reduce soil evaporation and increase crop water productivity in large areas where vineyards are drip-irrigated.

Drying times: plant traits to improve crop water use efficiency and yield.

Crop water use efficiency (WUE) has come into sharp focus as population growth and climate change place increasing strain on the water used in cropping. Rainfed crops are being challenged by an upward trend in evaporative demand as average temperatures rise and, in many regions, there is an increased irregularity and a downward trend in rainfall. In addition, irrigated cropping faces declining water availability and increased competition from other users. Crop WUE would be improved by, first, ensuring that as much water as possible is actually transpired by the crop rather than being wasted. Deeper roots and greater early crop vigour are two traits that should help achieve this. Crop WUE would also be improved by achieving greater biomass per unit water transpired. A host of traits has been proposed to address this outcome. Restricting crop transpiration through lower stomatal conductance is assessed as having limited utility compared with traits that improve carbon gain, such as enhancements to photosynthetic biochemistry and responsiveness, or greater mesophyll conductance. Ultimately, the most useful outcomes for improved crop WUE will probably be achieved by combining traits to achieve synergistic benefit. The potential utility of trait combinations is supported by the results of crop simulation modelling.